Since 1979, IFAD has invested US$455.09 million in 20 programmes and projects in Kenya (at a total cost of US$980.31 million), in support of the Government’s efforts to reduce rural poverty. In Kenya, IFAD loans provide support to smallholders and value chain actors (such as agrodealers, private extension services, small traders and processors) in the dairy sector, aquaculture, livestock and cereal value chains. In addition, they strengthen the resilience of the natural resource base and improve access to rural financial services.
Geographic information system (GIS) data is often used to map socio-economic data with a spatial component. This data, which is obtained from multiple open-source databases, complements official statistics and generates additional spatial inputs to statistical and econometric analyses. IFAD uses impact assessments using data from face-to-face interviews in order to determine the impact of their projects on strategic goal and objectives. However, the COVID-19 pandemic meant these interviews could no longer take place.
Le Programme d’appui au développement des filières agricoles (PADFA) a pour objectif d’améliorer les activités après-récolte (conditionnement, stockage, transformation et commercialisation) dans les filières du riz, des légumes et de la mangue en Côte d'Ivoire. Cette brochure réunit les témoignages de petits producteurs ayant participé au programme et dont les cultyures étaient affectés par les effets des changements climatiques et les insectes.
La notion de service écosystémique est devenue incontournable dans les discours institutionnels et académiques en dépit des controverses et des critiques. Initialement portée par les acteurs de la conservation de la biodiversité, elle connaît depuis plusieurs années un déploiement dans les milieux agricoles. Si l’idée selon laquelle les fonctionnalités des écosystèmes sont déterminantes dans la production agricole n’est pas nouvelle, cette notion permet de mettre en évidence les nouveaux enjeux liés aux changements climatiques et aux besoins alimentaires croissants.
Accurate and operational indicators of the start of growing season (SOS) are critical for crop modeling, famine early warning, and agricultural management in the developing world. Erroneous SOS estimates–late, or early, relative to actual planting dates–can lead to inaccurate crop production and food-availability forecasts. Adapting rainfed agriculture to climate change requires improved harmonization of planting with the onset of rains, and the rising ubiquity of mobile phones in east Africa enables real-time monitoring of this important agricultural decision.
Climate smart agriculture (CSA) technologies are innovations meant to reduce the risks in agricultural production among smallholder farmers. Among the factors that influence farmer adoption of agricultural technologies are farmers' risk attitudes and household livelihood diversification. This study, focused on determining how farmers' risk attitudes and household livelihood diversification influenced the adoption of CSA technologies in the Nyando basin. The study utilized primary data from 122 households from two administrative regions of Kisumu and Kericho counties in Kenya.
The potential beneficial and harmful social impacts generated by the introduction of novel technologies, in general, and those concerning nutrient recovery and the improvement of nutrient efficiency in agriculture, in particular, have received little attention, as shown in the literature. This study investigated the current social impacts of agricultural practices in Belgium, Germany and Spain, and the potential social impacts of novel technologies introduced in agriculture to reduce nutrient losses.
China will be confronted with many challenges in the years to come, including achieving carbon neutrality, ensuring environmental sustainability, protecting vulnerable people, and ensuring a smooth transition from smallholder to modern agriculture. This policy note discusses how China could further advance its food and agricultural development model, making it greener, more sustainable, and more inclusive.
The spatial and temporal variability of soil properties (fluid composition, structure, and water content) and hydrogeological properties employed for sustainable precision agriculture can be obtained from geoelectrical resistivity methods. For sustainable precision agricultural practices, site-specific information is paramount, especially during the planting season.
The determination of bunch features that are relevant for bunch weight estimation is an important step in automatic vineyard yield estimation using image analysis. The conversion of 2D image features into mass can be highly dependent on grapevine cultivar, as the bunch morphology varies greatly. This paper aims to explore the relationships between bunch weight and bunch features obtained from image analysis considering a multicultivar approach.