Journal of Food Legumes

Volume 23 Number 2 June 2010

I SPR D1987

ISSN0970-6380

of

Journal

Food Legumes

Indian Society of Pulses Research and DevelopmentIndian Institute of Pulses Research

Kanpur, India

Journ

al of Food

Legu

mes

Volu

me 23 N

um

ber 2

Jun

e 2010

Online ISSN0976-2434

The Indian Society of Pulses Research andDevelopment (ISPRD) was founded in April 1987 with thefollowing objectives: To advance the cause of pulses research To promote research and development, teaching and

extension activities in pulses To facilitate close association among pulse workers

in India and abroad To publish “Journal of Food Legumes” which is the

official publication of the Society, published four timesa year.

Membership : Any person in India and abroad interestedin pulses research and development shall be eligible formembership of the Society by becoming ordinary, life orcorporate member by paying respective membership fee.Membership Fee Indian (Rs.) Foreign (US $)Ordinary (Annual) 350 25Life Member 3500 200Admission Fee 20 10Library/ Institution 3000 100Corporate Member 5000 -

INDIAN SOCIETY OF PULSES RESEARCH AND DEVELOPMENT(Regn. No.877)

The contribution to the Journal, except in case ofinvited articles, is open to the members of the Societyonly. Any non-member submitting a manuscript will berequired to become annual member. Members will beentitled to receive the Journal and other communicationsissued by the Society.

Renewal of subscription should be done in Januaryeach year. If the subscription is not received by February15, the membership would stand cancelled. Themembership can be revived by paying readmission fee ofRs. 10/-. Membership fee drawn in favour of Treasurer,Indian Society of Pulses Research and Development,through M.O./D.D. may be sent to the Treasurer,Indian Society of Pulses Research and Development,Indian Institute of Pulses Research, Kanpur 208 024,India. In case of outstation cheques, an extra amount ofRs. 40/- may be paid as clearance charges.

EXECUTIVE COUNCIL : 2010-2012

Zone I : Dr. (Mrs) Livinder KaurPAU, Ludhiana

Zone II : Dr. H.K. DixitIARI, New Delhi

Zone III : VacantZone IV : Dr. Vijay Prakash

ARS, Sriganganagar

Editorial Board

Councillors

Dr. P.M. Gaur, ICRISAT, HyderabadDr. R.K. Varshney, ICRISAT, HyderabadDr. V.K. Shahi, RAU, PusaDr. S.C. Gupta, ARS, DurgapuraDr. Servjeet Singh, PAU, LudhianaDr. Shantanu Kumar Dube, IARI, New DelhiDr. B.G. Shiv Kumar, IARI, New Delhi

Chief PatronDr. S. Ayyappan

PatronDr. S.K. Datta

Co-patronDr. N. Nadarajan

Zone V : Dr. K.K. NemaRAK College, Sehore

Zone VI : Dr. Ch Srinivasa RaoCRIDA, Hyderabad

Zone VII : VacantZone VIII : Dr. Anoop Singh Sachan

IIPR, Kanpur

Dr. Aditya Pratap, IIPR, KanpurDr. Narendra Kumar, IIPR, KanpurDr. Mohd. Akram, IIPR, KanpurDr. P. Duraimurugan, IIPR, KanpurDr. Jitendra Kumar, IIPR, KanpurEr. M.K. Singh, IIPR, KanpurDr. C.P. Srivastava, BHU, Varanasi

PresidentDr. N.D. Majumder

SecretaryDr. A.K. Choudhary

Joint SecretaryMr. Brahm Prakash

TreasurerDr. K.K. Singh

Vice PresidentDr. J.S. Sandhu

Journal of Food Legumes(Formerly Indian Journal of Pulses Research)

Vol. 23 (2) June 2010

CONTENTSREVIEW PAPER1. Vegetable pigeonpea – a review 91-98

K.B. Saxena, R.V. Kumar and C.L.L. Gowda

RESEARCH PAPERS2. Significance and genetic diversity of SPAD chlorophyll meter reading in chickpea germplasm in the 99-105

semi-arid environments

Junichi Kashiwagi, Hari D. Upadhyaya and L. Krishnamurthy

3. Varietal characterization of urdbean for distinctiveness, uniformity and stability 106-109

P. K. Katiyar, G.P. Dixit and B.B. Singh

4. Genetic diversity among selected genotypes of M4 generation in horsegram 110-112

N. B. Patel, S. B. S. Tikka and J. B. Patel

5. Genetic analysis for yield and yield traits in pea 113-116

K.P. Singh, H.C. Singh and M.C. Verma

6. Diallel analysis for nodulation and yield contributing traits in chickpea 117-120

Preeti Verma and R. S. Waldia

7. Production potential of finger millet and Frenchbean intercropping under rainfed conditions of Uttarakhand 121-123

Rashmi Yadav

8. Growth and yield of groundnut in relation to soil application of panchgavya and foliar spray of endogenous 124-127plant leaf extracts

R.N. Kumawat, S.S. Mahajan and R.S. Mertia

9. Integrated phosphorus management on yield and nutrient uptake of urdbean under rainfed conditions 128-131of southern Rajasthan

D.S. Rathore, H.S. Purohit and B.L. Yadav

10. Effect of date of sowing on nodulation, growth, thermal requirement and grain yield of kharif 132-134mungbean genotypes

Guriqbal Singh, H.S. Sekhon, Hari Ram, K.K. Gill and Poonam Sharma

11. Performance of pulses during pre and post-WTO period in Andhra Pradesh: district-wise analysis 135-142

I.V.Y. Rama Rao

SHORT COMMUNICATIONS12. Combining ability for yield and its components in fieldpea 143-145

Inderjit Singh, J.S. Sandhu and Johar Singh

13. Genetical analysis and heterosis for green pod yield and its components in pea 146-148

K.P. Singh, H.C. Singh, B. Singh and J.D. Singh

14. Integrated nutrient management in lentil with organic manures, chemical fertilizers and biofertilizers 149-151

Guriqbal Singh, Navneet Aggarwal and Veena Khanna

15. Effect of planting time and seed priming on growth and yield of lentil under rice-utera system 152-153

Malay K. Bhowmick

16. Effect of sowing time and fertilization on productivity and economics of urdbean genotypes 154-155

S.S. Rathore, L.N. Dashora and M.K. Kaushik

17. Effect of different soil moisture regimes on biomass partitioning and yield of chickpea genotypes 156-158under intermediate zone of J&K

Anjani Kumar Singh, S.B. Singh, A.P. Singh, Awnindra K. Singh, S.K. Mishra and A.K. Sharma

18. Co-inoculation effect of liquid and carrier inoculants of Mesorhizobium ciceri and PGPR on nodulation, 159-161nutrient uptake and yields of chickpea

Pratibha Sahai and Ramesh Chandra

19. Bio-efficacy of insect growth regulator against tobacco caterpillar in blackgram 162-163

S. Malathi

20. Population fluctuations of pod fly on some varieties of pigeonpea 164-165

Ram Keval, Dharmpal Kerketta, Paras Nath and P.S. Singh

21. List of Referees 166

22. Proceedings of General Body Meeting of the ISPRD held atCSK HPKV, Palampur (H.P.) on May 18, 2010 167

Journal of Food Legumes 23(2): 91-98, 2010

ABSTRACT

Among sub-tropical legumes, pigeonpea or red gram (CajanusCajan (L.) Millspaugh) occupies an important place in rainfedagriculture. This crop has a wide range of uses and its use asfresh or canned green peas is common in parts of India, Africa,Central America and the Caribbeans. Vegetable pigeonpea ischaracterized by large pods and seeds because of easy shelling.Some parts of India prefer green pod colour but the studyrevealed that pod colour does not play an important role indetermining the organo-leptic qualities of vegetable pigeonpea.The anti-nutritional factors like phyto-lectins are also presentin pigeonpea, but it is heat sensitive and destroyed duringcooking. Vegetable pigeonpea can be grown in backyards, fieldbunds and also as a commercial crop. The fresh seeds can alsobe frozen and canned for commercialization and export. TheDominican Republic stands first in exporting commercializedvegetable pigeonpea to United States and other countries.Vegetable pigeonpea is a good source of protein, vitamins (A,C, B complex), minerals (Ca, Fe, Zn, Cu), carbohydrates anddietary fibre. In comparison to green peas (Pisum sativum), thevegetable pigeonpea has five times more beta carotene content,three times more thiamine, riboflvin and niacin content anddouble vitamin ‘C’ content. Besides it has higher shellingpercent (72%) than that of green peas (53%). These all factorsindicate that pigeonpea is nutritionally rich vegetable and itcan be used in daily cuisine.

Key words: Vegetable pigeonpea, Antinutritional factors, Betacarotene, Shelling percent

Pulses are known to be rich in edible proteins. In India,the most commonly grown pulses, in order of their importance,are chickpea, pigeonpea, green gram, black gram, peas,common beans, and cowpea. In spite of their high nutritivevalue and being important part of daily cuisine, most farmersgive low priority to pulses in cultivation and are assigned torainfed and relatively less productive portions of their fields.However, recent escalation in prices of pulses has broughtabout some changes in the mind set of some farmers and theyare taking the cultivation of pulses more seriously than before.At present, protein availability among rural masses in thedeveloping world is less than one - third of its normalrequirements and with continuously growing population andstagnation of productivity, and expensive animal protein, thenutritional programmes associated with protein supply arefacing tough challenges to meet the demand of unprivilegedgroup of masses. Since in most households, food production

Vegetable pigeonpea – a reviewK.B. SAXENA, R.V. KUMAR and C.L.L. GOWDA

International Crops Research Institute for the Semi-Arid tropics (ICRISAT), Patancheru-502 324, AndhraPradesh, India; e-mail: [email protected](Received: August, 2010; Accepted: October, 2010)

Communicated and edited by A.K. Choudhary

priority lies in the calorie-filled cereals, the issue of proteinavailability assumes a greater significance from health pointof view.

Among legumes, pigeonpea or red gram [Cajanus cajan(L.) Millspaugh] occupies an important place in rainfedagriculture. Globally, it is cultivated on 4.67 million ha, out ofwhich, 3.30 million ha is confined to India alone. Althoughthe crop is known to be grown in 22 countries, the majorproducers are only a few. In Asia besides India, Myanmar(570,000 ha), China (150,000 ha), and Nepal (20,988 ha) areimportant pigeonpea producing countries; while in Africa,Tanzania, Kenya, Malawi, Uganda, and Mozambique produceconsiderable amounts of pigeonpea. The Caribbean islandsand some South American countries also cultivate areasonable area with pigeonpea.

Pigeonpea is cultivated in a wide range of croppingsystems and so is its usage. In the northern India, its de-hulled split cotyledons are cooked to make dal while in thesouthern parts of the country, its usage as sambar is verypopular. Also in some parts of India including Karnataka andGujarat, the use of immature shelled seeds is very common asfresh vegetable. Besides this, in the tribal areas of variousstates, the use of pigeonpea as green vegetable is verycommon. The recipes prepared with green pigeonpea seedsare nutritive and tasty and are consumed with rice as well aschapati. During the off-season in southern and eastern Africa,southern America, and the Caribbean islands, the whole dryseeds are used in making porridge while in the crop season,its immature seeds are used as fresh vegetable. Green peas inthe form of frozen or canned products are also available foruse as vegetable in the markets of USA and Europe. Itsnutritious broken seeds, husks, and pod shells are fed to cattleand the dry stems make it a popular household fuel particularlyin rural areas. Pigeonpea is credited to be the most suitablecrop for subsistence agriculture that needs minimum externalinputs. It is known to produce reasonable quantities of foodeven under unfavorable production conditions mainly due toits qualities such as drought tolerance, nitrogen fixation, anddeep root system. Its seeds contain 20-22% protein andreasonable amounts of essential amino acids.

A. Important attributes of vegetable pigeonpea

Fresh Pod colour: There is a large variation for fresh podcolour in pigeonpea and for vegetable market, green podded

92 Journal of Food Legumes 23(2), 2010

pods fetch better price in the market. Saxena et al. (1983)studied the effect of pod colour on important organo-lepticproperties of vegetable pigeonpea. They found that freshseeds harvested from purple pods had poor texture, flavour,and taste as compared to those of green seeds; but aftercooking operation such differences disappeared, suggestingthat the pod colour does not play any important role indetermining the organo-leptic qualities of vegetablepigeonpea. In a survey conducted in Gujarat state of India,where vegetable pigeonpea is consumed on a large scale, itwas found that the rural consumers preferred pods with greenbase colour with minor or dense streaks on its surface. Incontrast, the urban consumers preferred green colour pods.Yadavendra and Patel (1983) reported that the pods producedon cultivar ‘ICP 7979’ were the most preferred because of theirgood taste, attractive green colour, less stickiness, and easyshelling.Pod and seed size: For vegetable purposes, generally largepods are preferred for they are attractive and relatively shelledeasily. Although seed number/pod in the germplasm rangesbetween 2 and 9, but on an average, the optimum seed number/pod that is easily marketed is 5-7. Recently, the new vegetabletypes have been developed with up to 8 – 9 seeds/pod. Inpigeonpea, seed and pod size is invariably correlated withlarge podded types having large immature as well as dry seeds.On the contrary, in some vegetable type lines, the immatureseeds are large but their size reduces gradually withapproaching maturity. Saxena (2008) observed that in thelong podded genotypes, all the ovules did not develop properlyto their full size due to ovule abortion. The exact reason forthe loss of ovules is not fully understood but there appears tobe some sort of blockage in the supply of carbohydrates andother vital nutrients to the growing ovules resulting in theirpre-mature cessation.Important Quality Parameters: The green pigeonpea seedsare considered superior to dal in general nutrition. Theobservations recorded at ICRISAT and some other laboratoriesshow that pigeonpea dal is better than vegetable with respectto starch and protein (Table 1). On the contrary, the greenpigeonpea grains have higher crude fibre, fat, and proteindigestibility. As far as trace and mineral elements are concerned,the green peas are superior in phosphorus by 28.2%,potassium by 17.2%, zinc by 48.3%, copper by 20.9%, andiron by 14.7% (Table 2). The dal however, has 19.2% more

calcium and 10.8% more manganese. Singh et al. (1977)reported that the vegetable type pigeonpea had higher amountof poly-saccharides and low crude fibre content than dalirrespective of their seed sizes. They also reported that crudefibre content in vegetable pigeonpea was similar to that ofgarden pea (Pisum sativum).

Constituent Green seeds Dal Starch content (%) 48.4 57.6 Protein (%) 21.0 24.6 Protein digestibility (%) 66.8 60.5 Soluble sugars (%) 5.1 5.2 Crude fibre (%) 8.2 1.2 Fat (%) 2.3 1.6

Table 1. Comparison of green pigeonpea seeds and dal forimportant quality constituents

Table 2. Trace and mineral elements (mg/100g) identified ingreen seeds of a vegetable variety ‘ICP 7035’ and dalof a pigeonpea variety ‘C11’

*Adopted from Singh et al. (1984)

Element Green seeds (‘ICP 7035’)

Dal (‘C 11’)

SEm Superiority of vegetable

grains (%) Phosphorus 264* 206 ± 3.95 28.2 Patassium 1498* 1279 ± 12.74 17.1 Calcium 92.3 114.3* ± 1.98 (–) 19.2 Zinc 3.07* 2.07 ± 0.01 48.3 Copper 1.39* 1.15 ± 0.08 20.9 Iron 5.16* 4.50 ± 0.06 14.7 Manganese 0.99 1.11* ± 0.02 (–) 10.8 Magnesium 108.3 108.5 ± 0.86 --

Table 3. Major anti-nutritional factors and toxic substancesidentified in pigeonpea seed

Source: Singh (1988)

Constituent Range Mean Protease inhibitors (units/mg)

Trypsin 8.1-12.1 9.9 Chymotrypsins 2.1-3.6 3.0

Amylase inhibitors (units/g) 22.5-34.2 26.9 Oligo-saccharides (100/g)

Raffinose 0.24-1.05 0.47 Stachyose 0.35-0.86 0.49

Poly-phenols (mg/g) Total phenols 3.0-18.3 10.7 Tannins 0.0-0.2 0.03

Phyto-lectins (units/g) 400 400

Like other legumes, pigeonpea seeds also contain someanti-nutritional factors. In dry pigeonpea seeds, poly–phenolcompounds are present which inhibit the normal activity ofsome digestive enzymes. These include trypsin, chymotrypsin,amylase, poly-phenols, and tannins (Table 3). According toKamath and Belavady (1980), pigeonpea seeds haveappreciable amounts of unavailable carbohydrates whichadversely affect bio-availability of certain vital nutrients. Someof the anti-nutritional factors such as phyto-lectins are heatsensitive and are destroyed during cooking. Some of theflatulence causing oligo-saccharides such as staychyose,raffinose, and verbascose are also present in pigeonpea seeds.

Seed development in relation to chemical changes:Pigeonpea plants produce profuse flowers and pods undernormal growing environments. The number of pods on theplants is also genetically related to their pod size. It has beenobserved that in small seeded varieties, pod load on anindividual plant is much higher than those of large seeded

Saxena et al.: Vegetable pigeonpea – a review 93

varieties. Under sub-tropical growing conditions, it takes about45 - 50 days from pollination to seed maturity. During thisperiod, both pods and seeds pass through a number ofphysiological, morphological, and chemical changes. It hasbeen observed that three days after fertilization, the floralpetals wither completely and the ovary starts emerging. Ayoung pod of about one centimeter long is generally visibleafter one week. Such pods grow rapidly and reach their fullsize in about 25 days. During this period of pod growth, theyoung seeds (ovules) inside pods remain alive and intact butdo not gain noticeable size and weight. Soon after achievingthe potential pod size, a greater proportion of food reservesof the plant start diverting into the ovules and rapid increasesin seed sizes and weights are observed for the next 10 - 12days.

From nutrition and marketing view points, it is essentialthat the growing pods are harvested at a right stage to optimizethe gains with respect to their yield and quality. To determinethe optimum pod age for harvesting, two commercial vegetablepigeonpea cultivars ‘ICP 7035’ and ‘T 15-15’ were selectedand the changes in the levels of principal dietary constituentsand minerals were studied (Singh et al. 1991) at different stagesof seed development. To record observations, over 3000flowers of the same age were tagged and hand pollinated in asingle day. The crossed pods were sampled on different datesfor chemical analysis of their seeds. It was found that the twocultivars differed grossly in their dry matter accumulation ratewith ‘ICP 7035’ being faster than ‘T 15-15’, and it was attributedto their respective seed sizes. In the growing seeds, starchcontent was negatively associated with their protein and sugarcontents. The amount of crude fibre content in the growingseeds increased slowly with maturation, while soluble sugarsand proteins decreased proportionately. The starch contentrecorded rapid increases between 24 and 32 days afterflowering. ‘ICP 7035’ exhibited relatively high soluble sugarsin each sample that was studied (Singh et al. 1991). Meinerset al. (1976) also showed that minerals and trace elementssuch as calcium, iron, zinc, magnesium, and copper did notproduce significant changes during seed development inpigeonpea. It was also found that these minerals play an

important role in improving cooking quality of pigeonpeaseeds (Sharma et al. 1977).

B. Breeding vegetable pigeonpea

Popular vegetable pigeonpea varieties are characterizedby their large pods and large seeds. It has been generallyobserved that in most germplasm, these two traits are linkedtogether and such lines are invariably photo-sensitive, latematuring (>180 days at 17oN), and perennial in nature. Thesecultivars flower at the onset of short photo-periods andproduce fresh vegetable pods for about 40 - 50 days, allowinga maximum of 2-3 pickings. However, to ensure good profitsand run the processing factories for longer periods, a regularsupply of quality green pods for extended periods is essential.Besides this, the vegetable pigeonpea should have goodappearance, taste, and other organo-leptic properties. Thebreeding objectives in a vegetable pigeonpea breedingprogramme revolve around such traits.Breeding objectives: In an ideal vegetable pigeonpea breedingprogramme, in general, the prime objectives include earlypodding with round-the-year production, annual as well asperennial varieties, high multiple harvest potential, longattractive green pods with fully grown ovules, non - stickypod surface with easy shelling, good taste, large white dryseeds, and long shelf life.Available germplasm: ICRISAT has a global responsibilityfor collection, characterization, maintenance, and distributionof pigeonpea germplasm, and at present a total of 13,632accessions representing 76 countries are available for use inbreeding programmes. Since long pod size is the mostimportant characteristic of vegetable pigeonpea, theaccessions with more than 5.5 mean seeds/pod are consideredin this group. At present, there are 231 such accessions inthis group. In this material, 50% flowering ranged from 80 to229 days. The plant height ranged from 85 to 285 cm, whilepod length varied from 3.2 to 11.6 cm (Table 4). It was alsoobserved that the majority of long - podded accessionsoriginated from Africa, South America, the Caribbean islands,and tribal areas of India, where traditionally large - whiteseeded cultivars and landraces are cultivated.

Table 4. Variation for some important traits within vegetable type pigeonpea germplasmDays to Region No. of accessions

available Flowering Maturity Plant height

(cm) Seeds/

pod Pods/ plant

Pod length (cm)

Eastern Africa 106 117 - 229 166 - 270 130 - 270 5.4 – 6.7 26 – 406 5 - 12 Southern Africa 17 131– 194 163 – 260 185 - 260 5.4 – 6.1 33 – 154 5 - 11 Central Africa 4 141 –166 215 – 232 200– 230 5.4 – 5.6 74 - 130 7 - 9 Western Africa 13 142– 156 194 – 218 17 – 250 5.4 – 5.6 67 – 246 7 – 10 Central America 26 106– 151 167 – 202 85 – 240 5.4 – 7.2 19 – 160 7 – 11 South America 16 132– 158 182 – 230 100– 285 5.4 – 6.1 27 – 420 5 – 11 South Asia 39 80 – 175 133 – 235 85 – 230 5.4 – 7.2 55 – 830 3 – 9 South-east Asia 8 134– 201 190 – 264 140– 210 5.4 – 5.9 24 – 119 5 – 9 Europe 2 156 - 174 222 - 237 210 - 260 5.4 – 5.8 137 9 Total 231 80 – 229 133 – 270 85 – 285 5.4 – 7.2 19 – 830 3 - 12


Genetics of important traits: For productive plant breeding,a good understanding of the genetic systems controllingimportant qualitative and quantitative characters is essential.The presence of both additive and non-additive gene actionsfor yield and other characters have been reported in literature(Saxena and Sharma 1990). D’Cruz et al. (1970) reported thatstreaked pod colour was dominant over green, and that asingle gene was responsible for streaked pods. A dihybrid F2segregation was reported by de Menezes (1956) and D’Cruzand Deokar (1970), while Deokar et al. (1972) found that thecolour development in unripe pigeonpea pods was due tointeraction of four genetic factors. Saxena et al. (1984) for thefirst time reported intra-plant pod colour variation in a purebreeding pigeonpea germplasm ‘ICP 3773’ and postulatedthat the pod colour variation and its unpredictable expressivitywere governed by the presence, absence, or interaction ofone or more unstable genes. The genetics of seed colour inpigeonpea is complex and is reported to be influenced bysome basic and inhibitory genes, and modifiers.

Deokar et al. (1972) reported the dominance of brownseed colour over white and it was controlled by a single gene.But, Deokar and D’Cruz (1971) observed a di-hybrid F2 ratioof 9 brown: 7 white seed colour. Similar results were alsorecorded by Chaudhary and Thombre (1977), Marekar andChopde (1985). Patil et al. (1972) reported that brown seedcolour was governed by three duplicate dominant genes.Gene action and heritability of key traits: In pigeonpea,both additive and non-additive gene actions control grainyield and other quantitative characters, but critical informationon the extent of non-additive effects, particularly dominanceand epistasis components is not very decisive. Saxena et al.(1981) observed predominance of additive gene action foryield and yield components. Reddy et al. (1981) and Sidhuand Sandhu (1981) reported the importance of both additiveand non-additive gene actions, while the predominance ofnon-additive gene action was observed by Dahiya and Brar(1977). Sharma et al. (1972) reported predominance of additivegene action for seed size and the genes controlling smallerseed size were found to be dominant over the large seeds.Gupta et al. (1981) also confirmed additive gene action andreported that seed size differences were determined by only 2or 3 genes. For days to flower, Dahiya and Satija (1978) reportedadditive genetic variance with partial dominance for earliness,while Gupta et al. (1981) reported predominance of additivegene effects.

The heritability estimates provide a guideline on theefficiency of selection as they refer to the proportion of thephenotypic variance that is due to genetic factors. A highheritability estimate suggests that the concerned charactercan be selected easily in a given test environment. Inpigeonpea, a number of reports on heritability estimates forvarious quantitative traits have been published. Togetherthese estimates provide a good idea about the ease of selection

for a particular character. In pigeonpea, a large variation inthe estimates of heritability has been reported for all theimportant agronomic traits. However, most of the studiessuggest that characters such as seed yield, pods/plant, andprotein content have low heritability. On the contrary, daysto flower, plant height, and seed size have high heritabilityestimates (Saxena and Sharma 1990).

C. Breeding Methods

Globally, very little work is being undertaken to breedvegetable type pigeonpea. However, some efforts were madein the West Indies, Dominican Republic, and ICRISAT to breednew varieties that produce vegetable pods early in the seasonand produce several flushes of flowers and pods. Vegetablepigeonpea breeding programmes in most countries arepredominantly based on selection and purification of nativegermplasm.Selection from germplasm: The local landraces are generallywell adapted in the area but the natural out-crossing has madethem genetically impure. With 25-30 per cent natural out-crossing, the pure lines become heterozygous andheterogeneous. Breeders generally select individual plantsof interest within such materials with due consideration toplant type, pod colour, seed colour, and the like. One or twobranches of such plants are bagged. At maturity, these selfedbranches are harvested separately and their seed is used forevaluation in progeny rows in the subsequent season.Selection should be made among lines and in each selectedprogeny, five plants should be bagged again for raising theirsingle plant progenies. In the subsequent generation, again 4- 5 plants are selfed in each selected progeny. The self seedsare used as nucleus seed for further multiplication.Hybridization and selection: To breed varieties with definiteobjectives in mind, the selection of parents for hybridizationis the first step towards breeding. For example, early maturingvarieties should be used as female parents. This will help inidentifying the self plants present in an F1 population.Emasculation should be done carefully and fresh pollen budsbe collected for pollination and a piece of thread is tied on thepollinated flowers. In the F1 generation, the selfed plants thatwould resemble early maturing parent should be removed.Plants flowering around mid-parent value should be selfed.Selection in F2 generation should be exercised for pod colour,seed colour, and their size and maturity. These plants can behandled further using classic pedigree selection method.

D. Available Varieties

India: The most popular vegetable pigeonpea cultivars havelong pods and large seeds (weighing at least 15 g/100 seedswhen dry). These cultivars are grown as a normal field crop,but immature pods are harvested at an appropriate stage foruse as vegetable. This practice is more prevalent aroundcities where green pods can readily be marketed at attractive


prices. After harvesting green pods, the crop is left forproducing dry seeds. Such dual purpose varieties are veryprofitable for peri–urban farmers. Cultivars with white seedcoat are preferred because the cooking water remains clearwhen such seeds are cooked. Sweetness of fully grownimmature seed is also a preferred trait. Normal sugar levels ingreen pigeonpea seeds are around 5.0 %; but researchers atICRISAT have identified a line ‘ICP 7035’ with a sugar contentas high as 8.8 %. This germplasm was collected from BedaghatTownship located near Jabalpur city in Madhya Pradesh, India.Its flowers are dark red that produce purple colour pods. Theseeds of ‘ICP 7035’ are large and purple with a mottle pattern.It produces an excellent quality of vegetable. Its pods are 7 -8 cm long and, on an average, each pod contains six seeds(Fig. 1). Another cultivar ‘T 15 – 15’ is widely grown in Gujarat

Southern and Central America and the Caribbean regions:In these regions, Dominican Republic is the highest pigeonpeagrowing country (17000 ha) with an average yield of 945 kg/ha (FAO, 2008). The other pigeonpea growing countries arePanama, Venezuela, Jamaica, Trinidad & Tobago, Puerto Rico,and Grenada. Pigeonpea in these countries is essentially asmall farmers’ enterprise but at national levels, it is an importantcrop. The first vegetable type variety released in the WestIndies was ‘Prensado’. It was early in maturity and determinatein growth habit. Subsequently, three more varieties ‘Tobago’,St.Augustine’, and ‘Lasiba’ were released, which were similarto traditional types in their phenology and are still undercultivation.

In Dominican Republic, pigeonpea is mainly grown bysmall farmers and about 80% of the annual harvest is exportedin the form of canned or frozen green peas. According toMansfield (1981), in Dominican Republic four pigeonpeavarieties are recognized. These are ‘Kaki’, ‘Pinto Villalba’,‘UASD’, and ‘Year-round’. All these varieties have long podswith large and white seeds. In Puerto Rico, ‘Kaki’ is the mostpopular pigeonpea variety (Aponte 1963) and ‘2B Bushy’ isanother early maturing semi-dwarf variety. Subsequently, afew vegetable type varieties such as ‘Panameno’, ‘Amarillo’,‘Kaki’, ‘Saragateado’, and ‘Totiempo’ (Rivas and Rivas 1975)were also released. Also, there have been recent releases ofpigeonpea varieties in Puerto Rico and Dominican Republic.These include ‘Guerrero’ and ‘Cortada’, and ‘Navideño’.According to Rivas and Rivas (1975), in Venezuela a cultivar‘Panameno’ was released in 1972.

E. Cultivation of vegetable pigeonpea

Pigeonpea is known to be highly sensitive to majorenvironmental factors such as photo-period and temperaturewhich influence the development of plant phenology. Latematuring non - determinate types require 40,000 – 50,000plants/ha for optimum yields.Backyard and bund cultivation: For domestic use, manyfamilies grow pigeonpea plants in their backyards (Fig. 2).

Fig 1. Green pods and seeds of ‘ICP 7035’, a popular vegetablevariety

state for both green and dry seed harvests. In southern India,the large - seeded lines such as ‘HY - 3C’ and ‘TTB - 6’ are alsopopular as vegetable. In hilly tribal areas of India, a largenumber of large - seeded landraces are traditionally grown forvegetable purpose. Scientists at ICRISAT have also bred anearly maturing determinate variety ‘ICPL 87’ which is alsoused for dual purpose. It produces pods for relatively longertime and allows 2 - 4 pickings within a year.Africa: The first early maturing variety ‘ICPL 87091’ wasreleased in Kenya, Malawi, Uganda, and Tanzania forvegetable as well as dry seed production. In eastern andsouthern Africa, about 20% of the farmers have adopted newmedium maturing pigeonpea varieties like ‘ICEAP 00554’ and‘ICEAP 00557’ both for grain as well as green vegetablepurposes. In Tanzania, about 50% of the farmers in Babatidistrict have adopted new varieties and pigeonpea productionarea has now extended to the neighbouring districts of Karatuand Mbulu (SN Silim, personal communication). The adoptionof a late maturing, market preferred variety ‘ICEAP 00040’ innorthern and central Tanzania, Kenya, and Malawi has resultedin increased grain yields. Fig 2. Vegetable pigeonpea plants in the backyard


Such plants are maintained up to 4 - 5 years and they attain aheight of over 3 m. The plants start flowering at the onset ofshort days and pods are picked for house-hold use as andwhen required. Under normal moisture conditions, new flowersare produced for extended periods and one can see buds,flowers, young, mature, and harvestable pods on the samebranch. No specific agronomic practices are followed for thissystem of cultivation. For local market, relatively largepopulations are grown on field bunds, mainly around rainyseason paddy fields (Fig. 3). In this system, generally 3 - 4seeds are sown in a single hill. Plants produce a large numberof branches on either side of the bunds. In such plantings, ifa few plants die due to any reason, the branches of otherplants compensate for the loss of biomass. The green podsare picked manually and sold in market either as whole podsor shelled seeds.

of isolation distance of at least 200 m, roguing of all the off-types at flowering or as soon as they are spotted, sun dryingof seeds for a few days to bring down seed moisture level to9.0%, treating seed with fungicides and packing it in smallpolyethylene bags for storage.

G. Commercial processing of vegetable pigeonpea

Commercial vegetable pigeonpea is commonlyprocessed into canned or frozen peas. Among the countriesinvolved in commercialization of vegetable pigeonpea,Dominican Republic stands first from where vegetablepigeonpea is exported to the United States and other countries.The literature on various aspects of processing is scanty andthe author could access only one good publication(Mansfield, 1981), which gave details of vegetable pigeonpeaprocessing technology. The following steps are essential incanning and freezing procedures of vegetable pigeonpea.Vining and cleaning: To maintain freshness of harvestedgreen pods, they should be shelled as quickly as possible.This will not only avoid fermenting but also make availablenecessary oxygen to maintain the quality. Vining (shelling) ofsmall lots of pods is usually done manually and the shelledpeas are generally consumed in local market either as fresh orfrozen peas. The bigger lots are used for commercial purposewhere vining and cleaning are performed mechanically (Fig.4). Most commercial canners feed the green pods directlyinto the vining machine while some use a pre-treatment ofheat for better yields and clear brine. For local market, theshelled peas are washed and cleaning operation is carried outto remove unwanted peas and inert materials. Themechanically vined peas are cleaned soon after shelling. Forthis purpose, the shelled peas directly fall onto conveyors forcleaning and washing. The dry cleaning operation isperformed by passing the shelled peas through an air blastwhich helps in removing small pieces of pods or vine, dust,etc. The cleaned lot passes through a mesh screen that allows

Fig 3. A vegetable pigeonpea plant growing on rice bund inKerala

Peri-urban commercial crop: Since pigeonpea cannotwithstand water-logging, low - lying fields should be avoidedfor vegetable pigeonpea production. Application of 100 kg/ha of di-ammonium phosphate and other soil amendments forthe known soil deficiencies is advisable. Green pods areharvested for sale as fresh vegetable in nearby township andcities. Since for vegetable purpose, fully grown bright greenseeds are preferred, the pods are harvested just before theystart loosing their green colour.

F. Production and maintenance of quality seed

Maintenance of genetic purity of elite genotypes isessential to get high quality performances repeatedly. In acrop like pigeonpea where cross-pollination takes place(Saxena et al. 1990), the maintenance of seed quality is notonly difficult but also expensive. Therefore, adoption ofappropriate isolation distance is essential, and it requires extraprecautions to maintain variety purity. Some of the importantsteps that would help in quality seed production includepurchasing good quality seed from a reliable source, adoptionof normal sowing time, selection of good field, maintenance Fig 4. Mechanical shelling of vegetable pigeonpea in China


the peas to drop through it but retains large size peas andextraneous materials. Subsequently, the product passesthrough a fine mesh that retains shelled peas but removesfine dirt and splits. This dry cleaning operation is followed bywashing for removing floating dirt, skins, split peas, andworms. The washing is carried out more than once in varioustypes of flotation washers with cold running water. Afterwashing, the shelled peas are forced to pass through rotaryrod washers where splits, undersize, and mashed peas areseparated. The washed peas fall on a belt where off-colourand remaining worm - damaged, and broken peas are removedmanually for further processing (Mansfield 1981).Blanching: Heat treatment or blanching is an essentialtreatment for both freezing as well as canning. This helps instabilizing colour and flavour besides improving the textureof seeds. According to Mansfield (1981), the blanchingoperation also helps in producing clear brine by discardingmucous substances, starch particles, and inter-cellular gases.The best blanching is done by heating the peas to 185o F forfive minutes in hot water followed by cooling in cold (80oF)water (Sanchez Nieva et al. 1961). Melmick et al. (1944) showedthat steam is excellent in preserving nutrients of fresh peasbut in most cases this process is not cost effective. After theabove mentioned series of treatments, the processed peascould be used either for canning or for freezing. These twofollow-up treatments are summarized below:(a) Freezing: According to Mansfield (1981), the followingtwo methods of freezing peas are used in Dominican Republic.In the automated freezing system the peas are cooled in waterat ambient temperature soon after blanching and then takento fluidized bed freezer. In this freezer, operating between -10o

F to -20o F, the peas are quick-frozen individually while movinginside a vibrating conveyor screen which receives a rapidmoving current of cold air from the lower side (Mansfield,1981). The frozen peas are then hand picked and kept in waxtreated cartons. These cartons are stored at 0o F. In batchfreezing system, a blast freezer is used for small quantities ofshelled peas. The blanched peas are dropped in cold watertanks and then the peas are hand picked in polyethylene bagsand placed for freezing in a batch freezer between -2o F to -10o

F for 4 to 10 hours. These packets are stored at 0o F (Mansfield,1981).(b) Canning: For canning purpose, the blanched peas aretaken to volumetric filler through an elevator. Here the cansare filled with peas and 2% brine at near-boiling (195-200o F)temperature. No additives are used for canning (Mansfield,1981). For closing the cans, if near-boiling brine is maintained,then the exhaust or steam closure is not adopted. This followsa thermal processing to check the growth of any thermo-philicbacterium. After the thermal processing, the cans must becooled immediately to reduce the thermal quality losses byputting the cans in cool water ponds to bring down theirtemperature to 90-105o F.

H. Marketing of vegetable pigeonpea

In southern America, green pigeonpea pods arecollected from the farm gate by the representatives of canningplants. The processed cans are sold to wholesalers for exportto the United States, Puerto Rico, and other Latin Americancountries. In India and Africa, the marketing of vegetablepigeonpea is not well organized. Generally, local venders buythe product from whole-sale vegetable market and sell in localretail market.

I. Conclusions

The importance of vegetables in human diet can not beunder-emphasized. Vegetable pigeonpea can be good sourcesof valuable proteins, vitamins, carbohydrates, and dietary fibrefor humans. Vegetable pigeonpea complements the nutritionalprofile of cereals, and is a good source of protein, vitamins(A, C, B complex) and minerals (Ca, Fe, Zn, Cu). Vegetablepigeonpea scores manifold advantages over green peas(Pisum sativum). It has more than five times beta carotenecontent, three times more thiamine (vitamin B1), riboflavin(Vitamin B2), and niacin. The ascorbic acid content is morethan two times over peas. Similarly, it scores over peas interms of minerals such as calcium and copper (more than twotimes higher), and magnesium. Besides all, the shellingpercentage of vegetable pigeonpea is 72% compared to 53%of green peas. All these factors render vegetable pigeonpea ahighly nutritive potential crop for all ages. It can become oneof the most nutritionally rich vegetables of the daily cuisine,especially for the poor in India, Nepal and Myanmar. It isalready a vegetable of choice for Kenya, Tanzania, Malawi,Uganda, and the Caribbean.

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ABSTRACT

The SPAD chlorophyll meter reading is a measurement of theleaf chlorophyll contents, viz., the nitrogen acquisitioncapability, and so it is often used to improve the yield throughimproved nitrogen status. The genetic diversity of the SCMRwas investigated in the chickpea mini-core germplasmcollection plus five control cultivars of chickpea (Cicer arietinumL.) (n = 216) of ICRISAT Genebank under field conditionsduring two consecutive post rainy seasons of 2005-06 and 2006-07. A large genetic variability for SCMR was observed amongthe 216 chickpea accessions. The SCMR at 62 days after sowingwas positively correlated with the seed yield under droughtenvironments. The SCMR at the earlier or later growth stagesor under irrigated environment was not related to yield underdrought environment, indicating that the selections for SCMRin chickpea need to be done at about mid pod-fill stage underdrought stress conditions. A known drought avoidant chickpeagenotype, ‘ICC 4958’ that has prolific and deep rooting systemalso showed the best SCMR performances among the 216chickpea germplasm. ‘ICC 4958’ can be a potential donor parentfor both root systems and SCMR advantages. In addition, fewother outstanding genotypes such as ‘ICC 1422’, ‘ICC 10945’,‘ICC 16374’ and ‘ICC 16903’, with the higher SCMR, werealso identified in this study. This genetic variability for SCMRin the mini core provides valuable baseline knowledge inchickpea for further progress on the selection and breeding fordrought tolerance through nitrogen acquisition capability.

Key words: Breeding, Chickpea (Cicer arietinum L.), Geneticdiversity, Mini-core collection, SPAD chlorophyllmeter reading (SCMR)

Chickpea (Cicer arietinum L.) is the third important foodlegume in terms of the cultivated area (11.7 million hectares)and in total annual production (9.3 million tons in 2007) (FAOStat 2009). The major chickpea cultivation occurs in thedeveloping countries that fall in the arid and semi-arid zones.The crop is largely grown rainfed, and therefore drought stressis one of the most serious constraints for the productivity(Ryan 1997).

In the last two decades, the chickpea yield under droughtenvironments have been increased through improving somephysiological, morphological and phenological characteristicsthat have been recognized to be significant in crop adaptationto drought stress during soil drying (Ludlow and Muchow

Significance and genetic diversity of SPAD chlorophyll meter reading in chickpeagermplasm in the semi-arid environmentsJUNICHI KASHIWAGI1, HARI D. UPADHYAYA2 and L. KRISHNAMURTHY2

1Hokkaido University, Kita 9 Nishi 9, Sapporo 060-8589, Japan; 2International Crops ResearchInstitute for the Semi-Arid Tropics (ICRISAT), Patancheru 502 324, Andhra Pradesh, India;E-mail: [email protected](Received: January, 2010; Accepted: August, 2010)

1990, Subbarao et al. 1995). Enhancing early maturity couldlead the chickpea crops to escape from severe soil waterdepletion that generally occurs during the reproductive stage.‘ICCV 2’, an early maturing chickpea variety, successfullybrought in the yield stability in shorter duration drought-proneenvironments (Kumar et al. 1985). Recently, chickpeagermplasm with deep and prolific root systems have attractedthe attention as means to improve the drought tolerancethrough enhanced water uptake (Kashiwagi et al. 2006).During extensive characterization of the root traits, severalchickpea genotypes with a prolific root system were identified,and brought into molecular marker assisted breeding programs(Chandra et al. 2004).

Under drought, the plants would also face difficultiesin nutrient uptake for maintaining a proper growth in additionto soil water acquisition as nutrient absorption requires water.The chickpea acquires water soluble nitrogen contained inthe soil via the roots, and also the nitrogen synthesized viabiological nitrogen fixation in the nodules on their rootsystems. The biological nitrogen fixation is also influencedby drought as the rhizobial activities are adversely affectedby heat as well as water deficit in the soil (Zahran et al. 1999).Thus, the leaf nitrogen concentration in chickpea is expectedto be reduced under drought environments as both thenitrogen acquiring mechanisms are suppressed under suchconditions, which would result in the serious yield reduction.Therefore, for a drought tolerance breeding program, it isimportant to characterize the chickpea germplasm and toidentify sources of drought-tolerant chickpea germplasm thatare efficient in nitrogen acquisition even under droughtenvironments.

Leaf nitrogen content, in situ, could be estimatedthrough SPAD chlorophyll meter reading (SCMR). The SPADchlorophyll meter is a simple portable diagnostic tool thatmeasures the greenness or relative chlorophyll content ofleaves (Inada 1963, 1985; Richardson et al. 2002) and thesereadings are dispayed in Minolta Company (Konica-MinoltaInc. Japan ) defined SPAD (soil plant analysis development)values. There has been a strong linear relationship betweenthe SPAD values and weight-based leaf N concentration (Nw)but this relationship varies with crop growth stage and variety(Takebe and Yoneyama 1989; Turner and Jund 1994) mostlybecause of leaf thickness or specific leaf weight (Peng et al.


1993). Similarly, across crops also, the SCMR shows a linearcorrelation with extractable leaf chlorophyll (Yadava 1986).Particularly in chickpea, a significant close relationshipbetween them (r2 = 0.81) was obtained (Esechie and Al-Maskri2006). The SCMR, therefore, could be taken as a good proxyfor the chlorophyll contents in chickpea crop. The chlorophyllquantity in the plant leaves have good correlation with leafnitrogen concentration since the leaf chloroplasts contain 70%of the leaf nitrogen (Bullock and Anderson 1998). Because ofthese, the SCMR is used to improve the yield via monitoringthe nitrogen status.

Although it is desirable, it is practically not feasible tocharacterize/phenotype the whole chickpea germplasmcollection for SCMR due to their large numbers (about 20, 000at present). The genebank of the International Crops ResearchInstitute for the Semi-Arid Tropics (ICRISAT) has developeda core collection of 1,956 germplasm accessions representingthe diversity of entire collection (Upadhyaya et al. 2001) andfrom this core collection, a chickpea mini-core germplasmcollection (211 accessions) has been developed (Upadhyayaand Ortiz 2001). In our previous studies, the characterizationof the mini-core chickpea germplasm has led to theidentification of sources of deep and prolific rooting knownto assist enhanced drought tolerance (Kashiwagi et al. 2005)as well as sources of salinity tolerance (Vadez et al. 2007). Itwould also be valuable to characterize this mini-core set forother relevant drought related traits so that a comprehensiveand integrated drought tolerance data base could bedeveloped for supporting a drought tolerance breedingprogram in chickpea.

Thus, the main objective of this study was to i)characterize the chickpea germplasm for SCMR and to identifythe superior chickpea germplasm in terms of the nitrogenacquisition capability, and ii) investigate the significance ofSCMR for further plant breeding aimed towards improvingthe drought tolerance in chickpea.

