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Scaling up Ethiopia’s ‘Seeds for Needs’ approach of using agro-biodiversity to
adapt to climate change
Carlo Fadda, Senior Scientist, Bioversity InternationalWorld Bank, Addis Ababa, 15/01/2015
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In partnership with:
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Presentation’s Outline
Climate change
Green economy strategy: agricultural targets
Seeds for Needs: what is all about
Upscaling seeds for needs
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Climate Change: Is It Real?
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Climate Change: Some Evidence
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•Climate change, floods, droughts, unpredictable temperatures and rainfall
•Changing pest and pathogen populations and levels of pollination efficiency
•Increased soil and land degradation
Major Environmental Threats to Sustainable Production
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Adaptation to climate change: recommended actions by the IPCC
Improving crop tolerance to high temperature is a frequently
identified adaptation for almost all crops and environments
worldwide as high temperatures are known to reduce both
yield and quality
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Adaptation to climate change: recommended actions by the IPCC
Improving gene conservation and access to extensive gene
banks could facilitate the development of variety with
appropriate thermal time and thermal tolerance characteristics
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Adaptation to climate change: recommended actions by the IPCC
Indigenous Knowledge (IK) has developed to cope with
climate hazards contributing to food security in many parts of
the world
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Ethiopian Green Economy Strategy
Target set for agriculture:
• Boost agricultural productivity (+40% increased production for major crops such as teff, maize, wheat);
• Intensify agriculture through usage of improved inputs and better residue management resulting in a decreased requirement for additional agricultural land that would primarily be taken from forests;
• Create new agricultural land in degraded areas through small-, medium-, and large-scale irrigation to reduce the pressure on forests if expansion of the cultivated area becomes necessary
• Introduce into cultivated areas lower-emission agricultural techniques, ranging from the use of carbon- and nitrogen-efficient crop cultivars to the promotion of organic fertilizers
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Under conditions of change
(reducing the probability of loss of agricultural
productivity in the future, while enhance productivity
today)
The fundamental question:
Productivity and reduced vulnerability
How can we ensure that agricultural productivity increases are
accomplished in ways that create and enhance ecosystem
resilience and services for the poor?
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Minimum Goals for 2050
Environmental Goals Development Goals
Total Agricultural Production
Nutritionally Complete Production
Biodiversity Conserved
Carbon Sequestered
Food Security Goals
Increased Farmer Livelihoods
And Resilience
Increase Farm Self Reliance
Adapted from Foley et al 2011
The Case of Durum Wheat
Improve Human Health
Food Distribution and Access
Conserve agrobiodiversity
Water Conserved
Improved Water Quality
Soil Formed
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Unexploited Potentials in Landraces
• disease resistance (Leppik, 1970; Negassa, 1986; Klindworthet al., 2007; Jemanesh et al., 2013);
– e.g. Ethiopian landraces are the source for Sr13 gene, which is responsible for stem rust resistance
• Drought tolerance/resistance (Tesfaye, 2001; Mondini et al., 2010, our study)
• Very diverse for qualitative and quantitative traits
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What We Did
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Phenotyping trials
The genotypes, 373 landraces and 27 improved wheat varieties, were phenotyped attwo locations (Hagreselam and Geregera) in 2012 and 2013 main cropping seasons for 10important traits:
A. Phenological traits
• days to 50% booting (DB);
• days to 50% flowering (DF) and;
• days to maturity (DM)
B. Morpho – agronomic traits
• plant height (PH);
• number of effective tillers per plant (NET);
• spike length (SPL);
• number of seeds per spike (SPS);
• above ground dry biomass (BY);
• grain yield (GY).
