Genetic Variability and inheritance pattern of seed yield and...
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Genetic Variability and inheritance pattern of seed yield and oil quality contributing traits in Brassica campestris L. By Hafiz Basheer Ahmad 96-ag-1455 M.Sc. (Hons.) PBG A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY IN PLANT BREEDING & GENETICS Department of Plant Breeding and Genetics Faculty of Agriculture UNIVERSITY OF AGRICULTURE, FAISALABAD PAKISTAN 2017
Transcript of Genetic Variability and inheritance pattern of seed yield and...
Genetic Variability and inheritance pattern of seed yield and oil
quality contributing traits in Brassica campestris L.
By
Hafiz Basheer Ahmad
96-ag-1455
M.Sc. (Hons.) PBG
A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE
REQUIREMENTS FOR THE DEGREE OF
DOCTOR OF PHILOSOPHY
IN
PLANT BREEDING & GENETICS
Department of Plant Breeding and Genetics
Faculty of Agriculture
UNIVERSITY OF AGRICULTURE,
FAISALABAD
PAKISTAN
2017
To,
The Controller of Examinations,
University of Agriculture Faisalabad,
Pakistan.
We, the supervisory committee, certify that the contents and form of the thesis
submitted by Mr. Hafiz Basheer Ahmad, Regd. No. 96-ag-1455 have been found
satisfactory and recommend that it may be processed for evaluation by the External
Examiner for the award of the degree.
Supervisory Committee
1) Supervisor _____________________________________
(Prof. Dr. Hafeez Ahmad Sadaqat)
2) Member ______________________________________
(Dr. M. Hammad Nadeem Tahir)
3) Member ______________________________________
(Dr. Bushra Sadia)
DDEEDDIICCAATTEEDD
TO
MY LOVING PARENTS
DECLARATION
I, hereby, declare that contents of the thesis “Genetic Variability and inheritance pattern
of seed yield and oil quality contributing traits in Brassica campestris L.” are product of
my own research and no part has been copied from any published source (except the
references, some standards mathematical or genetic models/equation/protocols etc).
__________________________ Hafiz Basheer Ahmad
96-ag-1455
TABLE OF CONTENTS
Chapter Title Page
Title Page …………………………………………………………………. i
Supervisory Committee …………………………………………………... ii
Certificate ………………………………………………………………… iii
Table of Contents ………………………………………………………… iv
List of Figures ……………………………………………………………..
List of Tables ……………………………………………………………...
1. Introduction ……………………………………………………………………… 1
2. Review of Literature …………………………………………………………….. 7
2.1 Phylogenetic Relationships ……………………………………………….. 7
2.2 Center of Origin and Domestication ……………………………………… 9
2.3 Forms of Brassica campestris …………………………………………….. 11
2.4 Genetic Variability in Different Seed and Plant Traits …………………… 12
2.4.1 Morphological Traits …………………………………………. 12
2.4.2 Phenological Traits……………………………………………. 12
2.4.3 Seed Yield Components ……………………………………… 14
2.4.4 Quality Related Traits ………………………………………… 14
2.5 Creating Genetic Variability through Hybridization …………………….. 16
2.5.1 Intraspecific Hybridization …………………………………… 16
2.5.2 Interspecific Hybridization …………………………………… 17
2.5.3 Introgression ………………………………………………….. 19
2.6 Inheritance of Different Seed and Plant Traits …………………………… 21
2.6.1 Morphological Traits …………………………………………. 21
2.6.2 Phenological Traits …………………………………………… 22
2.6.3 Seed Yield Components ……………………………………… 22
2.6.4 Oil Quality Traits …………………………………………….. 23
2.7 Hybrid Development ……………………………………………………… 26
2.7.1 Manifestation of Heterosis and Inbreeding Depression ………. 26
2.7.2 Explanation of Heterosis ……………………………………… 29
2.7.2.1 Classical Basis ……………………………………. 29
2.7.2.2 Molecular Basis ………………………………….. 29
2.8 Direct Selection Indices …………………………………………………... 30
2.8.1 Type of Gene Action ………………………………………… 30
2.8.2 Degree of Dominance ………………………………………… 31
2.8.3 Heritability ……………………………………………………. 31
2.8.4 Genetic Advance ……………………………………………… 31
2.9 In-Direct Selection Indices ……………………………………………….. 34
2.9.1 Correlation Analysis…………………………………………... 34
2.9.2 Path Analysis …………………………………………………. 36
3. Materials and Methods ………………………………………………………….. 43
3.1 Year wise work plan ……………………………………………………… 43
3.2 Experimental Genetic Material …………………………………………… 43
3.3 Hybridization Plan ………………………………………........................... 45
3.3.1 Intraspecific Hybridization …………………………………… 45
3.3.2 Interspecific Hybridization …………………………………… 45
3.4 Measurement Methods ……………………………………………………. 45
3.4.1 Morphological Traits …………………………………………. 45
3.4.1.1 Plant Height (cm) …………………………………. 45
3.4.1.2 Number of Primary Branches per Plant …………... 46
3.4.1.3 Number of Secondary Branches per Plant ………... 46
3.4.1.4 Green Biomass per Plant (g) ……………………… 46
3.4.1.5 Harvest Index …………………………………….. 46
3.4.2 Phenological Traits …………………………………………… 46
3.4.2.1 Number of Days to Flower Initiation …………….. 46
3.4.2.2 Number of Days to 50% Flowering ………………. 46
3.4.2.3 Number of Days to 50% Siliqua Formation ……… 46
3.4.2.4 Number of Days to Maturity ……………………... 46
3.4.3 Seed Yield Components ……………………………………… 46
3.4.3.1 Number of Siliquae per Plant ……………………. 46
3.4.3.2 Number of Seeds per Siliqua ……………………... 47
3.4.3.3 100-Seed Weight (g) ……………………………… 47
3.4.3.4 Seed Yield per Plant (g) …………………………... 47
3.4.4 Quality Related Traits ………………………………………… 47
3.4.4.1 Seed Oil Contents (%) …………………………… 47
3.4.4.2 Seed Cake Protein Contents (%) …………………. 47
3.4.4.3 Seed Cake Glucosinolate Contents (%) …………... 47
3.4.4.4 Oleic Acid Contents (%) …………………………. 47
3.4.4.5 Erucic Acid Contents (%) ………………………… 47
3.5 Biometrical Approaches ………………………………………………….. 47
3.5.1 Analysis of Variance …………………………………………. 47
3.5.2 Mean Comparisons …………………………………………… 48
3.5.3 Line x Tester Analysis ………………………………………... 49
3.5.4 Combining Ability Analysis ………………………………….. 52
3.5.5 Estimation of Heterosis ……………………………………….. 52
3.5.6 Estimation of Inbreeding Depression ………………………… 53
3.5.7 Estimation of Heritability …………………………………….. 53
3.5.8 Estimation of Genetic Advance ………………………………. 54
3.5.9 Correlation Analysis …………...……………………………... 54
3.5.10 Path Analysis …………………………………………………. 55
4 Results and Discussion…………………………………………………………… 55
4.1 Intraspecific Genetic Variability ……………………………. 60
4.2 Mean Comparisons for Various Plant Traits of 21 Intraspecific
Crosses of B.campestris……………………………………….
60
4.2.1 Phenological Traits……………………………………………. 60
4.2.2 Morphological Traits…………………………………………. 60
4.2.3 Yield Related Traits…………………………………………… 61
4.2.4 Quality Related Traits…………………………………………. 61
4.3 Estimates of General Combining Ability of Various Traits in
B. campestris…………………………………………………....
65
4.4 Specific Combining Ability Estimates of Various Traits in
B.campestris……………………………………………………
67
4.5 Components of Genetic Variance and Degree of Dominance… 70
4.6 Contribution (%) of Genotypes and Their Interaction………… 72
4.7 Heterotic Estimation of Yield and Yield Related Traits of
B.campestris……………………………………………………
73
4.7.1 Seed Yield per Plant…………………………………………... 73
4.7.2 Days to Flowering Initiation………………………………….. 73
4.7.3 Days to 50% Flowering……………………………………….. 73
4.7.4 Days to 50% Siliquae Formation……………………………… 73
4.7.5 Days to Maturity……………………………………………… 73
4.7.6 Plant Height…………………………………………………… 74
4.7.7 Primary Branches……………………………………………… 74
4.7.8 Secondary Branches…………………………………………… 74
4.7.9 Green Biomass and Harvest Index……………………………. 75
4.7.10 Number of Siliquae per Plant and Number of Seed per Siliqua. 75
4.7.11 Total Seed Weight (100 Seed)………………………………… 75
4.8 Genetic Variability For Quality Parameters…………………... 79
4.9 General Combining Ability Estimates for Quality Traits of
Intraspecific Crosses...................................................................
80
4.10 Specific Combining Ability Estimates for Quality Traits…….. 81
4.11 Components of Genetic Variance……………………………... 84
4.12 Heterotic Manifestation for Quality Traits……………………. 84
4.12.1 Oil Content (%)………………………………………………... 84
4.12.2 Protein Content (%)…………………………………………… 85
4.12.3 Glucosinolate Content (%)…………………………………… 85
4.12.4 Oleic Acid (%)………………………………………………… 85
4.12.5 Erucic Acid (%)……………………………………………….. 86
4.13 Good Cross Combinations for Seed Yield and Quality
Parameters ………………………………………………….....
86
4.14 Heritability and Genetic advance for Intraspecific 89
Combinations………………………………………………......
4.15 Heritability and Genetic Advance for Quality Traits…………. 90
4.16 Genotypic and Phenotypic Correlation for Quantitative Traits
in Intraspecific Crosses………………………………………...
91
4.17 Path Analysis for Quantitative Traits of Intraspecific Crosses... 93
4.18 Correlation And Path Analysis For Quality Traits For Intra-
specific Crosses………………………………………………..
95
4.19 Interspecific Genetic Variability………………………………. 97
4.19.1 Mechanism of Variation………………………………………. 97
4.20 Mean Comparisons for Various Plant Traits of 12 Inter
Specific Crosses of B.campestris………………………………
101
4.20.1 Phenological Traits……………………………………………. 101
4.20.2 Morphological Traits………………………………………….. 101
4.20.3 Yield Related Traits………………………………………….. 102
4.20.4 Quality Related Traits………………………. 102
4.21 General Combining Ability Estimates of Interspecific Crosses
of B. campestris ……………………………………………….
104
4.22 Specific Combining Ability Estimates for Interspecific
Crosses…………………………………………………………
105
4.23 Components of Genetic Variance of Interspecific
Combinations…………………………………………………
109
4.24 Contribution (%) of Lines, Testers and Their Interaction for
Various Traits of Interspecific Combinations………………….
110
4.25 Heterotic Manifestation of Interspecific Crosses of B.
Campestris …………………………………………………….
110
4.25.1 Seed Yield Per Plant…………………………………………... 110
4.25.2 Days to Flowering Initiation………………………………….. 111
4.25.3 Days to 50% Flowering……………………………………….. 111
4.25.4 Days to 50% Siliquae Formation……………………………… 111
4.25.5 Days to Maturity…………………………………………… 111
4.25.6 Plant Height…………………………………………………… 112
4.25.7 Primary Branches……………………………………………… 112
4.25.8 Secondary Branches…………………………………………… 112
4.25.9 Green Biomass and Harvest Index……………………………. 113
4.25.10 Number of Siliqua and Seed per Siliqua………………………. 113
4.25.11 Total Seed Weight (1000 Seed)……………………………….. 113
4.26 Genetic Variability for Quality Traits…………………………. 117
4.27 General Combining Ability Estimates of Interspecific Crosses 118
4.28 Specific Combining Ability Estimates for Quality Attributes… 118
4.29 Components of Genetic Variances……………….…………… 119
4.30 Contribution of Lines, Testers and Their Interaction for
Quality Traits. ………………………………………………....
120
4.31 Heterotic Manifestation of Interspecific Crosses For Quality
Traits…………………………………………………………...
121
4.31.1 Oil Content (%)………………………………………………... 121
4.31.2 Protein Content (%)…………………………………………… 121
4.31.3 Glucosinolate Content (µmolg-1)……………………………... 121
4.31.4 Oleic Acid (%)………………………………………………… 121
4.31.5 Erucic Acid (%)………………………………………………. 121
4.32 Good Cross Combinations for Seed Yield (g) and Quality
Traits on The Basis of SCA Estimates, Heterosis and GCA
Estimates……………………………………………………….
122
4.33 Heritability and Genetic Advance…………………………….. 123
4.34 Heritability and Genetic Advance for Quality Traits…………. 125
4.35 Genotypic and Phenotypic Correlation for Quantitative Traits
In Interspecific Crosses………………………………………...
131
4.36 Path Analysis for Quantitative Traits…………………………. 128
4.37 Correlation and Path Analysis for Quality Traits……………... 129
4.38 Genetic Variability among Direct and Indirect Interspecific
Crosses…………………………………………………………
130
4.39 Mean Comparisons for Various Plant Traits of 12 Inter
specific Crosses of B.campestris…………………………………..
134
4.39.1 Phenological Traits……………………………………………. 134
4.39.2 Morphological Traits………………………………………….. 134
4.39.3 Yield Related Traits…………………………………………… 135
4.39.4 Quality Related Traits…………………………………………. 135
4.40 General Combining Ability Effects for Various Traits of Inter-
specific Hybrids……………………………………………….
138
4.41 Specific Combining Ability Estimates of Interspecific
Combinations..............................................................................
139
4.42 Components of Genetic Variance……………………………... 142
4.43 Contribution (%) of Lines, Testers and Their Interactions for
Various Traits of Interspecific Combinations………………….
144
4.44 Heterotic Manifestation Due to Interspecific Hybridization….. 145
4.44.1 Seed Yield per Plant…………………………………………... 145
4.44.2 Days to Flowering Initiation…………………………………... 145
4.44.3 Days to 50% Flowering……………………………………….. 145
4.44.4 Days to 50% Siliqua Formation………………………………. 145
4.44.5 Days to Maturity………………………………………………. 146
4.44.6 Plant Height…………………………………………………… 146
4.44.7 Primary Branches……………………………………………… 146
4.44.8 Secondary Branches…………………………………………… 147
4.44.9 Green Biomass and Harvest Index……………………………. 147
4.44.10 Number of Siliqua per Plant and Number of Seed per Siliqua... 147
4.44.11 Total Seed Weight (100 Seed)………………………… 147
4.45 Heterotic Manifestation of Interspecific Crosses for Quality
Traits…………………………………………………………...
150
4.45.1 Oil Contents (%)………………………………………………. 150
4.45.2 Protein Content (%)…………………………………………… 150
4.45.3 Glucosinolate Content (µmolg-1)……………………………... 150
4.45.4 Oleic Acid (%)………………………………………………… 150
4.45.5 Erucic Acid (%)……………………………………………….. 150
4.46 Good Cross Combinations on The Basis of SCA, GCA
Estimates and Heterosis for Yield And Qualitative Traits…….
151
4.47 Inbreeding Depression for Quantitative Traits………………... 154
4.48 Inbreeding Depression for Quality Traits……………………... 156
4.49 Gentic Variability of Direct and Some Indirect Interspecific
Crosses for Quality Parameters………………………………..
156
4.50 General Combining Ability Estimates for Quality Traits……... 159
4.51 Components of Genetic Variance……………………………... 150
4.52 Contribution (%) of Lines, Testers and Their Interaction for
Quality Traits…………………………………………………..
162
4.53 Heritability and Genetic advance for Quantitative Traits……... 163
4.54 Heritability and Genetic Advance for Quality Traits…………. 164
4.55 Phenotypic and Genotypic Correlation for Interspecific
Hybridization…………………………………………………..
164
4.56 Path Analysis for Interspecific Hybridization………………… 167
4.57 Correlation and Path Analysis for Quality Traits……………... 169
GENERAL DISCUSSION…………………………………………………….. 171
5 SUMMARY 178
REFERENCES .................................................................................................... 184
LIST TABLE OF FIGURES
Figure NO. Discription Page
1.1 Seed and Edible Oil Production ……………………………………… 3
1.2 Area and Production of Rapeseed Oilseed…………………………… 3
1.3 Rapeseed Oil Seed Production and Import…………………………… 4
1.4 Major Rapeseed Producing Countries ……………………………… 4
1.5 Yield of Rapeseed Oilseed per Unit Area In Pakistan………………… 5
2.1 Phylogenetic Relationship among Brassica Species ….……………… 7
2.2 Evolutionary History of B. campestris and Its Relatives .......……… 10
Tables No LIST OF TABLES Page
3.1 Intraspecific Hybridization of B. campestris .................................... 44
3.2 Inter-Specific Hybridization f B. campestris with Its Relatives …….. 44
3.3 Analysis of Variance Format Used for Line×Tester Analysis ………. 48
3.4 Analysis of Variance for Combining Ability ……………………… 49
4.1 Mean Square Values Associated with Different Plant Traits of B.
campestris …………………………………………………………………...
57
4.2 Mean Square Values from Analysis of Variance of Lines, Testers and
Their used in Crossing of Brassica campestris ………………………...
59
4.3 Mean Comparison of Different Associated Plant Traits of B.
campestris …………………………………………………………………..
62
4.4 Estimates of General Combining Ability for Various Traits in Brassica
campestris ..................................................................................................................................... 66
66
4.5 Specific Combining Ability Estimates of Various Traits in Brassica
campestris ..................................................................................................................................... 68
68
4.6 Components of Genetic Variance and Degree of Dominance ................................................... 71 71
4.7 Contribution (%) of Genotypes and Their Interactions .............................................................. 72 72
4.8a Heterotic Manifestation for Various Traits of Brassica campestris .......................................... 76 76
4.9 Mean Square Values for Quality Traits of Brassica campestris ................................................ 80 80
4.10 General Combining Ability Estimates for Quality Traits of
Intraspecific Crosses..................................................................................................................... 81
81
4.11 Specific Combining Ability for Quality Traits of Intraspecific Crosses
of Brassica campestris ................................................................................................................. 83
83
4.12 Components of Genetic Varianc .................................................................................................. 84 84
4.13 Heterotic Manifestation for Quality Traits of Brassica campestris
Combinations ................................................................................................................................ 87
87
4.14 Good Cross Combinations for Seed Yield and Quality
Parameters…………………………………………………………..
88
4.15 Heritability and Genetic advance for Quantitative TraitsError!
Bookmark not defined...................
90
4.16 Heritability and Genetic Advance for Quality Traits for Intraspecific
Crosses……………………………………………………………….
91
4.17 Genotypic and Phenotypic Correlation between Quantitative Traits for
Intraspecific Crosses……………………………………………..
92
4.18 Path Analysis For Quantitative Traits of Intraspecific
Crosses…..Error! Bookmark not defined....
94
4.19 Phenotypic And Genotypic Correlation Coefficients for Quality
Traits.Error! Bookmark not
defined...................................................................................................
95
4.20 Direct (Diagonal) And Indirect Effect Path Coefficients of Quality
TraitsError! Bookmark not
defined.....................................................................................................
96
4.21 Mean Square Values Associated with Different Plant Traits……… 99
4.22 Mean Square Values from Analysis of Variance for Various Traits of
Interspecific Crosses of Brassica campestris with Its Relative
BrassicasError! Bookmark not
defined..............................................................................................
100
4.23 Mean Comparison for Various Plant Traits of 21 Intraspecific Crosses
of B.campestris Obtained from 7 Lines and 3 Testers………
103
4.24 General Combining Ability Estimated Effects for Various Traits of
Interspecific Crosses of Brassica campestris with Its Relative
BrassicasError! Bookmark not
defined..............................................................................................
107
4.25 Specific Combining Ability Estimated Effects for Various Traits of
Interspecific Combinations of Brassica campestris with Its Relative
Brassicas……………………………………………………………..
108
4.26 Components of Genetic Variance of Interspecific Combinations… 114
4.27 Contribution (%) of Lines, Testers and Their Interactions for Various
Traits of Brassica campestris……………………………..………..
114
4.28a Heterotic Manifestation for Various Traits of Brassica campestris with
Its RelativesError! Bookmark not
defined..................................................................................
115
4.29 Mean Square Values for Quality Traits of Interspecific Hybrids…… 117
4.30 General Combining Ability Estimates for Quality Attributes of
Interspecific Combinations……………………………………….......
118
4.31 Specific Combining Ability Estimates for Quality Attributes of
Interspecific Combinations.Error! Bookmark not
defined..................................................................
119
4.32 Variance Due To GCA, SCA, Additive, Dominance and Degree of
Dominance………………………………………………………….
120
4.33 Contribution (%) of Lines, Testers And Interaction……………….. 120
4.34 Heterotic Manifestation for Quality Traits of Interspecific Hybrids. 122
4.35 Good Cross Combinations For Seed Yield (g) and Quality on The
Basis Of GCA Estimates, Heterosis and GCA Estimates...................
123
4.36 Heritability (%) and Genetic Advance Values (%) Mean…………… 124
4.37 Heritability (%) and Genetic Advance Values (%) Mean for
Qualitative Traits…………………………………………………….
125
4.36 Genotypic and Phenotypic Correlation for Quantitative Traits In
Interspecific CrossesError! Bookmark not
defined.............................................................................
127
4.37 Direct (Diagonal) and Indirect Effect Path Coefficients of Interspecific
Crosses…………………………………………………
129
4.38 Genotypic and Phenotypic Correlation for Interspecific
Combinations.………………………………………………………..
130
4.39 Direct (Diagonal) and Indirect Effects of Quality Traits of Interspecific
Crosses………………………………………………….
130
4.40 Mean Square Values Associated With Different Plant TraitsError!
Bookmark not defined..............
132
4.41 Mean Square Values of Direct And Some Indirect Interspecific
Crosses of B. campestrisError! Bookmark not
defined......................................................................
133
4.42 Mean Comparison for Various Plant Traits of 12 Interspecific Crosses
of B.campestris.......................................................................
136
4.43 General Combining Ability Estimated Effects for Various Traits of 140
Interspecific Combinations………………………………………….
4.44 Specific Combining Ability Estimated Effects of Interspecific
CombinationsError! Bookmark not
defined........................................................................................
141
4.45 Components of Genetic Variance of Interspecific CombinationsError!
Bookmark not defined........
143
4.46 Contribution (%) of Lines, Testers and Their Interactions for Various
Traits of Brassica campestrisError! Bookmark not
defined..............................................................
144
4.48a Heterotic Manifestation For Indicated Traits of Interspecific
CrossesError! Bookmark not
defined.................................................................................................
148
4.49 Heterotic Manifestation of Interspecific Crosses for Quality Traits… 152
4.50 Good Cross Combinations For Seed Yield And Quality Traits on Basis
of SCA, Heterosis and GCA Effects…………………………..
153
4.51 Inbreeding Depression for Quantitative Traits ……………………. 157
4.52 Inbreeding Depression for Quality Traits In Brassica Cross
CombinationsError! Bookmark not
defined.......................................................................................
158
4.53 Mean Square Values For Quality Parameters of Brassica campestris 159
4.54 General Combining Ability for Quality Traits of Interspecific
Crosses………………………………………………………………..
161
4.55 Estimates of Specific Combining Ability Effects for Quality Traits of
Intersspecific Error! Bookmark not
defined...................................................................................
161
4.56 Components of Genetic Variances………………………………….. 162
4.57 Contribution (%) of Lines, Testers And Their Interactions for Quality
Traits of Interspecific Combinations.Error! Bookmark not
defined......................................
162
4.58 Heritability and Genetic Advance for Quantitative Trait…………… 163
4.59 Heritability (%) and Genetic Advance Values (%) Mean for Quality 164
Traits of Interspecific CrossesError! Bookmark not
defined..............................................................
4.60 Phenotypic (Below) & Genotypic (Above) DiagonalError!
Bookmark not defined.........................
166
4.61 Direct (Diagonal) and Indirect Effects of various traits on yield of
Interspecific Crosses………………………………………………….
167
4.62 Phenotypic (Below) & Genotypic (Above) Diagonal……………….. 169
4.63 Direct (Diagonal) and Indirect Effect Path Coefficients of Interspecific
Crosses………………………………………………….
170
ABSTRACT
Present studies were conducted to assess and create the genetic variability in B. campestris at
inter and intra specific levels. Hybridization with relative species was to obtain introgression
which could help improve the breeding material. Experimental material consisted of 14 lines/
cultivars (8 local and 6 exotic). Ten cultivars were of B. campestris, two of B. napus and two of
B. juncea. The data were subjected to Line × Tester analysis. Significant differences were noted
among all cultivars and their generations. Line × Tester mating design revealed the best
performing parents, crosses, appropriate breeding procedure based on GCA and SCA and genetic
components of variance. Heterosis, direct and indirect selection parameters were estimated for
quantitative and qualitative traits. F2 generation of some selected crosses was grown for further
analysis. The intraspecific cross combinations viz. Span × Tobin, Toria × Candle, 1072 × Torch
and Quinyou15 × Torch were identified as good combinations based on specific combining
ability, heterosis, heterobeltosis and general combining for yield. Regarding the quality
parameters the combinations, Toria×Candle, UAF11×Torch and Span× Candle showed the
highest negative heterosis for erucic acid. For glucosinolate content the crosses, Span×Candle,
Quinyou15×Torch and UAF11×Torch showed the highest negative heterosis. Correlation studies
revealed that genotypic correlations were higher than phenotypic correlations. Days to 50%
flowering, days to 50% siliquae formation, secondary branches, plant height, green biomass,
harvest index and number of seeds per siliqua had positive significant association with seed yield
per plant. Oil content had significant positive association with protein. Protein and glucosinolates
had significant direct relationship with erucic acid. Protein content had also positive and
significant correlation with glucosinolate content. Oleic acid had negative correlation with
protein, glucosinolates and erucic acid. Path coefficient analysis showed that traits like flowering
initiation, 50% flowering, maturity days, secondary branches, number of siliquae, seeds/siliqua,
harvest index had direct positive effect on seed yield while protein content, glucosinolates, oleic
acid had direct positive effect on oil content while erucic acid had direct negative effect on oil
content. Present genetic material can be improved through direct selection of traits like days to
50% siliquae formation, days to maturity, number of siliquae/plant, number of seeds per siliqua
and plant height. Oil, protein and glucosinolates content had high heritability with moderate
genetic advance that showed additive effect of genes. Interspecific hybridization to obtain
possible introgression of B. campestris with B. napus and B. juncea was successful. Interspecific
combinations viz. Napus2 × Toria, Toria × Napus2, Napus2 × Juncea, Juncea × Napus2, Shora ×
1072, UAF11×Napus1, Napus1×Shora and Napus1×1072 showed variation and were selected
for both quantitative and qualitative traits. Correlation, path analysis, heritability and genetic
advance studies showed similar behavior as in intraspecific crosses. However, these
combinations showed luxuriance heterosis, took more days of maturity and some were poor in
seed yield as compared to intraspecific combinations. Some crosses showed self incompatibility
and male sterility. There was substantial amount of inbreeding depression in most cross
combinations for seed yield per plant. Oil, protein and oleic acid showed positive and negative
inbreeding depression for different cross combinations. All combinations showed positive
inbreeding depression except one for erucic acid. The material developed through intra and
interspecific hybridization is early maturing, high yielding with good quality contents and robust
to grow in local cropping pattern. By developing high yielding and good quality brassicas, Rs
6.67 billion can be saved which are being spent on import of edible oil.
1
CHAPTER 1 INTRODUCTION
Pakistan is essentially an agriculture based economy. Agriculture contributes 20.9% of total
Gross Domestic Product (GDP) (Govt. of Pakistan, 2014-2015). It is the major income
source (43.5%) of population of rural area. The performance of agriculture sector for the year
2014-15 (growth 2.9 %) was better compared to the year 2013-14 (growth 2.7) due to
positive growth of agriculture subsector (Govt. of Pakistan, 2014-2015). Pakistan vision-
“2025” predicts the seven areas of priority and the 4th has been titled as-“ Water, Energy and
Food Security” and 5 top objectives to attain food security, the 4 th ensures the provision of
stable and inexpensive access to enough, nutritious and healthy food for better life. The
performance of agriculture sector in Pakistan remained slow due to some factors like low rate
of technological innovations, low quantity, poor quality and untimely supply of inputs. Less
investment in infrastructure, pests, disease attack, limited amount of credit and specific
financing for agriculture.
Rapeseed and mustard are grown especially in those areas where wheat is grown, so it
does not only compete with wheat but also fodder for water resources and other inputs.
Wheat is a major crop, staple food and have support price in the country therefore, farmer
prefers it to grow, and as a result, oilseed brassicas are deprived of water and inputs. Oilseed
crops are grown on marginal lands therefore; its production is stagnant rather decreasing.
Pakistan has been suffering from chronic shortage of edible oil due to above mentioned
factors. The local production of edible oil meets 25% of national demand and for remaining
75%, it depends on imports from Malaysia, Singapore, South Korea, Argentina and
Switzerland. Pakistan imports soybean and palm oil from these countries. This difficult
situation demands to develop local verities of oilseed crops which are high yielding with high
oil contents and have potential to fill the gap between the production and demand. The
demand of vegetable oil globally is increasing with the increase in diversity of its usage e.g.
food industry, chemical industry and diesel engine.
Brassica campestris has been cultivated in South and South East Asia since 4000 BC
for vegetable oil to be used in kitchen and lamps (Snowdow et al., 2007) while in Europe
since 13th century for oil lamps and in 19th century it was used as a lubricant in steam engine
2
(Downey and Robbelen, 1989; Colton and Sykes, 1992).Commercially, it was grown in
Canada in 1942 and used as lubricant in war-ships (Colton and Potter, 1999). Now-a-days
rapeseed is not only being used as biodiesel directly but also mixed with petroleum products.
In future it may replace the fossil fuel that is not renewable and friendly to the environment.
Rapeseed oil contains the fatty acid, erucic acid from which erucamide is derived which is
used as slippery agent in plastic industry. Brassica campestris completes life cycle in the
shortest duration compared with any of its relative species.Owing to advantages of
comparable yield, better seed oil contents and maturity time, farmers like to grow it. This
species is also grown strategically to control aphids in wheat.
The small and round seeds of brassica have been reported to contain about 40 to 44 %
oil (dry weight basis) and 38 to 41 % protein, high percentage of oleic acid (60.2 %),
linolenic acid (10.9%), linoleic acid (21.3 %), eicosenoic acid (1.3%) and low erucic acid
(0.5%) (Fehr and Jessen, 1987). This type of fatty acid composition has been suggested
suitable for human health by the Physicians (Rakow and Raney, 2003). Oilseed brassicas
have been ranked after soybean and palm oil in edible oil production and are at 5 th position in
production of oilseed protein (Salunkhe et al., 1992). Brassica species have played an
important role in agriculture and contributed to economy and health in the world. The
development of breeding techniques in rapeseed for oil technology that developed the canola
varieties in Canada and Europe also increased production of rapeseed all over the world. The
Brassica oilseed that contains 2 % or less erucic acid and 30µmoles/g or less glucosinolate of
oil free meal is known as canola. Therefore, canola oil replaced soybean that was a big
source of vegetable oil throughout the world.
Major oilseed brassicas producing countries in the world are Canada, Indian
subcontinent and Europe while Pakistan is on 10th position (Fig.1.1).
There is seed production decline in rapeseed and mustard after the year 2006-07 and
2007-08, however it slightly improved in the year 2013-14 and fell again the following year
(Fig.1.2), and that might be due to marketing problems, low support price and high cost of
production. These all above mentioned factors make the crop less profitable for a farmer.
Area under rapeseed has also the same trend as that of seed production (Fig.1.3).
3
(Source: Index mundi, 2015)
Figure 1.1 Major rapeseed producing countries.
(Source: Economic Survey of Pakistan 2014-15)
Fig.1.2 Seed and edible oil production
0
2000
4000
6000
8000
10000
12000
Major rapeseed producing countries (000MT)
47584930
4631
41813983 3865 3918 3947 3987
3825
793 855 833 718 662 696 636 612 573 546
200
650
1100
1550
2000
2450
2900
3350
3800
4250
4700
5150
2005-06 2006-07 2007-08 2008-09 2009-10 2010-11 2011-12 2012-13 2013-14 2014-15
Seed and edible oil production
Seed Edible oil
4
(Source: Index mundi, 2015)
Fig.1.3 Area and production of rapeseed oilseed About 0.612 million tons edible oil is produced locally from cottonseed, brassicas,
sunflower and soybean.Oilseed brassicas were grown about 482 thousand acres area and the
production of 176 thousand tones for seed yield during 2012-13. The remaining 1.738
million tones edible oil demand is met through imports. The total cost for import bill during
the year 2013-14 was 153.3 billion rupees (Economic Survey of Pakistan, 2013) that is huge
burden on national exchequer. The average local production of rapeseed oilseed remained
191.73 metric tons from 2005 to 2015 while the import of rapeseed oilseed was 772.55
metric tons (Fig.1.4).
(Source: Index mundi, 2015)
Fig.1.4 Rapeseed oil seed production and import
180
210
240
270
300
330
360
390
420
450
480
2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
Area and production of rapeseed oil seed
Area Production
181221
185 199162 192 179
220 190 220160
819 806
535596
977
811
932
577
930 915
600
0
100
200
300
400
500
600
700
800
900
1000
2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
Rapeseed oil seed production and import
Production Import
5
Such existing gap of about 70% between the production and consumption is due to
constraints such as
1) Non availability of canola version and high yielding varieties.
2) Discouraging marketing system for the farmer to grow oilseed crop.
3) Free import policy at government level.
4) High growth rate in population.
The high population growth rate has high input cost for edible oil and it is increasing
at the rate of 13% per annum (Razi, 2004). Pakistan is far behind in yield per unit area of
oilseed crop production compared with the leading countries of the world. There is a big
difference between seed yield per unit area of rapeseed and mustard in Pakistan and rest of
the world. Seed yield at global increased year after year but in Pakistan it remained stagnant
or negative due to the factors mentioned above. The average yield per unit area was 854.49
Kg per hectare from last eleven years (Fig.1.5)
(Source: Index mundi, 2015).
Fig.1.5 Yield of rapeseed oilseed per unit area in Pakistan
This difficult situation has posed a challenge for the plant breeders to search out the
conceivable solution of this problem. The main objective for plant breeders has become to
get higher yield, good nutritional qualities and other traits of commercial importance (Moose
and Mum, 2008 and Ali et al., 2013). To improve the edible oil production, there may be
three options;
750.00
800.00
850.00
900.00
950.00
2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
Yield of rapeseed oilseed per unit area in Pakistan
6
Area may be increased under the oilseed crops
The development of high yielding cultivars
The seed’s oil contents may be increased.
For the first option seed yield can be increased, however the competition with the
other main crops especially wheat and fodder will be increased. The most suitable options
are the 2nd and the 3rd. In these cases more production and oil yield can be taken per unit
area. To meet the challenges mentioned above, breeding for high yielding cultivars in
oilseed brassicas is the need of time. Breeding programs have been started at various stations
to develop high yielding cultivars in oilseed brassicas however local varieties have two
undesirable seed constituents i.e. erucic acid and glucosinolates. The safe limit for human
consumption and animal is < 5% erucic acid and < 30 µmoles/gram of glucosinolate in oil
free meal. Such varieties are called double zero or double low varieties. These varieties are
registered under the name of canola in Canada. Pakistan imports the seed of double zero or
double low varieties spending huge money. Present studies are meant to improve the genetic
potential and oil quality of Brassica campestris. The improvement would be based on
selection/breeding using the genetic cues of variability. These studies will generate breeding
material and scientific informations on inheritance pattern, correlation and path analysis,
heritability and heterotic manifestations to frame out future selection strategy for the
development of better yielding, short duration, and canola types in B. campestris having
higher seed oil content.
Objectives of the study:
1) To generate genetic information on various plant and seed traits.
2) To estimate genetic variability in the breeding material and finally to create it.
3) Development of potential hybrids on intraspecific and interspecific levels that could
yield better with better oil content.
4) Interspecific hybridization of B. campestris was also done to obtain probable
introgressions from B. napus and B. juncea.
7
2 CHAPTER REVIEW OF LITERATURE
Oilseed brassicas, rapeseed and mustard, are rich source of vegetable oil, contribute 12-14%
of world oilseed production and is the third largest source after palm and soybean (Sovero,
1993; Zhang et al., 1999; Beckman and Loeb, 2005; Porter and LeGare, 2006; Zhang and
Zhou, 2006; Gupta and Pratap, 2007 and Wittkop et al., 2009). Brassica species not only
contain vitamins and dietary fiber but also anticancerous compounds (Fahey and Talay,
1999).
Brassica campestris belongs to Brassicaceae/crucifereae family. The name cruciferae
had been given due to flower shape that has four diagonal opposite petals like cross. Brassica
campestris foliage is green. Leaves have smooth or rough surface with stiff hairs. Stem is
partially clasped with upper leaves and it is well branched. The numbers of branches depend
on the variety or biotype and condition of the environment. Branches develop from the leave
axils present on the stem. Lower sided leaves are petioled, pinnatified or toothed and upper
sided leaves are sessile, lance oblong, articulate, sub-entire and constricted above the base.
Inflorescence is raceme and the flowers are pale yellow with four petals. The above or at the
terminal buds, there is a cluster of open flowers which opens upward from the base of raceme
(Downey et al., 1980).
2.1 Phylogenetic Relationships
Rapeseed and mustard species are diploids and amphidiploids in nature.The amphidiploid
species of Brassica (Brassica napus and Brassica juncea) have been evolved from diploid
species like B. rapa, B. nigra and B. oleracea and and through hybridization as prescribed by
U’s triangle in figure (2.1).
Figure 2.1 Phylogenetic Relationship among Brassica species
8
This Brassica triangle is an excellent model system for these diploid species and their
amphiploids, to investigate homeologous recombination and polyploidization mechanisms
(Snowdon, 2007).
A numbers of studies focused on the origin and relationships of genomes of brassicas
and framed out a close relationship between various species, and suggested that species with
genome A, B and C are parental ones. (U, 1935; Attia and Robbelen, 1986a; Busso et al.,
1987 and Li et al., 2010)
Li et al. (2010) studied the comparative genome analysis and supported U, (1935) view
regarding the evolution Brassica species which were hypothesized that all A, B and C
genomes originated from diploid common ancestor with genome x = 6 chromosomes (Attia
and Robbelen, 1986a). During the course of evolution, a lot of chromosomal variation
resulted in the genome due to duplications, deletions. Because of this, rearrangement and the
intensity of relationship between A and C was higher than that of A with B and B with C.
Apparently chromosomes pairing in the amphidiploids may obstruct meiotic pairing
whereas pairing is quite normal and diploid in all tetraploid species in nature. Attia et al.
(1986b) and Busso et al. (1987) suggested that haploid hybrids of B. campestris, B. oleracea
with B. nigra had less amount of chromosomal pairing in contrast to B.campestris×B.
oleracea. Critically thinking, it can be deduced that B. nigra may have such system which
suppresses homeologous pairing in oilseed brassicas but the results revealed that incapability
of B. nigra to influence the pairing level between homeologous chromosomes of the A and
C genomes. No genetic involvement was found in B genome for the inhibition of pairing and
with out cytoplasmic effect on the pairing regulation. Attia et al. (1987) reported a high
meiotic pairing and evolutionary changes between the chromosomes of B. campestris (AA)
and B. oleracea (CC) which might help to understand the high level of chromosomal pairing
in A and C genome chromosomes compared with other genomes in any combination (Hühn,
1991)
The genomic studies of amphidiploid Brassica napus revealed that progenitor diploid
genomes (A and C) have been extensively duplicated with 73% of genomic clones and each
diploid genome had two or more duplicated sequences. This high range of duplication of loci
in a species showed its development through polyploidy. These duplicated loci in the diploid
genomes were found in different linkage groups as collinear blocks of linked loci. After the
9
duplication some showed a variety of rearrangements including inversions and
translocations. These diploid genomes showed many identical rearrangements which
indicated that they had occurred before the divergence of the two species. Some linkage
groups exhibited an organization consistent with centric fusion and fission indicating that this
mechanism might have played a role in Brassica genomes evolution. Homologous locus was
almost found in both genomes. This collinear arrangement indicated the primary regions of
homeology between the two genomes. About 16 gross chromosomal rearrangements were
responsible for differentiation of these two diploid genomes during their divergence from a
common ancestor (Parkin et al., 2003). A high level of co-linearity between Brassica species
have also been indicted using 3 SNP/indel and 41 SSR markers. However, two small regions
on A4, A5 and A10 showed apparently local inversions between them. This showed that
sequence-based molecular markers can help in exploitation of the B. rapa genome sequence
for the improvement of oilseed rape (Suwabe et al., 2008).
The arrangement of chromosome pairing and recombination in two contrasting
Brassica napus, F1 hybrids were studied. Segregation at 211 equivalent loci assayed in the
population derived from each hybrid produced two collinear genetic maps. Progenitor’s
genomes of B. napus have been unchanged since its origin. Although the frequency and
distribution of crossover could not be distinguishable, but also through recombination
machinery of B. napus different degree of genetic divergence between homologous
chromosomes could be determined. Novel alleles into oilseed rape can be introgressed from
B. rapa and B oleracea through recombination and their linkage can be reduced (Parkin and
Lydiate, 1997).
2.2 Centre of Origin and Domestication
Brassica campestris name was given to a weed annually growing in “non loamy fields
of Europe” by Linne, (1753) in “Species Planatarum”. DeCandolle et al. (1824) described it
as Brassica campestris “Chou des champs” (field kale) and indicated that it had rough, stiff
hairs when it is young plant as in Brassica rapa. After that Metzger in 1833 classified B.
campestris and B. rapa as similar species and the taxa was combined below the name B. rapa
(Toxeopus et al., 1984). Confusion was created in Nomenclature when these were classified
under the same species and then wild type was given second position under Brassica rapa
10
(Reiner et al., 1995). Oleifera, wild B. rapa is a subspecies from which var. rapa, var.
silvestris and Briggs had been evolved.
Generally believed it originated from central Asia and the Near East and throughout
Europe (Prakash and Hinata, 1980). Afghanistan may be the independent centre of origin for
the Asian and Eastern type that moved eastward and then it was domesticated. Oleiferous B.
rapa was established in two places and consisted of two races European and Asian (Prakash
and Hinata, 1980). According to Warwick and Francis (1994) Brassica rapa developed from
coastal lowlands, hills, plateaus and mountains up to 2300 meter. However, some believe B.
rapa has origin from highland areas near the Mediterranean Sea instead of areas of coastal
Mediterranean (Tsunoda, 1980). There is cold climate of these mountainous areas and B.
rapa shows high vegetative growth under the cool climate. So it extended northward to
Scandinavia and from west-ward to Germany and Eastern Europe (Nishi, 1980).
Figure 2.2 Evolutionary histories of B. campestris and its relatives (McNaughton, 1979).
It is also believed that cultivated B.campestris developed from a wild strain
B.campestris, originated from Western Europe to China (Gupta and Pratap, 2007) as shown
in Fig22. Nevertheless, B.campestris has been cultivated as an oilseed crop in subcontinent
and there is not known a valid wild form in Pakistan or India.
11
The right domestication place and time is not known but Indian Sanskrit writings of
1500 to 2000 BC suggest that rapeseed and mustard had been grown. Greek, Roman and
Chinese Writings of 200 to 500 BC refer the occurrence of oilseed brassicas (Downey and
Robbelen, 1989). Since 13th century oilseed brassicas has been cultivated in Europe for oil
for lamps and in 19th it was used in steam engine as a lubricant (Downey and Robbelen,
1989; Colton and Sykes, 1992). Oilseeds rape for the first time was commercially grown in
Canada in 1942 and was used as lubricant in war-ships (Colton and Potter, 1999). Breeding
of rapeseed for low erucic acid and low glucosinolate was started in Canada and Europe in
1960. Canola is high quality and modern form of Brassica. It was started in Canada from
genetic modification in rapeseed through plant breeding. The first cultivar with “double low’’
was developed in Canada in 1970. The name canola was trademarked (Uppstrom, 1995).
Today, among all the vegetable oil fatty acid profiles, canola oil fatty acid profile is the most
suitable (Stringam et al., 2003). Now the erucic acid is less than 2% and glucosinolates less
than 30 micromoles/gram in meal protein of canola (Downey, 1990 and Nelson, 2000).
Canola is cultivated for seed that contains 35-45% oil. Canola is the rich and cheap source of
omega-3 fatty acid and vitamin E. After the oil extraction the byproduct canola seed meal is
used for animal feed (Krzymanski, 1998). The new achieving target is 15µmol in seed meal.
2.3 Forms of Brassica campestris
Although there are different groups of B.rapa based on their morphology, however
three are well-known.
(1) The Oil type or oleiferous with special characteristics having erucic acid and
glucosinolate in less quantity in meal.
(2) The leafy or vegetable group that includes chinensis (pak-choi, celery mustard), Chinese
cabbage (the var. Pekinensis) and the perviridis (tender green). These vegetable groups
have large number of variation and are considered as separate species because these
have been evolved in isolation. Only Pekinensis has some relations to oilseed type.
(3) The rapiferous type B. rapa (turnip) that is grown as vegetable and fodder for animals all
over the world (Prakash and Hinata, 1980). Brassica rapa can be further subdivided into
two forms (I) Indian forms (II) Western European and North American form. Indian
forms include subspecies trilocularis (Roxb) Hanelt, called dichotoma (Roxb) Hanelt
and yellow sarson, brown sarson and Toria while Western European and North
12
American form includes oleifera subspecies of B. rapa (DC.) Metzg. (Kimber and
McGregor, 1995).
2.4 Genetic Variability in Different Seed and Plant traits
2.4.1 Morphological Traits
Plant height (cm), number of primary branches/plant, number of secondary branches/plant,
green biomass/plant and harvest index for genetic variability have been studied by different
researchers, significant and non-significant differences were noted for these morphological
traits. Nasibullah et al. (2015) and Mekonnen et al. (2015) found difference significantly in
Brassica for plant height, primary branches/plant, and secondary branches/plant,
biomass/plant and harvest index. The range of variability of height in spring rapeseed had
been reported from 69.5 to 180 cm (Ali et al., 2003; Sadaqat et al., 2003; Fahratullah et al.,
2004; Sincik et al., 2007; Dar et al., 2010; Sabaghni et al., 2010; Zareand Sharafzadeh,
2012; Synrem et al., 2014 and Iqbal et al., 2014). Shehzad and Fahratullah (2012) also
reported significant differences in interspecific crosses of genus Brassica for plant height.
The comparison of relative measure coefficient of variation showed that harvest
index had low variation as compared to grain/straw ratio (Huehn, 1993). However,
estimation for the relative incolvement of biomass, harvest index and other yield
contributing traits to seed yield gain of soybean showed that harvest index had more
contribution to the soybean yield grain than biomass (Cui and Yu, 2005). During the
comparison of development and yield of five Brassica spp. (genotypes two for B.juncea,
two for B. napus, and one for B. rapa (B. campestris), it was noted that plant height of one
canola-quality genotype of B. juncea was 21% greater than th average of other genotypes,
but its shoot biomass was not different for the identical assessment. The mean seed yield of
non-canola type genotype of B. juncea was 12% better than the maximum yield of B.
napus cultivars and 32% better than the B. rapa cultivar, and with higher harvest index
(Miller et al., 2003).
2.4.2 Phenological Traits
Number of days taken to flowering initiation, 50% flowering, 50% siliquae formation and
maturity are all crucial events in a plant life cycle that ensures its optimal reproduction.
Flowering is one of important stages in rapeseed where it affects the yield in large quantity
(Faraj et al., 2008). Siliquae formation, number of grains and seed yield are strongly affected
13
by flowering initiation (Downey and Rimer, 1993; Diepenbrock, 2000; Yasari and
Patwardhan, 2006). Oilseed brassicas showed significant and highly significant variation for
number of days to flowering reported by earlier researcher. The reported range for flowering
periods remained from 21 to 222 days (Ali et al., 2003; Iqbal et al., 2003; Cheema and
Sadaqat, 2004, Sabaghnia et al., 2010; Rameeh, 2012; Zada et al., 2013 and Singh et al.,
2014). Mostly agronomic traits show quantitative variation. These traits are controlled by
multiple genes or depend on environment. Only 60% phenotypic variation was contributed
through genetic effects. QTL numbers, interacting loci and aligned functional genes analysis
showed that there is a intricate genetic network that controls flowering period in B. napus
(Long et al., 2007). Crossed population of Brassica rapa was developed and quantitative trait
loci (QTL) analysis of 20 morphological trait was done including flowering time. Total 27
QTL affected 20 morphological traits and eight QTL effected the flowering time and
remaining was for other traits. The study also indicated that the some loci control leaf and
seed-related traits and those for flowering period and turnip formation may be the same (Lou
et al., 2007 and Nasim et al., 2014). Remarkable variation for days to 50% flowering was
reported for rapeseed. The range for variation was from 61.67 to133.70 days (Gosh and
Gulati, 2001; Sadaqat et al., 2003; Farhatullah et al., 2004 and Dar et al., 2010).
Singh et al., (2012) observed the non-significant results for 50% days to flowering in
Brassica juncea. The study for the effect of nursery age and row spacing on phenology of
canola (Brassica napus L.) revealed that transplanted nursery took more days to 50%
flowering as compared to direct sowing while siliquae formation took more days in form of
direct sowing as compared to nursery (Ingh and Singh, 2013). Studies on growing of oats
fodder as an intercrop indicated significant influence on the growth of B. napus but
phenology of crop was not affected. The range for number of days for 50% flowering was
from 63.8 to 102 days while for 50% siliquae formation was from 74.5 to 109.8 days. The
maturity days were from 144 to 157 days (Singh and Singh, 2014). Similarly evaluation of
canola version genotypes of B. napus under drought and normal recommended, irrigation
conditions, significant results were noted under irrigated condition for plant traits studied,
nevertheless the results were none significant under drought conditions for 50% flowering,
50% siliquae formation and 50% maturity days (Sadaqat et al., 2003) .
14
2.4.3 Seed Yield Components
Number of siliquae and seeds/siliqua, 100-seeds weight and seed yield per plant are major
yield contributing trait. Seed yield is the final outcome of genotypes and their environmental
interaction. Yield is a complex of population density, number of siliquae, seeds/ siliqua and
seed weight (Dipenbrock, 2000). Oilseeds brassicas have significant and highly significant
variation for seed yield and yield related traits such as number of siliquae/plant, number of
seeds/siliqua, 1000-seed weight and yield/plant ( Ghosh and Gulati, 2001; Ali et al., 2003;
Fahratullah et al., 2004; Rahman et al., 2009; Dar et al., 2010; Abiden et al., 2013;Ddin et al.,
2013; Kang et al., 2013 and Nasim et al., 2014). Interspecific hybrids also revealed
significant variations for seed yield/plant and 100-seed weight (Ullah et al., 2015).
