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TechFit: A tool for prioritizing feed technologies

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Presented by Adugna Tolera (Hawassa University) at the Training Workshop on Feed Assessment Tools, ILRI, Addis Ababa, 18-21 November 2013 …

Presented by Adugna Tolera (Hawassa University) at the Training Workshop on Feed Assessment Tools, ILRI, Addis Ababa, 18-21 November 2013

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  • Ethiopia

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  • 1. TechFit : A Tool for Prioritizing Feed Technologies Adugna Tolera (ICARDA) Training on Feed Assessment Tools, ILRI, Addis Ababa, 18-21 November 2013
  • 2. Objectives  To have a common understanding, interpretation and application of the tool  To learn how to score and match technology attributes and context attributes of farmers  To customize the application of the tool to the local context
  • 3. Background  Reality No. 1 (Reality of farmers)  Livestock production is important  Feed is a major constraints (FEAST & Other reports)  Farmers are looking for a remedy to the problem  Reality No. 2 (Reality of research & development efforts)  Various feed technologies generated by the research system  Lack of systematic approach for prioritizing available feed technologies  Poor adoption rate of available technologies  Wastage of substantial efforts and resources
  • 4. Feed interventions often do not work – why?  Failure to place feed in broader livelihood context  Lack of farmer design and ownership  Neglect of how interventions fit the context: land, labour, cash, knowledge etc FEAST Techfit
  • 5. What is TechFit?  A discussion tool for prioritizing feed technologies  Helps to identify suitable technologies for evaluation and screening  Designed to filter best bet technologies from a basket of technologies available to farmers  Provides better understanding of why and why not technologies work or do not work
  • 6. How does it work? Technology options to address feed problem (list of potentially available technologies) Technologies are filtered at different levels Only technologies with high total scores carried forward to the main filter
  • 7. How does it work? (Cont …)  Main filter – involves combining scores of technology and context attributes to arrive at total score  Technology attributes – requirement of a given technology for land, labor, cash/credit, inputs and knowledge  High score => low likelihood of adoption  Context attributes – availability of land, labor, cash/credit, inputs and knowledge  High score => high likelihood of adoption
  • 8. Match farmers’ context to technology Score (1-5) for technology attribute Land (1-5) Labor (1-5) Credit (1-5) Input (1-5) Knowledge (1-5) Total score Rank Score (1-5) for context attribute X X X X X Land (1-5) Labor (1-5) Credit (1-5) Input (1-5) Knowledge (1-5) = = = = = = ? If technology demands land => low score for land If farmers do not have or have very small land holding => Low score for land
  • 9. Technology filter III. TECHNOLOGY FILTER (Technology options to address quantity, quality, seasonality issues) Urea treatment of straw Supplement with UMMB By-pass protein feed Feed conservation (surplus) (HAY) etc etc Pre-select the obvious (5-6) based on context relevance and impact potential Score the pre-selected technologies based on the requirement, availability and scope for improvement of five technology attributes Attribute 1: Land Attribute 2: Labour Attribute 3: Cash /credit Attribute 4: Input delivery Attribute 5: Knowledge /skill Scope for improve ment of attribute s Context Impact Total Requ Avail Requ Avail Requ Avail Requ Avail Requ Avail Score 1-5 relevanc potential score Score 1-3 Score 1-3 Score 1-3 Score 1-3 Score 1-3 Score 1-3 Score 1-3 Score 1-3 Score 1-3 Score 1-3 (1 for e (score 1- (score 1- (context (1 for (1 for (1 for (1 for (1 for (1 for (1 for (1 for (1 for (1 for less and 6; low- 6; low- X impact) more; less; more; less; high; less; high; less; high; less; 5 for high)) high) 3 for 3 for 3 for 3 for 3 for low) 3 for 3 for low) 3 for 3 for low) 3 for more) less) more) less) more) more) more) more) 2 3 6 3 2 5 10 3 1 3 3 3 4 3 12 3 2 3 3 2 2 3 3 2 1 2 1 1 2 3 1 2 1 1 3 3 3 0 1 2 3 3 3 Total Score 22 0 3 1 41
  • 10. How to do scoring and ranking? • List of potential technologies obtained from the research system • Context relevance and impact potential – by experts at each specific location • Technology attributes (requirement of the technology for land, labor, etc. ) – by experts • Context of farmers (availability of land, labor etc.) – by farmers (interview a group of representative farmers and ask them to score)
  • 11. Cost benefit analysis • Short list the best 3-4 technologies for cost-benefit analysis • What does the technology cost? (type of feed, amount used, % of total feed, cost, % of total feed cost) • What does the technology deliver? (animal performance measure, % contribution to the performance change, % contribution to income gain) • Is it worthwhile?
  • 12. Cost-benefit analysis  Method not yet well developed and refined  Mostly based on a number of assumptions using partial budget analysis  Compare additional costs and additional benefits i.e. marginal benefits