MATERIALS AND METHODS

Field trials: The measurements of the SPAD chlorophyllmeter readings in chickpea mini-core collection were carriedout in Vertisol fields (fine montmorillonitic isohyperthermictypic pallustert) at ICRISAT Center, Patancheru (17o 53’ N;78o27’E; altitude 545 m) in two crop seasons, 2005-06 and2006-2007. The water holding capacity of these fields in lowerlimit: upper limit was 0.26: 0.40 cm3 cm-3 for the 0-15 cm soillayer, and 0.30: 0.47 cm3 cm-3 for the 105-120 cm soil layer. Theavailable soil water up to 120 cm depth was 165 mm, and thebulk density was; 1.35 g cm-3 for the 0-15 cm soil layer and 1.42g cm-3 for the 105-120 cm soil layer (El-Swaify et al. 1985).

A total of 216 chickpea genotypes comprising all of thechickpea mini-core germplasm collection of C. arietinum (211accessions) plus 5 control cultivars (‘Annigeri’, ‘ICC 4958’,‘Chafa’, ‘ICCV 2’, and ‘ICC 898’) were used. ‘Annigeri’ is an

early-maturing desi cultivar grown in large areas of PeninsularIndia (Ali and Kumar 2003). ‘ICC 4058’ is drought avoidantdesi germplasm lines with highly desirable root traits (Saxenaet al. 1993, Kashiwagi et al. 2005). ‘ICCV 2’ (‘ICC 12968’) is anICRISAT-bred early-maturing kabuli cultivar released in India(Kumar et al. 1985). ‘Chafa’ is the first variety of chickpea(desi type) released through selection in Wai at Niphad, in1948 Maharashtra, and in 1960 in Gujarat, India (Dua et al.2001). ‘ICC 898’ is a desi landrace from Rajasthan, India. Thecrop was sown on November 15 and November 2 in 2005 and2006, respectively. The experimental design was an alphalattice design (6 × 36 blocks) with three replications. The fieldmanagements were the same in both the seasons. Beforesowing, the field was solarized with polythene mulch in boththe seasons to prevent the incidence of Fusarium wilt, andthen18 kg N/ha and 20 kg P/ha was applied as di-ammoniumphosphate. A sprinkler irrigation (20 mm) was appliedimmediately after sowing to ensure uniform emergence. Duringboth the seasons, the fields were inoculated with Rhizobiumstrain ‘IC 59’ using liquid inoculation method. The plots werekept weed free by hand weeding and intensive protectionmeasures were taken against pod borer (Helicoverpaarmigera).

Two irrigation treatments, rainfed and optimally irrigated,were included as main plots. The rainfed treatment receivedno irrigation after the 20-mm post-sowing irrigation. Theirrigated treatments, received three furrow irrigations besidesthe post-sowing one at 27 days after sowing (DAS), 50 DASand 66 DAS in 2005-06 season, and 25 DAS, 48 DAS and 75DAS in 2006-07 season.

An earlier preliminary survey showed a significantvariation on the SCMR at different leaf positions. The SCMRof the top and the second top leaf was significantly lowerthan that of the other basal leaf positions, viz., a stable SCMRwas obtained below the third leaf position. Therefore, thethird leaf from the top was used for SPAD evaluation in thisstudy. In 2005-06, the SCMR was recorded at 62 and 90 DASand at 40 and 62 DAS in 2006-07.

At final harvest, the shoot biomass, seed yield and otheryield components were evaluated from an area of 1.5 × 2.5 m inboth the seasons after removing the plot border on either endof the plot. The shoots were dried in hot air dryers at 45°C forthree days, and the dry weights were recorded. Then, theshoots were threshed, and the extracted seeds were weighed.Statistical analysis: The data from each trial were analyzedusing a linear additive mixed effects model as described byUpadhyaya (2005). By using this model, the statisticalprocedure of residual maximum likelihood (ReML) wasemployed to obtain the unbiased estimates of the variancecomponents 2b,

2g and 2e, and the best linear unbiasedpredictors (BLUPs) of the performance of the chickpeaaccessions. Heritability was estimated as h2 = 2g/ (2g+2e).As the block effects within each replication are separately

Kashiwagi et al.: Significance and genetic diversity of SCMR in the chickpea germplasm 101

worked out with ReML, the heritability values calculated aremuch more precise than the broad sense heritability and yetnot that precise as that of the narrow sense heritability. In thephenotypic variability, which contain genetic as well asenvironmental variability, observed in the mini-core collectionplus several entries, the significance of genetic variability wasassessed from the standard error of the estimate of geneticvariance 2g, assuming the ratio 2g /S.E. (2g) to follow normaldistribution asymptotically. The above model was extendedfor over-season analysis if traits recorded in both seasons,assuming season effect as fixed, with genotype by seasoninteraction effect being a random effect assumed to have amean of zero and constant variance 2gE. The significance ofG × S was assessed in a manner similar to that of 2g. Thesignificance of the fixed effect of the season was assessedusing the Wald statistic that asymptotically follows a 2

distribution and is akin to the F-test in the traditional ANOVA.

RESULTS AND DISCUSSION

Genetic diversity of SCMR in chickpea mini-core germplasm:The chickpea cropping season was dry during both 2005-06and 2006-07 (Fig 1). Total precipitation during the croppingseason was only 3.1 mm and 17.2 mm, in 2005-06 and 2006-07respectively, and the pattern and amount of evaporation wassimilar between the years. The dynamics of temperature wasalso almost the same between the years, but the minimumtemperature across 2006-07 season was higher than that in2005-06. In addition, the air was drier in 2006-07 than in 2005-06. It can be concluded that 2006-07 was more droughty yearthan 2005-06.

Irrespective of irrigation treatments, there was asignificant difference on SCMR among the germplasmaccessions at any measurement stages in both the years (Table1). ‘ICC 16374’ was a noteworthy genotype as it showed thehighest SCMR under rainfed condition at 62 DAS in 2005-06,and also under irrigated condition at 62 DAS in 2006-07. Underthe rainfed (drought) conditions in 2006-07, the genotype ‘ICC4958’ showed the highest SCMR at 62 DAS and ‘ICC 7571’ at40 DAS. Genotypes ‘ICC 12654’ (62 DAS in 2005-06), ‘ICC4567’ (40 DAS in 2006-07), ‘ICC 11627’ (62 DAS in 2006-07)

showed the lowest SCMR under drought environments. Theheritability values estimated under irrigated conditions rangedfrom 0.38 (at 90 DAS in 2005-06) to 0.56 (at 62 DAS in 2005-06),and were higher than that in drought stress conditionsshowing between 0.13 (at 90 DAS in 2006-07) and 0.24 (at 62DAS in 2005-06) (Table 1). In one of our previous studies,shoot biomass at 35 DAS and root biomass at the same timepossessed heritability values of more than 60% and 50%,respectively, which was seen to decline to 14% at 50 DAS(Kashiwagi et al. 2005). Irrespective of the irrigation treatments,the heritability of SCMR in 2006-07 did not show big reductionat 62 DAS compared to that of 40 DAS although theheritability under rainfed conditions were very low as 17% at40 DAS and 13% at 62 DAS, respectively. Such poor heritabilityvalues indicate that larger populations would be required for

Table 1. Trial means, range of best linear unbiased predicted means (BLUPs) and analysis of variance of SCMR of the entries inthe field trials in 2005-06 and 2006-07.

DAS = days after sowing *, ** Significant at P = 0.05 and 0.01, respectively

Range of predicted means Heritability SCMR Mean Minimum Maximum Component S.E. Significance h2 S.E. 2005-06 Irrigated at 62DAS 47.4 40.1 53.1 5.07 0.63 ** 0.56 0.070 Rainfed at 62DAS 57.6 52.0 61.4 6.08 1.32 ** 0.24 0.052 Irrigated at 90DAS 53.4 49.1 58.6 5.21 0.82 ** 0.38 0.060 2006-07 Irrigated at 40DAS 57.5 52.8 62.0 4.97 0.74 ** 0.42 0.062 Rainfed at 40DAS 58.6 56.2 60.8 1.92 0.55 ** 0.17 0.049 Irrigated at 62DAS 49.2 43.6 54.4 5.01 0.77 ** 0.40 0.061 Rainfed at 62DAS 64.0 61.6 66.4 2.67 0.97 * 0.13 0.047

Fig 1. Weather at experimental site (ICRISAT, Patancheru)during the crop growing season of the years 2005-06 and2006-07.


selections to improve the SCMR of chickpea thereby enhancingthe drought tolerance.

The SCMR values in the drought environments weregreater compared to the irrigated conditions (Table 1), whichwas similar to the SCMR response made in groundnut (Nigamand Aruna 2008). This phenomenon is an expected droughtresponse in crop plants. Leaf area expansion gets moreaffected in response to drought with adversely affecting thespecific leaf area (SLA), thereby reducing the leaf size so thatthe plants could minimize the water loss via the leaf surface.As a consequence of increased leaf thickness, the leavescould have greater concentration of the chlorophyll densityin the leaves to maintain relatively better photosynthesis.Because of the denser chlorophyll content and thicker leaves,the SCMR is expected to be increased as repeatedly observedin groundnut (Nageswara Rao et al. 2001, Bindu Madhava etal. 2003, Upadhyaya 2005). In groundnut, a clear significantnegative correlation between SLA and SCMR, and betweenthe SLA and transpiration efficiency (TE) had been observed(Wright et al. 1994, Bindu Madhava et al. 2003) suggestingthat SCMR could be used as an easily measurable surrogatefor TE for improving the drought tolerance (Nigam and Aruna2008). This approach of screening for TE via SCMR can beapplicable also to chickpea to improve the drought tolerance.However, further studies with chickpea are needed to confirmthe extent of clarity in such relationships as observed ingroundnut.Significance of SCMR in chickpea to the yield under droughtconditions: At 62 DAS, under drought environments, therewas a significant positive correlation between the SCMR andthe seed yield in both the cropping seasons, whereas underirrigated conditions, only in one season, 2006-07, suchrelationship was observed between the SCMR and yield butnot in 2005-06 (Table 2). In many crops, such as groundnut(Nigam and Aruna 2008), sorghum (Xu et al. 2008), wheat(Silva et al. 2007), and maize (Zaidi et al. 2008), this strongcorrelation was observed between SCMR and seed yield underdrought environments. Interestingly, the SCMR at the 62 DASunder drought environments also showed significant positiverelationship with the shoot biomass and harvest index inchickpea (Table 2). Thus, the SCMR could be considered asone of the traits that should be incorporated into breedingprograms aimed at improving the drought tolerance inchickpea. On the other hand, at earlier growth stage, 40 DAS,the SCMR did not show any such significant relationshipwith the shoot biomass, harvest index, and seed yield, but asignificant relationship between the SCMR and yield wasobserved at 90 DAS. It is that the SCMR of chickpeaaccessions is an adaptive trait and some of the genotypes arecapable of adjusting their leaf thickness/leaf nitrogen contentunder drought stress as seen in the current case at 62 DAS,and that could reflect in a maximized vegetative as well asreproductive growth particularly under drought stress. Similar

behavior of SCMR had been reported in groundnut mappingpopulation derived out of a high (‘ICGV 86031’) and a low TE(‘TAG 24’) parents (Krishnamurthy et al. 2007).

The SCMR at 62 DAS under drought conditions aloneexhibited its contribution to the seed yield (Table 2). Asignificant linear relationship of the SCMR at 62 DAS in rainfedconditions was observed between 2005-06 and 2006-07,although the G × E interaction was not significant (F prediction= 0.732 ns). The regression coefficient, however, was low (r2 =0.202, P<0.01) (Fig 2), as an indicator of the heritabilitypresented in Table 1. Thus, the promising genotypes whichshowed constantly higher SCMR in both years were identifiedamong 216 accessions on a biplot chart (Fig 2). The top 20accessions with the best SCMR in each year are presented inTable 3 (the best 10% of the total 216 accessions). Fivegenotypes were the common ones that appeared on the listsof both the years. The genotype ‘ICC 4958’ that originated inIndia happened to be the most outstanding, showing thehighest SCMR of 66.4 in 2006-07 and 60.4 with the fourth rankin 2005-06. In our previous study, the same chickpea mini-

Table 2. Correlation coefficient between SCMR and the yieldand yield components

DAS = days after sowing*, ** Significant at P = 0.05 and 0.01, respectively

SCMR Shoot biomass

Harvest index

Yield

Rainfed Rainfed at 40DAS-2006 0.053 0.091 0.087 Rainfed at 62DAS-2005 0.342** 0.230** 0.341** Rainfed at 62DAS-2006 0.161* 0.301** 0.329** Irrigated Irrigated at 40DAS-2006 0.034 -0.109 -0.098 Irrigated at 62DAS-2005 0.000 0.056 0.042 Irrigated at 62DAS-2006 -0.069 0.209** 0.138* Irrigated at 90DAS-2005 0.171* 0.237** 0.389**

Fig 2. Relationship in the SCMR at 62 DAS under rainfedconditions between the year 2005-06 and 2006-07. Thevertical and horizontal lines indicate the mean of SCMRin 2005-06 and 2006-07, respectively.

y = 0.236x + 50.434r = 0.2022

61.0

62.0

63.0

64.0

65.0

66.0

67.0

50.0 52.0 54.0 56.0 58.0 60.0 62.0

SCMR at 62 DAS in 2005-06

SCM

R a

t 62

DAS

in 2

006-

07 ICC16374

ICC16903

ICC10954

ICC1422 ICC49

58


core collection plus 5 popular varieties were characterized forthe root traits (Kashiwagi et al. 2005). Interestingly, ‘ICC 4958’,a genotype identified to possess one of the most prolific anddeep root systems, showed the best SCMR performanceamong the 216 chickpea germplasm in the present study. Thisgenotype happens to be one of the most promising breedingmaterial for improving the drought tolerance of chickpea interms of not only the soil water acquisition but also nitrogenacquisition. The accessions ‘ICC 16374’ (origin unknown),‘ICC 1422’ (India), ‘ICC 16903’ (India) and ‘ICC 10945’ (India)were also noteworthy as they exhibited high and repeatableSCMR values.

Investigations on the existence of any associationbetween our previous results on various root traits and theSCMR did not exhibit any relationship (root length densityand SCMR: r = 0.102 ns, and rooting depth and SCMR: r =0.094 ns). In maize, however, the genotypes with extensiveand deep root systems had been shown to have the advantageof acquiring greater amount of nitrogen under droughtconditions (Banziger et al. 1999, Kamara et al. 2001). It wouldbe because the extensive roots in the surface soil layer allowedthe crops to use the soil inorganic nitrogen effectively, whilethe deeper roots were able to extract nitrate leached to deepersoil layers. However, in our current study on chickpea, itshowed that the soil nitrogen acquisition of chickpea isindependent of the root systems. This could more likely bedue to the nitrogen compensation provided by the biologicalnitrogen fixation in chickpea in addition to the root systemacquisition advantage. Interactions between the rhizobialactivities and the chickpea genotype-rhizobium affinity under

drought condition would influence the nitrogen acquisition.Our results suggest that the use of two different geneticsources, i.e. one for the root system advantage (viz., wateruptake) and the other for the SCMR advantage (nitrogenacquisition ability) could be a more beneficial strategy forgenetic improvement of drought tolerance in chickpea.Alternatively, a single genotype ‘ICC 4958’ also can be thesource for the twin alleles such as the best root system andthe best SCMR. The accessions/genotypes listed on Table 3would be valuable sources of nitrogen acquisition capabilityfor further breeding programs to improve the drought tolerancein chickpea.

A large genetic variability for SPAD chlorophyll meterreading (SCMR), as a proxy to the nitrogen acquisitioncapability, was observed among the 211 mini-core chickpeagermplasm accessions plus 5 cultivars from the ICRISATgenebank. The SCMR seemed to be an adaptive trait. Asignificant relationship between the SCMR and seed yieldunder drought environment was observed only at 62 DAS, astage when the crop had already experienced considerabledrought stress, while this relationship could not be noticed inearly growth stages and soil moisture environments.Therefore, selections for SCMR need to be made at a stagewhen the crop has been adequately subjected to droughtstress and at later stages of crop growth such as mid pod-fillstage. A known drought-avoidant genotype with the mostprolific and deep root system ‘ICC 4958’ also showed the bestSCMR performances among the 216 chickpea germplasmaccessions. This genotype will remain to be a unique promisingbreeding material for improving not only the soil water but

Table 3. Twenty top ranking chickpea germplasm on SCMR among 216 accessions in each year 2005-06 2006-07 Ranking Accession Origin SCMR Accession SCMR 1 ‘ICC 4958’ India 66.4 ‘ICC 16374’ 61.4 2 ‘ICC 1882’ India 66.3 ‘ICC 4872’ 60.9 3 ‘ICC 1422’ India 66.2 ‘ICC 4495’ 60.8 4 ‘ICC 5383’ India 66.1 ‘ICC4958’ 60.4 5 ‘ICC 283’ India 66.0 ‘ICC 14402’ 60.4 6 ‘ICC 15868’ India 65.8 ‘ICC 2580’ 60.3 7 ‘ICC 13124’ India 65.7 ‘ICC 13461’ 60.3 8 ‘ICC 7441’ India 65.7 ‘ICC 16903’ 60.3 9 ‘ICC 16374’ Unknown 65.7 ‘ICC 12155’ 60.3 10 ‘ICC 15618’ India 65.6 ‘ICC 15435’ 60.2 11 ‘ICC 8318’ India 65.5 ‘ICC 7308’ 60.2 12 ‘ICCV2’ India 65.5 ‘ICC 7272’ 60.1 13 ‘ICC 16903’ India 65.4 ‘ICC 4463’ 60.1 14 ‘ICC 13863’ Ethiopia 65.4 ‘ICC 15802’ 60.1 15 ‘ICC 10945’ India 65.3 ‘ICC 10945’ 60.0 16 ‘ICC 10399’ India 65.2 ‘ICC 1422’ 60.0 17 ‘ICC 7571’ Israel 65.2 ‘ICC 1431’ 59.9 18 ‘ICC 14778’ India 65.2 ‘ICC 2884’ 59.8 19 ‘ICC 8855’ Afghanistan 65.2 ‘ICC 6263’ 59.8 20 ‘ICC 14669’ India 65.1 ‘ICC 2990’ 59.8 Mean (n=216) 57.6 64.0 S.E. 1.32 0.97

DAS = days after sowing*, ** Significant at P = 0.05 and 0.01, respectively


also soil nitrogen acquisition. In addition, some otheroutstanding genotypes such as ‘ICC 1422’, ‘ICC 10945’, ‘ICC16374’ and ‘ICC 16903’ with the best SCMR were also identified.This can be used as valuable baseline information in futurebreeding programs to improve the drought tolerance and QTLmapping of nitrogen acquisition capability in chickpea todevelop high yielding cultivars for drought environments.

ACKNOWLEDGMENT

This research was partly supported by the unrestrictedfunds from the Japanese Government earmarked for droughttolerance research and breeding in ICRISAT.

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ABSTRACT

Morphological characterization of urdbean varieties is essentialfor their protection under Plant Variety Protection (PVP)legislation, because varietal testing for Distinctness, Uniformityand Stability (DUS) are the basis for granting protection ofnew variety under PPV&FR Act, 2001. Keeping this in view, atotal of 46 released varieties of urdbean were grouped for variousagro-morphological descriptors. All the varieties showed similarexpression for each character over the years depicting thestability of varieties. None of the attribute showed intra-varietalvariation. On the basis of 21 descriptors, varieties were groupedinto different categories for each character and may be used asreference varieties.

Key words : Characterization, Cultivars, Urdbean, Vigna radiata

Urdbean [Vigna mungo (L.) Hepper] is the third mostimportant pulse crops of India and is grown primarily as inter-crop with jowar, bajra, pigeonpea, etc., during kharif and assole crop during of rabi and spring seasons. On account ofits short duration, photo-insensitivity and dense crop canopy,it assumes special significance in crop intensification anddiversification, conservation of natural resources andsustainability of production systems. Improvement in urdbeanwas initiated during 1950s, when breeders mostly appliedpureline selections from land races and after multilocationaltesting, superior genotypes were recommended as improvedvarieties. With the inception of AICRP in sixties, collectiveefforts were diverted by the breeders to develop high yieldingvarieties through hybridization and mutation breeding whichled to increase in area and production. Further, varietal testingfor Distinctness, Uniformity and Stability (DUS) is the basisfor grant of protection of new plant varieties under theprotection of Plant Varieties and Farmer’s right Act, 2001 (PPV& FR, 2001) as the act has provision to compare the candidatevariety with the varieties of common knowledge on a set ofrelevant characteristics prescribed in the Draft National TestGuidelines for DUS testing of urdbean and commonly acceptedfor this purpose at the time of filling of application. Therefore,the present study was undertaken with the objective tocharacterize 46 released varieties of urdbean on the basis ofqualitative morphological characters and to establishdistinctiveness of the candidate variety from all other varietiesincluding extant varieties developed in India.


A total of forty six urdbean varieties viz., ‘Azad Urd 1’,‘Azad Urd 2’, ‘AKU 4’, ‘CO 5’, ‘GU 1’, ‘JU 2’, ‘KU 96-3’, ‘LBG

Varietal characterization of urdbean for distinctiveness, uniformity and stabilityP. K. KATIYAR, G.P. DIXIT and B.B. SINGH

Indian Institute of Pulses Research, Kanpur – 208 024, Uttar Pradesh, India; Email: [email protected](Received: July, 2009; Accepted: October, 2010)

20’, ‘LBG 17’, ‘LBG 611’, ‘LBG 623’, ‘LBG 645’, ‘LBG 648’,‘LBG 685’, ‘LBG 402’, ‘Manikya’, ‘Mash 1’, ‘Mash 2’, ‘Mash414’, ‘Naveen’, ‘NDU 1’, ‘PDU 1’, ‘RBU 38’, ‘Sekhar U 1’,‘Sekhar U 2’, ‘Sekhar U 3’, ‘Sarla’, ‘TU 94-2’, ‘TAU 1’, ‘TAU2’, ‘T 9’, ‘TMV 1’, ‘TPU 4’, ‘Uttara’, ‘UG 218’, ‘Vamban 1’,‘Vamban 2’, ‘WBU 108’, ‘G 338’, ‘Mash 1008’, ‘Pragya’, ‘PantU 19’, ‘Pant U 30’, ‘Pant U 35’, ‘Pant U 31’, and ‘Pant U 40’released and notified in India were evaluated during kharifseason, at Indian Institute of Pulses Research, Kanpur in aCompletely Randomized Block Design with three replicationsover three years (2006 to 2008). Each plot consisted of fourrows of 5 m length, spaced 45 cm apart with interplant distanceof 15 cm. Varieties were evaluated for 21 characters viz.,anthocyanin colour, growth habit, plant habit, stem colour,stem pubescence, plant height, leaf shape (terminal), leafcolour, leaf pubescence, vein colour, petiole colour, pedunclelength, days to 50% flowering, pre-mature pod colour, maturepod colour, pod pubescence, mature pod length, seed colour,seed coat lusture, seed shape and seed size. These descriptorswere recorded as per IBPGR (IBPGR, 1992).

The observations were recorded on 10 plants in eachreplication at specified stages of crop growth period whenthe characters under study had full expression. Anthocyanincolour was observed at cotyledons unfolded stage whereastime of flowering was observed on 50% plants with atleastone open flower. Nine characters viz., time of flowering, growthhabit, plant habit, stem colour, stem pubescence, leaf shape(terminal), foliage colour, leaf vein colour and leaf pubescencewere observed at 50% flowering. Similarly, petiole colour, colourof pre-mature pod and pod pubescence were observed at fullydeveloped green pods while plant height, peduncle length,pod colour and pod length were observed at maturity. Further,four attributes, viz., seed colour, seed lusture, seed shape andseed size were recorded of mature seeds.


Among the 46 urdbean varieties studied, considerablevariation was observed for all the important attributes understudy except for anthocyanin colour, stem pubescence, leafpubescence, petiole colour, peduncle length, and seed size.The characterization of blackgram varieties under study ispresented in Table 1 and frequency distribution of eachdescriptor of released varieties alongwith example varieties isdepicted in Table 2.

Three types of growth habit (erect, semi-spreading andspreading) are seen in the Indian varieties. The erect type

Katiyar et al.: Varietal characterization of urdbean for distinctiveness, uniformity and stability 107

Table 1. Characterization of urdbean varieties

Gen

otyp

e A

ntoc

yani

n co

lour

Plan

t Gro

wth

hab

it

Plan

t hab

it

Stem

col

our

Stem

Pub

esce

nce

Plan

t hei

ght

Lea

flet (

term

inal

) sha

pe

Lea

f col

our

Petio

le c

olou

r

Pedu

ncle

leng

th

Lea

f vei

n co

lour

Lea

f pub

esce

nce

Tim

e of

flow

erin

g

Prem

atur

e po

d co

lour

Mat

ure

pod

colo

ur

Pube

scen

ce o

n po

d

Pod

leng

th

Seed

col

our

Seed

coa

t lus

ture

Seed

shap

e

Seed

size

Azad U 1 9 3 2 2 9 3 3 1 2 5 1 9 3 3 1 9 3 4 2 2 5 Azad U 2 9 5 2 4 9 3 3 1 2 5 2 9 3 7 1 9 3 4 2 2 5 AKU 4 9 3 2 2 9 5 3 1 2 5 1 9 3 7 3 1 3 4 2 2 5 CO 5 9 3 2 2 9 5 2 1 2 5 2 9 7 7 3 9 3 4 2 2 5 Gujarat U 1 9 5 2 2 9 3 3 1 2 5 1 9 5 3 1 9 3 4 2 2 5 JU 2 9 5 2 2 9 3 3 1 2 5 1 9 5 3 2 9 3 2 2 2 5 KU 96-3 9 3 2 2 9 3 3 1 2 5 2 9 5 5 1 9 3 4 2 3 5 LBG 17 9 5 2 2 9 3 2 1 2 5 1 9 7 7 3 9 3 2 1 2 5 LBG 611 9 3 2 2 9 3 2 1 2 5 2 9 7 7 3 9 3 2 2 3 5 LBG 623 9 3 2 2 9 5 2 1 2 5 1 9 5 5 2 9 3 4 1 3 5 LBG 645 9 3 2 2 9 5 2 1 2 5 2 9 7 7 2 9 3 4 1 2 5 LBG 648 9 3 2 2 9 3 2 1 2 5 2 9 7 7 2 9 3 2 1 3 5 LBG 685 9 3 2 2 9 3 2 1 2 5 2 9 7 7 2 9 3 2 1 2 5 LBG 402 9 3 2 2 9 5 2 1 2 5 2 9 7 7 2 9 3 4 2 2 5 Manikaya 9 3 2 2 9 3 3 2 2 5 1 9 7 3 1 9 3 4 2 2 5 Mash 2 9 3 2 2 9 5 2 1 2 5 1 9 7 5 1 9 3 4 2 3 5 Naveen 9 7 2 2 9 5 2 1 2 5 1 9 7 5 1 9 3 2 2 3 5 NDU 1 9 5 2 2 9 3 3 2 2 5 1 9 5 5 1 9 3 4 2 2 5 PDU 1 9 3 2 4 9 5 3 1 2 5 2 9 5 3 1 9 3 4 2 2 5 Pant U 19 9 3 1 2 9 3 3 1 2 5 1 9 3 5 1 9 3 2 2 2 5 Pant U 30 9 3 1 4 9 7 3 1 2 5 1 9 5 3 2 9 3 2 2 2 5 Pant U 35 9 5 2 2 9 3 3 1 2 5 1 9 5 3 1 9 3 2 2 2 5 RBU 38 9 3 2 2 9 7 3 1 2 5 1 9 5 3 1 9 3 2 2 3 5 Sekhar U 1 9 3 2 2 9 5 3 1 2 5 1 9 5 3 1 9 3 1 2 2 5 Sekhar U 2 9 3 2 2 9 5 3 1 2 5 1 9 5 3 2 9 5 1 2 2 5 Sekhar U 3 9 3 2 2 9 7 2 1 2 5 1 9 5 5 2 9 5 2 2 2 5 Sarla 9 5 2 2 9 3 3 1 2 5 1 9 5 3 1 9 5 2 2 2 5 TU 94-2 9 7 2 2 9 7 3 1 2 5 1 9 5 3 2 9 3 4 2 2 5 TAU 1 9 3 2 2 9 5 3 1 2 5 1 9 7 5 3 9 3 4 2 2 5 TAU 2 9 3 2 2 9 5 3 1 2 5 2 9 7 3 3 1 3 4 2 2 5 T 9 9 3 1 2 9 3 3 1 2 5 1 9 3 5 3 1 3 2 2 2 5 TMV 1 9 3 2 2 9 5 3 1 2 5 1 9 5 3 1 9 3 4 2 3 5 TPU 4 9 5 2 2 9 5 3 1 2 5 1 9 5 3 1 9 3 4 2 3 5 Uttara 9 3 1 4 9 5 2 2 2 5 2 9 5 7 3 9 3 4 2 2 5 UG 218 9 3 1 2 9 3 3 2 2 5 1 9 3 3 1 9 3 4 2 2 5 Vambn 2 9 7 2 2 9 3 3 1 2 5 1 9 7 3 3 9 3 4 2 3 5 Vamban 1 9 7 2 2 9 7 4 1 2 5 1 9 5 3 1 9 3 4 2 2 5 WBU 108 9 5 2 2 9 3 3 1 2 5 1 9 5 3 1 9 3 2 2 2 5 G 338 9 3 1 2 9 3 3 1 2 5 1 9 3 5 3 9 3 4 2 2 5 LBG 20 9 3 2 2 9 5 2 1 2 5 1 9 7 5 3 1 3 4 1 2 5 Mash 1 9 5 2 2 9 7 2 1 2 5 1 9 7 5 1 9 3 4 2 3 5 Mash 414 9 5 2 2 9 5 2 1 2 5 1 9 7 5 1 9 3 4 2 3 5 UG 1008 9 3 2 2 9 5 3 1 2 5 1 9 7 3 3 9 3 4 2 2 5 Pragaya 9 3 2 1 9 7 2 2 2 5 2 9 7 7 1 9 3 4 2 2 5 Pant U 40 9 7 2 2 9 5 3 1 2 5 1 9 5 3 3 9 3 4 2 2 5 Pant U 31 9 3 1 2 9 3 3 1 2 5 1 9 3 5 3 9 3 4 2 2 5

Stat

e of

cha

ract

eris

tics a

ccor

ding

to

nat

iona

l tes

t gui

delin

es

1=A

bsen

t, 9=

Pres

ent

3=er

ect,

5=se

mi-e

rect

, 7=

spre

adin

g

1=de

term

inat

e, 2

=ind

eter

min

ate

1=gr

een,

2=g

reen

ish

purp

le,

4=pu

rple

1=ab

sent

, 9=p

rese

nt

3=sh

ort,

5=m

ediu

m, 7

=lon

g

1=de

ltoid

, 2=o

vate

, 3=l

ance

olat

e,

4=cu

nate

1=gr

een,

2=d

ark

gree

n

1=gr

een,

2=g

reen

with

pur

ple

spla

shes

, 3=p

urpl

e

3=sh

ort,

5=m

ediu

m, 7

=lon

g

1=gr

een,

2=p

urpl

e

1=ab

sent

, 9=p

rese

nt

3=ea

rly,

5=m

ediu

m, 7

=lat

e

3=ye

llow

ish

gree

n, 5

=gre

en,

7=da

rk g

reen

1=bu

ff, 2

=bro

wn,

3=b

lack

1=ab

sent

, 9=p

rese

nt

3=sm

all,

5=m

ediu

m, 7

=lon

g

1=gr

een,

2=g

reen

ish

brow

n,

3=br

own,

4=b

lack

, 5=m

otto

led

1=sh

iny,

2=d

ull

1=gl

obos

e, 2

=ova

l, 3=

drum

3=sm

all,

5=m

ediu

m, 7

=lar

ge


generally have a determinate growth habit while others haveindeterminate growth habit (Singh 1997). It is generallybelieved that evolution has been from indeterminate spreadingto determinate upright plant types (Smartt 1985, Smartt 1990,Steele and Mehra 1980). Early selections from the landraces(‘T 27’, ‘T 77’, ‘T 65’, ‘Gwalior 2’, ‘BR 68’, etc.) are indeterminatespreading types and have been in cultivation predominantlyas intercrop with cotton, sugarcane, pigeonpea, sorghum, etc.Cultivation of erect and determinate types have been

increasing steadily for the past three decades because of theease in cultivation in sole cropping system and their ability toavoid some diseases. In the present study, all the varieties ofdeterminate types viz., ‘Pant U 19’, ‘Pant U 30’, ‘T 9’, ‘Uttara’,‘UL 338’, ‘UG 218’, ‘G 338’ and ‘Pant U 31’ were also erect ingrowth habit. Further, the urdbean crop is a tropical one but itis grown in kharif, rabi and summer season in India. Anindeterminate plant type of 50-60 cm height (Pant U 40 andShekhar U 1) may be desirable for the kharif season (Singh

Table 2. Frequency distribution and example varieties of some important attributes of 46 released varieties of urdbeanPlant descriptors Range in expression No. of varieties Example varieties

Absent 0 Nil Anthocyanin colour Present 46 IPU 94-1, Pant U 35 Early (< 40 days) 8 Pant U 19, T 9 Medium (40-50 days) 20 Sekhar U 3

Time of flowering

Late (>50 days) 18 LBG 17, LBG 402 Erect 30 T 9, TAU 1 Semi-erect 11 Pant U 35, NDU 1

Plant growth habit

Spreading 5 Vamban 1, Naveen Determinate 7 T 9, Pant U 19 Plant habit Indeterminate 39 Vamban 1 Absent 0 - Stem pubescence Present 46 NDU 1, RBU 38 Deltoid 0 - Ovate 16 CO 5 Lanceolate 29 Pant U 19, WBU 108

Leaflet (terminal) shape

Cunate 1 Vamban 1 Green 41 PDU 1, Mash 1 Foliage colour Dark green 5 Uttara, NDU 1 Green 34 Pant U 19, NDU 1 Leaf vein colour Purple 12 Pragya Absent 0 Nil Leaf pubescence Present 46 KU 96-3, WBU 108 Green 0 Nil Green with Purple splashes 46 NDU 1, RBU 38

Petiole colour

Purple 0 Nil Yellowish Green 22 PDU 1, Sekhar U 2 Green 13 Pant U 19, T 9

Pod colour (Premature pod)

Dark Green 11 Uttara Absent 4 T 9, TAU 2 Pod pubescence Present 42 Pant U 19, NDU 1 Short (<5 cm) 0 Nil Medium (5-10 cm) 46 NDU 1, PDU 1

Peduncle length

Long (> 10 cm) 0 Nil Small (< 5 cm) 43 Azad U 2 Medium (5-7 cm) 3 Sekhar U 2

Pod length

Long (> 7 cm) 0 Nil Buff (Off-white) 22 PDU 1 Brown 10 Sekhar U 2, TU 94-2

Pod colour (mature)

Black 14 Uttara, TAU 1 Shiny 6 LBG 17 Seed lusture

Dull 40 Uttara, NDU 1 Short (<45 cm) 20 T 9, WBU 108 Medium (45-60 cm) 19 Sekhar U 1

Plant height Long (>60 cm) 7 PU 30, RBU 38

Green 2 Sekhar U 2 Greenish Brown 13 JU 2

Seed colour

Black 31 Uttara Small (<3 g) - Nil Medium (3-5 g) 46 Uttara, Pant U 30

Seed size

Large (>5 g) - Nil

Katiyar et al.: Varietal characterization of urdbean for distinctiveness, uniformity and stability 109

1997) whereas, determinate growth habit with 30 cm plantheight and greater early vigour are desirable for spring/summer/rabi season. Among the cultivars studied, ‘T 9’ is the onlyvariety suitable for spring season. Further, reduced plantheight is also an important attribute and majority of the varietiesviz., ‘Azad Urd 1’, ‘Azad Urd 2’, ‘GU 1’, ‘JU 2’, ‘KU 96-3’,‘LBG 611’, ‘LBG 648’, ‘LBG 685’, ‘LBG 17’, ‘NDU 1’, ‘Pant U35’, ‘Sarla’, ‘UG 218’, ‘T 9’, ‘UL 338’, ‘Vamban 2’, ‘WBU 108’,‘G 338’, ‘Pant U 31’, ‘Manikya’ and ‘Pant U 19’ were observedunder this category. Seven varieties exhibited plant heightmore than 60 cm whereas the remaining had height between45 to 60 cm. The urdbean varieties were largely of medium tolate flowering except some spring season varieties whichbelong to early flowering category. Short duration varietiesare often less sensitive to photoperiod than the late maturingones. Earliness and photo-insensitivity are recessive traitsand under the control of major gene (Singh and Dhaliwal 1971,Sinha 1988, Tiwari and Ramanujam 1976), and thus can bemanipulated with relative ease. Early maturing types are dwarfdue to short internodes and tend to mature after the first flushof flowers (Singh 1997). Therefore, in selecting early maturinggenotypes, early vigour is an important component.

Foliage colour varied from light green to dark green inthe varieties studied eg. ‘Uttara’, ‘NDU 1’, ‘Manikya’, ‘UL338’ and ‘Pragaya’ exhibited dark green colour and rest showedlight green foliage colour. Considerable variation was alsoobserved for leaflet (terminal) shape. Varieties like ‘CO 5’, ‘LBG17’, ‘LBG 611’, ‘LBG 645’, ‘LBG 623’, ‘LBG 648’, ‘LBG 685’,‘LBG 402’, ‘Mash 2’, ‘Uttara’, ‘LBG 20’, ‘Mash 414’, ‘Pragaya’,‘Naveen’, ‘Mash 1-1’ and ‘Sekhar U3’ were of ovate typeswhile ‘Vamban 1’ showed cunate leaf shape. Rest varietiesshowed lanceolate leaf shape. Leaf vein colour is anothercharacter with sufficient variability in urdbean varieties. Purpleleaf vein colour was observed in 12 varieties viz., ‘Uttara’,‘Azad U 2’, ‘CO 5’, ‘KU 96-3’, ‘LBG 611’, ‘LBG 645’, ‘LBG 685’,‘LBG 402’, ‘LBG 648’, ‘PDU 1’, ‘TAU 2’ and ‘Pragaya’ and theother varieties depicted green leaf vein colour.

Plants bearing more pods along with more seeds/podwould be desirable as the number of pods/plant has the highestpositive and significant correlation with yield (Singh 1997). Inthe present study, only four attributes related to pods viz.,pod colour (premature pod), pod pubescence, pod length andpod colour (mature pod) were studied. The trait prematurepod colour was categorized into three categories namely,yellowish green, green and dark green. For example 13 varietiesdepicted green colour, 11 showed dark green and the remainingshowed yellowish green. Pod pubescence was noticed in allthe varieties except for ‘AKU 9904’, ‘TAU 2’, ‘T 9’ and ‘LBG20’. On the basis of pod length, urdbean varieties can beclassified into three categories viz., short (< 5 cm), medium (5-7 cm) and long (> 7 cm). However in the present study, onlythree varieties i.e. ‘Sekhar U 1’, ‘Sekhar U 2’ and ‘Sekhar U 3’had medium pod length while rest of cultivars showed shortpod length. In respect of pod colour, 14 varieties depictedblack pod colour, 10 varieties with brown and rest showedbuff (off-white) pod colour.

Attractive seed colour has been the consumer preferenceas they offer good market price. In certain pockets, greenseed varieties are preferred over black seeded types. The greenseeded varieties are generally grown as mixed crop withsorghum, pigeonpea and cotton and popular amongconsumers of certain areas of the country (Singh 1997). In thepresent study, seeds were classified into three groups, namelygreen, black and greenish brown. Thirty one cultivars are ofblack seeded types, 13 greenish brown and two (‘Sekhar U 1’and ‘Sekhar U 2’) are green types. Further, six cultivars, viz.,‘LBG 623’, ‘LBG 20’, ‘LBG 645’, ‘LBG 17’, ‘LBG 685’ and ‘LBG648’ exhibited lustrous seed and the remaining showed dullseed. In relation to seed shape, twelve varieties depicted drumshape seed and others were oval. Seed size of urdbean cultivarsmay be grouped into three categories viz., small (< 3 g / 100-seed), medium (3 to 5 g / 100-seed) and large seeded (> 5 g /100-seed). In the present study, all the cultivars belong tomedium category.

On the basis of present preliminary characterization,these varieties were grouped into different categories for eachcharacter and may be used as reference cultivars. In the pastbreeding efforts in the development of varieties have utilizedonly a fraction of the vast available diversity as was evidentfrom their pedigree. While 30 parents involved in the ancestryof 32 cultivars developed through hybridization, only a fewwere frequently utilized with specific objectives such asincorporation of earliness, diseases and pest resistance. Pre-breeding or genetic enhancement needs emphasis for transferor introgression of genes and gene combinations fromunadapted sources into more usable breeding material. Thereare indications that novel and useful traits can be successfullycombined from related species.

REFERENCES

IBPGR. 1992. Descriptor of Vigna sp. International Plant GeneticResources Institute, Rome, Italy.

PPV & FR. 2001. Protection of Plant Varieties and Farmer’s Right Act(No. 53 of 2001). Dept. of Agriculture and Cooperation, Ministryof Agriculture, Gov. of India, Krishi Bhavan, New Delhi.

Singh, DP. 1997. Tailoring the plant type in pulse crop. Plant BreedingAbstracts 67(9): 1213-1220.

Singh KB and Dhaliwal HS. 1971. Combining ability and genetic of daysto 50% flowering in blackgram. Indian Journal of AgriculturalSciences 41: 719-723.

Sinha RP. 1988. Early maturity, dwarf mutant of urdbean. Journal ofNuclear Agriculture and Biology 17: 61-62.

Smartt J. 1985. Evolution of grain legume III. Pulses in the genusvigna. Experimental Agriculture 21: 87-100.

Smartt J. 1990. The evolution of agriculturally significant legumes.Plant Breeding Abstracts 60: 725-731.

Steele WM and Mehra KL. 1980. Structure, evolution and adaptationto farming system and environment in Vigna. In: RJ Summerfieldand AH Bunting (eds), HMSO London, UK. Pp. 393-404.

Tiwari AS and Ramanujam S. 1976. Genetics of flowering response inmungbean. Indian Journa of Genetics 36: 418-419.


Genetic diversity among selected genotypes of M4 generation in horsegramN. B. PATEL, S. B. S. TIKKA and J. B. PATEL

S. D. Agricultural University, Sardarkrushinagar, Gujarat, India; Email: [email protected](Received: December, 2008; Accepted: August, 2010)

ABSTRACT

Effect of different doses of gamma rays (5, 10, 15, 20, 25, 30, 35and 40) in three varieties of horsegram viz., ‘AK-21’, ‘AK-42’and ‘Maru-K-1’ was studied under field conditions at the MainPulses Research Station, S. D. Agricultural University,Sardarkrushinagar during summer, 2004 to kharif, 2005. Inall, eleven clusters were formed. Cluster I (34), followed bycluster IV (12), cluster V (4) and cluster VI (4) were found to bethe largest. The highest inter-cluster distance was observedbetween cluster VI and cluster X. It was observed that thegenotypes were clustered irrespective of their eco-geographicalregions. Test weight was the main contributor towards the totaldivergence. Yield per plant, number of seeds per pod, pod length,days to maturity, plant height, days to 50% flowering andnumber of pods per plant had moderate contribution towardstotal divergence.

Key words: Cluster, Gamma rays, Genetic divergence, Horsegram

Horsegram (Macrotyloma uniflorum Lam. verdc,Dolichos biflorus) is well known for its versatility to performwell under adverse edaphic and climatic conditions. It is ahardy grain legume with an ability to withstand protracteddroughts. It performs well in almost all types of soils, excepthighly alkaline soils. The grains may be utilized in multifariousways ranging from whole boiled seeds as dal to grind flourmixed with main calory sources like wheat flour. The seedshave an immense medicinal value and work like panacea forthose suffering from kidney stone which is the most prevalentproblem in arid and semi arid areas due to nagging poor qualityof potent water. Besides food, feed and medicinal uses, thecrop has immense pertinence in sustaining and enhancingsoil fertility by checking erosion and fixation of atmosphericnitrogen. In south India, the crop is especially grown as apreparatory crop in newly reclaimed lands to improve the soilfertility and organic matter status (Sen and Bhowal 1959).

Genetic diversity is a basic criterion to the crop plantswhether through natural selection or by directed plantbreeding. In plant breeding, genetic diversity plays animportant role because hybrid between lines of diverse origingenerally displays a greater heterosis than those betweenclosely related parents. D2 analysis (Mahalanobis 1936) is anextreme tool in quantifying the degree of divergence amongthe biological populations at genotypic level to assess therelative contributions of different components to the totaldivergence.


Seeds (250g) of three cultivars of horsegram viz., ‘AK21’, ‘AK 42’ and ‘Maru K-1’ were obtained from the germplasmpool maintained at the Main Pulses Research Station,Sardarkrushinagar Dantiwada Agricultural University,Sardarkrushinagar and were treated with different doses ofgamma rays at the Bhabha Atomic Research Centre (BARC),Trombay with gamma rays intensity of 1.8 kR per minute. Thedoses applied were 0, 5, 10, 15, 20, 25, 30, 35 and 40 kR in all thethree varieties, thus, making 27 treatments.

