Smartphone technology is promising for the future development of agriculture, as it can facilitate and improve many operational procedures and can also be combined with precision agriculture technologies. Yet, existing research on smartphone adoption in agriculture is scarce. Therefore, this paper empirically explores the factors influencing smartphone adoption by German farmers. The relationship between farmers, farm characteristics and smartphone adoption was analysed using a binomial logit model.
There has been an increasing interest in science, technology and innovation policy studies in the topic of policy mixes. While earlier studies conceptualised policy mixes mainly in terms of combinations of instruments to support innovation, more recent literature extends the focus to how policy mixes can foster sustainability transitions.
Fall Armyworm (Spodoptera frugiperda), or FAW, is an insect native to tropical and subtropical regions of the Americas. In the absence of natural controls or good management, it can cause significant damage to crops. It prefers maize, although it can feed on more than 80 additional species of crops including rice, sorghum, millet, sugarcane, vegetable crops and cotton.
Labor saving innovations are essential to increase agricultural productivity, but they might also increase inequality through displacing labor. Empirical evidence on such labor displacements is limited. This study uses representative data at local and national scales to analyze labor market effects of the expansion of oil palm among smallholder farmers in Indonesia. Oil palm is labor-saving in the sense that it requires much less labor per unit of land than alternative crops.
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.
Une évaluation approfondie du système de vulgarisation agricole tunisien montre que des paquets technologiques améliorés destinés au système de production agricole mixte élevage-orge en Tunisie semi-aride permettent d’économiser jusqu’à 40 % des coûts d’alimentation du bétail, mais ne sont pas largement adoptés. Les faibles taux d’adoption sont typiques pour de nombreuses technologies approuvées dans les pays en voie de développement.
There was a need for change in agricultural development in Angola, and CDAIS has been appreciated. Results show positive outcomes in a number of areas, including the acceptance of the benefits of strengthening functional capacities across different levels. And, although it is still too early to see the full benefits of the approach, many involved said they would continue to apply it in their other activities. This story begins with views and experiences from rice growers and their partners, as an example of one of the three innovation niche partnerships in Angola.
Agriculture provides the principle source of livelihood for more than 80% of its 170 million people, and is the backbone of the Bangladesh economy. The government acknowledges this in its strategy to 2041, with investment in research and extension. CDAIS began in 2015. At the outset, however, the need to also invest in strengthening functional capacities was not recognised by those used to the ‘traditional’ technology transfer model.
Results in Ethiopia show positive outcomes from CDAIS activities, proving the benefits of integrating functional capacity strengthening across individual, partnership, organisational and national levels. Common to all these levels are
Increasing attention is being given to evaluating the impact of advisory services in terms of their effectiveness in providing farmers with knowledge and networks for innovation as well as understanding the factors that influence this effectiveness (Prager et al, 2017). The demand and uptake of advisory services is one factor and Klerkx et al (2017) comment on the variation in farmers’ demand and the influences of variables such as farm size, asset status and education as well as stability or turbulence in the regulatory environment.