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
10 pages., Via open source journal., Farmbook is a novel information communication technology (ICT) tool for agricultural extension that is currently being field tested by the Catholic Relief Services (CRS) in Southern and East Africa. Farmbook enables extension agents to assess productivity and profitability of farming enterprises in a faster and more reliable manner, so as to increase farmer incomes and achieve food security. This study looked at the relationship between challenges faced by extension agents testing the Farmbook application and select socio-economic indicators influencing their work. Specific objectives were to identify and categorize the challenges facing extension agents in the field as they used Farmbook, assess gender differences in the use of Farmbook by extension agents, understand the relationship between socio-economic status of extension agents and the challenges faced in using Farmbook. Data were collected through document reviews, administration of a structured questionnaire and focus group meetings with field agents. Descriptive statistics and multivariate techniques were used to analyze data. The results show that personal and wider socio-economic conditions do have an impact on the proficiency of extension agents using Farmbook. The study goes on to recommend measures to improve the training and ICT proficiency of extension agents adopting Farmbook
