This study was carried out in Mashuru district, Kajiado County in the Southern Maasai rangelands ofKenya to assess the status of livestock technologies and services. Data was collected using a survey of 380 households, participatory stakeholder workshops, five focus groups with pastoralists, and key informant interviews. Analysis was done using frequency counts, percentages and chi square test. The findings of this study revealed that access to livestock technologies and services was hampered by institutional (77%), technological (12%), environmental (9%) and economic (2%) factors. Inadequate government staff, long distances to service providers and weak institutional linkages were the most common problems encountered by 27, 20 and 17% of pastoralists respectively. Technologies perceived to be important included: Availability of water and water harvesting technologies (52%); pastures (28%); vaccines and drugs (8%); dual purpose breeding stock for milk and meat production adapted to dry climatic conditions (4%); market infrastructure and information (4%); management skills (3%), and small equipment (1%). In view of problems encountered in accessing livestock services, Maasai pastoralists preferred the establishment of one-stop-shop centres stocked with priority inputs and technologies (P<0.05). The willingness of pastoralists (65%) to pay for this service should attract public-private partnerships to support livestock productivity in rangelands.
This study was carried out in Isiolo and Kajiado counties. Livestock production and marketing have been hampered by the unavailability and accessibility to livestock technologies, and information sharing. The overall objective of this study was to assess a multi-institutional model for enhancing the uptake of livestock technologies in Isiolo and Kajiado counties. The key parameters assessed were priority livestock constraints; technology needs; stakeholder partnerships; and technology delivery platform. The data were collected from 451 households belonging to Kenya Climate Smart Agricultural Production KCSAP groups red meat value chain of pastoralists, Common Interest Groups and Most Vulnerable Groups (CIGs and VMGs) using semi-structured questionnaires, Focus group discussions with groups, key informant interviews with public and private sector actors. The results showed that in both Kajiado and Isiolo Counties, priority livestock production constraints in Kajiado County in Dalalekutuk ward were diseases, lack of feeds, limited access to water and inadequate veterinary services, and in Isiolo County were lack of feeds, limited access to water and diseases. Priority livestock diseases in Kajiado, County, Dalalekutuk ward were, Foot and Mouth Disease (FMD), anthrax; contagious caprine pleuropneumonia (CCPP) and cerebral coenurosis and enterotoxemia and cerebral coenurosis for the sheep. In Isiolo County, priority cattle diseases were FMD and trypanosomiasis,’ in the goats CCPP and cerebral coenurosis while in the sheep enterotoxemia and cerebral coenurosis. The reasons for persistent livestock production constraints were ranked and ranked as single organization interventions not sufficient to solve problems and lack of prioritization by stakeholders (water, pasture, diseases). The major livestock technology needs were: pasture, water, access to veterinary vaccines, capacity building of groups; training of para vets to support in the delivery of veterinary services; information sharing platform and market infrastructure. The multi-institutional technology exhibitions consisting of public and private sector actors were held in Kajiado and Isiolo Counties linking KCSAP pastoralist groups to technology and service providers. To enhance sharing of information, a mobile application(MITDP) was established linking CIGs and VMGs leaders with KALRO, KEVEVAPI, County Governments of Kajiado and Isiolo departments of livestock production and veterinary services; suppliers of drugs, vaccines and equipment; water technology suppliers; Agro-vets and Non-governmental organizations along the red meat value chain.
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