Abiso, T.

Mekonnen, A.

Mengistu, S.

Wamatu, Jane

Woldi, S.

CGSpace

       Using the Techfit tool to prioritize feed technologies in Serera, Doyogena District, Southern Ethiopia    A. Mekonnen1, S. Mengistu1, S. Woldi1, T. Abiso1 and J. Wamatu2   1Areka Agricultural Research Center 2International Center for Agricultural Research in the Dry Areas          April 2014  www.livestockfish.cgiar.org      CGIAR is a global partnership that unites organizations engaged in research for a food secure future. The CGIAR Research Program on Livestock and Fish aims to increase the productivity of small-scale livestock and fish systems in sustainable ways, making meat, milk and fish more available and affordable across the developing world. The Program brings together four CGIAR Centers: the International Livestock Research Institute (ILRI) with a mandate on livestock; WorldFish with a mandate on aquaculture; the International Center for Tropical Agriculture (CIAT), which works on forages; and the International Center for Research in the Dry Areas (ICARDA), which works on small ruminants. http://livestockfish.cgiar.org  © 2014 This publication is licensed for use under the Creative Commons Attribution-Noncommercial-Share Alike 3.0 Unported Licence. To view this licence, visit http://creativecommons.org/licenses/by-nc-sa/3.0/. Unless otherwise noted, you are free to copy, duplicate, or reproduce and distribute, display, or transmit any part of this publication or portions thereof without permission, and to make translations, adaptations, or other derivative works under the following conditions:   ATTRIBUTION. The work must be attributed, but not in any way that suggests endorsement by the publisher or the author(s).   NON-COMMERCIAL. This work may not be used for commercial purposes.   SHARE ALIKE. If this work is altered, transformed, or built upon, the resulting work must be distributed only under the same or similar license to this one.   NOTICE:  For any reuse or distribution, the license terms of this work must be made clear to others. Any of the above conditions can be waived if permission is obtained from the copyright holder. Nothing in this license impairs or restricts the author’s moral rights. Fair dealing and other rights are in no way affected by the above. The parts used must not misrepresent the meaning of the publication. ILRI would appreciate being sent a copy of any materials in which text, photos etc. have been used.    .          Introduction Shortage of feed and its low quality are the major bottlenecks for livestock production in Ethiopia. A feed assessment study using the FEAST tool identified feed as the second most pressing problem limiting livestock productivity in Serera kebele of Doyogena District. Several feed technologies have been generated by the research systems over the last four to five decades, costing substantial amount of efforts and resources. However, adoption rate of the technologies has been very poor due to lack of suitable mechanisms for filtering and prioritizing the available feed technologies for specific locations and situations. In order to fill this gap, the International Livestock Research Institute (ILRI) has recently developed a simple tool known as TechFit for prioritization of feed technology options to enable better targeted interventions to address livestock feed problems in specific locations. Thus this study was carried out with objectives of prioritizing suitable feed technologies from a basket of options for Serera kebele of Doyogena district using the TechFit tool. The study was conducted from 26 - 30 December, 2013 by researchers from Areka Agricultural Research Center with backstopping from the International Center for Agricultural Research in Dry Areas (ICARDA).  The study areas  Doyogena district is found in Kembata Tembaro zone in the SNNPR region. The district is situated 258 km south of Addis Ababa. The altitude of the district ranges from 1900 to 2300 m.a.s.l. Agro-ecologies of the area are classified as midlands (30%) and highlands (70%). The annual rainfall varies between 1200-1600mm.The mean temperature varies from 10-160C. The district possesses 14 peasant association and 17,263.59 hectares of area coverage. Among this 86% used for crop cultivation, forest and bushes 11.8%, 2% grazing land, and 0.2% degraded land. The district has a livestock population of cattle (46703), sheep (13822), goat (1,444), equine (6,343) and poultry (27,253).  In Serera, the maximum, average and minimum landholding per household is 3.5ha, 0.75 and 0.25ha respectively with an average family size of 5. The major crops produced in the area include enset, wheat, potato and faba bean. Farmers rear different types of animals which include cattle, sheep, goat, equine and poultry. About 60% of the household income sources are from crop production and the remaining 40% from livestock production. From the 40% of livestock income, 30% comes from small ruminants and 10% from others.   