The objective of this study was to integrate sustainability in the innovation process by applying a systems view of foresight in an early stage of innovation development. For this end, we set up a back-casting process based on a triple-helix approach that was adapted to the agricultural setting by including science, policy and agricultural practice. Was deliberately selected four conceptual sustainability-oriented innovations that were driven by the motivation of actors in agricultural science and practice.
in the context of the EU-funded JOLISAA (JOint Learning in Innovation Systems in African Agriculture) project, four local innovation processes involving smallholders in Benin were selected for in-depth assessment: innovation in hwedo agrofishing, integrated soil fertility management (ISFM), rice parboiling and soy value chains. Stakeholders directly involved in the innovation process were interviewed.
This paper analyzes the status of Pakistan’s agriculture in the world and quantifies the potential of improving productivity and quality of value chain at its different nodes. A great potential of expansion in the value chain of large number of agricultural commodities produced in Pakistan are observed. Just bringing the average crop yield levels at par to the world average yield can generate over US$11 billion additional revenues to the producers. Despite lower yield, majority of commodities have lower prices compared to the world average prices at the farmgate.
This paper aims at analysing the competitive performance of a very tradeable global commodity and the main export crop of Cameroon from 1961 to 2013 through the application of a step-wise analytical framework accommodating aspects of agri-value chain analysis. This conventional analysis was expanded to include value chain comparisons between various valueadding processes in the Cameroonian cocoa value chain as well as consensus vs.
Based on three rounds of panel data (2007, 2009, and 2012) on indigenous households, this study assessed the impacts of Integrated Aquaculture-agriculture value chain participation on the welfare of marginalized poor indigenous rural households in Bangladesh. We also examined the distributional impacts of IAA value chain
This paper examined cowpea value chain mapping and marketing efficiency among cowpea farmers in Ga-Molepo of Capricorn district and Bela-Bela of Waterberg district. Primary data was collected through face to face interviews from 80 smallholder cowpea farmers using structured questionnaire. Value chain map, descriptive statistics and binary logistic regression model were used to analyse the data
This study analyzed the determinants of ICT usage in agricultural value chains among rural youth in Busia County, Kenya. A total of 213 young farmers were randomly selected and interviewed using semi-structured questionnaires. Descriptive statistics and Poisson regression model were applied in data analysis. Findings showed youth participation using ICTs was concentrated at the marketing level of the agricultural chain activities.
The objectives of this study were 1) to describe farming systems in Zoghmar community at Sidi Bouzid site; 2) analyze the existing lamb production chain and 3) develop potential technical and organizational pathways to better respond to farmers and consumers needs. A total of 120 surveys was conducted in Sidi Bouzid region including sheep owners, butchers and consumers. The project initiated the formation of a farmers association at Zoghmar community to establish a transparent lamb production chain.
Participatory Impact Pathways Analysis (PIPA) is a practical approach to planning, monitoring and evaluation, developed for use with complex research-for-development projects. PIPA begins with a participatory workshop where stakeholders make explicit their assumptions about how their project will make an impact, and produce an ‘Outcomes logic model’ and an ‘Impact logic model’. These two logic models provide an ex-ante framework of predictions of impact that can also be used in priority setting and ex-post impact assessment.
Agricultural innovation is an essential component in achieving the SDG and accelerating the transition to more sustainable and resilient farming systems across the world. Innovations generally emerge from collective intelligence and action, which requires effective agricultural innovation systems (AIS). An AIS perspective has been widely adopted, but the analysis of AIS, especially at country level, remains a challenge. The need for and potential of a diagnostic tool for AIS analysis is currently receiving attention in the global agricultural policy debate.