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.
CABI and the Cereal Growers Association (CGA) have been sharing information with farmers in Kenya on how to effectively and safely manage the continuing threat of the invasive fall armyworm (Spodoptera frugiperda). This was achieved thanks to a development communication campaign that combined video sharing through a network of lead farmers and social media.
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.
The impact of global warming on crop growth periods and yields has been evaluated by using crop models, which need to provide various kinds of input datasets and estimate numerous parameters before simulation. Direct studies on the changes of climatic factors on the observed crop growth and yield could provide a more simple and intuitive way for assessing the impact of climate change on crop production.
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.
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.
Soil texture is a key soil property influencing many agronomic practices including fertilization and liming. Therefore, an accurate estimation of soil texture is essential for adopting sustainable soil management practices. In this study, we used different machine learning algorithms trained on vis–NIR spectra from existing soil spectral libraries (ICRAF and LUCAS) to predict soil textural fractions (sand–silt–clay %). In addition, we predicted the soil textural groups (G1: Fine, G2: Medium, and G3: Coarse) using routine chemical characteristics as auxiliary.
Recent Society 5.0 efforts by the Government of Japan are aimed at establishing a sustainable human-centered society by combining new technologies such as sensor networks, edge computing, Internet of Things (IoT) ecosystems, artificial intelligence (AI), big data, and robotics. Many research works have been carried out with an increasing emphasis on the fundamentals of wireless sensor networks (WSN) for different applications; namely precision agriculture, environment, medical care, security, and surveillance.