Ethiopian Livestock Feed Project – approaches, tools, results


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Presented by Alan Duncan at the Ethiopian Livestock Feed Project Synthesis workshop, Addis Ababa, 28-29 May 2012

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Ethiopian Livestock Feed Project – approaches, tools, results

  1. 1. Ethiopian Livestock Feed Project – Approaches, Tools, Results Alan DuncanEthiopian Livestock Feed Project Synthesis workshop, Addis Ababa, 28-29 May 2012
  2. 2. Objectives Original: To develop a preliminary understanding of how feed components of intensifying livestock production systems in Ethiopia are changing as systems intensify and how this is reflected in the feed-related elements of focal value chains Evolving: To develop refined tools for rapid assessment of feed resources to allow effective feed intervention strategies to support intensification of livestock production in value chains benefiting smallholder producers.
  3. 3. Outputs s Refined tools for feed resource assessment, earc chain her s value analysis, rapid market appraisal and feedRe AR I technology prioritization R / AR EIA of feed elements of dairy, lera Targeted value chain assessment beef and sheep value chains gn a To Data base of price, quality and volume Ad udata on a seasonal basis for key feeds associated with the target value mat u chains. e Wa Ja n Synthesis of experiences with successful small ruminant pe/ feeding strategies from elsewhere andrtheir local a el ho h applicability B ill T e/Mic Assessment of feed availability and demandlas forsismall ruminant production in Menz area* e Hai les mel m Synthesis workshop Am ar Blu
  4. 4. Workshop objectives Review and refine the experience of using VCA, FEAST and Techfit tools and draw lessons for their improvement Think about application of the tools in wider contexts
  5. 5. Anticipated links to other initiatives CGIAR Research Programme 3.7, More milk, meat and fish, for and by the poor which involves targeted research on the small ruminant value chain in Ethiopia. Gates-funded East Africa Dairy Development Project (Phase 2) Multi-donor funded Agricultural Growth Programme for Ethiopia CIDA-funded Livestock Value Chain Enhancement (LIVES) project
  6. 6. Which tools? Value chain analysis (VCA) Feed assessment tool (FEAST) Feed technology prioritization (Techfit)
  7. 7. Process vs output Tools are designed as “discussion tools” No recipes or blue prints. Only a way of guiding and informing enquiry and suggesting options Use of tools needs to involve a range of actors: research, development, private sector, NGO etc
  8. 8. She epDa Menz iry Be e f
  9. 9. Value chain assessmentInputs & services Production Processing Marketing Consumers
  10. 10. FEASTThe problem
  11. 11. Feed assessment Conventionally focuses on: – The feeds – Their nutritive value – Ways of improving nutritive value FEAST broadens assessment: – Is livestock an important livelihood strategy? – How important are feed problems relative to other problems? – What about labour, input availability, credit, seasonality, markets for products etc.? – Involves dialogue with farmers
  12. 12. How does FEAST work?
  13. 13. Sample outputContribution of livelihood activities to household income (as a percentage) 6% 6% 32% Agriculture 14% Livestock Remmitance Labour Others Business 20% 22%
  14. 14. More sample output DM content of total diet Crop residues Purchased 5% 7% Naturally Cultivated occurring and fodder collected 25% 33% Grazing 30%
  15. 15. Final output Feast report with some ideas for key problems and solutions Better links and understanding between farmers, research and development staff
  16. 16. TechfitThe problem
  17. 17. What is your Feedmain problem
  18. 18. What feed technologies Planted foragehave you got? Urea treated straw Bypass protein OK, let’s try those
  19. 19. A solution
  20. 20. Techfit A discussion support tool for prioritizing feed technologies
  21. 21. The core conceptKey context attributes Key technology attributes Land Land Labour Labour Credit Credit Input Input Knowledge Knowledge
  22. 22. Matching context to technologyKey context Key technology attributes attributes Land Land Labour x Labour = Score Credit Credit Input InputKnowledge Knowledge
  23. 23. Technology filter r list ain filte core logy ilter M S hno P re-f III. Tec Score the pre-selected technologies based on the requirement, availability and scope for Pre-select the obvious improvement of five technology attributes TECHNOLOGY (5-6) based Scope for FILTER Attribute 5: improve on context relevance Attribute 1: Attribute 2: Attribute 3: Attribute 4: (Technology Knowledge ment of and impact potential Land Labour Cash /credit Input delivery attribute options to /skill s address Total Context Impact Total Requ Avail Requ Avail Requ Avail Requ Avail Requ Avail Score 1-5 quantity, Score 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 quality, 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 seasonality 6; low- 6; low- X impact) more; less; more; less; high; less; high; less; high; less; 5 for issues) 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)Urea treatment 2 3 6 3 2 2 2 2 0of strawSupplement with 2 5 10 3 3 3 2 1 1 1 1 3 1 2 22UMMBBy-pass protein 1 3 3 3 3 1 1 3 0feedFeedconservation 4 3 12 3 3 2 2 3 3 3 3 3 3 1 41(surplus)(HAY)etcetc
  24. 24. Cost-benefit assessment What does the technology cost? – Inputs, labour, land etc? What does the technology deliver? – Enhanced milk yield, improved reproductive performance, better growth etc Does it make sense? Adugna price/quality dataset helps here
  25. 25. Final output Ideas for some promising feed interventions that might work Better understanding of why the usual suspects often don’t work.
  26. 26. Fitting the tools together t VCA effor ee ded N Framework: is productivity the main issue? yes no FEAST Homing in: is feed the main issue? yes no ent C urr t or ffparticipatory Techfit options e testing
  27. 27. “If you do whatyou’ve always done, you’ll get what you always got.” Mark Twain
  28. 28. Key messages
  29. 29. More Information: 29