The challenges faced by agricultural systems call for an advance in risk management (RM) assessments. This research identifies and discusses potential improvements to RM across 11 European Union (EU) farming systems (FS). The paper proposes a comprehensive, participatory approach that accounts for multi-stakeholder perspectives relying on 11 focus groups for brainstorming and gathering suggestions to improve RM.
Agriculture 4.0 is comprised of different already operational or developing technologies such as robotics, nanotechnology, synthetic protein, cellular agriculture, gene editing technology, artificial intelligence, blockchain, and machine learning, which may have pervasive effects on future agriculture and food systems and major transformative potential. These technologies underpin concepts such as vertical farming and food systems, digital agriculture, bioeconomy, circular agriculture, and aquaponics.
This paper is a case study of a network that combined participatory approaches to propose best suited knowledge management (KM) interventions for its member countries. A five-step exercise used existing elements of the alliance’s strategy, a KM survey and a face-to-face participatory validation of the analysis, to identify gaps in current KM approaches and to collectively point to immediate opportunities for improvement. The KM survey, also referred to as a scan, provided a neutral space for reflection.
This article examines differences in the research approaches of farmers and scientists and analyzes how these differences are related to the conditions under which both groups engage in experimental work. Theoretical considerations as well as practical experiences are presented to emphasize the great potential of farmer–researcher collaboration for rural innovation.
In rural areas of developing countries, more than 70% of the population still depends on agriculture. However, economic crises, unscientific land allocation and climate change issues have hindered attempted gains in agricultural productivity and related rural development outcomes. Technology-driven breakthrough has usually pushed agriculture to the brink of another development that can affect not only plant diversity and yield, but also climatological and socio-economic outcomes.
AgriFoodTech start-ups are coming to be seen as relevant players in the debate around and reality of the transformation of food systems, especially in view of emerging or already-established novel technologies (such as Artificial Intelligence, Sensors, Precision Fermentation, Robotics, Nanotechnologies, Genomics) that constitute Agriculture 4.0 and Food 4.0. However, so far, there have only been limited studies of this phenomena, which are scattered across disciplines, with no comprehensive overview of the state of the art and outlook for future research.
El objetivo de este estudio fue identificar la estructura de la gobernanza para ampliar y consolidar el uso de prácticas de Adaptación basada en Ecosistemas (AbE) en agricultura. Se analizaron tres paisajes productivos distribuidos en tres países (Honduras, Guatemala y Costa Rica), caracterizados por la dedicación a la caficultura de pequeña escala. Para cada uno de estos paisajes se identificaron los actores que intercambian información entre la escala nacional y el nivel de los productores.
Una estrategia para apoyar a las comunidades de pequeños agricultores a adaptarse al cambio climático es el uso de prácticas de Adaptación basada en Ecosistemas (AbE), las cuales integran la conservación, restauración y manejo sostenible de ecosistemas y biodiversidad. Sin embargo, existe poca información de cómo los productores utilizan estas prácticas.
he article describes the institutionalization of farmer participatory research and plant breeding that has occurred in Honduras over the past 22 years and demonstrates how this approach can offer a positive response to climate change and sustainable agricultural development. In Honduras, participatory plant breeding (PPB) involves the collaboration of farmer researchers organized in local agricultural research committees (CIALs), plant breeders, and non-governmental organizations (NGOs).
The objectives of this study were to (1) develop a participatory method to delineate distinct agricultural landscapes and map the adaptive capacity of smallholder farmers in data-limited contexts, (2) apply the method systematically to understand the adaptive capacity of smallholder farmers in three Central American countries (Costa Rica, Guatemala, and Honduras), and (3) use the information generated to understand the variation in adaptive capacity of smallholder farmers across farming systems and regions