Selection of kebeles, farmers and context attribute scoring  Serera is one of the ICARDA sheep improvement sites where the sheep value chain was conducted. Thus the kebele was selected because it is under ICARDA program. Farmers for the study were selected based on gender, age and wealth criteria. Both male and female farmers were involved. Elders and youths to address the age issue were also considered. To get all wealth group of farmers, size of landholding was considered, thus farmers from small, medium and large land size were involved. A total of 20 farmers (18 male and 2 female) participated in the study. The Techfit group discussion was made after assessing feed resource availability using the Feed Resources Assessment Tool (FEAST) using a Participatory Rural approach. The participants were selected with the help of the kebele Administration and development workers using the pre-set criteria mentioned above.      Data collection  A checklist was used to collect information about the context attributes of farmers. Using the checklist farmers were asked to give score from 1 to 4 for availability of or access to land, labour, credit/cash, input delivery and farmer’s knowledge and skill. Highest availability of attribute scored a value of 4 whereas lowest availability scored 1.   Data analysis From the list of the technology options based on their context relevance and impact potential of each technology in addressing feed problem issues, technologies were pre filtered. The filtered and selected technologies were passed to the main filter to be evaluated by farmers for their context attribute (availability of land, labour, cash/credit, material input and knowledge) and the context attribute scoring of technologies were done with the value of 1-4 (1 for lowest attribute and 4 for the highest attribute). The data on the context attribute was entered into the Techfit excel template to get the total score based on which prioritization of technologies was made.    Results Farmers’ context score  During the focus group discussions, farmers gave a score for the context attribute with a justification. Table 1 below shows farmers’ context attribute scores (scores for availability of land, labour, cash/credit, inputs delivery, and knowledge) for Serera. The lowest score was given for cash/credit service. Land, labour and knowledge got the same and highest score of 3.   Table 1: Farmers’ context attributes score for the different attributes in the Serera  Attributes  ( 1- 4 scale)* Score Justifications given by farmers  Land  3  Even though land for farming is in shortage, the size of the land available to use for any land demanding technology is fairly available   Labour  3  Farmers believe there labour is not a problem in the area, because average family size in the kebele is large. Cash/credit  1 The money farmers have is not enough to properly run their farming business. In that case they need credit service, but the service in not easily accessible   Inputs  2  The availability of inputs particularly those related to livestock production are not easily accessible/available  Knowledge/skill  3  Farmers believe that they have no serious knowledge/skill problem as they get advice from DAs  *1 = lowest and 4 = highest  Technology screening at pre-filtering stage A total of 40 feed technologies categorized under different groups were screened based on their context relevance and impact potential for the area at pre- filtering stage. 18 technologies with    lower relevance and impact potential for the area to address issues of feed problems were dropped (Table 2), whereas 22 technologies that got higher total scores were carried forward for further evaluation at main filtering stage using scores for technology attributes, farmers’ context attributes and scope for improvement.   Table 2: List of dropped technologies at pre-filtering stage with justifications for dropping Technologies Reason for dropping  Improvements of crop residues   Machine chopping of residues Experience is limited and the technology not available Feeding of bought in legume residues Selling crop residues especially for legumes does not exist Supplementation  Supplement with home-produced local brewers waste Use of such supplementation is not experienced in the rural areas, it is most common in the cities Supplement with bought in local brewers waste Commercialization of local brewers waste is not common Use leaves and/or pods of farm trees (e.g. acacias, milletia etc) In the area such trees do not grow Commercial dairy supplements In the area commercial dairy