Characterisation and stratification of legume producers and production systems in Ethiopia Andrew Farrow N2Africa Ethiopia Launch Workshop February 2014

Phase 1 Mid-term Review: Key Questions for N2Africa How to embed G x E x M within market and institutional context? How to understand best fit without understanding farmer adoption?

Phase 1 Mid-term Review: Key Questions for N2Africa How to embed G x E x M within market and institutional context? Develop a conceptual framework to expand G x E x M

Conceptual framework for scaling-out N2Africa (G L x G R ) x E x M SU Marketing for sale and utilisation of the legume crop D 1 Delivery / availability of legume genotypes D 2 Delivery / availability of strains of rhizobium D 4 Delivery / knowledge of management practices D 3 Delivery / availability of other inputs

(G L x G R ) x E x M D 1 Delivery / availability of legume genotypes D 2 Delivery / availability of strains of rhizobium SU Marketing for sale and utilisation of the legume crop D 4 Delivery / knowledge of management practices D 3 Delivery / availability of other inputs

Research design required that allows learning about D 1, D 2, D 3, D 4 and SU Conceptual framework for scaling-out N2Africa

Phase 1 Mid-term Review: Key Questions for N2Africa How to understand best fit without understanding farmer adoption? Review literature of adoption of legumes in Africa

Review of constraints to adoption – methodology 318 papers screened 52 papers reviewed in detail Bias to studies in Africa Some non-legume studies included (e.g. agroforestry, CA, upland rice) Constraints recorded Frameworks for conceptualising constraints analysed

Review of constraints to adoption – effect on research design and site selection Test different treatments, delivery and dissemination and marketing mechanisms which can be influenced Stratify those constraints that cannot be controlled but which will have an effect on the ‘fit’ Monitor constraints which are dynamic, difficult to predict and therefore difficult to stratify or test

Characterisation and stratification  Practical objective – Provides a structure of domains for sampling and testing – Selecting action sites for implementation and evaluation (e.g. baseline)

Constraint / factor affecting adoption Scale / level of constraint Action Biophysical relevance of technology Multiple Stratify during woreda selection and within woredas Household access to Capital / Assets Household Land availability, quality or tenure Multiple Stratify during woreda selection and within woredas Output market for agricultural (legume) products Multiple Stratify during woreda selection and within woredas Availability of labour Household and Community Gender Household and Community level Education / literacy of the farm household members Household and Community Experience of the farm household members Household

Characterisation and stratification  Definition of variables, indicators and spatial units for each strata – Biophysical relevance of technology – Land availability, quality or tenure – Output market for agricultural (legume) products

Ethiopia – adoption domains High Agricultural Potential Low Agricultural Potential Good Market Access High Population Density 12 Low Population Density 34 Poor Market AccessHigh Population Density 56 Low Population Density 78 Biophysical relevance of technology – low and high potential Land availability, quality or tenure – low and high population density Output market for agricultural (legume) products – good and poor physical access to markets

N2Africa Target Districts in Ethiopia ‘Best bet’ grain legume crops defined in the bridging grant phase of N2Africa for Target Areas PartnerBest bet legume cropLocation / Woreda Amhara Regional Agricultural Research Institute (ARARI)/ Bahir Dar University Faba Bean Chickpea Farta Bichena Ethiopian Institute of Agricultural Research - Pawe Agricultural Research center - Debrezeit Agricultural Research Center - Melkasa Agricultural Research center Soybean, Common bean Chickpea Common bean Pawe Guanga (Guangua) Akaki Adje or Aje (in Shalla / Siraro woreda west Arsi) Hawassa University/Southern Agricultural Research Instititute Common bean Chickpea Borcha (Boricha) Bodity (Damot Gale) Oromia Regional Agricultural Research Institute (OARI) Soybean, Common bean Faba bean Bakko (Bako Tibe) Sinana

Stratify by key factors Adoption domains Factors: Agro-ecological Zone, Market Access, Population density Stratification

Adoption Domains - chickpea

Ethiopia – sites within adoption domains High Agricultural Potential Low Agricultural Potential Good Market Access High Population Density W Borcha (Boricha) Bodity (Damot Gale), E Borcha (Boricha), Farta Low Population Density NE Mandura Akaki, Bichena, Adje (Shalla), Bakko (Bako Tibe), Sinana Poor Market AccessHigh Population Density NE Farta Low Population Density SW Mandura Sinana, (Bako Tibe)

Constraint / factor affecting adoption Scale / level of constraint Action Biophysical relevance of technology MultipleStratify within woredas Household access to Capital / Assets Household Land availability, quality or tenure MultipleStratify within woredas Output market for agricultural (legume) products MultipleStratify within woredas Availability of labour Household and Community Gender Household and Community level Education / literacy of the farm household members Household and Community Experience of the farm household members Household

Probability pH < 5

Constraint / factor affecting adoption Scale / level of constraint Action Biophysical relevance of technology Multiple Household access to Capital / Assets Household Stratify within kebeles Land availability, quality or tenure Multiple Output market for agricultural (legume) products Multiple Availability of labour Household and Community Stratify within kebeles Gender Household and Community level Stratify within kebeles Education / literacy of the farm household members Household and Community Stratify within kebeles Experience of the farm household members Household Stratify within kebeles

Thank you Characterisation and stratification of legume producers and production systems