The mutated seeds were grown during summer, 2004 tokharif 2005. The M1 was raised following proper package ofpractices in single replication. From each treatment in M1generation, 25 normal appearing plants were randomly selectedto provide material for M2 generation up to 20 kR. M2 generationwas raised to assess induced polygenic variability and toscore the types of macro-mutations and their frequency. TheM2 and M3 were raised in Compact Family Block Design withthree replications. 25 seeds from each selected plants in M1were sown in a row for each replication. The selected 25 plantsfrom each treatment in M1 generation became families in M2generation. The row-to-row spacing was kept 45 cm and plant-to-plant 15 cm. Similarly M3 generation was sown in CompactFamily Block Design. M4 generation was raised in RandomizedBlock Design with three replications. The selected 58 linesthat yielded higher than respective checks in M3 generationwere selected and sown for their superiority in M4 generationalong with respective checks.

Transformation of original means of various characters(X1’s) to uncorrelated variables (Y1’s) was carried out bypivotal condensation as the common dispersion matrix bycomputer. This made D2 value as a simple sum of squares ofdifferences in transformed values for various characters.Grouping of the genotypes in different clusters was done byusing Tocher’s method (Rao 1952). The inter-cluster distancewas calculated by measuring the distance between clusters Iand II, I and III, II and III, and so on. Likewise, one by one allthe clusters were taken and their distances from each otherwere calculated.


Plant breeders are always interested to assess thegenetic diversity among the germplasm/varieties/advancedbreeding material available with them, so as to utilize them inthe breeding programme because genetically diverse parentsare likely to produce high heterotic effects (Griffing and

Patel et al.: Genetic diversity among selected genotypes in M4 generation in horsegram 111

Lindston 1954). The distantly related parents within the samespecies when utilized in cross breeding programme are likelyto produce a wider spectrum of variability.

To a plant breeder single character is not of muchimportance as the combined merit of a number of desirabletraits becomes more important, when he is concerned with acomplex trait like yield per plant. Hence, for improving yield,selection of parents based on number of characters havingquantitative divergence is required which can be fulfilled byD2 statistic developed by Mahalanobis (1936). In the presentstudy, D2 statistic estimated in 61 genotypes of horsegramisolated from M3 generation (58 mutants + 3 checks) on thebasis of their per se performance for nine characters showedthat generalized distance (D) between two populations variedfrom 0.00 to 11.04.

Clustering of 61 genotypes was carried out followingTocher’s method (Rao 1952). Over all, eleven clusters wereobserved (Table 1). Cluster I, followed by cluster IV, cluster Vand cluster VI were found to be the largest with 34, 12, 4 and4 genotypes, respectively. Seven more clusters, each havingsingle genotype, were observed. Genetic drift and selectionin different environments might result in greater diversity thangeographical distance. Moreover, free exchange of seedmaterial along different geographical regions changes the

character constellation associated with particular region.Absence of parallelism between genetic diversity andgeographical origin was reported in upland cotton and castor(Bhatt and Reddy 1987). Similar conclusion was derived byGaneshaiah (1982). The maximum inter-cluster distance (D =11.04) was observed between clusters X and VI, followed byclusters X and II (D = 9.86) and clusters X and V (D = 8.68)(Table 2). Large distances between clusters (inter-cluster) werereported by Balan et al. (1992) and Patil et al. (1993). Highheterotic combinations are obtained when the genotypes ofdistantly placed clusters are inter-crossed. In the presentinvestigation, genotypes of cluster X, if crossed with thoseof cluster VI, might give high heterosis. Similar results may beobtained by crossing cluster X and cluster II and cluster Xand cluster V.

Cluster VII depicted the lowest mean values for days to50% flowering and plant height, while cluster III depicted thelowest mean value for days to maturity. Cluster X showedhighest mean values for number of effective branches perplant and test weight. Similarly, cluster XI for number of podsper plant, cluster VIII for pod length, cluster IX for number ofseeds per pod and cluster III for yield per plant exhibited thehighest mean values (Table 3). Inter crossing of genotypesamong these clusters will induce variability for the respectivetraits.

Table 1. The distribution of 61 genotypes of horsegram to different clusters on the basis of D2 statisticsCluster Number of genotypes Genotypes I 34 AK-42 15 kR 20, MK-1 15 kR 10, AK-42 5 kR 10, MK-1 15 kR 13, AK-21 15 kR 14, AK-42 10 kR 5, AK-42 20 kR

12, MK-1 15 kR 19, MK-1 5 kR 17, AK-21 20 kR 15, AK-21 5 kR 13, MK-1 20 kR 4, MK-1 20 kR 11, AK-42 20 kR 23, AK-21 20 kR 3, AK-42 20 kR 1, AK-42 control, AK-42 5 kR 8, MK-1 15 kR 7, AK-42 15 kR 6, MK-1 5 kR 7, AK-21 5 kR 20, AK-21 5 kR 22, AK-42 15 kR 23, MK-1 15 kR 2, MK-1 5 kR 21, AK-21 15 kR 5, MK-1 20 kR 16, AK-21 20 kR 17, AK-42 5 kR 3, AK-21 5 kR 4, MK-1 5 kR 13, MK-1 15 kR 4, MK-1 15 kR 9

II 1 MK-1 10 kR 10 III 1 AK-21 10 kR 12

IV 12 AK-21 10 kR 9, MK-1 10 kR 17, AK-21 10 kR 8, MK-1 5 kR 22, AK-21 10 kR 20, AK-21 10 kR 17, MK-1 20 kR 18, AK-42 10 kR 2, AK-21 10 kR 4, AK-21 10 kR 6, AK-21 20 kR 23, MK-1 10 kR 19

V 4 AK-21 control, MK-1 control, MK-1 15 kR 23, AK-21 15 kR 12 VI 4 AK-42 10 kR 14, MK-1 10 kR 8, AK-42 10 kR 7, AK-42 5 kR 4 VII 1 AK-42 5 kR 24 VIII 1 AK-42 15 kR 25 IX 1 AK-21 5 kR 11 X 1 AK-21 15 kR 2 XI 1 MK-1 5 kR 2

Table 2. Average intra and inter-cluster (D) values for 61 genotypes of horsegram

Cluster 1 2 3 4 5 6 7 8 9 10 11 1 2.79 3.40 3.81 4.54 3.69 4.76 3.85 3.71 3.93 7.68 5.56 2 0.00 5.72 6.53 3.96 3.46 5.04 4.99 4.52 9.86 6.57 3 0.00 3.02 5.14 6.79 3.77 4.67 4.41 5.56 5.38 4 3.00 5.27 7.58 4.18 4.34 5.06 4.93 5.40 5 3.45 5.25 4.87 4.29 5.59 8.68 7.13 6 4.17 6.16 5.55 5.85 11.04 7.93 7 0.00 4.76 2.83 7.07 3.60 8 0.00 4.51 6.96 6.24 9 0.00 7.11 3.34 10 0.00 6.43 11 0.00


The results revealed that test weight was the maincontributor towards the total divergence (Table 4). Similarresults were obtained by Ramakrishnan et al. (1979) inhorsegram and Renganayaki and Rangasamy (1991) in greengram. Yield per plant, number of seeds per pod, pod length,days to maturity, plant height, days to 50% flowering andnumber of pods per plant had moderate contribution towardstotal divergence, while number of effective branches per planthad least contribution to the total divergence.

The clustering pattern could be utilized for identifyingthe best cross combinations in generating variability withrespect to various traits. Superior genotypes for hybridizationprogramme can also be selected on the basis of inter-clusterdistance and cluster means. In the present investigation, thesignificant correlation in positive direction with yield per plantwas observed by days to 50% flowering, number of effectivebranches per plant and number of pods per plant in ‘AK-21’;number of effective branches per plant, number of pods perplant, and number of seeds per pod in ‘AK-42’ and days to50% flowering, days to maturity, number of pods per plant,pod length and number of seeds per pod in ‘MK-1’. Maximumcluster mean was observed for yield per plant (cluster III),number of pods per plant (cluster XI) and number of seedsper pod (cluster IX). Therefore, for creating wide spectrum of

variability and improving yield, the genotypes included incluster III, cluster XI and cluster IX should be inter crossed.

The foregoing discussion clearly demonstrates that thegenetic variability induced by physical mutagen both atmorphological and quantitative levels in majority of thecharacter broadens the scope of selection for desiredcharacters and plant type for future breeding programme.Mutation breeding could not perform miracles but still it wasvery successful in opening new horizons for a crop likehorsegram, which is strictly self pollinated and crossing isvery difficult due to tiny structure of flower.

REFERENCES

Balan A, Ramasamy P and Sivasamy N. 1992. Genetic diversity inhorse gram (Macrotyloma uniflorum L. Verdec). Indian Journal ofPulses Research 5: 78-81.

Bhatt Dipika and Reddy TP. 1987. Genetic divergence and heterosis incastor (Ricinus communis L.). Indian Journal of Botany 10: 21-26.

Ganeshaiah KN. 1980. Multivariate analysis for yield and its contributingcharacters in horse gram (Dolichos biflorus L.). Mysore Journal ofAgricultural Sciences 14: 125.

Griffing B and Lindston EW. 1954. A study of combining abilities ofcorn inbreds having varying proportions of corn belt and non-cornbelt germplasm. Agronomy Journal 46: 545-552.

Mahalanobis PC. 1936. On the generalized distance in statistics.Proceedings of National Institute of Science, India 2: 49-55.

Patil RA, Jahagirdar JE, Shinde VS and Ghodke MK. 1993. Mungbeanvariety ‘BM-4’ is suitable for central zone. Indian Farming 42: 12.

Ramakrishnan A, Marappan PV and Sivasamy N. 1979. Geneticdivergence in horse gram. Indian Journal of Agricultural Sciences49: 719-723.

Rao CR. 1952. Advanced Statistical Methods in Biometrical Research(Edn. I), John Willey and Sons, Inc., New York. Pp. 337-363.

Renganayaki K and Rangasamy SR. 1991. Genetic divergence in Vignaspecies. Indian Journal of Pulses Research 4: 159-164.

Sen NK and Bhowal JG. 1959. Genetic studies in horse gram. IndianJournal of Genetics and Plant Breeding 19: 228-233.

Table 3. Cluster means for different characters of 61 genotypes of horsegramCluster Number

Number of

genotypes

Days to 50%

flowering (no)

Plant height (cm)

Effective branches/

plant (no)

Pods/ plant (no)

Pod Length

(cm)

Seeds/ pod (no)

Days to

maturity (no)

Test weight

(g)

Yield/ plant

(g)

I 34 57.04 58.91 3.09 38.23 4.03 4.84 105.50 3.49 7.39 II 1 59.45 58.80 2.83 40.59 4.08 5.00 105.92 3.31 8.07 III 1 55.44 56.53 2.89 38.84 3.64 5.38 102.56 3.69 8.37 IV 12 56.11 57.58 2.97 37.91 4.00 4.61 107.18 3.76 6.98 V 4 57.67 53.73 3.15 36.27 3.75 4.26 110.28 3.45 6.72 VI 4 54.67 60.59 2.82 39.94 4.11 4.70 104.79 3.26 7.55 VII 1 54.00 48.74 3.00 43.42 3.87 4.89 107.00 3.62 6.85 VIII 1 55.22 57.49 2.92 31.13 5.00 3.93 105.78 3.57 5.20 IX 1 56.00 53.09 2.83 35.65 4.68 5.44 103.33 3.55 6.23 X 1 59.22 62.22 3.21 29.89 4.70 4.92 104.11 4.02 5.56 XI 1 58.00 61.73 2.58 44.89 4.37 5.00 105.56 3.71 6.21

Table 4. Per cent contribution of each character towards thetotal divergence

Sr. No.

Character Number of times character ranked

first

Contribution (%)

1 Days to 50% flowering (no) 94 5.14 2 Plant height (cm) 109 5.96 3 Effective branches/plant (no) 20 1.09 4 Pods/plant (no) 90 4.92 5 Pod length (cm) 122 6.67 6 Seeds/pod (no) 166 9.07 7 Days to maturity (no) 111 6.07 8 Test weight (g) 937 51.20 9 Yield/plant (g) 181 9.89


ABSTRACT

All possible crosses excluding reciprocals were made among 10diverse genotypes of field and table pea. General and specificcombining ability variances were significant for all the traitsin both F1 and F2 generations. Higher values of variance due togca for days to flowering, days to maturity, plant height, podlength, number of developed ovules per pod, shelling percentageand green pod yield per plant showed presence of additive geneaction while it was non additive for number of productivebranches per plant and number of pods per plant based on boththe generations. Parents ‘KS-226’, ‘KS-225’, ‘KS-136’, ‘AzadP-1’ and ‘Azad P-3’ were good general combiners for green podyield based on both the generations. The average performanceof table pea parents were better than field pea parents. Crosscombinations namely ‘KPMR-184 × KS-136’, ‘Rachna × KS-225’, ‘KS-195 × AP-3’, ‘KPMR-184 × Mutant pea’ and ‘Mutant× KS-136’ in F1, ‘KS-195 × KS-225’, ‘KPMR-184 × AP-3’,‘Mutant × KS-226’, ‘KS-226 × AP-1’ and ‘KPMR-65 × KS-226’in F2 were found as good specific combinations for green podyield. The majority of these crosses falls in the high x lowgeneral combiners. The crosses between table x field pea gavehigher yield than table x table or field x field pea.

Key words: Combining ability, Field pea, Gene action, Green podyield, Pisum sativum L., Table pea

Peas are major source of protein in vegetarian diet ofIndia. It also plays an important role in soil improvement byvirture of its ability to fix atmospheric nitrogen through itssymbiotic association with Rhizobium. Exploitation of hybridvigour and selection of parents on the basis of their combiningability have opened a new avenue in crop improvement.Among various techniques developed, diallel analysis is avery convenient one for gathering information aboutcombining ability effects which helps in selection of parentsfor hybridization and ultimately the isolation and developmentof superior genotypes. The present study was undertaken tounderstand the genetic architecture of yield and itscomponents through diallel analysis.

Genetic analysis for yield and yield traits in peaK.P. SINGH, H.C. SINGH and M.C. VERMA

Department of Genetics and Plant Breeding; C.S. Azad University of Agriculture and Technology, Kanpur-208 002, UttarPrdesh, India; E-mail: [email protected](Received: September, 2009; Accepted: September, 2010)


A total of 10 diverse genotypes of field and table peasnamely ‘Rachna’, ‘KPMR-65’, ‘KPMR-184’, ‘mutant of ‘P-43’,‘KS-136’, ‘KS-195’, ‘KS-225’, ‘KS-226’, ‘Azad P-1’ and ‘AzadP-3’ were crossed in all possible combinations excludingreciprocals. The F0 seeds were advanced to get F1. The finalexperiment including 10 parents 45 F1s and 45 F2s each wereplanted in a randomized complete block design with threereplications at Vegetable Research Farm, Kalyanpur, Kanpurin the year 2003-04. Each parents and F1s were sown in singlerow of five meter length while F2s in two rows each spaced at45 cm x 5 cm between rows and plants, respectively. Therecommended package of practices was adopted to raise agood crop. Observations were recorded on ten randomlyselected plants in parents and F1s and 20 plants each in F2sfor days to flowering, days to maturity, plant height, numberof productive branches per plant, number of pods per plant,pod length, number of developed ovules per pod, shellingpercentage and green pod yield per plant. The mean datawere used for diallel analysis following Griffing (1956) method2 model 1.


Analysis of variance for combing ability showed highlysignificant differences both for gca and sca for all thecharacters based on both the generations. It indicates therole of both additive and non-additive genet effects forcontrolling these traits (Table 1). A perusal of the table revealedhigher the magnitude of s2gca for characters namely days toflowering, days to maturity, plant height, pod length and yield/plant (F2) indicating that these traits were under control ofadditive gene action. Similar results were also reported bySingh et al. (2006). The characters number of branches perplant, pods per plant, shelling percentage and green pod yieldper plant (F1s only) showed higher the value of sca variancesthan corresponding gca variance revealing the presence ofnon additive gene action. The ratio of s2 gca/s2sca alsoshowed similar pattern. These results are in accordance withKumar et al. (2006) and Singh and Singh (2003).

The gca effect and mean performance of the parents arelisted in Table 2 which revealed that none of the parentsshowed desirable gca effects for all the characters hence it is

* Author for Correspondence : Assistant Seed Production Officer, Breeder Seed Production Unit, Section of Seed and Farms, C.S. AzadUniversity of Agriculture and Technology, Kanpur-208 002, UttarPrdesh, India


Table 1. Analysis of variance for combining ability for yield and related traits in peasMean sum of squares Source of

variation d.f.

Days to flowering

(no)

Days to maturity

(no)

Plant height (cm)

Productive branches/ plant (no)

Pods/ plant (no)

Pod length (cm)

Developed ovules/pod

(no)

Shelling percent

Green pod yield/ plant

(g) F1 9 325.45** 374.81** 16403.86** 0.48** 143.10** 5.46** 3.00** 40.14** 2741.37** gca F2 9 332.40** 348.65** 12635.93** 0.48** 64.08** 5.05** 2.53** 20.95** 2881.16** F1 45 5.87** 9.39** 1256.25** 0.20** 74.02** 0.08** 0.46** 9.29** 761.23** sca F2 45 8.13** 12.20** 516.30** 0.06** 7.85** 0.16** 0.30** 6.03** 134.86** F1 108 0.55 0.36 8.80 0.01 2.14 0.004 0.006 0.02 14.33 Error F2 108 0.41 0.52 10.37 0.003 0.58 0.005 0.006 0.02 8.30 F1 26.63 30.45 1262.30 0.02 5.75 0.44 0.21 2.57 165.01 σ2g F2 27.02 28.03 1009.96 0.03 4.68 0.40 0.18 1.41 228.85 F1 5.32 9.03 1247.45 0.19 71.88 0.07 0.45 9.27 746.90 σ2s F2 7.72 11.68 505.93 0.05 7.27 0.15 0.29 6.01 126.56 F1 5.00 3.37 1.01 0.10 0.07 6.28 0.46 0.27 0.22 σ2g/σ2s F2 3.50 2.39 1.99 0.60 0.64 2.66 0.62 0.23 1.80

** Significant at P = 0.01

Table 2. Estimates of general combining ability effects of the parents for yield and yield related traits in peas

**Significant at P = 0.01

Days to flowering (no)

Days to maturity (edible pods) (no)

Plant height (cm)

Productive branches/plant (no)

Parent

F1 F2 Mean F1 F2 Mean F1 F2 Mean F1 F2 Mean Rachna 6.99** 7.05** 71.40 7.10** 7.25** 104.83 62.46** 42.62** 203.67 -0.37** -0.12** 3.00

KPMR-65 4.29** 4.71** 64.50 4.85** 4.85** 97.50 43.26** 48.68** 184.83 0.36** -0.42** 3.70 KPMR-184 6.64** 6.29** 68.83 7.37** 6.92** 101.67 42.04** 44.25** 180.97 0.04** -0.02** 2.63 Mutant of P-43 -4.04** -3.73** 48.27 -4.35** -3.65** 81.20 12.55** 3.42** 98.37 0.07** -0.14** 2.23 KS-136 -4.40** -4.64** 45.23 -5.28** -4.78** 75.37 -28.84** -21.49** 86.00 -0.09** -0.04** 2.90 KS-195 -1.61** -1.20** 52.27 -2.04** -1.57** 82.50 -22.72** -23.97** 85.63 -0.07** -0.13** 2.73

KS-225 0.40** 0.21** 56.10 0.19** 0.05 85.97 -27.42** -20.86** 93.70 0.19** 0.21** 3.53 KS-226 3.55** 3.60** 61.93 4.21** 3.36** 92.17 -13.23** -16.62** 92.27 0.09** 0.15** 3.23 Azad P-1 -3.48** -3.64** 46.70 -3.64** -3.97** 76.83 -31.71** -29.27** 64.13 -0.16** -0.23** 2.60 Azad P-3 -8.34** -8.65** 32.37 -8.42** -8.47** 62.40 -36.41** -26.77** 37.47 -0.07** -0.10** 2.93 S.E. (g i) ± 0.04 0.03 0.03 0.04 0.66 0.78 0.0009 0.0003

S.E. (gi – gj) ± 0.09 0.07 0.06 0.09 1.47 1.73 0.002 0.0006

Pods/plant (no)

Pod length (cm)

Developed ovules/pod (no)

Shelling percent

Green pod yield/plant (g)

Parent

F1 F2 Mean F1 F2 Mean F1 F2 Mean F1 F2 Mean F1 F2 Mean Rachna 0.96** 0.69** 26.87 -0.33** -0.52** 6.90 -0.47** -0.31** 5.83 2.60** 1.31** 53.30 -6.44** -13.53** 81.47 KPMR-65 6.89** 5.34** 32.40 -0.88** -0.80** 6.33 -0.66** -0.72** 4.60 1.40** -0.64** 53.30 -9.38** -4.45** 85.33 KPMR-184 1.80** -0.53** 25.07 -0.45** -0.39** 7.03 -0.41** -0.41** 4.93 0.68** 0.80** 55.67 -11.74** -13.52** 78.50 Mutant of P-43 3.27** -0.97** 21.43 -1.19** -1.11** 5.27 -0.45** -0.52** 3.63 1.93** 1.81** 54.03 -28.37** -29.07** 44.23 KS-136 -3.94** -1.74** 23.13 0.71** 0.56** 9.27 0.94** 0.62** 6.57 0.18** 0.53** 50.90 9.78** 7.40** 130.27 KS-195 -1.43** 1.39** 28.13 0.08** 0.12** 7.93 0.03** 0.06** 5.53 -0.77** -0.71** 47.80 -0.74 7.84** 119.03 KS-225 -0.57** -0.24** 26.73 0.49** 0.49** 8.63 0.14** 0.24** 5.90 -2.71** -1.81** 45.03 17.01** 13.98** 134.60 KS-226 0.25 0.93** 27.93 0.60** 0.64** 8.90 0.17** 0.22** 6.03 -2.91** -2.52** 48.23 23.92** 24.20** 148.77 Azad P-1 -4.27** -2.24** 23.60 0.49** 0.52** 8.67 0.49** 0.48** 6.30 0.40** 0.71** 52.80 0.96 5.49** 118.77 Azad P-3 -2.97** -2.64** 19.53 0.48** 0.49** 8.97 0.23** 0.34** 6.07 -0.80** 0.52** 51.33 5.00** 1.65 106.13 S.E. (g i) ± 0.16 0.04 0.0003 0.0003 0.0005 0.0004 0.001 0.001 1.07 0.62 S.E. (gi – gj) ± 0.36 0.10 0.0007 0.0008 0.001 0.001 0.003 0.003 2.39 1.38

Table 2. Cont…..

**Significant at P = 0.01

Singh et al.: Genetic analysis for yield and yield traits in pea 115

Table 3. Ranking of top five desirable crosses for yield and yield related traits in peas

gca status Character/cross sca effect Mean value P1 P2

Days to flowering (no) F1 Rachna x KS195 4.37** 55.93 L H Rachna x KS225 3.41** 58.90 L L Rachna x Mutant 3.34** 54.53 L H Mutant x KS226 0.10 51.30 H L KPMR184 x Mutant 2.73** 54.80 L H F2 Rachna x KS225 6.26** 53.37 L L KPMR184 x Mutant 4.30** 50.63 L H Mutant x KS195 4.25** 43.20 H H Rachna x KS136 4.24** 50.53 L H Mutant x KS226 3.04** 49.20 H L Days to maturity (no) F1 Rachna x KS195 5.01** 85.93 L H Mutant x KS226 4.58** 81.17 H L KS195 x KS225 4.49** 79.53 H L Rachna x KS225 4.37** 88.80 L L KPMR184 x Mutant 4.20** 84.70 L H F2 Rachna x KS225 6.78** 83.27 L L KPMR184 x Mutant 5.46** 80.57 L H Rachna x KS136 4.81** 80.40 L H Mutant x KS195 4.46** 73.07 H H Rachna x Mutant 3.75** 82.60 L H Plant height (cm) F1 KPMR65 x KPMR184 34.76** 195.47 L L Rachna x KPMR184 33.10** 216.33 L L KS195 x Azad P-1 32.80** 57.70 H H KPMR184 x Mutant 31.52** 168.00 L L Rachna x KPMR65 29.21** 221.43 L L F2 KPMR65 x Mutant 26.90** 158.80 L L Rachna x KPMR65 24.13** 200.77 L L KS136 x KS225 22.08** 69.17 H H KS136 x KS195 18.79** 69.33 H H KPMR65 x KPMR184 18.75** 207.77 L L Productive branches/plant (no) F1 KPMR184 x Mutant 1.05** 4.57 H H KPMR184 x Azad P-3 0.60** 3.97 H L KPMR65 x KS225 0.54** 4.50 H H KS195 x KS226 0.50** 3.93 L H KPMR65 x Azad P-1 0.49** 4.10 H L F2 KPMR65 x Mutant 0.41** 3.67 H L Rachna x Mutant 0.38** 3.10 L L Rachna x KS226 0.33** 3.33 L H KPMR65 x KPMR184 0.30** 3.67 H L KPMR184 x Mutant 0.29** 3.10 L L Pods/plant (no) F1 KPMR184 x Mutant 19.30** 62.27 H H KPMR65 x Mutant 12.04** 60.10 H H KPMR184 x Azad P-3 11.30** 48.03 H L KPMR184 x KS136 9.84** 45.60 H L

gca status Character/cross sca effect Mean value P1 P2

Rachna x Azad P-3 9.27** 45.17 H L F2 KPMR65 x Azad P-3 7.26** 37.93 H L Rachna x Azad P-3 5.58** 31.60 H L KPMR65 x Mutant 4.42** 36.77 H L KPMR184 x Azad P-3 4.13** 28.93 L L Mutant x KS226 3.26** 31.20 L H Pod length (cm) F1 KS195 x Azad P-3 0.50** 8.67 H H Rachna x KPMR65 0.35** 6.73 L L Azad P-1 x Azad P-3 0.30** 8.87 H H KPMR184 x KS136 0.27** 8.13 L H Rachna x KS225 0.24** 8.00 L H F2 KPMR184 x Mutant 0.59** 6.60 L L Rachna x Mutant 0.42** 6.30 L L Rachan x KPMR65 0.41** 6.60 L L KS225 x Azad P-3 0.41** 8.90 H H KS195 x KS225 0.38** 8.50 H H Developed ovules/pod (no) F1 KS136 x KS225 1.37** 8.17 H H KS195 x Azad P-3 1.35** 7.33 H H Mutant x KS136 1.13** 7.33 L H KS136 x KS226 1.10** 7.93 H H KS195 x Azad P-1 0.80** 7.03 H H F2 KS136 x Azad P-3 0.22** 7.83 H H Mutant x KS226 0.99** 6.33 L H Azad P-1 x Azad P-3 0.89** 7.37 H H KS195 x Azad P-1 0.88** 7.07 H H KPMR184 x KS225 0.66** 6.13 L H Shelling (%) F1 KPMR65 x KS225 6.83** 56.37 H L KS195 x Azad P-3 5.96** 184.57 L L KS136 x Azad P-3 4.13** 153.33 H L Mutant x Azad P-1 3.95** 108.10 H H KS225 x Azad P-1 2.93** 168.80 L H F2 Rachna x KPMR65 3.76** 55.37 H L KPMR184 x KS226 3.38** 52.60 H L KS195 x Azad P-3 2.49** 53.23 L H Mutant x KS225 2.46** 53.40 H L Rachna x KS136 2.40** 55.17 H H Green pod yield/plant (g) F1 KPMR184 x KS136 57.65** 198.23 L H Rachna x KS225 44.20** 197.30 L H KS195 x Azad P-3 37.77** 184.57 L H KPMR184 x Mutant 36.68** 139.10 L L Mutant x KS136 35.82** 159.77 L H F2 KS195 x KS225 18.02** 144.80 H H KPMR184 x Azad P-3 15.90** 109.00 L H Mutant x KS226 15.44** 115.53 L H KS226 x Azad P-1 15.04** 149.70 H H KPMR65 x KS226 14.05** 138.77 L H


not possible to pickup a good general combiner for all thecharacters. However, for days to flowering and maturityparents namely ‘AP-3’, ‘KS-136’, ‘Azad P-1’, mutant of ‘P-43’and ‘KS-195’ showed significant negative gca effects alongwith less number of days taken. These genotypes might beuseful for getting early recombinants. Parents ‘AP-3’, ‘AP-1’,‘KS-136’, ‘KS-225’, ‘KS-195’ and ‘KS-226’ with significantnegative gca effects were good general combiners for plantheight and might be possessing favourable genetic systemfor reducing height in their progenies. For number ofproductive branches per plant, only three parents i.e. ‘KPMR-65’, ‘KS-225’ and ‘KS-226’ possess desirable positivelysignificant gca effects based on both the generations. Fornumber of pods per plant ‘KPMR-65’ followed by ‘Rachna’,‘KS-226’ based on both the generations; ‘KPMR-184’ and‘Mutant P-43’ based on F1 generations possessed significantpositive gca effects. Similarly for pod length; parents ‘KS-136’ followed by ‘KS-226’, ‘AP-1’, ‘KS-225’, ‘AP-3’ and ‘KS-195’, for number of developed ovules per plant six parents,‘KS-136’, ‘KS-195’, ‘KS-225’, ‘KS-226’, ‘AP-1’ and ‘AP-3’;for shelling percentage ‘Rachna’, ‘KPMR-184’, ‘Mutant P-43’, ‘Azad P-1’, ‘KS-136’ were found promising. For greenpod yield, parents ‘KS-226’, ‘KS-225’, ‘KS-136’, ‘Azad P-3’and ‘Azad P-1’ expressed positive and significant gca effectsbased on both the generations which may produce highyielding recombinants in their progenies and may be utilizedin future pea improvement programme.

Five top ranking desirable cross combinations selectedon the basis of sca effect and per se performance have beenpresented in Table 3. None of the selected cross combinationsexhibited significant and desirable sca/ per se performance inboth the generations for all the characters under study.However, some crosses showed significant sca effect for otheryield traits along with green pod yield in either of thegeneration eg. ‘KPMR-184 × KS-136’ having significant scaeffect for green pod yield, pod length and number of pods perplant. Similarly ‘KPMR-184 × Mutant’ had significant scaeffects for number of pods per plant, number of productivebranches per plant, plant height, days to flowering and daysto maturity (earliness) besides green pod yield. These heteroticcrosses showed high × low and low × low gca status. Thecombination of high × low general combiners can producetransgressive segregants if additive effect of one parent andcomplementary effect of other parent works in same directionas also stated by Redden and Jenson (1974) in self pollinatedcrops. The cross combination showed that low × low generalcombiners might be produced due to non-additive gene effectsand as such could not be exploited in self pollinated crops likepea but assumed that they can be intermated in F2 by anysuitable design to produce transgressive segregants afterbreaking the tight linkage if any as also reported by Pederson

(1974). In present study desirable and promising crosses like‘KS-195 × KS-225’ and ‘KS-226 × Azad P-1’ in F2 generationsshowed high × high gca status for green pod yield per plant.These crosses might have asisen due to additive and/oradditive × additive type of gene interaction which is fixable innature and can be handled by simple pedigree or modifiedpedigree method as suggested by Brim (1966). Other yieldcontributing traits also showed such type of gca effects like‘KPMR × Mutant’, ‘KPMR-65 × KS-225’ for number ofproductive branches per plant and number of pods per plant:‘KS-165 × AP-3’, ‘AP-1 × AP-3’ for pod length, ‘KS-136 × KS-225’, ‘KS-195 × AP-3’, ‘KS-136 × KS-226’, ‘KS-195 × AP-1’(both in F1 and F2) for number of developed ovules per podand ‘Mutant × AP-1’ for shelling percentage.

It is also notable that majority of the crosses for yieldcontributing traits showing high sca effects and per seperformance involved one parents of field pea and other oftable pea genotypes.

For utilization of genetic variation related to non-additive or non-fixable in nature, population improvementprogrammes such as biparental mating followed by recurrentselection method of Frey (1975) and Rachie and Gardner (1975)would be more appropriate.

REFERENCES

Brim CA. 1966. A modified pedigree method of selection in soyeans.Crop Science 6: 220.

Frey KJ. 1975. Breeding concept and techniques for self pollinatedcrops. In: Proceeding of International Workshop on Grain Legumes,ICRISAT, Hyderabad, India. Pp. 257-278.

Griffing B. 1956. Concepts of general and specific combining ability inrelaiton to diallel crossing system. Australian Journal of BiologicalScience, 9: 463-493.

Kumar Subhash, Srivastava RK and Ranjeet Singh. 2006. Combiningability for yield and its component traits in field pea. Indian Journalof Pulses Research 19: 173-175.

Pederson DG. 1974. Arguments against intermating before selection inself fertilized species. Theoretical and Applied Genetics 45: 147-162.

Rachie KO and Gardner CO. 1975. Increasing efficiency in breedingpartially out crossing grain legumes. In: Proceedings of InternationalWorkshop on Grain Legumes, ICRISAT, Hyderabad, India. Pp. 285-297.

Redden RJ and Jenson NF. 1974. Mass selection and mating systems incereals. In: Proceedings of International Workshop on GrainLegumes, ICRISAT, Hyderabad, India. Pp. 345-350.

Singh HC, Srivastava RL and Rajendra Singh. 2006. Additive, dominanceand epistatic components of variation for some metric traits infield pea. Indian Journal of Pulses Research 19: 170-172.

Singh JD and Singh IP. 2003. Combining ability analysis in field pea(Pisum sativum L.). Indian Journal of Pulses Research 16: 98-100.


ABSTRACT

The experiment consisting six genetically diverse chickpealines and their fifteen F1s made in diallel fashion was conductedfor combining ability analysis for nodulation and seed yieldcomponents. Genetic analysis revealed that both additive andnon-additive genetic components of variation are importantfor inheritance of all the characters. However, the magnitudeof non-additive (sca) variance was considerably higher thanadditive (gca) variance. The parents ‘HC 3’ for 100-seed weight,biological yield, seed yield, nodule weight and root weight ;‘HC-1’ for harvest index and plant weight ; ‘HC-2’ for numberof nodules and nitrogen content and ‘H96-99’ for number ofpods and leghaemoglobin content were identified as goodgeneral combiners. The cross combination ‘ICC 4993’ × ‘HC 3’was the best for seed yield per plant, biological yield, harvestindex and plant weight while crosses involving ‘H96-99’ and‘HC-1’ as one of the parent were recorded as better combinationsfor leghaemoglobin content, nitrogen content and number ofnodules. In view of parallel role of both additive and non-additivegenetic effects determining the inheritance of differentcharacters, their simultaneous exploitation through adoptionof biparental approach/early generation mating is suggested.

Key words: Additive genetic variance, Chickpea, Non-additivegenetic variance

Chickpea (Cicer arietinum L.) commonly known as gram,is one of the most important leguminous crop of India, playinga crucial role in agricultural production due to its symbioticpotential to fix nitrogen in association with rhizobia. In India itis grown in 8.25 mha area giving an annual production of 7.05million tonnes. (Chaturvedi 2009). In any crop productionsystem high yielding varieties are must to harvest high yielddespite other inputs, for breeding these varieties a definedbreeding programme is to be followed.

The choice of breeding method depends on the geneaction involved in the inheritance of the characters. Diallelanalysis developed by Jinks and Hayman (1953) and Griffing(1956) is one of the most potent technique for the evaluationof the varieties in terms of their genetic makeup as it providesinformation on the nature and magnitude of genetic parametersand general and specific combining ability of parents andtheir crosses, respectively. In the present investigation, anattempt has been made to assess the nature of gene effectsfor nodulation and yield related components for decidingefficient breeding methodology following the diallel analysis.

Diallel analysis for nodulation and yield contributing traits in chickpeaPREETI VERMA and R. S. WALDIA

Department of Plant Breeding, College of Agriculture, CCSHAU, Hisar 125 004, Haryana, India;Email: [email protected](Received: July, 2010; Accepted: September, 2010)

The interpretation of the results from present diallelanalysis are restricted to the specific materials used in theexperiments as the parents and cannot be regarded as a randomsample from any population. The results have been discussedin view of the most appropriate breeding strategies for thegenetic improvement of agronomic characters in chickpea.


A diallel set of crosses were made excluding reciprocalsinvolving six diverse genotypes (chosen on the base ofpreviously assessed nodulation ability) of chickpea viz., ‘ICC4918’, ‘ICC 4993’ (non-nodulating), ‘H96-99’, ‘HC-1’ (mediumnodulating), ‘HC-2’, ‘HC-3’ (high nodulating). The materialcomprising twenty one genotypes including 6 parents andtheir 15 F1’s were sown in a randomized block design withthree replications during rabi 2004-05 at CCSHAU, Hisar. Therow and plant spacing were 30 and 15 cm, respectively. Fiverandom plants were selected from each genotype in eachreplication and observations were recorded for 13 charactersviz., plant height (cm), number of secondary branches, numberof pods per plant, 100-seed weight (g), biological yield (g),seed yield (g), number of nodules, nodule weight (g), nitrogencontent (%), leghaemoglobin content (mg/g), harvest index(%), root weight (g) and plant weight (g). The nitrogen contentwas estimated by Kjeldahl’s steam distillation method (Bremer1965) and leghaemoglobin content by Hartree (1955) method.The combining ability analysis was made following Griffing’smethod (1956).


The analysis of variance revealed significant genotypicdifferences among the genotypes for all the thirteen charactersindicating thereby considerable amount of variability for allthe characters thus, justifying the use of the material in thepresent study (Table 1). Analysis of variance for combiningability (Table 2) revealed significant general combining ability(gca) and specific combining ability (sca) variances for all thecharacters studied, indicating the importance of both additiveas well as non additive genetic components of variation in theinheritance or expression of these attributes. The importanceof both types of gene effects has been observed earlier alsoin chickpea for seed yield and related attributes (Jahagirdar etal. 1994, Patil et al. 2006, Bhardwaj et al. 2009). The magnitudeof the non additive (sca) variance was considerably higher

Present address : Agricultural Research Station (under MPUAT, Udaipur), Kota 324001, Rajasthan, India


than additive (gca) variance for all the characters indicatingthe preponderance of non additive genetic effects (dominanceand epistasis) in controlling the expression of these characters.Earlier studies also showed predominantly non additivegenetic control for one or more of these characters (Bajaj etal. 1984 and Bhaduoria et al. 2002). However, others (Chanderet al. 2001, Muhammad et al. 2003, Bhardwaj et al. 2009)reported additive gene effects to be more prominent for thesecharacters in their material. Such disparities in the observationsmay arise from differences in the genetic constitution of theparental materials studied, variation in the environment, thetechniques used in analyzing the data and the precision ofthe experiment (Singh et al. 1992).

The estimates of gca effects (Table 3) showed that none

of the parent evinced good gca for all the traits so it wasdifficult to pick good combiners for all the characters togetherbecause the combining ability effects were not consistent forall the yield components, possibly because of negativeassociation among some of the characters (Gowda and Bahl1978). This shows that genes for different desirable characterswould have to be combined from different sources (Kumari1999). The gca effects indicated that parent ‘H96-99’ was highgeneral combiner for plant height, number of pods andleghaemoglobin content. Parents ‘ICC 4918’ and ‘HC-3’showed high gca effects for number of secondary branches.The parent ‘HC-3’ was good general combiner for 100-seedweight, biological yield, seed yield, nodule weight and rootweight while ‘HC-1’ was good general combiner for harvestindex and plant weight. For number of nodules and nitrogen

Table 1. Analysis of variance for thirteen characters in chickpea

*, ** Significant at P = 0.05 and 0.01, respectively

Mean Square Source D.F. Plant height (cm)

Secondary branches

(no)

Pods (no)

100-seed weight

(g)

Biological yield (g)

Seed yield (g)

Nodules (no)

Nodule weight

(g)

Nitrogen content

(%)

Lb content (mg/g)

Harvest index (%)

Root weight

(g)

Plant weight

(g) Replications 2 1.254 2.427 70.266 1.196 62.029 5.198 0.062 0.004 1.355 0.0109 1.493 0.016 1.433 Treatments 20 149.82** 308.47** 9489.80** 53.81** 2712.34** 462.73** 5.782** 0.33** 1.041** 2.92** 39.103** 1.23** 40.46** Error 40 29.04 9.12 248.37 1.78 81.37 16.07 0.054 0.004 0.016 0.01 3.195 0.04 1.86

Table 2. Analysis of variance for combining ability for thirteen characters in chickpeaMean Square Source D.F.

Plant height (cm)

Secondary branches

(no)

Pods (no)

100-seed

weight (g)


Seed yield (g)

Nodules (no)

Nodule weight

(g)

Nitrogen content

(%)

Lb content (mg/g)

Harvest index (%)

Root weight

(g)

Plant weight

(g)

gca effects 5 55.775* 67.66** 1907.06** 44.75** 466.78** 78.29** 4.40** 0.28** 0.72** 2.05** 19.07** 0.73** 21.20**sca effects 15 47.992 114.54** 3582.00** 9.001** 1049.89** 179.56** 1.10** 0.05** 0.22** 0.61** 11.02** 0.30** 10.91**Error 40 9.679 3.04 82.79 0.591 27.12 5.355 0.018 0.001 0.005 0.004 1.065 0.013 0.619


Table 3. Estimates of general combining ability effects and the mean performance (in parenthesis) of parents for thirteencharacters in chickpea

*, **Significant at P = 0.05 and 0.01, respectively

Parents Plant height (cm)

Secondary branches

(no)

Pods (no)

100-seed weight

(g)


Seed yield (g)

Nodules (no)

Nodule weight

(g)

Nitrogen content

(%)

Lb content (mg/g)

Harvest index (%)

Root weight

(g)

Plant weight

(g)

ICC 4918 -2.389** (62.00)

4.431** (17.66)

-3.500 (33.77)

-1.326** (18.10)

-3.983** (33.33)

-3.095** (6.00)

-0.89** (0.00)

-0.196** (0.00)

-0.388** (2.70)

-0.240 (0.00)

-2.357** (18.420)

-0.547** (1.471)

-1.786** (13.962)

ICC 4993 0.0972 (63.333)

0.086 (12.933)

-20.106** (55.667)

0.761** (17.400)

-2.842 (34.400)

-1.266 (7.100)

-0.843** (0.000)

-0.266** (0.000)

-0.353** (2.953)

-0.810** (0.000)

-1.338** (20.753)

0.041** (1.890)

-1.935** (13.176)

H 96-99 4.944** (80.333)

-0.209 (18.667)

24.023** (132.533

)

-1.214** (18.200)

6.646** (74.200)

2.109** (22.433)

-0.062 (19.233)

0.014 (1.027)

0.102** (3.268)

0.681 (2.413)

0.322 (30.283)

-0.028 (2.223)

1.277** (16.654)

HC-1 0.653 (73.333)

-2.743** (21.200)

5.673 (77.933)

-1.656** (19.033)

1.208 (64.667)

1.868** (25.367)

0.429** (15.000)

0.137** (0.903)

0.148** (3.466)

0.144 (2.118)

1.799** (41.070)

0.208** (2.129)

1.646** (14.902)

HC-2 -1.764 (52.667)

-3.415** (15.200)

-11.635** (74.733)

-1.068** (18.333)

-11.042** (40.333)

-3.664** (15.067)

0.936** (27.167)

0.112** (0.849)

0.358** (3.317)

-0.063 (2.518)

0.800** (37.623)

-0.013 (1.271)

-0.514** (12.847)

HC-3 -0.472 (65.333)

1.850** (18.667)

5.544 (92.800)

4.503** (32.933)

10.013** (99.667)

4.048** (33.367)

0.429** (23.333)

0.200** (1.065)

0.133** (3.361)

0.288 (2.565)

0.774** (33.547)

0.338** (2.191)

1.311** (14.097)

SE (gi) 1.004 0.562 2.936 0.248 1.680 0.746 0.043 0.012 0.023 0.020 0.333 0.038 0.254 SE (gi-gj) 1.555 0.871 4.549 0.384 2.604 1.157 0.067 0.019 0.036 0.031 0.516 0.059 0.393

Verma and Waldia : Diallel analysis in chickpea for nodulation and yield contributing traits 119

content, ‘HC-2’ showed high gca effects. An overall perusalof parental lines for general combining ability revealed thatthe high nodulating variety ‘HC-3’ was superior over rest ofthe chickpea parental lines for yield and component traits.The per se performance of parents was also highly correlatedto the estimates of gca effects thereby, simplifying theselection of the parents based on the per se performance. Sothese parents may be extensively used in hybridizationprogramme.

It is evident that ‘HC-3’, ‘H96-99’, ‘HC-1’ and ‘HC-2’were the best parents having high gca effect coupled withgood per se performance not only for seed yield per plant butalso for nodulation and yield components so these parentscan be exploited for the development of improved lines ofchickpea. The genotypes showing good general combiningability for particular components may be utilized in componentbreeding for effective improvement in particular components,ultimately seeking improvement in seed yield itself (Singh etal. 1983).

