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.
This study aims to investigate blockchain technology for agricultural supply chains during the COVID-19 pandemic. Benefits and solutions are identified for the smooth conduction of agricultural supply chains during COVID-19 using blockchain. This study uses interviews with agricultural companies operating in Pakistan. The findings discover the seven most commonly shared benefits of applying blockchain technology, four major challenges, and promising solutions.
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 is characterized as ‘a large country with many smallholder farmers’ whose participation in modern agriculture is key to the country’s modern agriculture development. Promoting smallholder farmers’ adoption of modern agricultural production technology is one effective way to improve the capabilities of smallholder farmers. This paper aims to explore the impact of Internet use on the adoption of agricultural production technology by smallholder farmers based on a survey of 1 449 smallholders across 14 provinces in China.
This paper discusses how adapting food production systems to respond to consumer demand for healthier diets is a major opportunity to mitigate and adapt to climate change in agro-rural economies. It also addresses how existing technological solutions for climate change mitigation and adaptation need to create more balance between the production and consumption tiers of agrifood systems. Policy dialogue includes managing trade-offs between different sector and stakeholder interests and exploring synergies rather than focusing on exclusivity and competition.
El Proyecto "Desarrollo de capacidades para los sistemas de innovación agrícola: ampliación del marco común de la Plataforma de Agricultura Tropical" (en resumen, Proyecto TAP-AIS) es implementado por la Organización de las Naciones Unidas para la Alimentación y la Agricultura (FAO) en países de África (Burkina Faso, Malawi, Eritrea, Ruanda, Senegal), América Latina (Colombia), Asia y el Pacífico (Camboya, Lao PDR, Pakistán), con el objetivo estratégico de contribuir al fortalecimiento de capacidades para fomentar, reconocer y fortalecer la innovación rural en el contexto de la transformaci
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 digital transformation in agriculture introduces new challenges in terms of data, knowledge and technology adoption due to critical interoperability issues, and also challenges regarding the identification of the most suitable data sources to be exploited and the information models that must be used.
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.