Phenotyping (external characteristics)
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0
10
20
30
40
50
60
70
80
<µ - 2SD µ - 2SD to µ -SD
µ - SD to µ +SD
µ + SD to µ+2SD
>µ +2SD
DISTRIBUTION OFGENOTYPES INTO
VARIOUS CLASSES
HS GER Com
Performance of Genotypes Across Locations
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Landraces Performance Compared With the Best Improved Variety
The table tells that:
•21%, averaged over traits, of
the landraces are superior to
the best performer IM variety
•Many landraces mature
earlier than the IM varieties
•A yield advantage of 61%
obtained from the best
landrace over the best IM
variety (Robe)
Trait
Superior
(IM)
Superior
(LRs) no‡ %age
No
Geregera
%
Geregera
DB* 59.69 55.54 1 0.3 1 0.3
DF* 70.8 69.88 1 0.3 5 1.6
DM* 116.59 109.34 57 18.4 71 23.0
PH 110.34 115.07 8 2.6 5 1.6
NET 7.14 7.48 90 29.1 48 15.5
SPL 7.94 9.5 125 40.5 19 6.1
SPS 41.67 41.83 1 0.3 2 0.6
BY 7.17 9.99 97 31.4 47 15.2
GY 2.17 3.49 68 23.9 22 7.1
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Ethiopian Unique Genetic Diversity
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Landraces vs. Improved Genetic Divergence
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Crop Improvement
Grain Yield as
quantitative trait in
Hagereselam 2012
Plot overall
performance in
Hagereselam 2012
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Modified from Yu et al. 2008
Principal Facts• 52 RIL families
• 180 – 200 lines
• > 9,000 F6 lines in
Dec. 2014
• wide phenotypic
variation
Development of a Structured Multiparental PopulationNested Association Mapping - NAM-Population
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Misiko (2013)
Limitations
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Seeds for Needs
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(1)
Genetic
diversity
(2)
Selection &
cultivation
(3)
Harvest
(4)
Value addition
(5)
Marketing
(6)
Final
use
Outcomes
Empowerment of communities: more
resilient to eco-socio-economic changes,
more resilient food systems
Outcome
Preservation of options
for resilient systems
Outcome
Self-reliance of value chain
actors on broader set of
options, making them more
resilient to market changes
From Farm to Fork: Biodiversity Contribution along the Value Chain
IMPACTImproved
nutrition,
incomes and
other
livelihood
benefits
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3. Farmers test
and report back by
mobile phone
3. Environmental data
(GPS, sensors) to assess
adaptation4. Data are used
to detect
demand for new
varieties and
traits
4. Farmers receive tailored variety
recommendations and can order seeds
The process
2. Each farmer gets a different
combination of varieties
1. A broad set of varieties
is evaluated
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Participatory Evaluation
• 30 farmers per location (15
male + 15 female)
• Individual score on 5 traits for
800 plots
• > 200,000 data points
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Participatory Variety Selection (PVS)Mother and Baby Trial Approach
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3. Farmers test
and report back by
mobile phone
3. Environmental data
(GPS, sensors) to assess
adaptation
1. A broad set of varieties
is evaluated
4. Data are used
to detect
demand for new
varieties and
traits
4. Farmers receive tailored variety
recommendations and can order seeds
The process
2. Each farmer gets a different
combination of varieties
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Crowdsourcing
31
- 2 woredas
- 12 villages
- 85 km by 32 km cover
- 2400 to 3100 masl
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• 32 genotypes (pre-selected by farmers)
• 24 farmers
• 4 genotype per farmer
• 3 times replication of each genotype
Mother and Baby Trial Approach
32Monthly report by a group of farmers Method of communication with farmers
I-button in each farmer plot
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Crowdsourcing
• 4 genotypes per farmer
• All package was sent to each
farmer
• 200 farmers, 12 different villages
• 21 genotypes, 1 common for all 200
farmers
• 30 times replication of each genotype
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Crowdsourcing
• Enumerator selection and training
• Farmers trained
• Bylaws developed
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iButtons and Rain Gauge
iButton holder preparation
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Different Stage Performances
Undergone meeting every month at each village and made report
Researchers data collection
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2. Each farmer gets a different
combination of varieties
1. A broad set of varieties
is evaluated
4. Data are used
to detect
demand for new
varieties and
traits
4. Farmers receive tailored variety
recommendations and can order seeds
The process
3. Farmers test
and report back by
mobile phone
3. Environmental data
(GPS, sensors) to assess
adaptation
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group number FourFarmers Name: 1. Guzguz Gelaw2.Yeshi Nega 3. Aregitu Moges 4. Abebabye Mebrate 5.Melkam Tseganew
Farmer
No
Farmer Name የአ/አደርስም
Plot No.