Nevertheless non-significant results have also been reported (Zare and Sharahfzadeh, 2012)
and its expression is environmentally affected (Ali et al., 2003 and Dar et al., 2013). Genetic
variability studies showed that yield and yield contributing traits in rapeseed indicated low
variation at genotypic and phenotypic level for 1000-seed weight while moderate for
siliquae,seeds/siliqua and yield per plant (Parveen et al., 2015). Number of siliquae per plant
have important role for genetic divergence while yield per plant has less role as compared to
number of siliquae (Naznin et al., 2015). Genotypic variance was greater than phenotypic
variance for all traits studied without yield (Halder et al., 2015) . The numbers of siliquae per
plant varied from 70 to 165 (Sadaqat et al., 2003; Aytic and Kinaci, 2009; Raman et al., 2013
and Rameeh, 2011). The maximum mean value (365) reported for numbers of siliquae/plant
and significant differences were noted for brown mustard (Dar et al., 2010). Genetic diversity
analysis of F4 progenies developed through interspecific hybridization showed that, 1000-
seed weight played maximum role for genetic divergence (Choudhary et al., 2002a). The
genetic variation among seed-related traits and QTL involved were studied in Brassica rapa.
13 QTL were found for nine traits. A linkage map was developed with a map distance of
757cm and average distance between two consecutive markers was 6.4cm. QTL for seed
colour, seed weight, seed size, oil content, siliquae, seeds per siliqua were LOD 26, LOD 4.6,
LOD 7, LOD 6.6, LOD 3 and LOD 3 respectively (Bagheri et al., 2013).
2.4.4 Oil Quality Traits
Seed oil, seedcake protein, seed cake glucosinolates, seed oil oleic acid and seed oil erucic
acid contents are the output of a plant. Oil and fats have great value for human diet, energy,
15
taste and palatability. Oil content is a composite trait that is under control of many genes and
affected by the environment (Si et al., 2003). By increasing one percent in oil means
increasing 2.3 to 2.5% yield (Wang, 2004). Therefore increase in oil would increase in yield.
Studies on genetic variation for quality traits in oilseed brassicas indicate both significant and
non-significant variation. Derivative hybrids of interspecific population showed variation
highly and significant for oil content, oleic acid, linolenic acid, erucic acid and glucosinolates
while protein showed non-significant results (Khan et al., 2008). Estimation of genetic
variability in F2 segregating population developed though intra and interspecific
hybridization exhibited remarkable variation for oleic acid, linolenic acid, erucic acid and
glucosinolate. For protein results were also significant contrasting the results noted by Khan
et al. (2008) and Fayyaz et al. (2014). Biochemical analysis of advanced population F10:11
developed through interspecific hybridization indicated significant variation for oil and
protein traits (Naseebullah et al., 2015). Significant variation between yellow and brown
seeds only for oil and fatty acid were observed (Lionneton et al., 2004). Four oilseed species
castor bean, sunflower, rapeseed, flax and safflower were grown at different temperatures of
26.5, 21, 16 and 10 °C for the period of seed development. Temperature had no effect on oil
of safflower, sunflower and castor bean. The highest oil content was found in rapeseed and
flax seed at the lowest temperature. There was gradual decrease in oil content as the
temperature was increased. However, safflower fatty acid composition and oil of castor bean
were not affected by changing the temperature. Increase in temperature decreases unsaturated
fatty acids in rapeseeds, sunflower and flaxseed. This decrease, increased in the amount of
oleic acid. By changing the temperature the saturated fatty acid composition in all species did
not change (Canvin, 1965).
The genetic effect and Genotype×Environment interaction were studied on erucic acid
and linolenic acid through conditional and unconditional genetic models. The result for
unconditional analysis that G×E was important and seed selection would be helpful for the
improvement in these traits. Conditional analysis also showed that these traits were affected
by the environment. Narrow-sense heritability was higher for both traits and broad sense
heritability for erucic acid increased with the time interval. Phenotypic and genotypic
association was positive for these traits for pair wise comparisons. However negative and
significant association exists berween linolenic acid and erucic acid (Variath et al., 2015).
16
The glucosinolates are accumulated in Brassica tissues after the infestation of pests and
cause the resistance against the pest in Brassica species. Glucosinolates accumulation
concentration may be different in leaves and those leaves with more glucosinolates
concentration were more resistant than those with lower concentration (Doughty et al.,
1991).
2.5 Creating Genetic Variability through Hybridization
Genetic variation above or at the species level is created by the evolutionary forces and
variation at species level is more important for cultivation. Creation of new species and
variability within the species is generated by human interference according to his need
(Sharma and Thorpe, 1989).
There are four processes that bring the changes in the wild species making them
suitable for cultivation (Simmonds, 1962).
1) Gene recombination
2) Creation of novel variation
3) Differences in reproduction
4) Isolation Mechanism
These all processes are necessary to bring up and speed up the changes in species.
These changes occur more quickly in cultivated species than in natural species. So the
intraspecific variability generated in this way appears at lower and higher level. Intra
population variation in a specific specie i.e. lower level variation between genotypes that
occurs due to mutation or recombination of major genes, while inter population or higher
level variation is due to change in gene frequency that is due to the accumulation of lower
level variation. The variability created for gene frequency does not originate only from
mutation. Two other forces i.e. random variation fixation and role of natural selection are
also responsible for creation of new genetic variability (Stebbins, 1950). Inter population
variation that occurs due change in gene frequency is of great importance in evolution and
intra population variation plays its role in plant breeding (Sharma, 1989).
2.5.1 Intraspecific Hybridization
The individuals have similar genes within a species but they are different with respect to
phenotypic characteristics and behavior due to minute differences in genotypes and their
interaction to the environment. It was reported for the first time by” Charles Darwin and
17
Alfred Wallace’’ in their paper ‘‘On the Tendency of Species to form Varieties; and on the
Perpetuation of Varieties and Species by Natural Means’’ that was read in the Linnean
Society in London on July 1, 1858 (Harrison and Regional, 2001).
The knowledge of the genetic variability, its extent and the kind of relationship of
quantitative traits in rapeseed and mustard is necessary for a resourceful breeding program.
The use of quantitative genetic variability plays an important role for the high yielding
verities development and advancement of the economically important traits (Mahmood et al.,
2003). The relationship of seed yield components and quality traits are of main interest.
Genetic variations, association and heritability were studied for quantitative and qualitative
traits in different genotypes of rapeseed.Immediate selection for seed, oil yield and protein
content would be rewarding for improving oil and protein yield (Khan et al., 2006; Aytac
and Knac, 2009). Diversity analysis of Brassica genotypes based on protein polymorphism
showed a large degree of variations among genotypes of different Brassica species i.e.
Brassica rapa, Brassica juncea, Brassica napus and Brassica carinata as some cultivars
exhibited considerable polymorphism on the basis of protein banding pattern. Polymorphic
bands were different for Brassica species; Yellow sarson and brown seeded cultivars.No
direct relationship had been observed for genetic diversity and the geographical distribution
(Khurshid and Rabbani et al., 2012). A great variation has also been studied in rapeseed for
seed weight in naturally existing germplasm; however, causes of genetic variations were not
clear. Seed weight is controlled by the maternal effect having little or no xenia and
cytoplasmic effect (Li et al., 2015).
2.5.2 Interspecific Hybridization
Wide hybridization of B.napus and B. rapa is well-known (Wilkinson et al., 2000 and
Hensen et al., 2001). Production of hybrid was high when B.napus was used as female but it
was low when it was used as male parent (FitzJohn et al., 2007).Through interspecific
hybridization in B.napus×B.rapa and B.juncea×B.rapa good amount of hybrid seed was
produced without any special cell or tissue culture techniques (Raman et al., 2013).
Interspecific crossing was successful between (B.juncea×B.napus) produced hybrids at rate
of 2.1% and (B.napus×B.juncea) produced 2% hybrids on average. Crosses between B.
oleracea×B.napus were unsuccessful Heenan et al. (2007) but results were vice versa given
by Choudhary and Joshi (1999). Chiang et al. (1977) reported that successful combinations
18
used the tetraploid B.oleracea. Studies show that hybrids between B.napus and B.oleracea
could not be evolved without involving the in vitro techniques (Takeshita et al., 1980; Kerlan
et al., 1992). But in some cases it is very difficult to produce viable seed of interspecific
crosses, e.g. B.napus×B.oleracea, B.napus×B.nigra and B.juncea×B oleracea (Downey et
al., 1980; Benett et al., 2008; Rahman, 2013). In these situations invitro techniques i.e.
embryo culture or ovule culture (Rahman, 2004; Bennett et al., 2008) can be used. Heyn
(1977) revealed the high amount of hybrids production between B.napus×B.nigra that does
not agree with results noted above. Successful hybridization of B.napus with other species of
Brassica were reported for example B.carinata (U, 1935; Wahiduzzaman, 1987; Chen and
Haneen, 1992; Getinet et al., 1997), B.fruticulosa, B.tournefortii (Heyn, 1977), B.maurorum
(Bijal et al., 1995; Chrungu et al., 1999).
B. napus and differences in findings indicate that the rate of production of hybrid was
high when B. rapa was used as female parent instead of B. napus, in case B. rapa ssp.
Chinensis (Janetta et al., 2015). For the evaluation of wild relatives as genetic resource
intergeneric crosses with B.napus were attempted and majority has been reported as
unsuccessful (FitzJohn et al., 2007). Successful crosses of B. napus with its wild relatives
such as Diplotaxis catholica, D. erucoides, D. muralis D. tenuifolia, Eruca vesicaria,
Erucastrum gallicum, Hirschfeldia incana. Although the naturally gene flow is limited in
Brassicaceae family however it can be introduced easily (Brown and Brown, 1996; Riger et
al., 2001).
Brassica juncea (Indian mustard) is close relative of B. napus and have a common set
of genome of B. rapa (AABB) and (AACC) that enhances the possibility of inter-specific
crossing (Salisbury and Downey, 2002). B. rapa is their common progenitor and their
hybridization occurs in the field. During the study, the possibility of gene transfer from
domesticated species to the non- domesticated it was concluded that there are zero chances of
gene transfer from domesticated species to their wild relatives such as B.nigra and Sinapis
arvensis. However interspecific crossing among the cultivated species occurred in the field
conditions (Bing et al., 1996). Hybrids were obtained through crossing of B. juncea and B.
campestris in both directions. The frequency was higher when B. juncea was used female
parent (Choudary and Joshi, 1996). Interspecific hybridization is easy between B. juncea and
B. napus through hand pollination (Muhammad and Sikka, 1940; Rao and Shivana, 1997;
19
Mason et al., 2011a; Tsuda et al., 2011) while out crossing occurs between B. napus and B.
juncea in natural condition from 3 to 4.7% when B. napus male plants are in close contact
(Bing et al., 1991). Hybrid of (B. napus×B. juncea) have low pollen fertility that is from 0
to 28% however seed is viable and survives to next generation (Bing et al., 1991).
Spontaneous hybridization is possible if cultivation is made in isolation or through wind and
insect pollination (Becker et al., 1992). Nevertheless spontaneous hybridization is difficult in
B. juncea due to self incompatiblity and rate of spontaneous hybridization was 0.05% at 1 m
distance and was.03% at17.5m distance and there is no report of hybrid production distance
of 20 to 27.5m. Hybridization is successful when B.juncea is used as female in case of
B.nigra and B.carinata (Morinaga, 1931; U, 1935; Mizushima 1950; Raman 1976 and
Getinet et al., 1987). Struss et al. (1991) reported the successful hybridization of B. juncea
with B. carinata. Hybridization is possible with B. tournefotii (Goyal et al., 1997), B.
maurorum and B. gravinae (Bijiral et al., 1995 and Nada-kumar et al., 1988b). Intergeneric
crosses of Brassica juncea have been repoted with different genrera such as Diplotaxis
erucoides, Eruca vesicarea, Erucastrum virgatum and D. tanuifolia (Salisbury, 1991:
Inomata, 1998; Bijiral and Sharma, 1999a; Inomata, 2001). Lefol et al. (1997) produced the
hybrid under the natural conditions between B. juncea and Raphanus raphanistrum through
reciprocal crosses. Brassica trigenomic vegetable had been produced through interspecific
hybridization between mustard (B. juncea) and cabbage (B. oleracea with the help of embryo
culture. Li et al. (2014); Yan et al. (2009) and Weerkoon (2011) also reported the trigenomic
hexaploid Brassica though interspecific cross between B. juncea and B. oleracea. Normal
crossing had not been reported of B. juncea and B. oleracea under the field condition (Bing
et al., 1996). Artificial pollination has been reported only for obtaining hexaploid Brassica
somatic hybrids with the aid of protoplast fusion between B. oleracea and B. juncea
(Arumugam et al., 1996). Takeda (1983) revealed that hybridization between B. juncea and
B. oleracea was harder. It shows the more level of sexual incompatibility between B. juncea
and B. oleracea.
2.5.3 Introgression
Rapeseed and mustard species are closely related to one another (U, 1935). The crosses
between diploid species to form amphidiploids naturally occurred long ago where they grew
in close contact. It is important to note that genome of B. campestris is common to all three
20
economically important Brassica species. All three diploid species are self incompatible and
their amphidiploids are self-fertile. Studies on introgression and their cross ability between
and among the species are of great value for a plant breeder because there are great chances
to transfer the genes of economic importance from one species or genera to the others. The
success of the crosses depends on genetics of the parent and direction of crosses (Downey
and Rakow, 1987; Niemann et al., 2015). Moreover, there are some other factors which also
affect the success of the inter-specific hybridization such as growth, temperature, embryo
rescue techniques, age of silique and culture media (Takeshita et al., 1980; Zahang et al.,
2003; Rahman, 2004b and Benett et al., 2008). The rate of success of crosses is high if
amphidiploids are used as female parent nevertheless it is difficult to obtain the hybrids
among the monogenomic species (Downey et al., 1980). Hybrids production within oilseed
Brassica and allied genera have been reported and 35 species were crossed with Brassica
rapa, 34 with Brassica juncea, 27 with Brassica nigra, 26 with B. oleracea and 43 with B.
napus. However, the combination reported for B.carinata, Sinapis alba and Raphanus sativus
are limited. The rate of hybrid production for successful crosses is low about 0.007 hybrids
per pollination (FitzJohn et al., 2007) because the present genome of Brassica, Sinapis alba,
Raphanus sativus, Dilotaxis and Eruca sativa show the partial homology (Downey and
Rakow, 1987).
Cross compatibility of B.rapa is higher with B.napus than that of B.juncea (Schaeffler
and Dale, 1994; Bing et al., 1996 and Tsuda et al., 2012). The cross ability of B. rapa and B.
juncea is high with B. napus. Hybrids of B. rapa with B. napus and B.juncea can easily
produced (Tsuda et al., 2012; Bing et al., 1996; Schaeffler and Dale, 1994). Natural crossing
among these three species and hybridization in the field can be done, but no natural crossing
between other cultivated species such as B.nigra and Sinapsis arvensis is possible (Bing et
al., 1996). Crossing of B. rapa with B. juncea was successful if the B. rapa was used as male
parent. Similar other successful crosses of B. rapa with B.carinata (FitzJohn et al., 2007;
Howard, 1942; Mizushima, 1950; Choudary et al., 2000a.) and B.nigra (Mizushima, 1950;
Oslon, 1960; Bing et al., 1996) were reported. Inter generic crosses of B.rapa with other
species has also been studied but it was only successful with Dilpotaxis mularis. Variation
was present in the rate of the production of the hybrid among the species.
21
2.6 Inheritance of Different Seed and Plant Traits
The traits of economic importance are inherited quantitatively. They are controlled by poly
genes having small effects and are presented by continuous variation. Polygenes are the
genes present at different loci and affect the expression of same phenotypic trait. The
location of these genes present on chromosomes controlling quantitative traits is known as
quantitative trait loci (QTL).The principle of inheritance is same for polygene and for mono-
gene. The effect of each gene cannot be separated in case of polygenetic inheritance.
However the inference can be drawn from an average level of dominance for the expression
of a particular trait. The study of inheritance for quantitative traits in plants started from early
19thcentury and it was reported by Johannsen, (1903) who studied the inheritance on“
Princess” bean and Nilson-Ehle (1908) who also studied inheritance of color in kernels of
wheat (Sleeper and Poehlman, 2006).
2.6.1 Morphological Traits
Early study on genetics of Brassica species shows that morphological differences were
created through breeding (Oferson, 1924). Different morphological traits are under control of
different gene actions. The study on B. carinata for combining ability and potential heterosis
signified the gene action additive and non additive that control the plant height, primary
branches, secondary branches, biological yield and harvest index (Singh and Singh, 1994;
Asthana and Pandey, 1977; Choudhary et al., 2002a; Chema and Sadaqat, 2004; Sabaghnia et
al., 2010; Azizinia, 2011 and Mohammed, 2011). However, there is substantial amount of
additive gene action for plant height in B. juncea and B.napus (Gupta et al., 2011 and
Azizinia, 2012). Partial contrary findings of Tiwari and Singh (1973) indicated that additive
and dominance gene effects were significant for plant height. Inter-specific crossing between
B.rapa and B. juncea was created; F1 plants were intermediate and vigorous. Trangressive
segregates were found in both direction for plant height and primary branches. Estimates of
genetic effects on green biomass yield in inter-specific combinations of Brassica and
relationship of genetic diversity of parents and its effect on biomass yield were made that
indicated that biomass yield is controlled by additive and non additive gene action in inter-
specific hybrids but additive effects had more contribution (Qian et al., 2003).
For advancement in oilseed breeding it is important to know the combining ability or
mode of inheritance of economic traits. The combining ability or mode of inheritance for
22
morphological traits was estimated in rapeseed. Positive heterosis was noted for mentioned
traits (Marjanović-Jeromela et al., 2007a). General combining ability was not predominant
for secondary branches while significant specific combining ability were observed for
secondary branches in Ethiopian mustard (Teklewold and Becker, 2005). Qian et al. (2003)
observed substantial differences for combining ability estimates in B. napus. Some European
B. rapa showed significant negative GCA effects while Chinese B. rapa showed significant
positive GCA effects that meant Chinese B. rapa might be an important source for
transferring favourable genes of biomass. Significant additive and dominant gene action was
noted for B.napus and B.campestris (ssp. Pekinensis) for the genetic control in both species.
In B. napus while in Chinese cabbage additive and dominant effects were present
respectively (Zhang and Takahata, 2001).
2.6.2 Phenological Traits
The inheritance pattern of gene action was dominant for expression of phenological traits in
Brassica campestris while some traits such as flowering and maturity exhibited the values in
negative direction, showing the excess of recessive genes (Rahman et al., 2011). Both
additive and non additive gene actions were important in controlling days to 50% flowering
and days to 90% maturity.Maturity factors of biennial parents also affect expression of
flowering habit. Annual habit is dominant over biennial and is controlled by several major
genes with a strong effect of modifiers from both the annual and biennial parent. Time of
heading of annual plants in F2 progenies appeared to be controlled by quantitative, mainly
additive, factors. Distribution of heading dates for the F1 and annual broccoli parents showed
a large environmental or cultural effect. It appears that the biennial parents, especially
Brussels sprouts and collards, contributed strong factors for late maturity (Baggett and Kean,
1989).Significant heterosis was observed for 50% flowering and days to maturity. The
variance of GCA (σ2g) was higher for 50% flowering, maturity days while the variance due
to SCA (σ2s) was greater for other traits (Gupta et al., 2010).
2.6.3 Seed Yield Components
The inheritance pattern of gene action was was dominant for expression of yield related
traits.However seed/siliqua exhibited the values in negative direction that means excess of
recessive genes (Rahman et al., 2011). Both additive and non additive gene actions were
important in number of seeds per pod, 1000 seeds weight and seed yield per plant.
23
Significant heterosis was observed 1000-seed weight and seed yield per 100 siliqua. The
variance of GCA (σ2g) was higher for 1000-seed weight while the variance due to SCA (σ2
s)
was greater for seed yield and other traits (Gupta et al., 2010).
2.6.4 Oil Quality Traits
Brassica oil is a high-value agricultural commodity and as the world population increases the
demand for high oil content with good quality cultivars is increasing. Vegetable oils contains
valuable compounds such as vitamin E. Breeding efforts are continued for meal quality and
reduction of anti-nutritive compounds in oilseed Brassica (Wittkop et al., 2009). The
inheritance pattern of oil indicated that oil contents are under control of one major gene
acting in additive manner and polygenes acting in additive and dominance manners (Zhang et
al., 2006b). Inter-specific crossing of B. napus and B. oleracea with high level of erucic acid
and glucosinolate was done to investigate the inheritance of these traits and allelic diversity
in canola. In F2 generation zero-erucic acid plants were in low frequency. In F6 31% plant
families had zero erucic acid while low glucosinolate. Further analysis showed 54% alleles
contributed from B. oleracea (Rahman et al., 2015). The study for quality traits using RFLP-
genomic map in Brassica juncea lines revealed significant epistatic interaction and these
traits were linked with each other (Mahmood et al., 2006). The composition of fatty acid in
rapeseed oil showed that there was additive and partial dominance for oleic acid (Kondra and
Thomas, 1975). Inheritance pattern of rapeseeds shows that two major gene pair control the
erucic acid and oleic acid while glucosinolate is controlled by three major genes pair (Ze-su
et al., 2012). For B. rapa estimation of genetic expression (i.e. gene action) for oil quality-
related traits (oil percentage, glucosinolate, protein percentage, erucic acid, oleic acid was
made. All traits are controlled by dominant gene action except oil percentage. Number of
frequency of dominant genes was higher towards better parents, and number of recessive
genes ware more than dominant genes in all traits, except in the case of lenolenic acid
(Mumtaz et al., 2015). Additive effects are involved in controlling the oleic acid while
dominance effects were none significant (Schierholt et al., 2001). Downey and Harvey
(1963) made direct and reciprocal crosses between the Brassica napus plants having zeroed
and 40 % erucic acid indicated that dominant gene action was not present and fatty acid
composition was under embryonic control. In oilseed rape, the allele that control the erucic
24
acid production at two loci increase contents 9-10% in heterozygous condition (Harvey and
Downey, 1964).
Erucic acid inheritance in rapeseed is under control of two independent gene loci and
the effect of these genes is additive. The composition of oil is directly affected by pollen
source i.e. xenia effect (Stefansson et al., 1961). The studies on the inheritance mechanism in
Brassica campestris, the reciprocal crosses were made between Brassica campestris plants
containing low erucic acid with plants of Yellow and Brown Sarson with 59% erucic acid.
This was observed, the erucic acid from F1 embryo was intermediate between the parents,
indicated the embryonic controlled synthesis of this acid. The genetic analysis of F2, F3 and
back cross showed that erucic acid synthesis is under control of a single non-dominant gene.
The oil analysis from immature and partially germinated embryo indicated that erucic acid
content was the highest in matured and non-germinated seed (Dorrell and Downey, 1964).
The genetic analysis of F2, F3 and back cross revealed that erucic acid synthesis is commond
in two recessive genes acting additively. Erucic acid content is influenced by the
environment especially genotypes (Harvey and Downey, 1964). Reciprocal crosses showed
that erucic acid is controlled through embryo and there is no material effect in inheritance in
B. juncea (Pandey et al., 2013).
The synthesis of eicosenoic acid and erucic acid was under the control of same gene
and effects were additive and dominant for erucic acid and eicosenoic acid respectively
(Kondra and Stefansson, 1965). Stefansson and Hougen (1964) using the summer rape
investigated that each allele contributed the 7.5% increase in the erucic acid content while
summer rape gave 3.5% erucic acid in heterozygous form Krzymanski and Downey (1969).
Krzymanski (1970) studied that 50% of erucic acid is under control of three alleles at
different locus and contribute 0, 4 and 12.5% respectively.
Jonsson (1977) studied the inheritance in rapeseed for erucic acid and concluded that it
was controlled by many alleles and had many homozygosity levels. Levels; 5-10, 10-35 and
>35 % erucic acid were under control of one, one or two and two loci respectively. The
alleles can be distinguished from one another because one produces less than 2% and the
other does not produce erucic acid. However it produces more than 8% eicosenoic acid.
There is positive association between erucic acid and eicosenoic acid up to 25 % level but it
is negative more than 20%. Dominant effect for erucic acid in controlled by 30% allels but
25
there is partial dominance at higher level. The alleles that show the partial dominance in
eicosenoic acid give low erucic acid and those show over dominance produce more erucic
acid. In Brassica campestris erucic acid is monogenically controlled while allele for high
erucic acid is partially dominant over the allele for zero erucic acid (Rahman et al. , 1994).
The functional properties of Brassica campestris meal and reduction of anti-nutritional
factors through enzyme modification and the five enzyme were used i.e. pepsin, trypsin,
ficin, papain and hemicellulase. These enzymes were used to measure the anti-nutritional
factors and functional properties. The enzymes reduced the anti-nutritional factors such as
ficin improved absorption capacity for water and fat and properties for foaming and viscosity
along with nitrogen solubility. By the enzyme modification emulsifying properties is
decreased e.g. when meal is treated with hemicellulase showed good emulsifying activity and
stability but less treated with proteolytic enzyme (Mahajan et al., 1997). The inheritance of
colour of petals and seed in Brassica rapa was controlled by monogene. The genes of petals
and seed colour are independently inherited (Rahman et al., 2001). Silique position also
affects on glucosinolate concentration in Brassica napus. There was higher glucosinolate
concentration in seed of silique on top position within a branch or the whole plant than those
at lower positions. This indicted that silique position had a considerable effect on
glucosinolate content in the seeds (Rahman et al., 2009).
For the evaluation of rapeseed, combining ability plays an important role. Significant
mean square values of combining ability in B. napus for quality traits were noted. These
traits were under the control of genes acting in non-additive manners and vice versa for oil
contents (Shehzad et al., 2015). Prevalence of non-additive genetic control was detected for
all the traits except oleic acid content for which maternal effects were more important (Nasim
and Fahratullah, 2013). The combining ability of ten characters i.e. glucosinolate, protein,
oil, erucic acid, linolenic, eicosenoic, palmitic, oleic, stearic and linoleic was analyzed and
different levels of significance were found for glucosinolate, palmitic, stearic, oleic,
linolenic, eicosenoic acid. General combining ability effects of C-lines were different
significantly for glucosinolate, protein, oil, stearic, oleic, linolenic, eicosenoic acid. Specific
combining ability effect of A-line and C-line have marked influence to F1 three characters
only (protein, oil and stearic acid). General combining ability effects of A-lines and C-lines
26
had much influence most quality characters in F1. So the quality characters of parents should
be improved in breeding (Zun et al., 2005).
2.7 Hybrid Development
The current demands on oilseed brassicas are difficult to meet only with higher yield, good
quality and wider adaptation due to less genetic diversity in germplasm. The main objective
of crop breeding is to improve the existing and creation of new germplasm. The intraspecific
hybridization and interspecific hybridization among brassica species would meet the demand
and cope with the challenges.
Keeping in view the impact of environment and production of oilseeds at large scale, it
is necessary to look for the potential of development of hybrids. The hybrid development
through intra, interspecific and intergeneric crosses are globally underway in almost all sorts
of the field crops including oilseed brassicas. The development of these hybrids is expected
to result in the introgression of the novel traits into these related species. Meiotic analyses of
such hybrids showed that traits related to economic importance i.e. cytoplasm and nuclear-
male sterility, diseases resistance, insects and nematode pests, salt tolerance, cold and
drought conditions can successfully be introduced from related species to domesticated
species and is well illustrated in the literature (Mei et al., 2010; Chen et al., 2011 and Nie-
mann et al., 2012 and 2014). Similarly the development of synthetic amphidiploids, widely
used for improving Brassicas has also been documented in literature (Choudhary et al.,
2002).
2.7.1 Manifestation of Heterosis and Inbreeding Depression
Heterosis is the superiority of a hybrid over its parents and Inbreeding depression is
decrease in hybrid vigor due to inbreeding. Heterosis was first defined by Shull (1948).
Heterosis plays significant role in the development of hybrid varieties for different crops.
However its basic principle is not well understood.
The range of the results of heterosis is varied for rapeseed and mustard due to use of
various experimental materials. The average value of heterosis of better parent was 30% and
range was 20 to 50% in spring rapeseed while in winter rapeseed the average value of better
parent was 50% and range was 20 to 80% (McVetty, 1995). The heterosis studied in oilseed
rape for flowering, plant height, lodging, physiological maturity, 1000 seed weight, oil
percentage, protein percentage and seed yield. Hybrid vigour for seed yield was positive and
27
72% over the better parent and non-significant for plant height, lodging, oil percentage
and1000 seed weight. For flowering and physiological maturity hybrids were intermediate.
The high yielding hybrids in oilseed rape and the commercial exploitation of heterosis
depends on successful development of pollination control mechanisms (Grant and
Beversdorf, 1985). The comparison of nap and mur cytoplasmic system for heterosis, was
investigated and hybrids in nap and mur cytoplasms showed high-parent positive heterosis
for seed yield, total biomass and harvest index (lesser degree) while negative for flowering,
maturity days, oil content and protein concentrations. Moreover mur cytoplasmic male
sterility (CMS) system was better for use in summer rape hybrid cultivars and commercial
hybrids seed production (Riungu and McVetty, 2004). The estimation of heterosis over better
parent signified the yield attributing traits and oil content in Brassica napus L.
Heterosis for different traits showed remarkable magnitude such as for seed yield from
−14.8 to 82.8%, primary branches from−26.0 to 193.6% and siliqua per plant from−21.9 to
162.6%. Unidirectional dominance was also noted for maximum of the traits under
observation. Maximum heterosis was in positive direction for yield/plant (Thakur and
Sagwal, 1997). Heterosis mechanism in B. juncea L parents and F1 revealed that yield and
yield contributing traits were under the control of genes acting in additive and non-additive
manner but non-additive gene effects was dominant. The maximum heterosis with significant
and high GCA effects for seed yield was recorded (Meena et al., 2015). Heterosis may also
be exploited for vitamins and anti-oxidants pigments through best parental combinations.
Highest heterosis in positive direction was observed for ascorbic acid, anthocyanin and
lycopene. The negative heterosis was noted for carotenoids and chlorophyll pigments (Dey et
al., 2014). The highest value for heterosis and heterobeltosis was identified in B. carinata for
primary branches 24.25 vs. 12.30%, seed yield per plant 23.33%, protein content 11.34% and
oil conten14.41%. The highest heterobeltosis for seed yield 9.53%, oil content 7.61% and
protein content 4.11% (Nausheen et al., 2015).
Wang et al. (2009) studied the heterosis for oil content in Brassica napus L and
identified the potential hybrids for oil contents in different crosses. These crosses showed
different heterosis percentage. Some showed positive mid parent heterosis (0.43 to 9.86 %)
and others showed over parent heterosis (0.46 to 8.67). The use of plant biomass plays an
important role for animal hay and production of biogas. The data collected for various traits,
28
amount of heterosis in B. rapa can be increased up to 30% (Ofori et al., 2008). Genetically
diverse genotypes may increase heterosis in B. rapa. Additive gene effects mainly
contributed to hybrid performance (Qian et al., 2007). The inter sub-genomic studies
revealed that heterosis can be obtained and seed yield may be improved through the
introgression in Brassica rapa.
In oilseed brassicas heterosis studies for quality traits are not frequent. The
development of high erucic acid rapeseed hybrids may be the effective way to improve the
concentration of oil. Heterosis studies for seed oil, protein, sum of oil and protein, erucic acid
and glucosinolate, and for seed oil high parent heterosis was noted. For protein and
glucosinolate low heterosis were also observed. Erucic acid showed commercial heterosis.
Zero percent heterosis was also shown for many seed quality traits by many hybrids
(Cuthbert et al., 2011). However Engqvist and Becker (1991) reported different results for
erucic acid, heterosis was significant and negative for better parent and commercial in
rapeseed and for protein there was no heterosis of any kind.
Gami and Chauhan (2014) heterosis estimation for oil content and oil quality traits in
Indian mustard was recorded and identified the better parents and eight good combinations
for oil, oleic acid, linolenic acid, erucic acid and glucosinolate.
Inbreeding depression happens in animals, plant populations and in humans because
genetic variation present in natural populations is common in all species and environments.
Inbreeding depression promotes the out-crossing mating system because intercrossing of
inbreds increases yield i.e. heterosis. Inbreeding depression increases with increase in
population size. Inbreeding depression reduces the plant population strength and its viability.
The magnitude of inbreeding depression is influenced by the plant longevity and history of
life stage. The genetic basis is still unknown. However old genetics and new molecular
studies indicate that inbreeding depression and hybrid vigour are due to recessive and
deleterious mutations that occur in populations (Charlesworth and Willis, 2009). The
evaluation of double haploid lines indicated that some lines were deficient in chlorophyll,
others showed low seed and biological yield, low seed per pod and delayed flowering which
is possibly due to inbreeding depression (Dewan et al., 1998). Daamgaard and Loeschcke
(1994) studied inbreeding depression in rapeseed plants after two consecutive selfings by
comparing them with outcrossed half sibs at mating equilibrium and found 17% decrease in
29
biomass and 15% reduction in flowering. Both these characters are highly corelated with
yield. Ronse et al. (2009) discusses that though inbreeding depression varies with genotype
and environment but it is not possible to predict it. Using quantitative genetics model,
prediction can be made on quantity of inbreeding depression for fitness, arising from
Gaussian stabilizing selection for phenotypic traits that showed, genetic effects were
additive. Inbreeding depression is least affected by the stress environment but it depends on
the phenotypic variability (Waller et al., 2008).
2.7.2 Explanation of Heterosis
2.7.2.1 Classical Basis
Generally three theories exist for the heterosis explanation.
1) Dominance theory.
2) Over dominance theory.
3) Epistasis theory (Crow, 1999 and Goodnight, 1999)
The dominance theory supposes that heterosis occurs due to accumulation of
favorable dominant genes. The deleterious effects of recessive genes in one parent are
masked by effect of dominant genes in other parent. The over dominance theory explains that
heterozygous alleles combination at one locus is superior to the two possible homozygous
allele combination. Epistasis supposes that heterosis occurs due to non allelic interaction.
Different results based on different experiments favours these theories. Quantitative genetics
experimental results support the dominance theory (Crow, 1999). The multimeric enzyme
studies favour the over dominance theory (Stubber, 1999). The theoretical experiments
indicate the non allelic interaction (Goodnight, 1999).
2.7.2.2 Molecular Basis
The genetic based studies of heterosis at QTL level in rapeseed showed 30% and 0.7%
the heterosis for grain yield and kernel weight. In total 33 QTL were identified and 10
showed dominance effects. For grain yield dominance and over dominance was responsible,
however epistatic interactions effects were also identified. Epistasis with dominance or
partial dominance determine the heterosis in rapeseed (Radoev et al., 2008). Two populations
were used in the study, one with doubled-haploid population and other backcrossed test
hybrid population in green house and field trials for yield performance and seedling biomass.
Simple sequence repeats were the markers used to confine quantitative trait loci (QTL)
30
responsible for expression of yield traits as thousand seed mass, plant height at flowering,
siliquae per unit area, seeds per siliqua and seed yield. Different regions responsible for
heterosis were identified in two populations. The co-localization of two populations indicated
regulatory loci that might contributed fixed heterosis. These QTLs might be responsible for
expression of hybrid genes throughout life cycle of plant (Basunanda et al., 2010).
The genetic basis of heterosis was studied in F2 population of Brassica rapa. Heterosis
was noted of F1 hybrids over mid parent value that differed from 18.55% to 101.62% for the
traits studied. About 23 quantitative trait loci (QTLs) for main effects were estimated for
biomass and other traits and phenotypic variance was noted from 4.38% to 47.80%. These
QTLs showed 65% over dominance. Through epistasis studies 444 two-locus interactions
was significant for the 11 traits. It suggested that genetic basis of heterosis in Brassica rapa
might be due to over dominance and epistasis (Dong and Shi, 2007). To determine the effects
of genomic regions introgressed into spring canola from winter germplasm, quantitative trait
loci (QTL) were genetically mapped for seed yield and other traits. Two different populations
of brassica were used. RFLP markers used to map genetic linkages showed six QTL in test
cross populations for which seed yield was increased by winter alleles. Another QTL which
increased seed yield was coupled with a high glucosinolate QTL which suggest that
conversion of rapeseed into canola could result in the loss of better yield controlling alleles.
Those introgressed QTL alleles that caused low seed yield were related to genomic regions
having homeologous non-reciprocal transpositions. These rearrangements might be
responsible for some heterotic effects in oilseed rapa (Quijada et al., 2006).
2.8 Direct Selection Indices
2.8.1 Types of Gene Action
Gene action is a way in which gene expresses itself in genetic population. Studie on gene
action helps in selection of genotypes for the improvement of crops. With polygene, gene
action is a three types, additive, dominance and interaction (Sleeper and Poehlman, 2006).
These genes affect the expression of quantitative traits. For the selection of quantitative trait,
additive gene action is fruitful in isolating superior genotypes while epistasis and dominance
affects are less effective (Sleeper and Poehlman, 2006). Selection should be practiced in
early segregating generations for the trait controlled by additive gene action and delayed until
the later generations for non additive gene action (Cheema and Sadaqat, 2004).
31
2.8.2 Degree of Dominance
Degree of dominance is the ratio of dominace variance to additive variance. The genetic
analysis of quantitative traits and partition of hereditary variance into additive, dominance
and epistatic was done by Fisher (1918). Further, these components were defined as (1)
Additive genetic variance (2) variance that occurs due to dominance deviation from
additivity (3) Variance from the deviation of additive scheme due to interaction of non-allelic
genes (Wright, 1933). Next partition of epistatic variance into factorial component and higher
order interaction was given by Cockerman (1954) and Kempthorn (1954).
2.8.3 Heritability and Genetic Advance
Prediction for effective selection is more reliable on heritability along with genetic advance
than alone heritability (Johnson et al., 1955) while trait having low genetic advance do not
respond the simple selection only (Pant and Singh, 2011). Heritability is the ratio between the
genotypic and phenotypic variances and is the outcome of genetically inherited properties of
the material and the interaction of the environment in which the experiment is being
performed (Falconer and Mackay, 1996). Genetic advance and heritability are the direct
selection criteria that determine the degree to which trait respond to selection. So for
achieving further improvement, it is necessary to determine the genotypic and environmental
effects for the trait being considered. The basic information as the magnitude, genotypic and
phenotypic pattern, heritability and association of yield contributing traits would be helpful
in species improvement along with the selection of suitable breeding method (Marjanović-
Jeromela et al., 2011).
High heritability along with moderate genetic advance for plant height and days taken
to 50% flowering while high heritability with low genetic advance for days to maturity had
been studied in Brassica rapa (Jahan et al., 2014). High heritability was also studied for days
to 50% flowering in Brown sarson (Dar et al., 2010). However in Brassica juncea low
heritability along with low genetic advance had been reported (Singh et al., 2012). High
genetic advance along with high heritability indicate the additve gene action and selection
would be effective through different selection methods such as pure line selection,mass
selection, hybridization and pedigree selection while low heritability with low genetic
advance leads to the high influence of environment and selection would be ineffective.
Studies showed that flowering time in spring oilseed rape is highly heritable (Laosuwan,
32
1969; Campell and Kondera, 1978; Thurling et al., 1979 and Ali et al., 2003), nevertheless
for rapeseed low heritability estimates were reported for days to first flowering (Rameeh,
2012).Estimation of heritability and genetic advance among the different traits in Brassica
juncea was made. High heritability with high genetic advance percent of mean was noted for
number of silique on main raceme, 1000 seed weight, seed yield per plant and plant height.
The high magnitude of heritability and genetic advance % of mean ravealed that
improvement in these traits could be done through selection (Singh et al., 2012).
Moderate broad sense heritability with low genetic advance as % of mean for days to
first siliqua filling and low to low moderate for 1000-seed weight in winter rapeseed
genotypes was noted. The trait siliqua filling was greatly influenced by the environment and
selection would not be fruitful at early stages (Marjenovic-Jeromela et al., 2011).The
estimates of broad sense heritability and genetic advance were moderate to high for primary
branches and seeds per siliqua and selection would be successful in the early segregating
generations in Brassica juncea (Paul, 1978). Among Brassica inter-specific crosses,
heritability was low (0.30) for 100-seed weight (Nasibullah et al., 2015). Interspecific
hybridization between Brassica juncea and Brassica rapa vars (Toria,yellow sarson and
brown sarson) was made and hybrids were achieved from cross combination of B. juncea×
Toria and B. juncea× yellow sarson. Moderate to high broad-sense heritability, and expected
genetic advance were estimated for seed yield, 1000-seed weight, siliqua per plant, seeds per
siliqua and days to flowering (Choudhary et al., 2002b). Moderate to high heritability
estimates were observed among double haploid populations of Brassica napus and inter-
specific hybrids of other Brassicas (Basuanda et al. 2010; Shahzad and Frahtullah, 2012).
High narrow or broad sense heritabilities along with high genetic advance were recorded for
plant height in Brassica (Larik and Rajput, 2000; Zhang and Zhou, 2006; Aytc and Kinaki,
2009; Dar et al., 2010; Zare and Sharahfzadeh, 2012). When narrow sense heritability is
high, early selection may be practiced for the trait improvement. Broad sense heritability
leads to the environmental factors involvement. Trait accompanied with high value of narrow
sense heritability can be improved through mass selection
B. carinata having high heritability for number of siliqua on main raceme and high
genetic advance for seed yield per plant were observed (Ali et al., 2013). High heritability in
was noted for 50% flowering and 80% flowering days. Maximum genetic advance was noted
33
for number of silique/plant. Maximum genetic advance with low heritability with was
reported for yield (Halder et al., 2015). High heritability was noted in interspecific crosses in
Brassica for majority of the traits. The highest heritability was observed for plant height pods
per main raceme, seed yield per plant and protein content. Moderate heritability was recorded
for oil contents (Nasibullah et al., 2015).
The heritability for agronomic traits of Brassica napus evolved through introgression
of B.campestris and B.oleracea with ovary culture technique. The traits like plant height,
number of branches, number of pods per plant, number of seeds per pod, seed weight per
plant and 1000-seed weight and four quality traits, like erucic acid, glucosinolate, oil and
protein contents, had high heritability (Zhang and Zhou, 2006b). Improvement in rapeseed
yield and quality (0 and 00) can be achieved through selection (Pleines and Friedt, 1988).
The total narrow-sense heritability for erucic acid was 83.6% with the general heritability
being 51.9% and the interaction heritability was 31.7% in Brassica napus (Shi et al., 2003).
Sunflower oil with high linoleic acid is used for food while high oleic acid for non food.
Oleic and linoleic acid contents are highly heritable (h2 = 0.95). Fatty acid composition is
usually severely influenced by environmental factors such as temperature and photoperiod.
High oleic acid content is predominantly inherited by a dominant major gene (Schmidt et al.,
1989). The oileic acid is stable and is not influenced by the environment. Double haploid
population was analyzed and showed high heritability (h2 = 0.99) for oileic acid.DH
population was subdivided into a high (> 64% C18:1) and a low (< 64% C18:1) oleic acid
classes showed high heritability (h2 = 0.94) for oleic acid within both the high and low types
(Schierholt and Becker, 2001).
Genetic analysis of three characters such as percentage of callus induction, callus
diameter and callus fresh weight showed the dominance gene action for the control of these
traits (Etedali et al., 2011). In Brassica oleracea L, plant regeneration from prtoplast depends
upon genotype. To recognize genes for regenerability, genetic analysis of the characteristic
was performed in F2 generation of a cross between two accessions were selected having high
and low regenerability. Broad-sense heritability estimate were higher (0.492) at the early
stage and lower (0.046–0.149) at the advanced stages. Therefore selection for high
regeneration response may be done at early stages because environmental influence is low on
the characteristic and fewer genes are involved at early stage than at advanced stages
34
(Hansen et al., 1999). Brussels sprouts inbreed and F1 hybrids response to another culture
was studied and Narrow sense heritability was 0.48 that indicated partial dominance
(Ockendon and Sutherland, 1987). The inheritance of head splitting in F1, F2 and backcross
progenies of Cabbage.Narrow sense heritability was reported 47% (Chiang, 1972).
Inheritance of microspore embryogenic ability in Brassica napus and Brassica campestris
(pekinensis) was studied. In oilseed rape while in Chinese cabbage additive and dominant
effects were observed respectively. The broad- and narrow-sense heritability was 0.972 and
0.811 in oilseed rape, and 0.959 and 0.659 in Chinese cabbage respectively (Zhang and
Takahata, 2001). Conditional and unconditional models were used to see the effects of
cytoplasmic, nuclear and diploid maternal plant nuclear genes for two quality traits such as
oil and protein, that showed additive effects were more important than dominant effects for
these traits at different developmental stages (Variath et al., 2009).
The nitrogen use effeicincy in Brassica camprestris L. was estimated by using three
nutrient treatments. Results revealed sub- and super-optimal treatments showed maximum
production of ground biomass and flower production (Evans, 1991). Significant variation in
yield, its primary components and several vegetative traits that influence yield were studied
in turnip rape.Results indicated that direct selection for yield components or vegetative traits
both effects the yield (Thurling, 1974a). The double haploid population of Brassica juncea
was developed and its QTL analysis based RFLP markers was done for yield and yield
component .significant and stable were detected for all yield components except seed yield.
Selection efficiency can be increased 4% based on phenotypic and molecular data as
compared expected genetic advance based on phenotypic selection. However; selection
efficiency for higher yield could not be increased by inclusion of molecular and phenotyic
data of yield components because of negative relationships of yield components. Mostly
QTL compensated each other due to pleiotropy or linkage induced relationship among them
(Mahmood et al., 2005).
2.9 In-Direct Selection Indices
2.9.1 Correlation Analysis
Correlation coefficient is a statistical expression that determines the degree of relationship
between the two or more variables.Correlation coefficient in plant breeding describes the
relationship between the different plant parameters and component traits on which selection
35
can be relied on for the genetic improvement of yield. Correlation coefficient between
different traits of oilseed Brassicas has been reviewed.
Some agronomic traits like plant height, number of branches, number of pods per plant,
number of seeds per pod, seed weight per plant and 1000-seed weight were analyzed in F2
populations of synthetic oilseed Brassica napus developed through ovary culture. Number of
pods per plant, number of seeds per pod and 1000-seed weight had positive correlation with
seed yield per plant. Other agronomic characters showed non- significant association with
seed yield per plant (Zhang and Zhou, 2006b). For plant height and seed yield positive
correlation have been recorded in Brassica in various studies by (Tyagi et al., 1996; Thakral
et al., 1998; Oezer et al., 1999; Khan et al., 2006; Aytac and Kinaci, 2009). But some people
reported the negative correlation for these traits in rapeseed (Sadaqat et al., 2003; Zare and
Shrafzadeh, 2012). Plant height showed positive and significant correlation with days to
maturity, number of days to 50% flowering and number of days to flowering iniation (Ghosh
and Gulati, 2000 and Zare, 2011). The plant height had highly significant positive phenotypic
correlation with pods per main raceme and seed yield had significant positive phenotypic
association with number pods per plant and protein content in Brassica napus (Abideen et
al., 2013). Genetic basis of the relationship between timing and magnitude of reproduction in
an annual plant were studied. Brassica campestris, by selecting to change flowering date and
plant size in each of four directions (early and large, late and large, early and small, or late
and small). There is a strong positive relationship between flowering date and flowering
height. The response to selection was greatest along the axis of positive genetic co-variation.
Populations may evolve to become early flowering and small or late flowering and tall, but
there is little response for the alternative combinations of characters (Dorn and Mitchell-
Olds, 1991).The number of primary branches , number of pods on the main raceme and
number of seeds per pod were significantly correlated with to seed yield per plant , while
1000-seed weight was negatively correlated with seed yield in rapeseed. Moreover number of
pods per plant primary, and pods per plant had the greatest direct effects on seed yield. In
addition, pods per plant and number of primary branches were the best traits to determine the
seed yield in stepwise regression analysis (LU et al., 2011). Halder et al. (2015) reported that
phenotypic association of 80% days to maturity and secondary was significant and positive
while siliqua length and 50% flowering showed negative association with yield. Miri (2007)
36
observed positive and significant correlation of days to first flowering with seed yield,
harvest index and number of siliqua per plant. Basalma (2008) reported negative association
between number of days to first flowering and seed yield. Significantly negative correlation
of days to first flowering with number of seed per siliqua and seed weight but days to first
siliqua filling had strong positive correlation with days to first flowering and days to maturity
in rapeseed. Days to maturity had significantly negative correlation with seed weight and
seed yield per plant (Marjenovic-Jeromela et al., 2011). For days to maturity and seed yield
negative correlation had been studied in rapeseed (Zare, 2011; Zare and Shrafzadeh, 2012).
Significant and positive association was noted between number of siliquae per plant and seed
yield in oilseed brassicas (Thurling, 1974; Khan, 2000; Malik et al., 2000; Khan et al., 2006;
Marjanović-Jeromela et al., 2007b; Tuncturk and Ciftci, 2007). A negative association was
also reported between siliqua per plant and seed yield (Marinkovic et al., 2003).
Sadaqat et al. (2003) reported significant and positive correlation between siliquae per
plant and harvest index. Harvest index had positive and significant association with seed
yield and siliquae per plant (Tyagi et al., 1996; Thakral, 1998 and Sadaqat et al., 2003).
Positive correlation have been noted between seed per siliqua and seed yield in Brassica
napus (Thurling, 1974; Zare and Shrafzadeh, 2012) but negative and significant correlation
have been observed between seed per siliqua and seed weight in rapeseed (Basalma, 2008). A
significant and positive correlation was studied only for yellow seed colour and seed oil
content. Seed coat colour and size were controlled by the maternal affects. Plants having
more siliquae had more seed but smaller in size and higher seed oil content. Seed colour and
seed oil content were controlled by two closely linked loci in repulsion phase content in
Brassicas (Bagheri et al., 2013).
2.9.2 Path Analysis
Path analysis is a standardized partial regression that splits the correlation coefficients into
measure of direct and indirect effects.Genetic association in seed and growth characters of
high yielding of Jatropha curcas was studied. The path analysis showed that female to male
flower ratio had highest positive direct effect on seed yield, followed by number of branches
and number of days from fruiting to maturit. Negatively indirect effects were oberved in
number of days from flowering to fruiting and had negative indirect effect on yield via plant
height and number of branches (Rao et al., 2008).Variability and correlation studies for oil
37
and seed yield in Brassica napus revealed sufficient genetic variability. Expression of genetic
variability for oil and seed yield was found to be greatly influenced by the environment. Oil
yield and seed yield were positively and highly significantly correlated. Path analysis
revealed significant positive direct effect of seed yield on oil yield while plant height and
siliqua number had direct positive effect on seed yield (Singh et al., 1991). Zhang et al.