The sca effects of hybrids (Table 4) revealed that 8crosses viz., ‘ICC 4918’ × ‘ICC 4993’, ‘ICC 4918’ × ‘H96-99’,‘ICC 4918’ × ‘HC-1’, ‘ICC 4993’ × ‘H96-99’, ‘ICC 4993’ × ‘HC-2’, ‘ICC 4993’ × ‘HC-3’, ‘H96-99’ × ‘HC-1’ and ‘HC-1’ × ‘HC-2’exhibited positive significant sca effects for seed yield perplant. The cross combinations viz., ‘ICC 4993’ × ‘HC-3’ wasfound to be the best for seed yield per plant, biological yield,harvest index and plant weight; ‘ICC 4993’ × ‘H96-99’ forleghaemoglobin content and root weight, ‘ICC 4918’ × ‘ICC4993’ for 100-seed weight and nodule weight; ‘ICC 4918’ ×‘HC-3’ for number of secondary branches and number of pods;‘HC-1’ × ‘HC-2’ for plant height; ‘ICC 4918’ × ‘HC-1’ for numberof nodules and ‘ICC 4918’ × ‘H96-99’ for nitrogen content.Preponderance of non additive gene effects for yield and yieldcomponents offers a good scope for the exploitation of hybrid

vigour and therefore, heterosis breeding may be rewardingfor improving chickpea. But the practical production of hybridgram is not biologically feasible due to small size andcleistogamous nature of the flowers and strong hybridizationbarriers. In view of such problems, the possibility of derivingpurelines performing better than or as well as F1 hybrids inchickpea have been reported (Singh 1974). This suggest thata large proportion of non additive effects in self pollinatedcrops seems to be due to additive x additive effects and thatselection be deferred to later generations (Singh et al. 1992).

It may be inferred from sca effects that most of thesuperior cross combinations for seed yield and related traitsinvolved either both or atleast one parent with positive andsignificant gca effects which implies that additive x additiveor additive x dominance genetic interactions respectively, areoperating in the crosses studied. The high yield potential ofcross combinations with high × low gca effects were attributedto interactions between positive alleles from good generalcombiner and negative alleles from poor combiner (Dubey1975). These crosses would throw the desirable transgressivesegregants if additive genetic system is present in the goodcombiner and complementary epistatic effects in F1 acts in thesame direction to maximize the desirable plant attributes (Patilet al. 1987). Such cross combinations should be fully exploitedfor the isolation of higher yielding purelines. This is perhapsthe most rational breeding policy in pulse crops until hybridvarieties become a reality.

Thus, the sca effect of a cross was reflected throughthe gca of its parents which demands inclusion of atleast onegood combining parent in producing superior hybrids.However, a few of the superior crosses involved both of theparents with poor combining abilities. This suggests that highsca effect of any cross combination does not necessarilydepend on the gca effects of the parental lines involved. This

Table 4. Estimates of specific combining ability effects for thirteen characters in chickpea

*,**Significant at P=0.05 and 0.01, respectively

F1s Plant height (cm)

Secondary branches

(no)

Pods (no)

100-seed weight

(g)


Seed yield (g)

Nodules (no)

Nodule weight

(g)

Nitrogen content

(%)

Lb content (mg/g)

Harvest index (%)

Root weight

(g)

Plant weight

(g) ICC 4918 × ICC 4993 -0.179 10.184** -35.839** 4.621** 26.020** 6.781** 0.805** 0.813** 0.301** 0.929** 2.134** -0.386** -3.939** ICC 4918 × H96-99 -7.762 9.016** 12.132 -1.038 23.199** 13.672** 0.928** -0.022** 0.657** 0.397** 4.892** -0.609** -0.093 ICC 4918 × HC-1 1.530 -3.984** 90.549** -0.829 26.970** 14.814** 1.129** 0.250** -0.063 0.687** 4.034** -0.008 1.628** ICC 4918 × HC-2 6.280** 3.241** 2.790 -1.650** 4.987 -2.088 0.345** 0.399** 0.128** -0.226** -2.281** 0.462** 0.957 ICC 4918 × HC-3 -3.012 19.199** 112.978** -3.854** 15.166** 0.733 0.288** 0.004 -0.344** 0.686** -0.655 -0.228** -1.926** ICC 4993 × H96-99 2.821 2.760 47.938** 1.542** 27.858** 10.210** 0.292** -0.134** -0.799** 1.176** 2.018** 0.650** 0.358 ICC 4993 × HC-1 -12.887** -0.173 -12.512 -2.717** -20.505** -10.815** 1.050** 0.161** -0.538** -0.045 -2.520** -0.051 -2.221** ICC 4993 × HC-2 5.863** 2.699 28.996** 0.196 17.545** 5.783** 1.008** 0.038 0.386** -0.728** 0.992 -0.101 -3.213** ICC 4993 × HC-3 4.238 14.267** 43.817** 3.358** 47.858** 27.071** 0.531** 0.287** 0.618** -1.138** 6.292** 0.633** 6.617** H96-99 × HC-1 -10.470** 4.656** 49.359** -0.475 16.008** 3.943** -0.543** -0.080** 0.554** -0.073 -1.511 -0.100 3.095** H96-99 × HC-2 2.613 2.595 -3.466 0.871 8.658 1.742 -0.910** -0.116** 0.251** 0.087 -1.353 0.069 0.239 H96-99 × HC-3 2.321 -1.937 -10.779 -3.400** -18.596** -7.704** -0.427** -0.048 -0.518** -0.255** -1.126 -0.207** -0.105 HC-1 × HC-2 8.571** 5.128** 44.350** 0.846 39.829** 13.750** 0.955** 0.005 -0.113 -0.972** -0.906 0.648** 3.888** HC-1 × HC-3 -0.387 -3.737** -40.762** -2.758** -7.859 -6.663** -0.277** 0.004 -0.142** 0.178** -3.226** 0.445** 2.083** HC-2 × HC-3 -5.304** -2.465 -4.521 -2.446** -16.909** -5.684** 0.310** 0.022 0.368** -0.014 -0.525 0.688** 2.073** SE (Sij) 2.694 1.510 7.879 0.666 4.510 2.004 0.116 0.033 0.063 0.055 0.893 0.102 0.681 SE (Sij-Sjk) 4.1156 2.306 12.036 1.017 6.889 3.061 0.178 0.050 0.096 0.084 1.365 0.156 1.041 SE (Sij-Skl) 3.8103 12.135 11.143 0.942 6.378 2.834 0.165 0.047 0.089 0.077 1.264 0.144 0.964


superiority of sca effects may be due to complementary typeof gene action or involvement of non allelic interaction offixable and non fixable genetic variance (Sharma and Mani2001).

Thus, the hybrid combinations ‘ICC 4993’ × ‘HC-3’, ‘ICC4918’ × ‘HC-3’, ‘ICC 4993’ × ‘H 96-99’ and ‘HC-1’ × ‘HC-2’ withhigh means, with favourable sca estimates and involvingatleast one of the parents with high gca would tend to increaseconcentration of favourable alleles, a situation of great interestfor breeding. These could be expected to yield transgressiveand stable performing segregants possessing enhancedyielding ability.

The results of the present investigation revealed theimportance of both additive and non additive genetic effectsfor the different characters. Under such a situation where bothadditive and non additive genetic variances are importantfactors of inheritance, maximum grain production may beattainable with a system that can exploit both additive andnon additive genetic effects simultaneously. Therefore, in suchcases, it is advisable to practice biparental mating in F2 amongselected crosses by way of intermating the most desirablesegregants alternately with selection to isolate superiorgenotypes or use of recurrent selection scheme (diallelselective mating system) to enhance the frequency ofdesirable recombinants with high yield potential (Joshi 1979,Nagaraj et al. 2002). This will help in building the populationfrom which desirable purelines could be developedsimultaneously. Linkage is another factor that complicatesthe problem in selection. If linkages are predominantly of therepulsion type, a generation of intercrossing to increase theopportunity of recombination may become important (Singhet al. 1992). It can also be concluded from the data thatgenetically diverse and high combining parents should beused in formulating cross combinations. Selection by progenytesting as well as recurrent selection can then be used toevolve lines which may transgress both the combining parents.

ACKNOWLEDGEMENT

The first author gratefully acknowledges Indian Councilof Agricultural Research (ICAR) for providing her financialassistance in terms of Senior Research Fellowship during theperiod of the study.

REFERENCES

Bajaj RK, Sandhu TS and Sra SS. 1984. Regressions, correlations andcombining ability of some quantitative characters in chickpea.Journal of Research-Punjab Agricultural University 21: 155-158.

Bhaduoria P, Chaturvedi SK, Awasthi NNC and Bhaduoria P. 2002.Gene action for grain yield and agronomic characters in chickpea(Cicer arietinum L.). Progressive Agriculture 2: 34-37.

Bhardwaj R, Sandhu JS and Gupta SK. 2009. Gene action and combiningability estimates for yield and other quantitative traits in chickpea(Cicer arietinum). Indian Journal of Agricultural Sciences 79: 897-900.

Bremer JM. 1960. Determination of nitrogen in soil by Kjeldahl method.Journal of Agricultural Science 55: 11-13.

Chander S, Ram D, Ram K, Chander S, Dhari R and Kumar R. 2001.Variation in selected recombinant inbred lines of two crosses inchickpea (Cicer arietinum L.). Annals of Biology 17: 29-34.

Chaturvedi SK, Mishra DK, Vyas P and Mishra N. 2009. Breeding forcold tolerance in chickpea. Trends in Biosciences 2: 1-6.

Dubey RS. 1975. Combining ability in cigarfilter tobacco. IndianJournal of Genetics and Plant Breeding 35: 76-92.

Gowda CLL and Bahl PN. 1978. Combining ability in chickpea. IndianJournal of Genetics and Plant Breeding 38: 245-251.

Griffing B. 1956. A generalized treatment of the use of diallel crosses inquantitative inheritance. Heredity 10: 31-34.

Hartree EF. 1955. Heamatin compounds. In: K Paech and MV Tracy(Eds.), Springer-Verlag, Berlin. Pp. 197-211.

Jahagirdar J E, Patil RA, Ghodke MK and Kardile KR. 1994. Combiningability studies in chickpea. Indian Journal of Pulses Research 7: 21-24.

Jha SK, Jaiswal HK and Saha AK. 1997. Genetic analysis of somequantitative characters in chickpea (Cicer arietinum L.). Annals ofAgricultural Research 18: 420-426.

Jinks JL and Hayman BI. 1953. The analysis of diallel crosses ofNicotiana rustica varieties. Maize Genetics Newsletter 27: 48-54.

Joshi AB. 1979. Breeding methodology for autogamous crops. IndianJournal of Genetics and Plant Breeding 39: 567-578.

Kumari V. 1999. Genetics of yield and its component characters ingrasspea (Lathyrus sativus L.). Annals of Agricultural Research 20:73-76.

Muhammad A, Bakhsh A, Zubair M and Abdul G. 2003. Genetic variabilityand correlation studies in chickpea (Cicer arietinum L.) PakistanJournal of Botany 35: 605-611.

Nagaraj K, Salimath PM and Kajjidoni ST. 2002. Genetic variabilitycreated through biparental mating in chickpea (Cicer arietinum L.).Indian Journal of Genetics and Plant Breeding 62 (2): 259-260.

Patil JA, Pathak AR, Zaveri PP and Shah RN. 1987. Combining abilityanalysis in pigeon pea (Cajanus cajan L.). Indian Journal of Geneticsand Plant Breeding. 47: 183-187.

Patil JV, Kulkarni SS and Gawande VL. 2006. Genetics of quantitativecharacters in chickpea (Cicer arietinum L.) New Botanist-International Journal of Plant Science Research 33: 1-4.

Singh KB. 1974. Exploitation of heterosis in pulse crops. Indian Journalof Genetics and Plant Breeding 34A: 731-808.

Singh O, Gowda CLL, Sethi SC, Dasgupta T and Smithson JB. 1992.Genetic analysis of agronomic characters in chickpea. Theoreticaland Applied Genetics 83: 956-962.

Sharma RK and Mani SC. 2001. Combining ability studies for grainyield and other associated characters in Basmati Rice (Oryza sativaL.). Crop Improvement 28: 236-243.

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ABSTRACT

In order to find out the best combination of finger millet +Frenchbean intercropping system and nutrient managementpractices under rainfed conditions, an experiment was laid outin spilt plot design with three replications during 2007 and2008 with various intercropping combinations in main plot andfertilizer levels in sub plot. Among the intercropping systems,finger millet + Frenchbean (3:1) gave significantly highestgrain (21.61 and 27.30 q/ha during 2007 and 2008, respectively)than the sole crop of finger millet (16.85 and 17.77 q/ha during2007 and 2008, respectively). Among the treatments tried,application of recommended dose of NPK gave significantlyhigher grain yields (21.59 and 22.46 during 2007 and 2008,respectively) followed by Vermicompost + wild apricot cake(50% N from each source) + seed inoculation (20.63 and 21.28q/ha during 2007 and 2008, respectively) which was at par withrecommended dose of NPK. NMR and B: C ratio was also higherwith finger millet + Frenchbean (3:1) intercropping. The studysuggested that introducing a new crop like Frenchbean asintercrop with finger millet along with vermicompost + wildapricot cake (50% N from each source) + seed inoculation canincrease the production of finger millet + Frenchbeanintercropping and it will also improve the socio-economiccondition of the farmers as Frenchbean is used as a cash cropin the mid hills of North-West Himalaya.

Key words: Finger millet, Frenchbean, Intercropping, Yield

Poor yields and uncertainty of production are twinproblems of rainfed areas. The research has clearly indicatedthat there still exist a lot of potential to enhance the productivityin rainfed areas which can be exploited by adopting suitableagronomic and resource management practices. Selectingsuitable cropping system like intercropping will not only helpin increasing production of crop but also increase cropintensity. Intercropping is a potential agronomic system formaximizing crop production on dry lands over space and timein subsistence farming situations besides effective utilizationof natural resources (Willey 1979). Intercropping also minimizesrisk of crop failure and improves crop production in rainfedareas. In Uttarakhand hills, finger millet (Eleusine coracanaGaertn) is one of the important crops under rainfed farmingand Frenchbean (Phaseolus vulgaris L.) is also an importantkharif vegetable grown for its tender pods and has greatpotential among other traditional crops of the region. However,the average productivity of finger millet (12 q/ha) andFrenchbean (10 q/ha) is quite low due to low soil fertility status

and imbalanced use of fertilizers. The risk of crop failure isvery high in this region because of purely rainfed cultivation.To overcome with these problems the cereal - legumeintercropping systems is the right option to take full utilizationof resources of this area and to minimize the risk of crop failure.So, the inclusion of Frenchbean as intercropping with fingermillet may change the economics of the cropping sequenceand meet out the need of the household with saleable surplus.In this region, wild apricot is found abundantly and its cake isa rich source of nutrients (2-2.5% N, 1.2-1.3% P2O5, 1.5-1.8%K2O, 0.8-1.07% S) which can be used as a good source oforganic manure. Therefore, it was considered important toevaluate the productivity of finger millet based intercroppingwith Frenchbean and its nutrient management under rainfedconditions of Uttarakhand.


The field experiment was conducted at GBPUAT, HillCampus, Ranichauri, Tehri Garhwal, during kharif 2007 and2008 under rainfed conditions. The soil of experimental areawas silty clay loam in texture with pH of 5.8, available N 215kg/ha, available P 12.6 kg/ha and 421 kg/ha of available K. Thetreatment combinations comprised various finger millet +Frenchbean intercropping row ratio viz. finger millet sole crop,Frenchbean sole crop, finger millet + Frenchbean (1:1), fingermillet + Frenchbean (2:1), finger millet + Frenchbean (3:1) andfarmers practice assigned to main plots and fertilizermanagement viz., recommended dose of inorganic fertilizer(40:20:20), FYM 7.5 t/ ha, vermicompost + wild apricot cake(50% N from each source) + seed inoculation in sub plot, weretaken in spilt plot design with three replications. Finger milletvariety ‘PRM 1’ and Frenchbean ‘Contender’ was taken forthe evaluation. The sowing of finger millet was done at plantgeometry of 20 × 10 cm and Frenchbean was sown in thereplacement series as per treatment. Entire quantity ofphosphorus and potassium was applied uniformly to all theplots, whereas nitrogen was given as per treatments separatelyto both the crops. The top dressing of N in finger millet andintercropping was given at the close proximity line ofrespective crop. The system-wise finger millet yieldequivalents were calculated based on market price of produce(Rs. 7.0/kg for finger millet and Rs. 20/kg for Frenchbean).LER was calculated by taking into consideration the yield ofboth crops. The profitability in terms of net return with benefit:cost ratio was calculated for various crop sequence row ratio

Production potential of finger millet and Frenchbean intercropping under rainfedconditions of UttarakhandRASHMI YADAV

G.B. Pant University of Agriculture & Technology, Hill Campus, Ranichauri, Tehri Garhwal 249 199,Uttarakhand, India; Email: [email protected](Received: January, 2010; Accepted: July, 2010)


using prevailing market rates for various commodities.


Grain yield: Amongst the intercropping systems, statisticallyhigher grain yield was noted in 3:1 row ratio (Table 1). Theyield of Frenchbean was greatest in sole stand than intercrop.Within intercropping treatments, finger millet + Frenchbean(3:1) gave significantly highest finger millet grain equivalentyield (2161 and 2730 kg/ha during 2007 and 2008, respectively)than the sole crop of finger millet (1685 and 1777 kg/ha during2007 and 2008, respectively). Nutrient managementsignificantly influenced the grain yield of crop and theapplication of recommended dose of NPK gave significantlyhigher grain equivalent yields (2159 and 2246 kg/ha during2007 and 2008, respectively) followed by vermicompost + wildapricot cake (50% N from each source) + seed inoculation(20.63 and 21.28 q/ha during 2007 and 2008, respectively) whichwas statistically on par when the crop received 100% of therecommended dose of nutrients (Table 1). Pooled mean of

2007 and 2008 indicated that finger millet + Frenchbean in 3:1row ratio fertilized with 100% of the recommended dose ofnutrients produced the highest grain yield and it wasstatistically at par with the yield received under finger millet +Frenchbean in 3:1 row ratio receiving vermicompost + wildapricot cake + seed inoculation.Land equivalent ratio and monetary returns: On overall meanbasis of 2 years, intercropping of finger millet with Frenchbeanincreased the land equivalent ratio (LER) as compared to solecrops in the row ratio of 2:1and 3:1. The highest LER wasrecorded in intercropping of finger millet with Frenchbean at3:1 row ratio. This indicated greater biological efficiency ofintercropping treatments (Table 2).

The economic feasibility of the systems was tested asnet returns obtained. The net return/ha and B: C ratio werehighest with finger millet + Frenchbean (3:1) intercropping.This could be attributed to the yield recovery, land equivalentratio achieved with the treatment.

Table 1. Grain yield as influenced by various intercropping combinations and nutrient management options under rainfedconditions

Grain Yield (kg/ha) 2007 2008

Treatments Finger millet Frenchbean

Finger millet equivalent

yield

Finger millet Frenchbean Finger millet

equivalent yield

Mean finger millet equivalent

(kg/ha)

Crops Finger millet 1685 - 1685 1777 - 1777 1732 Frenchbean - 731 2090 - 767 2191 2142 Finger millet + frenchbean (1:1) 664 379 1744 687 440 1945 1845 Finger millet + frenchbean (2:1) 954 291 1785 1106 460 2421 2103 Finger millet + frenchbean (3:1) 1484 237 2161 1699 361 2730 2446 Farmer’s practice 1297 185 1825 1317 249 2028 1877 CD (5%) 352 133 347 281 238 556 465 Fertilizer Levels (kg/ha) Inorganic fertilizer 1337 439 2159 1380 553 2246 2201 Vermicompost + wild apricot cake (50% N from each) +seed inoculation 1173 372 2063 1300 421 2128 2096

FYM 7.5 t/ ha 1020 284 1525 1064 311 1857 1691 CD (5%) 51 36 129 84 60 191 170

Table 2. Land equivalent ratio (LER) and net returns as affected by various intercropping combinations (pooled over 2 years)Land equivalent ratio Net monetary returns ( Rs/ha) B-C Ratio Treatments

2007 2008 Mean 2007 2008 Mean 2007 2008 Mean Crops Finger millet 1.00 1.00 1.00 6594 7988 7291 1.48 1.58 1.53 Frenchbean 1.00 1.00 1.00 4975 6413 5694 1.36 1.47 1.42 Finger millet + frenchbean (1:1) 0.91 0.96 0.94 3701 5856 4779 1.27 1.42 1.35 Finger millet + frenchbean (2:1) 0.97 1.21 1.09 4559 9761 7160 1.33 1.71 1.55 Finger millet + frenchbean (3:1) 1.20 1.43 1.32 8406 13142 10774 1.61 1.95 1.78 Farmer’s practice 1.02 1.08 1.05 3928 8899 6414 1.29 1.65 1.47 CD (5%) 825 808 815 0.29 0.35 0.34 Fertilizer Levels (kg/ha) Inorganic fertilizer 1.39 1.50 1.45 8439 9798 9119 1.61 1.71 1.66 Vermicompost + wild apricot cake (50% N from each source) + seed inoculation 1.20 1.28 1.24 7194 9599 8397 1.52 1.69 1.61

FYM 7.5 t/ ha 1.00 0.99 0.99 4328 5698 5013 1.31 1.41 1.36 CD (5%) 431.2 433.9 432.55 0.26 0.31 0.29

Yadav: Production potential of finger millet and Frenchbean intercropping 123

Nutrient uptake: From the data it is revealed that the nutrientstatus of soil improved with the introduction of Frenchbeanwith finger millet as compared to sole crop (Table 3). Availablenitrogen content was significantly higher with sole crop ofFrenchbean; however, it was at par with finger millet +Frenchbean (3:1) than rest of the treatments. The availablenutrients content were significantly higher with the applicationof recommended dose of NPK followed by vermicompost +

wild apricot cake (50% N from each source) + seed inoculationbut they were statistically on par when the crop received 100%of the recommended dose of nutrients. Available phosphorusand potassium content of soil also showed similar trends.

This corroborates the findings of Gautam (1989) andShashidhara et al. (2000) who reported that the low yieldingcrop like small millets can be replaced by intercropping ofmillets with soybean to increase the crop profitability.

It can be concluded that introduction of crop likeFrenchbean as intercrop with Finger millet at 3:1 row ratiowith vermicompost + wild apricot cake (50% N from eachsource) + seed inoculation can increase the production offinger millet and affect the nutrient status of soil. It will alsoimprove the socio-economic condition of the farmers asFrenchbean is used as a cash crop under rainfed conditionsof Uttarakhand.

REFERENCES

Gautam HC. 1989. Potential area under soybean during kharif in India-an overview. Agricultural Situation in India 40: 821-824.

Shashidhara GB, Basavaraja R and Nadagouda VB . 2000. Studies onpegionpea intercropping system, in small millet under shallow redsoil. Karnataka Journal of Agricultural Sciences 13: 7-10.

Willey RN .1979. Intercropping- its importance and research needs.Part I. Competition and yield advantages. Field Crops Abstracts 32:1-10

Table 3. N uptake and nutrient status of soil as affected byvarious intercropping combinations (2 years pooleddata)

Soil available nutrients (kg/ha)

Treatments N Uptake (kg/ha) N P K

Crops Finger millet 213.2 305.6 18.0 325 Frenchbean 221.7 346.6 25.1 355 Finger millet + frenchbean (1:1) 214.9 320.4 20.9 345 Finger millet + frenchbean (2:1) 218.1 338.0 23.0 352 Finger millet + frenchbean (3:1) 219.9 346.2 24.0 356 Farmer’s practice 215.0 322.4 20.6 346 CD (5%) 3.5 7.8 0.10 5.1 Fertilizer Levels (kg/ha) Inorganic fertilizer 215.6 350.0 31.0 370 Vermicompost + wild apricot cake (50% N from each) +seed inoculation

212.2 346.1 29.0 367

FYM 7.5 t/ ha 204.6 340.2 25.0 350 CD (P=0.05) 4.6 8.0 4.1 4.0


ABSTRACT

In view of the cost effectiveness and eco-friendly characteristicsof the panchgavya, a field experiment was conducted on thehigh pH soils of arid zone of India to examine the effect of soilapplied panchgavya and foliar applied plant leaf extracts onthe growth yield of groundnut (Arachis hypogaea L.) duringkharif 2006 and 2007 at Jaisalmer. The results of the experimentrevealed that successive increase in panchgavya solution from0 to 3.0 l/m2 recorded significant increase in growth and yieldof groundnut. The pod, haulm and biological yield were 85, 93and 90 % higher than control with soil application of panchgavyasolution at 3.0 l/m2. The improvement in dry matteraccumulation and physiological growth in terms of SLW, CGR,RGR and NAR were recorded significantly higher with soilapplication of panchgavya at 2.0 l/m2. Foliar application of neem(Azadirachta indica), datura (Datura metel) and tumba (Citrulluscolocynthis) plant leaf extracts in combination with panchgavyain 1: 1 ratio at 35 and 55 days after application recorded highergrowth and yield compared to water sprayed control. The CGR,RGR and NAR at 45-70 DAS and 70 DAS –harvest and pod,haulm and biological yields were however recordedsignificantly maximum with foliar application of datura +panchgavya solution among sources of foliar application.

Key words: Growth, Groundnut, Leaf extract, Panchgavya, Yield

Groundnut (Arachis hypogaea L.) is an importantoilseed crop in India. India is the second largest producer ofgroundnut accounting for 38% of the total area (7.7 millionha) and 31% production (6.7 m t) of the world (Chandrasekaranet al. 2007) in groundnut production. India has immensepotential for exporting large seeded groundnut; however, lackof production technologies exclusive for organically producedgroundnut has restricted the scope for exports. In the existingtechnologies of organic farming where farm yard manure andcompost are being used as sources of nutrient supply,productivity of soils falls during the transitory period (untilfertility, structure and microbial activity of the soil had beenrestored) leading to low yield levels in initial years of cultivation(Natarajan 2002). Thus, it is imperative to develop technologiesthat sustain yield levels of all crops during the transitory periodfrom the very first year. Role of panchgavya in production ofmany plantation crops grown over wide agroclimatic conditionshas been well documented in India There are reports indicatedthat efficacy of panchgavya solution enhanced manifold withthe mixing of endemic plant leaves (Selvraj 2006). The endemicplants such as tumba (Citrullus colocynthis) and datura

Growth and yield of groundnut in relation to soil application of panchgavya andfoliar spray of endogenous plant leaf extractsR.N. KUMAWAT*, S.S. MAHAJAN1 and R.S. MERTIA

*Regional Research Station, CAZRI, Jaisalmer-345001, Rajasthan, India; 1Central Arid Zone ResearchInstitute, Jodhpur-342 003, Rajasthan, India; E-mail: [email protected](Received: April, 2010; Accepted: September, 2010)

(Datura metel) grow naturally on the waste lands of IndianThar desert producing lot of biomass of no values. Thus,these vegetations could serve as resource for supplying plantnutrients in agriculture. However, information on use ofpanchgavya in combination with leaf extracts of endemic plantson groundnut is very meager. In view of the aboveconsiderations, present study was conducted to examine theeffect of soil applied panchgavya and foliar applied plant leafextracts in combination with panchgavya on the growth andyield of groundnut in the desertic areas under irrigatedconditions.


The experiment was conducted at Central Arid ZoneResearch Institute, Regional Research Station, Jaisalmer,Rajasthan during kharif 2006 and 2007 under irrigatedcondition. The sandy soils of the experimental field was shallowin depth (30 cm) having 0.08% organic carbon, 72.80 kg/haavailable N, 6.45 kg/ha available P, 215.78 kg/ha available K,6.92 kg/ha available S and 7.55% free CaCO3 with pH 9.2. Theexperiment was laid out in a split-plot-design with four levelsof soil applied panchgavya (0, 1.0, 2.0 and 3.0 l/m2) in mainplots and four levels of foliar applied sources (control, neem,datura and tumba) in sub plots with three replications. Thecontrol was run with tape water. Panchgavya was preparedby thorough mixing of fresh cow dung (7.0 kg), cow ghee (1.0kg), fresh cow urine (10.0 l), cow milk (3.0 l) and cow milk curd(2.0 l) followed by fermentation for 20 days in an open plasticdrum. The leaf extracts of neem (Azadirachta indica), datura(Datura metal) and tumba (Citrullus colocynthis) wereprepared by mixing fresh ground leaves with cow urine in 1:1ratio followed by fermentation. After a pre-sowing irrigation,the groundnut cultivar ‘MA-10’ was sown in the second weekof July in both the years. The seeds were treated withTrichoderma viridae (6 g/kg seed) as prophylactic measureagainst seed borne diseases. Sowing was done in rows spacedat 45 cm apart using a seed rate of 80 kg/ha. Thinning wasdone at 10 days after sowing (DAS) in order to maintain plantto plant distance of 25 cm. The fermented panchgavya solutionwas diluted 15 times with water and applied near the groundnutplants in soil just after second irrigation at 25 DAS as per thetreatments. The filtrates of leaf extracts were mixed with thefiltered panchgavya solution in 1:1 ratio and diluted 30 timeswith water for foliar application. The foliar application of thesources was done twice on the groundnut leaves at 35 and 55

Kumawat et al.: Effect of panchgavya and plant leaf extracts on groundnut 125

DAS as per treatments. Five plants in each treatment wereuprooted manually for analysis of growth. The plants of thesample were separated into its component plant parts – leaves,stems and pods- and leaf area was measured using theplanimeter method (Milthorpe 1956). Dry weights of plant partswere obtained after oven drying at 70o C for 72 hours, todetermine shoot dry matter and its distributions. The leaf areaindex (LAI), specific leaf weight (SLW), crop growth rate (CGR),relative growth rate (RGR) and net assimilation rate (NAR)were calculated using formula as given in the literature(Gardner et al. 1995). Biological yield and pod yield wascomputed from the plants harvested from net plots in eachtreatment.


Effect of panchgavya: The mean results of the two kharifseasons on dry matter partitioning are presented in Table 2.Contribution of leaf and stem towards total plant dry matterproduction decreased with the progress in growth. At 45 DAS,leaf and stem contributed 43 and 57 % in the total plant drymatter which remained only 22 and 35 % at harvest. Theincrease in total plant dry matter production at 70 DAScoincided the pod formation stage in the groundnut. Thecontribution of pods in the total plant dry matter increasedfrom 31 % at 70 DAS to 43 % at harvest. Dry matter

accumulation in leaf, stem, pods as well as plant increasedlinearly with the successive increase in soil appliedpanchgavya from 0 to 3.0 l/m2 at all the phenophases, highestbeing with 3.0 l/m2. The physiological parameters viz., perplant leaflets and leaf area, LAI, SLW, CGR, RGR and NARwere influenced by panchgavya levels. The number of leaflets,leaf area and LAI per plant increased significantly withsuccessive increase in panchgavya levels up to 3.0 l/m2 (Table3) while SLW, CGR, RGR, and NAR at all the observed stagesrecorded significantly maximum with 2.0 l/m2 of panchgavya(Table 4). The biological, haulm and pod yields per hectarealso responded positively to the increased levels ofpanchgavya. Soil application of panchgavya at 3.0 l/m2

recorded 85, 93 and 90 per cent higher pod, haulm andbiological yield compared to control (Figure 1).

The increase in the dry matter accumulation in the study

Table 1. Chemical properties of finally filtered and undilutedpanchgavya and foliar sources

Sources Organic carbon

(%)

pH Electrical conductivity

(dS/m)

Nitrogen (%)

Phosphorus (%)

Panchgavya 1.50 4.35 19.36 0.58 0.90 Neem 1.90 4.39 33.70 1.05 0.78 Tumba 1.60 5.42 34.90 0.83 0.39 Datura 1.67 4.00 34.20 0.86 0.76

Fig 1. Effect of soil applied panchgavya on yield of groundnut(kg/ ha), mean of kharif 2006 and 2007 (S0 = control(panchgavya), S1 = soil application of [email protected] l/m2, S2 = soil application of panchgavya @2.0 l/m2 and S3 = soil application of panchgavya @3.0 l/m2.)

Table 2. Effect of soil applied panchgavya and foliar applied leaf extracts on the dry matter accumulation of groundnut at differentgrowth stages (mean of kharif 2006 and 2007)

S0= control (panchgavya), S1= soil application of panchgavya @ 1.0 l/m2, S2= soil application of panchgavya @ 2.0 l/m2 and S3= soil applicationof panchgavya @ 3.0 l/m2

Plant dry matter at 45 DAS (g/plant)

Plant dry matter at 70 DAS (g/plant)

Plant dry matter at harvest (g/plant)

Treatments

Stem Leaf Plant Stem Leaf Pod Plant Stem Leaf Pod Plant Soil application of panchgavya (l/m2) S0 1.99 2.82 4.81 4.40 5.99 4.44 14.82 7.30 10.76 14.92 32.98 S1.0 2.43 3.32 5.75 5.90 7.37 5.22 18.50 10.90 16.44 17.26 44.60 S2.0 2.92 3.76 6.68 7.09 9.34 8.02 24.45 12.67 20.49 26.40 59.56 S3.0 3.39 4.25 7.65 8.26 10.01 8.27 26.54 13.17 21.72 27.82 62.71 SEm± 0.05 0.08 0.09 0.11 0.16 0.11 0.46 0.13 0.30 0.30 0.73 CD (P=0.05) 0.16 0.24 0.29 0.35 0.49 0.33 1.41 0.41 0.92 0.91 2.24 Foliar sources Control (Water spray) 2.45 3.04 5.49 5.83 6.68 5.11 17.63 9.14 14.98 17.09 41.21 Neem leaf extract + panchgavya 2.99 3.86 6.84 7.01 9.11 7.25 23.37 12.44 19.43 22.84 54.71 Datura leaf extract + panchgavya 2.68 3.68 6.36 6.52 8.61 6.92 22.05 11.38 17.72 25.03 54.13 Tumba leaf extract + panchgavya 2.62 3.58 6.20 6.28 8.32 6.67 21.26 11.09 17.27 21.43 49.79 SEm± 0.05 0.06 0.09 0.10 0.15 0.10 0.44 0.13 0.28 0.28 0.69 CD (P=0.05) 0.14 0.18 0.24 0.29 0.43 0.29 1.24 0.37 0.81 0.80 1.97


was attributed to improved availability of micronutrients, soilmicrobiology and reduction in soil pH and EC with the additionof panchgavya. The increased nutrient supply (added ornative) in turn enhanced rapid initiation of leaves and theirexpansion thereby giving higher leaf area, higher chlorophyllsynthesis and photosynthetic rate which ultimately reflectedby higher dry matter accumulation in the plant. Further,panchgavya application increases the population of provenbiofertilizers that play important role in the promotion of plantgrowth by secreting phytohormones, auxin, cytokinin andgiberrelic acid (Mahalingam and Sheela 2003). The bioactivesubstances secreted by beneficial microorganisms might havekept the opening of stomata for longer period (both underfavourable and unfavourable conditions) leading to increasedLAI (Xu et al. 2000). The reduction in soil pH with applicationof panchgavya owing to low pH of the medium (4.35) increasesthe solubility of the Ca (Freney et al. 1962) and P in rootrhizosphere, essentially required for the formation anddevelopment of the shell of the pods. Thus increased drymatter of pods per plant with increased levels of panchgavyawas evident. The improvement in number of leaflets and plantdry matter with application of panchgavya might have resultedinto increased LAI, SLW, CGR, RGR and NAR. The increaseddry matter and yield attributes thus contributed for higherpod and biological yield with panchgavya levels compared tocontrol. Selvaraj (2003) also observed 36 % increased yield offrenchbean with application of vermicompost + panchgavyadue to restoration of soil fertility with these sources.Effect of foliar applied sources: All the sources of foliarapplication recorded significantly higher accumulation of plantdry matter and its distribution compared to water sprayedcontrol at all the observed stages (Table 2). Foliar applicationof neem leaf extracts however had recorded significantly thehighest dry matter accumulation in leaf and stem over other

foliar treatments. Though pod dry matter during pod formationstage (70 DAS) was recorded highest with neem leaf extracts,it was recorded statistically superior with datura leaf extractsat harvest. The number of leaflets, leaf area and LAI per plantat all the stages of crop growth was recorded significantlyhigher with foliar application of neem leaf extract than theother sources of application (Table 3). However, it remained atpar with datura leaf extract in this regard during 45 and 70DAS. The foliar applied neem, datura and tumba being at parwith each other had statistically higher SLW than the controlat all the stages of crop growth (Table 4). The CGR, RGR andNAR were recorded significantly higher with foliar applicationof datura leaf extract followed by neem and tumba both at 45-70 DAS and 70 DAS –harvest (Table 4). Foliar application ofleaf extracts of neem and datura remained at par to each otherin this regard except at 70 DAS-harvest where datura leafextract recorded the highest RGR and NAR than other foliarsources. Though foliar application of neem leaf extract recorded

Table 3. Effect of soil applied panchgavya and foliar applied leaf extracts on the number of leaflets, leaf area and leaf area index(LAI) of ground nut at different growth stages (mean of kharif 2006 and 2007)


Number of leaflets/plant Leaf area/plant (cm2) Leaf area index Treatments 45 DAS 70 DAS Harvest 45 DAS 70 DAS Harvest 45 DAS 70 DAS Harvest

Soil application of panchgavya (l/m2) S0 171 295 471 1056 1291 1825 0.88 1.08 1.52 S1 187 336 668 1272 1521 2676 1.06 1.27 2.23 S2 228 387 758 1446 1880 3254 1.20 1.57 2.71 S3 237 405 787 1555 1997 3429 1.30 1.66 2.86 SEm± 3 5 9 26 30 40 0.02 0.02 0.03 CD (P=0.05) 8 15 29 80 91 123 0.07 0.07 0.10 Foliar sources Control (Water spray) 195 326 648 1181 1465 2588 0.98 1.22 2.16 Neem leaf extract + panchgavya 213 375 710 1427 1808 3035 1.19 1.51 2.53 Datura leaf extract + panchgavya 210 366 669 1387 1737 2817 1.16 1.45 2.35 Tumba leaf extract + panchgavya 204 357 657 1334 1678 2744 1.11 1.40 2.29 SEm± 3 5 11 25 28 41 0.02 0.02 0.03 CD (P=0.05) 7 13 30 72 79 115 0.06 0.06 0.10

Fig 2. Effect of foliar application of leaf-extracts pluspanchgavya on yield of groundnut (kg/ha) (mean ofkharif 2006 and 2007)

0

1000

2000

3000

4000

5000

Control (waterspray)

Neem leafextract +

panchgavya

Datura leafextract +

panchgavya

Tumba leafextract +

panchgavya

Foliar application of leaf extracts + panchgavya

Yie

ld (k

g/ha

)Pod yield (kg/ha) Haulm yield (kg/ha) Biological tield (kg/ha)

Kumawat et al.: Effect of panchgavya and plant leaf extracts on groundnut 127

statistically higher haulm yield, pod yield per hectare wasobserved significantly higher with datura leaf extract (Figure2). Foliar application of datura leaf extract recorded 22 and 21per cent higher pod and biological yields compared to watersprayed control.

The higher dry matter accumulation in plant and its partswith neem, datura and tumba leaf extract in the study wasattributed to higher chlorophyll content, nitrate reductaseactivity, root nodule weight and plant nutrients which in turnincreases the photosynthetic capacity of the plants. Thehigher chlorophyll content, nitrate reductase activity and rootnodule weight with these leaf extract might be due to supplyof more of plant nutrients to crop plants owing to higher Nand P content of the medium used in the study compared tocontrol (Table 1). Besides, sources of foliar application (neem,datura and tumba) have many beneficial microorganism thatmaintain the opening of stomata for longer period both inoptimum and adverse conditions during the crop growth whichled to increased leaf area index providing stronger source forsink (Xu et al. 2000). Increased pod intensity per plant withapplication of neem leaf extract has also been reported byOparaeke et al. (2001) in cowpea. The significant improvementin dry matter and photosynthetic source thus might haveincreased the physiological growth indices of the groundnutin the study compared to control. However, the role of daturain increasing growth and pod yield is not known and is apoint of further exploration.

The study suggested that soil application ofpanchgavya at 3.0 l/m2 and foliar application of datura leafextract at 35 and 55 DAS could be a best combination oftreatments to get maximum plant dry matter, growth and pod

yield of groundnut on the high pH calcareous soils of the aridwestern India.

REFERENCES

Chandrasekaran R, Somasundaram E, Mohamed MA, Thirukumaran Kand Sathyamoorthi K. 2007. Influence of Varieties and Plant Spacingon the Growth and Yield of Confectionery Groundnut (Arachishypogaea L.). Research Journal of Agricultural and BiologicalSciences 3: 525-528.

Freney JR, Barrow NJ and Spancer KA. 1962. A review of certainaspects of sulphur as a soil constituent and plant nutrient. Plant andSoil 17: 940-944.

Gardner FP, Pearce RB and Mitchell RL. 1995. Physiology of cropplants. Iowa State University Press.

Mahalingam PU and Sheela S. 2003. Production of plant growth regulatorsby Pseudomonas aeruginosa. In: abstracts of the UGC sponsoredstate level seminar on Indigenisation of India farming: Problemsand prospects held at Gandhigram Rural Institute, DeemedUniversity, Gandhigram, Tamil Nadu on 7-8 March 2003. 61pp.

Milthorpe FL. 1956. The growth of Leaves. Buttrworths ScientificPublication, London.

Natarajan K. 2002. Panchakavya-Amanual. Other India Press, Mapusa,Goa, India.

Oparaeke AM, Dike MC and Amatobi CI. 2001. Botanical pesticidemixtures for insect peat management on cowpea (Vigna unguiculataL). Journal of Sustainable Agriculture 29: 5-13.

Selvaraj N. 2003. Report on the work done on organic farming atHorticultural research station (Tamilnadu Agricultural University),Ooty. pp. 2-5.

Selvaraj N. 2006. Dasagavya: Organic growth promoter for plants. (In)The Hindu, pp. 18.

Xu HL, Wang XJ and Wang JH. 2000. Effect of microbial inoculationon stomatal response of maize leaves. Journal of Crop Production3: 235-243

Table 4. Effect of soil applied panchgavya and foliar applied leaf extracts on the specific leaf weight (SLW), crop growth rate(CGR), relative growth rate (RGR) and net assimilation rate (NAR) of groundnut at different growth stages (mean ofkharif 2006 and 2007)


SLW (mg/cm2) CGR (g/m2/day) RGR (mg/g/day) NAR (mg/cm2/day) Treatments 45

DAS 70

DAS Harvest 45-70

DAS 70 DAS- harvest

45-70 DAS

70 DAS-harvest

45-70 DAS

70 DAS-harvest

Soil application of panchgavya (l/m2) S0 2.67 4.64 5.89 3.34 3.03 83.12 24.47 0.342 0.235 S1 2.61 4.84 6.14 4.25 4.35 88.57 28.20 0.365 0.255 S2 2.60 4.96 6.29 5.93 5.85 106.25 28.65 0.429 0.280 S3 2.78 5.02 6.38 6.30 6.03 98.80 27.59 0.427 0.274 SEm± 0.04 0.05 0.06 0.14 0.06 2.19 0.38 0.007 0.003 CD (P=0.05) 0.13 0.15 0.18 0.43 0.19 6.75 1.16 0.022 0.008 Foliar sources Control (Water spray) 2.58 4.55 5.78 4.05 3.93 87.31 26.54 0.363 0.237 Neem leaf extract + panchgavya 2.70 5.03 6.38 5.51 5.22 96.29 26.63 0.407 0.262 Datura leaf extract + panchgavya 2.69 4.93 6.24 5.23 5.35 97.49 29.18 0.397 0.284 Tumba leaf extract + panchgavya 2.69 4.95 6.29 5.02 4.75 95.65 26.56 0.395 0.261 SEm± 0.04 0.05 0.06 0.13 0.06 1.75 0.38 0.006 0.002 CD (P=0.05) 0.12 0.14 0.17 0.37 0.18 4.96 1.08 0.018 0.006


ABSTRACT

A field experiment was conducted during 2003-04 and 2004-05on Typic Haplustept at Maharana Pratap University ofAgriculture and Technology, Udaipur to assess the effect of Papplication through different sources on yield and nutrientuptake by urdbean. Application of FYM @ 5 t/ha, 40 kg P2O5/haand dual seed inoculation with PSB + VAM significantlyincreased the seed and stover yield and uptake of N, P and K byurdbean. Combined effect of 5 t FYM/ha + 40 kg P2O5/ha, 5 tFYM/ha + dual inoculation with PSB + VAM, and 40 kg P2O5ha-1 + dual inoculation with PSB + VAM produced significantlyhigher yield and uptake of N, P and K by urdbean. Maximumnet returns (Rs. 31835) were obtained with 5 t FYM/ha + 40 kgP2O5/ha + dual inoculation with PSB + VAM followed by 5 tFYM/ha + 30 kg P2O5/ha + dual inoculation with PSB + VAM.

Key words: FYM, Net returns, Nutrient uptake, Phosphorus,PSB, Urdbean, VAM

Urdbean (Phaseolus mungo L.) is important pulse cropof India. It is cultivated mostly on marginal lands in mono/mixed cropping system without any fertilizers under rainfedconditions of southern Rajasthan. Its productivity is verylow as compared to yield potential. This wide gap is minimizedthrough the use of adequate and balanced fertilization.Phosphours is an important mineral element for grain legumesas it helps in root development, participates in synthesis ofphosphate and phosphoproteins and takes part in energyfixing and releasing process in plants. Significant response oflegumes to phosphate nutrition has been reported by severalworkers (Namdev and Gupta 1999, Singh and Yadav 2008).Most of the applied P gets fixed and only 10-18% is utilized bythe current crop (Subehia and Sharma 2002). Addition of FYMto these soils not only supplies the additional nutrients to thegrowing plants but also affects the availability of nativenutrients from soil and chemical fertilizers due to release oforganic acids and other microbial products during thedecomposition (Stevenson 1967). Production of organic acidsduring decomposition of FYM lowers the pH due to whichstable complexes with cations like Ca2+, Mg2+, Fe2+ and Al3+ ofgreater stability and releases water soluble phosphates. Dueto this chelating effect, the organic acid solublizes more Pthan inorganic acids at the same pH (Pattanayak et al. 2009).

