Pd bioversity 19 5 2011
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Transcript of Pd bioversity 19 5 2011
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Use of Agrobiodiversity for Pest and Disease Management
Carlo Fadda, Bioversity International ODDG Seminars, 19 May 2011
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Outline
• Overview of the Project• Research Methodology• Main Results• Final Remarks
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The project ideaFarmers need to face several biotic and abiotic stresses. Traditional crop
varieties as one of the few resources available to poor farmers : Make use of the intra-specific diversity among the traditional varieties maintained by farmers to reduce pest and disease pressures
Strategy
Build on existing knowledge (farmer and researcher)
Exploit the natural resistance that results from the co-evolution of pest and host species
Provide farmers with low-input options through reduced use of pesticides
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But we can use local genetic diversity and have a diverse set of crop varieties for farmers to reduce their risk of crop loss from pests and diseases
A diverse set of varieties with:• Non-uniform resistance• Less probability that migrations of new pathogens or mutations of existing
pathogens will damage the crop
We can not predict that a new pest or pathogen will develop
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Crops (foodsecurity of smallfarmers; differentbreedingsystems)
• Coverage of different resistance gene system (where resistance is controlled by both major and minor genes)
• Transmission systems: seed-borne, soil-borne, and air-borne• Plant organ affected: leaf, stem, seeds and roots
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Outcome: Benefits to local communities
• Reduced crop vulnerability
• Reduced crop loss
• Increased incomes
• Increased capacity and leadership abilities
• Benefit sharing protocols with communities
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Methodology
• Participatory Diagnostic:
– Focus Group Discussion;
– Household Survey;
– Technical Evaluation (laboratory and field analysis).
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Focus Group Discussion
Barley Beans Faba bean Maize Plantain Rice China 10 10 10 25 Ecuador 15 15 10 Morocco 20 20 Uganda 15 15 Total 30 30 30 25 25 25
More than 1500 farmers attended the FGD globally
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• Based on the information from FGD;• Sixty farmers randomly selected interviewed
in each community for each crop;• More than 2000 farmers were interviewed
worldwide• Information on diversity is combined with field
observations (option 1).
Household Survey
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Amount and distribution of bean varieties
Kabwohe Rubaya Nakaseke
HH richness 2.21 2.20 2.556
HH Simpson 0.32 0.375 0.432
Community richness
23 26 16
Community Simpson
0.85 0.914 0.799
Divergence 0.62 0.59 0.46
Results – Farmers’ Knowledge
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Farmers’ Knowledge (Cont.)
0
0.5
1
1.5
2
2.5
3
Score onresistance
Overall resistance to rice blast
Dalixiang
BaiyangnuoMagu
Variation of resistance to rice blast in different traditional rice varieties
1-S
2-MS
3-MR
4-R
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Results - Option 1
10 sample points were taken randomly in a field and these points’ for panicle blast different levels of resistance. Its range of variation was from 7% to 25%.
Average disease incidence of 10 sample points for Dalixiang
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Results - Option 1 (Cont.)
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Biotic diversity regulates pests and diseasesCrop genetic diversity in farmer’s fields – reducing vulnerabilityReducing the probability of crop loss from pest and diseases now and in the future
Mai ze vari ety evenness VS NLB' s Wei ghteddi sease i ndex (NLB percentage)
0
20
40
60
80
100
120
0 0. 2 0. 4 0. 6 0. 8
Vari ety evenness (Si mpl son)
Weig
hted
dis
ease
ind
ex
Wei ghted di sease i ndex (Wei ghted di sease i ndex)线性
Mai ze vari ety ri chness VS NLB' s Wei ghteddi sease i ndex (NBL percentage)
0
20
40
60
80
100
120
0 1 2 3 4 5
Mai ze vari ety ri chness
Weig
hted
dis
ease
ind
ex(d
isea
se p
erce
ntag
e)
Wei ghted di sease i ndex
Wei
ghte
d D
amag
e In
dex
= Cr
op lo
ss (h
ouse
hold
)
Variety richness at household level
Variety Evenness at household level
Hou
seho
ld D
amag
e In
dex
Higher variety richness/evenness – less variance in damage: a risk minimizing argument for crop variety diversity in the production system
Peng et al., 2011
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Results – Option 2
HR 3 Qiena, Zhangmeleng-1, Chujing-27
R 1 Modelong-1
MR 9 Chengnuo-88 , Nuoyou-9 , Baiyangnuo , Qiejiaba ,Qiege , Chujing-24 , Bendipinzhong , Dulong-1 ,Xiangnuo
Of 63 varieties, 3 didn’t flower.HR, R and MR accounted for 5%, 1.67% and 15%, respectively. The remaining 78.33% ranged from MS to HS (56.67%).
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Option 2 (Cont.)
Within varieties, the resistance of different individual to rice blast was various.
For example, Shanyou-63 was susceptible to panicle blast, but its 30 individuals had different performance on resistance to blast, which was from HR to HS. So did other varieties.