(2006a) noted the positive association of seed yield with main raceme length, siliqua length,
number of siliquae and 1000-seed weight in double haploid populations of Brassica napus.
It was cleared from the path and variance analysis that thickness of seed coat had
positive and significant association with cellulose content while negatively associated with
oil content present in seed coat. Thickness of seed coat in yellow seeded varieties of
Brassica napus had direct effect on oil content present in embryo but vice versa for 1000-
seed weight. Condition in brown seeded varieties was totally opposite (Tang et al., 1997).
Path and correlation analysis revealed that yield and yield components were positively
correlated for days to flowering, plant height, number of branches, number of siliquae/ plant,
number of seeds/silique. Oil and protein content had negative association. Path analysis
showed that 100 seed weight had maximum direct effect on yield followed by number of
siliqua/plant (Oezer et al., 1999).
Quantitative trait loci (QTLs) based on genetic mapping for the yield related traits help
for the development of high-yielding cultivars. A genetic linkage map of B. napus using
different types of marker was constructed in an F2 population. In total, 133 QTLs were
identified. Eight of 10 QTLs for yield per plant (YP) were also associated of seeds per
siliqua, number of siliques per plant , and 1000-seed weight(Traw, 2002; Li et al., 2007 ).
Quantitative trait loci (QTL) control the yield-related traits such as Silique length and
seed weight in oilseed rape (Brassica napus L. QTL analyses was conducted ten and nine
non-redundant QTL were identified both for siliquae length and seed weight respectively.
The major QTLs cqSLA9 and cqSWA9showed 53.4% variation for siliqua across
environments. The major QTL cqSWA9 exhibited 28.2% of the total seed weight variation in
the SS09 and SS10 environments. The others are minor QTL and individually explained less
than 10% of the SL variation. Interestingly both major QTLs were localized in the same
chromosomal region and integrated into a unique QTL, uqA9. The presence and effect of
uqA9 was also confirmed. The results revealed that siliqua length in the S1 mutant is mainly
38
controlled by the cqSLA9 locus, which can be used for fine mapping and marker-assisted
breeding for high yield in rapeseed (Yang et al., 2012). Lionneton et al. (2004) observed that
colour of seed coat effects the oil and fatth acid contents. Colour of seed coat was correlated
with two mendalian trait loci Bjc1 and Bjc2 present on linkage group 3 and 6 respectively.
QTL correlated with the characters studied by composite inter mapping were not co-localized
and showed genetic independence, it means that quantitative and qualitative traits could be
improved independently in brown mustard.
Genetic diversity and heterotic gene pool can be produced through re synthesis of
Brassica napus L (Resyn). The potential of wild lines as a parent can be evaluated for Resyn
lines. Resyn lines with wild species exhibited more genetic diversity than domesticated
Resyn lines. The hybrid yield had slightly negative (r = −0.29) correlation with genetic
distance. wild B. oleracea hybrids gave lower yield as compared to hybrids with
domesticated Resyn lines (Jesske et al., 2013). However genetic distance was estimated
among canola cultivars through multivariate analysis. The positive association between
heterosis and genetic distance was significant for seed yield, number of pods per plant and
number of seeds per pod (Ali et al., 1995).
Inherit variation and genetic relationship among Indian and exotic genotypes Indian
mustard using RAPD assays was studied; 595 amplification products were detected and five
hundred of them showed polymorphism among all genotypes .Indian genotypes were less
variable as compared to exotic variable. Genotypes were divided into two groups A and B,
for exotic and Indian respectively. There was high a percentage of heterosis when crosses
were made between Indian and exotic genotypes while 80% negative heterosis between
Indian genotypes. This indicated lack of direct correlation between genetic distance and
heterosis, genetic diversity provides guidance for parent selection for heterotic hybrids
combinations (Ain et al., 1994). A significant and positive correlation was studied only for
yellow seed colour and seed oil content. Seed coat colour and size were controlled by the
maternal affects. Plants having more siliqua had more seed but smaller in size and higher
seed oil content. Seed colour and seed oil content were controlled by two closely linked loci
in repulsion phase. Therefore selection on yellow colour basis may not always be fruitful
when breeding is for high seed oil content in Brassicas (Bagheri et al., 2013).
39
Improvement in oil and protein quality is mandatory in rapeseed. Rapeseed contains
phytosterols that enriches food items, and sinapate esters, which limits the consumption of
rapeseed proteins in food industry. Increase in phytosterol content of oil and decrease in
sinapate ester content of meal can enhance the importance of rapeseed.Negative correlation
was observed between erucic acid and phytosterol content. For total phytosterol content,
three QTL were detected that showed 60% of the genetic variance. For sinapate ester content
four QTL were identified showing 53% of the genetic variance. Again, a close negative
correlation was observed between erucic acid and sinapate ester content. The results
indicated a pleiotropic effect of the two erucic acid genes on phytosterol and sinapate ester
content while the effect of the alleles for low erucic acid content is to increase phytosterol
and sinapate ester content (Amar et al., 2008).
The correlation studies in Brassica napus L showed that oleic acid content had
significant negative phenotypic correlation with oil and erucic acid content (Abideen et al.,
2013). Molecular marker RM322 was identified associated significantly with erucic acid and
oil content (Rajcan et al., 1999). Correlation studies in winter hardy rapeseed germplasm
showed, the correlation between oil and glucosinolate contents was significantly negative in
B.napus and significantly positive in B. rapa (Bhardwaj and Hamama, 2000). Genetic
correlation studies for various traits of Vernonia galamensis showed that seed yield per plant
had significant and positive correlation with seed weight and head numbers, negative but
highly significant correlation were observed between vernolic acid, palmitic, stearic, oleic,
and linoleic acid respectively. Positive and highly significant correlations were found
between seed and oil yield respectively. Path-coefficient analysis showed that seed weight
and secondary head number were the most important parameters for seed yield per plant.
Positive and direct effect was noted for Vernolic acid, oleic acid and linoleic acid but stearic
acid had negative direct effect on oil content. The direct positive effect of oleic acid on oil
content was, however, compensated by the negative indirect effects of stearic and vernolic
acid resulting in a negative correlation between oleic acid and oil content (Baye and Becker,
2005). Plant naturally has different defence mechanism against the invader.These have
secondary metabolites having various structures and their effect on the herbivours. B.
oleracea have aliphatic glucosinolates that is converted into toxin when leaf tissue is
damaged. Considerable association was found among herbivours infestation rate and
40
production of two types of glucosinolates (sinigrin and progoitrin) and there was
differentiation in the behaviour of species around the year (Newton et al., 2009).
Black mustard has great variation in both constitutive resistance and induction response
after the damage by herbivores. Positive genetic correlations were present between gluco
brassicin concentration and days to flowering iniation, suggesting a genetic cost of resistance.
Induction responses had negative correlation with constitutive allocation for leaf trichome
density and sinigrin concentration (Traw, 2002). Planting date effect the grain yield, yield
components and grain quality of B. campestris and B. napus. B. campestris, yield depends
on plant population and seed weight. In B. napus the number of pods per plant and the
number of seeds per pod effect the yield. The oil content was maximum in early plantings,
reduced in later plantings, and was inversely related to protein content. The oil content was
also inversely related to mean daily temperature during the grain-filling period (Hodgson,
1979). The effect of temperature and photoperiod on grain yield of two sorts of Sinapis alba,
Brassica juncea and Brassica nigra was investigated. The grain yield was significantly
influenced by increase in temperature at different levels and shortening the photoperiod in
warm climate also affected negatively. The fat content had positive correlation with yield and
negative correlation with raw protein and tochopherols. Erucic acid was positively correlated
with photoperiod shortening. The glucosinolate contents were in close positive correlation to
the protein contents (Marquard, 1983).
Improvement for yield of Brassica napus and Brassica campestris in drought condition
the selection should be performed in stressed environment instead the direct selection for
drought index because there was high heritability in stressed environment and positive
correlation with yield (Richards, 1978). Genetic study of physiological and morphological
traits was investigated in Brassica rapa under drought and control conditions. Total 54
quantitative trait loci (QTL) were investigated which were present in 11 QTL clusters.
Significant QTL–environment interaction (Q×E) was shown by seventeen QTL that
expresses the genetic variation for phenotypic flexibility. Correlation analysis revealed that
stomatal conductance had positive correlation with total leaf dry weight and above ground in
the control environment and had negative correlation under drought condition. This
correlation was explained by antagonistic fitness effects in the drought environment,
controlled by a QTL cluster on chromosome A7. It indicates that Q×E is important for
41
genetic variation and can be used for improvement of drought tolerance traits (El-Soda et al.,
2014).Correlation studies between yield components of canola and response to various
combinations of pre plant and side dress nitrogen with soil-applied sulfur and soil and foliar-
applied boron were conducted.
Canola yield and all its yield components were strongly correlated with the amount of
N applied, as was the above-ground biomass at 20% flowering and the leaf area index (Ma et
al., 2015). The characteristics of nitrogen accumulation, partition into different types and
mechanism of nitrogen use efficiency for seed production was studied that had significant
correlation with total number of seeds (Zuo et al., 2011). Grain yield can be increased by
increasing the biomass production and harvest index can be used as tool for the interpreting
of crop response to different environment and the climatic change (Hay, 1995).
43
3 CHAPTER 3 MATERIALS AND METHODS
The experiments related with research were conducted in the experimental area of the
department of university of Agriculture Faisalabad during 2014-2016. Geographically
Faisalabad lies 31-26 the latitude and 73-06 E longitude (Govt. of Pakistan, 2003).
Faisalabad climate is of semi arid type. The annual average rainfall in Faisalabad is 370 mm.
Local and exotic germplasm lines were crossed in the field to obtain hybrids/crosses in a
line×tester fashion. Lines and testers as parents and their crosses along with the standard
were sown in the field, following Randomized Complete Block Design (RCBD) with three
replications.
3.1 Year-wise work plan
The following activity plan was observed to achieve the objectives.
Year Activities
1. Collection of seeds of local and exotic germplasm and its multiplication. It was included
specifically high, low and zero erucic acid breeding material.
2. Sowing of crossing block in the field and crossing through hand pollinations. It was achieved
by covering the whole plant with musceline cloth to control pollinations. Collection of seeds
from the crosses and selfed plants.
3. Sowing of part of the above harvested seeds in the field as well as in the pots for generation
turnover. Fresh crosses were also made to increase the seed of crosses at both intra- and
inter-specific levels.
4. Sowing of parent material, crosses and standards in the field for comparative study of each
material to understand the genetic basis of variation in the material.
3.2 Experimental Genetic Material
The detail of experimental material used for intra specific hybridization is as under.
44
Table 3.1 Intra specific hybridization of Brassica campestris
The detail of experimental material used for inert- specific hybridization is as under
Table 3.2 Inter specific hybridization of B. campestris with its relatives
1 Toria Old variety of Oilseeds research institute Faisalabad
2 UAF11 High yielding line from the department of Plant Breeding and Genetics.
University of Agriculture, Faisalabad.
3 1072 High yielding line from Pakistan germplasm resource institute.
4 Napus-1 University of Agriculture, Faisalabad.
5 Napus-2 University of Agriculture, Faisalabad
6 Juncea-1 University of Agriculture, Faisalabad
S.NO. Name of
Genotypes
Source/description
1 Toria Old variety of Oilseed Research Institute, Faisalabad.
2 UAF11
Trilocularis elite line of Plant Breeding and Genetics department. UAF.
3 UAF12 Trilocularis elite line of Plant Breeding and Genetics department. UAF.
4 Candle Canada
5 Torch Canada
6 Tobin Canada
7 Span Canada
8 TR8 Canada.
9 Quinyan15 Canada
10 1072 PGRI Islamabad, Pakistan.
45
3.3 Hybridization Plan
3.3.1 Intraspecific Hybridization
Hybridization for the present studies was done at two levels i.e., intraspecific as well as
interspecific. For intra-specific hybridization, ten varieties/lines of B. campestris having local
and foreign origin were sown in the field as crossing block and crossed in line×tester fashion
fallowing Kempthorne (1957). Lines/varieties, UAF-11, UAF-12, Span, Quinyou15, TR-8
and Toria were used as lines whereas Candle, Torch and Tobin were used as testers.
3.3.2 Inter-Specific Hybridization
The inter-specific hybridization to achieve introgressions was carried out using UAF-11 and
UAF-12 of B. campestris as females and at least two types of each B. napus and B. juncea as
males. Part of seeds of hybrids at intra as well as interspecific levels was sown in the field for
generation turnover and to perform crosses afresh to increase the seeds of crosses. All the
breeding material so produced at intraspecific level, Parent lines, F1 hybrids, F2 segregating
generation, and standard hybrids/varieties being commercially grown in the area were sown
in the field in a randomized complete block design with three replications. Similarly, the
breeding material at interspecific level was sown in the field separately in the field in a
randomized complete block design with three replications. Sowing was done with the help of
wooden dibbler using 4-5 seeds per hill, maintaining plant to plant distance of 15cm and row
to row distance of 45cm. Only one plant was kept per hole after having repeated thinning.
Recommended dose of fertilizer, plant protection measures and number of irrigations
were applied. Ten plants were tagged in each entry in each replication and the data was
recorded on morphological, phenological, seed yield and oil quality related traits on these
individually tagged plants for data recording.
Data were recorded for various plant traits following the procedures given below.
3.4 Measurement Methods
3.4.1.1 Mrophological Traits
3.4.1.2 Plant Height (cm)
Plant height was measured in cm for already tagged plants at maturity with the help of meter
rod from ground level to the tip of the plant including the inflorescence.
46
3.4.1.3 Number of Primary Branches per Plant
Primary branches were counted for the plant arising from the main stem at the time of
maturity.
3.4.1.4 Number of Secondary Branches per Plant
Secondary branches were counted, having the origin from primary branches of tagged plants
at maturity.
3.4.1.5 Green Biomass per Plant (g)
Green biomass of plant was measured when plant was at maturity. The whole plant was
uprooted and it was weighed in gram
3.4.1.6 Harvest Index
Harvest index is the ratio of seed yield per plant and dry stem straw per plant that was
calculated from the fallowing mathematical relationship.
Harvest index=Seed yield/Dry straw.
3.4.2 Phenological Traist
3.4.2.1 Days to Flowering Initiation
Days of flowering initiation were counted from date of sowing to the first flower of opening
of the selected plant. The data recorded of all selected plants was averaged to compute the
mean number the flower initiation.
3.4.2.2 Number of Days to 50% Flowering
Days were counted from first day of sowing to about 50% days of flowering was completed.
The data was averaged to calculate for the calculation of number of 50% days to flowering.
3.4.2.3 Number of Days to 50% Siliqua Formation
Days were counted from first date of sowing to first day of sliqua formation to 50%
days of siliqua formation. The value was averaged from all tagged plants.
3.4.2.4 Number of Days to Maturity
Days to maturity were counted from first day of sowing to when plant turned to yellow .The
data was averaged of all selected plants.
3.4.3 Seed Yield Components
3.4.3.1 Number of Siliqua per Plant
Number of siliqua per plant of already selected
47
3.4.3.2 Number of Seeds per Siliqua
Ten siliqua per plant at the time of maturity were collected and threshed manually from
tagged plants to recover the seed. Number of seeds was counted from all plants and their
mean value was computed
3.4.3.3 100-Seeds Weight
Three samples of 100-seeds randomly were selected and weighed with electronic balance
and averaged for each replication.
3.4.3.4 Seed Yield per Plant (g)
The whole quantity of harvested seed from tagged plants was weighed with electronic
balance and averaged as seed yield per plant for each replication.
3.4.4 Quality Related Traits
3.4.4.1 Seed Oil Contents (%)
3.4.4.2 Seedcake Protein Contents (%)
3.4.4.3 Seedcake Glucosinolate Contents (%)
3.4.4.4 Oleic Acid Contents (%)
3.4.4.5 Erucic Acid Contents (%)
All these quality related traits were measured adapting the following procedure
The oil and protein, the glucosinolate contents (%) and fatty acid profile were determined
using a Foss NIRS Systems 6500 near-infrared reflectance spectroscopy (Foss NIRS Systems
Inc.). The samples were scanned on a mono chromator that was equipped with sample auto
changer. The standard ring cup, that requires a seed volume of about 5g, was used. The
reflectance spectrum (log I/R) from 400 to 2500 nm was recorded at 2-nm intervals for each
sample. Calibration and validation procedures were carried out with ISI software, version Ia.I
(Infra soft international) as described by Anonymous (1998).
3.5 Biometrical Approaches
3.5.1 Analysis of Variance of RBD
Data regarding the above stated traits was statistically analyzed for genetic variability (Steel
et al., 1997).
48
Source Df SS MS F
Replication (r-1) RSS RMS
Genotype (g-1) GSS GMS
Error (r-1) (g-1) ESS EMS
Total (rg-1) TSS
3.5.2 Mean comparisons
For the comparisons of means least significant difference (LSD) test was used
3.5.3 Line×Tester Analysis of Variance
The degree of freedom from different sources of variation for combining ability analysis
along parents and without parents in the experiment are given below
Where: r = number of replications, t = Number of treatments, p =Number of parents,
m = Number of males parents (Testers), f = Number of female parents (Lines)
Table 3.3 Analysis of Variance format used for line×tester analysis
Source Degree of freedom Mean sum of squares
Replications r-1
Treatments t-1
Parents p-1
Crosses mf-2
Lines (Females0 f-1 M1
Testers (Males) m-1 M2
Line × Testers (f-1)(m-1) M3
Error (t-1)(r-1) M4
Total tr-1
49
3.5.4 Combining Ability Analysis
The genetic components of variance were assessed through the estimates of combining
ability using the formula given by Kempthorne (1957). Since the expected mean sum of
squares were not available for the modified line x tester analysis, the mean of each
replication for the eleven characters recorded for the hybrids alone were subjected to analysis
and the fresh mean sum of squares, along with the variance of general combining ability
(GCA) of the parents and specific combining ability (SCA) of the hybrids were worked out
based on the procedure developed by Kampthorne (1957).
Where: r = Number of replications, m = Number of male parents (testers), f = Number
of female parents (lines), COV (FS) = Covariance of full sibs, COV (HS) = Covariance
of half sibs
To calculate the mean sum of squares the following estimates were worked out.
𝐶𝑜𝑣 (𝐻𝑆) =(𝑀1 − 𝑀3) + (𝑀2 − 𝑀3)
2𝑟(𝑚 + 𝑓)
Table 3.4 Analysis of Variance for Combining Ability
Source Df MSS Expected Mean Sum of Squares
Replications r-1
Crosses mf-1
Lines f-1 M1 σ2+ r COV (FS)-2COV(HS) + rm COV (HS)
Testers m-1 M2 σ2 + r COV (FS)-2 COV (HS) + rm COV (HS)
Line × Tester (m-1)(f-1) M3 σ2+ r COV (FS)-2 COV (HS) + rm COV (HS)
Error (r-1)(mf-1) M4 σ2 + r COV (FS)-2 COV (HS) + rm COV (HS)
Total mfr-1
50
𝐶𝑜𝑣 (𝐹𝑆) =(𝑀1 − 𝑀4) + (𝑀2 − 𝑀4) + (𝑀3 − 𝑀4)
3𝑟
+6𝑟𝐶𝑜𝑣 (𝐻𝑆) − 𝑟(𝑓 + 𝑚)𝐶𝑜𝑣 (𝐻𝑆)
3𝑟
Variance due to GCA = COV (HS)
Variance due to SCA = COV (FS) – 2COV (HS)
GCA varience for lines = 𝑀1 − 𝑀3
𝑟𝑚
GCA varience for Testers =𝑀2 − 𝑀3
𝑟𝑓
SCA varience for Hybrids =𝑀3 − 𝑀4
𝑟
Where,
M1 = Mean sum of squares due to lines
M2 = Mean sum of squares due to tester
M3 = Mean sum of squares due to line x tester
M4 = Mean sum of squares due to error
The model used to estimate GCA and SCA effects of ijk observations was
Xij = μ + gi + gj+ sij + eijk,
Where,
μ = Population mean
gi = GCA effect of ith line
gj = GCA effect of jth tester
sij = SCA effect of ijth combination
I = Number of female parents
J = Number of male parents
k = Number of replications
e = Error
The individual effects were calculated as
A.
Lines: gi =Xi
mr−
X …
mrf
51
Where,
Xi = total of ith line over all male parents and replications
B.
Testers: si =Xj
fr−
X …
mrf
Where,
Xj = total of jth tester over all female parents and replications
C.
Specific Combining Ability Effects
SCA: 𝑆𝑖𝑗 =𝑋𝑖𝑗
𝑟−
𝑋𝑖. .
𝑚𝑟−
𝑋𝑗. .
𝑓𝑟+
𝑥 …
𝑚𝑓𝑟
Where,
Xij = ijth combination totaled over all the replications
The standard errors (SE) and critical differences (CD) pertaining to the GCA effects of
male and female parents and SCA effects of different combinations were calculated as
follows.
𝑆𝐸 𝑜𝑓 𝐺𝐶𝐴 𝑓𝑜𝑟 𝑓𝑒𝑚𝑎𝑙𝑒𝑠 = √𝑀4
𝑚𝑟
𝑆𝐸 𝑜𝑓 𝐺𝐶𝐴 𝑓𝑜𝑟 𝑚𝑎𝑙𝑒𝑠 = √𝑀4
𝑓𝑟
𝑆𝐸 𝑜𝑓 𝑆𝐶𝐴 𝑓𝑜𝑟 𝑐𝑟𝑜𝑠𝑠𝑒𝑠 = √𝑀4
𝑟
Proportional contribution of lines, testers and their interaction
Contribution of Lines =𝑆𝑆 (𝑙)
𝑆𝑆 (𝐶)× 100
Contribution of testers =𝑆𝑆 (𝑡)
𝑆𝑆 (𝐶)× 100
Contribution of Line × testers =𝑆𝑆 (𝑙 × 𝑡)
𝑆𝑆 (𝐶)× 100
52
Where,
SS (l) = Sum of squares due to lines
SS (t) = Sum of squares due to testers
SS (l × t) = Sum of squares due to lines x testers
SS (C) = Sum of squares due to crosses
3.5.5 Estimation of Heterosis
Heterosis percentage over the mid parent (MP) and better parent (BP) was estimated
according to Falconer and Mackay (1996). An inbreeding depression was also calculated
according to Haldane (1948).
Heterosis for trait was estimated by using the following formula.
𝑃𝑒𝑟𝑐𝑒𝑛𝑡 𝐻𝑒𝑡𝑒𝑟𝑜𝑠𝑖𝑠 𝑂𝑣𝑒𝑟 𝑀𝑖𝑑 𝑃𝑎𝑟𝑒𝑛𝑡 (𝑀𝑃) =𝐹1 − 𝑀𝑃
𝑀𝑃× 100
Where
Mid Parent =𝑃1 + 𝑃2
2
Percent Heterosis Over better Parent (BP) =𝐹1 − 𝐵𝑃
𝐵𝑃× 100
Where
For better parent value (BP) for each character, superior value between the parents in
each cross was taken.
3.5.6 Estimation of Inbreeding Depression
Inbreeding depression values were measured using F1 and F2 means with the fallowing
formula
Percent of inbreeding depression (ID) = �̅�𝟏−�̅�𝟐
�̅�𝟏 ×100
Test of ID= Estimated value of ID
Estimated error of mean
Where, Standard error of mean =√VF̅1 + VF̅2
53
VF̅1=variance of F1 mean,
VF̅2=variance of F2means
Standard Error of Estimates
The standard error (SE) for estimates of heterosis, mean squares due to error (M4) from
RBD analysis was computed as given by Singh and Chaudhury (1977).
𝑆𝐸 (𝑀𝑃) = √3 × 𝑀4
2𝑟, For testing heterosis over mid parent
𝑆𝐸 (𝐵𝑃) = √2 × 𝑀4
𝑟, For testing heterosis over better parent
Significance of Mid parent and better parent heterosis was determined following the t
test suggested by Wynne et al. (1970).
MP (t) =F1 − MP
√3EMS2r
𝐵𝑃 (𝑡) =𝐹1 − 𝐵𝑃
√2𝐸𝑀𝑆𝑟
3.5.7 Estimation of Heritability
Broad sense heritability was computed according to Weber and Mort hay (1952)
3.5.8 Genetic Advance
Genetic advance was calculated at 20% selection intensity (i=1.4) according to formula
(Phoelman and Seleper, 1955).
An arbitrary scale for heritability and range of genetics advance as suggested by Johnson et
al. (1955) with formula for genetics advance has been given to make the differences among
the groups of traits.
54
Scale for Heritability
Low : Less than 30%
Moderate : From 30-60%
High : More than 60%
Scale for Genetics advance
Low : Less than 10%
Moderate : From10-20%
High : More than 20%
GA=iαh2
i=Selection intensity
α p =Standard error of phenotypic variance
h2=Coefficient of heritability.
3.5.9 Correlation Analysis
Genetic correlations were estimated for all combinations considering morphological,
phenological and quality traits following Kwon and Torrie (1964).
3.5.10 Path Analysis
Path coefficient analysis were performed following Dewey and Lu (1959) using the R
program.
55
4 CHAPTER RESULTS AND DISSCUSSION
4.1 Intraspecific Genetic Variability
The individuals have similar genes within a species but they are different with respect to
phenotypic characteristics and behavior due to minor differences in genotypes and their
interaction to the environment. This was reported for the first time by” Charles Darwin and
Alfred Wallace’’ in their paper ‘‘On the Tendency of Species to form Varieties and on the
Perpetuation of Varieties and Species by Natural Means’’ read in the Linnean Society in
London on 1st July 1858 (Harrison and Regional, 2001).
The knowledge of variability, its extent and type of relationship of quantitative
characters in oilseed brassicas is necessary for a resourceful breeding program. The use of
quantitative genetic variability plays an important role to evolve higher yielding varities and
improvement in traits of economic importance (Mahmood et al., 2003).Variation among the
characters such as phenological, morphological, yield related and quality contributing traits
are very important because they help in the development of genotypes adopted to a particular
environment and agro-climatic regions (Fick, 1978).
Local and exotic germplasm lines were crossed to obtain the ultimate goal of high
yielding and good quality lines. The data recorded for different parameters were analyzed
statistically for variance and the results in the form of mean square values (Table 4.1).Highly
significant (α ≥ 0.01) differences were noted for all the traits (Morphological, phenological,
yield and quality related traits) studied.Substantial variability noted among the genotypes,
used in the present studies for above mentioned traits were similar with findings like Gosh
and Gulati (2001); Ali et al. (2003); Sadaqat et al. (2003); Fahratullah et al. (2004); Aytac
and Kinaci (2009); Dar et al. (2010); Sabaghnia et al. (2010); Marjenovic -Jeromela et al.
(2011); Singh et al. (2012) and Arifullah et al. (2013).
The sum of squares were partition into those of parents, crosses and parent vs. crosses
which showed highly significant variation among them for most of the traits,except for
56
primary branches and seed per siliqua parent vs. crosses showed non-significant differences
for them.
The sum of square values for crosses was further divided into line, testers, line×tester
and line vs. tester. Maximum variation was present among lines and testers, for these traits.
However lines vs.tester’s difference was non-significant for values days to flowering
initiation, days to 50% flowering initiation and primary branches. Zare and Sharahfzadeh
(2012); Abideen et al. (2013); Ali et al. (2003); Dar et al. (2013); Singh et al. (2014) and
Parveen et al. ( 2015) also reported non-significant variability for days to 50% flowering
initiation, primary branches per plant and seeds per siliquae.
Expression affected by the environment was also observed. Evaluation of genetic
variability for economic important traits in rapeseed and mustard is a fundamental objective
in breeding, therefore characters of economically important such as plant height, secondary
branches, harvest index and green biomass were studied and significant differences were
noted for all sources of variation (Table 4.2). Variation for these traits in rapeseed and
mustard was also examined;significant and non-significant differences were observed by
Huehn (1993); Ali et al. (2003); Sadaqat et al. (2003); Farhatullah et al. (2004); Cui and Yu
(2005); Sincik et al. (2007); Dar et al. (2010); Synrem et al. (2014); Iqbal et al. (2014) and
Mekonen et al. (2015).
Yield and yield related parameters showed significant mean square values. Yield is the
most important trait for any outcome in term of breeding material. The improvement in yield
related traits indirectly is the improvement in yield. Seed yield is a complex of population
density, number of siliquae, seeds per siliqua and seed weight (Dipenbrock, 2000). Highly
significant variability in oilseed brassicas for yield and yield related traits was observed by
Kang et al. ( 2013); Nasim et al. (2014); Ullah et al. ( 2015); Naznin et al. (1015); Halder et
al. (2015)
57
Table 4.1 Mean Square Values Associated with Different Plant Traits of B. campestris
Source of Variation Replications Genotypes Error
Degree of freedom 2 30 60
Ph
en
olo
gica
l traits
Days to flowering initiation 11.36 36.12** 2.92
Days to 50% flowering 5.83 29.85** 5.21
Days to 50% siliqua formation 2.78 30.16** 1.51
Days to maturity 14.91 26.9* 2.04
Plant height 45.2 2262.17** 16.77
Mo
rp
holo
gica
l
traits
Primary branches 0.9 15.33* 1.81
Secondary Branches 0.72 87.24** 1.52
Green Biomass 20.2 1787.73** 7.78
Harvest index 4.57 1115.77** 6.01
Yie
ld re
late
d tra
its
Number of siliqua per plant 0.46 44.96** 1.59
Number of seed per siliqua 4.1 12343.4** 43.7
1000 seed weight 15.12 20.23* 10.43
Seed yield per plant 1.32 423.2** 0.45
Qu
ality
rela
ted
traits
Oil contents (%) 0.039 37.981** 0.695
Protein contents (%)
0.504 15.961** 1.902
Glucosinolates (%) 5.11 1915** 5.93
Oleic acid (%) 47.26 511.02** 20.8
Erucic acid (%) 5.58 521.88** 3.82
58
*=significant (p<0.05);**=highly significant (p<0.01
DFI stands for days to flowering initiation, D50%F for days to 50%flowering, D50%SF for days 50% siliqua formation, DM for days to maturity, PH for
plant height, PB for primary branches, SB for secondary branches, GB for green biomass yield, HI for harvest index, S/PL for siliquae per plant, S/S for seed
per siliqua, TSW for 100 seed weight, Y/P for yield per plant
Table 4.2 Mean square values from analysis of variance of lines, testers and their used in crossing of Brassica campestris
Phenological Traits Morphological traits Yield related traits
Source of
Variation DF DFI D 50% F D 50% SF DM PH PB SB GB HI SL/p S/S TSW Y/P
Replications 2 11.37** 5.84 2.78 14.91** 45.20 0.40 0.46 20.20 4.57 4.08 0.23 0.0003 1.32
Genotypes 30 36.12** 29.85** 30.16** 26.91** 2262.17** 18.41** 88.49** 1787.73** 1115.77** 12343.39** 45.14** 0.0072** 423.20**
Parents 9 11.22** 23.78** 26.08** 41.74** 3034.83** 22.91** 97.19** 2195.85** 975.82** 6971.41** 138.70** 0.0138** 460.79**
Crosses 20 47.54** 31.08** 31.33** 20.22** 1977.48** 17.22** 75.65** 1482.85** 1208.54** 15036.24** 5.30** 0.0042** 427.31**
P VS C 1 31.88** 60.06** 43.62** 27.21** 1002.14** 1.75 266.88** 4212.23** 519.86** 6834.19** 0.09 0.0071** 2.66**
Lines 6 75.59** 61.18** 68.77** 16.03** 2300.93** 13.98** 39.51** 619.07** 810.14** 17301.13** 5.95** 0.0034** 140.06**
Testers 2 17.48** 26.62** 32.59** 41.33** 1162.59** 8.78** 75.76** 140.11** 482.00** 2695.29** 2.78** 0.0016** 122.00**
L × T 12 38.53** 16.77** 12.40** 18.80** 1951.57** 20.24** 93.71** 2138.54** 1528.83** 15960.62** 5.39** 0.0051** 621.82**
L VS T 1 0.08 1.53 19.56** 2.93** 5131.43** 0.99 98.41** 7543.49** 2383.46** 414.48** 284.01** 0.0305** 277.84**
Error 60 2.92 5.21 1.51 2.05 16.77 0.74 0.84 7.78 6.01 43.72 0.99 0.0001 0.45
59
4.2 Mean Comparisons for Various Plant Traits of 21 Intra-specific Crosses of B.
campestris
4.2.1 Phenological Traits
The average performance of 21 hybrids of B. campestris for eighteen traits used in line×tester
analysis (Table 4.3) Number of days to flower initiation were ranged from 58 (UAF11×Torch) to
74 (1072×Torch). Seven hybrids were early maturing as they got less than 69 days for flowering
initiation. The number of days to 50% flowering initiation were varied from 73 to 85.The
number of days for 50% siliquae formation were ranged from 79 (Span×Candle) to
(Q15×Tobin). The number of days to maturity were varied from 105 (Span×Tobin) to 97
(Q15×Tobin). Out of 21 hybrids 11 hybrids were below in average for days to maturity (101).
Number of days taken to flowering initiation, 50% flowering, 50% siliquae formation and
maturity are all crucial events in a plant life cycle that ensures its optimal reproduction.
Flowering is one of important stages in rapeseed where it affects the yield in large quantity (Faraj
et al., 2008). Siliquae formation, number of grains and seed yield are strongly affected by
flowering initiation (Downey and Rimer, 1993; Diepenbrock, 2000; Yasari and Patwardhan,
2006). Oilseed brassicas showed significant and highly significant variation for number of days
to flowering reported by earlier researcher. The reported range for flowering periods remained
from 21 to 222 days (Ali et al., 2003; Iqbal et al., 2003; Cheema and Sadaqat, 2004, Sabaghnia et
al., 2010; Rameeh, 2012; Zada et al., 2013 and Singh et al., 2014). Studies on growing of oats
fodder as an intercrop indicated significant influence on the growth of B. napus but phenology of
crop was not affected. The range for number of days for 50% flowering was from 63.8 to 102
days while for 50% siliqua formation was from 74.5 to 109.8 days. The maturity days were from
144 to 157 (Singh and Singh, 2014).
4.2.2 Morphological Traits
Maximum plant height was 202 cm for cross (UAF11×Tobin) and minimum was 118 cm for
cross (Toria×Torch).Variation for number of primary ranged from three (Tr8×Candle) to
eleven (UAF11×Torch).Tewelve hybrids had more number of secondary branches than
average.For green biomass 12 hybrids had more quantity than that of average quantity of green
biomass. The average harvest index (%) was (30.38).The range for harvest index varied from
6.05 (UAF11×Candle) to 71 (1072×Tobin).
60
Plant height (cm), number of primary branches/plant, number of secondary
branches/plant, green biomass/plant and harvest index for genetic variability have been studied
by different researchers, significant and non-significant differences were noted for these
morphological traits. Nasibullah et al. (2015) and Mekonnen et al. (2015) found difference
significantly in Brassica for plant height, primary branches/plant, and secondary
branches/plant, biomass/plant and harvest index. The range of variability of height in spring
rapeseed had been reported from 69.5 to 180 cm (Ali et al., 2003; Sadaqat et al., 2003;
Fahratullah et al., 2004; Sincik et al., 2007; Dar et al., 2010; Sabaghni et al., 2010; Zareand
Sharafzadeh, 2012; Synrem et al., 2014 and Iqbal et al., 2014). Shehzad and Fahratullah (2012)
also reported significant differences in interspecific crosses of genus Brassica for plant height.
4.2.3 Yield Related Traits
For number of siliquae per plant, eight hybrids got maximum number of siliquae 563
(1072×Torch) and minimum 218 (Toria× Torch).A good degree of variation was noted for
number of seed per plant. The range of variation was from 10.67(Toria× Torch) to 16
(UAF11×Tobin).Thousand seed weight expressed good variation. The range maximum range
was .26 gm (Span×Tobin) and minimum was .12gm (Span×Candle). For yield nine hybrids
showed the value above from the average value. The range for these values from 2.75 gm per
plant (1072×Candle) to 48.72 gm (Span×Tobin)
Number of siliquae and seeds/siliqua,100-seeds weight and seed yield per plant are major
yield contributing trait.Oilseed brassicas have significant and highly significant variation for seed
yield and yield related traits such as number of silique/plant, number of seeds/siliqua, 1000-seed
weight and yield/plant (Ghosh and Gulati, 2001; Ali et al., 2003; Fahratullah et al., 2004;
Rahman et al., 2009; Dar et al., 2010; Abiden et al., 2013; Ddin et al., 2013; Kang et al., 2013
and Nasim et al., 2014).
4.2.4 Quality Related Traits
B. campestris hybrids showed good variation for oil contents and ranged from 32 (Q15×Tobin)
to 47(%) (UAF11×Tobin).For protein the contents ranged from 22.4 (Toria× Tobin) to 31 (%)
(UAF11×Tobin).Variation for glucosinolates was from 11 (Q15×Torch) to 96.57
(UAF11×Tobin). Oleic acid (%) exhibited lot of variation and its range was from 23
(Q15×Torch) to 71.87 (1072×Torch).
61
Table 4.3 Mean comparisons of different associated plant traits of B.campestris
Hybrids
Phenological traits Morphological traits Yield related traits
DFI
D 50%
F
D 50%
SF DM PH PB SB GB HI SL/p S/S TSW Y/P
Toria×Tobin 71.67 77.33 79.67 102.67 137.67 7.00 14.67 55.00 11.13 258.67 11.33 0.18 6.11
Toria ×Torch 71.00 73.33 80.33 105.00 118.67 7.67 17.33 34.00 10.69 218.67 10.67 0.18 3.64
Toria× Candle 70.67 76.33 82.33 98.67 187.67 4.00 8.67 63.00 54.36 334.00 12.33 0.14 34.22
UAF12 ×Tobin 69.33 78.33 82.67 99.67 173.33 5.33 8.33 72.67 21.47 282.33 12.00 0.16 15.60
UAF12×Torch 58.00 74.33 80.00 104.00 172.67 6.00 13.67 75.00 21.83 291.67 12.00 0.14 16.38
UAF12 ×Candle 63.33 77.33 82.33 103.00 171.00 6.33 9.00 34.00 35.46 319.33 11.33 0.18 12.03
1072 ×Tobin 64.67 74.00 82.33 99.00 141.67 11.00 23.67 27.00 71.75 317.67 12.67 0.17 19.28
1072x Torch 74.00 79.00 84.67 104.67 189.00 7.00 12.67 102.3 30.60 563.33 12.67 0.24 31.28
1072 × Candle 68.00 76.00 80.67 101.33 138.33 6.00 10.00 26.33 10.48 252.33 12.00 0.13 2.75
UAF11×Tobin 67.67 80.67 85.00 98.67 202.00 7.33 9.33 41.67 8.17 298.00 16.00 0.13 3.39
UAF11×Torch 73.00 77.67 86.00 100.33 187.00 11.33 20.67 66.67 29.99 248.33 10.67 0.19 19.98
Uaf11× Candle 63.67 74.67 82.33 102.33 190.33 4.33 8.33 56.33 6.05 243.33 14.33 0.15 3.40
Tr8 ×Tobin 72.67 80.67 88.33 102.33 152.00 4.67 12.33 20.67 49.46 277.00 10.67 0.22 10.11
62
Tr8 ×Torch 70.33 81.33 88.33 105.33 139.33 6.33 13.67 29.33 61.37 274.33 13.00 0.12 17.99
Tr8× Candle 70.00 81.67 85.67 98.00 191.67 3.67 7.33 57.33 22.18 309.33 10.67 0.15 12.67
Q15×Tobin 69.67 85.33 90.33 97.33 201.67 9.00 18.33 74.67 14.60 260.00 12.00 0.15 10.89
Q15×Torch 72.67 81.67 85.67 98.67 183.67 7.33 16.33 52.67 56.03 289.33 13.00 0.18 29.41
Q15× Candle 72.00 77.33 82.67 101.00 157.00 7.00 12.33 52.33 25.99 296.67 13.33 0.18 13.57
Span×Tobin 73.00 82.33 90.33 105.33 165.00 5.33 9.67 83.67 58.25 363.33 13.67 0.26 48.72
Span× Torch 71.00 82.00 86.67 103.67 122.33 4.00 8.00 21.67 18.56 329.33 11.67 0.16 3.86
Span× Candle 70.67 79.67 85.33 100.00 180.33 10.67 22.00 58.33 19.55 369.00 12.67 0.22 11.38
LSD 5% 2.91 3.91 2.15 2.32 6.68 2.26 1.96 4.54 4.32 12.03 1.94 0.017 1.07
LSD 1% 3.81 5.23 2.87 3.10 8.94 3.035 2.63 6.08 5.780 16.10 2.60 0.023 1.44
*=significant (p<0.05);**=highly significant (p<0.01
DFI stands for days to flowering initiation, D50%F for days to 50%flowering, D50%SF for days 50% siliqua formation, DM for days to maturity, PH for plant
height, PB for primary branches, SB for secondary branches, GB for green biomass yield, HI for harvest index, S/PL for siliquae per plant, S/S for seed per siliqua,
TSW for 100 seed weight, Y/P for yield per plant
63
Hybrids Quality related traits
O (%) PRT (%) GSL (%) OA (%) EA (%)
Toria ×Tobin 36.30 22.40 46.40 44.07 21.63
Toria ×Torch 37.53 27.57 46.40 44.20 25.60
Toria× Candle 37.80 29.40 65.13 70.33 19.70
UAF12 ×Tobin 38.07 26.73 43.07 50.77 27.27
UAF12×Torch 43.73 29.37 53.57 57.03 19.57
UAF12 × Candle 36.80 26.13 80.40 63.13 39.30
1072 ×Tobin 40.33 27.53 73.63 52.97 23.33
1072x Torch 41.23 23.70 42.70 71.87 24.43
1072 × Candle 39.03 24.03 71.20 48.60 23.67
UAF11×Tobin 47.30 31.73 96.57 29.07 34.00
UAF11×Torch 43.03 27.23 78.30 53.00 29.07
Uaf11× Candle 43.53 24.30 79.07 45.17 33.43
Tr8 ×Tobin 46.40 23.37 20.43 57.90 13.50
Tr8 ×Torch 37.77 25.00 25.27 29.33 15.47
Tr8× Candle 39.60 29.20 67.10 66.13 12.50
Q15×Tobin 32.00 27.23 57.33 47.43 14.27
Q15×Torch 39.57 29.43 11.20 23.07 13.33
Q15× Candle 36.90 27.07 65.50 50.83 12.33
Span×Tobin 37.80 26.47 57.77 56.40 15.07
Span× Torch 37.47 26.53 72.13 57.90 18.13
Span× Candle 36.93 29.37 23.33 53.40 13.37
LSD 5 % 0.903 2.581 0.887 0.871 3.859
LSD 1% 1.208 3.454 1.187 1.165 5.163
a considerable amount of variation was observed for erucic acid with ranged from 12.33
(Q15×Candle) to 39.30 (UAF12×Candle).seed oil, protein, glucosinolate, oleic acid and
erucic acid contents are the output of a plant. Studies on genetic variation for quality traits in
oilseed brassicas indicate both significant and non significant variation (Khan et al., 2008)
and Fayyaz et al. (2014).Significant variation between yellow and brown seeds only for oil
and fatty acid were also observed
64
4.3 Estimates of General Combining Ability of Various Traits in Brassica campestris
Variation for general combing ability was studied among lines and testers for thirteen plant
traits to identify the better parents. The results for general combining ability effects presented
(Table 4.4). Minimum number of days for initiation and maturity are required to develop the
short duration cultivars so that it may easily fit in our cropping pattern. UAF12 and UAF11
were the batter general combiner lines (-5.83), (-1.27) for flowering initiation while Span was
the poorest general combiner. Among tester Candle for GCA effects was the best. For 50%
days to flowering among lines Toria (-2.95) was the best combiner fallowed by 1072 (-2.29)
while Quinyou15 (2.83) showed the lowest combining ability. Again Candle was the best
tester (-1.05) and Tobin was the poorest tester. Toria (-3.59) was the best for GCA effects for
50% days to siliqua formation and Span (3.08) was the lowest general combiner among the
lines.Among testers Candle was good combiner and Tobin was poor general combiner. For
plant height the GCA effects values for 10 parents the best combiner line was Toria (-18.78)
and the best tester line was Torch (-7.83). Results were supported by Singh et al. (2010) and
Synrem et al. (2015). The range of GCA effects for primary branches, the best combining
line was 1072 (1.54) fallowed by Quinyou15 (0.87) and the poorest line was UAF12 ( -0.90).
Tobin (0.40) was the best combining tester line while Torch was the lowest combining tester
line (-7.83). For secondary branches the range of GCA affects 10 parents from (2.59) to (-
2.14). The best combining line was Quinyou 15 and the lowest line was TR8. The best tester
line was Torch (1.48) fallowed by Tobin (0.67) and the poorest tester line was Candle (-
2.14). For number of seeds per plant, UAF11 was the best combining line (1.37) and the
lowest combining line was TR8 (-0.80). The best general combining tester line was Tobin but
results were non_ significant statistically. For yield the best general combining line was Span
(5.76) fallowed by Quinyou 15 (2.40) and the poorest line was UAF12 (-0.88).
The best general combining tester line for was Torch (1.95). The genotype Span and
Torch can be considered as the superior parents in this study because they showed positive
and significant GCA effects for seed yield. Findings were inaccordance with Parmer et al.
(2011) and Synrem et al. (2015).
65
Table 4.4 Estimates of general combining ability for various traits in Brassica campestris
Phenological traits Morphological traits Yield related traits
Genotype DFI
D 50% F D50%SF DM PH PB SB B.Y HI SL/p S/S TSW Y/P
Lines
Toria 1.73 ** -2.95 ** -3.59 ** 0.63 -18.78** -0.57 0.59 -1.94 * -4.99 ** -34.13 ** -0.86 * -0.00 -0.90 **
UAF12 -5.83 ** -1.95 * -2.70 ** 0.75 5.56 ** -0.90 ** -2.86 ** 7.95 ** -4.12 ** -6.79 ** -0.52 -0.01 ** -0.88 **
1072 -0.49 -2.29 ** -1.81 ** 0.19 -10.44 ** 1.54 ** 2.48 ** -0.71 7.23 ** 73.21 ** 0.03 0.01 * 2.21 **
UAF11 -1.27 * -0.95 0.08 -1.03 * 26.33 ** 0.98 ** -0.41 2.29 * -15.64 ** -41.35 ** 1.37 ** -0.02 ** -6.63 **
TR8 1.62 ** 2.60 ** 3.08 ** 0.41 -5.78 ** -2.02 ** -2.19 ** -16.83 ** 13.96 ** -17.68 ** -0.86 * -0.01 * -1.97 **
Quinyou15 2.06 ** 2.83 ** 1.86 ** -2.48 ** 14.00 ** 0.87 ** 2.59 ** 7.29 ** 1.83 * -22.57 ** 0.48 -0.00 2.40 **
Span 2.17 ** 2.71 ** 3.08 ** 1.52 ** -10.89 ** 0.1 -0.19 1.95 * 1.74 49.32 ** 0.37 0.04 ** 5.76 **
SE 0.59 0.79 0.43 0.47 1.35 0.3 0.33 0.92 0.87 2.43 0.35 0.00 0.22
Testers
Tobin 0.43 1.19 * 1.16 ** -0.76 * 0.84 0.40 * 0.67 ** 1.02 3.17 ** -10.71 ** 0.32 0.01 ** 0.74 **
Torch 0.62 -0.14 0.16 1.62 ** -7.83 ** 0.35 1.48 ** 1.92 ** 2.34 ** 11.86 ** -0.4 -0.00 1.95 **
Candle -1.05 ** -1.05 * -1.32 ** -0.86 ** 6.98 ** -0.75 ** -2.14 ** -2.94 ** -5.51 ** -1.14 0.08 -0.01 ** -2.69 **
SE 0.38 0.52 0.28 0.31 0.88 0.19 0.21 0.6 0.57 1.59 0.23 0.00 0.14
*=significant (p<0.05);**=highly significant (p<0.01)
DFI stands for days to flowering initiation, D50%F for days to 50%flowering, D50%SF for days 50% siliqua formation, DM for days to maturity, PH for plant height, PB for
primary branches, SB for secondary branches, GB for green biomass yield, HI for harvest index, S/PL for siliquae per plant, S/S for seed per siliqua, TSW for 100 seed weight,
Y/P for yield per plant
66
4.4 Specific Combining Ability Estimates of Various Traits in Brassica campestris
Specific combining ability estimates of 21 Brassica campestris combinations (Table 4.5)
Minimum number of days to flowering initiation is a required trait of Brassica campestris to
fit for cropping pattern so that farmer may adapt it as a cash crop. The crosses viz.
UAF12×Torch, 1072×Tobin, UAF12×Candle and Quinyou15×Tobin were better, showing
negative and significant specific combining ability effects (-6.17), (-4.65), (-3.40) and (-2.21)
respectively. Cross combinations 1072×Tobin and Quinyou15×Candle had highly negative
and significant specific combining ability effects for days to 50% flowering. Toria×Tobin
and Quinyou15×Candle combinations showed significant negative specific combining ability
effects for days to 50% siliqua formation while TR8×Candle highly significant and negative
specific combining ability effects for days to maturity, these cross combinations can be
utilized to find early maturing genotypes in subsequent generations. Cross combination
Quinyou15×Candle was a better specific combiner for plant height. Cross combination
Span×Candle was good specific combiner for number of primary branches while the same
combination was good specific combiner for secondary branches. For green biomass and
harvest index the combinations 1072×Torch and 1072×Tobin were good specific combiners
respectively. Cross combination 1072×Torch for number of siliqua per plant was good
specific combiner while TR8×Torch was good specific combiner for seed per pod. The
combination 1072×Torch was good combination for 100 seed weight. Span×Tobin
combination showed maximum specific combining ability for yield.
Global acreage under oilseeds is increasing gradually. For advancement in breeding of
oilseeds it is important to determine the combining ability of selected material or mode of
inheritance of economic traits. GCA, SCA or mode of inheritance of plant height, number of
lateral branches were estimated in rapeseed (Marjanović-Jeromela et al., 2007). General
combining ability was not predominant for secondary branches while specific combining
ability was significant for secondary branches in Ethiopian mustard (Teklewold and Becker,
2005). Azizinia (2011) studied combining ability and noted significant differences for plant
height and number of lateral branches per plant.Qian et al. (2003) reported significant
negative and positive GCA effects for European B. rapa and for Chinese B. rapa respectively
that meant Chinese B. rapa might be an important source for transferring favorable genes of
biomass yield.
