By Dr. Solomon Mengestu Addisu Abera Solomon Abeyi Fantahun Dereje May, 2012 EIARBy Dr. Solomon Mengestu Addisu Abera Solomon Abeyi Fantahun Dereje May, 2012 EIAR Application of TechFit for Prioritization of Feed Technologies in Smallholder Beef Production System

2 No.VariablesWeredas AdamaArsi Negele KechemaKuriftuAli-WeyoKersa-Ilala 1Land size2 ha1.5 ha2 ha 2House hold Cropping Season3223 4IrrigationnoyesnoNo 5Labour Crops grownTef, wheat, maize, barley, beans and peas Tef, wheat, maize, barley, beans Tef, wheat, maize, barley Tef, wheat, maize, potato 7Fodder crops Grown Leucaena, Napier grass, Sesbania sesban Napier grass, fodder beet, alfalfa and Sesbania sesban vetchNo 8LivestockCattle, sheep, goats, donkey and poultry Cattle, sheep, goats, donkey, Horse and poultry Cattle, sheep, goats, poultry donkey and 9Source of Income 100% 9.1Agriculture Livestock Labour business00190 Overview of the production system

Introduction Adama and Arsi Negele Area  Feed scarcity is a major problem that limits animal productivity,  Improvement in livestock productivity can be achieved by alleviating feed constraints, Issue Farmers – Feed a constraint – Intervention needed Researchers – Technology options – Basket of technologies available  The aim is to select the best bet feed technologies for particular site/ selected villages of in Arsi and Adama Districts

What is Techfit? A tool used to prioritize of feed technologies at site-level TechFit is used to filter among the available technologies and prioritize best bet technologies from the available ones Involves combining scores of technology and context attributes to arrive at an overall score for how a technology is likely to fit a particular context. The tool it is still under refinement, for more use

METHODOLOGY  Adama District  Kechema  Wonji Kuriftu  Arsi Negele District  Ali Wayo  Kersa Ilala  Both Districts located in the Rift Valley

METHODOLOGY Adama Arsi Negele Kachema Wonji Kuriftu Ali Weyo Kersa Ilala  Proximity to woreda capital  Presence of Smallholder beef fattening activities Sites Selected Selection criteria

No. of Participants Wereda AdamaArsi NegeleTotal KechemaKuriftuAli-WeyoKersa-Ilala Male Female Total Numbers of participants from all kebeles.

Group discussion with farmers : Kechema 20 (15 men and 5 women) kuriftu 20 (11 men and 9 women) Aliweyo 22 (15 men and 7 women) KersaIlala 20 (15 men and 5 women) PRA Exercise PRA Exercise Scoring of the 5 tributes Work with the farmers Assessment of the 5 tributes Follow the steps given in the Techfit technology filtering excel sheet Ideas for Interventions select technologies based on score Filtering of Technologies 8 Methodology of The TechFit Tool

This preliminary study was conducted to score the context of farmers vis a vis land, labor, availability of cash, input delivery system, and skill of the farmer for technology adoption and demand of the technology for the above listed attributes.

Match farmers’ context to technology Score for technology attribute Score for context attribute LandX = LaborX = CreditX = InputX = KnowledgeX = If technology demands land => low score for land If farmers do not have or very small land holding => Low score for land

Potential technologies were filtered using farmers context and technology attribute scores Check list was used to collect information about the context attributes of farmers and the farmers gave scores to the context attributes The collected data were fitted to TechFit template to rank the technologies. Ref: Excel Sheet Feed technologies were evaluated based on 5 major attributes: land, labor, credit, input delivery system, and farmer skill.

III. TECHNOLOGY FILTER (Technology options to address quantity, quality, seasonality issues) Pre-filter available Technologies based on context relevance and impact potential Context relevance (score 1-6; low-high) X Impact potential (score 1-6; low- high) = Total score (context X impact)

13 Results and discussion TechFit-Beef Value Chain

NoTechnology options Pre-select the obvious (5-6) based on context relevance and impact potential Scope for improvement of attributes 1- 5 Total ScoreRank Context relevance (score 1- 6; low- high)) Impact potential (score 1- 6; low- high) Total score (context X impact) Score 1-5 (1 for less and 5 for more) A Improvements of crop residues 1 Machine chopping of residues 20I 2 Hand chopping of residues 12 IV 3 Generous feeding of CRs 18II 4 Generous feeding of CRs 14III 5 Feeding of home grown legume residues 11 V 6Feeding of bought in legume residues

Technology filter Technology options to address feed problem (list of technologies) After short listing first 3-4 technologies based on the Rank, go for cost benefit analysis of the selected ones Pre-filter – Context relevance X Impact potential score

Cost benefit analysis What does the technology cost? What does the technology deliver? Is it worthwhile?

DescriptionTechnology 1Technology 2Technology 3Technology 4 Cost Total Benefits 1 2 3

Notechnologies Total score (context X impact) Scope for improvement of attributes Total score Rank

Notechnologies Total score (context X impact) Scope for improvement of attributes Total score Rank

Notechnologies Total score (context X impact) Scope for improvement of attributes Total score Rank Table 2 cont’d

NoTechnology options Pre-select the obvious (5-6) based on context relevance and impact potential Scope for improvement of attributes 1- 5 Total ScoreRank Context relevance (score 1- 6; low- high)) Impact potential (score 1- 6; low- high) Total score (context X impact) Score 1-5 (1 for less and 5 for more) A Improvements of crop residues 1 Machine chopping of residues 20I 2 Hand chopping of residues 12 IV 3 Generous feeding of CRs 18II 4 Generous feeding of CRs 14III 5 Feeding of home grown legume residues 11 V 6Feeding of bought in legume residues

Final output Indentify promising feed technologies that are likely to work Better understanding of why and why not technologies work or do not work