Les technologies agricoles jouent un rôle central dans la production alimentaire mondiale. Une étude récemment publiée par le Conseil des technologies de l’information et des communications (CTIC) s’est penchée sur la question. On y fait valoir que les technologies sont nécessaires à l’amélioration de l’efficacité de la production agricole et de la durabilité des denrées alimentaires.
Bees provide a critical link in the maintenance of ecosystems, pollination. They play a major role in maintaining biodiversity, ensuring the survival of many plants, enhancing forest regeneration, providing sustainability and adaptation to climate change and improving the quality and quantity of agricultural production systems. In fact, close to 75 percent of the world’s crops that produce fruits and seeds for human consumption depend, at least in part, on pollinators for sustained production, yield and quality.
Agricultural innovation has played a critical role in the economic transformation of developing East Asian countries over the past half century. The Green Revolution—in the form of modern seed varieties, chemical fertilizers, pesticides, and modern machinery—has contributed to increased crop yields and farm incomes, and decreased poverty across the region. Although policy makers’ traditional focus on expanding and intensifying agricultural production has brought many benefits, the focus on productivity has come at a rising cost.
Written employment contracts may improve the conditions of agricultural workers in developing countries, but farmers as employers often prefer less formal oral arrangements. We evaluate whether farmers’ preferences, which are deeply rooted in traditional norms, can be influenced through a group awareness campaign. In a randomised experiment in Côte d’Ivoire, we show that such a campaign increases farmers’ preferences for written contracts and for contract features involving social benefits for workers.
To determine whether a farmer’s accessibility predicts the delivery of extension services, this study used banana Xanthomonas wilt (BXW) disease-management advisory as a typical case with which to collect extension-delivery information from 690 farmers, distinguished by their respective accessibility. Cost–distance analysis was applied to define each farmer’s accessibility. The results revealed that a farmer’s accessibility does not predict extension delivery to that farmer in all forms of the examined extension parameters.
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.
The national assessment of the agricultural innovation system (AIS) in Malawi was conducted using a framework of four types of analyses: functional, structural, capacity and enabling environment analysis. The approach included five case studies that addressed three methods including the use of indigenous methods for fall armyworm (FAW) control in Farmer Field Schools (FFS), livestock transfer programs, and a horticulture marketing innovation platform in Mzimba, Ntchisi, Balaka, and Thyolo districts.
This report introduces the reader to the concept of agricultural innovation systems (AIS) and the TAP-AIS project being implemented by FAO in nine countries, including Lao People's Democratic Republic (Lao PDR). The results of the AIS assessment for Lao PDR are presented, highlighting key barriers and opportunities for agricultural innovation in the country.
Inefficiencies and imprecise input control in agriculture have caused devastating consequences to ecosystems. Urban controlled environment agriculture (CEA) is a proposed approach to mitigate the impacts of cultivation, but precise control of inputs (i.e., nutrient, water, etc.) is limited by the ability to monitor dynamic conditions. Current mechanistic and physiological plant growth models (MPMs) have not yet been unified and have uncovered knowledge gaps of the complex interplay among control variables.