67
Table 4.5 Specific combining ability estimates of various traits in Brassica campestris
Traits Phenological traits Morphological traits Yield related traits
Crosses DFI D 50%
F
D 50%
SF DM PH PB SB GB HI SL/p S/S TSW Y/P
Toria × Tobin 0.13 0.48 -2.27 ** 1.32 -11.17 ** 0.38 0.56 3.32 * -17.43
** -1.06 -0.43 0.00 -9.29 **
Toria × Torch -0.73 -2.19 -0.60 1.27 -21.51 ** 1.10 * 2.41 ** -18.59 ** -17.05
** -63.63 ** -0.38 0.02 * -12.97 **
Toria×Candle 0.60 1.71 2.87 ** -2.59 ** 32.68 ** -1.48 ** -2.97 ** 15.27 ** 34.48 ** 64.70 ** 0.81 -0.02 ** 22.26 **
UAF12 × Tobin 5.35 ** 0.48 -0.16 -1.79 * 0.16 -0.95 -2.67 ** 11.10 ** -7.95 ** -4.73 -0.10 -0.01 0.18
UAF12×Torch -6.17 ** -2.19 -1.83 * 0.16 8.16 ** -0.24 1.86 ** 12.52 ** -6.77 ** -17.97 ** 0.62 -0.02 ** -0.24
UAF12×Candle 0.83 1.71 1.98 * 1.63 * -8.32 ** 1.19 * 0.81 -23.62 ** 14.72 ** 22.70 ** -0.52 0.03 ** 0.06
1072 × Tobin -4.65 ** -3.52 * -1.38 -1.90 * -15.51 ** 2.94 ** 8.00 ** -25.90 ** 30.97 ** -49.40 ** 0.02 -0.02 ** 0.76 *
1072× Torch 4.49 ** 2.81 * 1.95 * 1.38 40.49 ** -1.35 * -4.48 ** 48.52 ** -9.36 ** 173.70 ** 0.40 0.06 ** 11.56 **
1072 × Candle 0.16 0.71 -0.57 0.52 -24.98 ** -1.59 ** -3.52 ** -22.62 ** -21.62
**
-124.30
** -0.41 -0.04 ** -12.32 **
UAF11×Tobin -0.87 1.81 -0.60 -1.02 8.05 ** -0.84 -4.11 ** -14.24 ** -9.73 ** 45.49 ** 2.02 ** -0.04 ** -6.28 **
UAF11×Torch 4.27 ** 0.14 1.40 -1.73 * 1.71 3.54 ** 6.41 ** 9.86 ** 12.91 ** -26.75 ** -2.60 ** 0.03 ** 9.11 **
UAF11×Candle -3.40 ** -1.95 -0.79 2.75 ** -9.76 ** -2.70 ** -2.30 ** 4.38 ** -3.18 * -18.75 ** 0.59 0.01 -2.83 **
68
Traits Phenological traits Morphological traits Yield related traits
Crosses DFI D 50%
F
D 50%
SF DM PH PB SB GB HI SL/p S/S TSW Y/P
TR8 × Tobin 1.24 -1.75 -0.27 1.21 -9.84 ** -0.84 0.33 -16.13 ** 1.95 0.83 -1.10 0.05 ** -4.22 **
TR8 × Torch -1.29 0.25 0.73 1.83 * -13.84 ** 1.21 * 1.19 * -8.37 ** 14.69 ** -24.41 ** 1.95 ** -0.04 ** 2.45 **
TR8×Candle 0.05 1.49 -0.46 -3.03 ** 23.68 ** -0.37 -1.52 ** 24.49 **
-16.64
** 23.59 ** -0.86 -0.00 1.77 **
Quinyou
15×Tobin -2.21 * 2.70 2.95 ** -0.90 20.05 ** 1.27 * 2.22 ** 13.76 **
-20.78
** -11.29 ** -1.10 -0.03 ** -7.81 **
Quinyou
15×Torch 0.60 0.37 -0.71 -1.95 * 10.71 ** -1.35 * -0.92 -9.14 ** 21.48 ** -4.52 0.62 0.01 9.50 **
Quinyou
15×Candle 1.60 -3.06 * -2.24 ** 2.86 ** -30.76 ** 0.08 -1.30 * -4.62 ** -0.71 15.81 ** 0.48 0.02 * -1.69 **
Span×Tobin 1.02 -0.19 1.73 * 3.10 ** 8.27 ** -1.95 ** -4.33 ** 28.10 ** 22.97 ** 20.16 ** 0.68 0.04 ** 26.65 **
Span×Torch -1.17 0.81 -0.94 -0.95 -25.73 ** -2.90 ** -6.48 ** -34.81 ** -15.91
** -36.41 ** -0.60 -0.05 ** -19.41 **
Span×Candle 0.16 -0.62 -0.79 -2.14 * 17.46 ** 4.86 ** 10.81 ** 6.71 ** -7.06 ** 16.25 ** -0.08 0.02 ** -7.25 **
SE. 1.02 1.37 0.75 0.81 2.34 0.51 0.56 1.59 1.51 4.21 0.61 0.01 0.38
*=significant (p<0.05);**=highly significant (p<0.01)
DFI stands for days to flowering initiation, D50%F for days to 50%flowering, D50%SF for days 50% siliqua formation, DM for days to maturity, PH for plant
height, PB for primary branches, SB for secondary branches, GB for green biomass yield, HI for harvest index, S/PL for siliquae per plant, S/S for seed per
siliqua, TSW for 100 seed weight, Y/P for yield per plant
69
4.5 Components of Genetic Variance and Degree of Dominance
Variances due to GCA, SCA, Additive, Dominance and degree of dominance for indicated
traits in Brassica campestris (Table 4.6). It is clear from the table that specific combining
ability was more important than general combining ability and dominance variance than
additive variance. Specific combining ability or dominance variance was more important for
primary branches, secondary branches, and harvest index, siliquae per plant, seed per
siliquae, 100 seed weight and yield than general combining ability or additive variance.
Degree of dominance was greater than 1 for days to flower initiation, days to 50%flowering,
days to maturity and plant height; all these traits can be utilized for heterotic effects of their
genotypes.
Gene action is a way in which gene expresses itself in genetic population. A study on
gene action helps in selection of genotypes for the improvement of crops.With polygene,
gene action is of four types, additive, dominance, and epistasis and over dominance (Sleeper
and Poehlman, 2006).The nature and magnitude of gene action analysis and inheritance of
some selected genotypes of Brassica rapa (Toria) for phonological and yield traits indicated
the mean direction of dominance as well as importance of dominant genes in the expression
of these traits.On the other hand days to flowering, days to maturity, number of seeds per
siliqua, harvest index and oil content showed the values in negative direction, showing the
excess of recessive genes for these traits (Rahman et al., 2011).Both additive and non
additive gene actions were important in controlling days to 50% flowering, seed yield per
plant. Additive gene action was important for the expression of days to 90% maturity,
number of seeds per pod and 1000 seeds weight. Non-additive gene action was important in
controlling the expression of number of pods per plant (Bggett and Kean, 1989). Gupta et al.(
2010) verified high heterotic crosses on the basis of GCA and SCA in B. juncea L. The GCA
and SCA variances were noted significant for days to 50% flowering, days to maturity, 1000-
seed weight and seed yield per 100 siliqua. GCA in days to 50% flowering, days to maturity
and 1000-seed weight was higher and SCA was higher for seed yield and other traits.
70
Table 4.6 Components of genetic variance and degree of dominance
Traits Phenological traits Morphological traits Yield related traits
Genetics
components DFI D 50% F D 50% SF DM PH PB SB GB HI SL/p S/S TSW Y/P
Cov H.S(line) 4.12 4.93 6.26 -0.31 38.82 -0.70 -6.02 -168.83 -79.85 148.95 0.0626 -0.0002 -53.53
Cov H.S(tester) -1.00 0.47 0.96 1.07 -37.57 -0.55 -0.85 -95.16 -49.85 -631.68 -0.1243 -0.0002 -23.80
Cov F.S 13.27 9.25 11.42 7.75 595.31 4.62 23.53 342.20 322.28 4009.61 1.1961 0.0011 104.82
σ2 GCA 0.23 0.37 0.49 0.04 0.67 -0.08 -0.47 -17.08 -8.34 -24.07 -0.0024 -0.0001 -5.07
σ2SCA 11.81 3.72 3.57 5.60 645.06 6.48 30.92 710.31 507.33 5302.49 1.4204 0.0017 207.13
A 0.94 1.49 1.97 0.15 2.70 -0.32 -1.88 -68.30 -33.36 -96.29 -0.0096 -0.0001 -20.26
D 47.23 14.89 14.27 22.42 2580.23 25.94 123.67 2841.26 2029.31 21209.96 5.6815 0.0066 828.52
Degree of
Dominance 7.09 3.16 2.69 12.23 30.91 -9.00 -8.11 -6.45 -7.80 -14.84 -24.33 -8.12 -6.39
GCA for general combining ability and SCA for specific combining ability
DFI stands days to flowering initiation, D50%F for days to 50%flowering, D50%SF for days 50% siliqua formation, DM for days to maturity, PH for plant
height, PB for primary branches, SB for secondary branches, GB for green biomass yield, HI for harvest index, S/PL for siliquae per plant, S/S for seed per
siliqua, TSW for 100 seed weight, Y/P for yield per plant
71
4.6 Contribution (%) of genotypes and their interaction
A line×tester analysis of Brassica campestris with ten genotypes was adopted. Seven
genotypes were used as lines and three were used as tester to get the relative involvement of
lines, testers and their interactions to the whole variance for various traits. Contribution of
(%) lines, testers and their interaction of thirteen traits (Table 4.7). It is clear from the table
that lines made an important contribution towards all these traits. The maximum contribution
of lines was 65.85% for days to 50% siliqua formation and minimum value was towards
yield 9.83 % showing predominant maternal effect for these traits. The contribution of testers
was higher for days to maturity 20% fallowed by secondary branches 10.01%. It showed
preponderance of paternal effect for these traits. The contribution of their interaction was
relatively higher for all traits.
Table 4.7 Contribution (%) of genotypes and their interactions
DFI stands days to flowering initiation, D50%F for days to 50%flowering, D50%SF for days 50% siliqua formation, DM
for days to maturity, PH for plant height, PB for primary branches, SB for secondary branches, GB for green biomass
yield, HI for harvest index, S/PL for siliquae per plant, S/S for seed per siliqua, TSW for 100 seed weight, Y/P for yield per
plant.
4.7 Heterotic Estimation for Yield and Yield Related Traits in Brassica campestris
All 21 hybrids were compared with mid parental value and better parent for estimation of
heterosis. Substantial amount for heterosis was noted for yield and other related characters
studied. However, all crosses differed for the degree of heterosis (Table 4.8).
Traits Phenological traits Morphological traits Yield related traits
Parents DFI D5% F D50%SF DM PH PB SB GB HI SL/p S/S TSW Y/P
Lines 47.7 59.06 65.85 23.78 34.91 24.36 15.67 12.52 20.11 34.52 33.71 24.22 9.83
Testers 3.68 8.57 10.4 20.44 5.88 5.1 10.01 0.94 3.99 1.79 5.24 3.78 2.86
L x T 48.63 32.37 23.75 55.78 59.21 70.54 74.32 86.53 75.9 63.69 61.04 72 87.31
72
4.7.1 Seed yield per plant
Eight hybrids out of 21 combinations showed positive and significant relative heterosis and
heterobeltiosis for seed yield as given in the table 4.8. Positive and significant heterosis and
heterobeltiosis is preferred for the selection of genotypes and aim of the heterosis breeding is
to attain high yielding combinations with desirable quality traits. Significant and positive
heterosis was reported by earlier workers like Gupta et al. (2011); Verma et al. (2011); Patel
et al. (2012); Kumar et al. (2013); Kumar et al. (2014); Meena et al. (2014) and Synrem et al.
(2015).
4.7.2 Days to Flowering Initiation
Out of total 21 crosses, 6 hybrids were identified for significant and negative heterosis. These
hybrids were UAF12×Torch (-20.55), (-21.62), UAF12×Candle, (-12.24), (-14.41),
1072×Tobin, (-8.06), (-9.35.), 1072×Candle, (-4.0), (-4.67), UAF11×Candle, (-7.95), (-9.48).
Negative heterosis is desirable for flowering in Brassica. Early flowering is a first step
towards early maturing verities that prevents the yield losses and oil quality due to high
temperature. Grant and Beversdorf ( 1985) reported negative heterosis for flowering.
4.7.3 Days to 50% Flowering
Out of 21 hybrids only two showed significant negative heterosis over mid parent and batter
parent. Among them UAF12×Torch and UAF12×Candle showed negative significant relative
heterosis (-5.91) and heterobeltiosis (-9.35) and cross UAF12×Candle showed significant
negative heterosis and heterobeltiosis (-4.13) and (-5.69) respectively. Negative heterosis is
preferred for earliness in flowering. The crosses showing earliness can be used for further
evaluation. Observations were in accordance with results reported by Nassimi et al. (2006).
Synrem et al. (2015) observed desirable and significant negative heterosis for days to 50%
flowering in Brassica species.
4.7.4 Days to 50% Siliquae Formation
Out of 21 hybrids, eight reflected significant negative relative heterosis and heterobeltiosis
for days to 50% siliqua formation. For early maturing cultivars, negative heterosis for 50%
days to siliqua formation is an advantageous individuality.
4.7.5 Days to Maturity
Eight crosses revealed significant negative heterosis and heterobeltiosis for maturity days
viz.,Toria×Candle, (-5.73), (-8.07), UAF12×Tobin, (-2.61), (-3.86), UAF12 ×Candle, (-2.37),
73
(-4.04), TR8×Tobin, (-3.31), (-7.53), TR8×Candle, (-4.26), (-4.89), Quinyou15×Torch,
(-2.95), (-3.58), Quinyou15×Candle, (-3.66), (-5.90), Span×Candle, (-3.69), (-6.83). The
comparison of nap and mur cytoplasmic system for heterosis, was investigated and hybrids
in nap and mur cytoplasm showed negative heterosis for days to maturity (Riungu and
McVetty, 2004). Early maturity is a useful trait in many plant species; however it is very
important in Brassica species because late maturity causes the yield losses and quality of oil
due to high temperature (Turi et al., 2006). Nassimi et al. (2006); Yadava et al. (2012) and
Synrem et al. (2015) reported that negative heterosis was useful for days to maturity.
4.7.6 Plant Height
Out of 21 crosses, 14 showed negative heterosis for plant height. Values have been given in
the table 4.8. These crosses showed mid parent and batter parent heterosis for plant height.
Negative heterosis is desirable for plant height in Brassica species. Dwarf and medium plant
height resist to high wind velocity, logging and mechanical breakage. The heterosis studied
in oilseed rape for plant height was none significant. Negative values were also noted for
some crosses (Grant and Beversdorf, 1985). Significant and negative heterosis for plant
height had been noted by earlier different workers as Tyagi et al. (2000); Pourdad and Sachan
(2003); Nassimi et al. (2006) and Synrem et al. (2015).
4.7.7 Primary Branches
Four crosses showed positive relative heterosis and heterobeltiosis for primary branches.
Crosses viz., Toria×Torch, (39.93), (35.29), 1072×Tobin, (133.33), (84.21), UAF11×Tobin,
(62.96), (37.50), UAF11×Torch, (118.75), (118.75), Quinyou15×Tobin, (143.8), (133.33)
revealed positive and significant relative heterosis and heterobeltiosis. Positive heterosis is
desirable for Brassica species for primary branches. Plant with more branches will be
vigorous and produces more yield. Positive and significant heterosis was reported for
primary branches by Gupta (2009); Nasrin et al. (2011) and Synrem et al., (2015). The
highest value for heterosis and heterobeltiosis was identified for primary branches 24.25 and
12.30% in Brassica species by Nausheen et al. (2015).
4.7.8 Secondary Branches
Eleven hybrids reflected significant and positive heterosis for secondary branches per plant.
Significant and positive heterosis is desirable for secondary branches per plant. Vigorous
74
plant will provide opportunity for high yielding cultivar. Niranjana et al. (2014) and Synrem
et al. (2015) reported similar observations.
4.7.9 Green Biomass and Harvest Index
Only one hybrid showed significant and positive heterosis for green biomass shown in table
4.8. Positive relative heterosis and heterobeltiosis is desirable for high yielding cultivars.The
combination Span×Tobin showed significant positive heterosis (48.52) and heterobeltiosis
(11.56) while eight crosses showed positive and significant heterosis for harvest index. The
use of plant biomass plays an important role for animal hay and biogas production. Ofori et
al. (2008) studied the heterosis for fresh biomass, dry matter content and dry biomass
yield.The average value of genotypes was 5.3 tones per hectare and for hybrids was 5.3 tones
per hectare.The hybrids value was 7.6% more than parental value for fresh biomass, 5.9% for
dry biomass and 1.4% dry matter content.
Mid parent heterosis was noted 21.0% for fresh biomass yield and 30.4% for dry
biomass yield. Althoug heterosis percentage in crosses was so higher on an average, but it
may be increased up to 30% in good crosses.
4.7.10 Number of Siliquae per Plant and Number of Seed per Siliqua
Five hybrids showed positive heterosis for number of siliqua per plant and eight hybrids were
significant for number of seed per plant (Table 4.8). For both traits positive and significant
heterosis is advantageous for the development high yielding genotypes. Synrem et al. (2015)
also observed similar findings in his studies for heterosis.
4.7.11 Total Seed Weight (100 Seed)
Three hybrids showed positive and significant heterosis for 100 seed weight positive heterosis
for bold seed is a desirable quality for the development of high yielding genotype
75
Table 4.8a Heterotic manifestation for various traits of Brassica campestris
Triats Phenological traits
DFI D 50% F D 50% SF DM
Crosses MP BP MP BP MP BP MP BP
Toria×Tobin 1.42 -0.46 4.04 4.04 -2.45 * -5.16 ** 1.15 0.65
Toria×Torch -1.39 -1.39 -2.44 -3.51 -2.63 * -4.37 ** 3.45 ** 2.94 *
Toria×Candle -0.70 -1.85 -0.65 -3.78 -2.37 * -2.76 * -5.73 ** -8.07 **
UAF12×Tobin -3.26 -6.31 ** 0.21 -4.47 -1.39 -6.42 ** -2.61 ** -3.86 **
UAF12×Torch -20.55 ** -21.62 ** -5.91 ** -9.35 ** -5.51 ** -9.43 ** 1.63 0.32
UAF12×Candle -12.24 ** -14.41 ** -4.13 * -5.69 * -4.82 ** -6.79 ** -2.37 * -4.04 **
1072 ×Tobin -8.06 ** -9.35 ** -2.42 -4.31 1.65 -0.40 -1.00 -1.98
1072× Torch 3.26 2.78 3.04 2.16 3.46 ** 2.42 * 4.67 ** 3.63 **
1072 × Candle -4.00 * -4.67 * -2.98 -4.20 -3.59 ** -4.72 ** -1.78 -5.59 **
UAF11×Tobin -1.46 -2.40 8.04 ** 7.56 ** 6.47 ** 5.81 ** -1.33 -2.31 *
UAF11×Torch 4.29 * 1.39 2.87 2.19 6.61 ** 6.17 ** 0.33 -0.66
UAF11×Candle -7.95 ** -9.48 ** -3.24 -5.88 * -0.20 -2.76 * -0.81 -4.66 **
TR8 × Tobin 6.08 ** 4.81 * 4.09 0.00 6.43 ** 1.92 -3.31 ** -7.53 **
TR8 × Torch 0.72 -2.31 3.83 0.83 5.37 ** 1.92 -0.47 -4.82 **
TR8×Candle 1.45 -0.47 2.08 1.24 0.00 -1.15 -10.09 ** -11.45 **
Quinyou 15×Tobin -0.95 -2.34 14.03 ** 13.27 ** 12.68 ** 11.52 ** -4.26 ** -4.89 **
Quinyou 15×Torch 1.40 0.93 7.93 ** 7.46 ** 5.76 ** 5.76 ** -2.95 ** -3.58 **
Quinyou 15×Candle 1.65 0.93 -0.00 -2.52 -0.20 -2.36 * -3.66 ** -5.90 **
Span× Tobin 4.53 * 3.79 10.51 ** 10.27 ** 12.68 ** 11.52 ** 4.64 ** 4.29 **
Span× Torch -0.23 -1.39 8.85 ** 7.89 ** 7.00 ** 7.00 ** 2.98 ** 2.64 *
Span×Candle 0.47 0.47 3.46 0.42 3.02 ** 0.79 -3.69 ** -6.83 **
76
Continue
Traits Morphological Traits
PH PB SB GB HI
Crosses MP BP MP BP MP BP MP BP MP BP
Toria x Tobin -15.46 ** -22.37 ** 50.00 ** 23.53 100.00 ** 95.65 ** -22.72 ** -26.67 ** -23.18 -35.45 **
Toria ×Torch -36.65 ** -39.86 ** 39.39 ** 35.29 ** 89.29 ** 55.88 ** -61.87 ** -69.37 ** -41.71 ** -45.01 **
Toria× Candle -9.12 ** -20.37 ** -52.94 ** -64.71 ** -31.58 ** -51.85 ** -18.71 ** -28.14 ** 413.10** 215.45 **
UAF12 × Tobin 17.12 ** 16.85 ** 10.34 -11.11 78.57 ** 8.70 47.30 ** -3.11 -35.22 ** -60.65 **
UAF12×Torch 0.10 -12.50 ** 5.88 0.00 110.26 ** 20.59 ** 11.39 ** -32.43 ** -41.00 ** -60.00 **
UAF12 × Candle -10.78 ** -27.44 ** -26.92 ** -44.12 ** -8.47 -50.00 ** -38.92 ** -61.22 ** 21.18 ** -35.02 **
1072 ×Tobin -17.32 ** -27.10 ** 133.33 ** 84.21 ** 160.71 ** 121.21 ** -59.90 ** -64.00 ** 153.68** 60.01 **
1072x Torch -3.49 * -4.22 * 25.71 * 15.79 13.43 * 11.76 19.92 ** -7.81 ** -4.78 -31.76 **
1072 × Candle -35.66 ** -41.30 ** -32.08 ** -47.06 ** -31.03 ** -44.44 ** -64.25 ** -69.96 ** -57.03 ** -76.62 **
UAF11×Tobin 21.69 ** 9.98 ** 62.96 ** 37.50 ** 69.70 ** 21.74 * -42.26 ** -44.44 ** -64.04 ** -75.77 **
UAF11×Torch -1.84 -5.24 ** 118.75 ** 118.75 ** 181.82 ** 82.35 ** -26.06 ** -39.94 ** 12.84 -11.05
UAF11×Candle -9.22 ** -19.24 ** -48.00 ** -61.76 ** -21.88 ** -53.70 ** -28.24 ** -35.74 ** -67.90 ** -82.06 **
TR8 × Tobin -7.69 ** -16.02 ** -7.14 -23.53 80.00 ** 56.52 ** -75.73 ** -78.32 ** 78.22 ** 12.98 **
TR8 ×Torch -26.34 ** -29.39 ** 15.15 11.76 60.78 ** 20.59 ** -71.57 ** -73.57 ** 94.19 ** 40.20 **
TR8×Candle -8.00 ** -18.67 ** -56.86 ** -67.65 ** -38.03 ** -59.26 ** -37.34 ** -39.86 ** -7.06 -49.33 **
Quinyou 15×Tobin 42.02 ** 35.96 ** 143.48 ** 133.33 ** 103.64 ** 75.00 ** 26.20 ** -0.44 106.36** 24.47
Quinyou 15×Torch 10.31 ** -6.93 ** 42.86 ** 25.00 48.48 ** 44.12 ** -31.75 ** -52.55 ** 412.8** 188.34**
Quinyou 15×Candle -15.44 ** -33.38 ** -8.70 -38.24 ** -13.95 ** -31.48 ** -20.10 ** -40.30 ** 715.16** 556.87**
Span× Tobin 15.65 ** 11.24 ** -30.43 ** -54.29 ** -30.00 ** -50.88 ** 48.52 ** 11.56 ** 250.17** 170.39**
Span× Torch -26.82 ** -38.01 ** -49.02 ** -62.86 ** -47.25 ** -57.89 ** -70.85 ** -80.48 ** -9.43 -13.86
Span×Candle -3.22 * -23.48 ** -4.35 -5.71 17.12 ** 14.04 ** -6.91 * -33.46 ** 53.31 ** -9.27
77
Continue
Traits Yield related traits
SL/p S/S TSW Y/P
Crosses MP BP MP BP MP BP MP BP
Toria ×Tobin 3.12 -10.60 ** 19.30 * -8.11 7.84 1.85 -40.10 ** -47.37 **
Toria × Torch 4.46 * 2.98 3.23 -13.51 * 26.44 ** 1.85 -78.06 ** -83.12 **
Toria× Candle 19.64 ** -3.47 * 21.31 ** 0.00 -15.69 ** -20.37 ** 354.02 ** 194.80 **
UAF12 × Tobin 0.41 -2.42 -21.74 ** -50.00 ** -20.66 ** -34.25 ** 43.99 ** 21.14 **
UAF12×Torch 21.70 ** 6.84 ** -25.77 ** -50.00 ** -22.64 ** -43.84 ** -4.82 -23.97 **
UAF12 × Candle 3.18 * -7.71 ** -29.17 ** -52.78 ** -10.74 ** -26.03 ** 47.25 ** -6.56
1072 × Tobin 10.69 ** 9.79 ** 52.00 ** 26.67 ** -13.33 ** -27.78 ** 8.48 ** -27.94 **
1072× Torch 129.46 ** 97.89 ** 34.55 ** 23.33 ** 37.14 ** 0.00 29.53 ** 16.94 **
1072 × Candle -19.98 ** -27.07 ** 33.33 ** 20.00 * -35.00 ** -45.83 ** -81.80 ** -89.72 **
UAF11×Tobin 3.00 3.00 1.05 -36.00 ** -48.65 ** -62.00 ** -78.90 ** -85.48 **
UAF11×Torch 0.20 -14.17 ** -36.00 ** -57.33 ** -15.79 ** -44.00 ** -11.00 ** -14.42 **
UAF11×Candle -23.40 ** -29.67 ** -13.13 ** -42.67 ** -37.84 ** -54.00 ** -74.65 ** -85.45 **
TR8 × Tobin -13.84 ** -21.68 ** 3.23 -23.81 ** 42.55 ** 39.58 ** -59.90 ** -75.72 **
TR8 ×Torch -2.02 -22.43 ** 16.42 * -7.14 -8.86 -21.74 ** -43.08 ** -56.82 **
TR8×Candle -11.58 ** -12.54 ** -3.03 -23.81 ** -2.13 -4.17 -43.84 ** -69.58 **
Quinyou 15×Tobin -13.53 ** -16.67 ** 60.00 ** 44.00 ** 9.52 -4.17 121.38 ** 23.91 **
Quinyou 15×Torch 11.64 ** -7.26 ** 56.00 ** 56.00 ** 53.62 ** 47.22 ** 160.31 ** 36.50 **
Quinyou 15×Candle -9.83 ** -14.26 ** 63.27 ** 60.00 ** 26.19 ** 10.42 500.95 ** 291.49 **
Span× Tobin 24.22 ** 22.89 ** 100.00 ** 95.24 ** 36.84 ** 18.18 ** 477.38 ** 454.23 **
Span× Torch 31.21 ** 11.39 ** 52.17 ** 40.00 ** -5.05 -28.79 ** -73.93 ** -82.07 **
Span×Candle 15.01 ** 6.65 ** 68.89 ** 58.33 ** 17.54 ** 1.52 97.03 ** 40.75 **
*=significant (p<0.05);**=highly significant (p<0.01)
DFI stands for days to flowering initiation, D50%F for days to 50%flowering, D50%SF for days 50% siliqua formation, DM for days to maturity, PH for
plant height, PB for primary branches, SB for secondary branches, GB for green biomass yield, HI for harvest index, S/PL for siliquae per plant, S/S for seed
per siliqua, TSW for 100 seed weight, Y/P for yield per plant
78
4.8 Genetic Variability for Quality Parameters
Rapeseed and mustard oil quality depends on its important constituents such as oleic acid, erucic
acid and glucosinolate. Higher amount of protein and oleic acid, lower concentration of erucic
acid and glucosinolate are beneficial to health (Ahmad et al., 2012). Brassicas oil having low
amount of erucic acid is good for diet. However with high percentage of erucic acid is useful for
industrial products (Bhardwaj and Hamama, 2000; Burns et al. 2003 and Shehzad et al. 2015).
More quantity of glucosinolate is the reason for goiterogenic disorder .Therefore; it must be less
than30 µmole/g or lower than it (Snowdon et al. 2007). For quality attributes local and exotic
germplasm were crossed and mean squares values from the analysis of variance for five traits
(Table 4.9). Highly significant differences were noted for all the traits studied among the
genotypes, parents (lines and testers), crosses, P vs. C and line×tester interactions that shows
high genetic potential of genotype for improvement for mentioned quality traits.
Genetic variability plays an important role in improvement of any crop (Nasim et al.,
2013). Results were similar with research of Ping et al. (2003) who noted significant variation
for seed oil concentration. Alemayehu et al. (2005) observed significant variation for oil,
glucosinolate and protein contents in Brassica carinata. Ping et al. (2003) had studied significant
variation for protein meal ranging from 30 to 46%. Inayat et al. (2009) noted that genotype
(MRS-1) had the highest amount (90.97μmol/gm) and genotype (Siren) had the lowest amount
(44.83 μmol/g) of glucosinolate. Similar observations were taken by Khulbe et al. (2000) and
Bilgili et al. (2002) who revealed significant differences in it. Highly significant variability was
noted for glucosinolate, oleic acid, and erucic acid at 1% level of significance in rapeseed
(Ahmad et al., 2008; Inayt et al., 2009 and Fayyaz et al., 2014). Abideen et al. (2013) and
Azizinia (2012) gave similar observations for oil percentage with mean 51.1% and range was
noted from 42.7 to 53.3% for Brassica napus L.
79
Table 4.9 Mean square values for quality traits of Brassica campestris
*=significant (p<0.05);**=highly significant (p<0.01)
4.9 General Combining Ability Estimates for Quality Traits of Intraspecific Crosses
Variation for general combing ability was studied among the lines and testers for quality traits to
locate the best parent. The results for general combining ability estimates (Table 4.10). Data for
oil (%) in different genotypes of Brassica campestris revealed that the range for lines, was
maximum for UAF11 (5.54) and minimum for 1072 (0.72). Among the testers, the best general
combiner was Torch (0.57) and Candle showed negative but significant general combining
ability (-0.83). Turi et al. (2010) revealed desirable GCA effects for NUM124 (1.07) and
NUM113 (1.07) for oil contents in B juncea. Sabaghnia et al. (2010) also noted related
observation and had high significant GCA effects for oil. Nasim and Farhatullah (2013) reported
that two lines showed significant GCA effects.
Data for protein percentage showed that Quinyou15 was the best general combiner (1.06)
while among the tester all were non-significant statistically. Turi et al. (2010) revealed
significant effects of GCA for the above trait. Ahmad et al. (2012), Girke et al. (2012), Nasim
and Farhatullah (2013) and Noor-Ul-Abideen et al. (2013) observed the significant effects of
GCA for proteien.High range of glucosinolates concentration is health-risk. Significant effects
of GCA either in positive or in negative directions for glucosinolate contents were shown by
lines and testers.The lines and testers with negative GCA should be selected. Turi et al. (2010)
observed maximum GCA (-7.27) shown by line NUM103 and (-4.92) NUM113 in Indian
mustard. Similar results were studied in B.napus by Shehzad et al. (2015). For oleic acid
Quality related traits
Source of
Variation DF Oil content (%)
Protein
Content (%)
Glucosinolate
Content (%)
Oleic acid
(%)
Erucic acid
(%)
Replications 2 0.04 0.50 5.11 47.26 5.58
Genotypes 30 37.98** 15.96** 1915.68** 511.02** 521.88**
Parents 9 35.63** 12.78** 2973.19** 575.86** 1303.86**
Crosses 20 39.75** 17.55** 1528.87** 485.61** 187.42**
P vs C 1 23.71** 12.71 134.14** 435.56** 173.35
Lines 6 75.96** 10.31** 2061.30** 442.17** 500.12**
Testers 2 11.22** 2.00** 1602.03** 516.52** 8.22**
L × T 12 26.40** 23.77 1250.46** 502.18** 60.94**
L vs T 1 129.07** 3.20** 10635.61** 347.36** 2001.79**
Error 60 0.69 1.90 5.93 20.80 3.83
80
contents, the highest GCA effects were shown by line 1072 (6.73) while the highest general
combining ability was shown by the tester Candle (5.72). Positive GCA effects for oleic acid are
desirable trait for industry and diet purpose (Nasim and Farhatullah, 2013). All parental lines
reflected considerable effects of general combining ability for erucic acid in both positive and
negative direction. The maximum negative effect GCA effects were revealed by Span (-5.86)
and among tester all genotypes showed non-significant GCA effects.
The low erucic acid in rapseed is mandatory for diet and high quantity is not beneficial for
health. The genotypes with low effects of GCA for erucic acid are helpful to develop the
genotypes with low erucic acid. Results were in accordance with results by Nasim and
Farhatullah (2013) and Shehzad et al. (2015).
Table 4.10 General combining ability estimates for quality traits of intra-specific crosses
Traits Quality related traits
Parent (males
& females)
Oil contents
(%)
Protein
contents
(%)
Glucosinolat
e contents
(%)
Oleic acid
(%)
Erucic acid
(%)
Lines
Toria -2.27 ** -0.39 -3.38 ** 1.79 ** 0.93
UAF12 0.05 0.56 2.99 ** 5.90 ** 7.33 **
1072 0.72 ** -1.76 ** 6.49 ** 6.73 ** 2.43 **
UAF11 5.14 ** 0.91 28.62 ** -8.67 ** 10.79 **
TR8 1.77 ** -0.99 -18.42 ** 0.05 -7.56 **
Quinyou15 -3.33 ** 1.06 * -11.35 ** -10.63 ** -8.07 **
Span -2.08 ** 0.61 -4.95 ** 4.82 ** -5.86 **
SE 0.18 0.52 0.18 0.18 0.78
Testers
Tobin 0.26 * -0.35 0.43 ** -2.70 ** -0.08
Torch 0.57 ** 0.13 -8.94 ** -3.02 ** -0.58
Candle -0.83 ** 0.22 8.51 ** 5.72 ** 0.66
SE 0.12 0.34 0.12 0.12 0.51
*=significant (p<0.05);**=highly significant (p<0.01)
81
4.10 Specific Combining Ability Estimates for Quality Traits
The estimates of specific combining ability for 21 Brassica campestris combinations for five
quality traits presented (Table 4.11). Maximum oil content (%) is desirable trait in rapeseed.
Four combinations showed positive SCA effects. The maximum positive effect was found by the
combinationTR8×Tobin (4.88). Turi et al. (2010) revealed desirable SCA effects for NUM124
(1.07) and NUM113 (1.07) for oil contents in B juncea. Sabaghnia et al. (2010) also noted
related observation and showed considerable significant SCA effects. Nasim and Farhatullah
(2013) reported that two lines showed significant SCA effects. Shehzad et al. (2015) reported the
significant SCA effects in B.napus.
High protein contents are valuable trait in B.campestris. The highest SCA effects were
shown by the combination UAF11×Tobin (4.33). Turi et al. (2010) revealed considerable results
of SCA (0.68) for genotype NUM120. Ahmad et al. (2012); Girke et al. (2012); Nasim and
Farhatullah (2013) and Noor-Ul-Abideen et al. (2013) observed the considerable SCA effects.
Shehzad et al. (2015) supported our results in B. napus. The combination with negative specific
combining ability in term of glucosinolate is desirable in rapeseed. In case of SCA effects seven
combinations showed significant but negative effects for glucosinolate. Similar observations
were recorded by Turi et al. (2010) and Shehzad et al. (2015).
Ten combinations had considerable positive SCA effects (Table 4.9). The combination
1072×Torch revealed maximum positive SCA effects (17.06) for oleic acid fallowed by
Toria×Candle (11.74).Results were supported by Shahzad et al. (2015). Six hybrids showed
considerable effects of general combining ability for erucic acid in both positive and negative
direction. The remarkable negative SCA effects were revealed by UAF12 × Torch (-8.57). The
genotypes with low effects of SCA for erucic acid are helpful to develop the genotypes with low
erucic acid. Results were supported by Nasim and Farhatullah, (2013) and Shehzad et al. (2015).
82
Table 4.11 Specific combining ability for quality traits of intra-specific crosses of Brassica
campestris.
*=significant (p<0.05);**=highly significant (p<0.01)
Traits Quality related traits
Crosses Oil contents
(%)
Protein
contents
(%)
Glucosinolate
contents
(%)
Oleic acid
(%)
Erucic acid
(%)
Toria × Tobin -1.17 ** -3.70 ** -6.68 ** -6.10 ** -0.59
Toria ×Torch -0.24 0.98 2.70 ** -5.65 ** 3.87 **
Toria × Candle 1.41 ** 2.72 ** 3.98 ** 11.74 ** -3.27 *
UAF12 × Tobin -1.73 ** -0.33 -16.38 ** -3.51 ** -1.36
UAF12 × Torch 3.63 ** 1.83 * 3.50 ** 3.07 ** -8.57 **
UAF12 × Candle -1.91 ** -1.50 12.88 ** 0.43 9.93 **
1072 × Tobin -0.13 2.80 ** 10.69 ** -2.14 ** -0.39
1072 x Torch 0.47 -1.52 -10.87 ** 17.07 ** 1.20
1072 × Candle -0.34 -1.28 0.18 -14.93 ** -0.81
UAF11 × Tobin 2.42 ** 4.33 ** 11.49 ** -10.64 ** 1.92
UAF11 × Torch -2.15 ** -0.65 ns 2.60 ** 13.61 ** -2.52
UAF11 × Candle -0.26 -3.68 ** -14.09 ** -2.97 ** 0.60
TR8 × Tobin 4.88 ** -2.14 * -17.60 ** 9.48 ** -0.24
TR8 × Torch -4.05 ** -0.98 -3.39 ** -18.77 ** 2.22
TR8 × Candle -0.83 * 3.12 ** 20.99 ** 9.29 ** -1.99
Quinyou15× Tobin -4.42 ** -0.33 12.22 ** 9.69 ** 1.04
Quinyou1 × Torch 2.85 ** 1.39 -24.53 ** -14.36 ** 0.60
Quinyou15×Candl 1.57 ** -1.07 12.31 ** 4.67 ** -1.64
Span × Tobin 0.14 -0.64 6.26 ** 3.20 ** -0.37
Span × Torch -0.50 -1.05 30.00 ** 5.02 ** 3.19 *
Span × Candle 0.36 1.69 -36.25 ** -8.22 ** -2.82 *
SE 0.32 0.90 0.31 0.30 1.35
83
4.11 Components of Genetic Variance
Components of genetic variance for indicated traits in Brassica campestris (Table 4.12). It is
clear from the table that SCA was more important than GCA and dominance variance than
additive variance. Specific combining ability or dominance variance was more important for all
traits. Degree of dominance was greater than 1 for Oil content (%), glucosinolates and erucic
acid. All these traits can be utilized for heterotic effects of their genotypes.
Table 4.12 Components of genetic varianc
Traits Quality related traits
Genetic components
Oil
contents
(%)
Protein
contents
(%)
Glucosinolat
e contents
(%)
Oleic acid
(%)
Erucic
acid (%)
Cov H.S(line) 5.51 -1.50 90.09 -6.67 48.80
Cov H.S(tester) -0.72 -1.04 16.74 0.68 -2.51
Cov F.S 12.06 3.41 536.21 162.80 57.04
VAR OF GCA 0.35 -0.16 7.25 -0.43 3.29
VAR OF SCA 8.70 7.11 416.72 167.30 18.49
IF F=0 ; A 1.39 -0.65 29.00 -1.73 13.18
IF F=0 ; D 34.80 28.43 1666.90 669.20 73.96
Degree Dominance
{α2D
/α2A } ½
5.00 0.00 7.58 0.00 2.37
4.12 Heterotic Manifestation for Quality Traits
All 21 hybrids were compared with mid parent and better parent for estimation of relative
heterosis and heterobeltiosis. Substantial amount for relative heterosis and heterobeltiosis were
observed for oil contents and other related characters studied. However, all crosses differed for
the degree of heterosis (Table 4.13).
4.12.1 Oil content (%)
Two out of 21 combinations had significant and positive relative heterosis and heterobeltiosis
(Table 4.13). Positive and remarkable heterosis and heterobeltiosis is preferred and aim of the
heterosis breeding is to attain the combination with desirable quality traits. The combination
UAF11×Tobin and UAF11×Torch showed significant and positive heterosis for oil contents.
Negative or absence of heterosis for oil content is common and reported by earlier workers
(Brandle and McVetty, 1990; Schuler et al., 1992; Falk et al., 1994; Teklewold and Becker,
84
2005). However it has been reported by Zhong et al. (2009) when two low oil contents cultivar
were crossed, the heterosis was positive but low, when two medium or high oil content of same
level were crossed, there was positive relative heterosis or heterobeltiosis. When two parents
with different level oil contents i.e low and high were crossed the heterosis was negative.
Nausheen et al. (2015) also reported positive heterosis (14.41%) for oil content in combination
C-88 × C-97.
4.12.2 Protein content (%)
Results for protein content have been given in table 4.13 .Three combinations out of 21 were
positive and significant for protein contents. Cross combination of UAF11×Torch showed
maximum heterosis and heterobeltiosis (21.60 and 20.36 rspectively) for protein content. Low
heterosis was observed by (Cuthbert et al., 2011). However Engqvist and Becker (1991)
reported that there was no heterosis of any kind for protein. Nausheen et al. (2015) also reported
positive heterosis (11.34%, 23.33%) in F1 for protein in combination C-88 × C-89 and C-
88×plant -1 respectively.
4.12.3 Glucosinolate content
Out of 21 hybrids eight crosses showed negative and significant heterosis for glucosinolate.
Crosses with low glucosinolate content are desirable in rapeseed for nutritional usage.
Observations were agreed with Priyamedha et al. (2016) who noted the negative heterosis for
glucosinolates in Indian mustard (B. juncea).
4.12.4 Oleic acid (%)
Five combinations showed positive heterosis (Table 4.13). Oleic acid is an important enviable
component of Brassica seed meal therefore for getting improved Brassica varieties/lines positive
levels of heterosis and heterobeltiosis for oleic acid is considered. Cross Toria× Candle showed
maximum relative heterosis (66.80) heterobeltiosis (52.57) for oleic acid. Results were agreed in
accordance with Ali et al. (2015) who reported significant heterosis and heterobeltiosis for
different cross combinations.
85
4.12.5 Erucic Acid (%)
Erucic acid content of Brassica oil is an undesirable component that makes the oil unsuitable for
human diet. Negative heterosis and heterobeltiosis is valuable for erucic acid. Data regarding
erucic acid content (Table 4.13). Out of 21 crosses, 4 crosses showed significantly
Negative relative heterosis and heterobeltiosis (-25.97 and -53.89).Similar observations
were noted by Patel and Sharma (1999); Singh et al. (2003); Wang et al. (2009); Gami and
Chauhan (2014) and Chaudhari et al. (2015). Ali et al. (2015) also recoded remarkable negative
value (-70.28%) for relative heterosis in cross NUM009xNUM117. Heterobeltiosis values for
erucic acid content the maximum negative values (-61.67) was observed in cross
NUM009xNUM117.
4.13 Good Cross Combinations for Seed Yield and Quality Parameters
Four good cross combinations viz., Span×Tobin, Toria×Candle, 1072×Torch and Quinyou
15×Torch were identified for higher value of GCA, SCA, relative heterosis and heterobeltiosis
(Table 4.14).The combinations may be used for commercial exploitations for seed yield in
Brassica campestris. Similar results were supported by Sexena et al. (2010) who got 28.4% yield
superiority over check variety in farmer field. On basis of erucic acid (%) three combinations
viz. Toria×Candle, UAF11×Torch and Span × Candle were selected for SCA effects relative
heterosis, heterobeltiosis and GCA estimates. These three combinations can also be used as
source of low erucic acid combinations.
For glucosinolate (%) three combinations viz., Span × Candle, Quinyou15×Torch and
TR8×Tobin can be used as source of low glucosinolate (%). On the basis of oleic acid four good
crosses were identified. These good crosses were i.e. UAF11×Torch, Toria×Candle, Quinyou
15×Tobin and UAF12×Torch.These combinations were selected on the basis of GCA, SCA,
relative heterosis and heterobeltiosis. Oil (%) is an important parameter in Brassica. The four
good combinations for oil were selected on the basis of GCA, SCA, relative heterosis and
heterobeltiosis. These four combinations can also be used for commercial exploitations.
86
Table 4.13 Heterotic manifestation for quality traits of Brassica campestris combinations
*=significant (p<0.05);**=highly significant (p<0.01)
Traits
Oil contents
(%)
Protein contents
(%)
Glucosinolate
contents (%)
Oleic acid
(%)
Erucic acid
(%)
Crosses MP BP MP BP MP BP MP BP MP BP
Toria x Tobin -13.39 ** -18.17 ** -16.21 ** -17.55 ** -31.55 ** -59.44 ** -2.87 -16.06 * -26.29 ** -51.02 **
ToriaTorch -7.13 ** -9.27 ** 9.83 * 4.82 -33.15 ** -59.44 ** -6.52 -21.54 ** -7.08 -42.04 **
Toria×Candle -10.99 ** -16.86 ** 7.10 * 2.80 -8.84 ** -43.07 ** 66.80 ** 52.57 ** -27.26 ** -55.40 **
UAF12 ×Tobin -2.43 -14.19 ** 3.68 -1.60 -1.37 -34.91 ** 28.20 ** -3.30 -25.97 ** -53.89 **
UAF12×Torch 16.57 ** 5.72 ** 21.60 ** 20.36 ** 18.27 ** -19.04 ** 37.37 ** 1.24 -44.15 ** -66.91 **
UAF12 × Candle -6.99 ** -19.06 ** -1.38 -8.62 * 69.86 ** 21.51 ** 73.44 ** 36.95 ** 13.69 ** -33.54 **
1072 × Tobin -5.42 ** -9.08 ** 0.98 0.61 47.71 ** -6.24 * -0.06 -1.00 1.97 -25.29 **
1072x Torch 0.20 -0.32 -7.54 * -13.40 ** -17.04 ** -45.63 ** 30.86 ** 27.57 ** 15.89 * -21.77 **
1072 × Candle -9.65 ** -14.15 ** -14.12 ** -15.97 ** 33.04 ** -9.34 ** -2.41 -9.16 14.79 * -24.23 **
UAF11×Tobin 10.95 ** 6.63 ** 18.56 ** 16.81 ** 79.66 ** 11.85 ** -51.53 ** -56.90 ** 2.82 -34.11 **
UAF11×Torch 4.62 ** 4.03 * 8.36 * 3.29 41.40 ** -9.31 ** -14.35 ** -21.40 ** -7.04 -43.67 **
UAF11×Candle 0.81 -4.25 ** -11.58 ** -15.03 ** 37.71 ** -8.42 ** -20.43 ** -33.02 ** 8.55 -35.21 **
TR8 × Tobin 12.40 ** 4.60 ** -14.20 ** -14.41 ** -35.95 ** -52.07 ** 50.91 ** 10.29 85.65 ** -0.71
TR8 × Torch -5.07 ** -8.70 ** -2.34 -8.42 * -24.63 ** -40.73 ** -27.18 ** -47.93 ** 182.67 ** 41.46 *
TR8×Candle -5.34 ** -12.90 ** 4.47 2.10 88.66 ** 57.39 ** 88.06 ** 43.46 ** 149.75 ** 25.00
Quinyou15×Tobin -26.91 ** -27.86 ** 11.23 ** 0.25 129.95 ** 99.77 ** 0.78 -9.65 48.10 ** -1.83
Quinyou15×Torch -6.42 ** -8.41 ** 28.81 ** 23.15 ** -57.83 ** -60.98 ** -52.91 ** -59.05 ** 70.21 ** 21.95
Quinyou15×Candle -16.77 ** -18.84 ** 7.41 -5.36 129.02 ** 128.22 ** 15.88 * 10.27 67.42 ** 23.33
Span×Tobin -8.28 ** -14.79 ** -2.93 -3.29 78.11 ** 32.19 ** 2.27 -2.42 -3.42 -9.60
Span×Torch -5.67 ** -9.43 ** 3.51 -3.05 111.80 ** 65.06 ** 1.46 0.17 31.40 ** 8.80
Span×Candle -11.57 ** -18.77 ** 4.94 2.68 -35.36 ** -46.61 ** 2.79 -7.61 0.25 -19.80 *
87
*=significant (p<0.05);**=highly significant (p<0.01)
Table 4.14 Good cross combinations for seed yield and quality parameters
Character Name of
combinations SCA Effects Heterosis GCA Effects
MP BP Parent- 1 Parent-2
Yield Span × Tobin 26.65** 477.38** 454.23** 5.76** 0.74**
Toria × Candle 22.26** 354.2** 194.8** -0.9** -2.69**
1072 × Torch 11.56** 29.53** 16.94** 2.21** 1.95**
Quinyou 15 × Torch 9.5** 160.31** 36.5** 2.4** 1.95**
Erucic acid
(%)
Toria × Candle -3.27* -27.26** -5.4** 0.93 0.66
UAF12 × Torch -8.57 ** -44.15** -66.91** 7.33** -0.58
Span × Candle -2.82 * -0.25 -19.8** -5.86** 0.66
Glucosinolate
(%)
Span × Candle -36.25 ** -35.36 ** -46.61 ** -4.95 ** 8.51 **
Quinyou 15 × Torch -24.53 ** -57.83 ** -60.98 ** -8.94 ** -8.94 **
TR8 × Tobin -17.60 ** -35.95 ** -52.07 ** -18.42 ** 0.43 **
Oleic acid
(%)
UAF11 × Torch 13.61 ** 8.36 * 3.29 -8.67 ** -3.02 **
Toria × Candle 11.74 ** 7.10 * 2.80 1.79 ** 5.72 **
Quinyou 15 × Tobin 9.69 ** 11.23 ** 0.25 -10.63 ** -2.70 **
UAF12 × Torch 3.07 ** 21.60 ** 20.36 ** 5.90 ** -3.02 **
Oil Content
(%)
UAF12 × Torch 3.63 ** 16.57 ** 5.72 ** 0.05 0.57 **
UAF11 × Tobin 2.42 ** 10.95 ** 6.63 ** 5.14 ** 0.26 *
TR8 × Tobin 4.88 ** 12.40 ** 4.60 ** 1.77 ** 0.26 *
Quinyou 15 × Torch 2.85 ** -6.42 ** -8.41 ** -3.33 ** 0.57 **
88
4.14 Heritability and Genetic Advance for Intraspecific Combinations
Heritability as well as genetic advance is remarkable selection parameters. Heritability and
genetic advance can help in better way for estimation of the genetic gain under selection
(Johanson et al., 1955). Days to flowering initiation indicate high heritability (97.80) along
with high genetic advance (32.97) in percentage of mean that indicates heritability was due to
additive gene actions and selection for the trait may be effective (Table 4.15). Similar
findings were reported by Ali et al. (2003); Amiri-Oghan et al. (2009) and Zare and
Sharafzadah (2012). Days to 50% flowering indicat high heritability (71.29) and remarkable
genetic (56.10) advance in percentage of mean which indicated that selection will be
effective due to additive gene effects.These findings were agreed with findings of Dar et al.
