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
21 pages, Despite decades of investment in agricultural extension, technology adoption among farmers and agricultural productivity growth in Sub-Saharan Africa remain slow. Among other shortcomings, extension systems often make recommendations that do not account for price risk or spatial heterogeneity in farmers' growing conditions. However, little is known about the effectiveness of extension approaches for nutrient management that consider these issues. We analyze the impact of farmers' access to site-specific nutrient management recommendations and to information on expected returns, provided through a digital decision support tool, for maize production. We implement a randomized controlled trial among smallholders in the maize belt of northern Nigeria. We use three waves of annual panel data to estimate immediate and longer term effects of two different extension treatments: site-specific recommendations with and without complementary information about variability in output prices and expected returns. We find that site-specific nutrient management recommendations improve fertilizer management practices and maize yields but do not necessarily increase fertilizer use. In addition, we find that recommendations that are accompanied by additional information about variability in expected returns induce larger fertilizer investments that persist beyond the first year. However, the magnitudes of these effects are small: we find only incremental increases in investments and net revenues over two treatment years.