6 pages, Despite the huge potential for milk production, interventions to improve productivity in sub-Saharan Africa (SSA) are barely based on specified farm classifications. This study aimed to develop robust and context-specific farm typologies to guide content of extension farm advice/services in Uganda. From a sample of 482 dairy farmers, we collected data on farmer socio-demographics, farm management practices, ownership of farm tools and facilities, willingness to pay for extension services, milk production, and marketing. Farm typologies were obtained based on principal component and cluster analyses. Thereby, of the three dairy production systems that emerged, small-scale, largely subsistence yet extensive and low productive farms were more prominent (82.6%). Farms that were classified as large-scale, less commercialized yet extensive with modest productive systems were more than the medium-scale commercial farms with intensive and highly productive systems. However, the later were considered to potentially transform dairy farming in Uganda. It was also predicted that the validity of our farm classification may persist until half of the farms have moved between clusters. The study gives new insights on dairy production systems in Uganda, which can be used to organize more targeted research on farmers’ extension needs for facilitating delivery of relevant and effective extension services and designing appropriate extension policies
23 pages., Authors used a baseline survey, an intervention, and an end line survey to assess farmers' knowledge of farming practices, knowledge level, and relationship between information source and knowledge gain. Interventions were provided by radio broadcasts and audio CDs. Findings suggested that '...audio media remains a vital source of information for resource-poor farmers and can greatly enhance their agricultural knowledge when audio media is used as an intervention."
16 pages., Online via Directory of Open Access Journals (DOAJ.org)., Interviews with 203 smallholder farmers in Uganda indicated that households with higher level of information access through cell phone use and weak-tie information sources were more likely to use inputs.