(2010).
Days to 50% siliqua formation, days to maturity and plant height showed considerable
heritability and genetic advance. Results were partially agreed with that of Paikhomba et al.
(2014). Number of primary branches, secondary branches, and biomass yield and harvest
index revealed high heritability with low genetic advance in percentage of mean that showed
non-additive gene action and selection will not be rewarding in early generations. Heterosis
breeding and population improvement through recurrent selection will be effective. Findings
were not in contrary with results presented by Ali et al. (2003); Aytac et al. (2008) and
Mahmud (2008). Number of siliquae per plant and number of seed per siliqua had high
heritability and remarkable genetic advance in percentage of mean that revealed additive
genetic effects. Similar findigs were observed by Ali et al. (2003), Aytac et al. (2008),
Mahmud (2008) and Rameeh (2013). 100 seed weight showed low heritability with
remarkable genetic advance that shows additive gene effects. The low heritability was being
shown due to high environmental effect and selection may be effective in such cases. In case
of yield both heritability and genetic advance were high and selection will be effective way
for the improvement in yield. Observations were agreed with the findings of Singh and Singh
(1997) and Sheikh et al. (1999). Heritability and genetic advance in percentage of mean,
prediction can be made for the advancement in Brassica rapa L. through direct selection via
traits like days to 50% siliqua formation, days to maturity, number of siliquae/plant, number
of seed per siliqua and plant height.
89
DFI stands for flowering initiation, D50%F for days to 50%flowering, D50%SF for days 50% siliqua formation,
DM for days to maturity, PH for plant height, PB for primary branches, SB for secondary branches, GB for green biomass yield, HI for harvest index, S/PL for siliqua per plant, S/S for seed per siliqua, TSW for 1000
seed weight, Y/P for yield per plant
4.15 Heritability and Genetic Advance for Quality Traits
Oil content had high heritability (94.70) and moderate genetic advance (17.7) that showed
additive gene action and selection would be rewarding (Tabe 4.16). Similar results were
noted by Khulbe et al. (2000) and Ghosh and Gulati (2001). However, Shoukat et al. (2014)
who found low heritability for oil content. Protein contents had remarkable heritability
(71.13) along with moderate genetic advance (14.14). Glucosinolate also showed high
heritability (99.07) and high genetic advance (93.37). Similar studies were observed by
Bradshaw and Wilson (1998) in case of heritability for oleic acid and erucic acid high
heritability along with remarkable genetic advance were found. Results were supported by
Table 4.15 Heritability and Genetic advance for quantitative traits
Characters Heritability (%) Genetic advance (%)
DFI 97.81 32.97
D 50% F 71.29 56.12
D 50% SF 94.95 89.58
DM 98.71 87.08
PH 98.40 136.72
PB 79.12 8.74
SB 61.23 5.92
GB 86.37 7.05
HI 80.19 5.21
SL/p 98.95 43.93
S/S 90.04 60.46
TSW 23.83 214.53
90
Chauhan et al. (2002) who noted moderate to high heritability associated with high genetic
advance (45.0-62.5%) for erucic acid.
Table 4.16 Heritability and genetic advance for quality traits for intra-specific crosses
4.16 Genotypic and Phenotypic Correlation for Quantitative Traits in Intra specific
Crosses
Correlation coefficient is a statistical expression that determines the degree of relationship
between two or more variables. In plant breeding, correlation coefficient describes the
relationship among various plant parameters for which selection can be relied on for the
genetic improvement of yield. Table 4.17 shows that genotypic associations were higher than
phenotypic associations. Plant height had positive remarkable correlations with green
biomass, days to 50% flowering and seed yield per plant. The results were supported by
previous findings (Tyagi et al.1996; Thakral et al., 1998; Oezer et al., 1999; Ghosh and
Gulati, 2000; Khan et al., 2006, Aytac and Kinaci, 2009 and Zare, 2011). But some people
reported the negative correlation for these traits in rapeseed (Sadaqat et al., 2003; Zare and
Shrafzadeh, 2012).
Primary branches had positive significant correlation with secondary branches
(Cheema and Sadaqat, 2004). Secondary branches had negative significant correlation with
seed per siliqua and 100 seed weight. A significant correlation of green biomass was
observed with number of siliquae per plant and seed yield per plant.
Quality traits Heritability Genetic advance
Oil contents (%) 94.70 17.74
Protein contents (%) 71.13 14.14
Glucosinolate contents (%) 99.07 93.73
Oleic acid (%) 88.71 50.02
Erucic acid (%) 97.83 119.94
91
Table 4.17 Genotypic and Phenotypic Correlation between quantitative traits for intra-specific crosses
*=significant (p<0.05);**=highly significant (p<0.01)
DFI stands for days to flowering initiation, D50%F for days to 50%flowering, D50%SF for days 50% siliqua formation, DM for days to maturity, PH for
plant height, PB for primary branches, SB for secondary branches, GB for green biomass yield, HI for harvest index, S/PL for siliquae per plant, S/S for seed
per siliqua, TSW for 100 seed weight, Y/P for yield per plant
Morphological traits Phenological traits Yield related traits
PH PB SB GB HI DFI D50%F D50%SF DM SL/p S/S TWS Y/P
PH 1 0.172 -0.035 0.655** -0.096 -0.068 0.263* 0.203 -0.152 0.18 0.047 -0.057 0.269**
PB 0.142 1 0.849** -0.008 0.026 0.034 0.032 0.092 -0.079 0.085 -0.107 -0.139 -0.093
SB -0.032 0.753** 1 -0.074 -0.003 0.009 -0.084 -0.006 -0.167 0.036 -0.479** -0.487** -0.141
B.Y 0.644** -0.024 -0.072 1 -0.163 0.063 0.001 -0.04 0.17 0.285** -0.165 -0.116 0.504**
HI -0.093 0.032 -0.003 -0.17 1 0.118 0.281** 0.434** 0.019 0.191 0.329** 0.07 0.691**
DFI -0.052 0.024 0.005 0.051 0.118 1 0.347** 0.398** -0.026 0.114 -0.014 0.386 0.169
D50%F 0.210* -0.009 -0.057 0.001 0.226* 0.387** 1 0.959** 0.083 0.288** 0.217 -0.074 0.248*
D50%SF 0.184 0.109 0.006 -0.036 0.381** 0.338** 0.774** 1 0.171 0.215 0.217 0.256* 0.325**
DM -0.148 -0.06 -0.163 0.157 0.018 -0.023 0.0263 0.139 1 0.269** -0.077 0.079 0.162
SL/p 0.175 0.059 0.03 0.283** 0.189 0.099 0.225* 0.195 0.238* 1 0.017 -0.363** 0.401**
S/S 0.034 -0.096 -0.439** -0.147 0.304** -0.044 0.155 0.217* -0.052 0.019 1 0.492** 0.184
TWS -0.021 -0.054 -0.249* -0.059 0.061 0.13 -0.023 0.087 0.0731 -0.168 0.241* 1 -0.107
Y/P 0.266** -0.076 -0.137 0.491** 0.687** 0.156 0.202 0.302** 0.1454 0.399** 0.172 -0.044 1
92
Harvest index had positive association with days to 50% flowering, days to 50% siliquae
formation, number of seed per siliqua and seed yield per plant. Similar findings were noted by
Tyagi et al. (1996); Thakral et al. (1998); Sadaqat et al. (2003) and Zare and Shrafzadeh (2012).
Positive and significant association of found among days to flowering initiation, days to
50% flowering. Days to 50% siliquae formation presented positive and significant correlation
with 100 seed weight and highly significant correlation with seed yield per plant.Days to
maturity were significantly associated with number of siliquae per plant. Number of siliquae per
plant revealed negative association with 100 seed weight but positive with seed yield per plant.
Number of seed per siliqua reflected direct and considerable relationship with 100 seed weight.
4.17 Path Analysis for Quantitative Traits of Intraspecific Crosses
Path analysis is a standardized partial regression that split the correlation coefficients into
measure of direct and indirect effects. Correlation may not provide the comparative value of
direct and indirect effect of each yield components on seed yield. Path analysis has been used to
know inter-correlation between seed yield and yield contributing traits (Table 4.18). Path
coefficient analysis showed that harvest index had considerable positive and direct effect on seed
yield per plant (0.806) and positive indirect effect on yield via days to 50% flowering (0.083).
These findings showed that as the harvest index and days to 50% flowering increase, the yield
will also increase. Days to flowering initiation showed positive direct effect (0.049) on seed yield
and the highest indirect effect (0.102) via days to 50% flowering.
Days to 50% siliquae formation had direct effect (-0.30) and indirect positive effect (0.35)
via harvest index on seed yield. It is clear that reduction in days to 50 % siliquae formation
increases the harvest index, which will increase the seed yield. Days to maturity exerted positive
direct effect (0.05) on seed yield and maximum positive indirect effect (0.11) via green biomass.
It indicates that as days to maturity increase, the biological yield will also increase that will
ultimately increase in yield.
Plant height had negative direct effect (-0.08) while positive direct effect (0.44) via
biomass. It indicated that reduction in plant height will increase in green biomass yield. Belete
(2011) noted direct negative effect on seed yield. However, direct positive effects were also
found by Ali et al. (2003) and Basalma et al. (2008). Primary branches showed direct effect
93
Table 4.18 Path analysis for quantitative traits of intra specific crosses
DFI stands for days to flowering initiation, D50%F for days to 50%flowering, D50%SF for days 50% siliqua formation, DM for days to maturity,
PH for plant height, PB for primary branches, SB for secondary branches, GB for green biomass yield, HI for harvest index, S/PL for siliquae per
plant, S/S for seed per siliqua, TSW for 1000 seed weight, Y/P for yield per plant
Phenological traits Morphological traits Yield related traits
DFI D 50% F D 50% SF DM PH PB SB GB HI SL/p S/S TSW
DFI 0.049 0.102 -0.12 -0.001 0.005 -0.006 0.001 0.042 0.095 0.007 0.026 -0.0004
D 50% F 0.017 0.295 -0.29 0.004 -0.02 -0.005 -0.01 0.001 0.226 0.004 -0.001 -0.0019
D 50% SF 0.02 0.283 -0.302 0.009 -0.015 -0.016 -0.001 -0.027 0.35 0.011 0.018 0.0004
DM -0.001 0.024 -0.052 0.052 0.011 0.014 -0.02 0.114 0.016 0.008 0.017 -0.0013
PH -0.003 0.078 -0.061 -0.008 -0.075 -0.029 -0.004 0.438 -0.077 0.01 -0.006 -0.0004
PB 0.002 0.009 -0.028 -0.004 -0.013 -0.171 0.102 -0.005 0.021 0.007 0.004 0.0003
SB 0 -0.025 0.002 -0.009 0.003 -0.145 0.12 -0.049 -0.002 0.003 -0.009 0.0007
B.Y 0.003 0 0.012 0.009 -0.049 0.001 -0.009 0.669 -0.132 0.001 -0.039 0.0025
HI 0.006 0.083 -0.131 0.001 0.007 -0.004 0 -0.109 0.806 0.011 -0.013 0.0006
SL/p 0.006 0.085 -0.065 0.014 -0.013 -0.015 0.004 0.19 0.154 0.038 0.001 0.0018
S/S -0.001 0.064 -0.066 -0.004 -0.004 0.018 -0.057 -0.111 0.265 0.001 0.081 -0.0025
TSW 0.019 -0.022 -0.077 0.004 0.004 0.024 -0.058 -0.078 0.056 -0.014 0.04 -0.005
94
negatively (-0.17) and maximum indirect effect (0.10) via secondary branches on seed
yield.Yield can be increased by reducing the number of primary branches. Basalma (2008)
also indicated similar results.Positive direct effect (0.12) of secondary branches on seed yield
was noted and the highest indirect positive effect (0.003) via number of siliqua per plant.
Green biomass had positive direct effect (0.67) on seed yield and the highest indirect positive
effect (0.01) via days 50% siliqua formation. Number of siliquae per plant has direct positive
effect (0.03) on seed yield and highest indirect positive effect (0.19) via biological yield on
seed yield. The results were supported by the previous findings of Shabana et al. (1990); Ali
et al. (2002); Tusar-Patra et al. (2006); Tuncture and Ciftci (2007); Hashmei et al. (2010) and
Zare (2011).
Seed per siliqua presented direct effect (0.08) positively on seed yield whilest
maximum indirect direct effects (0.26) positvely via harvest index. Negative direct effect of
100 seed weight (-0.005) was recorded for seed yield. Results indicated that by increasing the
number of seed per siliqua will increase in yield and vice versa. Ali et al. (2002); Tuncture
and Ciftci (2007) and Zare (2011) reported positive direct effect of number of seed per plant.
On the other hand Belete (2008) reported negative direct effect of 1000 seed weight on seed
yield.
4.18 Correlation and Path Analysis for Quality Traits for Intraspecific Crosses
Oil content has positive and significant correlation with protein while protein content had
considerable positive correlation with glucosinolate and negative significant correlation with
Table 4.19 Phenotypic and Genotypic correlation coefficients for quality traits.
Qualitative traits Oil content
(%) Protein content
(%)
Glucosinolate
Content (%)
Oleic acid
(%) Erucic acid
(%)
Oil content
(%) 1 0.266* -0.242 -0.03 0.203
Protein content
(%) 0.167 1 0.621** -0.5796** 0.618**
Glucosinolate
contents
(%) -0.23 0.510** 1 -0.579** 0.510**
Oleic acid
(%) -0.046 -0.455** -0.564** 1 -0.807**
Erucic acid
(%) 0.189 0.509** 0.507** -0.777** 1
95
oleic acid and significant positive correlation with erucic acid (Table 4.19). Glucosinolates
has positive and significant correlation with erucic acid and negative with oleic acid. Oleic
acid was negatively correlated with erucic acid. Similar relationship between oil and protein
content was not supported by Alemeyehu and Becker (2000), who reported negative
correlation. Azam et al. (2013) observed that Protein content had positive and significant
correlation with erucic acid and non-significant with glucosinolate content. Abideen et al.
(2013) also reported positive non-significant association between glucosinolate and erucic
acid content. Similar findings were supported by Krzymanski and Downey (1969) that oleic
acid had negative association with erucic acid. Protein content has direct positive effect (.09)
and highest indirect effect (.004) via erucic acid on oil content (Table 4.20). Glucosinolate
contents have direct negative effect (-0.04) and indirect effect (0.017) was positive via
protein contents. Oleic has direct positive effect (.076) and Erucic acid has direct negative
effect (-0.072) on oil contents. Tahira et al.,(2015) also noted that negative direct effect of oil
contents on erucic acid and indirect effects via total glucosinolate (-0.167) and oleic acid (-
0.088) were also negative. Glucosinolate had positive direct effect (0.38) on erucic acid.
*=significant (p<0.05);**=highly significant (p<0.01
Table 4.20 Phenotypic and Genotypic path analysis for quality traits
Quality traits Protein contents
(%) Glucosinolate
Content (%) Oleic acid
(%) Erucic acid
(%)
Protein contents
(%) 0.094 -0.007 -0.002 0.004
Glucosinolate contents
(%) 0.017 -0.04 0.01 -0.048
Oleic acid
(%) -0.003 -0.005 0.076 0
Erucic acid
(%) -0.006 -0.027 0 -0.072
96
4.19 Interspecific Genetic Variability
Genetic variation above or at the species level is created by the evolutionary forces and
variation at species level is more important for cultivation. Creation of new species and
variability within the species is generated by human interference according to his need
(Sharma, 1989).
4.19.1 Mechanism of Variation
There are four processes that bring the changes in the wild species making them suitable for
cultivation (Simmonds, 1962).
1) Gene recombination
2) Creation of novel variation
3) Differences in reproduction
4) Isolation mechanism
These all processes are necessary to bring up and speed up the changes in species.
These changes occur more quickly in cultivated species than in natural species. So the intra-
specific variability generated in this way appears at lower and higher level. Intra population
variation i.e. lower level variation between genotypes that occurs due to mutation or
recombination of major genes and inter population variation or higher level due to change in
gene frequency that is the accumulation of lower level variation. The variability created for
gene frequency does not originate only from mutation. Two other forces i.e. random variation
fixation and role of natural selection are also responsible for creation of new genetic
variability (Stebbins, 1950). Inter population variation that occurs due change in gene
frequency is of great importance in evolution and intra population variation plays its role in
plant breeding (Sharma, 1989).
Interspecific hybridization of B.campestris was also done to obtain probable
introgressions from B. napus and B. juncea for the ultimate goal of high yielding and good
quality lines for further breeding program.The data recorded for different agronomic
parameters were analyzed to confirm differences among the genotypes obtained through
introgression. Mean squares values from the analysis of variance for indicated traits of
genotypes have been shown (Table 4.21).Highly significant differences among Brassica
genotypes for all the traits studied. Substantial variability noted among the genotypes used in
the present studies for various i.e. phenological, morphological, yield and yield traits was
97
similar with finding like (Gosh and Gulati, 2001; Ali et al., 2003; Sadaqat et al., 2003;
Fahratullah et al., 2004; Aytac and Kinaci, 2009; Dar et al., 2010; Sabghnia et al., 2010;
Marjenovic -Jeromela et al., 2011; Singh et al., 2012 and Arifullah et al., 2013).
The sum of squares values of Brassica genotypes for traits studied were partitioned into
parents, crosses and parent vs. crosses, revealed highly significant differences among
themselves except for 100 seed weight against parent vs. crosses showed none significant
differences for it (Table 4.22). The sum of square values for crosses was further divided into
line, testers, line×tester and line vs. tester. Highly significant differences are present among
lines and testers, for these traits. However lines vs. tester’s difference were non-significant
for the values for primary branches and harvest index. Results were in accordance with (Zare
and Sharahfzadeh, 2012; Abideen et al., 2013; Ali et al., 2003 and Dar et al. 2013).
Singh et al. (2014) and Parveen et al.( 2015) also reported non-significant variability
for days to 50% flowering initiation, primary branches per plant and seed per pod.
Nevertheless their expression was affected by the environment. Evaluation of genetic
variability for economic important traits in rapeseed and mustard is a fundamental purpose in
breeding Therefore characters of economic importance such as plant height, secondary
branches, harvest index and green biomass were studied and significant differences were
noted for all sources of variation (Table 4.22). Variation for these traits in rapeseed and
mustard was also examined and significant and none significant differences were noted by
earlier workers Huehn (1993); Ali et al. (2003); Sadaqat et al. (2003); Farhatullah et al.
(2004); Cui and Yu (2005); Sincik et al. (2007); Dar et al. (2010); Synrem et al. (2014); Iqbal
et al. (2014) and Mekonen et al. (2015)
Yield and yield related parameters showed significant mean square values for the
breeding material used in this study. Yield is the most important trait for any outcome. The
improvement in yield related traits indirectly is the improvement in yield itself. Seed yield is
a complex of population density, number of siliqua, seeds per siliqua and seed weight
(Dipenbrock, 2000). Oilseeds Brassicas have significant and highly significant variation for
yield and yield related traits (Kang et al., 2013; Nasim et al., 2014; Ullah et al., 2015; Naznin
et al., 2015 and Halder et al., 2015).
98
**
Significant at 5% and 1% levels of probability
DFI stands for days to flowering initiation, D50%F for days to 50%flowering, D50%SF for days 50%
siliqua formation, DM for days to maturity, PH for plant height, PB for primary branches, SB for secondary
branches, GB for green biomass yield, HI for harvest index, S/PL for siliquae per plant, S/S for seed per siliqua,
TSW for 100 seed weight, Y/P for yield per plant
Table 4.21 Mean square values associated with different plant traits
Source of variation Replications Genotypes Error
Degree of freedom 2 18 36
Ph
en
olo
gic
al
tra
its
Days to flowering initiation 24.86 743.53** 10.79
Days to 50% flowering 56.44 846.87** 9.42
Days to 50% siliqua formation 72.07 1001.22** 6.5
Days to maturity 121.42 2182.76** 12.5
Mo
rp
ho
log
ica
l tra
its
Plant height 405.28 4702.2** 217.61
Primary branches 0.28 89.81** 2.32
Secondary Branches 3.07 1063.57** 7.74
Green biomass 247.7 6127.3** 80.78
Harvest index 35.66 996.1** 14.84
Yie
ld
rela
ted
tra
its
Number of siliquae per plant 44536 3758445** 24216
Number of seed per siliqua 0.59 233.96* 0.94
1000 seed weight 0.002 0.03** 0.039
Seed yield per plant 1.19 1689.41** 5.93
Qu
ality
rela
ted
tra
its Oil contents (%) 0.03 75.11** 1.79
Protein content (%)
1.42 7.17** 1.77
Glucosinolates (%) 21.32 2788.16** 3.61
Oleic acid (%) 22.8 360.39** 0.23
Erucic acid (%) 0.2 465.65** 1.37
99
Table 4.22 Mean square values from analysis of variance for various traits of inter-specific crosses of Brassica campestris with
its relative Brassicas
Phenological traits Morphological traits Yield related traits
Source of
Variation DF DFI D 50% F
D 50%
SF DM PH PB SB GB HI SL/p S/S TSW Y/P
Replication 2 24.86 56.44** 72.07** 121.42** 405.28 0.28 3.07 247.7 35.66 44535.84 0.59 0.0002 1.19
Genotypes 18 743.53** 846.87** 1001.22** 2182.76** 4702.22** 89.81** 1063.57** 6127.30** 996.16** 3758444.99** 233.96** 0.0332** 1689.41**
Parents 6 1327.98** 1506.38** 1633.08** 5048.30** 4703.60** 105.63** 902.71** 2729.65** 692.56** 806964.83** 70.05** 0.0241** 1340.14**
Crosses 11 488.01** 552.31** 723.91** 706.51** 4580.60** 83.18** 1109.89** 8284.91** 1166.77** 4340388.55** 161.78** 0.0412** 1967.62**
P Vs C 1 47.52** 130.02** 260.59** 1228.20** 6031.72** 67.86** 1519.17** 2779.43** 940.95** 15065946.86** 2011.38** 0.0002 724.71**
Lines 2 1501.00** 1227.25** 1648.11** 1061.86** 9854.19** 131.25** 2997.25** 285.25** 1231.42** 7300989.08** 58.33** 0.0265** 1867.03**
Tester 3 398.99** 494.10** 439.06** 941.29** 857.37** 27.07** 173.81** 18805.26** 664.67** 2373917.73** 24.77** 0.0074** 1285.24**
L × T 6 194.85** 356.44** 558.26** 470.68** 4684.34** 95.21** 948.81** 5691.29** 1396.28** 4336757.12** 264.78** 0.0630** 2342.33**
L vs T 1 215.43** 217.29** 154.00** 69.14** 2006.04** 0.25 287.15** 2674.77** 517.06 132160.48** 162.88** 0.0546** 1458.25**
Error 36 10.79 9.42 6.5 12.5 217.61 2.32 7.74 80.78 14.84 24216.06 0.94 0.0004 5.93
*, ** Significant at 5% and 1% levels of probability DFI stands for days to flowering initiation, D50%F for days to 50%flowering, D50%SF for days 50% siliqua formation, DM for days to maturity, PH for plant
height, PB for primary branches, SB for secondary branches, GB for green biomass yield, HI for harvest index, S/PL for siliquae per plant, S/S for seed per
siliqua, TSW for 100 seed weight, Y/P for yield per plant
100
4.20 Mean Comparisons for Various Plant Traits of 12 Interspecific Crosses of
B.campestris
4.20.1 Phenological Traits
The average performance of 12 hybrids of B. campestris for eighteen traits used in line×tester
analysis (Table 4.23) Number of days to flower initiation were ranged from 36 (UAF11 ×Toia)
to 83 (Shora×Napus1).Five hybrids were early maturing as they got less than 67days for
flowering initiation. The number of days to 50% flowering initiation were varied from 43 to
92.The number of days for 50% siliqua formation were ranged from 49 (UAF11 ×Toria) to 1o5
(Napus2×Toria).The number of days to maturity were varied from 115 (UAF11 ×Toria) to 169
(Napus2×Toria). Out of 12 hybrids 6 hybrids were below in average for days to maturity
(142).Mostly agronomic traits show quantitative variation. These traits are controlled by multiple
genes or depend on environment. Only 60% phenotypic variation is contributed through genetic
effects. QTL numbers, interacting loci and aligned functional genes analysis showed that there
is an intricate genetic network that controls flowering period in B. napus (Long et al., 2007).
Remarkable variation for days to 50% flowering was reported for rapeseed. The range for
variation was from 61.67 to133.70 days (Gosh and Gulati, 2001; Sadaqat et al., 2003;
Farhatullah et al., 2004 and Dar et al., 2010). Similarly evaluation of canola version genotypes of
B. napus under drought and normal recommended, irrigation conditions, significant results were
noted under irrigated condition for plant traits studied, nevertheless the results were none
significant under drought conditions for 50% flowering, 50% siliqua formation and 50%
maturity days (Sadaqat et al., 2003) .
4.20.2 Morphological Traits
Maximum plant height was 208 cm for cross (Shora×Juncea-I) and minimum was 88 cm for
cross (UAF-11×Juncea).Variation for number of primary branches ranged from 6 (UAF-
11×Juncea) to 18 (Napus-II × Juncea). Four hybrids had more number of secondary branches
than average. For green biomass 4 hybrids had more quantity than that of average. The average
harvest index (%) was (39.83). The range for harvest index varied from 1.87 (Napus II×Toria)
to 56 (UAF-11×Toria)
Significant and non-significant differences have been noted for these morphological
traits by different researchers. Nasibullah et al. (2015) and Mekonnen et al. (2015) found
difference significantly in brassica for plant height, primary branches/plant, and secondary
branches/plant, biomass/plant and harvest index. The range of variability of height in spring
101
rapeseed had been reported from 69.5 to 180 cm (Ali et al., 2003; Sadaqat et al., 2003;
Fahratullah et al., 2004; Sincik et al., 2007; Dar et al., 2010; Sabaghni et al., 2010; Zareand
Sharafzadeh, 2012; Synrem et al., 2014 and Iqbal et al., 2014). Shehzad and Fahratullah (2012)
also reported significant differences in interspecific crosses of genus Brassica for plant height.
4.20.3 Yield Related Traits
For number of siliquae per plant, five hybrids got maximum number of siliqua 4166.67
(1072×Torch) and minimum 52 (UAF-11×Juncea1).A good degree of variation was noted for
number of seed per plant. The range of variation was from 0.73 (Shora×1072) to 22.93 (Napus
2×Napus1).Thousand seed weight expressed good variation. The maximum range was 0.43 gm
(UAF11×Toria) and minimum was 0.11gm (UAF11×Juncea1). For yield six hybrids showed the
value above from the average value. The range for these values from 3.19 gm per plant
(Napus2×Toria) to 80.27 gm (Napus2×Toria).
Oilseed brassicas have significant and highly significant variation for seed yield and yield
related traits such as number of siliquae/plant, number of seeds/siliqua, 1000-seed weight and
yield/plant ( Ghosh and Gulati, 2001; Ali et al., 2003; Kang et al., 2013 and Nasim et al., 2014).
Interspecific hybrids also revealed significant variations for seed yield/plant and 100-seed
weight (Ullah et al., 2015). Nevertheless non-significant results have also been reported by (Zare
and Sharahfzadeh, 2012).
4.20.4 Quality related traits
Interspecific hybrids showed good variation for oil contents and ranged from 34.3
(Napus2×Toria) to 49.2(%) (Napus2×Napus1).For protein, the content ranged from 22.6 (%)
(Napus2×Juncea1) to 28.9 (%) (UAF11×Juncea1).Variation for glucosinolates was from 35.5
(UAF11×Napus1) to 148.5 (UAF11×Juncea). Oleic acid (%) exhibited lot of variation and its
range was from 4.8 (Shora×Napus1) to 49.1 (Napus2×juncea1). A considerable amount of
variation was observed for erucic acid with ranged from 32.0 (Napus2×Juncea) to 60.1
(Napus2×Toria).
Oil content is a composite trait that is under control of many genes and affected by the
environment (Si et al., 2003). By increasing one percent in oil means increasing 2.3 to 2.5%
yield (Wang, 2004). Derivative hybrids of interspecific population showed highly significant
variation for oil contents, oleic acid, linolenic acid, erucic acid and glucosinolates while protein
showed nonsignificant results (Khan et al., 2008).
102
Table 4.23 Mean comparisons associated with different plant traits of interspecific crosses
Hybrids Phenological traits Morphological traits
DFI D 50% F D 50% SF DM PH PB SB GB HI
UAF11×Toria 36.33 43.67 49.67 115.33 169 16 18 123.33 56.45
UAF11×1072 52.33 63.00 74.67 137.00 193 15.33 51.67 175.67 29.6
UAF11×Napus1 67.33 84.67 95.33 130.67 140.00 10.00 17.67 73.00 51.42
UAF11×Juncea 61.00 71.33 81.33 146.67 88.00 6.67 6.67 17.00 54.64
Napus2×Toria 74.33 86.33 96.00 151.33 208.33 8.67 30.00 161.67 49.85
Napus2×1072 65.00 73.67 87.00 141.00 196.33 9.67 30.33 64.33 47.75
Napus2×Napus1 75.00 80.00 87.33 131.00 205.67 16.67 12.67 81.67 44.69
Napus2×Juncea 74.67 82.67 94.67 158.67 200 18.00 33.00 50.33 29.58
Napus2×Toria 77.33 87.33 105.33 169.00 204.33 18.33 65.67 168.33 1.87
Shora ×1072 64.67 72.00 81.00 137.00 142.33 12.67 31.67 65.33 19.46
Shora ×Napus1 83.00 92.33 103 134.33 180.33 16.33 60.33 47.00 20.74
Shora ×Juncea 74.00 88.00 103 162.33 228 25.67 51.33 72.33 71.95
LSD 5% 6.276 5.624 4.017 6.66 25.471 2.462 4.593 16.502 6.591
Continued
Yield related traits Quality related traits
Hybrids
SL/p S/S TSW Y/P O (%)
PRT
(%)
GSL
(%)
OA
(%)
EA
(%)
UAF11×Toria 1402 14.87 0.43 69.57 39.2 26.5 118.7 35.8 54.3
UAF11×1072 1758.67 14.73 0.31 51.97 42.9 26.5 108.5 37.4 60
UAF11×Napus1 924.67 0.73 0.21 37.42 38.8 25.3 35.5 46.1 46.5
UAF11×Juncea 52.33 12.47 0.11 9.13 44.4 28.9 148.5 32.5 60
Napus2×Toria 1402 7 0.34 80.27 44.7 27.2 95.3 38 60
Napus2×1072 3853.33 5.8 0.43 30.43 44.6 25.7 108.4 31.6 60
Napus2×Napus1 2790 22.93 0.38 36.33 49.2 24.7 81.4 42.1 33.5
Napus2×Juncea 2020 3.1 0.22 11.5 41.7 22.6 63.1 49.1 32
Napus2×Toria 4166.67 4.17 0.16 3.19 34.3 27.3 102.9 20.3 60.1
Shora ×1072 924.67 0.73 0.21 12.37 39.5 26.7 35.7 47.1 47.3
Shora ×Napus1 2249.67 3.23 0.21 9.7 35.8 26.9 81.2 4.8 38.2
Shora ×Juncea 1449 17.8 0.45 52.03 44.2 28.5 148.7 32.2 59.3
LSD 5% 293.03 1 0.03 3.84 2.0355 1.277 3.1471 2.417 2.0835
103
4.21 General Combining Ability Estimates of Interspecific Crosses of B. campestris
Combining ability is the capacity of individuals to transfer the better performance to their
offspring. Progeny test can be performed to know the combining ability of the traits that are
controlled by the recessive genes. Following are the results for the combining ability studied
in inter specific crosses of Brassica campestris.Variations for general combining ability
estimates were studied among 3 lines of B. campestris, B. napus and B. juncea one for each
and 4 testers, two for B. campestris, one for B.napus and one for B.juncea for thirteen
quantitative traits to identify the better parents. Results for GCA estimate (Table 4.24).
Minimum number of days for flowering and maturity are required to develop the short
duration cultivars. All three species showed different behavior towards the days to flowering
initiation. UAF11 (B. campestris) was the best combiner (-12.88) while Napus2 (napus)
(5.17) and Shora (B. juncea) (2.81) were poor general combiner for the flowering initiation.
UAF11 was good combiner (-11.44) while Napus2 (3.58) and Shora (7.83) were poor
combiner for 50% flowering, among testers, Toria (-4.42) was good combiner fallowed by
1072 (-6.42), while Napus1 (B. napus) (8.03) showed the lowest combining ability fallowed
by Juncea. Again UAF11 was good general combiner (-12.94) while Napus2 and Shora were
poor combiner for 50% siliqua formation while Toria (-4.53) followed by 1072 (-7.32) were
the goods tester. Napus1 (7.03) and Juncea (4.81) were the poor tester for GCA effects for
50% siliqua formation. UAF11 (-10.44) was the best general combiner among the lines for
days to maturity. Among the testers 1072 (-4.53) followed by Napus1 (-1086) were good
general combiner and juncea was the lowest for GCA effects. For plant height UAF11 was
good parent combiner line (-32.11) and Toria was poor tester line (14.28).Observations were
supported by Singh et al. (2010) and Synrem et al. (2015). The GCA effects for primary
branches the best combining line was Shora (3.75) and the poorest line was Napus2 (-1.25).
Juncea (2.28) was the best combining tester line. For secondary branches of GCA effects
Shora was the best combining line (18.75). The best tester combining line was Toria and
1072 (3.81, 3.81) and the lowest tester line was juncea (-3.75).
For biomass the results were non-significant, Toria showed highest value (59.44) for
GCA effects. UAF 11 (8.19) was the best combiner line for harvest index followed by
Napus2 (3.13) and the poorest line was Shora (-11.33). The best combiner tester line was
juncea (12.22). For number of siliqua per plant for the GCA effects Napus2 was the best
104
combining line (600.25) followed by Shora (281.42). Good tester line was Toria (407.47) for
number of siliqua per plant. The best combining line for number of seed per plant was
UAF11, (1.74) and best tester line was juncea (2.16). For 100 seed weight the best combining
line was Napus2 and the value for GCA effects was (.05) while 1072 was best combining
tester line (.03). For yield, UAF11 (8.36) was good general combiner followed by Napus2
(5.97). The good tester line was Toria (17.35) for 100 seed weight. The parents UAF11 and
Toria can be considered as superior parents in this study because they showed high per se
with positive and significant GCA effects for seed yield. Findings were similar to Parmer et
al. (2011) and Synrem et al. (2015). General combining ability was not predominant for
secondary branches while specific combining ability was significant for secondary branches
in Ethiopian mustard (Teklewold and Becker, 2005). Azizinia (2011) studied combining
ability and noted significant differences for plant height and number of lateral branches per
plant. Qian et al. (2003) reported significant negative and positive GCA effects for European
B. rapa and for Chinese B. rapa respectively that meant Chinese B. rapa might be an
important source for transferring favorable genes of green biomass yield.
4.22 Specific Combining Ability Estimates for Interspecific Crosses
General combining ability measures the additive gene action while specific combining ability
is the deviation from additive gene action. Following are the results for the specific
combining ability.
Specific combining ability estimtes of 12 Brassica campestris combinations with its
relative Brassicas (Table 4.25).Minimum number of days to flowering initiation is a required
trait of Brassica campestris to fit for cropping pattern so that farmer may get it as a cash
crop. The crosses viz., UAF11×Toria (campestris×campestris) and Napus2×Napus1
(napus×napus) are the best, showing negative and significant specific combining ability
effects of -11.53 and -5.28 for days to flowering initiation respectively.Cross combinations
UAF11×Toria followed by Napus2×Napus1 (napus×napus) and Shora×1072
(juncea×campestris) showed desirable remarkable significant negative SCA effects for days
to 50% flowering. Same combinations showed significant and negative specific combining
ability effects for days to 50% siliqua formation. UAF11×Toria, Shora×1072 and
Shora×Napus1 (juncea×napus) showed highly significant and negative specific combining
ability effects for days to maturity. These crosses combinations can be exploited to find early
105
maturing genotypes in subsequent generations. Cross combination UAF11 × Juncea
(campestris × juncea) and Shora × 1072 (juncea × campestris) showed negative and
significant specific combining ability for plant hight. Cross combination UAF11 × 1072,
(campestris × campestris), Shora × Juncea (juncea × juncea), Napus2 × Napus1 (napus ×
napus) and Napus2 × Juncea (napus × juncea) showed good SCA for number of primary
branches. For secondary branches combinations UAF11 × 1072, Shora × Napus1 (juncea ×
napus), Napus2 × Juncea (napus × juncea), Shora × Toria (juncea × campestris) showed
highly positive and significant specific combining ability effects. For green biomass and
harvest index the combinations UAF11 x 1072 (68.31) and Shora × Juncea (juncea × juncea)
showed positive andhighly significant combining ability effects Shora × Toria (juncea ×
campestris), Napus2 × 107 (napus × campestris), UAF11 × 1072, (campestris × campestris)
were good specific combiner for number of siliqua per plant. Cross combinations
Napus2×Napus1, Shora×Juncea and UAF11×1072 showed highly positive effects for number
of seed per plant. For 100 seed weight the combination Shora×Junce, UAF11×Toria and
Napus2×1072 showed highly and positive combining ability effects.The combination
Shora×Juncea (juncea×juncea), Napus1×Toria and UAF11×1072 showed maximum specific
combining ability for yield.
Global acreage under oilseeds is increasing gradually. Therefore, it is major concerned
to study the combining ability of selected material or mode of inheritance of economic traits.
(Marjanović-Jeromela et al., 2007a) estimated GCA, SCA and, mode of inheritance of
quantitative traits in rapeseed. General combining ability was not predominant for secondary
branches while specific combining ability was significant for secondary branches in
Ethiopian mustard (Teklewold and Becker, 2005). The combining ability studies to identify
prominent hybrid combinations in B.napus. Significant differences were examined in
selected genotypes for plant height and number of lateral branches per plant (Azizinia,
2011). Significant differences were detected among GCA effects and SCA) effects
continuously for two years. Qian et al. (2003) indicated considerable negative GCA effects
for European B. rapa and significant positive GCA effects Chinese B. rapa that meant
Chinese B. rapa might be an important source for transferring favorable genes of biomass
yield.
106
Table 4.24 General combining ability estimated effects for various traits of interspecific crosses of B.campestris with its
relative Brassicas.
Phenological traits Morphological traits Yield related traits
Parents
(females
and males) DFI D 50% F D 50% SF DM PH PB SB GB HI SL/p S/S TSW Y/P
Lines
UAF11 -12.83 ** -11.42 ** -12.94 ** -10.44 ** -32.11 ** -2.50 ** -10.58 ** 5.58 8.19 ** -881.67 ** 1.74 ** -0.02 ** 8.36 **
Napus2 5.17 ** 3.58 ** 3.06 ** 2.64 * 22.97 ** -1.25 ** -7.58 ** -2.17 3.13 * 600.25 ** 0.74 ** 0.05 ** 5.97 **
Shora 7.67 ** 7.83 ** 9.89 ** 7.81 ** 9.14 * 3.75 ** 18.17 ** -3.42 -11.33 ** 281.42 ** -2.48 ** -0.03 ** -14.34 **
SE 1.07 0.96 0.68 1.14 4.34 0.42 0.78 2.81 1.12 49.96 0.17 0.01 0.65
Testers
Toria -4.42 ** -4.64 ** -4.53 ** 2.36 14.28 ** -0.17 3.81 ** 59.44 ** -3.78 ** 407.47 ** -0.29 0.02 ** 17.35 **
1072 -6.42 ** -7.53 ** -7.31 ** -4.53 ** -2.39 -1.94 ** 3.81 ** 10.11 ** -7.56 ** 262.81 ** -1.88 ** 0.03 ** -2.07 *
Napus1 8.03 ** 8.58 ** 7.03 ** -10.86 ** -4.28 -0.17 -3.86 ** -24.44 ** -0.88 72.03 0.00 -0.02 ** -5.84 **
Juncea 2.81 * 3.58 ** 4.81 ** 13.03 ** -7.61 2.28 ** -3.75 ** -45.11 ** 12.22 ** -742.31 ** 2.16 ** -0.03 ** -9.44 **
SE 1.24 1.11 0.79 1.31 5.01 0.48 0.90 3.25 1.30 57.68 0.20 0.01 0.76
*=significant (p<0.05);**=highly significant (p<0.01). DFI stands for days to flowering initiation, D50%F for days to 50%flowering, D50%F for days to 50%flowering, D50%SF for days 50% siliqua formation, DM for days to maturity, PH for plant height, PB for primary branches, SB for
secondary branches, GB for green biomass yield, HI for harvest index, S/PL for siliquae per plant, S/S for seed per siliqua, TSW for 100 seed weight, Y/P
for yield per plant
107
Table 4.25 Specific combining ability estimated effects for various traits of interspecific combinations of B.campestris with
its relative Brassicas
Traits Phenological traits Morphological traits Yield related traits
Crosses DFI D 50% F D 50% SF DM PH PB SB GB HI SL/p S/S TSW Y/P
UAF11 ×Toria -13.50 ** -17.36 ** -21.06 ** -19.44 ** 7.22 4.17 ** -9.31 ** -33.36 ** 12.20 ** -39.89 4.45 ** 0.14 ** 10.20 **
UAF11 ×1072 4.50 * 4.86 * 6.72 ** 9.11 ** 47.89 ** 5.28 ** 24.36 ** 68.31 ** -10.86 ** 461.44 ** 5.91 ** 0.02 12.02 **
UAF11 ×Napus1 5.06 * 10.42 ** 13.06 ** 9.11 ** -3.22 -1.83 * -1.97 0.19 4.28 -181.78 -9.97 ** -0.03 ** 1.24
UAF11 × Juncea1 3.94 2.08 1.28 1.22 -51.89 ** -7.61 ** -13.08 ** -35.14 ** -5.61 * -239.78 * -0.39 -0.13 ** -23.45 **
Napus2 × Toria 6.50 ** 10.31 ** 9.28 ** 3.47 -8.53 -4.42 ** -0.31 12.72 * 10.66 ** -1521.81 ** -2.42 ** -0.02 23.29 **
Napus2 × 1072 -0.83 0.53 3.06 * 0.03 -3.86 -1.64 0.03 -35.28 ** 12.35 ** 1074.19 ** -2.03 ** 0.06 ** -7.13 **
Napus2 × Napus1 -5.28 * -9.25 ** -10.94 ** -3.64 7.36 3.58 ** -9.97 ** 16.61 ** 2.61 201.64 13.22 ** 0.06 ** 2.54
Napus2 ×Juncea1 -0.39 -1.58 -1.39 0.14 5.03 2.47 ** 10.25 ** 5.94 -25.61 ** 245.97 * -8.77 ** -0.10 ** -18.70 **
Shora × Toria 7.00 ** 7.06 ** 11.78 ** 15.97 ** 1.31 0.25 9.61 ** 20.64 ** -22.86 ** 1561.69 ** -2.03 ** -0.12 ** -33.48 **
Shora ×1072 -3.67 -5.39 * -9.78 ** -9.14 ** -44.03 ** -3.64 ** -24.39 ** -33.03 ** -1.48 -1535.64 ** -3.88 ** -0.08 ** -4.89 **
Shora × Napus1 0.22 -1.17 -2.11 -5.47 * -4.14 -1.75 * 11.94 ** -16.81 ** -6.88 ** -19.86 -3.25 ** -0.03 * -3.78 **
Shora × Juncea1 -3.56 -0.50 0.11 -1.36 46.86 ** 5.14 ** 2.83 29.19 ** 31.23 ** -6.19 9.16 ** 0.22 ** 42.15 **
SE 2.14 1.92 1.37 2.27 8.68 0.84 1.57 5.63 2.25 99.91 0.34 0.01 1.31
*=significant (p<0.05);**=highly significant (p<0.01)
DFI stands for days to flowering initiation, D50%F for days to 50%flowering, D50%SF for days 50% siliqua formation, DM for days to maturity, PH for
plant height, PB for primary branches, SB for secondary branches, GB for green biomass yield, HI for harvest index, S/PL for siliquae per plant, S/S for seed
per siliqua, TSW for 100 seed weight, Y/P for yield per plant
108
4.23 Components of Genetic Variance of Inter-specific Combinations
Components of variances and degree of dominance for indicated traits in inter-specific
combinations of Brassica campestris with its relative Brassicas (Table 4.26). It is clear from
the table that specific combining ability was more important than general combining ability
and dominance variance than additive variance. Specific combining ability or dominance
variance was more important for all indicated traits. The specific combining ability has
positive association with heterosis. Degree of dominance was greater than 1 for days to
flower initiation, days to 50% flowering, days to 50 % siliqua formation days to maturity,
secondary branches, Biomass, harvest index, number of siliqua per plant and 100 seed
weight; all these traits can be utilized for heterotic effects of their genotypes.
Gene action is a way in which gene expresses itself in genetic population. A study on
gene action helps in selection of genotypes for the improvement of crops. With polygene,
gene action is a four types, additive, dominance, epistasis and over dominance (Sleper and
Poehlman, 2006). The nature and magnitude of gene action analysis and inheritance of some
selected genotypes of Brassica rapa (Toria) for phonological and yield traits was studied by
(Rahman et al., 2011) who indicated that both additive as well as dominance components
were utmost for inheritance of all the traits in Brassica campestris.
The magnitude of dominance was higher than the additive component for all the traits
except days to maturity, number of siliqua per plant that means dominance component had a
predominant role in the inheritance of these traits. On the other hand days to flowering, days
to maturity, number of seeds per siliqua, harvest index and oil content showed the values in
negative direction, showing the excess of recessive genes for these traits. Both additive and
non additive gene actions were important in controlling days to 50% flowering, seed yield
per plant. Additive gene action was important for the expression of days to 90% maturity,
number of seeds per pod and 1000 seeds weight.
Non-additive gene actions were important in controlling the expression of number of
pods per plant (Bggett and Kean, 1989). Gupta et al. (2010) verified of high heterotic crosses
and noted that GCA and SCA variances were significant for days for days to 50% flowering,
days to maturity, 1000-seed weight and seed yield per 100 siliquae. The variance of GCA
was higher for days to 50% flowering, maturity and 1000-seed weight, while the variance of
SCA was higher in seed yield and other traits studied.
109
4.24 Contribution (%) of Lines, Testers and Their Interactions for Various Traits of
Interspecific Combinations
A line×tester analysis of interspecific combinations with seven genotypes was adopted, three
were used as lines and four were used as tester to get the relative part of each line and its
interactions with other to the whole variance for various traits studies.The relative
contribution of each line and its interaction for thirteen traits (Table 4.27).
It is clear from the table that lines made an important contribution towards all these
traits. The maximum contribution of lines was 55.92% for days to flower initiation and for
secondary branches 49.10 %.Minimum contribution was for biomass and seed per siliqua
showing predominant maternal effect for these traits. The contribution of tester was higher
for biomass 61.91% fallowed by days to maturity 36.34%. It showed preponderance of
paternal effect for these traits. The contribution of their interaction was relatively higher for
all traits.
4.25 Heterotic manifestation of interspecific crosses of B. campestris with its relative
brassicas
All 12 hybrids were compared with mid parent and better parent for evaluation of heterosis.
Substantial amount for relative heterosis and heterobeltiosis were observed for yield and
other related characters studied. However, all crosses differed for the degree of heterosis
(Table 4.28).
The heterosis obtained from the hybridization between races or species gives an
excessive increase in size, weight and growth rate in the interspecific or inter racial hybrids.
The races used in hybridization cannot be considered as inbred (Sherma, 1989). Such type of
heterosis was called luxuriance and hybrids are luxuriant (Dobzhansky, 1940). Luxuriance is
a pseudo heterosis. There is no continuation due to poor seed setting in luxuriant hybrids.
However creation of novel genotype or F1 is possible through inter-specific hybridization
which was unreal in nature.
4.25.1 Seed yield per plant
Only one hybrid out of 12 combinations indicated positive and remarkable relative heterosis
and heterobeltiosis (Table 4.28). Positive and considerable heterosis and heterobeltiosis is
preferred to choice the genotypes for the inclusion of further breeding program. The aim of
the heterosis breeding is to attain the high yielding combinations with desirable quality traits.
110
From the present study the combinations with high heterosis and heterobeltiosis can be used
for the progress of better yielding verities. Significant and positive heterosis has been
reported by earlier worker ( Gupta et al., 2011; Verma et al., 2011; Patel et al., 2012; Kumar
et al., 2013; Kumar et al., 2014; Meena et al., 2014 and Synrem et al., 2015).
4.25.2 Days to Flowering Initiation
Out of total 12 crosses, three hybrids were identified for significant and negative relative
heterosis and heterobeltosis. These hybrids were Napus2 × 1072 (napus × campestris),
(12.56), (-17.62), Shora × 1072, (juncea × campestris), (-18.66), (-27.611) and Shora ×
Juncea (juncea × juncea (-10.66), (-17.16).
Negative heterosis is desirable feature for flowering in brassica crops.Early flowering
is a first step towards early maturing varities that prevents the yield losses and oil quality due
to high temperature. Grant and Beversdorf ( 1985) reported negative heterosis for flowering.
