This report brings a review about the CTA activities in 2018 based on three intervention areas. One is promoting youth entrepreneurship and creating employment for young people, particularly through the use of information and communication technologies (ICTs). The second, digitalisation, cuts across all intervention areas and focuses on the application of digital technologies to transform business models and provide new revenue throughout agricultural value chains.
This brief draws on three cases to show how the private sector contributes to the conceptualisation, design, delivery and evaluation of climate-smart agricultural interventions and can help bring them to scale. Engaging the private sector in CSA interventions enhances the applicability – and thus the sustainability of interventions, increases uptake and delivers a triple win for donors, beneficiaries and the private sector.
In Yatta sub-County, a semi-arid land, there is scanty information on the causes and effects of climate change, as well as agricultural adaptation strategies. This scanty information assessment of climate related risks, and decision making about appropriate adaptation measures. A survey was conducted in two wards of Yatta, Kenya, to identify opportunities for building farmer capacity in dealing with climate variability.
In this study, it is applies a participatory scenario modelling framework to assess potential societal responses to the impacts of climate change by the mid-21st century, and model consequent land use and land cover change scenarios under different livelihood futures as guided by communities’ members in the areas under investigation. The authors focused their analysis on two montane sites of the Eastern Afromontane Biodiversity Hotspot , the Taita Hills, Kenya, and a montane area north-west of Jimma, Ethiopia
Weather risk is a serious issue in the African small farm sector that will further increase due to climate change. Farmers typically react by using low amounts of agricultural inputs. Low input use can help to minimize financial loss in bad years, but is also associated with low average yield and income. Increasing small farm productivity and income is an important prerequisite for rural poverty reduction and food security. Crop insurance could incentivize farmers to increase their input use, but indemnity-based crop insurance programs are plagued by market failures.
This publication brings some sucessful experiencies in Digital Agriculture in African countries. In this issue of Spore, it is explored how digitalisation is providing women with better access to finance, information and markets, as well as opening up new opportunities for young entrepreneurs to develop apps and other digital services in agribusiness
This brief summarizes the main activities carried out by the 15 international agricultural research centers of the global research partnership for a food secure future CGIAR and their affiliated institutions develop innovative solutions for sustainable agriculture
This paper presents a case study of the Honey Bee Network’s decentralized model for collecting, verifying and disseminating grassroots innovations and provides a roadmap for its replication in Africa. The Honey Bee Network brings together governmental and non‐governmental institutions, members of academia, scholars and a large number of volunteers.
This study investigated how value chain governance influences farmer participation in vegetable markets and food security in Kenya. This study employed exploratory case study design to provide chain architecture, isolate primary actors, their roles, relations, constraints and opportunities for upgrading by smallholders.
The objective of the study was to identify a viable trade-off between low data requirements and useful household-specific prioritizations of advisory messages. At three sites in Ethiopia, Kenya, and Tanzania independently, we collected experimental preference rankings from smallholder farmers for receiving information about different agricultural and livelihood practices. At each site, was identified socio-economic household variables that improved model-based predictions of individual farmers’ information preferences.