Di sease grade of vari eti es wi th di ff erent resi stance topani cl e bl ast
0
2
4
6
8
10
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29
No. of pani cl e
Disease grade
Chuj i ng-27
Model ong-1
Bai yangnuo
Afai
Shanyou-63
Dal i xi ang
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Results – Option 4
Disease grade of leaf blastDisease grade of
panicle blast
Resistance R MR MS S MS S HS
No. 25 13 14 6 11 13 27
Precentage 43.10 22.41 24.14 10.34 21.57 25.49 52.94
No. of varieties
58 51
Seedling nursery
Field identification nursery
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Isolates of Rice Blast Fungus 212 isolates were collected in farmer fields and in trials.Province isolates
Yunnan Yuanyang 62shiling 45Banna 21
Sichuan shehong 41Guizhou Meitan 31Yunnan+ Guizhou predominant races 12
Total 212
Results – option 3
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Option 3 - (Cont.)
0.85
Shili ShiliYuanyang Yuanyang Meitan Yuanyang Meitan Shehong Shehong
Banna
Banna
37 differenthaplotypesand 27genetic lineagesat 0.85 similar linkagedistancelevel ,in 212 isolatesofblastfungus.
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Results - option 5
Cultivars
Isolates Frequency of virulent on cultivars143-
7a 08-SL-1-21 9-3 Y2009-31-1-6
S-2009-10-1-5
G2009-7-1-1
G2009-6-1-3
Hongyang-3 R R R R R S S 28.57
Yijing-1 R S S R R R R 28.57
magu S R R S R R R 28.57
Tuobeigu R R R S S R R 28.57
Changnuo-2 R R S R S R - 33.33
Hejing-7 R S S S R R R 42.86
Zaogu S R R S S R R 42.86
Xiangnuo R R R S R S S 42.86
Yinuo931 R S R S R S R 42.86
Chujing27 S R S S R R R 42.86
tuojiangnuo R S S R S R R 42.86
Chujing24 S R R S R S R 42.86
dulong-2 R S S S R R S 57.14
Chengnuo88 R S R S S S R 57.14
Yuelianggu S S R R S S R 57.14
Zimigu S R S S R S R 57.14
Nuoyou-9 S R S S S R R 57.14
zhangmeleng-2 R R S R S S S 57.14
zhangmeleng-3 R S S S R S R 57.14
Aijiaogu S R - S R S S 66.67
kaomolao S S S - R R S 66.67
Baiyangnuo R R S S S S S 71.43
Dianza31 S R R S S S S 71.43
Amoqie S S S S R R S 71.43
Hongjiaogu S S S S R R S 71.43
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Option 5 (Cont.)
Ri ce seedl i ng bl ast Ri ce pani cl e bl ast
HR
RMR
MS
SHS
3.51%
59.65%
14.04%
21.05%
1.75%
54.39%
1.75%12.20%
19.30%
12.20%
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• Three cultivars were R and two cultivars were MR when varieties are inoculated with isolates from Guizhou All the others were susceptible. These five cultivars are traditional cultivars from Yunnan.
• The twelve cultivars that are more resistant when inoculated with Yunnan isolates are different from the 5 varieties resistant to the Guizhouinoculum. This showed that genetic and pathotypic structure of rice blast fungus population from Yunnan and Guizhou might be different.
Option 5 (Cont.)
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Anthracnose Ascochyta ALS Rust
2009 2010 2009 2010 2009 2010 2009 2010
Average 2.98 2.45 4.84 3.54 1.57 3.28 3.88 3.62
Conclusions
2009 wet; 2010 dry Ochoa et al., 2010, unpublished data
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DS of rust
Populations plot mixture
48.1 5.0 44.0
29 5.0 48.5
65.1 15.0 6.7
29.1 16.2 62.5
45 21.7 27.5
58.1 22.5 5.0
64 27.5 44.0
28 52.0 8.3
67 52.0 27.5
33 52.0 44.0
21 68.3 33.3
22 71.2 18.8
47 71.2 44.0
65 71.2 46.8
50.1 80.0 6.7
Average 45.0 26.1
Conclusions
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Theoretical framework Damage abatement framework (Litchenberg&Zilberman, 1986). Banana diversity is treated as a direct input to yield and as an abatement input to yield losses caused by biophysical constraints
Econometric estimation approachNon- linear methods, a logistic model specification.
Conclusions
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• Banana variety diversity has no direct effect on yield
• Banana variety diversity reduces the yield losses caused by bio-physical constraints
• Gender of the farmer, nature of the decision maker, pests and diseases and distance to the tarmac roads influence banana variety diversity on farms
• Evenness of banana varieties within a plot produces more abatement effects
Results (Cont.)
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• THANK YOU FOR YOUR ATTENTION
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Let’s support diversity
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• Production information: Yield, yield losses, acreage, information on the banana varieties, labor, etc
• Household characteristics: Age, education, decision making, etc
• Market characteristics: Distances to markets, roads, buying and selling characteristics
• Farm characteristics; Slope, soil fertility, soil moisture
Results (Cont.)