Adoptions of improved technologies and production practices are important drivers of agricultural development in low-income countries like Nepal. Adopting a broad class of such technologies and practices is often critical for meeting the multifaceted goals of efficiency, profitability, environmental sustainability, and climate resilience.
Smallholder farmers in East Africa need information and knowledge on appropriate climate-smart agriculture (CSA) practices, technologies, and institutional innovations in order to effectively adapt to changing climatic conditions and cope with climate variability. This paper assesses farmer adoption of climate-smart agricultural practices and innovation after being exposed to Farms of the Future Approach (FotF). First; we explore and assess the various CSA technologies and practices; including institutional innovations farmers are adopting.
In the light of ongoing debates about the suitability of proprietary seed technologies for smallholder farmers, this paper analyzes the adoption and impact of hybrid wheat in India. Based on survey data, we show that farmers can benefit significantly from the proprietary technology. Neither farm size nor the subsistence level influences the adoption decision, but access to information and credit does. Moreover, willingness-to-pay analysis reveals that adoption levels would be higher if seed prices were reduced.
Precision agriculture (PA) is growing considerably in Brazil. However, there is a lack of information regarding to PA adoption and use in the country. This study sought to: (i) investigate the perception of growers and service dealership about PA technologies; (ii) identify constraints to PA adoption; (iii) obtain information that might be useful to motivate producers and agronomists to use PA technologies in the crop production systems.
The honey production in Mexico is a relevant activity of the livestock subsector, due to the generation of jobs and income in the agricultural sector, as well as its contribution of foreign exchange. In the period from 2005 to 2015 the average annual production was 58 thousand tons, which fluctuated between 55 and 62 thousand tons. This has placed Mexico as the eighth largest producer in the world and the third exporting country.
The process of adopting innovation, especially with regard to precision farming (PF), is inherently complex and social, and influenced by producers, change agents, social norms and organizational pressure. An empirical analysis was conducted among Italian farmers to measure the drivers and clarify “bottlenecks” in the adoption of agricultural innovation. The purpose of this study was to analyze the socio-structural and complexity factors that affect the probability to adopt innovations and the determinants that drive an individual’s decisions.
Social learning processes can be the basis of a method of agricultural innovation that involves expert and empirical knowledge. In this sense, the objective of this study was to determine the effectiveness and sustainability of an innovation process, understood as social learning, in a group of small farmers in the southern highlands of Peru. Innovative proposals and its permanence three years after the process finished were evaluated. It was observed that innovation processes generated are maintained over time; however, new innovations are not subsequently generated.
Social learning processes can be the basis of a method of agricultural innovation that involves expert and empirical knowledge. In this sense, the objective of this study was to determine the effectiveness and sustainability of an innovation process, understood as social learning, in a group of small farmers in the southern highlands of Peru. Innovative proposals and its permanence three years after the process finished were evaluated. It was observed that innovation processes generated are maintained over time; however, new innovations are not subsequently generated
The process of knowledge brokering in the agricultural sector, where it is generally called agricultural extension, has been studied since the 1950s. While agricultural extension initially employed research push models, it gradually moved towards research pull and collaborative research models. The current agricultural innovation systems perspective goes beyond seeing research as the main input to change and innovation, and recognises that innovation emerges from the complex interactions among multiple actors and is about fostering combined technical, social and institutional change.
There is sufficient evidence, drawn from surveys of innovation in the public sector and cognitive testing interviews with public sector managers, to develop a framework for measuring public sector innovation. Although many questions that are covered in the Oslo Manual guidelines for measuring innovation in the private sector can be applied with some modifications to the public sector, public sector innovation surveys need to meet policy needs that require collecting additional types of data.