De nombreux agriculteurs africains pratiquent des formes d'agriculture potentiellement qualifiables de "?biologiques?". Pourtant, la capacité de l'agriculture biologique à répondre aux enjeux de la sécurité alimentaire en Afrique est encore mal connue, car il existe peu de références expérimentales disponibles dans cette région. L'élicitation probabiliste est une méthode permettant de rendre compte de manière précise des connaissances d'experts sur une ou plusieurs quantités d'intérêt, et de décrire les niveaux d'incertitude associés.
Les démarches participatives suscitent un intérêt grandissant en tant que pratiques de recherche en agriculture. Dans l'objectif de faciliter les échanges de pratiques entre chercheurs, cet article propose une grille d'analyse qui appréhende le processus de participation de façon globale et dynamique.
The agricultural industry is getting more data-centric and requires precise, more advanced data and technologies than before, despite being familiar with agricultural processes. The agriculture industry is being advanced by various information and advanced communication technologies, such as the Internet of Things (IoT). The rapid emergence of these advanced technologies has restructured almost all other industries, as well as advanced agriculture, which has shifted the industry from a statistical approach to a quantitative one.
This paper analyses a monitoring, evaluation and learning (MEL) system developed within an agricultural research for development institution. The system applies aspects of the Outcome Harvesting tool and focuses on learning for adaptation and improvement of innovation processes. Developmental evaluation principles are applied to discuss its application. The MEL system provides insight into the processes and interactions with next users that generate outcomes.
Agricultural innovation in low-income tropical countries contributes to a more effective and sustainable use of natural resources and reduces hunger and poverty through economic development in rural areas. Yet, despite numerous recent public and private initiatives to develop capacities for agricultural innovation, such initiatives are often not well aligned with national efforts to revive existing Agricultural Innovation Systems (AIS).
Indicator-based tools are widely used for the assessment of farm sustainability, but analysts still face methodological and conceptual issues, including data availability, the complexity of the concept of sustainability and the heterogeneity of agricultural systems. This study contributes to this debate through the illustration of a procedure for farm sustainability assessment focussed on the case study of the South Milan Agricultural Park, Italy. The application is based on a set of environmental, social and economic indicators retrieved from the literature review.
Although the benefits of genetically modified (GM) crops have been well documented, how do farmers manage the risk of new technology in the early stages of technology adoption has received less attention. We compare the total factor productivity (TFP) of cotton to other major crops (wheat, rice, and corn) in China between 1990 and 2015, showing that the TFP growth of cotton production is significantly different from all other crops. In particular, the TFP of cotton production increased rapidly in the early 1990s then declined slightly around 2000 and rose again.
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.
Past studies showing that barriers to farmers’ adaptation behaviors are focused on their socio-economic factors and resource availability. Meanwhile, psychological and social considerations are sparingly mentioned, especially for the related studies in developing countries. This study investigates the impact of psychological factors and social appraisal on farmers’ behavioral intention to adopt adaptation measures for the aforementioned reason, due to climate change and not to anthropogenic climate change.
The challenge of food security in Nigeria hinges on several factors of which poor technical efficiency is key. Using a stochastic frontier framework, we estimated the technical efficiency of agricultural households in Nigeria and tested for the significance of mean technical efficiency of food-secure and food-insecure agricultural households. We further assessed the determinants of agricultural households’ inefficiencies within the stochastic frontier model and adopted a standard probit model to assess the determinants of households’ food security status.