Information and Communication Technology (ICT) development strategy in Chinese rural areas is an indispensable part of national development strategies. This paper reviews the ICT framework in agriculture and rural areas launched by the Department of Agriculture in China. It compares the rural ICT policies and strategies between China and the European Union (EU). The ICT development strategy framework is analyzed based on the situation in Chinese rural area and the experiences of the EU. Some lessons and suggestions are provided
Controlled Environment Agriculture (CEA) is the production of plants, fish, insects, or animals inside structures such as greenhouses, vertical farms, and growth chambers, in which environmental parameters such as humidity, light, temperature and CO2 can be controlled to create optimal growing conditions.
The research programme URBAL (Urban-driven Innovations for Sustainable Food Systems) (2018–2020), funded by Agropolis Fondation (France), Fondation Daniel & Nina Carasso (France/Spain), and Fundazione Cariplo (Italy), and coordinated by CIRAD (France) and the Laurier Center for Sustainable Food Systems at Wilfrid Laurier University (Canada), seeks to build and test a participatory methodology to identify and map the impact pathways of urban-driven innovations on all the dimensions of food systems sustainability.
The study assesses the relationship of prices of onion at the farm level as well as at wholesale, retail and export level with a view to understand price mechanism involved in the marketing of onion. It and also addresses problems faced by stakeholders in the marketing of their onion
This paper examines the role of postsecondary agricultural education and training (AET) in sub-Saharan Africa in the context of the region’s agricultural innovation systems. Specifically, the paper looks at how AET in sub-Saharan Africa can contribute to agricultural development by strengthening innovative capacity, or the ability of individuals and organisations to introduce new products and processes that are socially or economically relevant, particularly with respect to smallholder farmers who represent the largest group of agricultural producers in the region.
Social media (SM) such as Twitter and Facebook are new communication tools for rural communities, and SM has enabled the creation of rural social networks. Increased use by farmers of 'mobile digital devices' and better rural access to broadband services have enhanced so that SM is being used to support farming decisions. However, in depth studies on how SM is used for knowledge sharing amongst farmers and the role of rural professionals (e.g. advisors) in this space is an emergent field with limited literature.
In this paper the authors present the development of an analytical framework to study agricultural innovation systems. They divide the agricultural sector into four levels and expand the innovation system approach to study innovation processes.
The agrarian system Analysis and Diagnosis is used for this study, the goal of which was to provide a corpus of basic knowledge and elements of reflection necessary for the understanding the Niayes farming systems dynamics in Senegal, West Africa. Such holistic work has never been done before for this small region that provides the majority of vegetables in the area, thanks to its microclimate and access to fresh water in an arid country.
Innovation is considered as one of the key drivers for a competitive and sustainable agriculture and the European Commission highlights the importance of tailoring innovation support to farmers’ needs, especially in European Rural Development Policy (reg EU 1305/2013). The scientific literature offers a wide panorama of tools and methods for the analysis of innovation in agriculture but the lack of data on the state of innovation in the farms hampers such studies. A possibility to partially overcome this limit is the use of data collected by the Farm Accountancy Data Network (FADN).
This data article contains annotation data characterizing Multi Criteria Assessment (MCA) Methods proposed in the agri-food sector by researchers from INRA, Europe's largest agricultural research institute (INRA, https://institut.inra.fr/en). MCA can be used to assess and compare agricultural and food systems, and support multi-actor decision making and design of innovative systems for crop production, animal production and processing of agricultural products.