The potential of beekeeping to mitigate the exposure of rural sub-Sahara African farmers to economic stochasticity has been widely promoted by an array of development agencies. Robust outcome indicators of the success of beekeeping to improve household well-being are unfortunately lacking. This study aimed to identify the key drivers and barriers of beekeeping adoption at the household level, and quantified the associated income contribution in three agro-ecological zones in Uganda. Beekeepers were generally the most economically disadvantaged people in the study areas and tended to adopt beekeeping following contact with non-government organisations and access to training. Whilst incomes were not statistically lower than their non-beekeeping counterparts; their mean household well-being scores were significantly lower than non-beekeeping households. The inability of beekeeping to significantly improve well-being status can in part be attributed to a lack of both training in bee husbandry and protective equipment provision such as suits, gloves and smokers. These are critical tools for beekeepers as they provide the necessary confidence to manage honey bees. Rather than focussing solely on the socio-economic conditions of farmers to effectively adopt beekeeping, future research should also attempt to evaluate the effectiveness of development agencies’ provision to the beekeeping sector.

Female plot managers in Sub-Saharan Africa often realize significantly lower crop yields than their male counterparts. Even for legumes, which are often referred to as ‘women’s crops’, yields are significantly lower. This study investigated the underlying causes of this gender yield gap in groundnut production. The analysis is based on survey data from 228 farm households from two groundnut growing regions in Uganda. We used the Blinder-Oaxaca model to decompose factors that contribute to this yield gap. Results show 63% and 44% gender yield gaps for improved and local varieties, respectively, with female plot managers realizing less than their male counterparts. Improved groundnut seeds increase female plot manager’s yields but not the yields of male plot managers. Male advantage and female disadvantage combined account for more than 70% of the yield gap in both improved and local groundnut variety production and exceed pure productivity differences. Labor use differences between female and male plot managers and variety types explain the observed yield gap. Interventions and policies that increase women’s access to productive inputs including improved seed will significantly contribute to closing the yield gap, and thereby increase crop production, food security, as well as women’s incomes.

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.

To support farmers in their transition towards sustainable agriculture, sub-Saharan Africa needs a more effective extension. Thus, effective improvements based on a clear view of current and desired extension capacity are necessary. As in the past, mostly one-sided studies have been conducted. This paper proposes a more integral approach based on both characteristics and viewpoints of both farmers and extension workers. Capacity to provide effective extension and advisory services (EAS), or extension capacity, is defined and analyzed with mixed-research methods using data from 471 Ugandan dairy farmers, from three distinct production systems and 67 extension workers. Extension capacity is determined by farmers’ satisfaction, the frequency of delivering EAS to farmers, and the perceptions of both farmers and extension workers on the use of appropriate methods to deliver EAS. Results revealed moderate satisfaction across production systems, with a pronounced negative effect of long working experiences on the frequency of delivery. Positively influencing factors for delivery frequency are intrinsic motivation and the number of in-service trainings received by extension workers. On-farm demonstrations, individual farm visits, the use of contact farmers, and farmer training are perceived as the four most effective delivery methods among dairy farmers in Uganda. Given the moderate farmer satisfaction, low frequency of delivery, and slight mismatch between the perceived effective delivery methods and those being used, the study concludes that the current extension capacity remains low. However, low-hanging fruits for improvement include increasing in-service training opportunities, employing extension workers on contractual basis and motivating extension workers.

In sub-Saharan Africa, targeting on-farm extension can support farmers to increase agricultural productivity. To achieve a targeted extension system, it is crucial to be able to assign contact farmers who can act as role models for follower farmers. Given the importance of productivity increase, frontier analysis can help to define benchmarks for selecting contact farmers. However, in countries transitioning from subsistence to more commercialized production systems, this benchmarking needs to take into account the heterogeneity among farms and farming systems. This paper evaluates the potential of peer outcomes from two non-parametric frontier analysis techniques (Free Disposable Hull, FDH, and Data Envelopment Analysis, DEA) for their suitability to generate possible benchmarks in the case of Ugandan dairy farming. To account for the existing transitional heterogeneity of small subsistence, large extensive and medium intensive farming systems, meta-frontier analysis is compared with separated technology-specific analyses. Data from 471 dairy farmers were analysed using output-oriented efficiency models that used land, the number of dairy cows and labour as inputs and milk as a single output. Results confirmed that the non-convex FDH yields more realistic peers than the convex DEA. Comparing meta-frontier and technology-specific outcomes indicates that peers do not necessarily come from similar production systems, because in particular large extensive farming systems proved to be inferior to the two other systems. A detailed peer analysis revealed that the FDH and DEA frontiers are complementary in suggesting benchmarks. The non-convex frontier better captures heterogeneity, while the convex DEA has some advantage in exploring inter-technology benchmarks.