Familiar mixed dairy sheep farm is the most widespread system in the Mediterranean basin, in Latin America and in developing countries (85%). There is a strong lack of technological adoption in packages of feeding and land use in small-scale farms. To increase competitiveness, it would be of great interest to deepen the knowledge of how innovation was selected, adopted, and spread. The objective of this research was to select strategic feeding and land use technologies in familiar mixed dairy sheep systems and later assess dairy sheep farms in Spain.
The Newsletter of the Tropical Agriculture Platform (TAP) provides regular updates on activities by TAP and its partners, on the projects and on upcoming events. This issue specifically refers to the period from November 2021 to January 2022.
The video (in Vietnamese language- English subtitles) tackles how to mainstream Gender and Social Inclusion (GSI in setting up a Climate-Smart Village (CSV). GSI should be integrated in the eight guide steps in establishing a CSV, such as: determining the purpose and scope of CSV; identifying the climate risk in the target area/s; locating the CSV in a small landscape; consulting the stakeholders; evaluating the CSA options; developing portfolio; scaling-up; and monitoring and evaluating uptake and outcome.
This study draws on social-psychology in an attempt to identify the various motivations for technology adoption (TA), including both economic and non-economic, and to gain insights into how and why Brazilian innovative beef farmers make decisions about whether or not to adopt particular technologies.
The Digital Innovation Strategy (DIS) of the Regional Office for Africa (RAF) of FAO has been prepared to respond to critical challenges facing inclusive and sustainable agrifood system transformation in sub-Saharan Africa. It is enshrined in the new Strategic framework 2022–2030 that aims to accelerate the "transformation to more efficient, inclusive, resilient and sustainable agri-food systems for better production, better nutrition, a better environment and a better life, leaving no one behind".
The need to urgently transition food systems to net-zero, nature-positive that can nourish all people, leaving no one behind is more critical than ever. The COVID-19 pandemic has furthered deepened complex challenges we already face from hunger and nutrition, climate and nature, and societal inequity. Innovation offers a profound opportunity to achieve these transitions and help unlock challenges across food systems.
Facilitation has proved crucial for enabling the interaction of Agricultural Innovation System (AIS) actors to address the target and to innovate. This “Guide on training of facilitators of multi-actor agricultural innovation platform” is aimed at serving facilitators when multi-actor agricultural innovation platforms (MAIPs) are organized. Since MAIPs are still an emerging concept, there are not many cases to refer to.
This article departs from the assumption that the challenge of putting the Farm to Fork Strategy (F2F) into action stems from the broader challenge of attaining cross-sectoral policy integration. Policy integration has been part of the EU's policy approach for a long time and has predominantly been achieved in the form of environmental policy integration (EPI). However, the scope of the F2F extends beyond EPI, as it includes the integration of climate-related concerns into sectoral policies, for instance.
Digitization in agriculture is rapidly advancing further on. New technologies and solutions were developed and get invented which ease farmers’ daily life, help them and their partners to gain knowledge about farming processes and environmental interrelations. This knowledge leads to better decisions and contributes to increased farm productivity, resource efficiency, and environmental health. Along with numerous advantages, some negative aspects and dependencies risk seamless workflow of agricultural production.
This article extends social science research on big data and data platforms through a focus on agriculture, which has received relatively less attention than other sectors like health. In this paper, I use a responsible innovation framework to move attention to the social and ethical dimensions of big data “upstream,” to decision-making in the very selection of agricultural data and the building of its infrastructures.