Use of Agrobiodiversity for Pest and Disease Management

Carlo Fadda, Bioversity International ODDG Seminars, 19 May 2011

Outline

• Overview of the Project• Research Methodology• Main Results• Final Remarks

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

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

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

Outcome: Benefits to local communities

• Reduced crop vulnerability

• Reduced crop loss

• Increased incomes

• Increased capacity and leadership abilities

• Benefit sharing protocols with communities

Methodology

• Participatory Diagnostic:

– Focus Group Discussion;

– Household Survey;

– Technical Evaluation (laboratory and field analysis).

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

• 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

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

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

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

Results - Option 1 (Cont.)

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

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%).

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

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

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

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.

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

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%

• 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.)

 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

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

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

• 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.)

• THANK YOU FOR YOUR ATTENTION

Let’s support diversity

• 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.)