4.25.3 Days to 50% Flowering
Out of 12 hybrids only three illustrated considerable negative heterosis over mid parent and
batter parent. Among them Napus2×1072, Napus2×apus1 and Shora×1072 showed negative
significant relative heterosis (-13.50) and heterobeltiosis (-17.54), (-6.80), (-10.45), (-19.10),
(-25.77) respectively. Negative heterosis is preferred in B. campestris because it shows
earliness in flowering. The crosses showing earliness can be used for further breeding
program. Similar results were reported by Nassimi et al. (2006a). Synrem et al. (2015) also
described desirable and significant; negative heterosis for days to 50% flowering in Brassica
species.
4.25.4 Days to 50% Siliqua Formation
Out of 12 hybrids, three crosses confirmed important and negative relative heterosis and
heterobeltiosis for days to 50% siliqua formation. The three above mentioned crosses for
50% days to flowering showed negative and significant heterosis. For early maturing
cultivars negative heterosis for 50% days to siliqua formation is advantageous character.
4.25.5 Days to Maturity
About 4 hybrids illustrated remarkable negative heterosis for days to maturity. Hybrids viz.,
Napus2×Napus1, (-12.47) and (-12.67). Shora×1072,(-13.02), (-23.03), Shora×Napus2, (-
18.09), (-24.53) and Shora×Juncea, (-5.53), (-8.80).The comparison of nap and mur
111
cytoplasmic system , was investigated and hybrids in nap and mur cytoplasms showed
negative heterosis for days to maturity (Riungu and McVetty, 2004).
Early maturity is a useful trait in many plant species; however it is very important in
Brassica species because late maturity causes the yield losses and quality of oil due to high
temperature (Turi et al., 2006). Negative heterosis is valuable for Brassica in early maturity
(Nassimi et al., 2006; Yadava et al., 2012 and Synrem et al., 2015).
4.25.6 Plant Height
Out of 12 crosses, one showed negative heterosis for plant height. Values have been given in
the table 6. These crosses showed mid parent and batter parent heterosis for plant height.
Negative heterosis is desirable for plant height in Brassica species. Dwarf and medium
plant height resist to high wind velocity, logging and mechanical breakage. The heterosis
studied in oilseed rape for plant height was none significant. Negative values were also noted
for some crosses (Grant and Beversdorf, 1985). Significant and negative heterosis for plant
height was also been confirmed by many other researchers as Tyagi et al (2000); Pourdad
and Sachan (2003); Nassimi et al (2006) and Synrem et al (2015).
4.25.7 Primary Branches
Five crosses out of 12 showed positive relative heterosis and heterobeltiosis for primary
branches.These crosses were UAF11×Toria,(88.24), (65.52), UAF11×1072, (61.40), (58.62),
Shora×Toria, (144.44), (139.13), Shora×1072, (49.02), (35.71) and Shora×juncea (185.19),
(148.39) revealed positive and significant relative heterosis and heterobeltiosis.
Positive heterosis is desirable for Brassica species. Plant with more branches will be
vigorous and produces more yield. Positive and significant heterosis was reported for
primary branches by Gupta (2009). Similar illustrations were also described by Nasrin et al.
(2011) and Synrem et al. (2015). Maximum value for heterosis and heterobeltiosis was
identified for primary branches 24.25 vs. 12.30% in Brassica species by Nausheen et al.
(2015).
4.25.8 Secondary Branches
Six crosses out of 12 showed positive relative heterosis and heterobeltiosis for
secondary branches per plant. Crosses UAF11×Toria, (191.89), (58.82), UAF11×1072,
(342.86), (131.86), Shora×Toria, (398.73), (337.78), Shora×1072, (69.64), (41.79),
Shora×Napus-1 (82.83), (18.30) and Shora×Juncea (180), (136.92). Positive and significant
112
heterosis is desirable for secondary branches per plant. Vigorous plant will provide
opportunity for high yielding cultivar. Niranjana et al. (2014) and Synrem et al. (2015)
confirmed similar discriptions for secondary branches.
4.25.9 Green Biomass and Harvest Index
Only three hybrids showed significant and positive heterosis for green biomass shown in
table 7. Positive relative heterosis and heterobeltiosis is desirable for high yielding cultivar.
The combination UAF11×1072 showed significant positive heterosis and heterobeltiosis
(138.46), (58.26), 1072×UAF11 (166.48), (90.94), Shora×1072 (201.49*), (124.44) while
three, Napus2×1072 (58.83), (52.75), Napus2×Napus1 (29.89), (19.01), Shora×Juncea
(314.72), (282.19) crosses depicted positive and considerable heterosis for harvest index.
Usage of plant biomass plays an important role for animal hay and biogas production.
Ofori et al. (2008) studied the heterosis in B.rapa for fresh biomass, dry matter content dry
biomass.The average value of hybrids was greater 7.6%, 5.9% than parents for fresh biomass
and dry biomass while dry matter content was greater 1.4% in parents.The heterosis can be
increased up to thirty percent.
4.25.10 Number of Siliquae and Seed per Siliqua
Five hybrids confrmed positive significant heterosis for number of siliqua per plant and all
were none significant for number of seed per plant (Table 4.22). For both traits positive and
significant heterosis is advantageous for the development high yielding genotypes. Our
results were partially similar reported by Synrem et al. (2015).
4.25.11 Total seed weight (100 seed)
One hybrid showed positive and significant heterosis for 100 seed weight. Positive heterosis
is desirable quality for the development of high yielding genotype.
113
Table 4.26 Components of genetic variance of inter-specific combinations
Traits Phenological traits Morphological traits Yield related traits
Genetics
Components DFI D 50% F D 50% SF DM PH PB SB GB HI SL/p S/S TSW Y/P
Cov H.S(line) 108.85 72.57 90.82 49.27 430.82 3.00 170.70 -450.50 -13.74 247019.33 -17.20 0.002 -39.61
Cov H.S(tester) 22.68 15.30 -13.24 52.29 -425.22 -7.57 -86.11 1457.11 -81.29 -218093.27 -26.67 -0.01 -117.45
Cov F.S 223.97 224.37 289.68 266.32 1636.73 27.64 452.99 2684.58 364.07 1546817.38 40.02 0.01 614.19
VAR OF GCA 12.65 8.45 7.15 10.17 -4.48 -0.52 6.95 111.88 -9.90 156.65 -4.44 0.0001 -16.16
VAR OF SCA 60.37 115.14 184.21 151.74 1486.03 31.03 313.82 1865.44 460.38 1435603.69 88.14 0.02 779.06
IF F=0 ; A 50.58 33.80 28.58 40.69 -17.90 -2.08 27.79 447.53 -39.60 626.60 -17.77 0.0001 -64.66
IF F=0 ; D 241.49 460.54 736.84 606.95 5944.11 124.13 1255.27 7461.75 1841.51 5742414.76 352.57 0.08 3116.25
Degree Dominance
{α2D
/α2A } ½
2.18 3.69 5.07 3.86 0.00 0.00 6.72 4.08 0.00 95.73 0.00 28.28 0.00
*=significant (p<0.05);**=highly significant (p<0.01)
Table 4.27 Contribution (%) of lines, testers and their interactions for various traits of B. campestris
Traits Phenological traits Morphological traits Yield related traits
Parents and
Interactions DFI D 50% F D 50% SF DM PH PB SB GB HI SL/p S/S TSW Y/P
Lines 55.92 40.40 41.39 27.33 39.11 28.69 49.10 0.63 19.19 30.58 6.56 11.70 17.25
Testers 22.30 24.40 16.54 36.34 5.10 8.88 4.27 61.90 15.54 14.92 4.18 4.89 17.81
L x T 21.78 35.20 42.06 36.34 55.78 62.43 46.63 37.47 65.27 54.50 89.27 83.41 64.93
DFI stands for days to flowering initiation, D50%F for days to 50%flowering, D50%SF for days 50% siliqua formation, DM for days to maturity, PH for
plant height, PB for primary branches, SB for secondary branches, GB for green biomass yield, HI for harvest index, S/PL for siliquae per plant, S/S for seed
per siliqua, TSW for 100 seed weight, Y/P for yield per plant
114
Table 4.28a Heterotic manifestation for various traits of B. campestris with its relatives
Traits Phenological traits
DFI D 50% F D 50% SF DM
Crosses MP BP MP BP MP BP MP BP
UAF11×Toria 0.93 -5.22 3.15 -6.43 -1.65 -9.70 * 51.09 ** 46.61 **
UAF11 ×1072 -3.09 -24.88** -1.31 -22.22** -0.22 -21.13** 27.05 ** 0.00
UAF11×Napus1 24.31 ** -3.81 31.27 ** 2.83 28.54 ** 2.14 14.29 ** -12.89**
UAF11×Juncea1 6.40 -20.09** 9.74 ** -14.40** 10.91 ** -11.27** 20.05 ** -11.47**
Napus×Toria 31.95 ** -5.91 35.60 ** -3.36 31.21 ** -4.32 * 35.52 ** 1.34
Napus2×1072 -12.56** -17.72** -13.50** -17.54** -10.77** -13.29** -1.51 -5.58 **
Napus2×Napus1 0.67 -5.06 -6.80 ** -10.45** -9.81 ** -12.96** -12.47** -12.67**
Napus2×Juncea1 -3.86 -5.49 -4.25 -7.46 * -1.39 -5.65 ** 0.74 -4.23 *
Shora×Toria 25.75 ** -13.43** 29.38 ** -9.97 ** 39.21 ** -0.00 34.13 ** -5.06 **
Shora×1072 -18.66** -27.61*8 -19.10** -25.77** -19.00** -23.10** -13.02** -23.03**
Shora×Napus1 4.18 -7.09 * 2.97 -4.81 3.69 * -2.22 -18.09** -24.53**
Shora×Juncea1 -10.66** -17.16** -2.40 -9.28 ** 4.57 * -2.22 -5.53 ** -8.80 **
115
Table 4.28b
Morphological traits
PH PB SB GB HI
MB BP MB BP MP BP MB BP MP BP
12.42 ns -0.59 88.24 ** 65.52 ** 31.98 ** -7.97 67.04 ** 11.11 31.98 ** -7.97
42.79 ** 38.19 ** 61.40 ** 58.62 ** -35.75 ** -51.73 ** 138.46 ** 58.26 ** -35.75 ** -51.73 **
-11.95 -25.27 ** -37.50 ** -55.22 ** 4.00 -16.16 ** -31.88 ** -34.23 ** 4.00 -16.16 **
-41.46 ** -48.24 ** -33.33 ** -35.48 ** -41.18 * -69.23 ** -83.36 ** -84.68 ** 41.53 ** -10.92 *
8.23 -3.10 -34.18 ** -54.39 ** 13.92 -27.42 ** 166.48 ** 90.94 ** 79.75 ** 59.46 **
10.71 -8.68 -31.76 ** -49.12 ** -4.71 -26.61 ** 6.34 -24.02 ** 53.83 ** 52.75 **
2.24 -4.34 -19.35 ** -25.37 ** -72.56 ** -75.16 ** -13.12 -20.97 ** 29.89 ** 19.01 *
3.90 -6.98 22.73 ** -5.26 4.76 -20.16 ** -43.45 ** -46.07 ** 25.49 * -5.40
54.02 ** 20.20 ** 144.44 ** 139.13 ** 398.73 ** 337.78 ** 201.49 ** 124.44 ** -91.29 ** -92.26 **
21.13 * 1.91 49.02 ** 35.71 ** 69.64 ** 41.79 ** 17.37 -12.89 -21.60 -36.86 **
27.59 ** -3.74 8.89 -26.87 ** 82.83 ** 18.30 ** -47.29 ** -54.52 ** -26.43 ** -44.77 **
71.86 ** 34.12 ** 185.19 ** 148.39 ** 180.00 ** 136.92 ** -14.06 -22.50 ** 314.72 ** 282.19 **
DFI stands for days to flowering initiation, D50%F for days to 50%flowering, D50%SF for days 50% siliqua formation, DM for
days to maturity, PH for plant height, PB for primary branches, SB for secondary branches, GB for green biomass yield, HI for
harvest index, S/PL for siliquae per plant, S/S for seed per siliqua, TSW for 100 seed weight, Y/P for yield per plant
Table 4.28c
Yield related traits
SL/p S/S TSW Y/P
MP BP MP BP MP BP MP BP
54.15 ** 4.71 81.48 ** 81.48 ** 49.13 ** 11.21 * 81.48 ** 2.30 **
31.34 ** 31.34 ** 31.01 ** 31.01 ** 1.66 -20.69 ** 31.01 ** -23.58 **
21.16 -30.94 ** -29.98 ** -29.98 ** -41.51 ** -46.55 ** -29.98 ** -44.98 **
-95.74 ** -96.09 ** -78.59 ** -78.59 ** -64.32 ** -71.55 ** -78.59 ** -86.57 **
64.46 ** 14.45 358.67 ** 358.67 ** 13.81 ** -16.94 ** 358.67 ** 204.81 **
200.57 ** 187.78 ** 61.59 ** 61.59 ** 35.45 ** 3.23 61.59 ** 15.57 *
295.09 ** 127.76 ** -7.65 ** -17.90 ** 3.64 -8.06 * 11.45 * -6.52
72.28 ** 64.90 ** -85.91 ** -88.90 ** -32.64 ** -47.58 ** -47.33 ** -56.33 **
1023.60 ** 768.06 ** -77.68 ** -78.74 ** -23.20 ** -29.41 ** -71.03 ** -76.10 **
15.54 -30.94 ** -95.90 ** -95.94 ** -6.77 -8.82 0.27 -7.25
902.08 ** 759.75 ** -83.61 ** -85.12 ** -23.17 ** -34.37 ** -62.84 ** -75.04 **
109.75 ** 29.38 * 5.33 0.38 98.54 ** 97.10 ** 239.35 ** 200.19 **
116
4.26 Genetic Variability for Quality Traits
The measurement of genetic variability and inheritance pattern of quantitative and qualitative
traits are of prime importance in planning the programme efficiently and effectively (Shah et
al., 2015). For quality attributes inter-specific hybridization was also done of B. campestris
with its two close relative Brassicas. Mean squares values from the analysis of variance for
five traits (Table 4.29). Highly remarkable differences were noted for all traits studied among
the genotypes, parents (lines and testers), crosses, p vs. c and lines×tester interactions. The
sum of squares values were partitioned into parents, crosses and parent vs. crosses revealed
highly significant differences among themselves except for protein contents against parents
showed none significant difference among them and oil content against parent vs. crosses
showed none significant differences for them.Further partition for sum of square values for
line, testers, line×tester and line vs. tester. Highly significant differences are present among
lines and testers, for these traits. However protein contents were none significant against
tester and line vs. tester’s difference were none significant for the value of protein content
and oleic acid
Table 4.29 Mean square values for quality traits of interspecific hybrids
Quality related traits
Source of
variation DF
Oil contents
(%)
Protein contents
(%)
Glucosinolate
contents (%)
Oleic acid
(%)
Erucic acid
(%)
Replications 2 0.03 1.42 21.32** 22.80** 0.20
Genotypes 18 75.11** 7.17** 2788.16** 360.39** 465.65**
Parents 6 126.85** 2.51 601.14** 176.41** 422.54**
Crosses 11 53.71** 8.62** 4135.57** 460.56** 369.10**
P vs.C 1 0.11 19.31** 1088.86** 362.42** 1786.40**
Line 2 131.09** 17.22** 777.12** 686.22** 235.75**
Tester 3 26.12** 3.16 5083.19** 153.01** 625.70**
L×T 6 41.72** 8.47** 4781.24** 539.11** 285.25**
L vs T 1 63.30** 0.29 1563.52** 0.45 596.78**
Error 36 1.79 1.77 3.61 0.23 1.37
117
4.27 General Combining Ability Estimates of Inter-specific Crosses
Variation for general combing ability affects was studied among the lines and testers used in
inter-specific hybridization for quality traits to locate the best parent for further investigation
program. The results for general combining ability effects presented in Table 4.30. For oil
contents among lines Napus2 showed maximum general combining ability (3.44) effects and
among testers Juncea was the best general combiner (1.82). Regarding the protein, Shora
among lines showed maximum GCA effects while results were none significant for testers.
High proteins contents are valuable for Brassica meal therefore the general combiner should
be selected that have maximum general combining ability effects. All lines and testers
showed the GCA effects in positive or in negative directions for glucosinolate contents. For
glucosinolate contents parents Napus2, Shora, 1072 and Napus1 were found to be good
general combiner while parents UAF11, Napus2, 1072 and Juncea revealed good general
combining ability in term of oleic acid ,while Napus1 and Napus2 for low erucic acid.
Table 4.30 General combining ability estimates for quality attributes of interspecific
combinations
4.28 Specific Combining Ability Estimates for Quality Attributes
The estimates of specific combining ability effects showed that one inter-specific cross
combinations illustrated considerable positive SCA estimates for oil contents (Table 4.31).
Maximum significant and positive SCA effect was shown by Napus2×Toria (1.82) while for
Traits Quality related traits
Parents
(Males &females)
Oil contents
(%)
Protein contents
(%)
Glucosinolate
contents (%)
Oleic acid
(%)
Erucic acid
(%)
Lines
UAF11 -0.29 0.40 8.82 ** 3.18 ** 4.28 **
Napus2 3.44 ** -1.35 ** -6.95 ** 5.45 ** -4.57 **
Shora -3.15 ** 0.94 * -1.87 ** -8.63 ** 0.29
S.E 0.40 0.38 0.5 0.16 0.33
TESTERS
Toria -2.19 ** 0.60 11.65 ** -3.38 ** 7.19 **
1072 0.70 -0.11 -9.79 ** 3.94 ** 4.84 **
Napus1 -0.32 -0.77 -27.96 ** -3.74 ** -11.54 **
Juncea1 1.82 ** 0.28 26.10 ** 3.17 ** -0.49
S.E 0.46 0.44 0.58 0.18 0.39
118
protein maximum SCA effects were shown by inter-specific combination UAF11×Juncea
(1.8). All inter-specific cross combinations except one showed SCA effects in positive as
well as negative trend for glucosinolate contents (Table 4.31). The combinations with
negative SCA effects should be selected for nutritional usage. Maximum significant and
positive GCA effects were exhibited by the inter-specific combinations shora×1072 (17.07),
UAF11×Napus1 (11.93), Napus2× Juncea (5.72) and Napus2×Toria (1.21) while for erucic
negative and significant SCA effects were shown by the cross combination Napus2× Juncea
(-13.91), Shora×1072 (-8.74) and Shora ×Napus1 (-1.49).
Table 4.31 Specific combining ability estimates for quality attributes of interspecific
combinations.
Traits Quality related traits
Combinations Oil contents
(%)
Protein contents
(%)
Glucosinolate
contents
(%)
Oleic acid
(%)
Erucic acid
(%)
UAF11 × Toria 0.11 -0.90 4.24 ** 1.21 ** -8.08 **
UAF-11 × 1072 0.85 -0.19 15.48 ** -4.48 ** -0.06
UAF11 × Napus 1 -2.19 * -0.73 -39.32 ** 11.93 ** 2.82 **
UAF11 × Juncea1 1.23 1.82 * 19.59 ** -8.65 ** 5.31 **
Napus 2 × Toria 1.82 * 1.55 -3.36 ** 1.21 ** 6.44 **
Napus 2 × 1072 -1.17 0.76 31.12 ** -12.58 ** 8.79 **
Napus 2 × Napus1 4.52 ** 0.43 22.32 ** 5.66 ** -1.33
Napus × Juncea1 -5.16 ** -2.73 ** -50.07 ** 5.72 ** -13.91 **
Shora × Toria -1.92 * -0.64 -0.88 -2.41 ** 1.64 *
Shora × 1072 0.32 -0.57 -46.60 ** 17.07 ** -8.74 **
Shora × Napus1 -2.32 ** 0.30 17.00 ** -17.59 ** -1.49 *
Shora × Juncea1 3.93 ** 0.91 30.48 ** 2.93 ** 8.59 **
SE 0.80 0.75 1.01 0.31 0.67
4.29 Components of Genetic Variances
Genetic components of variance for indicated quality traits in interspecific crosses (Table
4.32). It is clear from the table that specific combining ability was more important than
general combining ability and dominance variance than additive variance. Specific
combining ability or dominance variance was more important for all traits. Degree of
dominance was greater than 1 for oil content (%) and protein content, 0 for glucosinolate and
119
oleic acid, and greater than 1 for erucic acid. All these traits that have more than 1 degree of
dominance can be utilized for Heterotic effects of their genotypes.
4.30 Contribution of Lines, Testers and Their Interaction for Quality Traits
A line×tester analysis of inter-specific crosses with 4 female lines and 3 male lines was used
to find the relative contribution of lines, testers and lines× testers to the total variance for
indicated quality traits. The results presented in Table 4.33. It is clear from the table that lines
made more contribution towards oil (44.37%), protein (36.33%) and oleic acid (27.09 %)
showing predominant maternal influence for these traits. Testers made more contribution for
glucosinolate (27.09%) and erucic acid (46.23%) indicating preponderance of paternal effect
for these two traits. Their interaction contribution was relatively higher for protein (53.66%),
glucosinolate (63.06%) and oleic acid (63.85%).
Table 4.33 Contribution (%) of lines, testers and their interaction for quality traits.
Traits Quality related traits
Genotypes
Oil
contents
(%)
Protein contents
(%)
Glucosinolate
contents
(%)
Oleic acid
(%)
Erucic acid
(%)
Lines 44.37 36.33 3.42 27.09 11.61
Testers 13.26 10.01 33.52 9.06 46.23
L×T 42.36 53.66 63.06 63.85 42.15
Table 4.32 Variance due to GCA, SCA, additive, dominance and degree of dominance
Traits Quality related traits
Genetic components Oil contents
(%)
Protein contents
(%)
Glucosinolate
contents
(%)
Oleic acid
(%)
Erucic acid
(%)
Cov H.S(line) 7.45 0.73 -333.68 12.26 -4.13
Cov H.S(tester) -1.73 -0.59 33.55 -42.90 37.83
Cov F.S 21.29 2.64 1190.66 154.18 125.76
VAR OF GCA 0.52 0.01 -27.85 -3.39 3.62
VAR OF SCA 13.26 2.26 1592.73 179.61 94.64
IF F=0 ; A 2.07 0.02 -111.41 -13.55 14.47
IF F=0 ; D 53.06 9.03 6370.91 718.42 378.55
Degree Dominance
{α2D
/α2A } ½
5.06 21.25 0.00 0.00 5.11
120
4.31 Heterotic manifestation of interspecific crosses for quality traits:
4.31.1 Oil Contents (%)
Heterotic manifestation for oil contents (Table 4.34). Out of 12 hybrid combinations 2
combinations showed relative heterosis and heterobeltiosis. The cross combination
Shora×1072 maximum value for relative heterosis and heterobeltiosis (12.28 and 7.93)
followed by the combination Napus2×Toria (8.99 and 5.35).
4.31.2 Protein Contents (%)
For protein contents combination UAF11×Juncea showed maximum heterosis and
heterobeltiosis (14.46 and 9.89).
4.31.3 Glucosinolate Content (µMolg-1)
Out of 12 inter-specific hybrids seven crosses depicted negative and remarkable heterosis for
glucosinolate. Maximum heterosis and heterobeltiosis was shown by combination
UAF11×Napus1 (-67.04, -68.36), Shora×1072 (-62.15, -67.58) and Napus2×Juncea (-37.73,-
44.78). Hybrid combinations with low glucosinolate content are desirable in rapeseed for
nutritional usage. Studies were confirmed by Priyamedha et al. (2016) who illustrated the
negative heterosis for glucosinolstes in Indian mustared (B. juncea)
4.31.4 Oleic Acid (%)
Only two combinations showed positive heterosis.Oleic acid is major enviable component of
Brassica oil.Therefore for getting improved Brassica varieties/lines positive levels of
heterosis and heterobeltiosis for oleic acid is considered. Cross UAF11×Napus1 showed
maximum relative heterosis (48.82) heterobeltiosis (34.76) followed by Napus2×Juncea
(19.03), (11.17) for oleic acid. Our results were in accordance with Ali et al. (2015) who
reported the maximum positive (40.30%) value for cross NUM123xNUM113 and
heterobeltiosis was positive and significant for 8 crosses.
4.31.5 Erucic Acid (%)
Erucic acid content of Brassica oil is an undesirable component that makes the oil unsuitable
for human diet. Negative heterosis and heterobeltiosis is valuable for erucic acid. Out of 12
crosses, 1 cross showed significantly negative relative heterosis and heterobeltiosis ( -27.46, -
27.57). Similar discriptions were also illustrated by Patel and Sharma (1999); Singh et al.
(2003); Wang et al. (2009); Gami and Chauhan (2014) and Chaudhari et al. (2015).
121
4.32 Good cross Combinations for Seed Yield (G) and Quality Traits on the Basis of
sca Estimates, Heterosis and gca Estimates
Three cross combinations viz., UAF11×Toria, Napus2×Toria, Shora×Juncea were identified
for the seed yield as they revealed significant relative heterosis and heterobeltiosis (Table
4.35). These cross combinations may be expolited for commercial utilization of heterosis for
seed yield. For erucic acid four combinations as UAF11×Toria, Napus2×Juncea, Shora×1072
and Shora×1072 were identified. These four combinations can be used for the source of
erucic acid reduction. Glucosinolate content is an important trait for animal feed. Four
combinations UAF11×Napus1, Napus2×Toria, Napus2×Juncea and Shora×1072 were found
suitable for negative heterosis for glucosinolate. For oil contents four combinations
Napus2×Toria, Shora×Juncea, UAF11×Napus1 and Napus2×Juncea were identified as they
revealed significant positive heterosis for oil. These combinations can be used for the
exploitation of heterosis for oil content.
Table 4.34 Heterotic manifestation for quality traits of interspecific hybrids
Oil contents
(%)
Protein contents
(%)
Glucosinolate
contents (%)
Oleic acid
(%)
Erucic acid
(%)
MP BP MP BP MP BP MP BP MP BP
UAF11×Toria -14.43 ** -24.74 ** 5.16 1.15 4.75 ** 3.82 ** 8.33 ** -6.53 ** 6.05 ** -6.00 **
UAF-11×1072 -0.16 -17.77 ** 9.81 * 9.50 * -2.49 * -3.38 * -2.05 * -23.05 ** 44.64 ** 3.81 *
UAF11×Napus1 -22.73 ** -25.58 ** 3.69 2.85 -67.04 ** -68.36 ** 48.82 ** 34.76 ** 12.45 ** -19.55 **
UAF11×Juncea1 -2.81 -14.90 ** 14.46 ** 9.89 * 31.13 ** 30.04 ** -1.77 -15.30 ** 17.79 ** 3.86 *
Napus2×Toria 8.99 ** 5.35 * 5.22 3.82 -5.94 ** -16.62 ** -7.72 ** -13.89 ** 35.34 ** 34.33 **
Napus2×1072 17.08 ** 5.11 3.70 0.78 9.13 ** -1.69 -31.94 ** -35.05 ** 73.49 ** 36.36 **
Napus2×Napus1 8.56 ** 1.93 -1.40 -3.14 -15.08 ** -21.23 ** 7.48 ** -4.60 ** -2.76 -23.86 **
Napus2×Juncea1 2.25 -1.65 -12.74 ** -14.07 ** -37.73 ** -44.78 ** 19.03 ** 11.17 ** -27.46 ** -27.57 **
Shora×Toria -9.81 ** -13.23 ** 5.68 4.20 6.67 ** -10.00 ** -53.15 ** -58.10 ** 51.43 ** 34.48 **
Shora ×1072 12.28 ** 7.93 * 7.67 * 4.71 -62.15 ** -67.58 ** -2.95 ** -3.02 ** 58.22 ** 36.54 **
Shora × Napus1 -15.63 ** -25.88 ** 7.32 5.50 -10.77 ** -21.45 ** -88.40 ** -90.11 ** 28.26 ** 10.19 **
Shora × Juncea1 16.73 ** 12.85 ** 10.24 ** 8.49 * 54.25 ** 30.21 ** -25.79 ** -33.59 ** 50.59 ** 34.44 **
122
Table 4.35 Good cross combinations for seed yield (g) and quality on the basis of GCA
estimates, heterosis and GCA estimates
*=significant (p<0.05);**=highly significant (p<0.01)
4.33 Heritability and Genetic Advance
Heritability and genetic advance is an imperative selection criteria.Days to flowering
initiation displayed high heritability (87.29) along with greater genetic advance (43.33)
(Table 4.36) that indicated the heritability was because of additive gene action and selection
might be successful.Related findings were described by Ali et al. (2003); Amiri-Oghan et al.
(2009) and Zare and Sharafzadah (2012). Days to 50% flowering indicated high heritability
(92.64) and high genetic (78.35) advance in percentage of mean that shows will be effective
due to additive gene effects. Results were confirmed by Dar et al. (2010). Days to 50%
siliqua formation, days to maturity and plant height showed considerable heritability along
with high genetic advance. Findings were partially agreed with the results reported by
Paikhomba et al. (2014). Number of primary branches, secondary branches, and biomass and
harvest index showed high heritability along genetic advance in percentage of mean that
shows additive gene action and selection will be rewarding. Our findings were in accordance
with results presented by Ali et al. (2003); Mahmud (2008) and Aytac et al. (2008). Number
of siliqua per plant and number of seed per siliqua showed high heritability along with high
Traits Name of
combinations
SCA effects Heterosis GCA effects
MP BP Parent 1 Parent2
Yield UAF11×Toria 10.20 ** 81.48 ** 2.30 8.36 ** 17.35 **
Napus2×Toria 23.29 ** 358.67 ** 204.81 ** 5.97 ** 17.35 **
Shora× Juncea 42.15 ** 239.35 ** 200.19 ** -14.34 ** -9.44 **
Erucic acid
(%)
UAF11×Toria -8.08 ** 6.05 ** -6.00 ** 4.28 ** 7.19 **
Napus2 × Juncea -13.91 ** -27.46 ** -27.57 ** -4.57 ** -0.49
Shora×1072 -8.74 ** 58.22 ** 36.54 ** 0.29 4.84 **
Shora×Napus1 -1.49 * 28.26 ** 10.19 ** 0.29 -11.54 **
Glucosinolate
(%)
UAF11×Napus1 -39.32 ** -67.04 ** -68.36 ** 8.82 ** -27.96 **
Napus2×Toria -3.36 ** -5.94 ** -16.62 ** -6.95 ** 11.65 **
Napus2×Juncea -50.07 ** -37.73 ** -44.78 ** -6.95 ** 26.10 **
Shora×1072 -46.60 ** -62.15 ** -67.58 ** -1.87 ** -9.79 **
Oil contents
(%)
Napus2× Toria 1.82 * 8.99 ** 5.35 * 3.44 ** -2.19 **
Shora ×Juncea 3.93 ** 16.73 ** 12.85 ** -3.15 ** 1.82 **
UAF11×Napus1 11.93 ** 48.82 ** 34.76 ** 3.18 ** -3.74 **
123
genetic advance in percentage of mean that revealed additive genetic effects. Similar reports
were presented by Ali et al. (2003); Mahmud (2008); Aytac et al. (2008) and Rameeh (2013).
100 seed weight showed high heritability along with remarkable genetic advance. Yield had
heritability and genetic advance high and selection will be valuable for the improvement in
yield. Related description was reported by Singh and Singh (1997) and Sheikh et al. (1999).
Prediction for improvement of B. campstris by direct selection of quantitative traits might be
successful based on heritability and genetic advance in percentage of mean
Table 4.36 Heritability (%) and Genetic Advance values (%) mean
Characters Heritability (%) Genetic Advance (%)
DFI 87.29 43.33
D 50%F 92.64 78.35
D 50%SF 97.85 126.83
DM 97.90 138.25
PH 98.81 133.67
PB 96.53 74.03
SB 95.77 47.46
GB 96.74 44.58
HI 98.08 42.92
SL/p 98.30 39.43
S/S 96.15 105.04
TWS 95.66 99.21
Y/P 98.95 156.92
*=significant (p<0.05);**=highly significant (p<0.01)
DFI stands for days to flowering initiation, D50%F for days to 50%flowering, D50%SF for days 50% siliqua formation, DM for
days to maturity, PH for plant height, PB for primary branches, SB for secondary branches, GB for green biomass yield, HI for
harvest index, S/PL for siliquae per plant, S/S for seed per siliqua, TSW for 100 seed weight, Y/P for yield per plant
124
4.34 Heritability and Genetic Advance for Quality Traits
Oil contents had remarkable heritability (89.28) with moderate genetic advance (14.91) in
percentage of mean that showed additive gene action and selection might be fruitful (Table
4.37). Similar results were noted by Ghosh and Gulati (2001). However, Khulbe et al. (2000)
and Shoukat et al. (2014) observed low heritability for oil content. Protein contents displayed
high heritability (56.86) along with less genetic advance (5.74) that shows these traits were
highly influenced by the environment and selection cannot be rewarding. Glucosinolate also
showed high heritability (99.07) and considerable genetic advance (48.15). Similar studies
were discribed by Bradshaw and Wilson (1998) in case of heritability. For oleic acid and
erucic acid greater heritability along with high genetic advance were noted. Results were
supported by Chauhan et al. (2002) who noted moderate to high heritability associated with
high genetic advance (45.0-62.5%) for erucic acid.
Table 4.37 Heritability (%) and Genetic Advance values (%) mean for qualitative traits
4.35 Genotypic and Phenotypic Correlation for Quantitative Traits in Interspecific
Crosses
In order to make suitable selection criteria for successful breeding program, correlation
coefficient determinant is necessary to know the relationship between the traits considered.
The results for quantitative traits of inter-specific crosses (Table 4.38) indicated that
genotypic correlations were higher than phenotypic correlations at genotypic. Plant height
had positive and remarkable correlation with primary branches, secondary branches, number
Characters Heritability Genetic advance
Oil contents (%)
93.16 23.60
Protein contents
(%) 50.48 7.57
Glucosinolate contents
(%) 99.61 64.35
Oleic acid
(%) 99.80 61.46
Erucic acid
(%) 99.12 54.67
125
of siliqua per plant, biomass, 50% flowering and seed yield per plant. Results were supported
by Ghosh and Gulati (2000); Shalini et al. (2000); Choudhary et al. (2003); Chema and
Sadaqat (2004); Singh and Singh (2010) and Zare (2011). Primary branches had positive
considerable correlation with secondary branches and number of siliqua, days to 50%
flowering and days to 50% siliqua formation.
Results were partially supported by Masood et al. (1999) and Chema and Sadaqat
(2004). Secondary branches have significant correlation with seed per siliqua, days to
flowering initiation, days to 50% flowering , days to 50% siliqua formation days to maturity,
biomass, negative but significant with number of seed per siliqua and harvest index. Number
of siliqua per plant has negatively significant association with number of seed per siliqua and
positive relationship with biomass.
Number of seeds per siliqua had negative significant correlation with days to 50%
flowering, days to 50% siliqua formation days to maturity. Days to flowering initiation had
positive and significant correlation with days 50% flowering, days to 50% siliqua formation,
Days to maturity, but negative and remarkable with seed yield per plant and harvest
index. Halder et al.(2016) reported that days to 1st flowering were significantly and positively
correlated with the days to 50% flowering. Basalma (2008) also observed negative
correlation between days to first flowering and seed yield. However Miri (2007) reported
positive and remarkable correlation of days to first flowering with seed yield and harvest
index. Days to 50% flowering had positive significant correlation with days to 50% siliqua
formation, days to maturity but negative with seed yield per plant and harvest index.
Days to 50% siliqua formation had considerable correlation positively with days to maturity
and negative with seed yield and harvest index. Days to maturity were significantly negative
correlated with harvest index. Yield was positively correlated with biomass and harvest index
(Uddin et al., 1995; Rawat and Anand 1977 and Satyavathi et al., 2000). Kumar et al. (2016)
reporting positive correlation of yield with biological yield and harvest index
126
Table 4.36 Genotypic and Phenotypic correlation for quantitative traits in intespecific crosses
*=significant (p<0.05);**=highly significant (p<0.01)
DFI stands for days to flowering initiation, D50%F for days to 50%flowering, D50%SF for days 50% siliqua formation, DM for days to maturity, PH for plant height, PB for
primary branches, SB for secondary branches, GB for green biomass yield, HI for harvest index, S/PL for siliquae per plant, S/S for seed per siliqua, TSW for 100 seed
weight, Y/P for yield per plant
Characters Morphological traits Phenological traits Yield related traits
PH PB SB SL/p S/S DFI D 50% F D 50%S F DM Y/P GB HI
PH 1 0.726** 0.638** 0.566** 0.002 0.185 0.169 0.221 0.160 0.273* 0.413** 0.024
PB 0.639** 1 0.725** 0.275* 0.093 0.260 0.283* 0.325* 0.329* 0.113 0.243 0.062
SB 0.560** 0.682** 1 0.420** -0.29* 0.429** 0.466** 0.537** 0.476** -0.117 0.388** -0.362**
SL/p 0.532** 0.245 0.389** 1 -0.324* 0.184 0.148 0.219 0.139 -0.047 0.321* -0.176
S/S 0.003 0.080 -0.292* -0.31* 1 -0.234 -0.261* -0.287* -0.283* 0.254 0.024 0.243
DFI 0.141 0.241 0.414** 0.172 -0.226 1 0.991** 0.968** 0.853** -0.368** -0.071 -0.359**
D 50% F 0.172 0.260 0.448** 0.144 -0.256 0.970** 1 0.992** 0.853** -0.296* -0.040 -0.26*
50%S F 0.208 0.302* 0.518** 0.215 -0.283* 0.956** 0.985** 1 0.855** -0.315* -0.017 -0.272*
DM 0.145 0.301* 0.461** 0.138 -0.283* 0.827** 0.833** 0.840** 1 -0.257 0.131 -0.290*
Y/P 0.248 0.102 -0.112 -0.045 0.249 -0.362** -0.291* -0.310* -0.255 1 0.575** 0.703**
B.Y 0.382** 0.229 0.357** 0.311* 0.020 -0.073 -0.043 -0.015 0.126 0.564** 1 -0.071
HI 0.008 0.043 -0.332* -0.166 0.238 -0.334* -0.251 -0.257 -0.278* 0.693** -0.085 1
127
4.36 Path Analysis for Quantitative Traits
Days to flowering initiation has direct positive effect (0.79) and maximum positive indirect
effect (0.78) via number of days to 50% flowering on seed yield (Table 4. 37). Days to 50%
flowering showed positive direct effect (0.79) and maximum indirect effect (0.12) via
secondary branches on seed yield. Similar finding were reported by Sinha et al. (2001).
Ogrodowczyk and Wawrzyniak (2004) also observed that flowering period has the strongest
direct effect on seed yield. Days to 50% siliqua formation revealed direct negative effect (-
1.53) and maximum indirect effect 0.148 via secondary branches on seed yield. Days to
maturity showed maximum negative direct effect (-0.21) and maximum indirect effect (0.68)
via days to flower initiation.
Results were supported by Sinha et al. (2001). Plant height has maximum direct
positive effect (0.14) and maximum indirect effect (0.27) via biological yield on seed yield.
Primary branches depicted maximum negative direct effect (-0.23) and maximum indirect
effect (0.23) via days to 50% flowering on seed yield. Our findings were not supported by
Sinha et al. (2001). Secondary branches showed maximum direct positive effect (0.276) and
maximum indirect effect (0.258) via biological yield on seed yield. Similar results were
shown by (Dhillon et al., 1990 and Ramani et al., 1995). Biological seed yield has direct
effect (0.665) and maximum indirect effect (0.107) via secondary branches on seed yield.
Number of siliquae per plant has maximum negative direct effect (-0.0149) and maximum
indirect effect (0.214) via biological yield on seed yield Tusar- Patra et al. (2006) observed
strong positive direct effect on seed yield. Number of seeds per siliqua showed maximum
direct effect (0.005) and maximum indirect effect (0.44) via days to 50% siliqua formation on
seed yield. Thurling (1974); Ozer et al. (1999); Ali et al. (2002) and Tusar- Patra et al. (2006)
reported strong direct effect of number of pods per plant on seed yield per plant.
128
DFI stands for days to flowering initiation, D50%F for days to 50%flowering, D50%SF for days 50%
siliqua formation, DM for days to maturity, PH for plant height, PB for primary branches, SB for secondary
branches, GB for green biomass yield, HI for harvest index, S/PL for siliquae per plant, S/S for seed per siliqua, TSW for 100 seed weight, Y/P for yield per plant
4.37 Correlation and Path Analysis for Quality Traits
Only glucosinolate had positive and significant correlation with erucic acid. All other results
were statistically none significant (Table 4.38) Abideen et al. (2013) also reported positive
non-significant association between glucosinolate and erucic acid content. Protein contents
had direct negative effect (-.983) and highest indirect effect (.567) via erucic acid on oil
contents. Glucosinolate contents have direct positive effect (0.425) and indirect positive
effect (0.252) via protein contents. Oleic has direct negative effect (-0.09) and indirect
negative effect (-0.072) via erucic acid on oil contents. Erucic acid has positive direct effect
on oil (0.744). Tahira et al. (2015) also discribed that direct negative effect of oil contents on
erucic acid and indirect effects via total glucosinolate (-0.167) and oleic acid (-0.088) were
also negative. Glucosinolate had positive direct effect (0.384) on erucic acid (Table 4.39).
Table 4.37 Direct (Diagonal) and indirect effect path coefficients of interspecific crosses
Characters DFI D 50% F D 50% SF DM PH PB SB GB HI SL/p S/S
DFI 0.798 0.789 -1.482 -0.179 0.026 -0.059 0.119 -0.047 -0.31 -0.027 0.005
D 50% F 0.791 0.796 -1.518 -0.179 0.024 -0.064 0.129 -0.027 -0.231 -0.022 0.006
D 50% SF 0.773 0.79 -1.53 -0.179 0.031 -0.074 0.148 -0.012 -0.235 -0.033 0.005
DM 0.681 0.68 -1.31 -0.21 0.023 -0.075 0.131 0.088 -0.251 -0.021 0.000
PH 0.148 0.135 -0.339 -0.034 0.14 -0.165 0.176 0.275 0.021 -0.084 -0.001
PB 0.208 0.225 -0.499 -0.069 0.102 -0.227 0.2 0.162 0.054 -0.041 0.006
SB 0.343 0.371 -0.822 -0.1 0.09 -0.165 0.276 0.258 -0.313 -0.063 -0.005
GB -0.057 -0.032 0.027 -0.028 0.058 -0.055 0.107 0.665 -0.062 -0.048 0.005
HI -0.286 -0.213 0.417 0.061 0.003 -0.014 -0.1 -0.048 0.862 0.026 0.006
SL/p 0.147 0.118 -0.337 -0.029 0.079 -0.062 0.116 0.214 -0.152 -0.149 -0.020
S/S -0.187 -0.208 0.44 0.059 0 -0.021 -0.082 0.016 0.21 0.048 0.005
129
Table 4.38 Genotypic and phenotypic correlation for interspecific combinations
4.38 Genetic variability among direct and indirect interspecific crosses
Interspecific indirect and some direct crosses of B. campestris were also done with B. napus
and B. juncea. Twelve crosses were adopted and 10 of them were reciprocal of part (a)
because genetic system allows the successful crossing in one direction while it is not
successful in other direction due cross-incompatibility. Therefore reciprocal crosses are
recommended for inter-specific hybridization (Fehr, 1987). The data recorded for different
agronomic parameters were analyzed to confirm differences among the genotypes obtained
through introgression.Mean squares values from the analysis of variance for thirteen
quantitative traits (Tables 4.40). Highly significant differences were noted among Brassica
Characters Oil contents
(%) Protein contents
(%) Glucosinolate
contents (%) Oleic acid
(%) Erucic acid
(%)
Oil contents (%)
1 0.089 -0.061 0.067 -0.104
Protein contents
(%) 0.082 1 0.180 -0.027 -0.060
Glucosinolate
contents (%) -0.063 0.149 1 0.128 0.671**
Oleic acid
(%) 0.062 -0.024 0.102 1 0.004
Erucic acid
(%) -0.097 -0.051 0.661** 0.006 1
Table 4.39 Direct (Diagonal) and indirect effects of quality traits for interspecific crosses
Characters Protein contents
(%) Glucosinolate contents
(%) Oleic acid
(%) Erucic acid
(%)
Protein contents
(%) -0.983 0.223 0.045 0.567
Glucosinolate contents
(%) -0.514 0.425 0.031 0.283
Oleic acid
(%) 0.49 -0.146 -0.09 -0.252
Erucic acid
(%) -0.749 0.162 0.03 0.744
*=significant (p<0.05);**=highly significant (p<0.01)
130
genotypes for all traits studied. Substantial variability noted among the genotypes used for
various i.e. phenological, morphological, yield and yield traits is similar (Gosh and Gulati,
2001; Ali et al., 2003; Sadaqat et al., 2003; Fahratullah et al., 2004; Aytac and Kinaci, 2009;
Dar et al., 2010; Sabghnia et al., 2010; Marjenovic-Jeromela et al., 2011; Singh et al., 2012
and Arifullah et al., 2013).The sum of squares values for indicated traits were partitioned into
parents, crosses and parent vs. crosses, displayed considerable differences among themselves.
The sum of square values for crosses was further divided into male, females, male’s×females
and males vs. females. Highly significant differences were present among lines and testers,
for these traits except for primary branches and secondary branches for testers. However
lines vs. tester’s difference were non-significant for the values of biomass. (Table 4.41)
Abideen et al. ( 2013); Zare and Sharahfzadeh (2012); Ali et al. (2003); Dar et al.
(2013); Singh et al. (2014) and Parveen et al.( 2015) also reported that there was non-
significant variability for days to 50% flowering initiation, primary branches per plant and
seed per pod. Nevertheless their expression is affected by the environment. Evaluation of
genetic variability for economic important traits in rapeseed and mustard is a fundamental
purpose in breeding Therefore characters of economic importance such as plant height,
secondary branches, harvest index and green biomass were studied and significant
differences were noted for all sources of variation (Table 4.38). Variation for these traits was
also examined by different people. Significant and non-significant differences were noted.
Huehn (1993); Ali et al. (2003); Sadaqat et al. (2003); Farhatullah et al. (2004); Cui and
Yu (2005); Sincik et al. (2007); Dar et al. (2010); Iqbal et al. (2014); Synrem et al. (2014)
and Mekonen et al. (2015). Yield and yield related parameters showed significant mean
square values for the material used in this study. Seed yield is a complex of population
density, number of siliqua, seeds per siliqua and seed weight (Dipenbrock, 2000). Oilseeds
Brassicas have significant and highly significant variation for yield and yield related traits
(Kang et al., 2013; Nasim et al 2014; Ullah et al., 2015; Naznin et al., 2015 and Halder et al.,
2015).
131
Table 4.40 Mean square values associated with different plant traits
Source ofVariation
Replications Genotypes Error
Degree of freedom 2 18 36
Ph
en
olo
gic
al tr
aits
Days to flowering initiation 49.95 720.7** 6.69
Days to 50% flowering 75.23 777.1** 6.27
Days to 50% siliqua formation 135 1177** 13.78
Days to maturity 171 2286** 13.81
Plant height 107.7 5013** 126.6
Mo
rp
ho
log
ica
l
tra
its
Primary branches 3.18 50.05** 5.27
Secondary Branches 3.211 452.4** 25.21
Green Biomass 17.39 4273** 41.46
Harvest index 13.31 1999** 18.55
Yie
ld r
ela
ted
tra
its
Number of siliquae per plant 89479 6E+06** 22061
Number of seed per siliqua 0.77 216** 1.14
1000 seed weight 6.00E+04 0.023** 4.00E-04
Seed yield per plant 0.364 724.1** 4.132
Qu
ality
rela
ted
tra
its
Oil contents (%) 3.94 31.31** 1.2
Protein contents (%) 4.55 3.59** 0.71
Glucosinolates (%) 0.84 1386.93** 3.06
Oleic acid (%) 5.959 174.7** 1.507
Erucic acid (%)
3.25 479.47** 1.4
132
Table 4.41 Mean square values of direct and some indirect interspecific crosses of B. campestris
*=significant (p<0.05);**=highly significant (p<0.01)
DFI stands for days to flowering initiation, D50%F for days to 50%flowering, D50%SF for days 50% siliqua formation, DM for days to maturity, PH for
plant height, PB for primary branches, SB for secondary branches, GB for green biomass yield, HI for harvest index, S/PL for siliquae per plant, S/S for seed
per siliqua, TSW for 100 seed weight, Y/P for yield per plant
Traits Phenological traits Morphological traits Yield related traits
Source of
Variation DF DFI D 50%F D 50%SF DM PH PB SB GB H.I SL/p S/S TWS Y/P
Replication 2 49.95** 75.23** 134.97** 171.02** 107.70 3.18 3.21 17.39 13.31 89479.00* 0.77 0.00 0.36
Genotypes 18 720.72** 777.11** 1176.97** 2286.20** 5013.08** 50.06** 452.40** 4273.14** 1999.35** 6397220.41** 215.97** 0.02** 724.12**
Parents 6 1327.98** 1506.38** 1633.08** 5048.30** 4703.60** 98.89** 893.27** 2729.65** 692.56** 806964.83** 70.05** 0.02** 1340.14**
Tester 3 1454.31** 1479.22** 1583.22** 5229.64** 7600.56** 77.00** 846.53** 2872.31** 985.17** 818824.33** 99.56** 0.03** 2083.42**
Lines 2 1590.33** 2010.78** 2164.33** 7212.11** 300.44 171.44** 1281.00** 3877.78** 358.80** 682560.44** 24.57** 0.01** 725.42**
L Vs T 1 424.32** 579.06** 720.14** 176.67** 4819.06** 19.44 258.04** 5.43 482.28** 1020195.06** 72.48** 0.02** 339.74**
Crosses 11 446.76** 433.33** 1034.49** 814.26** 4764.57** 24.84** 252.03** 5498.98** 2890.54** 7602869.79** 166.59** 0.02** 355.01**
P Vs C 1 90.70** 182.98** 7.70** 1904.85** 9603.58** 34.43** 11.34** 49.94** 37.06** 26676610.71** 1634.71** 0.03** 1088.22**
Testers 3 784.25** 688.07** 451.63** 1421.04** 3713.44** 9.67 89.44 4070.18** 3430.81** 104137.58** 67.08** 0.01** 405.75**
Lines 2 880.78** 846.58** 2835.75** 538.36** 6847.69** 33.78** 713.03** 6215.58** 5866.01** 2398556.33** 54.73** 0.04** 175.34**
L×T 6 133.33** 168.21** 725.49** 602.84** 4595.77** 29.44** 179.66** 5974.51** 1628.58** 2478771.75** 253.63** 0.02** 389.54**
Error 36 6.69 6.27 13.78 13.81 126.57 5.27 25.21 41.46 18.55 22061.35 1.14 0.00 4.13
133
4.39 Mean Comparisons for Various Plant Traits of 12 Interspecific Crosses of B.
campestris
4.39.1 Phenological Traits
The average performance of 12 hybrids of B. campestris for eighteen traits used in line×tester
analysis (Table 4.42) Number of days to flower initiation were ranged from 38 (Toria ×UAF11)
to 83 (Napus1×Shora).Five hybrids were early flowering as they got less than 67days for
flowering initiation. The number of days to 50% flowering were varied from 47 to 91.The
number of days for 50% siliquae formation were ranged from 37 (Toia×Shora) to 99.67
(Juncea×Shora).The number of days to maturity were varied from 117 (Toria × UAF) to 175
(Toria×Shora). Out of 12 hybrids 5 hybrids were early maturing (less than 145days).