Besides, FYM also maintains a congenial hydro-thermal regimefor optimum crop production. Biofertilizers enhance soilfertility and crop yield by solubilizing unavailable sources ofelemental nitrogen and bound phosphate into available formsin order to facilitate the plant to absorb them. Inoculants ofefficient phosphate solubilizing bacteria (PSB) and vasiculararbuscular mycorrhiza (VAM) which have established theircapability in augmenting the productivity of pulses may fulfilthe P needs considerably. Inoculation of phosphorussolubilizing micro-organism with legume crops has been foundto substitute around 20 per cent P requirement by Psolubilization (Singh et al. 1998). It is well known that vesiculararbuscular mycorrhizal (VAM) fungi improve plant growththrough increased availability of phosphorus by remobilizationof fixed phosphate under low fertility conditions (Taraftar andRao 2001). Their activity was better reflected under FYMapplication (Qureshi et al. 2005; Pattanayak et al. 2009). Thus,the present study was undertaken to study the effect of FYM,phosphorus and biofertilizers on yield and nutrient uptake(N, P and K) by urdbean under rainfed conditions of southernRajasthan.


The experiment was conducted during kharif season of2003-04 and 2004-05 at the instructional research farm ofRajasthan college of Agriculture, Udaipur. The experimentalsoil was clay loam in texture with pH 7.8 and EC2 1.18 (dSm-1)containing 0.76 per cent organic carbon, 268.4 kg available N/ha, 19.5 kg available P2O5/ha and 370.8 kg available K2O/ha.The phosphorus fixing capacity of these soils is very high(15.6 cmol/kg of soil). The experiment was laid out at the samesite during both the years in split plot design keeping FYMlevels (0 and 5 t/ha) and phosphorus levels (0, 20, 30 and 40 kgP2O5/ha) in main plot and biofertilizers (untreated control, PSB,VAM and PSB + VAM) in sub- plots. The treatments werereplicated three times. The FYM was incorporated 20 daysbefore sowing in the soil as per treatment. The recommendeddose of N (20 kg/ha) and phosphorus as per treatments wereapplied as basal. Nitrogen and phosphorus were given throughurea and diammonium phosphate. The seeds of urdbean wereinoculated with PSB (phosphorus megatherium var.phosphacticum) before sowing and VAM (Glomus

Integrated phosphorus management on yield and nutrient uptake of urdbean underrainfed conditions of southern RajasthanD.S. RATHORE, H.S. PUROHIT and B.L. YADAV*

Department of Agricultural Chemistry and Soil Science, Rajasthan College of Agriculture, Maharana PratapUniversity of Agriculture and Technology, Udaipur 313001, Rajasthan, India; Email: [email protected](Received: January, 2010; Accepted: August, 2010)

*Present address: Department of Agricultural Chemistry and Soil Science, S.K.N. College of Agriculture, Jobner, Jaipur 303 329,Rajasthan, India

Rathore et al.: Integrated phosphorus management on yield and nutrient uptake of urdbean 129

fasciculatum) was drilled below seed just before sowing asper treatments. Sowing of urdbean was done on July 5, 2003and July 6, 2004. The total rainfall received during the croppingseason was 465.7 mm and 569.6 mm in 2003 and 2004,respectively. The available phosphorus of soil after harvestof crop under all treatments varied from 18.40 to 23.86 kg P2O5/ha in the first year and 20.29 to 24.55 kg P2O5/ha in the secondyear of study. N, P and K contents in seed and stover wereanalysed as per standard methods and their uptakes wascalculated by multiplying their contents and respective yield.


Effect of FYM: Perusal of data (Table 1 and 2) revealed that

the application FYM @ 5 t/ha increased the seed and stoveryield and uptake of N, P and K by urdbean and could beattributed to the release of macro and micro nutrients duringthe course of microbial decomposition (Singh and Ram 1982).The increase in uptake of N, P and K due to application oforganic matter could be attributed to higher availability ofthese nutrients and increased utilization of native P (Shrikanthet al. 2000).Effect of Phosphorus: Application of phosphorus upto 40kg/ha increased the seed and stover yield and uptake of N, Pand K by urdbean (Table 1 and 2). Application of phosphorusimproved the nutrient availability in soil, resulting into greateruptake which might have increased the photosynthesis and

Table 1. Effect of FYM, phosphorus levels and biofertilizers on yield of urdbean (pooled over two years)No FYM 5 t FYM/ha

Phosphorus levels (kg P2O5/ha) Phosphorus levels (kg P2O5/ha) Treatments

0 20 30 40 Mean 0 20 30 40 Mean Seed yield (q/ha) Control 7.10 7.68 8.08 8.85 7.93 8.31 9.29 10.25 10.58 9.61 PSB 7.32 7.93 8.34 9.13 8.18 8.91 9.96 10.99 11.35 10.31 VAM 7.42 8.03 8.45 9.25 8.29 9.16 10.23 11.29 11.66 10.59 PSB + VAM 7.86 8.50 9.10 9.80 8.78 9.64 10.78 11.88 12.26 11.15 Mean 7.43 8.04 8.46 9.26 8.30 9.01 10.07 11.11 11.47 10.41 Stover yield ( q/ha) Control 13.23 14.54 15.39 17.14 15.01 15.46 17.61 19.51 20.14 18.18 PSB 13.64 14.99 15.86 17.67 15.47 16.60 18.91 20.95 21.63 19.52 VAM 13.83 15.20 16.09 17.92 15.69 17.04 19.41 21.50 22.20 20.04 PSB + VAM 14.68 16.13 17.07 19.01 16.65 17.98 20.48 22.68 23.42 21.14 Mean 13.85 15.22 16.11 17.94 15.71 16.77 19.10 21.16 21.85 19.72

FYM P BF FYM x P FYM x BF P x BF CD (P=0.05) Seed yield 0.138 0.195 0.179 0.276 0.253 0.358 Stover yield 0.264 0.374 0.343 0.529 0.485 0.686

Table 2. Effect of FYM and phosphorus levels and biofertilizers on N, P and k uptake by urdbean (Pooled over two years)Treatment No FYM 5 t FYM/ha

Phosphorus level (kg/ha) Phosphorus level (kg/ha) 0 20 30 40 Mean 0 20 30 40 Mean

N uptake (Kg/ha) Control 43.80 49.79 51.66 58.95 50.80 53.49 60.82 69.93 74.05 64.58 PSB 46.92 52.27 55.35 61.16 54.43 58.75 66.81 76.81 81.34 70.93 VAM 46.76 52.09 55.16 62.94 54.24 61.14 69.52 79.93 84.64 73.81 PSB + VAM 52.06 58.00 61.41 70.08 60.39 65.91 74.94 86.16 91.24 79.57 Mean 47.39 52.79 55.90 63.79 54.97 59.68 67.86 78.02 82.62 72.05 P uptake (kg/ha) Control 3.82 4.54 4.88 5.72 4.74 4.88 5.93 6.66 7.22 6.17 PSB 4.33 5.14 5.53 6.48 5.37 5.75 6.99 7.85 8.50 7.27 VAM 4.48 5.32 5.72 6.71 5.56 5.94 7.22 8.11 8.79 7.51 PSB + VAM 4.87 5.78 6.22 7.29 6.04 6.54 7.95 8.93 9.67 8.27 Mean 4.38 5.20 5.59 6.55 5.43 5.77 7.02 7.88 8.54 7.30 K uptake (kg/ha) Control 19.13 20.40 21.76 24.00 21.32 21.25 25.45 28.33 29.44 26.11 PSB 20.22 21.57 23.00 25.37 22.54 23.17 27.75 30.89 32.10 28.48 VAM 20.26 21.61 23.04 25.41 22.58 23.76 28.46 31.69 32.93 29.20 PSB + VAM 21.56 23.00 24.52 27.04 24.03 25.52 30.56 34.03 35.36 31.36 Mean 20.22 21.57 23.00 25.37 22.54 23.42 28.05 31.23 32.45 28.78

FYM P BF FYM x P FYM x BF P x BF CD (P=0.05) N uptake 1.01 1.42 1.41 2.01 2.00 2.83 P uptake 0.11 0.15 0.15 0.21 0.22 0.31 K uptake 0.54 0.77 0.64 0.21 0.90 1.27


translocation of assimilates to different parts of plants. Inlater stages, more assimilates are diverted to storagecompounds resulting into increased seed yield. Yadav andJakhar (2001) and Singh and Pareek (2003) also foundsignificant effect of phosphorus on yield and N, P and Kcontents in grain of mungbean.Effect of Biofertilizers: Seed inoculation with biofertilizersproved superior to untreated control with respect to yield andnutrients uptake (Table 1 and 2). Dual inoculation with PSBand VAM recorded highest values of all these parametersstudied and proved its superiority to untreated control, PSBor VAM alone. PSB and VAM solublizes native phosphorusbringing more phosphorus to soil solution. Thus, dualinoculation of PSB and VAM improved N (282.60 to 293.42 kg/ha), P (19.89 to 23.27 kg P2O5/ha) and K (344.40 to 352.61 kgK2O/ha) status of soil and ultimately increased N, P and Kuptake which enhanced growth and yield of crop. Similarresults were also reported by Singh and Pareek (2003).Interaction effect: Interaction effect of FYM and phosphoruson yield and nutrient uptake was found significant (Table 1and 2). In general, combined effect of 5 t/ha FYM and 40 kgP2O5/ha gave higher seed and stover yield and values of N, Pand K uptake by urdbean and this combination was foundsignificantly superior over other combinations. It may be dueto sufficient supply of nutrients by applied FYM and Pfertilizers (Rao et al. 1987). The results clearly indicated thatlegume cropping helped to increase the available nitrogen.This might be attributed to nitrogen fixation by legume crop(Rao 2003). Incorporation of FYM along with inorganic Pincreased the availability of P and this was attributed toreduction in fixation of water soluble P, increased mineralizationof organic P due to microbial action and enhanced availabilityof P (Varalakshmi et al. 2005).

In general, combined effect of 5 t FYM/ha + dualinoculation of PSB + VAM and 40 kg P2O5/ha + dual inoculationof PSB + VAM gave higher seed and stover yield as well asuptake of N, P and K by urdbean and these combinationswere found significantly superior over other combinations. Itmight be attributed to the response of urdbean to the effect of

nutrient management on account of balanced supply ofinorganic P fertilizers, FYM and biofertilizers. These resultsare in line with the findings of Anil Kumar et al. (2003) andSingh and Yadav (2008).Economics: The maximum net returns (Rs. 31835.3/ha) wasrecorded with 5 t FYM/ha + 40 kg P2O5/ha + dual inoculationof PSB + VAM combination followed by 5 t FYM/ha + 30 kgP2O5/ha + dual inoculation of PSB + VAM (Rs. 30105.3/ha)with B:C ratio of 3.88 and 3.75, respectively (Table 3).

This study indicated that application of FYM @ 5 t/ha+ 40 kg P2O5/ha along with dual inoculation of PSB + VAMwas not only improved the productivity of urdbean but alsogave maximum monitory benefits.

REFERENCES

Anil kumar BH, Sharanappa KT, Krishne Gowda and Sudhir K. 2003.Growth, yield and nutrient uptake as influenced by integrated nutrientmanagement in dryland finger millet. Mysore Journal of AgriculturalScience 37: 24-28.

Namdev SL and Gupta SC. 1999. Efficacy of biofertilizers with differentlevels of chemical fertilizer on pigeonpea. Crop Research 18: 19-23.

Pattanyak SK, Sureshkumar P and Tarafdar JC. 2009. New Vista inphosphorus research. Journal of the Indian Society of Soil Science57: 536-545.

Qureshi AA, Narayanasamy G, Chhonkar PK and Bala Sundram VR.2005. Direct and residual effect of phosphate rocks in presence ofP solubilizers and FYM on the available P, organic carbon andviable counts of P solubilizers in soils after soybean, mustard andwheat crops. Journal of the Indian Society of Soil Science 53: 97-100.

Rao SS. 2003. Nutrient balance and economics of integrated nutrientmanagement in groundnut (Arachis hypogaea L.) - mustard(Brassica juncea L.). Madras Agricultural Journal 90: 465-471.

Rao MR, Rego TJ and Wiley RW. 1987. Response of cereals to nitrogenin sole cropping and intercropping with different legumes. Plantand Soil 101: 167-177.

Shrikanth K, Shrinivasmurthy CA, Siddaramappa R andRamakrishnaparam. 2000. Direct and residual effect of enrichedcomposts, FYM, vermicompost and fertilizers on properties of anAlfisol. Journal of the Indian Society of Soil Science 48: 496-499.

Table 3. Effect of FYM, phosphorus levels and biofertilizers on monetary returns and B : C ratio of urdbean (mean of two years)No FYM 5 t FYM/ha

Phosphorus levels (kg P2O5/ha) Phosphorus levels (kg P2O5/ha) Treatments

0 20 30 40 0 20 30 40 Net returns (Rs/ha) No inoculation (control) 16668.6 18922.0 18817.7 19565.1 18784.8 22228.4 24222.9 24896.7 PSB 16956.0 18534.8 19565.0 21964.5 20198.3 24515.2 26706.3 27501.3 VAM 16924.9 18560.1 19900.2 22484.3 21303.7 25376.4 27250.7 27940.1 PSB + VAM 18086.9 19176.5 21554.6 25332.6 23272.1 23698.1 30105.3 31835.3 B : C ratio No inoculation (control) 2.72 2.93 2.84 2.89 2.54 2.88 3.08 3.10 PSB 2.75 2.86 2.95 3.23 2.73 3.17 3.38 3.42 VAM 2.70 2.81 2.94 3.25 2.83 3.23 3.40 3.42 PSB + VAM 2.87 2.90 3.18 3.65 3.08 3.01 3.75 3.88

Rathore et al.: Integrated phosphorus management on yield and nutrient uptake of urdbean 131

Singh B and Parrek RG. 2003. Effect of phosphorus and biofertilizerson growth and yield of mungbean. Indian Journal of Pulses Research16: 31-33.

Singh RS and Ram H. 1982. Effect of organic matter on thetransformation of inorganic phosphorus in soil science 30: 185-189.

Singh RS and Yadav MK. 2008. Effect of phosphorus and biofertilizerson growth, yield and nutrient uptake of long duration pigeonpeaunder rainfed condition. Journal of Food Legumes 21: 46-48.

Singh AK, Ram H and Maurya BR. 1998. Effect of nitrogen andphosphorus applciation on microbial population in inceptisols ofVaranasi Indian. Journal of Agricultural Chemistry 31: 90-94.

Stevenson FJ. 1967. Organic acids in soil. In: Soil Biochemistry Vol I(A.D. MacLaren and G.H. Perterson, Ed) Marcel Dekker New York.pp. 119.

Subehia SK and Sharma SP. 2002. Nutrient budgeting in a long-termfertilizers experiment. In transactions, 17 th world congress of soilscience held at Bangkok in Thailand from 14-21st August, 2002.33: 1-8.

Tarafdar JE and Rao AV. 2001. Response of clusterbean to Glomusmosseae and Rhizobium in an arid soil fertilized with nitrogen,phosphorus and FYM. Journal of the Indian Society of Soil Science49: 751-755.

Varalakshmi LR Srinivasmurthy CA and Bhaskar S. 2005. Effect ofintegrated use of organic manures and inorganic fertilizers on organiccarbon, available N, P and K in sustaining productivity of groundnut-fingernillet cropping system. Journal of the Indian Society of SoilScience 53: 315-318.

Yadav BL and Jakhar SR. 2001. Effect of tillage and phosphorusfertilization on yield and water expense efficiency of rainfedmungbean. Journal of the Indian Society of Soil Science 49: 193-194.


ABSTRACT

A field experiment was carried out during kharif 2005 and 2006to study the effect of different dates of sowing on nodulation,growth and yield of four mungbean genotypes ‘SML 668’, ‘ML818’, ‘ML 1265’ and ‘ML 1405’. There was a drastic reduction inyield in case of August 5 sowing in both the years compared toJuly sowing. Genotype ‘ML 1265’ produced higher yield than‘SML 668’ in both the years. Interaction between dates of sowingand genotypes for grain yield was significant in 2005. Genotype‘ML 1265’ produced significantly higher yield than the othergenotypes under late sowing of August 5. Early sowing resultedin absorbing sufficient amount of heat units in less time ascompared to late sowings which acquired more days to matureduring 2006 as compared to 2005 and resulted in accumulationof more growing degree days (GDD) as compared to first season.Among genotypes ‘SML 668’ followed by ‘ML 1265’ consumedlesser days to attain 50% flowering and physiological maturityas compared to other genotypes during both the years. On thebasis of two-year mean values, days to 50% flowering were43.0, 42.0, 41.0 and 39.5 and days to maturity were 70.5, 69.0,65.5 and 63.0 in July 5, 15, 25 and August 5 sowings, respectively.SML 668 was the earliest in maturity (60.5 days) whereas ‘ML818’, ‘ML 1265’ and ‘ML 1405’ matured in 69.0, 67.5 and 69.6days, respectively.

Key words: Mungbean, Nodulation, Thermal indices

Mungbean [Vigna radiata (L.) Wilczek] is an importantpulse crop of kharif season in India. The crop is highlysensitive to environment. Therefore, time of sowing showsremarkable influence on the growth and productivity ofmungbean in kharif due to rainy season (Brar et al. 1988). Theoptimum time of sowing ensures the complete harmonybetween the vegetative and reproductive phases on one hand,and the climatic rhythm on the other and helps in realizing thepotential yield (Singh and Dhingra 1993). Temperature is theprime weather variable which affects plant life. Heat unitconcept is the agronomic application of temperature effect onplant, which has been employed to correlate phenologicaldevelopment in crops and to predict maturity dates (Nuttonson1955, Major et al. 1975). Crop phenology is an essentialcomponent of the crop-weather models, which can be used tospecify the most appropriate rate and time of specific plantgrowth and development process. The duration of each growthphase determines the accumulation and partitioning of drymatter in different plant organs as well as crop response toenvironmental factors. The duration of particular stages of

Effect of date of sowing on nodulation, growth, thermal requirement and grain yieldof kharif mungbean genotypesGURIQBAL SINGH, H.S. SEKHON, HARI RAM, K.K. GILL* and POONAM SHARMA

Department of Plant Breeding and Genetics, *Department of Agricultural Meteorology, Punjab AgriculturalUniversity, Ludhiana 141 004, Punjab, India; E-mail: [email protected](Received: October, 2009; Accepted: July, 2010)

growth is directly related to temperature and the duration forparticular species could be predicted using the sum of dailyair temperature (Wang 1960). The data on the effect of datesof sowing were lacking on the new promising genotypes ofmungbean. In addition, there was a dire need to find outgenotypes for late sowing according to heat unit requirement.Therefore, an experiment was planned and conducted ondifferent dates of sowing on kharif mungbean genotypes, sothat these indices can be used as tools for characterizingthermal responses in different cultivars of mungbean.


The experiment was conducted at the PunjabAgricultural University, Ludhiana (30° 56' N, 75° 52' E, altitude244 m) in kharif 2005 and 2006. The soil of the experimentalfield was loamy sand, having pH 8.2, organic carbon 0.29%,available phosphorus 14.4 kg/ha and available potassium 318kg/ha. The experiment was conducted in a split plot designwith three replications. The four dates of sowing (July 5, July15, July 25 and August 5) were kept in the main-plots and fourgenotypes ‘SML 668’, ‘ML 818’, ‘ML 1265’ and ‘ML 1405’were assigned in the sub-plots. The nutrient dose of 12.5 kg/ha N and 40 kg/ha P2O5 was applied through urea (46% N) andsingle superphosphate (16% P2O5), respectively at the time ofsowing. Sowing was done in rows 30 cm apart. Plant to plantspacing was maintained at about 10 cm by thinning about twoweeks after sowing. Weeds were controlled by usingpendimethalin @ 0.75 kg/ha as pre-emergence application. Allother agronomic practices were adopted according to thepackage of practices (PAU 2004). The total rainfall of 399.9mm and 446.1 mm was received during 2005 and 2006,respectively. The data on nodulation, days to 50% flowering,dates to maturity, plant height, branches/plant, pods/plant,seeds/pod, 100-seed weight and grain yield were recorded.The accumulated heat units (GDD) for each day werecalculated for different phenological event as per the equationsuggested by Nuttonson (1955), using base temperature of10oC. Heliothermal units (HTU) are the product of growingdegree days (GDD) and corresponding actual sunshine hoursfor that day. Photothermal units (PTU) are the product ofgrowing degree days and corresponding day length hoursfor that day. GDD, HTU and PTU were accumulated from thedate of sowing to each date of observation i.e. 50% floweringand physiological maturity. Heat use efficiency (HUE) for grainyield was computed following the method as described by

Singh et al.: Effect of date of sowing on nodulation, growth, thermal requirement and grain yield of mungbean genotypes 133

Rajput (1980) as below:HUE= Seed yield/Accumulated heat units


Effect of date of sowing: In both the years, the maximumplant height was recorded in July 5 sowing which wassignificantly higher than all other sowing dates (Table 1). Therewas linear decline in plant height with delay in sowing.Branches/plant were not significantly influenced by sowingdates in 2005, however, in 2006, July 5 and July 15 showedsignificantly higher branches/plant than July 25 and August5 sowing dates. In 2005, maximum pod/plants were recordedin July 25 sowing which was statistically superior to all othersowing dates. In 2006, significantly higher number of pods/plant were recorded in July 5 and 15 sowing dates and bothwere statistically at par. Pod bearing was the least in the caseof August 5 sowing date. Differences in seeds/pod due tosowing dates were found to be non-significant in 2005 whilein 2006, July 5 and July 15 dates of sowing had significantlyhigher seeds/pod than July 25 and August 5 sowing dates.The 100-seed weight was found to be non-significant in boththe years.

During both the years of the study, nodules and theirdry weight were influenced significantly due to dates ofsowing (Table 2). In both the years, number of nodules andtheir dry weight/plant were highest in the case of July 15while minimum number of nodules and their dry weight wererecorded in the case of August 5 sowing. In both the years,date of sowing showed significant effect on the grain yield ofmungbean. In 2005, sowing on July 25 gave significantlyhigher grain yield (1282 kg/ha) than July 5 and August 5sowings but was statistically at par with July 15 sowing.However, in 2006, significantly higher grain yield (1488 kg/ha) was recorded in July 15 sowing which was statisticallyon par with July 5 sowing but significantly superior to July25 and August 5 sowing dates. There was a drastic reductionin the grain yield in the case of August 5 sowing. Singh et al.(2003) revealed that July 12 to 24 was the best sowing time forkharif mungbean. In another study, Fraz et al. (2006) observedhigher grain yield attributes of mungbean in the case of the

crop sown in the third week of July than the sowings in thirdweek of June and first week of July. In 2005, due to good rainsat vegetative stage the crop attained more plant height, withthe result lodging was observed in July 5 and 15 sowings,which caused reduction in grain yield.

With delay in sowing, days to 50% flowering as well asdays to maturity were reduced in all the genotypes (Table 3).Two-year mean values of days to 50% flowering were 43.0,42.0, 41.0 and 39.5 and days to maturity were 70.5, 69.0, 65.5and 63.0 under July 5, 15, 25 and August 5 sowings,respectively. During 2005, early sown crop availed moregrowing degree days (GDD), photothermal units (PTU) andheliothermal units (HTU) at physiological maturity and witheach delay in sowing GDD, PTU and HTU decreased. Almostsimilar trend was observed for 50% flowering. However, July25 sowing had the highest HUE and resulted in highest grainyield. During 2006, the different trend was observed due tooccurrence of higher maximum and minimum temperature thatprobably accelerated the process of development and as aresult duration of 50% flowering as well as physiologicalmaturity was shortened by 2-3 days in case of first sowingduring 2006 as compared to 2005. So early sowing resulted inabsorbing sufficient amount of heat units in short time due to

Table 1. Effect of dates of sowing and genotypes on growth and yield attributing characters of kharif mungbeanPlant height (cm) Branches/plant Pods/plant Seeds/pod 100- seed weight (g) Treatment

2005 2006 Mean 2005 2006 Mean 2005 2006 Mean 2005 2006 Mean 2005 2006 Mean Dates of sowing July 5 75.5 71.3 73.4 5.38 4.95 5.17 14.7 23.3 19.0 8.78 10.47 9.63 4.08 3.94 4.01 July 15 69.0 60.8 64.9 5.30 5.00 5.15 16.5 24.4 20.5 8.86 10.55 9.71 4.08 3.98 4.03 July 25 60.9 54.6 57.8 5.13 4.63 4.88 18.6 18.6 18.6 8.83 10.12 9.48 4.10 3.52 3.81 August 5 61.1 39.6 50.4 5.10 3.95 4.53 13.6 12.5 13.1 8.86 9.87 9.37 3.99 3.93 3.96 CD (P=0.05) 3.7 3.0 4.9 NS 0.31 0.51 1.1 1.5 1.6 NS 0.30 NS NS NS NS Genotypes SML 668 56.1 43.4 49.8 4.68 4.07 4.38 14.2 14.3 14.3 9.08 9.18 9.13 5.56 5.02 5.29 ML 818 68.2 62.2 65.2 5.43 4.72 5.08 15.7 21.8 18.8 8.86 10.63 9.75 3.58 3.41 3.50 ML 1265 70.0 58.1 64.1 5.36 4.90 5.13 18.3 22.7 20.5 8.83 11.28 10.06 3.75 3.67 3.71 ML 1405 72.3 62.6 67.5 5.43 4.85 5.14 15.2 20.5 17.9 8.86 9.9 9.38 3.36 3.29 3.33 CD (P=0.05) 3.5 2.7 4.2 0.40 0.32 0.23 1.2 1.9 2.1 0.18 0.51 0.43 NS 0.62 0.49

Table 2. Effect of dates of sowing and genotypes onnodulation and grain yield in kharif mungbean

NR - Not recorded

Treatment Number of nodules/

plant

Dry weight of nodules

(mg)/plant

Grain yield

(kg/ha) 2005 2006 2005 2006 2005 2006 Date of sowing July 5 13.7 18.7 36.5 40.7 1111 1372 July 15 22.3 27.7 61.3 56.8 1186 1488 July 25 NR 26.1 NR 54.0 1282 1123 August 5 15.3 17.5 39.8 36.9 983 1063 CD (P=0.05) 2.7 1.1 5.2 3.3 108 119 Genotypes SML 668 14.3 20.7 40.8 43.0 1062 1158 ML 818 17.8 22.5 46.4 45.6 1078 1272 ML 1265 19.3 25.1 50.9 53.9 1278 1362 ML 1405 17.3 21.9 49.3 45.8 1145 1255 CD (P=0.05) 1.8 1.6 4.3 2.2 106 63


high temperature but late sowings (July 25 and August 5)acquired more days to mature during 2006 as compared to2005 and resulted in accumulation of more GDD. During 2006,July 15 sown crop recorded higher grain yield, leading tocomparatively better HUE for grain yield as compared to otherdates of sowing. This could be due to resource inducedcompetition for attaining physiological maturity in sufficientaccumulated heat units.Performance of genotypes: Among the genotypes ‘ML 1405’was the tallest (67.5 cm) whereas ‘SML 668’ was the shortest(49.8 cm) in height (Table 1). Number of branches/plant andpods/plant were least in ‘SML 668’. The highest number ofpods/plant was recorded in ‘ML 1265’ during both the years.‘SML 668’ had the highest seed weight (5.29 g/100 seeds) dueto its large seed size while in ‘ML 1265’, ‘ML 818’ and ‘ML1405’ the 100-seed weight was 3.71, 3.50 and 3.33 g,respectively.

Higher numbers of nodules were observed in ‘ML 1265’than in ‘ML 818’, ‘ML 1405’ and ‘SML 668’ (Table 2). The dryweight of nodules/plant was also higher in the case of ‘ML1265’ than the other genotypes. Genotypes differedsignificantly in the grain yield during both the years. ‘ML1265’ was the highest yielder whereas ‘SML 668’ was thelowest yielder. Genotype ‘ML 1265’ gave 20.3% and 17.6%higher grain yield than ‘SML 668’ in 2005 and 2006,respectively. Genotypes ‘ML 1405’ and ‘ML 818’ were on parin yield. Interaction effects regarding dates of sowing andgenotypes were significant in 2005. Data showed that ‘ML1265’ was superior to other genotypes under late sowing(August 5). Though interaction was non-significant betweendates of sowing and genotypes in 2006 yet the trend wasalmost the same as observed in 2005.

‘SML 668’ was the earliest in flowering (Table 3). On thebasis of two-year mean values, 50% flowering was observed36.5 days after sowing (DAS) while in ‘ML 818’, ‘ML 1265’and ‘ML 1405’, 50% flowering occurred 43.5, 43.0 and 42.0DAS under different dates of sowing. Similarly, two-year meanvalues of dates to maturity were 60.5, 70.0, 68.0 and 70.0 in‘SML 668’, ‘ML 818’, ‘ML 1265’ and ‘ML 1405’, respectively.In different genotypes, high variation in days taken to reach

different phenological stages and agroclimatic indices i.e.GDD, HTU and PTU was observed during 2005 as well as2006. ‘SML 668’ followed by ‘ML 1265’ consumed lesser daysto attain 50% flowering and physiological maturity ascompared to other genotypes during both the years. Similarly,‘ML 1265’ attained lesser GDD, HTU and PTU units andrecorded higher grain yield as compared to other genotypesunder study except ‘SML 668’. This also resulted incomparatively better HUE for seed yield in ‘ML 1265’ overother genotypes.

It may be concluded that July 5-25 seemed to be thebest time of sowing for kharif mungbean under Punjabconditions. Genotype ‘ML 1265’ was superior to others bothunder timely and late sowings.

REFERENCES

Brar ZS, Singh M and Singh G. 1988. Effect of planting dates andgrowth regulators on production of mungbean. Journal of ResearchPunjab Agricultural University 25: 515-520.

Fraz RA, Iqbal J and Bakhsh MAAHA. 2006. Effect of sowing dates andplanting patterns on growth and yield of mungbean [Vigna radiata(L.)] Cv . M-6. International Journal of Agriculture & Biology 8:363-365.

Major DJ, Johnson DR, Tanner JW and Anderson IC. 1975. Effect ofdaylength and temperature on soybean development. Crop Science15: 174-179.

Nuttonson MY. 1955. Wheat-climate relationships and the use ofphenology in ascertaining the thermal and photothermalrequirement of wheat. American Institute of Crop Ecology,Washington DC, pp. 388.

PAU. 2004. Package of Practices for Kharif Crops of Punjab. PunjabAgricultural University, Ludhiana, pp. 206.

Rajput RP. 1980. Response of soybean crop to climate and soilenvironments. Ph.D. Dissertation, IARI, New Delhi.

Singh G, Sekhon HS, Sandhu JS, Singh SJ, Gumber RK and Randhwa AS.2003. Effect of location and seed rate on three genotypes ofmungbean. Tropical Science 43: 116-120.

Singh T and Dhingra KK. 1993. Response of mungbean [Vigna radiata(L.)] cultivars to time of sowing under South-Western region ofPunjab. Journal of Research Punjab Agricultural University 30: 157-159.

Wang JY. 1960. A critiques of the heat unit approach to plant responsestudies. Ecology 41 : 785-790.

Table 3. Accumulated Growing Degree Days (AGDD), Accumulated Heliothermal Units (AHTU) and Accumulated PhotothermalUnits (APTU) at 50% flowering and maturity and heat use efficiency at maturity under different dates of sowing andgenotypes

2005 2006 50% Flowering Maturity 50% Flowering Maturity

Heat use efficiency (kg/ha/oC/day)

Treatment

Days AGDD AHTU APTU Days AGDD AHTU APTU Days AGDD AHTU APTU Days AGDD AHTU APTU 2005 2006 Dates of sowing July 5 44 880 6240 11870 72 1422 11184 18713 42 837 5244 11468 69 1368 10815 18040 0.79 1.00 July 15 42 858 6647 11406 69 1362 10951 17650 42 851 5961 11317 69 1346 9683 17437 0.87 1.11 July 25 41 825 7081 10795 64 1244 10258 15920 41 798 5502 10453 67 1279 9495 16299 1.04 0.88 August 5 39 759 6871 9738 62 1174 10370 14676 40 776 6050 9946 64 1213 9859 15130 0.84 0.88 Genotypes SML 668 36 718 5708 9514 62 1224 10134 15811 37 791 5116 9842 59 1155 8741 14976 0.88 1.00 ML 818 43 865 7014 11400 68 1330 10849 17159 44 877 6143 11536 72 1380 10591 17660 0.83 0.92 ML 1265 43 863 7002 11367 68 1315 10817 16939 43 829 6004 11360 68 1317 10108 16915 0.97 1.03 ML 1405 44 876 7135 11533 70 1352 11079 17351 40 791 5492 10444 70 1355 10412 17356 0.85 0.92


ABSTRACT

The present study was attempted to cluster the districts basedon different criterion, estimating the patterns of growth andmagnitude of instability, and assessing the explanatoryvariables’ affects on pulses production in Andhra Pradesh. Thetime series data for the period 1986-87 to 2007-08 on area,production and productivity were collected from variouspublications of the Bureau of Economics and Statistics,Government of Andhra Pradesh. Hierarchical and K-MeansClustering, Compound Growth Rate (CGR), Coppock’sInstability Index (CII), and decomposition analysis (change inaverage production) were employed for achieving the objectives.Growth performance of pulses production was high, but it wasaccompanied by high degree of instability. Decompositionanalysis revealed that area effect was marginally higher thanthe productivity effect on the production differential. Therefore,growth in production should mainly come from area attributingfactors like assured supply of farm inputs and provision ofremunerative prices.

Key words: Clustering, Decomposition analysis, Growth,instability, Pulses

India is the largest producer, consumer and importer ofpulses in the world. In India, during the year 2005-06, pulseswere grown on 22.22 million hectares with a production of13.18 million tones (593 kgs/ha of yield). Pulses accounts for18.46 % of area and 6.54 % of production to the total foodgrain of the country. The major pulses grown in India arepigeonpea and chickpea. The projected demand for pulses by2020 in India is 27.2 million tones. Andhra Pradesh ranks fourthin pulses production with 1.78 (7.95%) million hectares ofcultivated area and 1.38 (10.31%) million tones of productionduring 2005-06. Major pulses grown in Andhra Pradesh arepigeonpea, chickpea, urdbean and mungbean. Productionrequirement of pulses in Andhra Pradesh as per ICMRrecommendation (40gms/day) by 2020 is 1.629 million tones.While, rice and wheat output has grown considerably andthere has been a considerable lag in output growth of pulsesand coarse cereals in India (Shah and Shah 1997). Further, thefindings of Hazell (1984) and Jayadevan (1991) revealed thatthe growth in crop production during the post-greenrevolution period has been accompanied with increasedinstability and yield fluctuation turned out to be the majorsource of production instability. In order to find out causesfor these fluctuations, an attempt has been made to study

Performance of pulses during pre and post-WTO period in Andhra Pradesh: districtwise analysisI.V.Y. RAMA RAO

Regional Agricultural Research Station, Anakapalle, Visakhapatnam-531 001 (A.P.);Email: [email protected](Received: November, 2008; Accepted: September, 2010)

growth rates in area, production and productivity of pulses,to examine the extent of instability in production, to identifythe productivity clusters, to identify the growth and instabilityclusters based on pulses production and to assess the changein average production caused by exploratory variables


The study pertains to all the districts i.e., 22 districts,(Data for Hyderabad district is not available) threegeographical regions of Andhra Pradesh viz., Coastal Andhra,Rayalaseema, Telangana and State as a whole. Time seriesdata on total pulses for 20 years from 1986-87 to 2005-06 wascollected from published literature of Bureau of Economicsand Statistics, Government of Andhra Pradesh. For calculatingthe CGR, CII and Decomposition rate, whole period wasdivided into two sub periods resulting in the formation ofthree periods viz., Period-1 (pre-WTO) (1988-89 to 1997-98),Period-II (post-WTO) (1998-99 to 2007-08) and Overall Period(1988-89 to 2007-08). Analysis was conducted separately foreach period.Estimation of growth rates: Compound growth rates wereestimated by fitting an exponential function of the followingform.

Y= A.bt; Log Y = Log A + t. log bWhere, Y = Area/production/productivity ; A= Constant

b= (1+r), r = Compound growth rate, t = Time variable in years(1,2,3…n)

The percent compound growth rate is calculated asbelow:

CGR (%) = [(Antilog of ‘b’) - 1] x 100Estimation of extent of instability: The extent of instabilityis calculated by using Coppock’s Instability Index (CII), whichis a close approximation of the average year-to-year percentagevariation adjusted for trend. In algebraic form:

CII = [Antilog V log – 1] x 100

Log V = 1– N

m]– )X / (X [Log 2t1 t

Where, Xt = Area/ production/ productivity in the year‘t’, N= Number of years, log V = Logarithmic variance,


m=Arithmetic mean of difference between the logs of Xt+1 etc.Clustering: Cluster analysis is a multivariate procedure ideallysuited to segmentation application. Clustering is thetechnique, which groups the objects of interest based on theproximities of the concerned character. Two-stage clusteringtechnique was employed by using the Hierarchical and K-Means Clustering techniques (SPSS 15 trial version)Hierarchical Clustering gives the number of groups to beformed. Where as, K-Means Clustering will decide themembership in each cluster.Based on productivity: Hierarchical Cluster analysis giventhree clusters of districts. These clusters were named as low(< 400), medium (400-600) and high (> 600) based on yield (kg/ha).Based on growth vis-à-vis instability: Hierarchical Clusteranalysis classified the districts based on the productiongrowth (CGR) into three clusters viz., Low (<2%), Medium (2-10%) and High (>10%), and in terms of production instability(CII) into three clusters viz., Low (<20%), Medium (20-40%)and High (>40%). Then these three clusters were crosstabulated and resulted in nine clusters viz., L-L (Low-Low),L-M,L-H,M-L,M-M,M-H,H-L,H-M, and H-H (High-High)clusters, and presented in the form of 3 x 3 tables (tables 6,7and 8). Further, analysis was carried for the all the periods.\Decomposition analysis (change in average production):Change in average production between the periods arisesfrom changes in mean area and mean yield (productivity),interaction between changes in mean yield and mean area andchange in yield-area covariance (Hazell 1982).

The change in average production E (P) between theperiods can be obtained as follows:

Y) (A, Cov Y . A A . Y Y . A (P) E 11

Where 1A . Y = change in mean area; 1Y . A = changein mean yield; A . Y = changes in mean area and meanyield; Cov (A,Y) = changes in area and yield covariance


Growth rates: During the over all period, state as a whole,pulses had shown high growth rate in area (1.60%), production(3.17%) and productivity (1.54%) (Table 1). Thus, growth inarea had marginally higher effect on growth in productionthan by the growth in productivity. Among the regions, highestgrowth rates in area, production and productivity wereregistered in Rayalaseema. About range of growth rates, inarea it varied from 0.39 per cent (Telangana) to 5.76 per cent(Rayalaseema), in production it ranged between 1.61 per cent(Coastal Andhra) and 11.53 per cent (Rayalaseema) and inproductivity it was between –0.12 per cent (Coastal Andhra)and 5.46 per cent (Rayalaseema). So, the lowest growth ratesin production and productivity were recorded in Coastal

Andhra, where as, in area was recorded in Telangana. Amongthe districts, growth rates in area varied between –5.0 per cent(Karimnagar) and 10.37 per cent (Kadapa), in production from–5.78 per cent (Karimnagar) to 18.33 per cent (Kadapa),whereas, in productivity it was between -3.86 per cent (EastGodavari) and 7.21 per cent (Kadapa). Further, eight, six andfive districts shown the negative trend in area, productionand productivity respectively.

During the period I, state as a whole, growth rate waslow in productivity (0.38%), whereas, growth rates in area(1.11%) and production (1.49%) were moderate. So, growth inarea contributed more towards growth in production than bygrowth in productivity. Among the regions, ranges of growthrates in area varied between -1.97 per cent (Telangana) and4.09 per cent (Coastal Andhra), in production they were from0.51 per cent (Coastal Andhra) to 14.17 per cent (Rayalaseema)and in productivity varied between –3.03 per cent (CoastalAndhra) and 12.61 per cent (Rayalaseema). So, productionand productivity were the highest in Rayalaseema. So, growthin area contributed more towards growth in production inCoastal Andhra, where as, by growth in productivity inRayalaseema. Among the districts, range of growth rates inarea was between -7.03 per cent (Karimnagar) and 14.17 prcent (East Godavari), in production the lowest was -7.91 percent (Karimnagar) and the highest was 18.36 per cent (Kurnool)and in productivity growth rates varied from –5.47 per cent(West Godavari) to 14.49 per cent (Kadapa). So, Karimnagarrecorded the lowest growth rate in area and production. Outof 22 districts, nine (eight in Telangana) in area, six (two inTelangana) in productivity and seven (three in Telangana) inproduction has showed negative growth rates.

During the period, among the districts, highest growthrate in area (17.89%), production (22.17%) and productivity(12.01%) were recorded respectively in Kadapa, Prakasam andMedak. While, lowest growth rates in area (-3.17) was inGuntur, whereas, in production (-3.84%) and productivity(-3.42) were noticed in East Godavari. So, lowest growth ratesin area, production and productivity were observed amongthe districts of Coastal Andhra region. Further, six, three, fivedistricts registered with negative CGR in area, production andproductivity respectively. Among the regions, growth ratesin area varied between 1.13 per cent (Coastal Andhra) and10.66 per cent (Rayalaseema) and in production varied from3.43 (Coastal Andhra) to 14.76 (Rayalaseema), in productivitythe lowest was 2.27 per cent (Coastal Andhra) and the highestwas 6.3 per cent (Telangana). Further, growth in areacontributed more towards growth in production inRayalaseema, whereas, growth in productivity contributedmore towards growth in production in Coastal Andhra andTelangana. For state as a whole, growth in productivity (3.80%)contributed more towards growth in production (6.85%) thanby growth in area (2.94)

Rangi et al. (2002) has stated that compound growth

Rao : Performance of pulses during pre and post-WTO period in Andhra Pradesh: district wise analysis 137

rates for pulse production of India (1.07%) and world (1.38%)was same for the period of 1970-71 to 1998-99. Whereas, incase of pulses acreage growth rate was found negative andnon significant. In the present study compound growth ratefor Pulses production during period I (1986-87 to 1995-96) inAndhra Pradesh was 1.49 per cent. Thus, it can be concludedthat pulses production growth rate was same in AndhraPradesh, India and the world with least exception of 3 yearsperiod. But, in present study, pulses production in post-WTOera (1996-97 to 2005-06) has showed tremendous growth(6.85%) that to more contribution from productivity than area.Reason may be due to effective implementation of Technologymission on pulses since 1990-91 in Andhra Pradesh and moreimportantly expansion of area of chickpea in rabi season.Extent of instability: Among the districts, during the periodI, the lowest and the highest instability in area, productionand productivity were respectively recorded in Visakhapatnam(4.86%) and Srikakulam (35.0 %), in Chittoor (12.02%) andEast Godavari (86.94%) and in Khammam (7.20 %) and EastGodavari (86.71 %) as shown in table 2. During the period II,the lowest and the highest instability in area (3.89 % and 57.31%), production (15.25 % and 107.46 %)and in productivity(12.07 % and 52.81 %) were registered respectively in Adilabadand Kadapa, Chittoor and Prakasam and in Vizianagaram andPrakasam. During the overall period, the lowest instability inproduction (13.44 %) and productivity (15.48 %) were recorded

in Chittoor. Whereas, in area (5.02 %) was in Adilabad. But,the highest instability in area (83.53 %), production (168.34%) and productivity (63.25 %) were recorded in Kadapa.Further, in 12 out of 22 districts, contribution of instability inproductivity in relation to variability in area was more towardsproduction fluctuations.

Among the regions, during the period I, the lowestinstability in production (12.44%) and productivity (13.73 %)were recorded in Coastal Andhra, whereas, in area (6.94 %)was observed in Telangana. The highest instability in area(13.38 %) and production (46.04%) and productivity (39.47 %)were recorded in Rayalaseema. Contribution towardsproduction fluctuations was more by variability in productivityin all regions. During the period II, the lowest instability inarea (7.70 %), production (21.00 %) and productivity(14.25 %) were recorded in Coastal Andhra. Where as, thehighest in area (32.06%) and production (60.18%) were inTelangana and in productivity (31.95%) was in CoastalAndhra. Contribution towards production variability wasmore by area variability in Rayalaseema and by instability inproductivity in Coastal Andhra and Telangana. During theoverall period, the lowest instability in area (8.74%) was noticedin Telangana, whereas, in production (17.74 %) andproductivity (13.03 %) were recorded in Coastal Andhra. Thehighest instability in area (42.56%), production (86.39%) andproductivity (40.78%) were recorded in Rayalaseema.

