Despite significant work to enhance women’s empowerment in agriculture, women remain marginalized across the globe. This includes gender gaps in agricultural extension and advisory service implementation that can lead to inequitable resource and knowledge access by farmers, specifically women. However, gender does not exist in isolation, it is place and time specific. This study investigated the impact of gender and geography on smallholder farmer access to and agency over resources/knowledge.
There are growing expectations that Information and Communication Technology (ICT) applications could help improve on-farm yields amongst smallholder farmers in developing countries, and consequently, food and nutrition security. However, few studies have quantified the actual contribution of ICT applications on farmers’ yields, and these studies predominantly focused on crop production. We assessed the potential of ICT applications to close milk yield gaps among small- and medium scale dairy cattle farmers in Africa.
Food insecurity remains a major challenge to rural households in Eastern Ethiopia. To improve food and nutrition security of vulnerable households in eastern Ethiopia, several agricultural technologies have been scaled-up by Haramaya University for more than six decades. However, the impact of these technologies on household nutritional outcomes was not systematically studied. This study examined the impact of selected agricultural technologies on household food and nutrition security. Cross-sectional data were generated from 248 randomly selected rural households.
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.
One-fifth of the innovative solutions to fight the Covid-19 pandemic have emerged from low and middle-income countries, and these responses offer promising insights for how we think about, manage, and enable innovation. As the international community now faces the historic challenge of vaccinating the world, more attention and resources must be directed to the innovators who are developing technically novel, contextually relevant, and socially inclusive alternatives to mainstream innovation management practices.
Droughts are causing severe damages to tropical countries worldwide. Although water abundant, their resilience to water shortages during dry periods is often low. As there is little knowledge about tropical drought characteristics, reliable methodologies to evaluate drought risk in data scarce tropical regions are needed.
Digitization in agriculture is rapidly advancing further on. New technologies and solutions were developed and get invented which ease farmers’ daily life, help them and their partners to gain knowledge about farming processes and environmental interrelations. This knowledge leads to better decisions and contributes to increased farm productivity, resource efficiency, and environmental health. Along with numerous advantages, some negative aspects and dependencies risk seamless workflow of agricultural production.
This article extends social science research on big data and data platforms through a focus on agriculture, which has received relatively less attention than other sectors like health. In this paper, I use a responsible innovation framework to move attention to the social and ethical dimensions of big data “upstream,” to decision-making in the very selection of agricultural data and the building of its infrastructures.
Cotton, a major crop worldwide, is harvested in mechanized production systems once at the end of the growing season. To facilitate harvest and maximize fiber quality, the plants are typically defoliated when about 60% of the cotton bolls are open. Due to non-uniform maturation, the bolls that have opened early expose their fiber to weather until harvest, commonly for weeks, degrading fiber quality. Furthermore, high capacity harvesting machines are heavy, potentially compacting the soil that in turn reduces hydraulic conductivity in the wheel tracks and reducing yield.
Accurate and operational indicators of the start of growing season (SOS) are critical for crop modeling, famine early warning, and agricultural management in the developing world. Erroneous SOS estimates–late, or early, relative to actual planting dates–can lead to inaccurate crop production and food-availability forecasts. Adapting rainfed agriculture to climate change requires improved harmonization of planting with the onset of rains, and the rising ubiquity of mobile phones in east Africa enables real-time monitoring of this important agricultural decision.