The study for the effect of nursery age and row spacing on phenology of canola (Brassica
napus L.) revealed that transplanted nursery took more days to 50% flowering as compared to
direct sowing while siliqua formation took more days in form of direct sowing as compared to
nursery (Ingh and Singh, 2013). Studies on growing of oats fodder as an intercrop indicated
significant influence on the growth of B. napus but phenology of crop was not affected. The
range for number of days for 50% flowering was from 63.8 to 102 days while for 50% siliqua
formation was from 74.5 to 109.8 days. The maturity days were from 144 to 157 days (Singh and
Singh, 2014)
4.39.2 Morphological Traits
Maximum plant height was 227.67 cm for cross (Napus1×Shora) and minimum was 117 cm
for cross (Juncea × UAF-11). Variation for number of primary branches ranged from 6 (Juncea
×UAF-11) to 14.67 (Juncea ×Shora).Five hybrids had more number of secondary branches
than average. For green biomass 6 hybrids had more quantity than that of average. The average
harvest index (%) was (33.08.). The range for harvest index varied from 4.06 (Juncea×Napus2)
to 107.8 (Juncea × UAF-11). Shehzad and Fahratullah (2012) also reported significant
differences in inter-specific crosses of genus Brassica for plant height. The comparison of
relative measure coefficient of variation showed that harvest index had low variation as
compared to grain/straw ratio (Huehn, 1993). However, estimation for the relative
involvement of biomass, harvest index and other yield contributing traits to seed yield gain of
soybean showed that harvest index had more contribution to the soybean yield grain than
biomass (Cui and Yu, 2005).
134
4.39.3 Yield Related Traits
For number of siliqua per plant, five hybrids got above the average and it ranged from 52
(Juncea1× UAF-) to 52.35 (Napus1×UAF11).A good degree of variation was noted for number
of seed per siliqua. The range of variation was from 2.67 (Juncea×1072) to 21.05 (Napus
1×Shora).Thousand seed weight expressed good variation. The maximum range was 0.33 gm
(Toria × UAF11) and minimum was 0.06 gm (Juncea×1072). For yield six hybrids showed the
value above than average. The range for these values from 2.5 gm per plant (Juncea×UAF11) to
39.45 gm (Juncea1×Shora).Number of siliqua per plant has important role for genetic divergence
while yield per plant have less role as compared to number of siliqua (Naznin et al., 2015).
Genotypic variance was greater than phenotypic variance for all traits studied without yield
(Halder et al., 2015). The number of siliqua per plant varied from 70 to 165 (Sadaqat et al., 2003;
Aytic and Kinaci, 2009; Raman et al., 2013 and Rameeh, 2011). The maximum mean value
(365) reported for number of silique/plant and significant differences were noted for brown
mustard (Dar et al., 2010)
4.39.4 Quality Related Traits
B.campestris hybrids showed good variation for oil contents and ranged from 35.6
(Juncea×1072) to 49.47(%) (Napus1×Napus2).Protein content ranged from 23.9 (%)
(Toria×Napus1) to 28.33 (%) (Napus1×Shora).Variation for glucosinolates was from 58.3
(Napus1×1072) to 145.33 (Juncea × UAF11). Oleic acid (%) exhibited lot of variation and its
range was from 31.53 (Juncea1× UAF11) to 49.6. (Toria×Napus1).A considerable amount of
variation was observed for erucic acid with ranged from 25 (Napus1×Shora) to 60.17
(Juncea1×UAF11).Five hybrids were low erucic acid because they got less amount of erucic acid
than the average value. Estimation of genetic variability in F2 generation of intra and
interspecific hybridization exhibited remarkable variation for oleic acid, linolenic acid, erucic
acid and glucosinolate. For protein results were also significant contrasting the results noted by
Khan et al. (2008) and Fayyaz et al. (2014). Biochemical analysis of advanced population F10:11
developed through interspecific hybridization indicated significant variation for oil and protein
traits (Naseebullah et al., 2015).
135
Table 4.42 Mean comparison for various plant traits of 12 interspecific crosses of B.campestris
Traits Phenological traits Morphological traits
Hybrids DFI D 50% F D 50% SF DM PH PB SB GB HI
Toria x 1072 66.00 76.33 85.00 118.67 205.33 11.67 22.67 27.00 107.80
Toria×Napus2 62.67 73.33 81.67 146.00 186.67 12.00 23.00 97.33 11.97
Toria x Shora 65.67 75.00 37.33 175.00 139.33 10.33 37.33 39.00 56.79
Toria×UAF11 38.00 47.67 57.00 117.00 166.00 14.67 40.33 43.33 54.58
Napus1 x1072 81.67 91.67 98.00 151.00 227.67 9.67 17.33 39.00 56.79
Napus1×Napus2 75.33 85.00 92.67 144.00 227.67 9.67 17.33 111.67 18.57
Napus1×Shora 83.00 90.67 99.33 162.33 188.33 8.33 13.33 62.33 22.07
Napus 1 ×UAF11 57.00 67.67 78.00 152.33 206.67 7.67 18.00 95.00 7.84
juncea x 1072 66.67 75.00 85.00 132.67 123.33 13.00 16.33 160.67 6.63
juncea×Napus1 72.33 82.00 91.67 143.00 222.33 7.00 21.33 102.67 4.06
juncea×Shora 77.67 88.33 99.67 151.67 211.67 14.67 27.67 104.00 37.99
juncea x UAF 11 67.67 79.33 90.67 149.00 117.33 6.00 9.67 21.00 11.89
LSD 5% 4.604 4.103 6.958 7.127 17.317 3.77 9.43 9.36 7.19
LSD 1% 6.26 5.58 9.46 9.69 23.54 5.13 12.81 12.73 9.78
136
DFI stands for days to flowering initiation, D50%F for days to 50%flowering, D50%SF for days 50% siliqua
formation, DM for days to maturity, PH for plant height, PB for primary branches, SB for secondary branches, GB
for green biomass yield, HI for harvest index, S/PL for siliquae per plant, S/S for seed per siliqua, TSW for 100 seed
weight, Y/P for yield per plant, O (%)For oil contents, PRT for protein content,GLS for glucosinolates,OA for oleic
acid, EA for erucic acid
Continue
Yield related traits Quality related traits
SL/p S/S TSW Y/P O (%) PRT
(%) GSL (%) OA (%) EA
1120.67 19.07 0.27 29.07 41.40 26.30 98.13 39.37 37.03
1355.67 2.67 0.21 11.53 41.57 23.90 60.87 49.60 36.60
3078.67 5.47 0.30 22.00 42.37 25.53 113.97 32.50 54.53
1619.00 10.47 0.33 23.43 42.53 25.43 113.57 32.33 60.13
3078.67 5.47 0.30 22.00 43.40 25.30 58.30 42.37 49.30
1331.00 20.63 0.26 20.66 49.47 24.47 82.50 39.43 33.17
1152.33 21.05 0.21 13.60 36.63 28.33 91.30 47.50 25.40
5235.00 3.20 0.26 7.43 35.60 26.53 95.33 41.73 45.00
4744.00 2.70 0.06 10.67 42.33 26.67 114.53 44.70 56.23
3233.33 2.67 0.18 4.17 41.90 25.70 75.70 40.70 60.07
1221.33 16.27 0.33 39.45 44.47 25.43 78.37 35.33 57.33
52.33 12.47 0.11 2.50 41.67 27.60 145.33 31.53 60.17
293.21 1.38 0.03 2.54 2.04 1.28 3.15 2.42 60.17
398.53 1.88 0.04 3.45 2.77 1.74 4.28 3.29 25.4
137
4.40 General Combining Ability Effects for Various Traits of InterSpecific Hybrids
Variation for general combing ability effects for 10 reciprocal {interspecific (a)} and two
non-reciprocal combinations were studied. There were 3 lines, consisted of (B.campestris, B.
napus and B. juncea) and four testers, (two from B .campestris, one B. napus and one B.
juncea) for thirteen plant traits to locate the best parent for the further breeding program.The
results for general combining ability estimates (Table 4.43). Minimum number of days for
initiation and maturity are required to develop the short duration cultivars so that it may
easily fit in our cropping pattern. All three species showed different behavior towards the
days to flowering initiation. Toria (campestris) was the best combiner (-9.72) while Napus1
(napus) (6.42) and Juncea (juncea) (3.2) were the poor general combiner for the flowering
initiation. UAF11 was the best combining line (-13.58) while Shora (7.64) was the poor
combining tester for 50% flowering. Toria (-17.75) was the best combining line and UAF11
was the best tester line (-7.78) for 50% siliqua formation. Toria (-6.06) was the best general
combiner among the lines and UAF11 (-5.42) among the tester for days to maturity. Female
lines Juncea (-16.53) and Toria (-10.86) indicated negative and significant GCA effects for
plant height. Results were in accordance with Singh et al. (2010) and Synrem et al. (2015).
Positive and considerable GCA effects for primary and secondary branches were observed in
line Toria (1.78) and (8.81) respectively. The GCA effects for primary branches the best
combining line was Shora (3.75) and the poorest line was napus2 (-1.25). Juncea (2.28) was
the best combining tester line. For secondary branches of GCA effects Shora was the best
combiner line (18.75).
Regarding the biomass the parental line Juncea (21.83) and tester Napus2 (28.64)
showed significant GCA effects in positive direction. Parent line Toria showed the highest
value (24.58) for GCA effects for harvest index. For number of siliqua per plant the GCA
effects positive and highly significant were shown by Toria and Napus1 among lines, 1072
and Shora among testers. The best general combining line for number of seed per plant was
napus and Shora. For 100 seed weight the positive and GCA effects were shown by Toria
and Napus1 among lines and Shora among the testers. The positive and significant GCA
effects for seed yield per plant were displayed by Toria among lines and Shora and Napus2
138
among testers. The parents Toria and Shora can be considered as the superior parents because
they showed high positive and remarkable GCA effects for seed yield. Findings were similar
to Parmer et al. (2011) and Synrem et al. (2015).
4.41 Specific Combining Ability Estimates of Interpecific Combinations
The estimates of specific combining ability effects of 12 Brassica campestris combinations
and relative Brassicas (Table 4.44).Minimum number of days to flowering is a required trait
of Brassica campestris. The crosses Napus1×UAF11 (napus×campestris) and Toria×UAF11
(campestris×campestris) were the best, showing negative and significant specific combining
ability effects (-11.53) and (-5.28) for days to flowering initiation respectively. Cross
combinations Juncea × 1072 followed by Toria×UAF11 showed desirable significant
negative specific combining ability effects for days to 50% flowering. Juncea × 1072
followed by Toria×Shora combinations depicted considerable and negative specific
combining ability effects for days to 50% siliqua formation. Toria×UAF11 and
Shora×Juncea showed significant and negative specific combining ability effects for days to
maturity. These crosses combinations can be exploited to find early maturing genotypes in
subsequent generations. Five cross combinations showed negative and significant specific
combining ability for plant height.
Hybrids Toria×UAF11 and Napus1×Shora exhibited significant and positive SCA
effects for primary branches. The combination Shora ×juncea showed positive specific
combining ability effects for secondary branches. Regarding the biomass and harvest index,
hybrids Juncea×1072 and Napus1×UAF11 for biomass, Juncea×Shora and Napus1×Napus2
for harvest index showed positive and significant specific combining ability effects. Only one
cross combination Juncea×UAF11 showed positive and considerable SCA effects for number
of seed per pod. The highest SCA effects were shown by the combination Juncea×Shora and
followed by Toria×UAF11 for yield.
139
*=significant (p<0.05);**=highly significant (p<0.01)
DFI stands for days to flowering initiation, D50%F for days to 50%flowering, D50%SF for days 50% siliqua formation, DM for days to maturity, PH for
plant height, PB for primary branches, SB for secondary branches, GB for green biomass yield, HI for harvest index, S/PL for siliquae per plant, S/S for seed
per siliqua, TSW for 100 seed weight, Y/P for yield per plant
Table 4.43 General combining ability estimated effects for various traits of inter specific combinations
Phenological traits Morphologcal traits Yield related traits
Parents DFI D 50%F D 50%SF DM PH PB SB GB H.I SL/p S/S TWS Y/P
Lines
Toria -9.72** -9.58** -17.75** -6.06 * -10.86** 1.78** 8.81* -23.58** 24.70** -475.00** -0.76 0.04 4.30**
Napu1 6.44** 6.08* 9.00* 7.19** 27.39** -1.56 -5.53 1.75 -6.76** 430.75** 2.41 0.02 -1.29**
Juncea1 3.28 3.50 8.75** -1.14 -16.53 -0.22 -3.28 21.83** -17.94** 44.25 -1.65 -0.06 -3.01**
S.E 0.35 0.22 0.54 0.41 0.36 0.35 0.22 0.54 0.41 0.36 0.35 0.22 0.54
Testers
1072 3.64** 3.33 6.33* -11.11** 0.25 1.06 -3.25** 0.31 23.99** 712.61** -1.10 -0.03 3.37**
Napus2 2.31 2.44 5.67** -0.89 27.03 ** -0.83 -1.47 28.64** -21.55** -295.17** -1.52 -0.02 -5.09**
Shora 7.64* 7.00* -4.22 17.78** -5.42 0.72 4.08 -6.81 5.87** -451.06** 4.09 0.05 7.81**
UAF11 -13.58** -12.78** -7.78** -5.78 -21.86 ** -0.94 0.64 -22.14** -8.31** 33.61 -1.47** 0.00 -6.09**
S.E 0.4 0.25 0.62 0.48 0.41 0.4 0.25 0.62 0.48 0.41 0.4 0.25 0.62
140
*=significant (p<0.05);**=highly significant (p<0.01)
DFI stands for days to flowering initiation, D50%F for days to 50%flowering, D50%SF for days 50% siliqua formation, DM for days to maturity, PH for
plant height, PB for primary branches, SB for secondary branches, GB for green biomass yield, HI for harvest index, S/PL for siliquae per plant, S/S for seed
per siliqua, TSW for 100 seed weight, Y/P for yield per plant
Table 4.44 Specific combining ability estimated effects of interspecific combinations
Phenological traits Morphological traits Yield related traits
Combinations DFI D 50%F D 50%SF DM PH PB SB GB H.I SL/p S/S TWS Y/P
Toria× 1072 4.28* 4.92** 13.42** -9.39** 30.75 -1.56 -4.92** -24.97** 26.02** -1385.44** 10.75 0.02 4.19**
Toria×Napus2 2.28 2.81 10.75** 7.72** -14.69 0.67 -6.36 17.03** -24.27** -142.67 -5.23 -0.05 -4.89**
Toria × Shora -0.06 -0.08 -23.69* 18.06** -29.58** -2.56** 2.42 -5.86** -6.86 1736.22** -8.04 -0.03 -7.32**
Toria ×UAF11 -6.50** -7.64** -0.47 -16.39** 13.53** 3.44* 8.86 13.81** 5.11 -208.11* 2.52 0.05 8.01**
Napus1 ×1072 3.78** 4.58** -0.33 9.69** 14.83** -0.22 4.08 -38.31** 6.48 -333.19 -6.02** 0.07 2.71**
Napus1 ×Napus2 -1.22 -1.19 -5.00 -7.53 -11.94** 1.67** 2.31 6.03 13.80** -1073.08** 9.57 0.02 9.82**
Napus1 ×Shora 1.11 -0.08 11.56* -7.86 -18.83* -1.22** -7.25** -7.86 -10.12** -1095.86** 4.38 -0.09 -10.13**
Napus1 ×UAF11 -3.67* -3.31** -6.22** 5.69** 15.94** -0.22 0.86 40.14** -10.17** 2502.14** -7.92 0.00 -2.40**
Juncea × 1072 -8.06** -9.50** -13.08 ** -0.31 -45.58** 1.78 0.83 63.28** -32.50** 1718.64 -4.73 -0.08 -6.90**
Juncea × Napus2 -1.06 -1.61 -5.75** -0.19 26.64** -2.33** 4.06 -23.06** 10.46** 1215.75** -4.34 0.03 -4.94**
Juncea × Shora -1.06 0.17 12.14** -10.19 * 48.42** 3.78 4.83** 13.72** 16.98** -640.36** 3.66 0.11 17.45**
Juncea × UAF11 10.17** 10.94** 6.69* 10.69** -29.47** -3.22** -9.72** -53.94** 5.06** -2294.03** 5.41** -0.06** -5.61**
SE 2.10 1.80 1.30 2.20 8.60 0.80 1.55 5.60 2.20 99.90 0.33 0.01 1.28
141
4.42 Components of Genetic Variance
Components of variance and degree of dominance for indicated traits in interspecific
combinations of Brassica campestris with its relative Brassicas (Table 4.45). Specific
combining ability was more important than general combining ability and dominance
variance than additive variance. Specific combining ability or dominance variance was more
important for all indicated traits except for days to flowering initiation and days to 50%
flowering showed more additive variance than dominance variance. Phenotypic variance
arising due to additive gene action has great value in plant breeding; the additive effect is the
breeding value of an individual .The breeding value of parent is estimated by the average
value of its progeny. The specific combining ability has positive association with heterosis.
Degree of dominance was greater than 1 for days to flower initiation, days to 50% flowering,
days to 50 % siliqua formation days to maturity, secondary branches, biomass, harvest index,
number of siliqua per plant and 100 seed weight; all these traits can be utilized for heterotic
effects of their genotype.
The inheritance pattern of gene action was dominant for expression of phenological
and yield related traits in Brassica campestris while morphological traits such as flowering,
maturity, seed/siliqua, harvest index and oil content exhibited the values in negative
direction, showing the excess of recessive genes for these traits (Rahman et al., 2011). Both
additive and non additive gene actions were important in controlling days to 50% flowering,
seed yield per plant. Additive gene action was important for the expression of days to 90%
maturity, number of seeds per pod and 1000 seeds weight. Non-additive gene actions were
important in controlling the expression of number of pods per plant. Maturity factors of
biennial parents also affect expression of flowering habit. Annual habit is dominant over
biennial and is controlled by several major genes with a strong effect of modifiers from both
the annual and biennial parent. Time of heading of annual plants in F2 progenies appeared to
be controlled by quantitative, mainly additive, factors. Distribution of heading dates for the
F1 and annual broccoli parents showed a large environmental or cultural effect. It appears
that the biennial parents, especially Brussels sprouts and collards, contributed strong factors
for late maturity (Baggett and Kean, 1989).
142
DFI stands for days to flowering initiation, D50%F for days to 50%flowering, D50%SF for days 50% siliqua formation, DM for days to maturity.PH for
plant height, PB for primary branches, SB for secondary branches, GB for biomass yield, HI for harvest index, S/PL for siliquae per plant, S/S for seed per
siliqua, TSW for 100 seed weight, Y/P for yield per plant
Table 4.45 Components of genetic variance of inter specific combinations
Traits Phenological traits Morphological traits Yield related traits
Genetic
Components DFI D 50%F D 50%SF DM PH PB SB GB H.I SL/p S/S TWS Y/P
COV(HS) 66.59 57.06 87.45 35.89 65.22 -0.74 21.10 -79.20 287.60 -902323.35 -18.36 0.00 -9.43
COV(FS) 175.16 168.23 411.10 266.82 1627.50 6.69 91.76 1822.90 1112.05 2156378.22 47.61 0.01 110.24
VAR of GCA 66.59 57.06 87.45 35.89 65.22 -0.74 21.10 -79.20 287.60 -902323.35 -18.36 0.00 -9.43
VAR of SCA 41.98 54.11 236.20 195.04 1497.06 8.16 49.56 1981.31 536.84 3961024.91 84.32 0.01 129.10
IF F=0 ; D 266.35 228.24 349.79 143.56 260.88 -2.94 84.41 -316.81 1150.41 -3609293.39 -73.42 0.00 -37.71
IF F=0 ; D 167.92 216.46 944.81 780.17 5988.24 32.65 198.23 7925.24 2147.38 15844099.64 337.29 0.03 516.39
Degree of Dominance
{α2D
/α2A } ½
0.79 0.97 1.64 2.33 4.79 0 1.53 0 1.37 0 0 5.29 0
143
4.43 Contribution (%) of Lines, Testers and Their Interactions for Various Traits of
Interspecific Combinations
A line×tester analysis of interspecific combinations with seven genotypes was adopted,
three were used as lines and four were used as tester to get relative contribution of each
genotype and its interactions the whole variance for various plant traits. The contribution of
lines, testers and their interaction for thirteen traits (Table 4.46). It is clear from the table
that lines made an important contribution towards all these traits. The maximum
contribution of lines was 51.44% for secondary branches. Minimum contribution was for
number of siliqua per plant and seed per siliqua showing predominant maternal effect for
these traits. The contribution of tester was the highest for number of siliqua per plant
85.47% fallowed by seeds per siliqua 83.04 %. It showed preponderance of paternal effect
for these traits. The contribution of their interaction was relatively higher for all traits.
Table 4.46 Contribution (%) of lines, testers and their interactions for various traits
of interspecific crosses
DFI stands days to flowering initiation, D50%F for days to 50%flowering, D50%SF for days 50% siliqua formation,
DM for days to maturity, PH for plant height, PB for primary branches, SB for secondary branches, GB for green
biomass yield, HI for harvest index, S/PL for siliquae per plant, S/S for seed per siliqua, TSW for 100 seed weight,
Y/P for yield per plant
4.44 Heterotic Manifestation Due To Inter-specific Hybridization
The heterosis obtained from hybridization between races or species gives an excessive
increase in size, weight and growth rate in the interspecific or inter racial hybrids (Sherma,
1989). Such type of heterosis was called luxuriance and hybrids are luxuriant (Dobzhansky,
1940). Luxuriance is pseudo heterosis. There is no continuation due to poor seed setting in
Traits Phenological traits Morphological traits Yield related traits
Parents and
Interactions DFI
D 50%
F
D 50%
SF DM PH PB SB GB HI SL/p S/S TSW Y/P
Lines 35.85 35.52 49.84 12.02 26.13 24.73 51.44 20.55 36.9 5.93 5.97 33.1 8.98
Testers 47.88 43.31 11.91 47.6 21.26 10.61 9.68 20.19 32.37 8.6 10.98 11.63 31.17
L x T 16.28 21.17 38.25 40.38 52.61 64.66 38.88 59.26 30.73 85.47 83.04 55.27 59.85
144
luxuriant hybrids. However creation of novel genotype or F1 is possible through inter-
specific hybridization which was unreal in nature. All 12 hybrids were compared with mid
parent and batter parent for evaluation of heterosis. Substantial amount for relative heterosis
and heterobeltiosis were noted for yield and other related characters studied. However, all
crosses differed for the degree of heterosis (Table 4.47).
4.44.1 Seed Yield per Plant
Only Three hybrids out of 12 combinations showed positive and significant relative heterosis
and heterobeltiosis (Table 4.47).The combination was Toria ×1072 (156.47), Juncea×Shora
(127.58) and Toria×Shora (65) were at the top for heterosis in yield per plant. Positive and
considerable heterosis and heterobeltiosis is preferred to select the genotypes with higher
values. The aim of the heterosis breeding is to attain the high yielding combinations with
desirable quality traits. It has been reported that the genomic components introgressed
from B. rapa can improve the seed yield of rapeseed (Qian et al., 2005). Significant and
positive heterosis has been reported by earlier worker (Aher et al. 2006; Gupta et al. 2011;
Verma et al. 2011; Patel et al. 2012; Kumar et al. 2013; Kumar et al. 2014; Meena et al.
2014 and Synrem et al. 2015).
4.44.2 Days to Flowering Initiation
Out of total 12 crosses, 3 hybrids were identified for significant and negative relative
heterosis and 3 were at the top for heterobeltiosis .Negative heterosis is desirable for
flowering in Brassica crops. Early flowering is a first step towards early maturing verities
that prevents the yield losses and oil quality due to high temperature. Grant and Beversdorf
(1985) reported negative heterosis for flowering.
4.44.3 Days to 50% Flowering
Out of 12 only 4 showed considerable negative heterosis over mid parent and 9 over batter
parent heterosis.Juncea×1072 (-8.72), Juncea×Napus2 (-5.02) and Juncea×Shora (-2.03)
showed negative significant relative heterosis and combinations Toria×Shora (-22.8),
Toria×Napus2 (-17.91) and Napus1×UAF11 (-17.81) for heterobeltiosis.Negative heterosis is
preferred in Brassica campestris because it shows earliness in flowering. The crosses
showing earliness can be used for further breeding program.similar studies were discribed by
Nassimi et al. (2006). Synrem et al. (2015) also reported desirable negative and significant
heterosis for days to 50% flowering in Brassica species.
145
4.44.4 Days to 50% Siliquae Formation
Out of 12 hybrids, two crosses showed significant and negative relative heterosis and seven
for heterobeltiosis for days to 50% siliqua formation. For early maturing cultivars negative
heterosis for 50% days to siliqua formation is an advantageous trait.
4.44.5 Days to Maturity
About three hybrids were at the top for significant negative relative heterosis and six
heterobeltiosis for days to maturity. The comparison of nap and mur cytoplasmic system
showed negative heterosis for days to maturity (Riungu and McVetty, 2004). Early maturity
is a useful trait in many plant species; however it is very important in Brassica species
because late maturity causes the yield losses and quality of oil due to high temperature (Turi
et al., 2006). Negative heterosis is valuable for brassicas in early maturity reported Nassimi
et al. (2006); Yadava et al. (2012) and Synrem et al. (2015).
4.44.6 Plant Height
Out of 12 crosses, only one hybrid for mid parent heterosis and three showed significant and
negative heterobeltiosis for plant height (Table 4. 43). Negative heterosis is desirable for
plant height in Brassica species. Dwarf and medium plant height resist to high wind velocity,
logging and mechanical breakage. The heterosis studied in oilseed rape for plant height was
none significant. Negative values were also noted for some crosses (Grant and Beversdorf,
1985). Significant and negative heterosis for plant height had also been discribed by many
research workers as Tyagi et al. (2000); Pourdad and Sachan (2003); Nassimi et al. (2006)
and Synrem et al. (2015).
4.44.7 Primary Branches
Two crosses out of 12 showed positive relative heterosis and heterobeltiosis for primary
branches.These crosses were Toria×UAF11, (72.55), (51.72) and Juncea×Shora (62.96),
(41.94) revealed positive and significant relative heterosis and heterobeltiosis. Positive
heterosis is desirable for Brassica species. Plant with more branches will be vigorous and
produces more yield. Positive and significant heterosis was reported for primary branches by
Gupta (2009). Similar studies were also discribed by Nasrin et al. (2011) and Synrem et al.
(2015). The highest value for heterosis and heterobeltiosis was identified for primary
branches 24.25 vs. 12.30% in Brassica species by Nausheen et al. (2015).
146
4.44.8 Secondary Branches
Two crosses out of 12 showed positive and significant heterosis secondary .Crosses
viz.Toria×UAF11 (633.33), (303.33) and Toria×Shora (198.67), (148.89). Positive and
significant heterosis is desirable for secondary branches per plant. Vigorous plant will
provide opportunity for high yielding cultivar reported by Niranjana et al. (2014) and Synrem
et al. (2015).
4.44.9 Green Biomass and Harvest Index
Only two cross combinations depicted considerable and positive heterosis and heterobeltiosis
for green biomass (Table 4. 48). Positive relative heterosis and heterobeltiosis is desirable for
high yielding cultivar. The combination Juncea×1072 (147.82), (72.14) and Toria×
(66.44),(14.96) showed positive and significant heterosis and heterobeltiosis while three,
Toria×1072 (291.77), (249.72), Juncea×Shora (118.98), (101.81) and Napus×1072 (66.12),
(51.32) crosses showed positive and significant heterosis and heterobeltiosis for harvest
index.The use of plant biomass plays an important role for animal hay and biogas
production.The estimation of heterosis for fresh biomass, dry matter and dry biomass. The
average was greater of hybrids than parental genotypes; however dry biomass was greater in
parents. It might be increased up to thirty percent (Ofori et al., 2008).
4.44.10 Number of Siliqua per Plant and Number of Seed per Siliqua
Seven hybrids showed positive and significant relative heterosis and heterobeltiosis for
number of siliqua per plant and none of 12 hybrids was significant for number of seed per
plant (4.40). For both traits positive and significant heterosis is advantageous for the
development high yielding genotypes. Results were partially similar reported by Synrem et
al. (2015).
4.44.11 Total Seed Weight (100 Seed)
Three cross combinations; Toria×1072(32.79), (24.62), Toria×Shora (42.40), (30.88) and
Juncea×Shora (44.53), (43.48) hybrid showed positive and considerable heterosis and
heterobeltiosis for 100 seed weight. Positive heterosis is desirable trait for the development
of high yielding genotype.
147
Table 4.48a Heterotic manifestation for indicated traits of interspecific crosses
Phenological traits
Traits DFI D 50%F D 50%SF DM
Crosses MP BP MP BP MP BP MP BP
Toria × 1072 27.74** -5.26 28.29** -5.76** 20.85** -10.21** 12.48** -13.38**
Toria× Napus2 11.24** -20.68** 15.18** -17.91** 11.62** -18.61** 30.75** -2.23
Toria × shora 6.78* -26.49** 11.11** -22.68** -50.66** -64.56** 38.89** -1.69
Toria ×UAF11 5.56 -0.87** 12.60** 2.14 12.87* 3.64 53.28** 48.73**
Napus1 ×1072 16.95** 16.67** 12.25** 11.34** 4.26 3.52 5.23** 0.67
Napus1 ×Napus2 1.12 -4.64** -0.97 -4.85* -4.30 -7.64* -3.79* -4.00
Napus1 ×Shora 4.18 -7.09** 1.12 -6.53** 0.00 -5.70** -1.02 -8.80**
Napus1 ×UAF11 5.23 -18.57** 4.91 -17.81** 5.17 -16.43** 33.24** 1.56
Juncea1 × 1072 -8.68** -12.66** -8.72** -10.00** -8.77** -10.21** -12.34** -19.92**
Juncea1 × Napus2 -6.87** -8.44** -5.02* -8.21** -4.51 -8.64 -9.21** -13.68**
Juncea1 × Shora -6.24** -13.06** -2.03 -8.94** 1.18** -5.38 -11.74** -14.79**
Juncea1 × UAF11 18.02** -11.35** 22.05** -4.80** 23.64** -1.09 21.97** -10.06**
148
Table 4.48 c
*=significant (p<0.05);**=highly significant (p<0.01)
Table 4.48b
Morphological traits
PH PB SB BY HI
MP BP MP BP MP BP MP BP MP BP
32.62** 20.78** 45.83* 34.62 40.21 1.49 -26.03** -26.36 291.77** 249.72**
-3.03 -13.18** -7.69 -35.71** -10.39 -44.36** 60.44** 14.96* -56.85** -61.72**
5.03 -18.04** 37.78 34.78 198.67** 148.89** -30.15** -48.00** 163.95** 134.62**
10.42 -2.35 72.55** 51.72* 633.33** 303.33** -41.31** -60.96** 27.61** -11.01
39.25** 21.53** -36.26** -55.39** -52.07** -65.33** -44.15** -62.26** 66.12** 51.23**
13.17** 5.89 -52.07** -55.39** -62.04** -65.33** 18.79** 8.07 -46.03** -50.55**
33.26** 0.53 -43.18** -61.54** -58.97** -73.33** -30.09** -39.68** -21.70 -41.22**
29.98** 10.32* -51.06** -64.62** -29.41* -64.00** -11.35* -14.41** -84.14** -87.22**
-20.34** -27.45** 36.84* 25.81 -24.62 -26.87 147.82** 72.14** -71.59** -78.48**
15.50** 3.41 -51.72** -62.50** -31.55** -48.39** 15.36** 10.00 -82.79** -87.02**
59.55** 24.51** 62.96** 41.94* 53.70** 31.75 23.56** 11.43 118.98** 101.81**
-21.95** -30.98** -40.00* -41.94* -12.12 -53.97** -79.45** -81.08 -69.18** -80.60**
Yield related traits
SL/p S/S TWS Y/P
MP BP MP BP MP BP MP BP
23.22* -16.31 1.24 -2.72 32.79** 24.62** 190.67** 156.47**
59.02** 10.67 -88.78** -90.45** -29.28** -48.39** -34.10** -56.20**
730.20** 541.39** -70.71** -72.11** 42.40** 30.88** 100.00** 65.00**
78.01** 20.91** -55.85** -62.37** 13.30** -15.52** -38.87** -65.54**
303.41** 129.92** -72.53** -74.85** 10.56 -7.29 -12.35** -43.40**
88.48** 8.65 -16.91** -26.13** -29.09** -37.10** -36.64** -46.85**
413.29** 340.38** 6.69 -3.13 -21.95** -33.33** -47.89** -65.01**
585.96** 290.96** -87.08** -88.50** -27.36** -33.62** -86.09** -89.07**
285.85** 254.29** -84.18** -85.06** -71.64** -72.46** -25.58** -38.46**
175.76** 163.95** -87.88** -90.45** -44.04** -56.45** -80.92** -84.18**
76.79** 9.05 -3.75 -8.27 44.53** 43.48** 157.26** 127.58**
-95.74** -96.09** -43.18** -55.18** -64.32** -71.55** -94.14** -96.32**
149
4.45 Heterotic Manifestation of Inter-specific Crosses for Quality Traits
4.45.1 Oil Content (%)
Heterotic manifestation for oil contents are presented in table 4.49. Out of 12 hybrid
combinations 2 combinations showed relative heterosis and heterobeltiosis. The cross
combination Toria×Shora exhibited maximum value for relative heterosis and heterobeltiosis
(11.34, 7.35) fallowed by the combination Napus1×1072 (9.87, 6.03).
4.45.2 Protein Content (%)
For protein contents combination Napus1×Shora showed maximum heterosis and
heterobeltiosis (9.14, 8.28).
4.45.3 Glucosinolate Content (µMolg-1)
Out of 12 inter-specific hybrids 3 crosses showed negative and significant heterosis for
glucosinolate. Maximum heterosis and heterobeltiosis was shown by combinations
Toria×Napus2 (-46.79,-14.22), Napus1×1072 (-25.18,-25.76) and Juncea×Napus2 (-8.81,-
14.59). Hybrid combinations with low glucosinolate content are desirable in rapeseed for
nutritional usage. This study was suported by Priyamedha et al. (2016) who indicated the
negative heterosis for glucosinolate in Indian mustard
4.45.4 Oleic Acid (%)
Only one combination showed positive heterosis as shown in table 4.49. Oleic acid is
enviable constituent of Brassica oil.Therefore for obtaining improved Brassica varieties/lines
positive levels of relative heterosis and heterobeltiosis for oleic acid is considered. Cross
Toria×Napus2 showed maximum relative heterosis (21.67) heterobeltiosis (57.29) for oleic
acid. Our results were in accordance with Ali et al. (2015) who reported the maximum
positive relative heterosis (40.30%) value for cross NUM123xNUM113 and heterobeltiosis
was positive and significant for 8 crosses.
4.45.5 Erucic Acid (%)
Erucic acid content of brassica oils, is an undesirable component that makes the oil
unsuitable for human diet. Negative heterosis and heterobeltiosis is valuable for erucic acid.
Data regarding erucic acid content (Table 4. 49). Out of 12 crosses, 1 cross showed
150
significantly negative relative heterosis and heterobeltiosis (-19.26, -21.29). Similar findings
were noted by Patel and Sharma (1999); Singh et al. (2003); Wang et al. (2009); Gami and
Chauhan (2014) and Chaudhari et al. (2015). Ali et al. (2015) also recoded the maximum
negative value (-70.28%) for relative heterosis in cross NUM009xNUM117. The maximum
negative heterobeltiosis values (-61.67) was observed in cross NUM009xNUM117.
4.46 Good Cross Combinations on The Basis of SCA, GCA Estimates and Heterosis for
Yield and Qualitative Traits.
Two cross combinations Juncea×Shora and Toria×1072 were found to be good combinations
on the basis of SCA, GCA and heterosis, presented in the table 4.50. So these two
combinations can be for commercial utlization of the heterosis for seed yield. For quality,
five combinations viz., Toria×1072, Toria×Napus2, Napus1×Shora, Juncea×1072 and
juncea×UAF11 were found batter for low erucic acid heterosis. Four combinations viz.,
Toria×Napus2, Toria×UAF11, Napus1×1072, Napus1×UAF11 and Juncea×Napus2 showed
negative heterosis for glucosinolate contents (%). Significant positive heterosis, good SCA
and GCA estimates for oleic acid were observed.
When SCA is high such crosses may be desirable combination for the improvement of
respective traits because SCA effects would be probably due to additive× additive gene
action that are fixable. Amarnth and Subrahmanyam (1992) suggested that combination with
high SCA might be useful if GCA of the parent is involved with them. The crosses selected
for oleic acid (%) i.e. Toria×Napus2, Napus1×Shora, Napus1×UAF11 and Juncea×1072 had
high SCA,GCA and heterosis, These crosses might be used for the further improvement for
the respective trait. Three combinations were also identified for oil content (%).These
combinations Napus1×1072, Napus1×Napus2 and Juncea×Shora had high SCA, GCA and
heterosis. Therefore these crosses can be used for the exploitation of heterosis for oil contents
151
Table 4.49 Heterotic manifestation of interspecific crosses for quality traits
*=significant (p<0.05);**=highly significant (p<0.01)
Quality Traits
Quality related traits
Oil contents
(%)
Protein contents
(%)
Glucosinolate content
(%)
Oleic acid
(%)
Erucic acid
(%)
Combinations MP BP MP BP MP BP MP BP MP BP
Toria ×1072 2.99 1.14 -1.99 -3.90 1.73 -14.22 ** -14.17 ** 24.84 ** -1.77 -16.15 **
Toria × Napus 2 1.51 -2.04 -7.72 ** -9.13 ** -40.04 ** -46.79 ** 21.67 ** 57.29 ** -19.26 ** -21.29 **
Toria×Shora 11.34 ** 7.35 ** -1.92 -2.92 18.02 ** -0.38 -25.03 ** 3.07 39.00 ** 23.47 **
Toria×UAF-11 1.27 -4.49 * -3.54 -3.78 7.24 ** -0.73 -12.18 ** 2.54 15.46 ** 0.22
Napus1× 1072 9.87 ** 6.03 ** -5.48 * -7.55 ** -25.18 ** -25.76 ** -20.98 ** 34.36 ** 84.99 ** 57.84 **
Napus1×Napus2 22.90 ** 16.58 ** -5.29 * -6.50 * -0.56 -6.92 ** -18.72 ** 25.05 ** -3.26 -28.67 **
Napus1×Shora -1.92 -3.77 9.11 ** 8.28 ** 17.03 ** 15.96 ** -7.05 ** 50.63 ** -9.88 ** -25.95 **
Napus1×UAF11 -13.80 ** -20.06 ** 0.89 0.38 9.14 ** -2.12 -6.36 ** 32.35 ** 9.67 ** -25.00 **
Juncea×1072 4.06 * 3.42 -2.44 -2.56 46.90 ** 45.84 ** -19.29 ** 41.75 ** 68.36 ** 58.11 **
Juncea×Napus 2 1.13 -1.26 -2.65 -5.86 * -8.81 ** -14.59 ** -19.06 ** 29.07 ** 46.39 ** 29.18 **
Juncea×Shora 15.40 ** 9.98 ** -4.15 -6.84 ** 0.38 -0.47 -33.17 ** 12.05 ** 64.12 ** 61.20 **
Juncea×UAF11 -1.92 -6.44 ** 2.73 1.10 66.29 ** 49.21 ** -31.94 ** 0.00 25.92 ** 0.28
152
Table 4.50 Good cross combinations for seed yield and quality traits on basis of SCA,
heterosis and GCA effects
Character Name of
combinations SCA effects
Heterosis GCA effects
MP BP Parent 1 Parent2
Yield Juncea ×Shora 17.45** 157.26** 127.58** -3.01** 7.81**
Toria × 1072 4.19** 190.67** 156.47** 4.30** 3.37**
Erucic acid (%)
Toria ×1072 -9.65 ** -1.77 -16.15 ** -0.84 * -0.39
Toria × Napus 2 -5.84 ** -19.26 ** -21.29 ** -0.84 * -4.64 **
Napus1 × Shora -10.66 ** -9.88 ** -25.95 ** -9.70 ** -2.16 **
Juncea × 1072 -1.83 * 68.36 ** 58.11 ** 10.54 ** -0.39
Juncea × UAF11 -5.47 ** 25.92 ** 0.28 10.54 ** 7.19 **
Glucosinolate (%)
Toria × Napus 2 -14.80 ** -40.04 ** -46.79 ** 2.64 ** -20.97 **
Toria × UAF-11 -7.15 ** 7.24 ** -0.73 2.64 ** 24.09 **
Napus 1 ×1072 -19.89 ** -25.18 ** -25.76 ** -12.13 ** -3.67 **
Napus1 × UAF11 -10.61 ** 9.14 ** -2.12 -12.13 ** 24.09 **
Juncea × Napus 2 -6.81 ** -8.81 ** -14.59 ** 9.49 ** -20.97 **
Oleic acid (%)
Toria × Napus 2 7.66 ** 21.67 ** 57.29 ** -1.31 ** 3.49 **
Napus1 × Shora 6.06 ** -7.05 ** 50.63 ** 3.00 ** -1.31 *
Napus1 × UAF11 3.53 ** -6.36 ** 32.35 ** 3.00 ** -4.56 **
Juncea × 1072 4.25 ** -19.29 ** 41.75 ** -1.69 ** 2.39 **
Oil (%)
Napus 1×1072 1.69 * 9.87 ** 6.03 ** -0.67 0.43
Napus1 ×Napus2 5.83 ** 22.90 ** 16.58 ** -0.67 2.37 **
Juncea × Shora 2.66 ** 15.40 ** 9.98 ** 0.65 -0.79
153
4.47 Inbreeding Depression for Quantitative Traits
Inbreeding depression is central phenomenon in the history of evolution of out crossing
mating system because intercrossing inbred strain recovers the yield (heterosis). The genetic
base is under discussion since twentieth century. Classical and modern molecular genetics
studies propose that inbreeding depression and heterosis are mainly due to the occurance of
recessive deleterious (Charlesworth and Willis, 2009). The inter-specific crosses were made
and their inbreeding depression in F2 generation of some selected hybrids has been studied
(Table 4.51). The cross combination UAF11×Toria (-77.86) and Toria×UAF11 (-52.45)
showed negative and significant inbreeding depression for days to flowering initiation that
showed none additive gene action is involved. All other combinations showed none
significant inbreeding depression.
For days to 50%flowering three combinations indicated negative and considerable
inbreeding depression while one combination indicated non-inbreeding depression. The
magnitude of negative inbreeding depression from F1 to F2 indicated the enhancement for
days to 50%flowering in F2. However, Gupta et al. (1981) described additive gene action for
this trait. For days to maturity all combinations depicted positive inbreeding depression. Only
four combinations showed positive and significant inbreeding depression. Inbreeding
depression range was from 10.98 to 34.32 %. The results indicate that there was difference
between F1 and F2 combinations for days to maturity. Anantharuja and Muthiah (2008)
observed 50 to 78.57% of inbreeding depression for days to maturity. Pandey (1972) and
Sharma et al. (1972) indicated additive gene action for days to maturity. However Sindhu and
Sandhu (1981) reveled that days to maturity were due to non-additive gene action.
Nine combinations out of 12 combinations showed positive inbreeding depression for
plant height. All values were none significant. The highest value of inbreeding depression
was found in UAF11×Juncea (-51.14). The negative inbreeding depression shows that F1
were smaller than F2 .Sharma (1981) discribed that both dominant and additive gene effects
were important in plant height. Gumber et al. (2006) observed -23 to 78% of inbreeding
depression. Anantharuja and Muthiah (2008) observed described up to 23.80 86.95% of
inbreeding depression. Seven combinations showed inbreeding depression in primary
branches. All combinations were positive significant in inbreeding depression. Two
combinations showed negative but significant inbreeding depression. For primary branches
154
inbreeding depression was significant. Both negative and positive inbreeding depression
shows significant difference between F1s and F2s Chaudhari et al. (1980) showed additive
gene action for this character.
For secondary branches five cross combinations showed positive and significant
inbreeding depression. UAF11×Juncea showed negative maximum inbreeding depression.
Both positive and negative inbreeding depression indicated the significance of additive and
dominance gene action. Biological yield showed negative significant inbreeding depression.
The negative inbreeding depression showed that there was dominance effect of gene. High
level of positive and negative inbreeding depression was also confirmed for harvest index.
Three crosses had maximum values of inbreeding depression. Inbreeding depression range
was from -8.8 to 71.88 % showing importance for additive and non additive gene action for
the harvest index that is an important yield contributing trait in brassicas.
Number of siliquae per plant showed positive inbreeding depression for all
combinations except UAF11×Juncea that showed negative inbreeding depression. Positive
inbreeding depression showed additive gene action. Sexena et al. (1981) showed additive
gene action for number of pods per plant. Four cross combinations showed high and
significant values of inbreeding depression for number of seed per siliqua. Seven
combinations showed significant and negative inbreeding depression for number of seed per
siliqua. The results indicate both dominant and additive gene action for number of seed per
siliqua. Sexena et al. (1981) showed additive gene action for number of seed per plant while
Kapur (1977) comfirmed additive aswell as non-additive gene action for number of seed per
siliqua.
Out of 12 cross combinations, seven showed positive and significant inbreeding
depression for 100 seed weight. Four combinations showed significant negative inbreeding
depression. Similar results were reported by Sexena et al. (1981) and Mohamed et al. (1985).
Reddy et al. (1979) showed none additive gene action for 100 seed weight. There was
substantial amount of inbreeding depression in most cross combinations for seed yield per
plan. Out of 12 cross combinations 6 showed positive and significant inbreeding depression
and two showed significant negative inbreeding depression. Both positive and negative
significant values of inbreeding depression have been recorded. Anantharuja and Muthiah
(2008) observed 22.20 to 43.47% of inbreeding depression for seed yield per plant.
155
4.48 Inbreeding Depression for Quality Traits
For quality traits the cross combination Napus2×1072 showed highest positive inbreeding
depression that was statistically significant followed by Napus1×Napus2 (Table 4.52). Four
combinations showed negative and non-significant inbreeding depression for oil. The
combination showed positive inbreeding depression that means an additive gene action is
involved.
For protein the combination Shora×Juncea showed highest negative inbreeding
depression (-9.17) followed by Napus2×Toria (-7.60).The positive highest level of
inbreeding depression was shown by Napus1×UAF11 (7.79). For positive inbreeding
depression additive gene action is involved. All combinations showed non-significant results
for in breeding depression in case of glucosinolate contents. All combinations showed
negative and significant inbreeding depression for oleic acid. All combination significant
showed positive and significant positive inbreeding depression except the Napus2×Napus1
indicated negative and significant inbreeding depression for erucic acid.
4.49 Gentic Variability of Direct and Some Indirect Inter Specific Crosses for Quality
Parameters
The data recorded for different quality traits were subjected to analysis of variance to confirm
the variation among them. Mean square values from analysis of variance (Table 4.53). The
results show highly considerable differentiation among genotypes for all quality parameters.
The sum of square values of genotypes was further partitioned into parents, Crosses and P vs.
C which showed highly significant differences in quality traits studied. The sum of square
values calculated for crosses were also divided into lines, testers, line×tester and L vs. T
components. Highly considerable differences were present among them for all these traits
except for protein content for tester and line×tester that was none significant. The mean sum
of square due to genotype, parents, crosses lines ×testers and their interaction were
significant showing that parental lines used in present study having the diverse genetic
makeup.
156
Table 4.51 Inbreeding depression for quantitative traits
*=significant (p<0.05);**=highly significant (p<0.01) DFI stands for days to flowering initiation, D50%F for days to 50%flowering, D50%SF for days 50% siliqua formation, DM for days to maturity, PH for
plant height, PB for primary branches, SB for secondary branches, GB for green biomass yield, HI for harvest index, S/PL for siliquae per plant, S/S for seed
per siliqua, TSW for 100 seed weight, Y/P for yield per plant
Phenological traits Morphological traits Yield related traits
Combinations DFI D50%F D50%SF DM PH PB SB GB HI SL/P S/S TWS Y/P
ID ID ID ID ID ID ID ID ID ID ID ID ID
UAF11×Toria -77.86** -93.58** -72.48** 10.98 50.3 22.92** -12.96 60.81 20.72 89.18 23.55** 33.33** 69.18*
UAF11×1072 -24.34 -44.27** -15.18 21.65 4.84 -15.22* 50.32** 61.86 37.48 81.14 30.77** 16.30** 76.69**
UAF11×Napus1 7.87 -4.46 11.19 18.11 12.14 46.67** 3.77 44.29 37.94 79.81 -94.02** -69.35** 65.10*
UAF11×Juncea -9.81 -18.03 -4.92 34.32* -51.14 15.00* -35.00* -209.80** 38.45 -361.78 2.19 -178.79** -87.52**
Napus2×1072 -6.79 -10.77 6.13 26.48 -9.34 -3.45 19.78 -63.21 57.66** 90.08 -52.33** 46.09** 30.29
Napus2×Toria 7.72 2.69 10.42 29.3 17.12 -88.46** 13.33 32.16 32.07 78.67 -41.83** 25.83** 53.69*
Napu2×Napus1 0.83 3.56 1.15 20.61 37.28 2.00 15.79 -33.06 5.23 91.16 121.94** 19.30** -26.8
Napus2×Juncea 6.05 4.02 10.56 34.03* 12.67 16.67* 49.49** -25.83 26 84.36 -76.03** -46.15** -17.96
shora×Toria 10.31 7.76 18.35 31.36* 16.48 -5.45 47.21* 43.56 -628.03** 93.37 -59.55** -35.42** -307.63**
Shora×Juncea 9.47 0 15.53 29.16 16.96 28.57** 42.86* -47.47 71.88** 79.53 44.72** 52.94** 58.53*
Toria×UAF11 -52.45** -71.93** -40.35** 11.11 -11.24 29.55** 41.32* -166.15** -8.8 78.98 -17.80** 3.06** -192.40**
1072×Napus2 2.48 0.94 6.14 31.26* 7.17 11.43 39.22* 53.33 69.07** 91.97 -51.31** -10.17** 85.75**
SE 14.55 15.3 17.38 18.14 52.91 7.12 19.05 63.66 23.07 1260.65 6.72 0.12 30.71
157
Table 4.52 Inbreeding depression for quality traits in Brassica cross combinations
*=significant (p<0.05);**=highly significant (p<0.01)
Characters
Quality related traits
Oil % Protein % Glucosinolate % Oleic acid % Erucic acid
%
Crosses ID ID ID ID ID
UAF11×Toria -3.23 2.39 34.29 -25.67** 35.58**
UAF-11 ×1072 11.98* -1.01 2.3 -50.31** 39.11**
Napus2×Toria -2.46 -7.60** 18.5 -111.19** 32.89**
Napus2×1072 22.29** -4.15* 28.36 -34.49** 45.39**
Napus2×Napus1 18.48** -5.26** 28.95 -136.07** -21.19*
Shora×Toria -4.95 -6.59** -39.42 -102.48** 32.57**
Shora×Juncea 11.39* 3.97* 33.78 -28.62** 52.98**
Toria×1072 5.8 -5.07** -6.79 -93.20** -8.01
Toria×UAF-11 14.42** 6.55** 29.23 -25.28** 48.17**
Juncea×1072 12.83** -0.37 46.39 -63.87** 42.68**
Juncea×Shora 17.77** -9.17** -50.19 -58.63** 19.65*
Napus1×UAF11 -2.53 7.79** 32.59
40.59**
SE of mean 5.06 1.93 31.63 9.31 11.25
158
Table 4.53 Mean square values for quality parameters of Brassica campestris.
