For millennia, humans have modified plant genes in order to develop crops best suited for food, fiber, feed, and energy production. Conventional plant breeding remains inherently random and slow, constrained by the availability of desirable traits in closely related plant species. In contrast, agricultural biotechnology employs the modern tools of genetic engineering to reduce uncertainty and breeding time and to transfer traits from more distantly related plants.
There are divergent views on what capacity development might mean in relation to agricultural biotechnology. The core of this debate is whether this should involve the development of human capital and research infrastructure, or whether it should encompass a wider range of activities which also include developing the capacity to use knowledge productively. This paper uses the innovation systems concept to shed light on this discussion, arguing that it is innovation capacity rather than science and technology capacity that has to be developed.
We present a model for research and development (R&D) investment in food innovations based on new plant engineering techniques (NPETs) and traditional hybridization methods. The framework combines uncertain and costly food innovation with consumers' willingness to pay (WTP) for the new food. The framework is applied with elicited WTP of French and US consumers for new improved apples. NPETs may be socially beneficial under full information and when the probability of success under NPETs is relatively high. Otherwise, the traditional hybridization is socially optimal.
Fair Trade is a labeling initiative aimed at improving the lives of the poor in developing countries by offering better terms to producers and helping them to organize. Although Fair Trade-certified products still comprise a small share of the market—for example, Fair Trade-certified coffee exports were 1.8 percent of global coffee exports in 2009—growth has been very rapid over the past decade. Whether Fair Trade can achieve its intended goals has been hotly debated in academic and policy circles.
Despite increasing interest and support for multi-stakeholder partnerships, empirical applications of participatory evaluation approaches to enhance learning from partnerships are either uncommon or undocumented. This paper draws lessons on the use of participatory self-reflective approaches that facilitate structured learning on processes and outcomes of partnerships. Such practice is important to building partnerships, because it helps partners understand how they can develop more collaborative and responsive ways of managing partnerships.
This paper explores the use of complex adaptive systems theory in development policy analysis using a case study drawn from recent events in Uganda. It documents the changes that took place in the farming system in Soroti district during an outbreak of African cassava mosaic virus disease (ACMVD) and the subsequent decline in cassava production — the main staple food in the area. Resultant adaptation impacts are analysed across cropping, biological, economic and social systems each of which operate as an interlinked sub-system.
This paper draws lessons from selected country experiences of adaptation and innovation in pursuit of food security goals.
Small-scale farmers' experimental innovations have not generally been considered for on-farm research trials as those in the traditional sector have been perceived as recipients, rather than originators, of technical knowledge and sustainable and viable practices. Yet there is abundant evidence throughout the tropics that small-scale farmers are adaptive and experimental problem solvers, and experts at devising innovative survival strategies. While literature on the topic is rich with accounts from Africa, Asia and Latin America, there is a general dearth of examples from the Caribbean.
This study examines the role of public–private partnerships in international agricultural research. It is intended to provide policymakers, researchers, and business decisionmakers with an understanding of how such partnerships operate, how they promote the exchange of knowledge and technology, and how they contribute to poverty reduction.
The article examines the effect of membership in farmer groups (MFG) on adoption lag of agricultural technologies and farm performance in Burundi, the Democratic Republic of Congo and Rwanda. We use duration and stochastic production frontier models on farm household data. We find that the longer the duration of MFG, the shorter the adoption lag and much more so if combined with extension service delivery. Farmer groups function as an important mechanism for improving farm productivity through reduced technical inefficiency in input use.