የመደብ
ቁጥር
Treat
No.
የተጠኝ
ቁጥር
Acc
Name
የዝርያ ስም
Earliness/ፈጥኖ ደራሽነት Tillerig C/የጋቻ አመታት Spike Q/የዛላ ሁኔታ Disease/የበሽታ ሁኔታ Overall/አጠቃላይ
Remark/ማስታ
ወሻየአ/አ ተ.ቁ 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5
አራጋውመብራት 1 8 222854 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 3 2 2 2 2 2 3 2 2
Aragaw Mebrat 2 9 238576 3 3 2 2 2 2 2 2 2 2 2 2 2 3 2 3 3 2 2 2 2 2 3 2 33 22 236300 4 3 3 2 2 1 1 1 1 1 1 2 1 2 1 2 2 1 2 2 2 3 2 1 34 25 222736 1 2 2 2 1 2 2 1 1 1 2 2 1 2 1 2 2 1 2 2 1 2 2 1 2
ምስጋናውሙሉጌታ 1 2 204488 4 4 4 4 3 3 3 3 3 2 4 4 3 4 3 3 3 3 3 3 3 4 3 3 3
Misganaw Mulugeta 2 11222816B 3 4 4 3 3 3 3 3 3 3 3 4 3 4 4 3 3 3 4 3 4 4 3 4 33 24 206551 5 5 5 3 4 3 3 3 3 3 3 3 3 4 4 4 3 3 3 3 3 4 4 5 34 27 222408 2 3 3 3 2 3 3 3 4 3 3 4 3 4 4 3 4 3 4 3 4 5 4 5 4
የሽ ነጋ 5 5 5 4 4 2 3 3 4 3 3 2 3 3 3 3 2 2 3 3 3 3 3 3 2
Researcher Data
Farmers score Mother trial
Farmers score Baby trial
Both farmer data and researcher data has been recorded and is being processed
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Harvesting Biomass
Grain yieldNumber of seeds per spike
Balance was distributed to all villages
Harvesting and data collection
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3. Farmers test
and report back by
mobile phone
2. Each farmer gets a different
combination of varieties
3. Environmental data
(GPS, sensors) to assess
adaptation
1. A broad set of varieties
is evaluated
4. Data are used
to detect
demand for new
varieties and
traits
4. Farmers receive tailored variety
recommendations and can order seeds
The process
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Strengthening Community Seed Systems
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Upscaling and Outscaling Seeds for Needs
Reaching more farmers and for more crops
• Capacity development
• Approach institutionally embedded in extension services and agro-
dealer networks
• Methodology improved and expanded using ICT-based solutions
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Crowdsourcing plan
• Initial investment for a new crop such as teff, sorghum, pulses,
targeting 500 farmers/site for 2 years
• Crop technical characterization
• Participatory evaluation
• Capacity development
• Crowdsourcing
• Subsequent distribution through crowdsourcing: targeting
10,000,000 HH over 3-4 years including seed multiplication
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Strengthening Seed Systems
Institutional
genebanks(National, private, experimental
stations, universities…)
Community Seedbanks
CGIAR genebanks
International Genebanks
Regional
genebanks
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To strengthen the seed network one needs more than one
seed bank/landscape (roughly 10 to reach 10,000
households).
Goal: to reach 200,000 households in 20 landscapes
across the country