*=significant(p<0.05);**=highlysignificant(p<0.01)
4.50 General Combining Ability Estimates for Quality Traits
Variations for general combing ability affects were studied among the lines and testers used
in inter-specific hybridization for quality traits to locate the best parent. The results for
general combining ability effects are presented in Table 4.54. For oil contents among lines all
difference were none significant and among testers Napus2 was the best general combiner
(2.37). Regarding the protein, among lines showed none GCA effects while results for testers
UAF11 (0.59) showed maximum positive GCA effects. High proteins contents are valuable
for Brassica meal therefore the general combiner should be selected that have maximum
general combining ability effects. Some lines and some testers showed the GCA effects in
positive or in negative directions for glucosinolate contents. For glucosinolate contents
parents Toria (2.64) and juncea (9.49) among lines and UAF11 (24.09) were good general
combiner among testers while parents Napus1 (3.00) among lines and 1072 (2.39) and
Napus2 (3.49) among testers revealed good general combining ability in term of oleic acid,
while Toria (-0.84), (-9.70) among lines, Napus2 and Shora (-2.16) among testers for low
erucic acid.
Quality related traits
Source of
variation DF
Oil
contents
(%)
Protein
contents
(%)
Glucosinolate
contents
(%)
Oleic acid
(%)
Erucic acid
(%)
Replication 2 3.94* 4.56** 0.84 5.96** 3.25
Genotype 18 31.31** 3.50** 1386.93** 174.73** 479.47**
Parents 6 21.00** 1.51** 593.10** 210.07** 452.39**
Crosses 11 36.74* 4.63** 1894.98** 105.85** 444.56**
P Vs C 1 33.42** 2.95** 561.40** 720.46** 1025.90**
Lines 2 5.21** 3.82** 1465.73** 81.44** 1234.50**
Testers 3 31.37** 6.51 3100.89** 121.05** 233.84**
L × T 6 49.94** 3.96 1435.11** 106.38** 286.61**
L VS T 1 16.87** 0.53* 77.22** 107.77** 423.54**
Error 36 1.20 0.71 3.06 1.51 1.40
159
4.51 Specific Combining Ability Estimates for Quality Traits
The specific combining ability estimates showed that 1 inter-specific cross combinations
displayed considerable positive SCA effects for oil contents (Table 4.55). Maximum
significant and positive SCA effect was shown by Napus1×1072 (1.69*) while for protein
maximum SCA effects were shown by inter-specific combination Napus1×Shora (1.67*).All
cross combinations showed SCA effects in positive or in negative direction for glucosinolate
contents. The combinations with negative SCA effects should be selected for nutritional
usage. Maximum significant and positive SCA effects were exhibited by the inter-specific
combinations Napus1×1072 (-19.89), Toria×Napus2 (-14.80), Napus1×UAF11 (-10.61) and
Juncea×Napus2 (-6.81) while for oleic acid the cross combination Toria×Napus2 (7.66),
Napus1×Shora (6.06), Juncea×1072 (4.25) and Napus1×UAF11 (3.53). For erucic negative
and remarkable SCA effects were dipcted by the cross combination Napus1×Shora (-10.66),
Toria×Napus2 (-5.84) Juncea ×1072 (-1.83) and Juncea×UAF11 (-5.47).
4.52 Components of Genetic Variance
Components of variances for indicated quality traits in inter-specific crosses (Table 4. 56). It
is clear from the table that specific combining ability was more important than general
combining ability and dominance variance than additive variance. Specific combining ability
or dominance variance was more important for all traits. Degree of dominance was 0 for oil
content (%), greater than 1 for protein and glucosinolate, 0 for oleic acid and greater than 1
for erucic acid. All these traits can be utilized for heterotic effects of their genotypes. The
magnitude of SCA was higher than GCA for oil content indicating the performance of
dominant gene action.Several studies suggested occurance of additive genetic action for oil
content (Shen et al., 2005; Delourme et al., 2006; Wu et al. 2006; Qian et al., 2007;
Sabaghnia et al., 2010 and Singh et al., 2010) the results of study showed the importance of
dominance effects in this trait. Downey and Rimer (1993); Sheikh (1998) and Sabaghnia et
al. (2010) described the importance of non-additive gene action in controlling the oil content.
Both additive and non-additive effects were also found to influence oil content in B. napus
(Rameah et al., 2003; Cheema and Sadaqat, 2004). Wang et al. (2010) indicated that oil
content was mainly influenced by dominant and additive effects, with dominant effect the
most important player.
160
Table 4.54 General combining ability for quality traits of inter-specific crosses
Parents
(males & females)
Oil contents
(%)
Protein contents
(%)
Glucosinolate
Content (%)
Oleic acid
(%)
Erucic acid
(%)
Lines
Toria 0.02 -0.64 ** 2.64 ** -1.31 ** -0.84 *
Napus1 -0.67 0.23 -12.13 ** 3.00 ** -9.70 **
Juncea 0.65 0.42 9.49 ** -1.69 ** 10.54 **
SE 0.35 0.22 0.54 0.41 0.36
Testers
1072 0.43 0.16 -3.67 ** 2.39 ** -0.39
Napus2 2.37 ** -1.24 ** -20.97 ** 3.49 ** -4.64 **
Shora -0.79 0.50 0.55 -1.31 * -2.16 **
UAF11 -2.01 ** 0.59 * 24.09 ** -4.56 ** 7.19 **
SE 0.40 0.25 0.62 0.48 0.41
Table 4.55 Estimates of Specific Combining Ability Effects For Quality Traits of Interspecific crosses
Combinations Oil contents
(%)
Protein contents
(%)
Glucosinolate
Content (%)
Oleic acid
(%)
Erucic acid
(%)
Toria ×1072 -1.00 0.85 5.17 ** -1.47 -9.65 **
Toria × Napus 2 -2.77 ** -0.15 -14.80 ** 7.66 ** -5.84 **
Toria × Shora 1.19 -0.26 16.78 ** -4.64 ** 9.62 **
Toria × UAF11 2.58 ** -0.45 -7.15 ** -1.56 5.87 **
Napus1 ×1072 1.69 * -1.01 * -19.89 ** -2.78 ** 11.47 **
Napus 1× Napus2 5.83 ** -0.45 21.61 ** -6.81 ** -0.41
Napus1× Shora -3.85 ** 1.67 ** 8.89 ** 6.06 ** -10.66 **
Napus1 × UAF11 -3.66 ** -0.21 -10.61 ** 3.53 ** -0.40
Juncea × 1072 -0.69 0.16 14.72 ** 4.25 ** -1.83 *
Juncea × Napus2 -3.06 ** 0.59 -6.81 ** -0.85 6.25 **
Juncea × Shora 2.66 ** -1.42 ** -25.67 ** -1.42 1.04
Juncea × UAF11 1.09 0.66 17.76 ** -1.97 * -5.47 **
SE 0.69 0.44 1.07 0.82 0.71
161
Table 4.56 Components of genetic variance
*=significant (p<0.05);**=highly significant (p<0.01)
4.53 Contribution (%) of Lines, Testers and Their Interaction for Quality Traits
A line×tester analysis of inter-specific crosses with 4 female lines and 3 males’ lines was
used to find the relative contribution of lines, testers and line×tester to the whole of variance
for indicated quality traits. Their proportional contribution for five quality traits has been
presented in the table 4.57. It is clear from the table that lines made less contribution towards
oil (2.58%), protein (14.19%), oleic acid (11.99. %) and more for erucic acid showing
predominant maternal influence for these traits. Testers made more contribution for all traits
except erucic acid (14.23%) indicating preponderance of paternal effect for these traits. Their
interaction contribution was relatively higher for oil (74.14%), protein (46.66%),
glucosinolate (41.31%) and oleic acid (54.82%).
Table 4.57 Contribution (%) of lines, testers and their interactions for quality traits of
interspecific combinations.
Parents and
their interactions
Oil content
(%)
Protein content
(%)
Glucosinolate
Content (%)
Oleic acid
(%)
Erucic acid
(%)
Lines 2.58 14.99 14.06 13.99 50.49
Testers 23.28 38.35 44.63 31.19 14.35
Lines × Testers 74.14 46.66 41.31 54.82 35.17
Genetic components Oil contents
(%)
Protein contents
(%)
Glucosinolate
Contents
(%)
Oleic acid
(%)
Erucic acid
(%)
Cov H.S (line) -3.73 -0.01 2.55 -2.08 78.99
Cov H.S(tester) -2.06 0.28 185.09 1.63 -5.86
Cov F.S 9.32 1.39 659.09 33.65 192.22
VAR OF GCA -0.57 0.03 19.84 -0.02 6.81
VAR OF SCA 16.17 1.13 477.22 34.78 95.03
IF F=0 ; A -2.28 0.12 79.35 -0.09 27.25
IF F=0 ; D 64.66 4.52 1908.87 139.12 380.13
Degree Dominance
{α2D
/α2A } ½
0.00 6.14 4.90 0.00 3.73
162
4.54 Heritability and Genetic Advance for Quantitative Traits
Days to flowering initiation showed high heritability (97.27) along with high genetic advance
(42.76) that indicated the additive gene action and selection might be successful (Table 4.58).
Similar approaches were noted by Ali et al., (2003); Amiri-Oghan et al. (2009) and Zare and
Sharafzadah (2012). Days to 50% flowering indicated high heritability (97.62) and high
genetic (47.86) advance in percentage of mean.studies were agreed with results noted by Dar
et al. (2010). Days to 50% siliquae formation, days to maturity and plant height showed high
heritability along with high genetic advance. Results were partially agreed with reults
reported by Paikhomba et al. (2014). Number of primary branches, secondary branches, and
biomass and harvest index presented remarkable heritability along genetic advance. Our
findings were in accordance with results presented by Ali et al. (2003); Mahmud (2008) and
Aytac et al. (2008). Number of siliqua per plant and number of seed per siliqua showed high
heritability along with high genetic advance in percentage of mean that revealed additive
genetic effects. Similar results were reported by Ali et al. (2003); Mahmud (2008); Aytac et
al. (2008) and Rameeh (2013). 100 seed weight showed high heritability along with high
genetic advance that shows additive gene effects. In case of yield both heritability and
genetic advance were high and selection will be effective way for the improvement in yield.
Our results are in accordance with the findings of Singh and Singh (1997) and Sheikh et al.
(1999).
Table 4.58 Heritability and Genetic advance for quantitative trait
Character Heritability Genetic advance DFI 97.27 42.76
D 50%F 97.62 47.86
D 50%SF 96.57 39.9
DM 98.21 45.69
PH 92.79 62.31
PB 73.92 101.3
SB 84.96 100.38
GB 97.15 160.79
HI 97.27 171.11
SL/p 98.97 121.23
S/S 98.44 68.29
TWS 95.13 154.01
Y/P 98.31 154.01
163
4.55 Heritability and Genetic Advance for Quality Traits
Oil contents have high heritability (89.28) with moderate genetic advance (14.91) in
percentage of mean that showed additive gene action and selection might be successful
(Table 4.59). Similar results were noted by Ghosh and Gulati (2001). However, Khulbe et al.
(2000) and Shoukat et al. (2014) who observed low heritability for oil content. Protein
contents depicted considerable heritability (56.86) with less genetic advance (5.74) that
showed these traits were highly influenced by the environment and selection cannot be
rewarding. Glucosinolate also showed high heritability (99.07) and high genetic advance
(48.15). Similar findings were reported by Bradshaw and Wilson (1998) in case of
heritability. For oleic acid and erucic acid high heritability along with high genetic advance
were observed. Results were supported by Chauhan et al. (2002) who noted moderate to
greater heritability associated with more genetic advance (45.0-62.5%) for erucic acid.
4.56 Phenotypic and Genotypic Correlation for Interspecific Crosses
Correlation is useful for evaluating the traits for further breeding program. Before going to
the selection of a trait, it is imperative to know effect of trait under study on other traits.
Correlation present between different traits helps the plant breeders in selection of superior
parents for their breeding (Qulipor et al., 2004).
Days to flower initiation had highly significant correlation with 50% flowering, 50%
siliquae formation, maturity days and negative for seeds per siliqua. Correlation of flower
initiation was negative with harvest index, 100 seed weight and yield per plant. Days taken to
50% flowering indicated significant correlation with days to flower initiation, days to 50%
siliquae formation and days taken to full maturity but it gave negative correlation with yield
of the plants while. Days to 50% siliquae formation was highly significant correlated with
Table 4.59 Heritability (%) and Genetic advance values (%) mean for quality traits.
Characters Heritability Genetic advance
Oil contents (%) 89.28 14.91
Protein contents (%) 56.86 5.74
Glucosinolate contents (%) 99.34 48.15
Oleic acid (%) 97.46 36.38
Erucic acid (%) 99.13 57.96
164
traits like days to flower initiation, days to 50% flowering, days to maturity, plant height and
also for harvest index while on other hand it had negative correlation with seed yield
Maturity days had positive significant correlation with days to flower initiation, days to 50%
flowering, number of secondary branches, harvest index and seeds/ siliqua (Table 4.60).
Related observation were noted by (Poorva-sinha et al., 2001). Plant height had significant
correlation with number of primary branches and secondary branches but was highly
significant with 100 seed weight and non-significant correlation with seed yield.Studies were
supported by Marjanovic-Jeromela et al. (2015) and Khayat et al. (2012). Number of primary
branches displayed highly considerable correlation with secondary branches and thousand
seed weight but significant with seed yield and harvest index. Number of secondary branches
had significant association with days to maturity and seeds per siliquae but 1000 seed weight
and number of secondary branches had highly significant correlation. With seed yield
primary branches indicated negative non-significant correlation. Alam (2010) did not support
the results and described significant correlation between number of primary branches per
plant and seed yield/hectare.Correlation was considerable between biomass and number of
primary branches, and was also highly significant between biomass and harvest index and
number of siliquae/plant. There was a non-significant correlation between biomass yield and
seed yield. Correlation of harvest index with days to maturity was significant and highly
significant with biomass, seeds/siliquae, thousand grain weight and yield per plant. Number
of siliquae/ plant showed significant correlation with yield/plant but was highly significant
with seeds/ siliquae biomass. Guo et al. (1987); Ozer et al. (1999) and Rameeh (2011)
reported almost similar results.Significant correlation was estimated between seeds/ siliquae
and harvest index but highly significant correlation was found between seeds/ siliquae and
days to maturity, number of siliquae per plant, thousand seed weight and yield per plant.
Gangapur et al. (2009) supported these results. Tyagi et al. (1996) and Dhillon et al. (1990)
also indicated the similar results. Correlation of thousand seed weight was highly significant
with plant height, number of primary branches, and number of secondary branches, harvest
index, seeds per siliquae and yield per plant. Yield/plant was significantly correlated with
traits like days to maturity, number of primary branches, harvest index, seeds/ siliquae and
thousand seed weight. Halder et al. (2016) and Tuncturk and Ciftci (2007) supported these
results.
165
Table 4.60 Phenotypic Correlations (below) & Genotypic (Above) Diagonal
*=significant (p<0.05);**=highly significant (p<0.01) DFI stands for days to flowering initiation, D50%F for days to 50%flowering, D50%SF for days 50% siliqua formation, DM for days to maturity, PH for
plant height, PB for primary branches, SB for secondary branches, GB for green biomass yield, HI for harvest index, S/PL for siliquae per plant, S/S for seed
per siliqua, TSW for 100 seed weight, Y/P for yield per plant
Phenological traits Morphological traits Yield related traits
DFI D 50%F D 50%SF DM PH PB SB GB HI SL/p S/S TWS Y/P
DFI 1 0.995** 0.824** 0.833** 0.181 0.057 0.13 0.115 -0.204 0.018 -0.286* -0.091 -0.221
D 50%F 0.990** 1 0.835** 0.841** 0.201 0.105 0.181 0.109 -0.181 0.036 -0.306 -0.063 -0.201
D 50%SF 0.819** 0.830** 1 0.530** 0.262* 0.122 0.001 0.218 -0.287* -0.089 -0.127 -0.125 -0.183
DM 0.817** 0.826** 0.520** 1 0.041 0.051 0.341** 0.048 -0.300* 0.207 -0.565** -0.088 -0.349**
PH 0.163 0.185 0.247 0.034 1 0.280* 0.281* 0.095 0.11 0.238 -0.216 0.359** 0.041
PB 0.047 0.083 0.12 0.047 0.19 1 0.850** 0.320* 0.266* 0.002 0.151 0.560** 0.499**
SB 0.127 0.175 0.039 0.318* 0.245 0.725** 1 -0.014 0.201 0.137 -0.274* 0.468** 0.121
GB 0.113 0.105 0.211 0.05 0.085 0.282* -0.022 1 -0.450** 0.378** 0.08 -0.054 0.217
HI -0.197 -0.175 -0.281 -0.300* 0.094 0.221 0.188 -0.447** 1 -0.203 0.392** 0.551** 0.592**
SL/p 0.019 0.038 -0.08 0.2 0.231 0.016 0.135 0.365** -0.189 1 -0.727** -0.197 -0.265*
S/S -0.182 -0.184 -0.063 -0.385** -0.099 0.128 -0.176 0.054 0.283* -0.413** 1 0.612** 0.878**
TWS -0.082 -0.057 -0.115 -0.081 0.347** 0.464** 0.40621** -0.044 0.519** -0.191 0.438** 1 0.751**
Y/P -0.224 -0.204 -0.186 -0.345** 0.037 0.429** 0.104 0.214 0.590** -0.253 0.631** 0.729** 1
166
4.57 Path analysis for Interspecific Crosses
Path coefficient analysis is generally used for evaluation of significance of traits on yield.
This method explains the relationship between traits and also tells about the direct and
indirect effect of the traits on yield. Seeds per silique had positive direct effect on over all
yield (0.569) and highest indirect positive effect via days to maturity followed by thousand
grain weight and siliqua per plant (Table 4.61). It is clear from the results that by increasing
seeds per siliqua yield is directly increased (Ara et al., 2013). Days taken to 50% flowering
(2.470) showed positive direct effect with yield of the plant and indirect effect (-1.980) by
days to flower initiation. It means that reduction to days to flowering required to get 50%
flowering in less days to increase yield. Direct effect of days to 50% siliqua formation had
positive (0.027) but days to flower initiation (-1.641) exhibited highest indirect effect on the
yield (Halder et al., 2016).Days to maturity exert highest negative direct effect (-0.775) on
yield while on the other had maximum positive indirect effect (2.078) on yield via days to
50% flowering. If days to maturity were reduced then get highest yield. Plant height
presented negative direct effect (-0.326) on seed yield and on the other hands it had
maximum positive indirect effect (0.495) through days to 50% flowering followed by
thousand grain weight (Ara et al., 2013) Number of primary branches depicted direct effect
(-1.265) on seed yield but gave had maximum indirect effect (0.831) on seed yield via
secondary branches. Results indicate that by reducing the number of primary branches yield
can be increased. Basalma (2008) also gave samilar results as in our experiment. Number of
secondary branches exerted highest direct positive effect (0.978) on yield while had highest
indirect effect (0.447) via days to 50% flowering on overall yield. So by increasing number
of secondary branches yield can be improved. Biomass gave positive direct effect (1.151) on
seed yield while on the other hand positive indirect effect (0.269) via days to 50% flowering.
Seeds/silique presented negative effect on yield but had maximum indirect effect via
thousand grain weight. But increasing thousand grain weights, yield per plant can be
increased. Similar results were reported by (Rameeh, 2011). Thousand seed weight presented
maximum positive effect (0.668) on overall yield while on other hand had maximum indirect
effect (0.368) through harvest index on yield.Similar observations were indicated by Uddin et
al. (1995); Yadava et al. (1996); Chaudhury et al. (1987) and Tuncturk and Ciftci (2007).
167
Table 4.61 Direct (Diagonal) and indirect of various traits on yield of inter specific crosses
DFI stands for days to flowering initiation, D50%F for days to 50%flowering, D50%SF for days 50% siliqua formation, DM for days to maturity, PH for
plant height, PB for primary branches, SB for secondary branches, GB for green biomass yield, HI for harvest index, S/PL for siliquae per plant, S/S for seed
per siliqua, TSW for 100 seed weight, Y/P for yield per plant
Traits Phenological traits Morphological traits Yield related traits
DFI D 50% F D 50% SF DM PH PB SB GB HI SL/p S/S TSW
DFI -1.99 2.458 0.022 -0.646 -0.059 -0.072 0.127 0.132 -0.136 -0.007 0.011 -0.061
D 50% F -1.98 2.47 0.022 -0.652 -0.065 -0.133 0.177 0.125 -0.121 -0.014 0.012 -0.042
D 50% SF -1.641 2.064 0.027 -0.411 -0.086 -0.154 0.001 0.251 -0.192 0.036 0.005 -0.083
DM -1.658 2.078 0.014 -0.775 -0.013 -0.064 0.334 0.055 -0.201 -0.084 0.022 -0.059
PH -0.36 0.495 0.007 -0.032 -0.326 -0.354 0.276 0.109 0.074 -0.096 0.008 0.24
PB -0.114 0.26 0.003 -0.039 -0.091 -1.265 0.831 0.369 0.178 -0.001 -0.006 0.374
SB -0.258 0.447 0 -0.265 -0.092 -1.075 0.978 -0.016 0.134 -0.055 0.011 0.313
GB -0.228 0.269 0.006 -0.037 -0.031 -0.406 -0.014 1.151 -0.3 -0.153 -0.003 -0.036
HI 0.406 -0.448 -0.008 0.233 -0.036 -0.337 0.197 -0.518 0.668 0.082 -0.015 0.368
SL/p -0.036 0.088 -0.002 -0.16 -0.078 -0.003 0.134 0.435 -0.136 -0.404 0.028 -0.132
S/S 0.569 -0.755 -0.003 0.437 0.07 -0.191 -0.268 0.092 0.261 0.293 -0.038 0.409
TSW 0.181 -0.155 -0.003 0.068 -0.117 -0.709 0.457 -0.063 0.368 0.079 -0.024 0.668
168
4.58 Correlation and Path Analysis for Quality Traits
Protein content had considerable positive correlation with glucosinolate and negative
significant correlation with oleic acid and considerable positive correlation with erucic acid.
Glucosinolate has positive and significant correlation with erucic acid and negative with oleic
acid. Oleic acid had negative correlation with erucic acid (Table 4.62). The similar
relationship between oil and protein content was not supported by Alemeyehu and Becker
(2000), who reported negative correlation. Azam et al. (2013) observed that Protein content
had positive and significant correlation with erucic acid and none significant with
glucosinolate content. Abideen et al. (2013) also reported positive non-significant association
between glucosinolate and erucic acid content. Similar findings were supported by
Krzymanski and Downey (1969) that oleic acid was negatively associated with erucic acid.
Protein contents had direct negative effect (-0.983) and highest indirect effect (0.567)
via erucic acid on oil contents (Table 4.63). Glucosinolate contents had direct positive effect
(0.425) and indirect effect (0.283) was positive via erucic acid. Oleic has direct negative
effect (-0.09) and Erucic acid has direct negative effect (-0.072) on oil contents. Tahira et al.
(2015) also indicated the similar results for these quality traits.
Table 4.62 Phenotypic (below) & Genotypic (Above) Diagonal
*=significant (p<0.05);**=highly significant (p<0.01)
Characters Oil
contents
(%)
Protein
contents
(%)
Glucosinolate
contents (%) Oleic acid
(%) Erucic
acid (%)
Oil contents
(%) 1 -0.149 0.224 0.002 0 .187
Protein contents
(%) -0.128 1 0.525** -0.498** 0.768**
Oil contents
(%) 0.214 0.368** 1 -0.3428** 0.380**
Glucosinolate
contents (%) 0.001 -0.347** -0.342** 1 -0.338**
Erucic acid
(%) 0.18 0.544** 0.378** -0.337* 1
169
Table 4.63 Direct (Diagonal) and indirect effect path coefficients of inter-specific crosses
Characters Protein content
(%)
Glucosinolates
content (%)
Oleic acid
(%)
Erucic acid
(%)
Protein contents (%)
-0.506 0.010 -0.038 -0.027
Glucosinolates
contents(%)
-0.235 0.022 0.113 0.076
Oleic acid (%)
-0.106 -0.014 -0.184 -0.126
Erucic acid (%)
0.082 0.010 0.140 0.165
170
GENERAL DISCUSSION
Increasing demand for vegetable oil with increasing amount of imports to Pakistan urges the
concerns for evolution of high yielding and good quality Brassicas. Through Brassicas the
burden can be decreased on national economy by meeting the domestic demand of both
vegetable and fossil fuel. The present studies were under taken to improve the genetic
potential and oil quality of Brassica campestris based on selection/breeding methods.
Hybridization was done at two levels i.e., intraspecific as well as interspecific to obtain
probable introgressions from B. napus and B. juncea. Data were recorded for mrophological,
phenological, quality and yield related traits. Biometrical analysis was performed to work out
genetic variability, heterosis, direct, indirect selection parameters and inbreeding depression
of some selected crosses. Parents and their generations at both levels, i.e., intraspecific and
interspecific executed differently for quantitative as well as qualitative traits. Results
revealed that variability presents in genotypes may be the first step for the evolution of
brassicas. Mean square values for intraspecific crosses indicate genetic variability among all
quantitative and qualitative traits studied. General combining ability effects for quantitative
traits showed that genotypes UAF12, UAF11, Candle and Toria are the most suitable parent
for the development of early maturing genotypes because they took minimum number of
days to flowering initiation. The genotypes Span and Torch can be considered as superior
parents because they showed high positive and significant GCA effects for seed yield. The
crosses UAF12×Torch, 1072×Tobin and UAF12×Candle showed considerable negative
specific combining ability effects for days to flowering. The combination 1072×Torch
reveals maximum specific combining ability for seed yield. Estimated components of
variances indicated that dominance variances were more important than additive variances
for yield contributing traits and these can be utilized for heterotic effects of their genotypes.
The aim of heterosis breeding to attain high yielding crosses. Six combinations showed
positive and significant heterosis and heterobeltosis for early maturing and high yielding.
Data regarding the quality traits indicated that for oil (%) in UAF11, 1072, Torch and Candle
had maximum GCA effects but Candle showed negative significant general combining
ability effects. Q15 for protein (%) showed the best general combining ability effects and all
were none significant statistically. All genotypes used as lines or testers displayed
considerable effects of GCA either in positive or in negative directions for glucosinolate
171
contents. For oleic acid content the highest GCA effects were shown by genotype 1072 while
the highest general combining ability was shown by Candle. Positive GCA effects for oleic
acid are desirable trait for industrial and nutritional purpose. All parental lines revealed
significant effects of general combining ability for erucic acid in both positive and negative
direction. The rapeseed oil with low erucic acid is mandatory for diet and high concentration
is not beneficial for health. The genotypes with low effects of GCA for erucic acid are
helpful to develop the genotypes with low erucic acid. Results were supported by (Nasim and
Farhatullah, 2013) and shazad et al. (2015). Maximum oil content (%) is desirable trait in
rapeseed. Four combinations showed positive SCA effects. The maximum positive effects
were found by the combination TR8×Tobin. High protein content is valuable trait. The
highest SCA effects were shown by the combination UAF11×Tobin .The combination with
negative specific combining ability in term of glucosinolate is desirable. In case of SCA
effects seven combinations showed significant but negative effects for glucosinolate.
The combination 1072×Torch had maximum positive SCA effects for oleic acid
fallowed by Toria× Candle. Six cross combinations revealed significant effects of general
combining ability for erucic acid in both positive and negative direction. Rapseed and
mustard oil having erucic acid in low quantity is mandatory for diet and high quantity is not
beneficial for health. The genotypes with low GCA effects for erucic acid are helpful to
develop the genotypes with low erucic acid. Genetic components of variance for indicated
trait showed that specific combining ability was more important than general combining
ability and dominance variance than additive variance. Specific combining ability or
dominance variance was more important for all traits. Degree of dominance was greater than
1 for oil content, glucosinolates and erucic acid.
All these traits can be utilized for heterotic effects of their genotypes. All 21 hybrids
were compared with mid parent and batter parent for estimation of relative heterosis and
heterobeltosis. Two combinations showed positive and significant relative heterosis and
heterobeltosis. Positive significant heterosis and heterobeltosis is preferred to select the
genotypes with high oil contents. The combination UAF11×Tobin andUAF11×Torch showed
significant and positive heterosis for oil contents. Negative or absence of heterosis for oil
content is common and reported by earlier workers (Brandle and McVetty, 1990., Schuler et
al., 1992; Falk et al., 1994, Teklewold and Becker, 2005). However it has been reported by
172
Zhong et al. (2009) when two low oil content cultivars were crossed, the heterosis was
positive but low, when two medium or high oil content of same level were crossed, there was
positive relative heterosis or heterobeltosis .when two parents with different oil contents i.e
low and high were crossed the heterosis was negative. Therefore it is necessary to increase
the oil contents two high oil contents cultivar must be crossed. For protein contents three
combinations are positive and significant for protein contents. Cross combination of
UAF11×Torch showed maximum heterosis and heterobeltosis for protein content. Low
heterosis was observed by (Cuthbert et al., 2011). However Engqvist and Becker (1991)
reported that there was not any kind of heterosis for protein. Nausheen et al. (2015) also
reported positive heterosis F1 in combination. Eight crosses revealed negative and significant
heterosis for glucosinolate. Priyamedha et al., (2016) who reported the negative heterosis for
glucosinolstes in Indian mustard (B. juncea). Oleic acid is one of the major enviable
components of Brassica seed meal therefore for getting improved Brassica varieties/lines
positive levels of heterosis and heterobeltosis for oleic acid is considered.Cross combination
Toria× Candle showed maximum relative heterosis and heterobeltosis for oleic acid. Ali et al.
(2015) who observed positive and significant heterosis and heterobeltosis for oleic
acid.Erucic acid content of brassica oil is an undesirable component that makes the oil
unsuitable for human consumption. Four crosses showed significantly negative relative
heterosis and heterobeltosis. Similar results were also reported by Patel and Sharma (1999);
Singh et al. (2003); Wang et al. (2009); Gami and Chauhan (2014) and Chaudhari et al.
(2015). Ali et al. (2015) also recoded the maximum negative values for heterosis and
heterobeltosis. Four cross combinations viz., Span×Tobin, Toria×Candle, 1072×Torch and
Q15×Torch were identified the good cross combinations on the basis of specific combining
ability, relative heterosis, heterobeltosis and general combining ability estimates. These
combinations may be used for commercial exploitations for seed yield in Brassica
campestris. Similar results were supported by Sexena et al., (2010) who got 28.4% yield
superiority over check variety in farmer field. On basis of erucic acid (%) three combinations
viz. Toria×Candle, UAF11×Torch and Span × Candle were selected for SCA effects relative
heterosis, heterobeltosis and GCA estimates. These three combinations can also be used as
source of low erucic acid combinations.
173
For glucosinolate (%) three combinations viz., Span × Candle, Q15×Torch and
TR8×Tobin can be used as source of low glucosinolate (%).On the basis of oleic acid four
good crosses were identified. These good crosses were i.e. UAF11×Torch, Toria× Candle,
Q15×Tobin and UAF12×Torch.These combinations were selected on the basis of SCA
estimates relative heterosis, heterobeltosis and GCA estimates. These combinations can also
be used for commercial exploitations.
Correlation coefficient in plant breeding describes the relationship between different
plant parameters and component traits on which selection can be relied on for the genetic
improvement of yield. The correlation studies indicated that genotypic correlations were
higher than phenotypic correlations at genotypic and phenotypic level. The indirect selection
parameter for seed yield and yield related components like plant height, secondary branches,
biological yield, number of siliqua per plant, and number of seed per siliqua can be
considered to develop high yield genotypes. Oil content has positive and significant
correlation with protein while protein content has significant positive correlation with
glucosinolate and negative but significant correlation with oleic acid and significant positive
correlation with erucic acid. Glucosinolate has positive and significant correlation with erucic
acid and negative with oleic acid. Oleic acid has negative correlation with erucic acid. The
similar relationship between oil and protein content was not supported by Alemeyehu and
Becker (2000), who reported negative correlation. Azam et al., (2013) observed that Protein
content had positive and significant correlation with erucic acid and none significant with
glucosinolate content. Abideen et al. (2013) also reported positive non-significant association
between glucosinolate and erucic acid content. Similar findings were supported by
Krzymanski and Downey (1969) who indicated negative correlation of oleic acid with erucic
acid.
Path analysis has been used to determine the inter-relationship between yield and yield
contributing traits. Path coefficient analysis showed that days to flowering initiation, number
of siliqua, and seed per siliqua, secondary branches, and biomass and harvest index had
considerable positive direct effect on seed yield per plant. Protein contents had direct positive
effect. Glucosinolate contents have direct negative effect. Oleic has direct positive effect and
Erucic acid has direct negative effect on oil contents.
174
If genotypic correlations and direct effects almost are equivalent and positive,
correlation indicates accurate relationship and direct selection of considered trait absolutely
would improve the yield. Heritability along with genetic advance can help in better way in
predicting the genetic gain under the selection Johanson et al. (1955). Therefore enhancement
through direct selection is probable in Brassica campestris for traits like days to 50% siliqua
formation, plant height, days to maturity, number of siliqua/plant and number of seed per
siliqua.
Variation for general combing ability effects for interspecific crosses, B. campestris
showed good general combining ability for early maturing, followed by B.napus and B.
juncea. For yield parental lines from B. campestris and B. napus were good general combiner
as compared to B. juncea. The results from cross combinations specific combining ability
effects revealed that crossing within the species for earliness and yield is better than among
the species. Interspecific combinations took more days to flowering, siliqua formation and
maturity as compared intraspecific combinations using the same genotypes. Specific
combining ability was more important than general combining ability and dominance
variance as compared to additive variance. Degree of dominance was greater than 1 for days
to flower initiation, days to 50% flowering, days to 50 % siliqua formation days to maturity,
secondary branches, biomass, harvest index, number of siliqua per plant and 100 seed
weight; all these traits can be utilized for heterotic effects of their genotypes.
The heterosis obtained from the hybridization between races or species gives an
excessive increase in size, weight and growth rate in the interspecific or inter racial hybrids.
Such type of heterosis was called luxuriance and hybrids are luxuriant (Dobzhansky, 1940).
Luxuriance is pseudo heterosis. There is no continuation due to poor seed setting in luxuriant
hybrids. However creation of novel genotype or F1 is possible through interspecific
hybridization which was unreal in nature. Only one cross combinations viz., Napus2×Toria
was identified for the seed yield as it revealed significant relative heterosis and
heterobeltosis. This cross combination may be used for further evaluation for seed yield. For
erucic acid two combinations as, Napus2×Juncea, Shora×1072 were identified. These two
combinations can be used for the source of erucic acid reduction. Glucosinolate contents (%)
is an important trait for animal feed. Four combinations UAF11×Napus1, Napus2×Toria,
Napus2×Juncea and Shora×1072 were found suitable for negative heterosis for glucosinolate.
175
For oil contents (%) three combinations Napus2×Toria, UAF11×Napus1 and Napus2×Juncea
were identified as they revealed significant positive heterosis for oil. These combinations can
be used for the exploitation of heterosis for oil contents. Correlation for quantitative traits of
inter-specific crosses shows that genotypic correlations were higher than phenotypic
correlations. Plant height, Primary branches, secondary branches Number of siliqua per plant,
number of seeds per siliqua, biological yield and harvest index can be considered for yield
improvement. Glucosinolate had positive and significant correlation with erucic acid. All
other results were statistically non-significant. Abideen et al. (2013) also reported positive
non-significant association between glucosinolate and erucic acid content.
Path analysis showed that days to flowering initiation, days to 50% flowering plant
height, biological yield, number of seeds per siliqua had direct effect on seed yield. Primary
branches depicted maximum negative direct effect and maximum indirect effect via days to
50% flowering on seed yield. Results were not supported by Sinha et al. (2001). Protein
contents and oleic acid had direct negative effect on oil contents. Glucosinolate and erucic
acid contents have direct positive effects on oil contents. Tahira et al. (2015) also discribed
the direct negative effect of oil contents on erucic acid and indirect effects via total
glucosinolate and oleic acid were also negative. Overall glucosinolate had positive direct
effect on erucic acid.
Oil contents had high heritability with moderate genetic advance in percentage of mean
that indicated additive gene effects and selection would be succeesful.Protein contents
showed high heritability along with low genetic advance that showed these traits are vastly
influenced by the environment and selection cannot be rewarding. Glucosinolate oleic acid
and erucic acid also presented high heritability and considerable genetic advance.Similar
results were displayed by Bradshaw and Wilson (1998) and Chauhan et al. (2002).
Inbreeding depression is an imperative phenomenon in the history of evolution of out
crossing mating system because inter-crossing inbred strain improves the yield (heterosis)
which is important in crop breeding. The genetic bases are under discussion since early
twentieth century. Classical genetic and modern molecular studies propose that inbreeding
depression and heterosis are mainly due to the occurance of recessive deleterious
(Charlesworth and Willis, 2009). The interspecific crosses were made and their inbreeding
depression in F2 generation of some selected crosses has been studied. There was substantial
176
amount of inbreeding depression in most cross combinations for seed yield per plan. Six
showed positive and significant inbreeding depression and two showed significant negative
inbreeding depression. Both positive and negative significant values of inbreeding depression
have been recorded. Anantharuja and Muthiah (2008) observed 22.20 to 43.47% of
inbreeding depression for seed yield per plant.
For quality traits the cross combination Napus2×1072 showed highest positive
inbreeding depression that was statistically significant.Four combinations showed negative
and non-significant inbreeding depression for oil. The combination showed positive
inbreeding depression means additive gene action is involved. For protein the combination
showed negative inbreeding depression. The positive highest level of inbreeding depression
was shown by Napus1×UAF11. All combinations showed non-significant results for in
breeding depression in case of glucosinolate contents. All combinations showed negative and
significant inbreeding depression for oleic acid. All combination showed positive and
significant inbreeding depression and one non-inter specific combination showed negative
and significant inbreeding depression for erucic acid.
177
.CHAPTER 5 SUMMARY
This study was conducted to understand the genetic variability of Brassica campestris within
the species and to obtain the probable introgression of Brassica napus and Brassica juncea.
Line×tester mating design, direct and indirect selection parameters were adapted and the
genetic information gained from this variability were used to select the high yielding, good
quality and early maturing lines.14 lines/Cultivar local and exotic (10 genotypes of B.
campestris, two genotypes of B. napus and two genotypes of B. juncea) were used on the
basis of their reported performance with respect to different traits. Both intra and inter
specific crosses were attempted and their further generations were developed for
morphological, phenological, yield and quality attributing traits. The data regarding for these
traits were analyzed. Analysis of variance showed significant differences at (P=0.05-0.01) for
most of the traits at intraspecific and interspecific levels. Variation for general combining
ability estimates of intraspecific crosses for thirteen quantitative and five qualitative traits
was studied. Four cross combinations viz., Span×Tobin, Toria×Candle, 1072×Torch and
Quinyou15×Torch were identified the good cross combinations on the basis of specific
combining ability, relative heterosis and heterobeltosis and general combining ability
estimates. The combinations may be used for commercial exploitations for seed yield in
Brassica campestris. For erucic acid (%), three combinationsviz.Toria×Candle,
UAF11×Torch and Span×Candle were selected for SCA effects relative heterosis,
heterobeltosis and GCA estimates. These three combinations can also be used as source of
low erucic acid combinations.
For glucosinolates (%) three combinations viz., Span×Candle, Quinyou15×Torch and
TR8×Tobin were identified and can be used as source of low glucosinolate (%). For oleic
acid four good crosses were identified. These good crosses were i.e. UAF11×Torch, Toria×
Candle, Quinyou15×Tobin and UAF12×Torch.These combinations were selected on the
basis of SCA estimates relative heterosis, heterobeltosis and GCA estimates. Oil (%) is an
important parameter in brassicas. The four good combinations for oil were selected from
different combinations on the basis of SCA estimates, relative heterosis, heterobeltosis and
GCA estimates. These four combinations can also be used for commercial exploitations
178
Variance due to GCA, variance SCA, additive variance, dominance variance and degree of
dominance for the traits was studied. General combining ability and dominance variance was
more important than additive variance. Specific combining ability was more important for
primary branches, secondary branches, siliquae per plant, 100 seed weight and yield than
general combining ability or additive variance. Degree of dominance was greater than 1for
flowering traits and maturity days and these traits can be utilized for the heterotic effect.
Correlations studies revealed that genotypic correlations were higher than phenotypic
correlations at genotypic and phenotypic level. Plant height had positive considerable
association with biomass, days to 50% flowering and seed yield per plant. Primary branches
had positive significant correlation with secondary branches. Biomass had positive
significant correlation with number of siliqua per plant and seed yield per plant. Harvest
index had positive association with number of seed per siliqua and seed yield per plant.
Days to 50% flowering has positive significant correlation with days to 50% siliqua
formation, number of siliqua per plant and seed yield per plant. Days to 50% siliqua
formation has positive significant correlation with 100 seed weight and strongly correlated
with seed yield per plant. Days to maturity are significantly correlated with number of siliqua
per plant. Number of seed per siliqua has positive and significant correlation with 100 seed
weight.
Oil content had positive and significant correlation with protein while protein content
had significant positive correlation with glucosinolate and negative but significant correlation
with oleic acid and significant positive correlation with erucic acid. Glucosinolate had
positive and significant correlation with erucic acid and negative with oleic acid. Oleic acid
has negative correlation with erucic acid. Path coefficient analysis showed that traits like
days to flowering, days to 50% flowering, days to maturity, Secondary branches, Number of
siliqua, Seed per siliqua, harvest index have direct positive effect on seed yield while
protein contents, glucosinolate, oleic acid have direct positive effect on oil contents while
erucic acid has direct negative effect on oil contents.Heritability and genetic advance in
percentage of mean is main criteria, prediction can be made that enhancement through direct
selection is promsing in Brassica rapa L. for traits as days to 50% siliquae formation, days
to maturity, number of siliquae/plant, number of seed per siliqua and plant height. Oil content
had remarkable heritability with moderate genetic advance that depicted additive gene action
179
and selection may be successful. Protein content showed high heritability along with
moderate genetic advance. Glucosinolate also showed high heritability and high genetic
advance.
Interspecific cross combinations were divided into two sets, in first two cross
combinations viz., Napus2×Toria, Shora× Juncea were identified for the seed yield as they
revealed significant relative heterosis and heterobeltosis. For erucic acid four combinations
as UAF11×Toria, Napus2×Juncea, Shora×1072 and Shora×1072 were identified. These four
combinations can be used for the source of erucic acid reduction. Four combinations
UAF11×Napus1, Napus2×Toria, Napus2×Juncea and Shora×1072 were found suitable for
negative heterosis for glucosinolate. For oil contents (%) four combinations Napus2×Toria,
Shora×Juncea, UAF11×Napus1 and Napus2×Juncea were identified as they revealed
significant positive heterosis for oil. They showed luxuriance heterosis for plant biomass, for
leaves and branches. For flowering they took more days than any other intraspecific crosses.
Some crosses showed self-incompatibility and male sterility that can be used for the hybrid
development.
Correlations for quantitative traits of interspecific crosses indicated that genotypic
correlations were higher than phenotypic correlations at genotypic and phenotypic level.
Plant height has positive significant correlation with primary branches, secondary branches,
number of siliqua per plant biomass, days to 50% flowering and seed yield per plant.
Secondary branches have significant correlation with seed per siliqua, days to flowering
initiation, days to 50% flowering, days to 50% siliquae formation days to maturity, and
biomass. Yield is positively correlated with biomass and harvest index. Only glucosinolate
had positive and significant correlation with erucic acid. All other results were statistically
none significant.
Days to flowering initiation, days to 50% flowering, plant height, secondary branches,
number of seeds per siliqua and biomass has direct positive effect on seed yield. Only
glucosinolate had positive and significant correlation with erucic acid. Protein contents had
direct negative effect. Glucosinolate contents have direct positive effect and oleic has direct
negative effect on oil contents. Erucic acid has positive direct effect on oil. Heritability along
with genetic advance can help in better way in predicting the genetic gain under the selection
180
Days to flowering initiation, days to 50% flowering, days to maturity and plant height,
number of primary branches, secondary branches, number of siliquae per plant and number
of seed per siliqua biomass and harvest index showed high heritability along with high
genetic advance in percentage of mean that indicates the heritability is due to additive gene
effects and selection may be effective. In case of yield both heritability and genetic advance
were high and selection will be effective way for the improvement in yield.
Oil content had high heritability with moderate genetic advance in percentage of mean
that showed additive gene effects and selection may be rewarding. Glucosinolate also
showed high heritability and high genetic advance. For oleic acid and erucic acid, high
heritability along with high genetic advance was observed.
Interspecific 2nd part direct and some indirect crosses of B. campestris were also made
with B. napus and B. juncea.Twelve crosses were adopted and ten of them were reciprocal of
part (a) because genetic system allows the successful crossing in one direction when it is not
successful in other direction due to cross-incompatibility.
No interspecific cross combination was found to be good for yield. However these
were vigorous with respect to biomass but not high yielding. For quality, five combinations
viz., Toria×Napus2, Napus1×Shora, Juncea×1072 and juncea×UAF11 were found batter for
low erucic acid heterosis. Three combinations viz., Toria×Napus2, Napus1×1072,
Napus1×UAF11 and Juncea×Napus2 showed negative heterosis for glucosinolate contents
(%). Significant positive heterosis, good SCA and GCA estimates for oleic acid were
observed.When SCA is high such crosses may be desirable combination for the improvement
of respective traits because SCA effects would be probably due to additive× additive gene
action that is fixable. The crosses selected for oleic acid (%) i.e.Toria×Napus2,
Napus1×Shora, Napus1×UAF11 and Juncea×1072 had high SCA, GCA and heterosis, these
crosses might be used for the further improvement for the respective trait. Three
combinations were also identified for oil content (%).These combinations Napus1×1072,
Napus1×Napus2 and Juncea ×Shora had high SCA, GCA and heterosis. Therefore these
crosses can be used for the exploitation of heterosis for oil contents.
Days to flower initiation had highly significant correlation with days taken to 50%
flowering, days taken to 50% siliquae formation, days to maturity and also for seeds per
siliqua. Correlation of days to maturity with days taken to flower initiation, days to 50%
181
flowering, number of secondary branches, harvest index and seeds/ siliqua was highly
significant. Plant height had significant correlation with number of primary branches and
secondary branches but was highly significant with 100 seed weight but exhibited positive
non-significant correlation with yield. Number of secondary branches showed significant
correlation with days to maturity and seeds per siliquae. Correlation of harvest index with
days to maturity significant and was highly significant with biological yield, seeds/siliqua,
thousand grain weight and yield per plant. Number of siliquae/ plant showed significant
correlation with yield/plant but was highly significant with seeds/ siliqua biological yield.
Significant correlation was estimated between seeds/ siliqua and harvest index but highly
significant correlation was found between seeds/ siliqua and days to maturity, number of
siliquae per plant, thousand seed weight and yield per plant. Yield/plant was significantly
correlated with traits like days to maturity, number of primary branches, harvest index, seeds/
siliqua and thousand seed weight. Protein content has significant positive correlation with
glucosinolate and negative but significant correlation with oleic acid and significant positive
correlation with erucic acid. Glucosinolate has positive and significant correlation with erucic
acid and negative with oleic acid. Oleic acid has negative correlation with erucic acid.
Path coefficient analysis is generally used for the evaluation of importance of traits on
yield. Seeds per siliquea, days taken to 50% flowering, number of secondary branches,
biological yield and thousand grain weights showed highest positive effect on overall yield.
Protein contents have direct negative effect. Glucosinolate contents have direct positive
effect. Oleic has direct negative effect and Erucic acid has direct negative effect on oil
contents.
Heritability and genetic advance in percentage of mean are the direct selection
parameters for the enhancement of traits like flowering initiation, days to 50% flowering,
days to 50% siliquae formation, days to maturity and plant height number of primary
branches, secondary branches, and biomass and harvest index.Oil content had high
heritability with moderate genetic advance in percentage of mean that shows additive gene
effects. For oleic acid and erucic acid high heritability along with high genetic advance were
noted. Inbreeding depression is an imperative phenomenon in the evolution of out crossing
mating system because inter-crossing inbred strain improves the yield (heterosis) which is
essential in crop breeding. The inter-specific inbreeding depression in F2 generation of some
182
selected crosses was studied. There was substantial amount of inbreeding depression in most
cross combinations for seed yield per plant. Out of 12 cross combinations 6 showed positive
and significant inbreeding depression and two showed significant negative inbreeding
depression. Oil, protein, oleic acid showed positive and negative inbreeding depression for
different cross combinations. All combinations showed positive inbreeding depression except
one for erucic acid.
183
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