Table 1. Compound growth rates of area, production and productivity of pulses in Andhra Pradesh during different periods

*A = area, PD = production, P = productivity

Overall period (1988-89 to 2007-08)

Period-I (1988-89 to 1997-98)

Period-II (1998-99 to 2007-08)

Districts and regions

A* PD P A PD P A PD P Srikakulam 2.27 2.53 0.25 10.08 10.30 0.20 0.47 0.48 0.02 Vizianagaram 2.00 2.90 0.88 7.44 7.65 0.19 -2.54 -3.20 -0.67 Visakhapatnam -1.16 0.55 1.73 1.71 2.90 1.17 -2.45 1.40 3.94 East Godavari 3.87 -0.14 -3.86 14.17 10.76 -2.99 -0.43 -3.84 -3.42 West Godavari -2.51 -3.41 -0.92 0.67 -4.84 -5.47 5.61 11.13 5.23 Krishna -0.80 -1.07 -0.28 -1.96 -4.92 -3.02 2.09 2.79 0.68 Guntur -0.40 -1.40 -1.00 1.98 -0.60 -2.53 -3.17 -3.25 -0.09 Prakasam 8.37 13.62 4.85 6.84 9.89 2.85 10.20 22.17 10.86 Nellore 7.18 10.98 3.54 7.91 10.02 1.96 5.29 9.01 3.53 Coastal Andhra 1.70 1.61 -0.12 4.09 0.51 -3.03 1.13 3.43 2.27 Kurnool 7.72 13.36 5.23 3.44 18.36 14.42 11.55 17.57 5.39 Ananthapur 3.13 5.70 2.49 0.18 11.78 11.58 7.43 1.76 -5.28 Kadapa 10.37 18.33 7.21 2.41 17.25 14.49 17.89 21.17 2.79 Chittoor -0.86 0.57 1.44 -2.02 -0.01 2.05 3.51 3.16 -0.33 Rayalaseema 5.76 11.53 5.46 1.39 14.17 12.61 10.66 14.76 3.70 Ranga Reddy 1.86 4.69 2.78 1.74 2.52 0.77 0.93 9.42 8.41 Nizamabad 1.58 4.62 2.99 -2.27 6.21 8.68 4.15 5.72 1.51 Medak 5.49 10.34 4.59 4.64 9.44 4.58 5.84 18.55 12.01 Mahaboob Nagar 1.99 4.37 2.34 -4.01 -4.30 -0.30 4.98 9.54 4.34 Nalgonda 1.57 5.15 3.53 -1.86 1.77 3.70 3.70 12.18 8.18 Warangal -2.22 1.08 3.38 -5.13 1.35 6.83 1.09 5.75 4.61 Khammam -2.57 -0.90 1.72 -0.96 -0.48 0.49 -0.54 1.33 1.88 Karim Nagar -5.00 -5.78 -0.82 -7.03 -7.91 -0.96 -1.56 2.55 4.17 Adilabad 0.03 7.03 6.99 -1.59 4.57 6.25 1.06 8.47 7.34 Telangana 0.39 3.18 2.78 -1.97 0.57 2.59 2.55 9.02 6.30 Andhra Pradesh 1.60 3.17 1.54 1.11 1.49 0.38 2.94 6.85 3.80


Contribution towards production fluctuations was more byinstability in productivity in Coastal Andhra and Telanganaand by variability in area in Rayalaseema.

State as a whole, during the period I, productivityvariability (5.06 %) had more influence on productionfluctuations (6.37%) than by instability in area (3.23%). Duringthe period II also instability in productivity (18.87%) has moreinfluence on production variability (29.85%) than by instabilityin area (10.80%). During overall period, instability in production(25.00%) was more than productivity variability (14.67%) andarea fluctuations (10.56%). Thus, variability in productivityhas more influence on production variability than by areafluctuations. Inter period comparison revealed that instabilityin area, production and productivity during the period II wasmore than period I.

Shukla (1998), in his interstate analysis of growth andinstability in pulses, stated that production of gram was foundconstant. Whereas, results of present study revealed theproduction variability (25.00 % CII) during the overall period(1988/89 to 2007/08) was high. Major reason behind this is,majority of pulses are being cultivated under rain fedconditions. Further, it is clear from tables 1 and 2 that growthand instability are going together. That is to say, pulses hadinstabilized growth.

Above results compelled to identify the high and lowproductivity level districts from each region and this was donein Fig 1 & 2 by taking one district from each region with lowand high PCOPP (Percentage Change Over Previous Period).

From high PCOPP (Fig 1) it is clear that though hightrend was there in Prakasam and Kadapa, it was accompaniedby high fluctuations (This was clear in Table 5). Low orNegetive PCOPP (Fig 2) revealed that there was negative trendin East Godavari and Karim Nagar. Whereas, low stagnanttrend was observed in Chittoor. Further, there was uniformityin some years except sharp dip in 2000-01 and rise in 2002-03.

Above results helps as pointer for further research indeveloping region specific strategies. For example forTelangana region, exploring and establishing the factors forhigh trend in Karimnagar and low trend in Adilabad in differentyears.

Clustering

Based on productivity: During the total period (Table 3) three,ten and nine districts were in low, medium and high clustergroups respectively. The high, medium and low cluster districtscontributed 38%, 36% and 26% respectively towards stateaverage production (825974 tones). Looking districts r region-wise, two, five and two districts in Coastal Andhra, one, one

Table 2. Coppock’s Instability Indices (CII) of area, production and productivity in Andhra Pradesh during different periods(values given are in %)

*A = area, PD = production, P = productivity

Overall period (1988-89 to 2007-08)

Period-I (1986-87 to 1995-96)

Period-II (1996-97 to 2005-06)

Districts and regions

A* PD P A PD P A PD P Srikakulam 24.35 36.19 16.34 35.00 49.22 19.23 7.77 18.09 12.93 Vizianagaram 19.90 35.59 18.40 22.77 39.13 20.85 11.67 20.14 12.07 Visakhapatnam 11.71 15.94 17.72 4.86 15.10 11.80 8.86 16.78 19.19 East Godavari 29.53 39.03 37.64 41.50 86.94 86.71 5.16 30.81 30.62 West Godavari 38.64 64.35 30.38 22.16 55.37 34.52 29.09 46.07 25.78 Krishna 12.71 22.08 20.45 11.74 18.71 14.76 11.79 25.38 26.12 Guntur 17.51 27.35 19.34 9.24 19.16 19.49 22.89 29.79 17.62 Prakasam 59.63 125.30 47.34 22.76 43.15 25.12 38.29 107.46 52.81 Nellore 59.82 99.15 27.97 28.27 36.02 13.76 50.10 80.45 23.29 Coastal Andhra 11.65 17.74 13.03 12.35 12.44 13.73 7.70 21.00 14.25 Kurnool 56.13 102.03 43.95 19.86 61.75 49.98 35.75 72.05 32.22 Ananthapur 26.11 53.02 42.48 13.68 40.58 37.41 20.92 46.71 46.00 Cuddapah 83.53 168.34 63.25 17.97 71.07 61.57 57.31 88.88 31.96 Chittoor 16.46 13.44 15.48 7.14 12.02 13.65 20.37 15.25 12.13 Rayalaseema 42.56 86.39 40.78 13.38 46.04 39.47 32.06 60.18 28.32 Rangareddy 11.77 42.12 33.11 6.48 19.39 18.34 5.51 44.33 40.48 Nizamabad 15.89 48.96 45.43 10.65 49.40 57.37 13.24 36.49 29.58 Medak 36.13 91.71 49.77 16.39 46.34 32.98 21.04 84.73 57.49 Mahaboobnagar 25.95 51.83 30.50 21.79 34.61 22.55 21.26 45.87 28.74 Nalgonda 17.01 54.73 41.56 10.88 28.38 26.41 17.35 65.69 50.16 Warangal 18.51 37.94 35.29 17.61 36.71 35.80 10.20 40.73 31.97 Khammam 21.78 18.17 13.74 8.88 14.18 7.20 12.14 17.05 12.96 Karimnagar 35.23 59.93 29.78 21.96 39.55 23.71 13.57 36.81 32.47 Adilabad 5.02 61.85 59.27 5.68 40.33 39.14 3.89 42.77 40.00 Telangana 8.74 32.95 26.62 6.94 14.65 15.58 9.82 42.25 31.95 Andhra Pradesh 10.56 25.00 14.69 3.23 6.37 5.06 10.90 29.85 18.87


and two districts in Rayalaseema and none, four and fivedistricts in Telangana were in high, medium and low clustergroups, respectively.

From Tables 4 and 5, it is clear that in period-I, 38%, 30%and 32% of state average production was in high, mediumand low cluster groups. Whereas, in period-II, a good amount(51%) was in high group clusters. That shows the definiteincrease in the productivity levels of some districts over thetime. During pre-WTO period, two, six and one districts inCoastal Andhra, none, one and three districts in Rayalaseemaand none, two and seven districts in Telangana were in high,medium and low cluster groups respectively. So, productivitylevels in the districts of Coastal Andhra are higher thanRayalaseema and Telangana. Further, during post-WTOperiod, three, four and two districts in Coastal Andhra, two,none and two districts in Rayalaseema and none, five andfour districts in Telangana were in high, medium and low clustergroups respectively. So, productivity levels in the districts ofCoastal Andhra are higher than Rayalaseema and Telangana.

Table 3. Productivity (kg/ha) clusters of different districts intotal period (1988-89 to 2007-08)

aState average productivity during total period was 483 kg/ha; bStateaverage production during total period was 825974 tones

Cluster-I (High) Cluster-II (Medium) Cluster-III (Low) S.N Name Yield Name Yield Name Yield

1 Krishna 708 Prakasam 597 E.Godavari 381 2 Guntur 699 Nellore 473 Vizianagaram 350 3 Kurnool 603 W.Godavari 469 Ananthapur 342 4 Visakhapatnam 440 Chittoor 265 5 Srikakulam 432 Karim Nagar 398 6 Kadapa 576 Warangal 373 7 Khammam 440 Nalgonda 333 8 Nizamabad 423 Adilabad 283 9 Ranga Reddy 407 Mahaboobnagar 276

10 Medak 405 Average 670 466 333 % to state productivitya 139 97 69 % to state productionb 38 36 26

Table 4. Productivity (kg/ha) clusters of different districts inperiod I (1986-87 to 1995-96)

aState average productivity during total period was 447 kg/ha; bStateaverage production during total period was 699573tones


1 Guntur 732 W.Godavari 498 Vizianagaram 330 2 Krishna 704 Prakasam 462 Kadapa 414 3 E.Godavari 443 Ananthapur 302 4 Srikakulam 429 Chittoor 243 5 Visakhapatnam 407 Nizamabad 387 6 Nellore 384 Ranga Reddy 356 7 Kurnool 513 Warangal 331 8 Karim Nagar 428 Medak 327 9 Khammam 398 Nalgonda 283

10 Mahaboobnagar 243 11 Adilabad 191

Average 718 449 314 % to state productivitya

161 101 70

% to state productionb

38 30 32

Table 5. Productivity (kg/ha) clusters of different districts inperiod II (1996-97 to 2005-06)

aState average productivity during total period was 518 kg/ha; bStateaverage production during total period was 952375 tones


1 Guntur 666 Srikakulam 435 Vizianagaram 369 2 Krishna 713 Visakhapatnam 473 E.Godavari 319 3 Prakasam 733 W.Godavari 439 Chittoor 286 4 Kadapa 692 Nellore 563 Ananthapur 382 5 Kurnool 737 Ranga Reddy 458 Mahaboobnagar 309 6 Nizamabad 459 Karim Nagar 367 7 Medak 482 Adilabad 376 8 Warangal 416 Nalgonda 384 9 Khammam 482

Average 708 474 344 % to state productivitya

137 91 66

% to state productionb

51 26 23

0

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Karim NagarEast Godavari

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Fig 2. Productivity trends of selected districts with low PCOPPFig 1. Productivity trends of selected districts with high PCOPP

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KadapaPrakasamAdilabad


This shows the movements of the some districts from low andmedium range to high range from period-I to Period-II. That isto say that five districts viz., Ranga Reddy, Nizamabad, Medak,Nalgonda and Warangal moved from low group to mediumgroup. Whereas, Prakasam and Kurnool districts moved frommedium to high groups.

But, point of concern is that productivity levels of 11districts were stagnant. Whereas, three districts Srikakulam,East Godavari and Karim Nagar, were slipped from medium tolow productivity cluster groups.Based on growth vis-à-vis instability: Production growth was1.49% and 6.85% in P-I and P-II respectively for state as a

whole (Table 1). It looks high but basic fact is that beingpulses production base itself is low in the state, if a smallchange in absolute values will be reflected highly in percentageterms.

Looking in isolated manner (Table 6), first from growthrates angle there was 46% of production base was in lowcategory, followed by 30% in high and 24% in mediumcategories. Where as, from instability angle 46% of productionbase was in medium category followed by 43% in high and11% in low categories.

Then looking from both viz., growth and instability, themost desirable combination is the district with high growth

Table 6. Cross tabulated growth clusters with instability clusters in total period (1988-89 to 2007-08)

*A.P = Average production in total period for the respective districts, **State average production during total period was 825974 tones

Growth clusters (production in tones) Cluster-I (Low) Cluster-II (Medium) Cluster-III (High)

Instability clusters

Name A.P* Name A.P* Name A.P*

Total % to state

production** Chittoor 4543 - - Karim Nagar 27896 Visakhapatnam 12760 - - W.Godavari 8704

Cluster-I (Low)

Khammam 38938 - - - - % to state production of each group 7 0 4 11

Krishna 111938 Srikakulam 33950 - Guntur 142108 Vizianagaram 20688 - Warangal 25814

Cluster-II (Medium)

E.Godavari 43458 % to state production of each group 39 - 7 0 46

- - Mahabubnagar 26729 Medak 44265 - - Nizamabad 14939 Prakasam 76691 - - Ranga Reddy 25489 Nellore 11351 - - Nalgonda 30936 Kurnool 60868 - - Ananthapur 21366 Kadapa 21037

Cluster-III (High)

- - Adilabad 25753 % to state production of each group 0 - 17 - 26 43 Total % to state production 46 - 24 - 30 100

Table 7. Cross tabulated growth clusters with instability clusters in period-I (1986/87 to 1995/96)

*A.P = Average production in period-I for the respective districts, **State average production during l period-I was 699573 tones

Growth clusters (production in tones) Cluster-I (Low) Cluster-II (Medium) Cluster-III (High)

Instability clusters

Name A.P* Name A.P* Name A.P*

Total % to state

production** Krishna 117497 Visakhapatnam 12728 - - Guntur 150051 Ranga Reddy 19715 - - Chittoor 4481 - - - -

Cluster-I (Low)

Khammam 41529 - - - - % to state production of each group 45 - 4 - 0 49

Karim Nagar 37377 Vizianagaram 20688 Nellore 5303 Mahabubnagar 20140 - - - - Warangal 25595 - - - -

Cluster-II (Medium)

Nalgonda 23029 - - - - % to state production of each group 15 - 3 - 1 19

W.Godavari 11130 Prakasam 31345 Srikakulam 32118 - - Nizamabad 12120 E.Godavari 47271 - - Medak 24233 Ananthapur 15880 - - Adilabad 17149 Kurnool 30383

Cluster-III (High)

Kadapa 6484 % to state production of each group 1.5 - 12 - 18.5 32 Total % to state production 61.5 - 19 - 19.5 100


Table 8. Cross Tabulated Growth Clusters with Instability Clusters in Period-II (1996/97 to 2005/06)

*A.P = Average production in period-II for the respective districts, **State average production during period-II was 952375 tones

Grow Clusters (production in tones) Cluster-I (Low) Cluster-II (Medium) Cluster-III (High)

Instability Clusters Name A.P* Name A.P* Name A.P*

Total % to state

production** Cluster-I (Low) Srikakulam 35783 Chittoor 4605 - - Visakhapatnam 12792 - - - - Khammam 36348 - - - - % to state production of each group 9 - 0 - - 9 Cluster-II (Medium) Vizianagaram 23559 Krishna 106379 - - E.Godavari 39643 Karim Nagar 18416 - - Guntur 134166 Nizamabad 17758 - - % to state production of each group 21 - 15 - - 36

Ananthapur 26852 Nellore 17399 W.Godavari 6278 - - Adilabad 34357 Prakasam 122038 - - Warangal 26032 Kurnool 91353 - - Ranga Reddy 31264 Kadapa 35589 - - Mahabubnagar 33318 Medak 64298

Cluster-III (High)

- - Nalgonda 38843 % to state production of each group 2 - 15 - 38 55 Total % to state production 32 - 30 - 38 100

Table 9. Components of change in average production in Pulses between period I and II

Sources of change (%) Districts and Regions Change in mean

yield Change in mean

area Changes in mean area and mean

yield Changes in area and yield

covariance Srikakulam 12.57 78.27 1.12 8.04 Vizianagaram 36.87 56.95 6.82 -0.63 Visakhapatnam 3214.54 -2545.04 -416.10 -153.40 East Godavari 204.19 -146.35 47.77 -5.61 West Godavari 26.38 79.67 -9.36 3.30 Krishna -12.95 109.22 1.34 2.39 Guntur 84.84 20.77 -1.86 -3.76 Prakasam 19.92 43.98 25.70 10.40 Nellore 20.29 48.95 22.93 7.84 Coastal Andhra 4.10 85.12 0.59 10.19 Kurnool 16.85 57.98 20.23 4.94 Ananthapur 38.14 51.57 13.64 -3.36 Cuddapah 16.96 43.75 34.19 5.10 Chittoor 631.29 -426.40 -74.59 -30.31 Rayalaseema 28.03 45.11 22.70 4.15 Rangareddy 48.93 38.03 10.88 2.17 Nizamabad 40.82 44.12 8.18 6.87 Medak 27.84 43.31 20.41 8.44 MahaboobNagar 41.79 43.93 12.02 2.26 Nalgonda 52.21 29.68 10.62 7.49 Warangal 1534.69 -1264.71 -325.78 155.80 Khammam -168.21 217.78 45.88 4.55 Karim Nagar 27.52 82.57 -11.63 1.54 Adilabad 96.72 1.18 1.15 0.95 Telangana 76.31 12.87 3.53 7.29 Andhra Pradesh 43.91 44.87 7.12 4.10

and low instability (top-right corner group), where as, opposite(bottom-left corner group) is most undesirable group. Therewas 39% of production base was in L-M (low growth andMedium Instability) category. Followed by 26% in H-Hcategory. But, point of concern is that nearly 18% ofproduction base is in M-H category.

Tables 7 and 8 shows that in period-I (pre-WTO era),62% of state production base was in low growth category,followed by 19% equally in medium and high categories.Whereas, in instability scenario, 49% of the state production

was in low category, followed by 33% in high and 18% inmedium category. Looking from both (growth and Instability)45% of production was in L-L category, followed by 19% in H-H category. It reveals that growth and instability are goingtogether.

Looking through Tables 7 and 8, reveals that exceptthree districts viz., Khammam (L-L), Kadapa and Kurnool (H-H), all the districts moved from one category to anothercategory from period-I to period-II. Majority of the districtsmoved from low growth category to medium and towards high


groups, in instability also same trend was observed. The factestablished here is that growth and instability are goingtogether.

Most undesirable movement is in the direction fromTop-Right corner (H-L group) to Down-Left corner (L-H group)like Nellore district’s movement from H-M group to M-H group.Other undesirable movements are from right to left Horizontallylike Visakhapatnam (from M-L to L-L), Vizianagaram (from M-M to L-M) etc., and movement from top to bottom verticallylike Ranga Reddy (from (M-L to M-H) etc. Concern aboutmovement from top-left corner to bottom-right corner andopposite direction depends upon production base. That is, ifproduction base is high generally then low instability at thecost of growth is desirable, whereas, at low production basehigh growth is desirable at the cost of fluctuations.Decomposition analysis (change in average production):Among the districts, in thirteen districts change in mean areahas more effect on average production differential than byother components of change (Table 9). The highest mean areaeffect was recorded in Khammam (217.78%). Where as, highestchange in mean yield (3214.54%) was noticed inVisakhapatnam. Further, in majority of districts (13 out of 22)mean area effect was higher than other components.

Among the regions, from period I to period II change inmean yield was higher than other components of change in

Telangana, where as, change in mean area was higher in CoastalAndhra and Rayalaseema, of which, the highest was in CoastalAndhra (85.12%).

State as a whole, effect of change in mean area (44.87%)was marginally higher than mean yield (43.91), mean area andyield (7.12%) and area and yield covariance (4.10%). Thus,change in mean area and mean yield has equal destabilizingeffect on average production differential between the periodsI and II.

REFERENCES

Hazell PBR. 1982. Instability in Indian food grain production. ResearchReport 30, International Food Policy Research Institute,Washington DC, USA.

Hazell PBR. 1984. Sources of increased instability in India and UScereal production. American Journal of Agricultural Economics 66:302-311.

Jayadevan CM. 1991. Instability in wheat production in M.P. AgriculturalSituation in India 46(4): 219-223.

Rangi PS, Jagdeep Kaur and Marsimran Kaur. 2002. Present status andfuture prospects of pulses in India. Economic Affairs 47: 32-36.

Shah D and Shah D. 1997. Food grain production in India: a drivetowards self-sufficiency. Artha Vijnana 39: 219-239.

Shukla ND. 1998. Growth and instability in pulse production. Aninterstate analysis. Agricultural Situation in India 54: 639-645.


The knowledge of combining ability is useful in theselection of parents and hybrids which can provide superiorprogenies for the characters of interest. It also providesinformation about nature of gene action and the relativemagnitude of fixable and non-fixable genetic variation to followup the sound breeding programme. Studies based oncombining ability analysis have been made earlier in fieldpeato study gene effects and genetic worth of parents (Bhardwajand Kohli 1998, Kumar et al. 2006). The line x tester analysiswas adopted in the present study on fieldpea to gatherinformation on general and specific combining abilities andestimating various types of gene effects involved in variousquantitative characters.

Sixty F1 hybrids of fieldpea developed by line x testermating design involving 20 diverse and homozygous lines offieldpea and three testers (Table 2) were grown along withtwenty-three parents in a randomized complete block designwith two replications at Punjab Agricultural University,Ludhiana during rabi 2006-07. Observations were taken onfive competitive and randomly taken plants on different traits(Table 2). The data was subjected to line x tester analysis asper procedure given by Kampthorne (1957). The averagedegree of dominance was also calculated as (s2 sca/2s2 gca)0.5.

Variation due to lines and lines x testers were highlysignificant for all the characters, whereas variation due totesters was found to be significant for all the characters exceptdays to maturity and primary branches per plant (Table 1).The estimates of sca variances were much higher than the

gca variances for all the characters indicating importance ofnon-additive gene effects than additive gene effects. The highermagnitude of sca variance as compared to gca variance hasbeen reported earlier (Bhardwaj and Kohli 1998, Kumar et al.2006). The average degree of dominance indicated overdominance for all the characters studied except plant heightas their average degree of dominance values were greaterthan unity indicating predominance of non-additive gene actionin the inheritance of these characters. Predominance of non-additive gene action has been reported earlier for yield and itscomponents by Kumar et al. (2006); Singh and Singh (2003);Singh and Singh (1990) and Singh et al.(1987).

For days to flowering ‘DDR 23’, ‘LFP 41’, ‘EC 334160’and ‘LFP 446’ have significant negative gca effects. For daysto maturity the genotype ‘DDR 23’, followed by ‘LFP 202’,‘KPMR 752’, ‘EC 502159’, ‘EC 385246’ and ‘NDDP 5-12’ havehigh significant gca effects indicating their usefulness forgetting short duration recombinants. For plant height,genotype ‘EC 389374’ followed by ‘DDR 23’, ‘LFP 362’, ‘EC385246’, ‘LFP 363’, ‘LFP 305’, ‘KPMR 752’, ‘IFPD 5-8’, ‘NDDP5-12’ and ‘LFP 210A’ have high negative gca effects showingtheir importance for developing dwarf pure lines from theirprogenies. Genotypes ‘P 2005’, ‘EC 389374’, ‘LFP 207A’, ‘LFP210A’ and ‘PG 3’ have shown significant positive gca effectfor primary branches per plant. The genotypes ‘DDR 23’, ‘LFP207A’, ‘LFP 202’, ‘EC 334160’, ‘P 289’, ‘LFP 446’, ‘PG 3’ and‘HFP 8909’ appeared to be good general combiners for numberof pods per plant. For seeds per pod ‘LFP 413’, ‘LFP 363’,

Short Communication

Combining ability for yield and its components in fieldpeaINDERJIT SINGH, J.S. SANDHU and JOHAR SINGH

Department of Plant Breeding & Genetics, Punjab Agricultural University, Ludhiana-141004, India;E-mail: [email protected](Received: March, 2009; Accepted: August 2010)

Table 1. Analysis of variance, estimates of combining ability variance and degree of dominance in fieldpeaSource of variation DF Days to

flowering (no)

Days to maturity

(no)

Plant height (cm)

Primary branches/ plant (no)

Pods/ plant (no)

Seeds/ pod (no)

100-seed weight

(g)

Seed yield/ plant

(g) Replications 1 47.75* 50.98* 160.02* 4.72* 520.68* 0.02 0.35 79.67* Parents 22 112.30** 55.95** 1700.86** 3.60** 323.26** 0.29** 29.11** 105.22** Lines 19 125.52** 64.57** 1962.89** 3.81** 220.19** 0.34** 32.96** 114.84** Testers 2 31.17** 2.00 10.17 2.00** 151.17* 0.01 6.13** 26.17** Lines vs testers 1 25.45** 0.06 103.70** 2.74** 2625.67** 0.01 1.85 80.55** Parents vs crosses 1 222.78** 5.31 1062.22** 0.62 3412.92** 0.34** 45.28** 1120.24** Crosses 51 43.22** 32.80** 1807.90** 2.96** 699.61** 0.31** 23.06** 196.95** Lines 19 88.57** 84.43** 5024.11** 7.32** 917.50** 0.60** 58.71** 284.99** Testers 2 19.41** 1.58 280.03** 0.41 1377.32** 0.29** 9.11** 56.15** Lines × testers 28 21.79** 8.63** 280.21** 0.91** 554.99** 0.16** 5.97** 160.33** Error 82 1.00 1.27 8.90 0.17 29.71 0.04 0.52 3.70 2 gca 1.40 1.49 103.12 0.13 25.76 0.018 1.21 0.45 2 sca 10.40 3.68 135.66 0.37 262.64 0.057 2.72 78.31 (2 sca/2 2 gca)0.5 1.93 1.11 0.81 1.19 2.26 1.54 1.06 9.33


Table 2. Estimates of general combining ability (gca) effects of parents in fieldpeaParents Days to 50%

flowering (no)

Days to maturity

(no)

Plant height (cm)

Primary branches/ plant (no)

Pods/ plant (no)

Seeds/ pod (no)

100- seed weight

(g)

Seed yield/ plant

(g) Females (Lines) LFP 413 1.99** (83.50) 5.71** (146.50) -18.56** (55.50) -1.07 (2.50) -9.41** (33.00) 0.53** (3.40) 0.93** (23.00) -5.80** (21.00) LFP 305 0.99* (80.00) 3.54** (140.50) -16.89** (61.00) -6.07** (2.00) 5.09* (52.50) -0.02 (4.74) 0.92** (21.25) -7.72** (20.50) LFP 362 -1.68* (78.00) 0.21 (140.00) -23.39** (23.00) -0.40* (2.00) -17.91** (44.50) -0.20* (4.15) 0.52 (20.50) -7.22** (37.00) LFP 363 -0.34 (80.00) 0.04 (140.00) -20.56* (53.00) 0.10 (2.00) - 4.41* (44.50) 0.38** (3.55) 0.25 (20.50) -0.55 (28.75) LFP 202 1.99** (82.00) -3.29** (143.00) 46.11** (132.50) -0.73** (2.00) 12.76** (44.50) 0.17* (4.00) -1.62** (22.20) 3.61** (30.00) KPMR 752 2.99** (85.00) -1.46** (140.00) -15.23** (65.00) -0.07 (2.50) -5.74** (37.00) 0.80** (3.40) 3.58** (23.75) 3.45** (28.00) IFPD 5-8 8.16** (90.00) 3.21** (142.50) -13.39** (58.50) 0.10 (3.00) -9.24** (12.00) 0.38** (4.15) 1.52** (24.00) -1.55* (24.00) NDDP 5-12 -0.34 (84.00) -1.63** (142.00) -11.06** (70.00) -0.40* (4.00) -11.58** (33.00) -0.04 (3.30) 0.02 (16.50) -5.22** (16.00) KPMR 760 4.99** (86.00) 2.54** (143.00) 2.61* (75.50) -0.57** (3.50) -7.24** (52.50) -0.30** (4.05) 1.85** (24.50) 0.11 (25.50) LFP 207A -0.68 (89.00) 0.71 (143.00) 57.78** (119.00) 0.43** (2.00) 10.26** (60.50) -0.27** (3.50) 1.02** (23.00) 2.61** (36.50) LFP 41 -5.84** (78.00) 1.21** (143.00) 38.11** (123.00) 0.10 (3.00) 2.42 (41.00) -0.15 (3.05) -0.82** (18.20) 1.11 (20.50) DDR 23 -9.68** (54.00) -11.96**(119.00) -31.89** (40.00) -1.07** (1.00) 24.42** (22.50) 0.20* (3.35) -2.82** (22.75) 9.45** (17.50) EC 334160 -3.68** (71.00) -0.63 (141.00) 28.77** (115.00) -0.57** (1.50) 15.42** (42.50) -0.40** (3.25) -0.48 (19.75) 11.45** (26.00) EC 502159 -1.34* (79.00) -2.46** (140.50) 39.44** (119.50) -0.73** (2.50) -4.08 (48.00) -0.22** (3.60) 1.18** (19.00) -2.55** (31.00) EC 385246 -1.68** (77.00) -1.79** (131.00) -22.89** (64.50) -0.73** (2.50) -1.41 (36.50) -0.32** (3.45) 1.02** (24.50) 0.11 (24.00) EC 389374 1.82** (82.00) -1.13* (141.50) -38.39** (47.50) 0.93** (3.00) 5.42* (33.00) -0.18* (3.30) 1.52** (21.10) 6.95** (17.00) P 2005 (local collection) 1.66** (79.00) 4.71** (146.50) 32.77** (112.50) 4.10** (7.50) -16.41** (49.00) 0.03 (3.30) -10.23** (7.75) -18.39** (11.00) LFP 446 -3.01** (68.00) -0.46 (110.50) -11.89** (75.00) 0.43** (2.00) 8.59** (49.00) -0.12 (3.60) 1.10** (21.75) 5.11** (27.00) P 289 (Germplasm line) 1.82** (81.00) -0.476 (139.00) -12.89** (95.50) -0.23 (2.00) 19.42** (67.50) -0.08 (3.50) -4.32** (1.00) 7.11** (17.00) LFP 210A 1.82** (81.00) 3.38** (142.00) -8.56** (57.50) 0.43** (4.50) -16.41** (33.50) -0.19* (3.50) 4.85** (22.00) 2.05** (25.00) SE (gi) female 0.40 0.45 1.19 0.17 2.17 0.08 0.29 0.77 SE (gi-gi) 0.58 0.65 1.72 0.24 3.15 0.12 0.42 1.11 Males LFP 48 0.33* (74.00) 0.23** (139.00) 2.43** (77.00) -0.06 (4.50) -6.70** (56.00) -0.01 (3.60) 0.45** (23.00) 1.35** (31.00) PG 3 -0.80** (76.00) -0.12 (140.00) 0.38 (81.50) 0.12* (3.50) 4.22** (69.00) 0.09** (3.58) -0.50** (19.50) 0.51* (31.50) HFP 8909 0.47** (81.50) -0.12 (141.00) -2.82** (19.00) -0.06 (2.50) 2.47** (72.50) -0.08** (3.60) 0.052 (1.25) 0.85** (25.00) SE (gi ) males 0.13 0.15 0.17 0.05 0.70 0.03 0.09 0.25 SE (gi-gi) 0.22 0.25 0.39 0.09 1.22 0.05 0.16 0.43

Table 3. Crosses showing significant desirable sca effects for eight metric traits in fieldpeaCharacter Crosses sca effects gca of parents

DDR 23 x LFP 48 -10.33** H x L LFP 305 x LFP 48 - 3.99** L x L P 2005 x PG 3 - 3.53** L x H

Days to 50% flowering (no)

KPMR 760 x LFP 48 - 2.99** L x L P 2005 x LFP 48 - 4.23** L x M LFP 305 x LFP 48 - 2.57** L x M DDR 23 x LFP 48 - 2.57** H x M

Days to maturity (no)

NDDP 5-12 x HFP 8909 - 2.55** M x M EC 334160 x LFP 48 -29.05** L x L LFP 207A x HFP 8909 -22.85** L x H LFP 202 x HFP 8909 -14.18** L x H

Plant height (cm)

LFP 202 x LFP 48 -13.43** L x L EC 385246 x HFP 8909 1.06** L x M EC 389374 x LFP 48 0.89** H x M LFP 207A x HFP 8909 0.89** H x M

Branches/plant (no)

P 2005 x LFP 48 0.73** H x M LFP 202 x HFP 8909 46.69** H x H LFP 207A x HFP 8909 20.69** H x H LFP 413 x HFP 8909 19.36** L x H

Pods/plant (no)

P 289 x PG 3 16.78** H x H LFP 413 x HFP 8909 0.65** H x L P 2005 x LFP 48 0.47** M x M LFP 305 x PG 3 0.43** M x H

Seeds/pod (no)

LFP 446 x LFP 48 0.42** M x M LFP 202 x HFP 8909 2.85** L x M KPMR 752 x HFP 8909 2.80** H x M NDDP 5-12 x HFP 8909 2.61** M x M

100-seed weight (g)

LFP 207A x PG 3 2.17** H x L LFP 202 x HFP 8909 29.99** H x H EC 334160 x LFP 48 14.35** H x H LFP 207A x PG 3 12.33** H x M

Seed yield/plant (g)

LFP 413 x HFP 8909 8.90** L x H

Singh et al.: Combining ability for yield and its components in fieldpea 145

‘KPMR 752’, ‘IFPD 5-8’, ‘FP 289’ and ‘PG 3’ were found to begood general combiners. The genotypes ‘LFP 210A’, ‘KPMR752’, ‘LFP 413’, ‘LFP 305’, ‘IFPD 5-8’, ‘EC 502159’, ‘EC 385246’,‘EC 389394’ and ‘LFP 48’ showed significant positive gcaeffects for 100-seed weight. The gca effects of the genotypes‘EC 334160’, ‘DDR 23’, ‘EC 389374’, ‘P 289’, ‘LFP 446’, ‘LFP210A’, ‘PG 3’ and ‘HFP 8909’ were positive and significantand might be useful for identifying high yieldingrecombinants.

The crosses ‘DDR 23 × LFP 48’, ‘LFP 305 × LFP 48’, ‘P2005 × PG 3’ and ‘KPMR 760 × LFP 48’ showed significantdesirable negative sca effects for days to flowering (Table 3).The crosses ‘P 2005 × LFP 48’, ‘LFP 305 × LFP 48’, ‘DDR 23 xLFP 48’ and ‘NDDP 5-12 × HFP 8909’ showed significantdesirable sca effects alongwith desirable low mean values fordays to maturity. The crosses ‘EC 334160 × LFP 48’, ‘LFP207A × HFP 8909’, ‘LFP 202 × HFP 8909’ and ‘LFP 202 × LFP48’ showed significant sca effects alongwith desirable lowmean values for plant height. The crosses important forbranches per plant were ‘EC 385248 × HFP 8909’, ‘EC 389374 ×LFP 48’, ‘LFP 207A × HFP 8909’ and ‘P 2005 × LFP 48’ withsignificant positive sca effects. The crosses ‘LFP 202 × HFP8909’, ‘LFP 207A × HFP 8909’, ‘LFP 413 × HFP 8909’ and ‘P 289× PG 3’ recorded significant sca effects as well as high per seperformance for pods per plant. For seeds per pod, the crosses‘LFP 413 × HFP 8909’, ‘P 2005 × LFP 48’, ‘LFP 305 × PG 3’ and‘LFP 446 × LFP 48’ had significant positive sca effects forseeds per pod. The crosses ‘LFP 202 × HFP 8909’, ‘KPMR752 × HFP 8909’, ‘NDDP 5-12 × HFP 8909’ and ‘LFP 207A × PG3’ showed significant and positive sca effects for 100-seedweight. For seed yield per plant the cross combinations viz.‘LFP 202 × HFP 8909’, ‘EC 334160 × LFP 48’, ‘LFP 207A × PG 3’and ‘LFP 413 × HFP 8909’ recorded the significant positivesca effects.

The parents namely ‘DDR 23’, ‘LFP 305’, ‘LFP 48’ and‘KPMR 760’ for earliness, ‘LFP 202’, ‘LFP 413’ and ‘LFP 207A’for pods per plant, ‘LFP 413’ for seeds per pod, ‘KPMR 752’and ‘NDDP 5-12’ for 100-seed weight and ‘EC 334160’, ‘LFP202’, ‘LFP 207A’ for seed yield per plant were found goodgeneral combiners. The cross combination ‘LFP 202 × HFP8909’ was best for pods per plant, 100-seed weight, seed yieldper plant and plant height. The desirable cross combinationsincluded high × high and high × medium types of generalcombiners. The crosses like ‘LFP 202 × HFP 8909’ and ‘EC334160 × LFP 48’ for seed yield and crosses ‘LFP 202 × HFP8909’ and ‘LFP 207A × HFP 8909’ for pods per plant with highsca involving parents with good gca can be exploitedeffectively by conventional breeding methods like pedigreeselection. However, those crosses which involved one goodcombiner and other medium combiner could be exploitedthrough selection followed by intermating of segregants inearly generation.

REFERENCES

Bhardwaj RK and Kohli UK. 1998. Combining ability analysis for someimportant yield traits in garden pea (Pisum sativum L.). CropResearch, Hissar 15: 245-249.

Kempthorne O. 1957. An Introduction to Genetic Statistics. The IOWAState University Press, IOWA.

Kumar S, Srivastava RK and Singh R. 2006. Combining ability for yieldand its component traits in field pea. Indian Journal of PulsesResearch 19: 173-175.

Singh BB, Singh UP, Singh RM and Rai B.1987. Genetic analysis ofyield and yield components in field pea. Journal of AgricultureScience, Cambridge 109: 67-71.

Singh JD and Singh IP. 2003. Combining ability analysis in field pea(Pisum sativum L.). Indian Journal of Pulses Research 16: 98-100.

Singh MN and Singh RB. 1990. Estimates of additive, dominance andepistatic interaction effects for certain yield characters in pea(Pisum sativum L.). Indian Journal of Genetics and Plant Breeding50: 348-353.


Information on gene action for yield and its componentsis pre-requisite for planning of an effective breeding strategy.Yield is the end product of the action and interaction of anumber of quantitative components. Such characters are oftencontrolled by large number of genes which individually havesmall effects. The environmental contribution to the variationof these characters is also appreciable. The study of the geneaction of quantitative characters of economic value is essentialto improve the yield potential. The heterosis on the otherhand plays a significant role in improving any character ofeconomic value. In self-pollinated crops like peas, itsexploitation is most important as the crop is significant bothas grain and vegetables for the country like India. Thus inthe present investigation, an attempt has been made to studythe genetics and extent of heterosis of green pod yield andyield traits to isolate desirable recombinants involving fieldand table pea genotypes.

The material comprising four field pea varieties/strainsi.e. ‘Rachna’, ‘KPMR-65’, ‘KPMR-184’, mutant of ‘P-43’ andsix table pea varieties/strains i.e. ‘KS-136’, ‘KS-195’, ‘KS-225’, ‘KS-226’, ‘Azad P-1’ and ‘Azad P-3’, was raised incrossing block and all possible combinations were made toobtain 45 crosses. The final experiment comprising of 45genotypes, F1s and F2s alongwith their parents were sown ina Randomized Block Design in three replications at VegetableResearch Farm of Chandra Shekhar Azad University ofAgriculture and Technology, Kanpur during rabi 2003-04.Eachplot consisted of five meter row length with spacing of 45 x 15cm between rows and plants. All recommended practices werefollowed to raise a good crop. Ten random plants in each ofparents and F1s and 20 plants from each F2 per replicationswere scored for nine characters. The components analysis ofdiallel cross were carried out following Hayman (1954).

The analysis of variance indicated appreciable geneticvariability among the parents and hybrids for almost all thetraits under study. Over dominance of consistent nature wasobserved by component analysis (H1/D)1/2 for all the charactersin both the generations except for days to flowering in F1 andF2 and days to maturity and pod length in F1 only (Table 1).The presence of over dominance might be due to linkage in F2which caused an upward estimation of dominance from F2population (Moll et al. 1964), while (Mather 1955) pointed out

that over dominance might be attributed due to epistaticinteraction. Complete to over dominance was also reportedfor grain yield and its components by (Kumar et al. 2006,Singh et al. 2006).

Conversion of partial dominance into over dominancemight be attributed to gene combination, like positive allele,negative allele complementary gene action or simply correlatedgene distribution (Hayman 1954). Partial dominance was alsoreported by Srivastava et al. (1986) for days to flowering,node number up to the first pod and seed yield, (Singh et al.1986) for pods per plant, seeds per pod in F2 and for podnumber, seed number per plant, 100-seed weight and seedyield per plant (Singh et al. 2006).

The estimates of F were positive and significant basedon both the generations for days to flowering and days tomaturity and for pod length in F2. The estimate of h2 waspositive for all the traits except days to flowering in F1 andgreen pod yield in F2 generation. The significant and positivevalues of F and h2 indicated that dominant genes exhibitedsignificant role in the control of these characters viz., days toflowering and maturity in F2, plant height, number of pods perplant, pod length and harvest index in both F1 and F2 andnode number of first pod formed, number of productivebranches and green pod yield in F1 and days to flowering andmaturity in F2 only (for h2). The above findings for these traitsare in accordance with earlier reports of Koranne and Singh(1974), Sharma et al. (1977) and Verma (1978).

The proportion of positive and negative alleles in theparents (H2/4H1) was not equal to the theoretical values of0.25 in all the characters in both F1 and F2 generations whichindicated that positive and negative genes were distributedasymmetrically as also reported by Srivastava (1982).

In the present study, the ratio of (4DH1)1/2 + F/(4DH1)

1/2

– F indicated that the dominant alleles were more frequentthan recessive ones for all the characters except for plantheight, number of pods per plant and harvest index in both F1and F2 generations. Similar findings were also recorded formost of the characters studied in pea (Koranne and Singh1974, Srivastava et al. 1986)

The ratio of (h2/H2) was less than unity for all the

Short Communication

Genetical analysis and heterosis for green pod yield and its components in peaK.P. SINGH*, H.C. SINGH, B. SINGH and J.D. SINGH

Department of Genetics and Plant Breeding; C.S. Azad University of Agriculture and Technology, Kanpur-208 002; E-mail: [email protected](Received: June, 2009; Accepted: October, 2010)

*Author for correspondence, Present address : A.S.P.O., Section of Seed and Farms, C.S.A. University of Agriculture & Technology,Kanpur-208 002, India

Singh et al.: Genetical analysis and heterosis for green pod yield and its components in pea 147

character in both the generations except for plant height,number of productive branches, number of pods per plantand green pod yield per plant in F1 generation only, whichindicated that the inheritance of the characters was governedby one major gene group. The remaining characters in theirrespective generations having higher value than unityindicated that more than one gene group was involved in theinheritance of these characters. Complementary geneinteraction also seems to depress the ratio (Liang and Walter1968).

The genetic system controlling these importantquantitative traits showed a role of dominance as well as

additive gene action (Kumar et al. 2006, Singh et al. 1988).Cross combinations ‘KS 226/Azad P-1’, ‘KPMR-184/

KS-136’, ‘KS-225/Azad P-3’, ‘KS-195/KS-226’, ‘KS-195/AzadP-3’ and ‘KS-136/KS-225’ showed more than 50% (50.48 –69.82%) economic heterosis over ‘Azad P-1’ for green podyield (Table 2). The crosses showing high heterosis alsoshowed high inbreeding depression in F2 generations (25.78to 48.39%. Gupta et al. (2003) and Singh et al. (2005) alsoreported similar results.