supplement is not available  Use of oats grain and hulls for supplementary feeding The feed technology is not known by farmers. Moreover, grain production of oat is not common  Poultry litter Commercial poultry farm is not available in the area Feed conservation  Making hay from cultivated perennial fodder wth specialist seed (e.g. alfalfa, Rhodes) Due to land shortage allocation of land for perennial fodders is relatively difficult  Buying baled day (e.g. oats/vetch, rhodes grass, meadow etc.) The feed technology is not available Feed conservation (silage) It is labour demanding, new to the area, needs investment Fodder tree leaf meal The technology is new , difficult for adoption and it is land demanding Improved forages  Fodder beet for cooler highlands Agro-ecological limitation and it occupy the limited land the farmers have  Use of improved perennial grass-legume mixture (e.g.Rhodes-alfalfa forage or hay) Allocation of land for production of perennial feed is not possible Feeds from cropping systems  Thinning (e.g. maize and/or sorghum - cutting green at knee height)  Agro-ecological limitation. Production of maize is not common, maize and sorghum are not produced in the areas)  Use of tops, leaf strips (e.g. maize or sorghum) Agro-ecological limitation; maize and sorghum are not grown in the areas  Crop/forage intercropping (sorghum/cowpea for dry areas and maize/lablab for wetter areas) Intercropping of forage with crops is not common and adoption will be difficult Balancing feeds  Complete feed-TMR (mash, block, pellet) The feed is not available in the area     Prioritization of potential feed technologies at main filtering stage  At the main filter stage, out of the 22 technologies 12 top ranking technologies were selected for Serera based on context attributes, technology attribute and scope for improvement (Tables 3). Technologies with lower requirement for land, labour, cash/credit, input and knowledge had higher probability of being selected. Hence, most prioritized technologies as a remedy to the problems of feeds in quality, quantity and seasonality for the study area were those which demand less land, labour, cash, input and knowledge.   The selected technologies for Serera included crop residues improvement (feeding of home grown legume residues, hand chopping of residues, and rethreshing and mixing of crop residues before storage, generous feeding of crop residues and treatment of crop residues, e.g. urea treatment, improved forages (fodder trees, use of improved annual grass-legume mixture, and improved forage grasses), supplementation (supplement with agro-industrial by-products, and supplement with urea molasses mineral blocks), feeds from cropping systems (use of weeds, cut grass, tree leaves) and smart feeding (targeted use of bought-in concentrates to target productive animals). Feeding of home grown legume residues got highest total score followed by hand chopping residues and use of weeds, cut grass, tree leaves. On the other hand improved forage grasses and treatment of crop residues (e.g. urea treatment) got the lowest score.   Table 3: List of feed technologies prioritized using the TechFit tool in Serera   List of feed technologies Total score Rank Feeding of home grown legume residues 36 1 Hand chopping of residues 34 2 Use of weeds, cut grass, tree leaves 39 3 Rethreshing and mixing of crop residues before storage and feeding 32 4 Generous feeding of crop residues 32 4 Supplement with agro-industrial by-products (wheat bran, wheat middlings, oilseed cakes, pulse crop milling by-products such as lentil bran and hulls, etc.) 32 5 Supplement with UMMB 31 6 Smart feeding (targeted use of bought-in concentrates to target productive animals)  31 7 Fodder trees (sesbania, leucaena, tagasaste, gliricidia) 26 8 Use of improved annual grass-legume mixture (e.g. oat-vetch forage or hay) 26 8 Improved forage grasses (napier grass, rhodes grass) 23 9 Treatment of crop residues (e.g. urea treatment) 23 10  Conclusions According to the TechFit analysis, the favourable technology options relate to crop residue improvement, supplemental feeding and improved forages. Thus, in order to mitigate the feed problems of livestock production, focus needs to be placed on introducing feed technology related to crop residues which are easily obtained from wheat and barley as well as pulse straws. This may go a long way into improving the predominant poultry and fattening of sheep and cattle systems.    

Using the Techfit tool to prioritize feed technologies in Serera, Doyogena District, Southern Ethiopia

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Using the Techfit tool to prioritize feed technologies in Serera, Doyogena District, Southern Ethiopia

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