  • 13. Intervention name Clear description focusing processes and actions with pictures and glossary for specific terms Technical Information Key technology attributes • Land area required • Labour, including gender • Skills/Knowledge • Cash/Credit • External inputs • Capital / infrastructure Benefits • Primary (including time dimension, etc.) • Secondary • … Applicability • Purpose / Addresses constraints – opportunities • Which animal? • Agroecological, farming system suitability including socio-cultural issues (e.g., taboos) if applicable • Scale • History of use • Potential to integrate with … Adoptability characteristics • (=conclusion: simplicity, observability, use, etc. • …
  • 14. Adoptability Protocol - Process • Past experiences regarding introduction of technologies, including uptake, community feeling, etc. • Ranking of livelihood ambitions/aspirations in general and for agriculture and livestock in particular After becoming more and more reductionist and analytical, bring it back into the broader perspective Objective  Subjective  FGD on options • Give info on options • Ask community to rank • Discuss ranking, ‘why’, etc. (guiding points/questions)  Link to CBA data  Select trial farmers for AR (model or pioneer farmers)
  • 15. Factor Relative advantage superiority Compatibility Complexity Guiding points/questions to keep in mind in FGD CBA analysis, but subjective points may be raised in group • Quality of labour (drudgery), etc. • Riskiness - technology, risk aversion • Social acceptability &/or taboos • Effect on gender aspects or child labour • Possibility of adapting to or in local situation Relatable to something simple, familiar, routine, etc. Trialability Resources present for implementation Observability (Should perhaps be made as Techfit filtre) Delivery process • Competence, capacity & buy-in of local extension staff • Enabling environment
  • 16. Data we need to derive from FEAST to feed into Techfit  Main constraint  Seasonality  Quantity  Quality  Dominant commodity  Beef  Dairy  Sheep/Goats  Pigs/poultry  Farming system  Pastoral  Agro-pastoral/mixed  Intensive/mixed (crop-livestock)  Landless  Core context attributes  Requirement for land  Requirement for labour  Requirement for cash credit  Requirement for inputs  Requirement for knowledge/skills
  • 17. Seasonality  Consult seasonal calendar – estimate proportion of minimum availability to maximum availability      1.0 = 0 >0.75 = 1 >0.5 = 2 >0.25 = 3 >0.0 = 4  Is minimum in the dry/winter season? – Winter season scarcity  Is minimum in the growing season? – Growing season scarcity
  • 18. Quantity  If you place more basal feed in front of your animals would they consume it?      With extreme enthusiasm = 4 With considerable interest = 3 With some interest = 2 Yes but not immediately = 1 No = 0  Something also about interest in supplemental/high quality feed?
  • 19. Quality  If you placed more basal feed in front of your animals would they consume it?      With extreme enthusiasm = 0 With considerable interest = 1 With some interest = 2 Yes but not immediately = 3 No = 4
  • 20. Commodity focus  On a scale from 1 to 10 how important are the following enterprises to cash income:  Beef  Fattening  Breeding stock  Dairy  Sheep/Goats  Fattening  Breeding stock  Pigs/poultry      0-2 = 0 2-4 = 1 4-6 = 2 6-8 = 3 8-10 = 4
  • 21. Farming system  Which of the following best describes the target group:     Pastoral Agro-pastoral/mixed Intensive/mixed (crop-livestock) Landless
  • 22. Experiences in testing and application of the tool  Tested to prioritize feed technologies for 3 different commodities (dairy, beef, sheep) in different parts of Ethiopia  Preceded by assessment of livestock production and feeding systems using Feed Assessment Tool (FEAST)  Enabled rapid prioritization and short listing of potential feed technologies  The pre-filter (context relevance score) helped a great deal to focus attention on those technologies that are relevant in the area.
  • 23. Strengths of the tool  Enables rapid location specific prioritization and short listing of feed technologies in different agroecologies and production systems  Puts feed in a broader context and filters technologies for specific contexts (agro-ecology, production system, farmers’ contexts etc.) • It is robust in screening out technologies that are not relevant in a given context • Gives good indication why some technologies are not easily adopted
  • 24. Limitations of the tool  All scores are based on subjective judgments. Thus one has to be well versed with the subject matter and the local conditions to give a realistic score.  Cost benefit analysis is based on a number of assumptions and the validity depends on the soundness of each assumption.  Most feed technologies make only partial contribution to the total diet  a challenge of partitioning the contribution of the feed in question to the performance of the animal
  • 25. Project partners in Ethiopia
  • 26. Thank You Africa Research in Sustainable Intensification for the Next Generation africa-rising.net The presentation has a Creative Commons licence. You are free to re-use or distribute this work, provided credit is given to ILRI.