However, few cross combinations namely, ‘KS-226/AzadP-1’, ‘KS-195/KS-225’ and ‘KS-195/KS-226’ showed higheconomic heterosis for pod yield per plant with comparatively

Pods/plant (no)

Pod length (cm)

Developed ovules/pod (no)

Harvest index (%)

Green pod yield/plant (no)

Genetic parameters

F1 F2 F1 F2 F1 F2 F1 F2 F1 F2 D 11.79

± 23.25 13.35** ± 4.19

1.79** ± 0.04

1.79** ± 0.03

0.80** ± 0.24

0.80** ± 0.13

26.82** ± 2.88

26.80** ± 2.37

1002.60** ± 92.89

1008.63** ± 55.03

H1 245.66** ± 49.49

120.23** ± 35.71

0.33** ± 0.08

1.47** ± 0.29

2.21** ± 0.52

5.63** ± 1.14

34.12** ± 6.14

146.52** ± 20.20

2376.43** ± 197.73

2185.69** ± 468.54

H2 200.94** ± 42.06

102.37** ± 30.35

0.29** ± 0.06

2.24** ± 0.25

1.65** ± 0.44

4.35** ± 0.97

30.86** ± 5.22

102.22** ± 17.16

2281.17** ± 168.05

2030.71** ± 398.20

h2 745.50** ± 28.15

29.80** ± 5.08

0.18** ± 0.04

0.38** ± 0.04

0.15 ± 0.29

0.05 ± 0.16

16.28** ± 3.49

11.63** ± 2.87

6919.85** ± 112.49

-2.68 ± 66.64

F -5.25 ± 53.64

-11.46 ± 19.35

0.00 ± 0.08

0.35* ± 0.16

0.23 ± 0.56

0.43 ± 0.62

-5.65 ± 6.66

-2.83 ± 10.95

189.78 ± 214.33

184.81 ± 253.94

E 2.14 ± 7.01

0.58 ± 1.26

0.00 ± 0.01

0.00 ± 0.01

0.01 ± 0.07

0.01 ± 0.04

0.16 ± 0.87

0.18 ± 0.72

14.33 ± 28.01

8.30 ±16.59

(H1/D)1/2 4.56 3.00 0.43 1.17 1.66 2.65 1.13 2.34 1.54 1.47 H2/4H1 0.20 0.21 0.22 0.23 0.19 0.19 0.23 0.17 0.24 0.23 (4DH1)1/2+F /(4DH1)1/2 – F

0.91 0.75 1.00 1.18 1.19 1.23 0.83 0.96 1.13 1.13

h2/H2 3.71 0.29 0.60 0.17 0.09 0.01 0.53 0.11 3.03 0.00 ‘r’ -0.70 -0.84 -0.67 0.66 -0.13 -0.07 0.62 0.54 -0.80 0.32 t2 value 6.56* 4.83* 0.72 1.19 2.79 6.19* 1.69 2.34 0.03 0.24

Table1. Contd…..


Table 1. Estimates of genetic components of variation in F1 and F2 progenies for nine characters in peaDays to flowering Days to maturity

(edible pods) Plant height

(cm) Productive branches/plant

(no) Genetic parameters

F1 F2 F1 F2 F1 F2 F1 F2 D 147.07**

±2.25 147.22**

± 2.34 172.95**

± 4.11 172.78**

± 3.34 3167.50** ± 304.18

3165.93** ± 142.30

0.19** ±0.06

0.19** ± 0.04

H1 26.90** ± 4.78

130.14** ± 19.88

46.74** ± 8.75

201.62** ± 28.47

5133.79** 647.48±

8775.41** ± 1211.56

0.82** ± 0.13

1.12** ± 0.31

H2 19.86** ± 4.06

107.66** ± 16.90

31.71** ± 7.44

152.79** ± 24.20

4179.37** ± 550.29

6582.54** ± 1029.69

0.58** ± 0.11

0.86** ± 0.26

h2 -0.07 ± 2.72

27.52** ± 2.83

0.00 ± 4.98

52.53 ** ± 4.05

5021.65** ± 368.34

2108.28** ± 172.31

1.00** ± 0.07

0.00 ± 0.04

F 52.32** ± 5.18

96.97** ± 10.78

70.22** ± 9.48

156.36** ± 15.43

-1962.85** ± 701.84

-1591.27* ± 656.64

0.24 ± 0.14

0.19 ± 0.17

E 0.55 ± 0.68

0.41 ± 0.70

0.36 ± 1.24

0.52 ± 1.01

8.80 ± 91.71

10.37 ± 42.90

0.0.1 ± 0.02

0.00 ± 0.01

(H1/D)1/2 0.43 0.94 0.52 1.08 1.27 1.66 2.11 2.40 H2/4H1 0.18 0.21 0.17 0.19 0.20 0.19 0.18 0.19 (4DH1)1/2+F /(4DH1)1/2 – F

2.42 2.08 2.28 2.44 0.61 0.74 1.87 1.53

h2/H2 0.00 0.26 0.00 0.34 1.20 0.32 1.73 0.00 ‘r’ -0.45 0.33 -0.22 0.22 -0.91 -0.89 -0.63 -0.36 t2 value 0.72 0.06 1.34 0.06 3.81 2.20 3.58 1.19


low inbreeding depression. The increase in pod yield in thesecrosses might be due to gene interaction of which substantialpart could be due to fixable gene effect i.e. additive type.Thus, these crosses may likely produce some desirabletransgressive segregants in advance generations as was alsosuggested by Brim and Cockerham (1961) and Singh et al.(1993). Further, these crosses also showed significant heterosisfor other attributes with low inbreeding depression reflectingthat more emphasis could be placed on these attributes duringselection (Kumar and Tewatia 2005) were in view of aboveresults.

Cross combinations namely, ‘KPMR-184/KS-136’, ‘KS-225/Azad P-3’, ‘KS-195/KS-226’ and ‘KS-195/Azad P-3’ showedhigh economic heterosis and comparatively high inbreedingdepression which might be due to non-allelic gene interactionsas also reported by Jatasra and Paroda (1979) in wheat crop.

REFERENCES

Brim CA and Cockerham CC. 1961. Inheritance of quantitativecharacters in soybeans. Crop Science 1: 189-190.

Gupta D, Semwal BD and Srivastava JP. 2003. Heterosis in table pea.Progressive Agriculture 3: 95-98.

Hayman BI. 1954. The theory and analysis of diallel crosses. Genetics39: 789-809.

Jatasara DS and Paroda RS. 1979. Stability for synchrony traits inwheat. Indian Journal of Genetics and Plant Breeding 39: 378-382.

Koranne KD and Singh HB. 1974. Genetic analysis of yield and yield

contributory characters in pea. Indian Journal of AgriculturalSciences 44: 294-298.

Kumar Manoj and Tewatia AS. 2005. Heterosis in pea (Pisum sativumL.) Haryana Agriculture University Journal Research 34: 27-33.

Kumar Subhash, Srivastava RK and Singh Ranjeet. 2006. Combiningability for yield and its component traits in field pea. Indian Journalof Pulses Research 19: 173-175.

Liang GHL and Walter TL. 1968. Heritability estimates and gene effectsfor agronomic traits in grain sorghum. Crop Science 8: 77-80.

Mather K. 1955. The genetical basis of heterosis. Proceedings RoyalSociety of Botany 144: 143-150.

Moll RH, Lindsey MF and Robinson HF. 1964. Estimates of geneticvariances and level of dominance in maize. Genetics 49: 411-423.

Sharma RP, Nandpuri KS and Kumar JC. 1977. Mode of inheritance ofyield, number of pods, days to first flowering and plant height inpea. Indian Journal of Horticulture 34: 157-162.

Singh AP, Singh GP and Singh AK. 1993. Variability studies in tall anddwarf peas. Crop Research 6: 239-242.

Singh HC, Srivastava RL and Singh Rajendra. 2006. Additive, dominanceand epistatic components of variation for some metric traits infield pea. Indian Journal of Pulses Research 19: 170-172.

Singh HG, Singh V and Srivastava RL. 1989. Additive, dominance andepistatic components of variation for economic traits in field pea.In: National Symposium of Recent Advances on Genetics and PlantBreeding Research in India. Nov. 15-16, 1989, BHU Varanasi, VI-14, 0-26.

Singh HG, Tyagi HN and Mishra LB. 2005. Combining ability andheterosis for grain yield and some yield components in pea (Pisumsativum L.). Pakistan Journal of Biological Science 8: 1447-1452.

Singh KN, Santoshi Singh U and Singh HG. 1986. Genetic analysis ofyield components in pea. Indian Journal of Agricultural Sciences56: 757-764.

Singh UP, Singh BB, Singh RM and Singh RK. 1988. Additive, dominanceand epistatic components of variation for economic traits in fieldpea. Indian Journal of Pulses Research 1: 1-5.

Srivastava RL. 1982. Genetic parameters of breeding values in pea.Ph.D. Thesis, C.S.A. University of Agriculture and Technology,Kanpur.

Srivastava RL, Santoshi US and Singh HG. 1986. Diallel and partialdiallel analysis of some yield components in pea. Genetika 18: 35-41.

Verma HS. 1978. Genetic analysis of yield and its components in tablepea. Ph.D. Thesis, Kanpur University, Kanpur.

Table 2. Top ten crosses for economic heterosis in pea

I: Days to flowering, II: Days to maturity, III: Plant height, IV: Numberof productive branches/plant, V: Number of pods/plant, VI: Pod length,VII: Number of developed ovules/pod, VIII: Harvest index**Significant at P = 0.01

Name of the cross

Economic heterosis

(%)

Inbreeding depression

(%)

Characters exhibiting desirable significant economic heterosis

KS-226 × Azad P-1 69.82** 25.78** IV, V, VI, VII KPMR-184 × KS-136 66.90** 48.39** IV, V, VII KS-225 × Azad P-3 64.52** 38.11** I, IV, V KS-195 × KS-226 64.21** 29.96** IV, V KS-195 × Azad P-3 55.40** 34.71** IV, V, VII KS-136 × KS-225 50.48** 27.49** IV, V, VI, VII KPMR-65 × KS-225 49.31** 30.77** IV, V KS-225 × Azad P-1 42.12** 20.54** IV, V, VI, VII, Rachna × Azad P-3 39.93** 37.00** IV, V KS-195 × KS-225 39.07** 12.33** IV, V


Short Communication

Integrated nutrient management in lentil with organic manures, chemical fertilizersand biofertilizersGURIQBAL SINGH, NAVNEET AGGARWAL and VEENA KHANNA

Department of Plant Breeding and Genetics, Punjab Agricultural University, Ludhiana 141 004, Punjab,India; Email: [email protected](Received: July, 2010; Accepted: September, 2010)

Nutrient application is essential to improve growth andyield of lentil (Lens culinaris Medikus). Due to intensivecropping systems, soils are becoming deficient in macro aswell as micro nutrients. The organic matter content in the soilis declining which also affects the soil microflora. Hence thelogical alternative is to increase the usage of organic manuresand biofertilizers. Lentil is known to respond to applicationsof nutrients (Singh et al. 2000), farmyard manure (FYM) (Singhet al. 2003) and Rhizobium inoculation (Singh et al. 2000).Nutrient requirement of the crop can be met by supplyingnutrients through chemical fertilizers, organic manures suchas FYM or vermicompost or through the use of biofertilizerssuch as Rhizobium and Phosphate Solubilizing Bacteria (PSB).However, the information on integrated use of organicmanures, chemical fertilizers and biofertilizers on the growth,symbiotic parameters and yield of lentil are meagre.

A field experiment was conducted during rabi (winter)season 2008-09 at the Punjab Agricultural University, Ludhianato study the effect of organic manures, chemical fertilizersand biofertilizers on symbiotic efficacy, growth and yield oflentil. The soil of the experimental field was loamy sand withpH 8.0 and testing low in organic carbon (0.30%) and availablenitrogen (110 kg/ha) and medium in available phosphorus (15.2kg/ha) and potash (295 kg/ha).

Ten treatments, given in Tables 1 and 2 were tested in arandomized block design with three replications. In thetreatment of recommended dose of fertilizers (RDF) 20 kg N/ha and 40 kg P2O5/ha was applied through urea (46% N) andsingle superphosphate (16% P2O5), respectively. In Rhizobium+ PSB treatments, seed was inoculated with Rhizobiumleguminosarum and Bacillus sp. each @ 500 g/ha seed usingminimum amount of water. Prior to sowing the inoculated seedwas shade dried for about one hour. Chemical fertilizers andorganic manures (FYM and vermicompost) were applied asper the treatments just before sowing. The cultivar ‘LL 699’was sown on 22 November 2008 in rows 22.5 cm apart using aseed rate of 35 kg/ha. Weeds were managed manually by handweeding at 30 days after sowing (DAS) and 60 DAS. Noinfestation of any insect pests or disease was observed andtherefore no chemicals were sprayed.

Data on number and dry weight of nodules/plant wererecorded 60 and 90 DAS by digging five plants from eachplot. Number of nodules/plant were counted and then dried

to get nodule weight/plant. Five plants were sampled 90 DASfor measuring shoot dry weight. Dry weight of the nodulesand shoots were recorded by drying samples in an oven at60oC for 72 hours. Chlorophyll content in the leaves weremeasured at 90 DAS as per the method described by Withamet al. (1971). At maturity, data on plant height, pods/plant,seeds/pod, 100-seed weight, biological yield and grain yieldwere recorded. Harvest index was calculated by dividingeconomical yield by total biomass production. Net returns aswell as B: C ratio were also worked out. All data were subjectedto analysis of variance.

The results showed that all the treatments significantlyenhanced the number and dry weight of nodules as comparedto the control where no organic manure, chemical fertilizer orbiofertilizer was applied (Table 1). The treatments which hadreceived Rhizobium inoculation recorded significantly highernumber and dry weight of nodules than those where noRhizobium inoculation was done. Rhizobium inoculation isknown to improve nodulation in lentil (Chowdhury et al. 1998).Furthermore, in these treatments, apart from Rhizobium, PSBwas also used. PSB is known to solubilize the nativephosphorus (El-Sayed 1999) and enhance its availability tothe plants. This increased availability of the phosphorus mighthave helped in better nodulation. Improved nodulation wasalso observed in those treatments where Rhizobium was notapplied but chemical fertilizers, FYM or vermicompost wereapplied alone or in combination. The organic manures areknown to decrease P adsorption/fixation and enhance Pavailability. Thus resulting in better root growth andconsequently exploitation of greater soil volume fornodulation. Similar trend was also observed in terms of noduledry weight. Increased nodule biomass was recorded whencombinations of chemical and organic fertilizers was used.More pronounced effects of Rhizobium and PSB in thepresence of added fertilizers have been reported (El-Sayed1999). Rao and Patra (2009) have also stated that recommendeddose of fertilizers has no effect on microbial proliferation andperformance, as also observed in the present study.

The number of nodules and their dry weight was higherat 90 DAS compared with 60 DAS, which could be due toimproved plant growth (root as well as shoot) with age. Theperiod of 60 DAS occurred on 22 January, 2009 when the cropwas exposed to very low temperature under Punjab conditions


and a month later (90 DAS) on 22 February as the temperatureincreased, the improvement in nodulation was also observed.So the better nodulation recorded at 90 DAS compared to 60DAS could be due to improved plant growth with age as wellas better environmental conditions in terms of warmertemperature.

Shoot dry weight and chlorophyll content increasedwith application of various organic manures, chemical fertilizersand biofertilizers, though the differences were non-significanton a small unit basis (per plant for shoot dry weight and pergram leaf weight for chlorophyll content). However, on wholecrop area basis improvements in these parameters seem to bequite meaningful.

Pods/plant was significantly improved with theapplication of various nutrients through different sourceseither singly or in combination over the control (Table 2).Plant height, seeds/pod and 100-seed weight were notinfluenced significantly by different treatments. However,numerical increases over the control were observed in thecase of plant height and 100-seed weight. Pods/plant andplant height of lentil are known to be improved with he use ofRhizobium inoculation + N + P2O5 (Chowdhury et al. 1998)and of Rhizobium inoculation + P2O5 (Singh et al. 2001).

The application of RDF increased the grain yield of lentilsignificantly (19.7%) over control treatment (Table 2). Theapplication of FYM @ 5 t/ha or vermicompost @ 2 t/ha tendedto increase the grain yield over control, however, the increasewas not significant. Inoculation of seed with Rhizobium +PSB did not increase the grain yield significantly over control,which could possibly be due to the presence of effectivenative rhizobia in the soil where lentil crop had been grownduring previous years as well. It has been reported thatRhizobium inoculation may not always have significant effecton grain yield (Bhatt and Chandra 2009). However, Rhizobium+ PSB with inorganic as well as organic nutrient sourcesenhanced the grain yield. FYM @ 5 t/ha is known to increasethe grain yield of lentil (Singh et al. 2003).

Integrated use of RDF, FYM or vermicompost andbiofertilizers (Rhizobium + PSB) tended to increase the grainyield further over their sole applications, which could be dueto the combined and synergistic effect. Furthermore, manurescontain high amounts of organic matter which increases themoisture retention of the soil and improves dissolution ofnutrients particularly phosphorus. High grain yields of lentilhave been reported with the combined use of Rhizobium +phosphorus (Singh et al. 2001). Similar effects were observedin case of biological yield. Nutrient applications generally

Table 1. Effect of INM on nodule parameters, shoot weight and chlorophyll content in lentil

Nodules/plant (no)

Nodule dry weight (mg/plant)

Shoot dry weight

(g/plant)

Chlorophyll content (mg/g fresh weight of

leaves)

Treatment

60 DAS 90 DAS 60 DAS 90 DAS 90 DAS 90 DAS Control (no organic manure, chemical fertilizer or biofertilizer)

11.0 14.8 32.2 35.5 2.90 1.915

RDF (20 kg N + 40 kg P2O5/ha) 14.8 17.0 36.6 38.6 3.26 2.890 FYM 5 t/ha 13.6 16.2 33.9 37.3 3.05 2.321 Vermicompost 2 t/ha 15.9 16.8 36.8 37.8 3.13 2.418 RDF + FYM 5 t/ha 15.3 18.0 36.9 39.0 3.30 2.800 RDF + Vermicompost 2 t/ha 16.8 18.3 37.9 40.3 3.35 2.910 Rhizobium + PSB 19.0 24.0 39.8 45.5 3.06 2.465 RDF + Rhizobium + PSB 20.9 26.2 40.3 46.8 3.23 2.680 FYM 5 t/ha + Rhizobium + PSB 20.0 25.0 39.5 45.9 3.30 2.710 Vermicompost 2 t/ha + Rhizobium + PSB 22.8 25.6 41.6 47.6 3.21 2.790 CD (P=0.05) 1.7 2.0 2.5 3.7 NS NS

Table 2. Effect of INM on plant growth, yield attributes and yield of lentilTreatment Plant

height (cm)

Pods/ plant (no)

Seeds/ pod (no)

100-seed weight

(g)

Grain yield

(kg/ha)

Biological yield

(kg/ha)

Harvest index (%)

Net returns (Rs/ha)

B:C ratio

Control (no organic manure, chemical fertilizer or biofertilizer)

32.9 44.0 1.5 2.40 947 2963 32.0 19310 3.12

RDF (20 kg N + 40 kg P2O5/ha) 38.9 54.6 1.5 2.50 1134 3175 35.7 24020 3.40 FYM 5 t/ha 33.1 51.7 1.4 2.43 1035 3128 33.1 21550 3.27 Vermicompost 2 t/ha 35.4 52.1 1.4 2.53 1005 2939 34.2 20550 3.14 RDF + FYM 5 t/ha 37.3 60.2 1.4 2.50 1181 3410 34.6 24930 3.37 RDF + Vermicompost 2 t/ha 39.1 51.9 1.5 2.50 1135 3292 34.5 23450 3.21 Rhizobium + PSB 36.2 47.0 1.4 2.50 987 2869 34.4 20410 3.22 RDF + Rhizobium + PSB 37.6 60.8 1.4 2.73 1270 3833 33.1 28000 3.77 FYM 5 t/ha + Rhizobium + PSB 35.3 55.1 1.4 2.66 1141 3668 31.1 24630 3.57 Vermicompost 2 t/ha + Rhizobium + PSB 38.9 52.3 1.5 2.63 1129 3363 33.6 24170 3.49 CD (P=0.05) NS 4.9 NS NS 172 542 NS 968 0.18

Singh et al.: Integrated nutrient management in lentil with organic manures, chemical fertilizers and biofertilizers 151

tended to improve the harvest index. Net returns as well as B:C ratio improved with the application of nutrients throughvarious sources.

The results showed that the application of RDF, FYM5t/ha or vermicompost 2t/ha produced similar seed yield oflentil. Therefore, depending upon the resources available withthe farmers, sources of nutrient could be selected.

REFERENCES

Bhatt P and Chandra R. 2009. Interaction effect of Mesorhizobiumciceri and rhizospheric bacteria on nodulation, growth and yield ofchickpea. Journal of Food Legumes 22: 137-139.

Chowdhury AK, Newaz MA, Samanta SC, Huda S and Ali M. 1998.Response of lentil genotypes to cultural environments onnodulation, growth and yield. Bangladesh Journal of Scientific andIndustrial Research 33: 258-262.

El-Sayed SAM. 1999. Influence of Rhizobium and phosphate-solubilizingbacteria on nutrient uptake and yield of lentil in the New Valley

(Egypt). Egyptian Journal of Soil Sciences 39: 175-186.

Rao DLN and Patra AK. 2009. Soil microbial diversity and sustainableagriculture. Journal of the Indian Society of Soil Science 57: 513-530.

Singh G, Sekhon HS and Sharma P. 2001. Effect of Rhizobium, vesiculararbuscular mycorrhiza and phosphorus on the growth and yield oflentil (Lens culinaris) and fieldpea (Pisum sativum). Environmentand Ecology 19: 40-42.

Singh ON, Sharma M and Dash R. 2003. Effect of seed rate, phosphorusand FYM application on growth and yield of bold seeded lentil.Indian Journal of Pulses Research 16: 116-118.

Singh YP, Chauhan CPS and Gupta RK. 2000. Effect of sulphur,phosphorus and inoculation on growth, yield and sulphur utilizationby lentil (Lens culinaris). Indian Journal of Agricultural Sciences70: 491-493.

Witham PH, Baidyes DF and Delvin RM. 1971. Chlorophyll absorptionof spectrum and quantitative determination. In: Experimental PlantPhysiology, Van Nastrand Reinhoed Company, New York. pp. 51-56.


Lentil is mostly planted after aman (kharif) rice as arelay (utera or paira) crop in major lentil growing areas (Dasand Das 1998, Gupta and Bhowmick 2005). Availability of soilmoisture is must at the time of sowing seeds for their propergermination, better emergence and early establishment (Sahaand Maharana 2005). Timely planting is, therefore, the keyfactor to better utilize the residual soil moisture on rice-fallows.Seed priming is another technology to obtain better plantstand and high crop yield (Ali et al. 2005a). Pre-sowing soakingof seeds with KH2PO4, Na2HPO4, etc. or simple water wasearlier reported to improve seed germination, seedling vigorand root growth early in the season, resulting in goodestablishment, better drought tolerance and more yield of cropplants (Solaimalai and Subburamu 2004). There is a limitedscope for agronomic manipulation under rice-utera systemthough it has potential for increasing cropping intensity inconsiderable areas that remain idle after aman rice (Rautaray2008). Information on the effect of planting time and seedpriming in rainfed lentil under this system is scanty. Keepingthis background in view, the present investigation was initiatedto identify a suitable planting time and seed priming methodfor enhancing yields of lentil under utera cultivation.

A two-year field study was conducted during rabiseason of 2003-04 and 2004-05 at the Pulses and OilseedsResearch Sub-station, Beldanga, Murshidabad, West Bengal,India, located at 23°55/ N latitude and 88°15/ E longitude withan altitude of 19.0 m above MSL. The soil of the experimentalsite was clay loam having pH 7.6, organic carbon 0.30%,available P2O5 67 kg/ha and available K2O 117 kg/ha. Twodifferent times of planting viz. 7 and 15 days before rice harvest(DBRH), and four levels of seed priming viz. no seed soaking,seed soaking in water for 6 hours, seed soaking in 2% KH2PO4solution for 6 hours and sprouted seeds were tested in afactorial randomized block design with three replications.Individual plot size was 4 m x 3 m. The crop variety Subrata(WBL 58) was used for study. A basal dose of N: P2O5: K2O: S@ 20:40:20:20 kg/ha was given at 3 days prior to lentil sowingin between the rows of rice crop plants, whereas the previousrice crop was fertilized with N: P2O5: K2O @ 60:30:30 kg/ha andharvested on November 28 and 19 in 2003 and 2004,respectively. As per the treatments, seed priming was done

before sowing of lentil seeds which were broadcast using arecommended seed rate of 50 kg/ha (Ali et al. 2005b) in thestanding aman rice crop without any land preparation. Otherrecommended practices (Bhowmick et al. 2005) were followedmeticulously to raise the crop. Treatment-wise harvesting wasdone on March 11-17 and 9-16 in 2004 and 2005, respectively.Data on plant height, yield attributes and seed yield wererecorded at harvest.

Time of planting had a significant influence on plantstand, pods/plant and seed yield in the first year (2003-04),whereas no significant difference in respect of all theparameters studied was recorded in the second year (2004-05). Regardless of seed priming, highest seed yields were,however, recorded in the crop sown at 15 DBRH during boththe years of study (Table 1). This might be due to the fact thatsowing at 15 DBRH could enable better and earlierestablishment of lentil seedlings because of an adequateavailability of soil moisture which otherwise would quickly bedepleted once the rice crop was harvested. Saha and Maharana(2005) also advocated sowing of utera crops at about 2-3weeks before harvesting of rice preferably at dough stage.Sowing at 7 DBRH did not show any remarkable improvementin growth and yield attributes along with seed yield (Table 1).

Seed yield and most of the yield attributes differedsignificantly due to various seed priming methods during boththe years of study (Table 1). Use of sprouted and KH2PO4soaked seeds recorded significantly the highest number ofpods/plant. Higher plant height, better plant stand and morenumber of seeds/pod as well as 100-seed weight were alsoregistered under these treatments which ultimately exhibitedyield advantages of 30.0 and 19.6%, respectively, comparedwith no soaking. Next in order was soaking of seeds in water,registering an average of 13.7% higher seed yield over nosoaking. Better performance of crop plants under seed primingtreatments could be attributed to their good establishment(Solaimalai and Subburamu 2004). Ali et al. (2005a) alsoreported that seed priming in water for a short period of 2hours and non-priming were equally ineffective as smallseeded lentil having a hard testa would require a longer timefor water to reach the cotyledon and embryos.

Short Communication

Effect of planting time and seed priming on growth and yield of lentil under rice-utera systemMALAY K. BHOWMICK*

Pulses and Oilseeds Research Station, Berhampore 742 101, Murshidabad, West Bengal, India;E-mail: [email protected](Received: April, 2010; Accepted: September, 2010)

*Present Address: Rice Research Station, Chinsurah (R.S.) 712 102, Hooghly, West Bengal, India

Bhowmick: Effect of planting time and seed priming on growth and yield of lentil under rice-utera system 153

Thus, from the above study, it can be concluded thatsowing of properly primed (either sprouted or KH2PO4 soaked)seeds at 15 days before rice harvest would be a promisinglow-cost technology for growing lentil in rice-fallows underrainfed utera condition.

REFERENCES

Ali MO, Sarker A, Rahman MM, Gahoonia TS and Uddin MK. 2005a.Improvement of lentil yield through seed priming in Bangladesh.Journal of Lentil Research 2: 54-59.

Ali MO, Sarker A, Rahman MM and Gahoonia TS. 2005b. Lentil as arelay crop in rice field: a key technology for lentil production inBangladesh. Journal of Lentil Research 2: 64-68.

Bhowmick MK, Aich A, Aich SS, Shrivastava MP, Gupta S and Man GC.

2005. Crop diversification through paira (utera) cropping withrabi pulses. SATSA Mukhapatra – Annual Technical Issue 9: 43-60.

Das NR and Das AK. 1998. Production potentiality and economics ofrainfed winter paira crops after transplanted kharif rice in WestBengal. Advances in Agricultural Research in India IX: 77-81.

Gupta S and Bhowmick MK. 2005. Scope of growing lathyrus and lentilin relay cropping systems after rice in West Bengal, India. Lathyrusand Lathyrism Newsletter 4: 28 – 33.

Rautaray SK. 2008. Productivity and economics of rice based uteracrops for lower Assam. Journal of Food Legumes 21: 51-52.

Saha S and Maharana Monalisa. 2005. Utera cultivation - A viabletechnology option for rainfed shallow lowland of coastal Orissa.Indian Farming 54: 8-9 & 10.

Solaimalai A and Subburamu K. 2004. Seed hardening for field crops - Areview. Agricultural Reviews 25 : 129-140.

Table 1. Effect of planting time and seed priming on growth, yield attributes and seed yield of lentil under rice-utera systemduring 2003-04 and 2004-05

DBRH: Days before rice harvest; NS: Not significant

Plant height (cm) Plant stand (‘000/ha) Pods/plant Seeds/pod 100-seed weight (g) Seed yield (kg/ha) Treatments 2003-04 2004-05 2003-04 2004-05 2003-04 2004-05 2003-04 2004-05 2003-04 2004-05 2003-04 2004-05

Planting time 7 DBRH 36.0 33.6 841.7 734.2 64.3 51.1 1.6 1.9 1.8 1.8 1162.2 1078.8 15 DBRH 37.9 34.8 940.0 790.8 77.0 53.4 1.7 1.9 2.0 1.9 1232.3 1130.0 S.E.m± 0.7 0.5 28.0 20.0 1.5 2.0 0.0 0.0 0.1 0.0 13.5 33.6 C.D. (P=0.05) NS NS 84.9 NS 4.5 NS NS NS NS NS 40.8 NS Seed priming No soaking 34.2 32.9 773.3 657.5 62.0 48.2 1.6 1.8 1.8 1.8 1018.8 981.7 Water soaking 34.9 33.6 855.0 739.8 69.6 49.6 1.7 1.9 1.9 1.8 1174.8 1099.2 KH2PO4 soaking 36.5 33.9 928.3 804.2 73.7 54.5 1.7 1.9 1.9 1.9 1265.3 1126.7 Sprouted seeds 42.1 36.5 1006.7 848.5 77.2 56.6 1.8 1.9 2.1 2.0 1329.8 1210.0 S.E.m± 1.1 0.6 39.6 22.4 2.1 2.1 0.1 0.1 0.1 0.0 19.0 34.6 C.D. (P=0.05) 3.2 1.3 120.0 46.7 6.4 4.3 0.2 NS NS 0.1 57.7 72.1


Urdbean (Phaseolus mungo L.) is an important pulsecrop grown in different parts of the country. It is rich in protein,amino acids, vitamins and minerals. Urdbean is being grownby the farmers of Southern Rajasthan in recent years in placeof traditional pulses like greengram and cowpea because ofits higher market value. Suitable urdbean variety, optimumsowing time and fertilizer sources are the key inputs for gettinghigher yield under this region. An effort was therefore, madein this study to optimize the agronomic management practicesfor enhancing urdbean productivity under sub-humidsouthern plain and Arawali hills agroclimatic zone of Rajasthan.

A field experiment was conducted at the InstructionalFarm, Rajasthan College of Agriculture, MPUAT, Udaipurduring kharif 2006. Experiment was laid out in a factorialrandomized block design. There were 18 treatmentcombinations consisting of three urdbean varieties (Barkha,TAU-1 and T-9), two dates of sowing (7th July i.e. onset ofmonsoon and 27th July i.e. 20 days after first sowing) andthree levels of fertilizer (0 N + 0 P2O5 + Rhizobium + PSB, 10 kgN + 20 kg P2O5/ha + Rhizobium + PSB and 20 kg N + 40 kgP2O5/ha) with three replications. The soil of experimental sitewas clay-loam in texture with pH 8.1. The soil was higher inavailable nitrogen (340.1kg/ha), medium in phosphorus (21.5kg/ha) and high in potassium (292.8 kg/ha) contents. Seedswere inoculated as per treatments and sown in row spacing of30 cm. Doses of N and P2O5 were applied as basal according totreatments in the form of DAP and urea, respectively. Datawere collected viz. plant height (cm), number of pods/plant,number of seeds/pod, 1000-seeds weight, seed yield, haulmyield and nutrient content and uptake (N, P).

Among varieties, Barkha recorded significantly higherseed yield (1103 kg/ha) compared to T-9 and TAU-1. Theincrease in seed yield of Barkha over T-9 and TAU-1 was to anextent of 9.8 per cent and 23.1 per cent, respectively. This isdue to longer maturity period of Barkha (85 days) over othervarieties. Variety Barkha obtained significantly higher haulmyield (2254 kg/ha) over T-9 (1818 kg/ha) and TAU-1 (1694 kg/ha). The higher seed yield of Barkha over other genotypes isattributed to better yield components (number of pods/plant,number of seeds/pod and 1000-seed weight) (Table 1).

The nitrogen and phosphorus content in seed (3.25 and0.6 per cent, respectively) were higher in Barkha over T-9 (3.25

Short Communication

Effect of sowing time and fertilization on productivity and economics of urdbeangenotypesS.S. RATHORE, L.N. DASHORA and M.K. KAUSHIK

Department of Agronomy, Rajasthan College of Agriculture, Maharana Pratap University of Agriculture andTechnology, Udaipur 313 001, Rajasthan, India; E-mail: [email protected](Received: March, 2009; Accepted: September, 2010)

and 0.58 per cent) and TAU-1 (3.17 and 0.53 per cent). Thehigher nitrogen and phosphorus uptake were also significantlyobtained by Barkha (87.8 kg/ha and 13.18 kg/ha, respectively)over T-9 (74.40 kg/ha and 10.83 kg/ha) and TAU-1 (66.70 kg/haand 8.96 kg/ha). Higher nutrient uptake in Barkha over T-9and TAU-1 is attributed to long duration and higher seedyield. Singh and Singh (2000) and Yadahalli and Palled (2004)also reported similar results.

Among the agronomic practices of field crops, sowingat optimum time is an important non-monetary input that resultsin considerable increase in the seed yield under rainfedconditions. This means a favourable soil and climatic conditionare made available for the expression of genetic potential.Urdbean varieties sown at onset of monsoon (7th July) recordedmaximum seed yield (1185 kg/ha) when compared to crop sownon 27th July (20 days after first sowing). The crop sown on 7th

July registered 45 per cent higher yield over crop sown on 27th

July. Similarly, urdbean sown on 7th July recorded significantlyhigher haulm yield (3415 kg/ha) over 27th July (2432 kg/ha).The onset of monsoon sown crop (7th July) got adequate soilmoisture particularly during its flowering and pod filling stagesin August and September months as a result of rainfall. Thehigher seed yield in onset of monsoon sown crop can also beattributed to higher values of yield components over the latesown crop. Higher harvest index (34.8 per cent) was also noticedin early sown crop over late sown crop.

There was considerable increase in the values of yieldattributing characters (number of pods/plant, number of seeds/pod and 1000-seed weight) in onset of monsoon sown cropcompared to crop sown late (27th July). Higher seed yield ofurdbean from early sown crop was also reported by Singhand Singh (2000), Panwar and Sharma (2004), Yadahalli andPalled (2004) and Yadahalli et al. (2006). Significantly higher Nand P content in seed (3.23 and 0.58 per cent, respectively)were obtained by the onset of monsoon sown crop over latesown crop. Similarly, significantly higher N uptake (89.75 kg/ha) and P uptake (13.01 kg/ha) were obtained by the onset ofmonsoon sown crop over late sown crop. This is mainlyattributed to better conditions for nutrient availability in earlymonsoon period and leading to higher biomass production(seed and haulm yield) by onset of monsoon sown crop overlate sown crop. The results agree with the findings of Singh

Rathore et al.: Effect of sowing time and fertilization on productivity and economics of urdbean genotypes 155

and Singh (2000), Patel et al. (2004) and Yadahalli and Palled(2004).

The seed and haulm yield, yield components, nutrientcontent and uptake (N and P) of urdbean were obtainedsignificantly higher with 20 kg N + 40 kg P2O5/ha over 10 kg N+ 20 kg P2O5/ha + Rhizobium + PSB and 0 N: 0 P2O5 +Rhizobium + PSB. Similar results were reported by Singh andSingh (2004) and Kumar and Elamathi (2007).

Net return were maximum in Barkha sown on 7th Julywith 20 kg N + 40 kg P2O5 /ha (38672.55 Rs./ha) followed byBarkha sown on 7th July with 10 kg N + 20 kg P2O5 /ha +Rhizobium + PSB. This can be attributed to higher urdbeanyield in these treatment combinations over others. However alowest net return was realized by the urdbean variety TAU-1sown on 27th July with 0 N: 0 P2O5 + Rhizobium + PSB (Table1). This mainly attributed to lower gross returns and high costof cultivation in this treatment combination as a result ofconsiderable reduction in urdbean yield due to moisture stressand pest attack.

Higher benefit cost ratio (4.68) was obtained in theurdbean variety Barkha sown on 7th July with 20 kg N + 40 kgP2O5/ha. This is mainly due to higher net returns as a result ofhigher seed yield over other treatment combinations. Theminimum benefit cost ratio (1.32) was obtained in urdbeanvariety TAU-1 sown on 27th July with 0 N: 0 P2O5 + Rhizobium+ PSB which can be attributed to minimum net returns as aresult of drastic reduction in urdbean yield and relatively highercost of cultivation in this treatment combination.

Thus, it can be inferred that urdbean genotype Barkha

performed better than other genotypes. However, sowing withonset of monsoon (7th July) and 20 kg N + 40 kg P2O5 foundsuperior than other practices in southern plains and Arawalihills of Rajasthan.

REFERENCES

Kumar A and Elamathi S. 2007. Effect of nitrogen levels and Rhizobiumapplication methods on yield attributes, yield and economics ofurdbean (Vigna mungo L.). International Journal of AgriculturalSciences 3: 179-180.

Patel JJ, Mevada KD and Chotaliya RL. 2004. Response of summermungbean to dates of sowing and levels of fertilizers. Indian Journalof Pulses Research 17: 143-144.

Panwar R and Sharma BB. 2004. Effect of planting date, seed rate androw spacing on yield and yield attributes of bold seeded mungbeanduring spring summer season. Indian Journal of Pulses Research 17:45-46.

Singh AK and Singh VK. 2004. Effect of row spacing and nitrogenmanagement practices on rainy season urdbean under late sowncondition. Indian Journal of Pulses Research 17: 89-90.

Singh DK and Singh VK. 2000. Growth and nitrogen uptake pattern ofpromising urdbean genotypes under different sowing dates andplanting densities during rainy season. Annals of AgriculturalResearch 21: 456-458.

Yadahalli GS and Palled YB. 2004. Response of urdbean genotypes todates of sowing and phosphorus levels in Northern TransitionalTract of Karnataka. Karnataka Journal of Agricultural Sciences 17:215-219.

Yadahalli GS, Palled YB and Hiremath SM. 2006. Effect of sowingdates and phosphorus levels on growth and yield of black gramgenotypes. Karnataka Journal of Agricultural Sciences 19: 682-684.

Table 1. Yield components, yield, nutrient content, uptake and economics of urdbean as influenced by genotypes, dates of sowingand fertilizer sources

*DAFS: Days after first sowing, COC: Cost of cultivation, Selling price, Seed: Rs. 3000/q, Haulm: Rs. 135/q

Nutrient content

(%)

Nutrient uptake (kg/ha)

Treatments Pods/ Plant (no)

Seeds/ Pod (no)

1000- seeds

weight (g)

Seed Yield

(kg /ha)

Haulm yield

(kg/ha) N P N P

COC Net return

B/C ratio

Varieties Barkha 22.83 5.89 43.50 1103 2254 3.25 0.60 87.81 13.18 7889 28244 3.58 TAU-1 22.22 3.94 38.22 896 1694 3.17 0.53 66.70 8.96 7920 21304 2.69 T-9 21.22 4.11 41.08 1005 1818 3.22 0.58 74.40 10.83 7874 24724 3.14 SEm+ 0.18 0.12 0.18 20 41 0.02 0.01 1.59 0.23 - 641 0.09 CD (P=0.05) 0.52 0.34 0.51 57 117 0.05 0.02 4.50 0.66 - 1819 0.25 Sowing time 7th July 22.26 5.11 41.20 1185 2230 3.23 0.57 89.75 13.01 7890 30691 3.89 20 DAFS* 20.59 4.19 40.67 817 1614 3.20 0.56 62.85 8.97 7909 18824 2.38 SEm+ 0.15 0.10 0.15 16 34 0.02 0.004 1.29 0.186 - 523 0.07 CD (P=0.05) 0.37 0.24 0.36 40 83 NS NS 3.18 0.458 - 1286 0.18 Fertilizer sources 0 N : 0 P2O5 + Rhizobium + PSB 19.39 3.44 40.27 885 1710 3.09 0.48 64.74 7.71 7480 21392 2.86 10 kg N + 20 kg P2O5/ha + Rhizobium + PSB 21.33 4.50 41.14 1032 1938 3.19 0.56 77.20 10.98 7900 25675 3.25 20 kg N + 40 kg P2O5/ha 23.56 6.00 41.39 1087 2119 3.35 0.66 86.96 14.28 8244 27205 3.30 SEm+ 0.18 0.12 0.18 20 41 0.02 0.01 1.59 0.23 - 641 0.09 CD (P=0.05) 0.52 0.34 0.51 57 117 0.05 0.02 4.50 0.66 - 1819 0.25


Short Communication

Effect of different soil moisture regimes on biomass partitioning and yield of chickpeagenotypes under intermediate zone of J&KANJANI KUMAR SINGH, S.B. SINGH, A.P. SINGH*, AWNINDRA K. SINGH, S.K. MISHRA andA.K. SHARMA

Regional Agricultural Research Station, (SKUAST-J), Tandwal, Rajouri 185 131, India; *Krishi Vigyan Kendra,SKUAST-J, Rajouri 185 131, India; E-mail: [email protected](Received: January, 2010; Accepted: August, 2010)

Chickpea (Cicer arietinum L.) is most important pulsecrop in the Indian sub -continent. It is generally grown onstored soil moisture, making terminal drought stress a majorconstraint to productivity. A considerable area of about 43,435ha remains unutilized during rabi season in most parts of theintermediate zone and foothills of the Shivalik ranges insubtropical rainfed area of Jammu region especially after theharvest of long duration rice and maize crops. Chickpea canbe a good alternate crop under these conditions to encouragedouble cropping in otherwise mono-cropped area. As thetemperature during sowing time varies in different growingareas of Jammu province due to variable agro-climaticconditions so there is a requirement of chickpea genotypesthat can perform well across these regions. On the other handwater deficit is another constraint in the area during cropgrowth. However, the influence of water deficit on distributionof assimilate depends on stage of the growth and relativesensitivity of various plant organs to water deficit. Greaterproportions of photosynthates are allocated to pods andseeds when the crop is stressed after flowering or when raisedcompletely without irrigation (Deshmukh et al. 2004). Thedevelopment of moisture stress leads to a wide range ofchanges in plant processes like diversion of biomass toundesirable plant parts. The chickpea genotypes with betterbiomass partitioning and mobilization efficiency will be suitablefor cultivation in the rainfed. Therefore, the presentinvestigation was conducted with the objectives to identifysuitable chickpea genotypes that can perform well under waterdeficit conditions and can be used as substitute of wheatcrop in rice-wheat or maize-wheat cropping system and toincrease the production of rabi pulse in the region.

The experimental material consisted of 10 cultivarsobtained from IARI, New Delhi. These genotypes were plantedin randomized block design with three replications at RegionalAgricultural Research station, SKUAST-J, Rajouri during rabiseason 2007-08 and 2008-09. Each plot consisted of 4 rows of3 m length with row to row and plant to plant spacing of 40 x10 cm. Each genotype was sown under two environments,namely irrigated and rainfed. The recommended agronomicpackages of practices and plant protection measures werefollowed for raising the crop successfully. There was no rainduring the growing season. Plants were taken randomly from

each replication for recording growth parameters. Recordingof biomass in leaves, stem and other reproductive plant parts(seeds/pod) was done at two growth stages i.e., at full bloomand physiological maturity for all the genotypes under differentenvironments. Five plants were taken out randomly from eachplot with roots by digging of soil and thereafter thoroughwashing of roots was done under gently running water. Afterwashing plants were separated into different parts viz., leaves,stem, pods and root for recording observations on partitioningof biomass. The height of shoot and root length was measuredfrom soil surface (crown position) to terminal point and the tipof root, respectively. The average of five plants in eachreplication was worked out for each treatment. The plant partswere dried at 700C temperature till constant weight. Yieldattributes were recorded from five plant samples taken fromeach plot at harvest. Seed and biological yield were recordedfrom individual plants. The statistical analysis for differentparameters and yield was done as per standard procedures.

Chickpea plants attained the maximum plant height androoting depth at full bloom stage (Table 1). Moisture stressreduced the plant height significantly but the reverse wastrue for root depth. Among genotypes, the plants of PUSA-1103 were the tallest followed by BGD-72 at full bloom stage.However, the roots of PUSA-1053, PUSA-1103 and PUSA-362 were statistically at par and penetrated significantly deeperin the soil profile than the roots of other genotypes at fullbloom stage.

At full bloom stage, the biomass allocation in roots,leaves and stem was 20.78, 33.15 and 37.24 per cent of totalbiomass, respectively. The dominating role of the stem, withrespect to biomass accumulation, followed by leaves indicatethat chickpea needs strong stem to bear more number of podsthrough increased branching and higher leaf area to producemore food to fill the pods. These findings are in concomitancewith the earlier observations (Ahlawat 1990, Singh 1995).Among the genotypes, percentage of total dry matteraccumulation in stem, leaves and roots was higher in PUSA-1103, PUSA-1053, PUSA-1108 and PUSA-362. The contributionof stem and leaves increased to total biomass because of lesspod development at the time of full booming stage.

Singh et al.: Effect of soil moisture regimes on chickpea productivily 157

At harvest, moisture stress reduced accumulation ofdry matter in different plant parts significantly. The dry matteraccumulation in vegetative parts (leaves and roots) decreasedat harvest as compared to full bloom stage due to mobilizationof biomass to the active sink (pods). The mild moisture stressdid not affect the biomass partitioning in chickpea but severemoisture stress reduced the allocation of biomass to seeds,pods and root in spite of increase in root length over irrigatedcontrol. At harvest, the functional rooting depth decreasedas compared to full bloom (Table 1).

