This study examines the effectiveness of mobile as a novel approach for providing targeted and equitable agri-advisory services to farmers at scale. A cross-sectional survey of farmers registered on CABI's Direct2Farm (D2F) user database was undertaken using a combination of telephone interviews, household survey and focus group discussions covering six states in India. Was used mixed method approach that utilized both quantitative and qualitative data collection methods.
This study, evaluates the intervening influence of extension services on livelihood impacts of drought tolerant maize adoption and the potential mechanisms through which extension can enhance or reduce impact of drought tolerant maize using cross-sectional household level data from smallholder maize producers in Zimbabwe. Specifically, we examine whether access to agriculture extension services influences the relationship between livelihood outcomes and the adoption of drought-tolerant maize varieties in selected districts in the country
This study aims to contribute to literature on climate smart agriculture (CSA) scaling by identifying institutional and policy strategies that can help effect scaling of CSA practices in developing regions particularly SSA region. Increased adoption rates are more likely to enhance the overall impact of CSA innovations on productivity, food security, livelihoods and overall sustainability of agriculture. Furthermore, the study seeks to highlight and suggest possible approaches/strategies that the research and development community can adopt in taking CSA to scale.
In this paper is presented a novel approach for technology innovation and dissemination to achieve sustainable intensification in the fields of smallholder farmers. The Science and Technology Backyard (STB) is a hub in a rural area that links knowledge with practices to promote technology innovation and exchange.
In this paper, is introduced an integrated supply chain planning tool for fresh vegetables that takes into consideration the characteristics and resources of three specific states in Mexico, to make recommendations in terms of the crops to be planted, the timing of planting and harvesting, and what markets to target such that the farmers’ profits are maximized. Also relevant is the selection of the appropriate agriculture technology level (e.g. open field, shade structures, or greenhouse) within each region analyzed.
The innovations of this paper lie in the establishment of a multi-product supply chain model composing of a farmer cooperative and a supermarket in which the farmer cooperative supply multiple types of agricultural products to the supermarkets rather than single type of agricultural product. The study started by studying the optimal decision-making behavior of the members of the supply chain in non-coordinated modequantitatively. Then, was applied the revenue-sharing contract to coordinate the mode.
This paper used systematic literature network analysis to review the state-of-the-art blockchain technology including its recent advances, main applications in agri-food value chain and challenges from a holistic perspective. The findings suggest that blockchain technology together with advanced information and communication technology and internet of things have been adopted for the improvement of agri-food value chain management in four main aspects: traceability, information security, manufacturing and sustainable water management.
Developing regions' food system has transformed rapidly in the past several decades. The food system is the dendritic cluster of R&D value chains, and the value chains linking input suppliers to farmers, and farmers upstream to wholesalers and processors midstream, to retailers then consumers downstream. This study analyze the transformation in terms of these value chains' structure and conduct, and the effects of changes in those on its performance in terms of impacts on consumers and farmers, as well as the efficiency of and waste in the overall chain.
The objective of the study was to identify a viable trade-off between low data requirements and useful household-specific prioritizations of advisory messages. At three sites in Ethiopia, Kenya, and Tanzania independently, we collected experimental preference rankings from smallholder farmers for receiving information about different agricultural and livelihood practices. At each site, was identified socio-economic household variables that improved model-based predictions of individual farmers’ information preferences.
This paper addresses this gap by examining the nature of disruption to farm advisors from data-driven smart farming and identifies the challenges and opportunities. The authors aim to better theorize smart farming innovation by examining the advisory role to provide insights for technology developers, and policy directions for governments in relation to supporting uptake of farming innovations.