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.
The problems of agricultural development for small and medium enterprises (SMEs) are considered. The features of modeling business processes in agriculture are analyzed. A financial decision support system is proposed to increase sustainability and reduce risks in the development of agricultural SMEs. The software modules are based on TEO-INVEST.
Rwanda has experienced exceptional economic growth since 2000 despite more than 60% of the predominately-agrarian population living on less than $1.25 a day. Approximately 76% of the country’s working population are engaged in agricultural production, which makes up about one-third of the national economy. Agriculture is also an important source of foreign exchange, making up about 63% of the value of Rwanda’s exports.
This work examined the determinants of the adoption of improved Irish potato technologies by farmers in three divisions of the Western Region of Cameroon. Data were collected from 170 farmers from 14 villages in our study area using a mixed-method approach—structured questionnaires, focus group discussion, key informant interviews, and participatory observations with individual farmers and farmers belonging to cooperative and common initiative groups. The study employed descriptive statistics and regression analysis to assess the adoption status of farmers and its determinants.
Inclusive business models dominate current development policy and practices aimed at addressing food and nutrition insecurity among smallholder farmers. Through inclusive agribusiness, smallholder food security is presumed to come from increased farm productivity (food availability) and income (food access). Based on recent research, the focus of impact assessments of inclusive business models has been limited to instrumental aspects, such as the number of farmers supported, the training provided, and immediate farm outcomes, namely revenue.
Mobile phones fit well into the lives of pastoralists in low-income countries. The technology is firmly integrated into most pastoralist communities, affecting and transforming several core activities. Most studies concerned with this relationship, however, have narrow regional and thematic foci. The complementarity or discrepancy between relevant research is unknown, and a critical assessment of the current state of research is lacking.
This paper reviews the empirical literature on the determinants of farmer adoption of sustainable intensification technologies in maize agri-food systems of the Global South. The attributes of the technology and the dissemination institutions interact with farm/farmer-specific variables, leading to heterogeneous impacts, making the prediction of technology adoption challenging.