Yield attributes viz., number of effective pods/plant,seeds/pod and 100- seed weight along with seed and biologicalyield and harvest index decreased significantly with increasedmoisture stress (Table 2). Among the genotypes, the highestpod density and 100-seed weight were observed in PUSA-

1103 and seeds per pod were recorded in PUSA-1105 andPUSA-372. Lower harvest index was recorded among all thegenotypes in severe moisture stress in environment indicatingthat the vegetative growth (source) was relatively less affectedthan the sink. Therefore, only few pods were formed in eachplant resulted in more adversely reduced seed yield than thebiomass accumulation. Similar reduction in yield attributesunder rainfed condition has been reported by Rahman andUddin (2000) and Kashiwagi et al. (2006a). The maximumbiomass, seed yield and harvest index were recorded in PUSA-1103. However, the seed yield of PUSA-1103 and BGD-72 werestatically at par and significantly higher than all the othertested genotypes. Similar genotypic variation in yield and itsattributes in chickpea under moisture stress have already beenreported (Kashiwagi et al. 2006b).

The associations of biomass partitioning in differentplant parts with seed yield at both the stages were observed.At full bloom stage, chickpea showed significant positiveassociation of seed yield with plant height (0.41) and totalbiomass (0.73). Omar and Singh (1997) reported that plantheight had the highest direct effect on biomass yield andconsequently to higher seed yield. However, at harvest, theseassociations further increased over full bloom. Seed yield atharvest had significant positive association with plant height(0.40). Among the yield attributes, with seed yield, the highestassociation was recorded with number of pods per plant (0.67)and biological yield (0.69). However, the biological yield hadhighest association (r=0.81) with seed yield. Significantpositive association with biomass partitioning in plant partsindicated that higher biomass yield and its maximumpartitioning in pods brought about positive improvement inseed yield of chickpea under moisture stress condition.

Table 1. Biomass partitioning of chickpea genotypes at full bloom and harvest stage under irrigated and rainfed conditions.

*Values in parenthesis are per cent contribution to total biomass

Full bloom AT harvest Dry weight/plant (g) Dry weight/plant (g) Treatment Plant

height (cm)

Root depth (cm) Stem Leaf Root Pod

Plant height (cm)

Root depth (cm) Stem Leaf Root Pod

Environment Irrigated 59.5 74.6 4.18(40.1)* 3.95(32.4) 2.99(23.2) 1.77(13.6) 57.9 42.7 7.5(39.9) 2.62(13.8) 1.3(6.9) 7.34(39.1) Rainfed 52 80.2 3.53(34.3) 3.50(33.9) 1.91(18.3) 1.6(15.4) 51.3 53.3 5.94(37.6) 2.13(13.4) 1.0(66.7) 6.61(41.9) CD (P=0.05) 7.8 6.5 0.32 4.511 3.5 2.4 6.5 19.5 7.2 4.1 1.08 2.3 Genotypes PUSA-1103 42.2 52.2 3.55(29.0) 4.03(33.0) 1.62(13.2) 3.16(25.8) 41.2 42.2 5.91(27.9) 2.77(12.9) 1.78(8.4) 10.67(50.6) BGD-72 41.2 51.4 2.98(33.1) 3.2(35.6) 1.45(16.1) 1.36(15.1) 40.8 23.5 4.68(33.3) 2.09(21.2) 0.6(14.1) 5.77(41.1) PUSA-1053 41.2 54.5 3.33(31.3) 3.17(29.8) 1.97(18.5) 2.15(20.2) 32.2 29.2 4.27(29.2) 2.74(18.5) 1.05(7.2) 6.55(44.9) PUSA-1105 37.8 47.5 2.49(25.4) 3.19(32.7) 1.77(18.0) 2.33(23.7) 31.9 31.4 4.18(25.3) 2.53(15.2) 1.02(6.2) 8.66(53.1) PUSA-372 35.9 49.5 2.28(24.4) 3.09(33.2) 1.70(18.2) 1.21(12.9) 30.8 37.5 3.49(25.3) 2.54(18.3) 1.68(12.8) 6.04(43.9) PUSA-1108 33.2 50.2 2.17(26.4) 3.15(38.5) 1.38(16.9) 1.48(18.1) 30.2 32.1 5.09(33.9) 1.68(10.8) 1.77(11.5) 6.61(43.9) PUSA-362 33.2 52.1 2.68(27.0) 3.21(35.5) 1.67(16.9) 2.31(23.3) 29.2 40.2 5.86(26.8) 2.68(12.1) 2.5(11.5) 10.76(49.4) PUSA-1003 29.2 46.4 2.47(31.4) 3.56(45.3) 0.5(6.36) 1.32(16.7) 24.2 18.8 7.5(39.9) 2.62(13.8) 1.3(6.9) 7.34(39.1) PUSA-256 27.7 45.2 3.05(33.5) 3.30(36.3) 0.8(8.78) 1.86(20.4) 25.5 20.5 5.94(37.5) 2.13(13.4) 1.0(66.7) 6.61(41.9) PUSA-391 24.8 39.6 2.07(25.9) 3.49(43.8) 1.06(13.2) 1.36(17.0) 21.7 18.3 6.56(38.6) 2.62(15.0) 0.95(5.4) 7(40.9) CD (P=0.05) 4.6 0.59 0.1 0.21 0.31 0.28 1.07 0.7 0.37 0.255 4.8 0.32

Table 2. Yield attributes of chickpea genotypes underirrigated and rainfed conditions.

Treatment Effective pods/ plant

Seeds/ pod

100-seed weight

(g)

Seed yield

(kg/ha)

Biological yield

(kg/ha)

Harvest index (%)

Environment Irrigated 67.6 1.3 26.6 1900.0 8158.3 23.4 Rainfed 55.1 1.4 21.5 1683.3 7516.6 22.7 CD (P=0.05) 7.1 0.6 7.1 571.5 445.0 3.7 Genotypes PUSA-1103 97.5 1.5 28.3 2966.6 10283.3 31.4 PUSA-1105 93.1 1.8 27.1 1816.6 7100.0 25.6 PUSA-362 77.8 1.4 14.1 2225.7 8000.0 27.7 PUSA-1108 70.3 1.3 21.8 2058.3 9116.6 22.7 PUSA-391 73.7 1.1 21.2 2016.6 8333.3 24.1 BGD-72 67.7 1.1 28.1 2016.6 7450.0 27.0 PUSA-1003 67.8 1.1 24.7 1600.0 6541.6 24.4 PUSA-256 64.5 1.2 25.1 2008.3 8266.6 24.3 PUSA-372 59.8 1.7 13.4 1316.6 6950.0 19.1 PUSA-1053 58.7 1.3 23.6 2116.6 9441.6 22.3 CD (P=0.05) 1.8 0.08 3.2 340.0 668.9 3.6


REFERENCES

Ahlawat S. 1990. Effect of long term water deficit on some aspects ofchickpea physiology. M.Sc. Thesis, Haryana Agricultural University,Hissar, India.

Deshmukh DV, Mhase LB and Jamadagni BM. 2004. Evaluation ofchickpea genotypes for drought tolerance. Indian Journal of PulsesResearch 17:47-49.

Kashiwagi J, Krishnamurthy L, Upadhyaya HD, Krishna H, Chandra S,Vincent V and Serraj R. 2006a. Genetic variability of drought-avoidance root traits in the mini-core germplasm collection ofchickpea (Cicer arietinum L.). Euphytica 146: 213-222.

Kashiwagi J, Krishnamurthy L, Crouch JH and Serraj R. 2006b.Variability of root length density and its contributions to seed yieldin chickpea (Cicer arietinum L.) under terminal drought stress.Field Crops Research 95: 171-181.

Omar M and Singh KB. 1997. Increasing seed yield in chickpea byincreased biomass yield. International Chickpea and Pigeon peaNews Letter 4:14-15.

Rahman LSM and Uddin ASM. 2000. Ecological adaption of chickpea(Cicer arietinum L.) to water stress -2 grain yield, harvest index,flowering and maturity studies. Legume Research 23: 1-8.

Singh S. 1995. Response of kabuli chickpea to irrigation andphosphorus. M.Sc. Thesis, HAU, Hissar, India.


Seed inoculation with bio-inoculants of rhizobia, PSBand PGPR in pulse crops is recommended to ensure adequateroot nodulation, N-fixation, growth and yields. Carrier basedinoculants are currently being produced in the country. Theseinoculants suffer with major drawback of short shelf liferesulting in inconsistent performance under field conditions.The cost of production of carrier based inoculants is alsohigh, being energy and labour intensive process(Somasegaran and Hoben 1994). Liquid inoculants have beenclaimed to provide solutions to some of these problemsassociated with the carrier based inoculants. It has beenreported that liquid inoculants formulations promote cellsurvival during storage and after application to seed and alsoprovide protection to microbial cells under extreme conditionssuch as high temperature and desiccation (Brahmprakash etal. 2007). Liquid inoculants being the new innovation inbiofertilizer technology, we compared the performance ofcarrier and liquid inoculants of Mesorhizobium sp. and PGPR,alone and in combination, in chickpea under field conditions.

A field experiment was conducted during rabi seasonof 2007-08 to compare the performance of liquid and carrierbased inoculants of Mesorhizobium ciceri and PGPR(Pseudomonas diminuta) in chickpea at Crop Research Centreof G. B. P. U. A. & T, Pantnagar. The experimental soil wassandy in texture, medium in organic C (0.61 %), low in availablenitrogen (175 kg/ha), available P (18 kg/ha) and available K(285 kg/ha) with pH 6.85 and EC 0.38 dS/m. Mesorhizobiumciceri (LN 7007) was obtained from Department ofMicrobiology, CCSHAU, Hisar and Pseudomonas diminuta(LK-884) from Pulse Microbiology programme of AICRP atPantnagar. Treatments comprising inoculation with carrier andliquid inoculants of Mesorhizobium sp. and PGPR, alone or incombinations, uninoculated and fertilizer (20 kg N + 40 kgP2O5 /ha) control. The experiment was laid out in plots of 2.4 mx 4.0 m following randomized block design in 3 replications.The liquid inoculants of these microorganisms were preparedusing modified YEM and nutrient broths of compositions asdescribed by Sahai and Chandra (2009). These medium in 50ml portions were inoculated with a 1 ml fresh inoculum of theMesorhizobium sp. and PGPR (Pseudomonas sp.) separately.The Mesorhizobium sp. was grown for 72 h and PGPR for 48h at 28 ± 1°C in incubator shaker so as to reach the culture tothe stationary phase. Carrier based inoculants were prepared

Short Communication

Co-inoculation effect of liquid and carrier inoculants of Mesorhizobium ciceri andPGPR on nodulation, nutrient uptake and yields of chickpeaPRATIBHA SAHAI and RAMESH CHANDRA

Department of Soil Science, College of Agriculture, G.B. Pant University of Agriculture and Technology,Pantnagar 263 145, Uttarakhand, India; E-mail: [email protected](Received: October, 2009; Accepted: October, 2010)

by growing Mesorhizobium sp. in YEM broth for 72 h andPGPR in nutrient broth for 48 h and then mixing the brothsseparately with sterilized charcoal (pH 7.0) in 1: 2 ratio. Seedwas treated with carrier based Mesorhizobium sp. and PGPRinoculants at the rate of 20 g/kg seed and liquid inoculants atthe rate of 4.0 ml/kg seed. Dual inoculation, wherever required,was done by mixing the required quantity of both theinoculants at the time of seed treatment. The crop was raisedfollowing recommended agronomic practices.

Five plants from each plot were randomly uprootedalong with a soil core at 30, 60, 90 and 120 days after sowing(DAS), roots were washed off to remove the adhering soil,nodules were removed from roots and counted. Dry weightsof nodules and plants were determined after drying to constantweight at each interval. Grain and straw yields were recordedat final harvest. N and P content in finely grind grain andstraw samples were determined following methods asdescribed by Page (1982) and N and P uptake were computed.

Results indicated that liquid inoculants ofMesorhizobium sp. and PGPR were better than carrier basedinoculants in root nodulation (Table 1). Carrier inoculants ofMesorhizobium sp. and PGPR gave significant increase innodule number of 20.3 to 68.7% and 36.6 to 66.2% and noduledry weight of 22.1 to 98.8% and 30.1 to 169.1% overuninoculated control at different crop age. Liquid inoculantsof Mesorhizobium sp. and PGPR recorded more nodulenumber of 15.7 to 35.1% and 11.2 to 30.9% and nodule dryweight of 12.4 to 46.2% and 3.0 to 27.3%, respectively overcarrier based inoculants at different intervals. Such beneficialresponse of liquid inoculants on nodulation in chickpea wasalso reported by Gupta (2005) and may be attributed to bettersurvival of inoculated organisms in rhizophere applied as liquidinoculant, which gives competitive advantage to theinoculated Mesorhizobium sp. Dual inoculation ofMesorhizobium sp. + PGPR with either carrier or liquidinoculants was slightly better over Mesorhizobium sp. orPGPR alone in nodulation due to synergistic interaction amongthem as reported earlier by Chandra and Pareek (2002).

Different inoculants influenced the plant dry weightsignificantly at different intervals, except at 60 DAS. The carrierand liquid inoculants of Mesorhizobium sp. recorded 30.1 to71.6% and 31.8 to 83.2%, more plant dry weight over


uninoculated control, respectively (Table 2). These inoculantsof PGPR also showed increase of 18.0 to 57.7 % and 19.7 to66.2 % in plant dry weight over the uninoculated control atdifferent intervals, respectively. Their combined inoculationfurther improved the plant dry weight over respectiveMesorhizobium sp. and PGPR alone inoculants, however theincrease was non-significant. The increase in plant dry weightmay be due to better crop nutrition as a result of N-fixation(Gupta 2005).

Carrier inoculants of Mesorhizobium sp. and PGPR gavesignificant increase in grain yield of 16.6 and 19.5 % andnumerical increase in straw yield of 18.4 and 19.7 % overuninoculated control (Table 2). Similarly, liquid inoculants ofMesorhizobium sp. and PGPR gave significant increases ingrain yield of 17.1 and 20.8 % and numerical increase in straw

yield of 20.5 and 21.3 % over uninoculated control, respectively.This may due to higher nodulation with liquid inoculant ofMesorhizobium sp. resulting in more N-fixation (Brahmprakashet al. 2007). The liquid and carrier inoculants of Mesorhizobiumsp. were comparable in grain and straw yields as observedearlier also by Chandra and Pareek (2007) in urdbean andmungbean and Gupta (2005) in chickpea. Dual inoculation ofMesorhizobium sp.+ PGPR with carrier or liquid inoculantswas slightly better than their respective inoculants alone.

Carrier based inoculant of Mesorhizobium sp. recordedsignificant increase of 43.0 and 47.1 % in N uptake and 20.4and 44.1 % in P uptake by grain and straw, respectively (Table3). Similar increase with carrier inoculant of PGPR were 53.2and 51.2 % and 28.1 and 62.7 %. Liquid inoculant ofMesorhizobium sp. gave slightly more N uptake of 6.1 and 5.4

Table 1. Effect of carrier and liquid inoculants of Mesorhizobium sp. and PGPR on nodulation at different crop age Nodule/plant (no) Nodule dry weight (mg/plant) Treatment

30 DAS 60 DAS 90 DAS 120 DAS 30 DAS 60 DAS 90 DAS 120 DAS

Uninoculated control 6.5 12.3 9.0 8.3 20.4 43.7 40.2 33.0 20 kg N + 40 kg P2O5/ha 8.3 13.3 10.5 8.3 23.3 68.0 60.1 54.1 Carrier inoculant Mesorhizobium sp. 9.5 14.8 13.5 14.0 24.9 81.6 74.9 65.6 PGPR 10.8 16.8 14.0 11.8 26.7 91.7 77.0 77.9 Mesorhizobium sp.+ PGPR 12.5 19.3 14.5 15.3 28.9 96.4 80.7 88.8 Liquid inoculant Mesorhizobium sp. 11.0 20.0 16.0 14.0 27.9 102.8 98.4 95.9 PGPR 12.0 22.0 14.5 12.8 28.9 94.2 98.0 75.5 Mesorhizobium sp.+ PGPR 13.0 22.3 17.8 16.0 35.2 107.3 108.1 104.4 CD (P=0.05) 1.7 4.3 4.8 5.4 5.6 25.9 26.1 22.5

Table 2. Effect of carrier and liquid inoculants of Mesorhizobium sp. and PGPR on plant dry weight at different crop age and yield

Plant dry weight (g/plant) Yield (kg/ha) Treatment 30 DAS 60 DAS 90 DAS 120 DAS Grain Straw

Uninoculated control 0.289 1.571 3.984 9.704 1898 2824 20 kg N + 40 kg P2O5/ha 0.349 1.732 4.204 13.162 2060 3167 Carrier inoculant Mesorhizobium sp. 0.361 1.823 4.460 15.231 2213 3343 PGPR 0.368 1.891 5.325 15.831 2269 3380 Mesorhizobium sp.+ PGPR 0.376 1.958 5.855 16.648 2315 3611 Liquid inoculant Mesorhizobium sp. 0.364 1.855 5.135 15.311 2222 3403 PGPR 0.369 1.881 5.591 16.137 2292 3426 Mesorhizobium sp.+ PGPR 0.381 1.970 6.828 17.774 2338 3699 CD (P=0.05) 0.060 NS 1.099 2.806 298 NS

Table 3. Effect of Mesorhizobium sp. and PGPR inoculants on N and P uptake by chickpea

Nitrogen (kg/ha) Phosphorus (kg/ha) Treatment Grain Straw Grain Straw

Uninoculated control 57.62 35.00 5.70 2.86 20 kg N + 40 kg P2O5/ha 72.03 41.40 6.34 3.45 Carrier based inoculant Mesorhizobium sp. 82.39 51.50 6.86 4.12 PGPR 88.28 52.92 7.30 4.54 Mesorhizobium sp.+ PGPR 96.74 59.14 7.34 5.25 Liquid inoculant Mesorhizobium sp. 87.38 54.28 7.12 4.19 PGPR 94.22 63.21 7.82 4.53 Mesorhizobium sp.+ PGPR 99.20 73.21 7.99 5.88 CD (P=0.05) 17.75 15.91 1.29 1.47

Sahai and Chandra: Effect of liquid and carrier inoculants of Mesorhizobium ciceri and PGPR on chickpea 161

% and P uptake of 3.8 and 2.0 % by grain and straw over itscarrier based inoculants, respectively. Liquid inoculant ofPGPR gave significantly more N uptake of 6.7 and 19.4 % bygrain and straw, respectively, and P uptake of 7.1 percent bygrain over its carrier inoculants. Dual inoculation ofMesorhizobium sp. + PGPR as carrier or liquid inoculantsfurther improved the N and P uptake. The results are inagreement with the findings of Gupta (2006), who also reportedpositive response of dual inoculation on N and P content andtheir uptake due to better nodulation and N-fixation.

It can be concluded that liquid inoculants ofMesorhizobium sp. and PGPR though recorded betternodulation and nutrient uptake, nevertheless were at par withcarrier based inoculants in grain and straw yields. Dualinoculation of Mesorhizobium sp. + PGPR as carrier or liquidinoculants gave advantage over their individual inoculation.

REFERENCES

Brahmaprakash GP, Girisha HC, Navi Vithal, Laxmipathy R and HedgeSV. 2007. Liquid Rhizobium inoculant formulations to enhance

biological nitrogen fixation in food legumes. Journal of FoodLegumes 20: 75-79.

Chandra R and Pareek N. 2007. Comparative performance of liquidand carrier based inoculants in urdbean and mungbean. Journal ofFood Legumes 20:80-82.

Chandra R and Pareek RP. 2002. Effect of Rhizobactaria in urdbeanand lentil. Indian Journal of Pulses Research 15: 152-155.

Gupta SC. 2005. Evaluation of liquid and carrier based Rhizobiuminoculants in chickpea. Indian Journal of Pulses Research 18: 40-42.

Gupta SC. 2006. Effect combined inoculation on nodulation nutrientuptake and yield of chickpea in Vertisol. Journal of the IndianSociety of Soil Science 54: 251-254.

Page AL. 1982. Methods of soil analysis. Part II. Chemical andmicrobiological properties (2nd ed). ASA and CSSA. Madison,Wisconsin USA., pp 1158.

Sahai Pratibha and Chandra R. 2009. Shelf life of liquid and carrierbased Mesorhizobium sp. and Pseudomonas sp. inoculants underdifferent storage conditions. Journal of Food Legumes 22 (4): 280-282.

Somasegaran P and Hoben HJ. 1994. Handbook for Rhizobium, methodsin legume-Rhizobium technology. Spinger Verlag, New York. Inc.


Short Communication

Bio-efficacy of insect growth regulator against tobacco caterpillar in blackgramS. MALATHI

Regional Agricultural Research Station, Acharya N.G. Ranga Agricultural University, Warangal - 506 007,Andhra Pradesh, India; E-mail: [email protected](Received: January, 2010; Accepted: September, 2010)

Tobacco caterpillar (Spodoptera litura Fab.) ispolyphagous in nature and causes considerable damage topulses, oilseeds, cotton and vegetables (Seema Rani et al.2002). Blackgram is an important pulse crop which is mainlycultivated as a rabi crop under rice fallows in certain areas ofAndhra Pradesh. S. litura is known to infest blackgram frompreflowering to pod development stage and causesconsiderable yield losses especially during September toFebruary. Several chemical pesticides to control S. litura werestudied; however, problems like build up of resistance toinsecticides, harmful effects to non-target organisms, etc aremajor limiting factors in their use. In this context, insect growthregulators (IGRs) inhibiting chitin synthesis in insects, whichare selective in action, less hazardous to the environment(Vadodaria et al. 2000; Kuldeep and Rahman 2004), wereconsidered to be appropriate. Therefore, present study wasundertaken to evaluate the efficacy of an IGR, viz., lufenuron(Cigna 5 EC) against S. litura in blackgram at RegionalAgricultural Research Station, Warangal during rabi, 2006.

Field trial was laid out in a randomized block designwith seven treatments viz., lufenuron 5EC @ 20, 25, 30 g a.i./ha, thiodicarb 75 WP @ 750 g a.i./ha, quinalphos 25 EC @ 250g a.i./ha, endosulfan 35 EC @ 525 g a.i./ha and an untreatedcontrol. Each treatment was replicated three times. Theexperiment was conducted with the test variety WBG-26,

following all recommended agronomic practices in deep blacksoil under irrigated conditions. The plot size was 28 m2. Spacingadopted was 40 x 10 cm. The experiment was sown on 27-09-06 and harvested on 20-12-06. Incidence of S. litura wasnoticed right from last week of October to last week ofNovember, 2006. Four sprayings were taken up at 10 daysinterval starting from the initial notice of the pest. Observationswere recorded on total number of defoliated leaves/plant onfive randomly selected plants in each plot before sprayingand 7 days after spraying. The data on defoliation (%) due tolarval feeding was computed.

Significant differences were found among the treatmentssubsequent to spraying. Seven days after I spraying, per centdefoliation was lowest in the plot treated with lufenuron @ 30g a.i. /ha (12.61) followed by thiodicarb @ 750 g a.i./ha (14.56)which were at par with each other. Lufenuron @ 25 g a.i./hawith 16.16 per cent defoliation was equally effective asthiodicarb @ 750 g a.i./ha. Quinalphos @ 250 g a.i./ha,endosulfan @ 525 g a.i./ha and lufenuron @ 20 g a.i./ha, withdefoliation in the range of 19.77 to 22.01%, were at par witheach other. Lufenuron @ 30 g a.i./ha recorded 11.30 per centdefoliation and was significantly superior over all othertreatments after the second spray, followed by thiodicarb@ 750 g a.i./ha, quinalphos @ 250 g a.i./ha (Table 1).Lufenuron @ 30 g a.i./ha maintained consistency in recording

Table 1. Efficacy of lufenuron on tobacco caterpillar, Spodoptera litura in blackgram

*Significant at P=0.05, Figures in parentheses arc-sine transformations

Per cent defoliated leaves Treatment Dose (g a.i./ha) Pre

treatment 7 days after

Ist spray 7 days after IInd spray

7 days after IIIrd spray

7 days after IVth spray

Cumulative mean of sprays

Yield Kg/ha

Lufenuron 5 EC 20 13.73 (21.72)

19.80 (26.42)

29.70 (33.02)

31.33 (34.02)

30.67 (33.66)

27.86 (31.88)

1443

Lufenuron 5 EC

25 12.63 (20.75)

16.16 (23.73)

24.60 (29.73)

24.98 (30.00)

23.67 (29.13)

22.36 (28.26)

1707

Lufenuron 5 EC

30 13.65 (21.66)

12.61 (20.79)

11.30 (19.64)

13.07 (21.22)

13.57 (21.64)

12.64 (20.79)

1757

Thiodicarb 75 WP 750 15.58 (23.12)

14.56 (22.46)

16.00 (23.58)

17.02 (24.36)

17.37 (24.66)

16.24 (23.73)

1750

Quinalphos 25 EC 250 14.96 (22.60)

19.77 (26.42)

19.60 (26.28)

22.26 (28.18)

22.57 (28.38)

21.04 (27.28)

1582

Endosulfan 35 EC 525 16.11 (23.65)

22.01 (27.97)

27.73 (31.76)

24.99 (30.00)

25.33 (30.20)

25.00 (30.00)

1546

Untreated control - 15.98 (23.12)

28.01 (31.95)

34.03 (35.57)

32.35 (34.70)

34.37 (35.91)

32.19 (34.57)

1171

F-Test - NS * * * * * * SEm + - - 0.71 0.5 0.95 1.06 0.52 63.04 CD (P=0.05) - - 2.19 1.54 2.94 3.27 1.6 1.94

Malathi: Bio-efficacy of insect growth regulator against tobacco caterpillar in blackgram 163

lowest defoliation subsequent to all sprays (11.30 to 13.57%)and was superior over all other treatments throughout cropperiod. Highest defoliation was observed in untreated plotthroughout the crop period.

Mean defoliation over all the sprays indicated thatlufenuron @ 30 g a.i./ha with 12.64 per cent defoliation wassignificantly superior over other treatments. Thiodicarb @750 g a.i./ha with 16.24 per cent defoliation was the next besttreatment. Quinalphos @ 250 g a.i./ha and lufenuron @ 25 ga.i./ha were equally effective. Data taken on plot yield revealedthat highest yield was recorded in the plots treated withlufenuron @ 30 g a.i./ha (1757 kg/ha) and thiodicarb (1750 kg/ha). Untreated control plot recorded lowest yield among alltreatments. Kuldeep et al. (2004) reported that lufenuron(Match 5 EC) suppressed growth and development of S. lituraunder laboratory conditions. He reported that per centpupation and adult emergence were severely reduced.

It is concluded that, lufenuron 5 EC @ 30 g a.i./ha andthiodicarb 75 WP @ 750 g a.i./ha reduced defoliation byS.litura and increased the yield and can be used as effectivemeasures against S. litura in blackgram ecosystem.

REFERENCES

Kuldeep and Rahman MA. 2004. Impact of insect growth regulators(IGRs) on natural enemies of soybean caterpillar. Insect Environment10: 92-94.

Kuldeep, Rahman MA and Ram S. 2004. Effect of sublethal doses oflufenuron against Spodoptera litura Fab. and Spilarctia obliquaWalk. Indian Journal of Entomology 66: 287-292.

Seema Rani, Goel BB and Gupta GP. 2002. Growth and development ofSpodoptera litura Fabricius on different host plants. Annals ofPlant Protection Science 16: 216-219.

Vadodaria MP, Maisuria IM, Patel RB, Patel CJ and Patel UG. 2000.Insect growth regulator (IGR) – a new tool in the management ofHelicoverpa on cotton in Gujarat. Pestology 24: 11-14.


Pigeonpea (Cajanus cajan (L.) Millsp.) is grownthroughout the tropics, but most widely in south and south-east Asia, where it is preferred source of vegetable protein. Itis one of the major grain legumes in the semi-arid tropics (Neneand Sheila 1990). Pigeonpea yields have remained stagnantfor the past 3 to 4 decades, largly due to insect pests’ damage.More than 200 species of insects feed on this crop, of whichpod fly (Melanagromyza obtusa Malloch) is important pest,in addition to ubiquitous pest, Helicoverpa armigera (Hub.)(Lateef and Reed 1990, Shanower et al. 1999, Kumar and Nath2003, Kumar et al. 2003, Nath et al. 2008). Losses due to podfly damage have been estimated to be US$ 256 millionsannually. Identification and cultivation of cultivars which areless preferred by pod fly have number of advantages,particularly for an eco-friendly management of pigeonpea.

More than 10,000 germplasm accessions have beenscreened for pod fly resistance (Lateef and Pimbert 1990).However, Singh and Singh (1990) reported that no definiteconclusions could be drawn about the relative susceptibilityof pigeonpea genotypes to pod fly damage because ofstaggered flowering and variation in pod fly abundance overtime. Since levels of resistance to these pests in the cultivated

Short Communication

Population fluctuations of pod fly on some varieties of pigeonpeaRAM KEVAL, DHARMPAL KERKETTA, PARAS NATH and P.S. SINGH

Department of Entomology & Agricultural Zoology, Banaras Hindu University, Varanasi-221 005,Uttar Pradesh, India; E-mail: [email protected](Received: April, 2010; Accepted: September, 2010)

pigeonpea are low to moderate, it is important to identifypigeonpea cultivar that permits slow growth or lesserpopulation buildup of pod fly.

The population buildup of pod fly on six long durationvarieties of pigeonpea was studied during kharif seasons of2007-08 and 2008-09 at the Institute of Agricultural Sciences,Banaras Hindu University, Varanasi. The experiment wasconducted with 3 replications and 6 treatments followingfactorial randomized block design. The plot size was 4 m x 3.75m (15 m2) and the row-to-row and plant-to-plant distance were75 cm and 10 cm, respectively. The pigeonpea cultivars usedfor study were ‘NDA 5-25’, ‘PDA 85-5E’, ‘MAL-27’, ‘KAWR92-2’, ‘MAL-13’ and ‘MAL-20’. The population of pod flywas recorded by observing 10 pods selected randomly out of100 pods picked up from 5 selected plants from eachreplication. All the data recorded were subjected to statisticalanalysis as per the factorial randomized block designprocedure.

The first incidence of pod fly was observed in the 4th

standard week on 24th January and remained active till 12th

standard week in all the varieties. The peak population of podfly irrespective of variety was in 9th standard week and

Table 1. Pooled data for population of pod fly, Melanagromyza obtusa on long duration pigeonpea during 2007-08 and 2008-09

Figures in parentheses are transformed value = 0.5 x Difference between varieties (CD: P=0.05) = 0.11Difference between periods (CD: P=0.05) = 0.09Difference between varieties and periods (CD: P=0.05) = 0.27

Maggots/10 pods (no)

Periods (standard week) Variety 4th S.W. 24th Jan

5th S.W. 31st Jan

6th S.W. 7th Feb

7th S.W. 14th Feb

8th S.W. 21st Feb

9th S.W 28th Feb

10th S.W. 7th March

11th S.W. 14th March

12th S.W. 21th March

Average

NDA-5-25 0.06 (.77)

0.47 (0.96)

0.23 (0.85)

0.56 (1.01)

0.60 (1.03)

1.26 (1.30)

1.03 (1.21)

0.73 (1.11)

0.46 (0.97)

0.57 (1.01)

PDA85-5E 0.26 (0.86)

0.27 (0.86)

0.26 (0.91))

0.17 (0.81)

0.50 (0.99)

0.76 (1.12)

0.23 (0.84)

0.37 (0.92)

0.33 (0.90)

0.33 (0.90)

MAL-27 0.17 (0.80)

0.17 (0.80)

0.63 (1.05)

0.16 (0.81)

0.36 (0.91)

0.47 (0.97)

0.2 (0.82)

0.23 (0.85)

0.20 (083)

0.28 (0.87)

KAWR92-2 0.13 (0.79)

0.13 (0.78)

0.43 (0.95)

0.17 (0.81)

0.40 (0.93)

0.20 (0.83)

0.20 (0.82)

0.10 (0.77)

0.27 (0.81)

0.21 (0.83)

MAL-13 0.10 (0.77)

0.20 (0.83)

0.20 (0.83)

0.43 (0.95)

0.40 (0.94)

0.33 (0.91)

0.36 (0.91)

0.46 (0.96)

0.43 (0.96)

0.31 (0.88)

MAL-20 0.20 (0.86)

0.36 (0.93)

0.33 (0.9)

0.66 (1.04)

0.60 (1.03)

0.57 (1.03)

(0.80) (1.13)

0.43 (0.95)

0.30 (0.89)

0.46 (0..97)

Average 0.11 (0.81)

0.27 (0.86)

0.35 (0.92)

0.40 (0.90)

0.48 (0.97)

0.60 (1.03)

0.47 (0.95)

0.39 (0.92)

0.32 (0.89)

0.37 (0.92)

Keval et al.: Population fluctuations of pod fly on some varieties of pigeonpea 165

thereafter, it declined due to maturity of grains (Table 1). Thepopulation in various standard weeks was found in order 9th >8th >10th >7th > 11th > 6th > 12th > 5th > 4th during both the years.The highest mean population of pod fly was recorded in NDA-5-25 (0.57 maggots/ 10 pods), followed by MAL-20 (0.46maggots/ 10 pods), PDA 85-5E (0.33 maggots/ 10 pods), MAL-13 (0.31 maggots/ 10 plots), MAL- 27 (0.28 maggots/ 10 pods)and the lowest in KAWR 92-2 (0.21 maggots/ 10 pods) duringboth the years. The present findings are in agreements to thereports of Kumar et al. (2003) and Nath et al. (2008).

The pod fly population variation in different cultivarsmay be due to pod character which either attracted or repelledthe pod fly for egg laying. The meteorological factors such astemperature and humidity affect the physiological conditionof the plant as a whole and particular high temperature driedthe pod, making it unfit for egg laying resulting in reduction inpopulation.

REFERENCES

Kumar S, Singh B and Kumar N. 2003. Assessment of pod damagecaused by pod borere complex in pre-rabi pigeonpea. Indian Journalof Pulses Research 16: 169-170.

Kumar AL and Nath P. 2003. Pest complex and their populationdynamics on medium-late variety of pigeonpea Bahar. Indian Journalof Pulses Research 16: 150-154.

Lateef SS and Reed W. 1990. Insect pests on pigeonpea. In: S.R. Singh(ed.), Insect Pests of Tropical Food Legumes, John Wiley andSons, New York. Pp. 193-242.

Nath P, Singh RS, Singh PS and Keval R. 2008. Study of the successionof insect pest associated with pods of pigeonpea under sole andintercropping system. Indian Journal Environment and Ecoplan.15: 455-461.

Nene YL and Sheila VK. 1990. Pigeonpea: Geography and importance.In The Pigeonpea, ed. Y. L. Nene, S. D. Hall and V. K. Sheila, pp. l-14. CAB International, Wallingford.

Shanower TG, Romeis J and Minja EM. 1999. Insect pests of pigeonpeaand their management. Annual Review of Entomology 44: 77–96.

Lateef SS and Pimbert MP. 1990. The search for host plant resistanceto Helicoverpa armigera in chickpea and pigeonpea at ICRISATSummary proceedings of the First Consultative Group Meeting onHost Selection Behaviour of Heliothis armigera . ICRISAT,Patancheru, Andhra Pradesh, India, pp. 25–28.

Singh HK and Singh HN. 1990. Screening of certain pigeonpea cultivarssown at kharif and rabi crops against tur pod bug, Clavigralla gibbosaand pod fly, Melanagromyza obtusa. Indian Journal of Entomology52: 320–327.

Journal of Food Legumes 23(2): 166, 2010

1. Dr. A.S. GaneshmurthyPrincipal ScientistIIHR, Bangalore

2. Dr. P.K. GhoshHeadCrop Production DivisionIIPR, Kanpur

3. Dr. S.C. GuptaAssociate ProfessorARS, Durgapura,Jaipur, Rajasthan

4. Dr. A. Bhattacharya,Retd. Principal Scientist,CPBM Division, IIPR, Kanpur

5. Dr. M. S. VenkateshSenior ScientistCrop Production Division,IIPR, Kanpur

6. Dr. Narendra KumarSenior Scientist,Crop Production DivisionIIPR, Kanpur

7. Dr. Anup DasICAR Research Complex for NEH RegionBarapani, Meghalaya

8. Dr. Mahaveer P. SharmaKhandawa RoadIndore

9. Dr. Sarvjeet SinghSr. Plant BreederPAU, Ludhiana

List of Referees

10. Dr. S.K. ChaturvediHeadCrop Improvement Division,IIPR, Kanpur

11. Dr. G.P. DixitSenior ScientistPC Unit, MULLaRPIIPR, Kanpur

12. Dr. K.S. ReddySenior Scientific OfficerBARC, Trombay, Mumbai

13. Dr. M. N. SinghProfessorB.H.U., Varanasi

14. Dr. S.K. SinghPrincipal Scientist, Crop Protection DivisionIIPR, Kanpur

15. Dr. S.D. MohapatraSenior ScientistCrop Protection Division,IIPR, Kanpur

16. Dr. Harsh Nayyar,Professor,Panjab UniversityChandigarh

17. Dr. DevrajI/C Agril. Statistics & Computer Application IIPR, Kanpur

PROCEEDINGS OF GENERAL BODY MEETING OF THE ISPRD HELD ATCSK HPKV, PALAMPUR (H.P.) ON MAY 18, 2010

General body meeting of the Indian Society of Pulses Research and Development was held at 10.0 hr onMay 18, 2010. Dr N Nadrajan, Director (IIPR, Kanpur) & Co-Patron (ISPRD) presided over the meeting.l At the outset, four pulse scientists namely, Dr B B Sharma (GBPUA&T, Pantnagar), Dr (Mrs) Rekha Mathur

(ARS, Durgapura, Jaipur), Dr Jai Dev Singh and Dr Vijay Shankar Singh (CSAUA&T, Kanpur) were felicitatedby the Society for their contributions in the field of pulses research and development.

l Dr (Mrs) Livinder Kaur (Treasurer, ISPRD NWPZ Local Chapter, PAU, Ludhiana) presented details of auditedfinancial reports (income-expenditure status) of the Society for the year 2009.

l Secretary (ISPRD) presented details of the status of manuscripts for the official Journal (Journal of FoodLegumes) of the Society. The house expressed concern over the pending manuscripts of previous years. Secretaryassured the House to process those manuscripts on priority basis. It was decided further that the manuscriptsapproved for publication would also bear their date of receipt and date of acceptance from the forthcomingissues of the Journal (2010).

l The House was informed about online display of Journal of Food Legumes, the latest issue of which could beviewed at www.indianjournal.com.

l Secretary (ISPRD) put before the House recommendations of the core committee of the Executive regardingfee hike for annual/life membership and library subscription. The General body approved hike of fee: (a) fromRs. 250 to Rs. 350 for annual membership, (b) from Rs. 2500 to Rs. 3500 for life membership, and (c) fromRs. 2500 to Rs. 3000 for library subscription.

l The House retained the criteria of 5 years and 3 publications for the award of Fellowship to the members of theSociety. However, it was decided that: (a) out of the three, one paper must have published in the Journal of FoodLegumes, and (b) all the three publications must have NAAS journal rating at or above par with Journal of FoodLegumes. It was further decided that Fellowship would be awarded every year and members can apply directlyfor such award (recommendation from parental university/Institute would not be required).

l Secretary (ISPRD) informed the House about the preliminary discussion with private companies for creation offacility for online submission and processing of research articles for the Journal of Food Legumes. General bodyapproved the proposal for creation of such facility (which would include creation of separate website and itssubsequent annual maintenance) and associated one time cost of about Rs. 1.5 lakh. The House also approvedthe Annual maintenance cost (~Rs. 50000=00) of the website for the succeeding year.

l The election of the Office bearers (President, Secretary and Treasurer) of the Local Chapter (NWPZ LocalChapter, PAU, Ludhiana) would be conducted by the Local Chapter in consultation with the Central Unit afterthe expiry of the term (3 years). The result of the election would be endorsed by the Central Core Committee.

In his Presidential address, Dr N D Majumder assured the House that concerns of the members would berapidly addressed. At last, Dr N Nadrajan (Co-Patron of ISPRD & Director, IIPR) addressed the General Body. Heappealed the House to extend whole-hearted support to the Executive for meaningful solutions to their genuineproblems. In the last, Secretary (ISPRD) proposed vote of thanks to the Chair and all the respected members of theIndian Society of Pulses Research and Development.

Sd/(A K Choudhary)Secretary, ISPRD

Journal of Food Legumes 23(2): 167, 2010

Journal of Food Legumes (formerly Indian Journal of PulsesResearch) publishes original papers, short communicationsand review articles by renowned scientists, covering all areasof food legumes research. The paper should not have beenpublished or communicated elsewhere. Authors will be solelyresponsible for the factual accuracy of their contribution.Language of publication is English (British).Please send your manuscript to following address:SecretaryISPRDIndian Institute of Pulses ResearchKalyanpur, Kanpur 208 024, IndiaEmail: [email protected] must be submitted through e-mail. You shouldalso submit a hard copy of your manuscript for our officialrecord. Besides author(s) is required to submit a certificatethat the paper is exclusive for Journal of Food Legumes.Manuscripts must conform to the Journal style (see the latestissue). Correct language is the responsibility of the author.After having received your contribution (date of submission),there will be a review process before the editorial board takesdecision regarding acceptance for publication. One copy ofthe revision together with the original manuscript must bereturned to the subject editor or Secretary. The submittedpaper must be one complete word document file comprising atitle page, abstract, text, references, tables, figure legends andfigures. When preparing your text file, please use only TimesNew Roman for text (12 point, double spacing) and Symbolfont for Greek letters to avoid inadvertent charactersubstitutions.FormatEvery original paper should be divided into the following fivesections: ABSTRACT, Key words, INTRODUCTION,MATERIALS AND METHODS, RESULTS ANDDISCUSSION, and REFERENCES. The manuscript should betyped on one side of the paper only, double spaced, and with4-cm margins with page and line numbers. The main title mustbe capital bold. Subheading must be bold italic and Sub-subheading normal italic.At the head of the manuscript, the following informationshould be given: the title of the paper, the name(s) of theauthor(s), the institute where the research was carried out,the present addresses of the authors (foot note) and of thecorresponding author (if different from above Institute).Authors are required to provide running title of the paper.You must supply an E-mail address for the correspondingauthor.The abstract should contain at least one sentence on each ofthe following: objective of investigation (hypothesis, purpose,aim), experimental material, method of investigation, datacollection, result and conclusions. Maximum length of abstractis 175 words. Up to 10 key words should be added at the endof the abstract and separated by comma. Key words must bearranged alphabatically (e.g., EMS, Gamma ray, Mungbean,Mutations, Path coefficient, ......).Each figure, table, and bibliographic entry must have areference in the text. Any correction requested by the reviewershould also be integrated into the file.Manuscript file including tables must be in MS Word andWindows-compatible and must not contain any files otherthan those for the current manuscript. Please do not importthe figures into the text file. The text should be prepared usingstandard software (Microsoft Word); do not use automatedor manual hyphenation.

Length

Manuscripts should not exceed a final length of 15 printedpages, i.e., 5,000 words, including spaces required for figures,tables and list of references. Manuscripts for shortcommunications should not exceed 3000 words (3 printedpages, with not more than a total of 2 figures or tables).

Units, abbreviations and nomenclature

For physical units, unit names and symbols, the SI-systemshould be employed. Biological names should be givenaccording to the latest international nomenclature. Botanicaland zoological names, gene designations and gene symbolsare italicised. Yield data should be reported in kg/ha. The nameof varieties or genotypes must start and end with singleinverted comma (e.g., ‘Priya’, ‘IPA 204’, ......).

Tables and Figures

Tables and figures should be limited to the necessary minimum.Please submit reproducible artwork. For printing of colouredphotograph, authors will be charged Rs. 4000/- perphotograph. It is essential that figures are submitted as high-resolution scans.

References

The list of references should only include publications citedin the text. They should be cited in alphabetical order underthe first author’s name, listing all authors, the year ofpublication and the complete title, according to the followingexamples:Becker HC, Lin SC and Leon J. 1988. Stability analysis in plantbreeding. Plant Breeding 101: 1-23.Sokal RR and Rholf FJ. 1981. Biometry, 2nd Ed. Freeman, SanFrancisco.Tandon HLS. 1993. Methods of Analysis of Soils, Plants, Waterand Fertilizers (ed). Fertilizer Development and ConsultationOrganization, New Delhi, India. 143 pp.Singh DP. 1989. Mutation breeding in blackgram. In: SA Farookand IA Khan (Eds), Breeding Food Legumes. PremierPublishing House, Hyderabad, India. Pp 103-109.Takkar PN and Randhawa NS. 1980. Zinc deficiency in Indiansoils and plants. In: Proceedings of Seminar on Zinc Wastesand their Utilization, 15-16 October 1980, Indian Lead-ZincInformation Centre, Fertilizer Association of India, New Delhi,India. Pp 13-15.Satyanarayan Y. 1953. Photosociological studies on calcariousplants of Bombay. Ph.D. Thesis, Bombay University, Mumbai,India.In the text, the bibliographical reference is made by giving thename of the author(s) with the year of publication. If there aretwo references, then it should be separated by placing ‘comma’(e.g., Becker et al. 1988, Tandon 1993). If references are of thesame year, arrange them in alphabatic order, otherwise arrangethem in ascending order of the years.While preparing manuscripts, authors are requested to gothrough the latest issue of the journal.

Instructions to Authors

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Journal of Food Legumes

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