The Colombian Ministry of Agriculture Colombia, an international research center and a national farmers’ organization developed a data-driven agricultural program that: (i) compiles information from multiple sources; (ii) interprets that data; and (iii) presents the knowledge to farmers through the local advisory services. Data was collected from multiple sources, including small-scale farmers. Machine learning algorithms combined with expert opinion defined how variation in weather, soils and management practices interact and affect maize yield of small-scale farmers.

The framework is designed to assess resilience to specific challenges (specified resilience) as well as a farming system's capacity to deal with the unknown, uncertainty and surprise (general resilience). The framework provides a heuristic to analyze system properties, challenges (shocks, long-term stresses), indicators to measure the performance of system functions, resilience capacities and resilience-enhancing attributes. Capacities and attributes refer to adaptive cycle processes of agricultural practices, farm demographics, governance and risk management.

The interactions between bottom-up initiatives and top-down structures in the implementation of regional development policies and projects are complex in theoretical and practical terms. Using concepts such as transformative social innovation, adaptive governance, and bridging institutions, we developed an analytical framework to enhance understanding of the processes by which local top-down and bottom-up forces enhance sustainable rural development by co-developing bottom-linked governance.

This paper presents a case study of a machinery manufacturer in Bangladesh producing 2WT. The study aims were to identify ways to increase machinery manufacturers’ capacity while improving manufacturing operations and workplace safety through equipment selection, workshop layout, and usability. As a locally-owned, small-scale agricultural machinery manufacturer in Bangladesh, Janata Engineering (JE) is representative of many small-scale and emerging machinery manufacturing enterprises in South Asia

Recently, a new approach to extension and climate information services, namely Participatory Integrated Climate Services for Agriculture (PICSA) has been developed. PICSA makes use of historical climate records, participatory decision-making tools and forecasts to help farmers identify and better plan livelihood options that are suited to local climate features and farmers’ own circumstances.

This study refines the participatory management (PM) in agricultural extension education (AEE) by adopting a multidimensional approach. PM is a process where extension agent (EA) tries to provide a good situation for AEE and share significant degree of power with their farmers. The data were obtained from samples of 290 Iranian farmers in Torbat Heydarieh, Iran. Methodology was descriptive and correlation. There was directly and a statically significant relation between all of components of PM regarding in effective AEE. The PM is a panacea for improving the AEE.

Climate forecasts have shown potential for improving resilience of African agriculture to climate shocks, but uncertainty remains about how farmers would use such information in crop management decisions and whether doing so would benefit them. This article presents results from participatory research with farmers from two agro-ecological zones of Senegal, West Africa. Based on simulation exercises, the introduction of seasonal and dekadal forecasts induced changes in farmers’ practices in almost 75% of the cases.

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).

Agricultural innovation systems has become a popular approach to understand and facilitate agricultural in-novation. However, there is often no explicit reflection on the role of agricultural innovation systems in food systems transformation and how they relate to transformative concepts and visions (e.g. agroecology, digital agriculture, Agriculture 4.0, AgTech and FoodTech, vertical agriculture, protein transitions). To support such reflection we elaborate on the importance of a mission-oriented perspective on agricultural innovation systems.

Evaluation provides effective feedback for development plans and programs. In this respect, it is of utmost importance to ensure that the outputs of agricultural extension and education projects are compatible with the ones expected. Therefore, the main purpose of this study was to evaluate agricultural extension model sites approach from actors’ perspectives and to analyze their gaps via the context, input, process, and product (CIPP) evaluation model.