Organic agriculture has experienced remarkable growth in recent decades as societal interest in environmental protection and healthy eating has increased. Research has shown that relative to conventional agriculture, organic farming is more e cient in its use of non-renewable energy, maintains or improves soil quality, and has less of a detrimental e ect on water quality and biodiversity. Studies have had more mixed findings, however, when examining the impact of organic farming on greenhouse gas (GHG) emissions and climate change.
Inclusive business models dominate current development policy and practices aimed at addressing food and nutrition insecurity among smallholder farmers. Through inclusive agribusiness, smallholder food security is presumed to come from increased farm productivity (food availability) and income (food access). Based on recent research, the focus of impact assessments of inclusive business models has been limited to instrumental aspects, such as the number of farmers supported, the training provided, and immediate farm outcomes, namely revenue.
This study examines the influence of farmers’ social capital on their decisions to deal with climate change and climate variability in Burkina Faso. The study is based on a household survey conducted among 450 households, randomly selected from three communities in Burkina Faso.
Agricultural production systems are a composite of philosophy, adoptability, and careful analysis of risks and rewards. The two dominant typologies include conventional and organics, while biotechnology (GM) and Integrated Pest Management (IPM) represent situational modifiers. We conducted a systematic review to weigh the economic merits—as well as intangibles through an economic lens—of each standalone system and system plus modifier, where applicable. Overall, 17,485 articles were found between ScienceDirect and Google Scholar, with 213 initially screened based on putative relevance.
Agricultural production is a crucial and fundamental aspect of a stable society in China that depends heavily on the climate situation. With the desire to achieve future sustainable development, China’s government is taking actions to adapt to climate change and to ensure food self-sufficiency.
The Guidance Note on Operationalization provides a brief recap of the conceptual underpinnings and principles of the TAP Common Framework as well as a more detailed guide to operationalization of the proposed dual pathways approach. It offers also a strategy for monitoring and evaluation as well as a toolbox of select tools that may be useful at the different stages of the CD for AIS cycle.
The Conceptual Background provides an in-depth analysis of the conceptual underpinnings and principles of the TAP Common Framework. It is also available in French and Spanish.
This publication represents a synthesis of assessments of national agricultural innovation systems in countries of Central Asia, South Caucasus and Turkey. The first chapter gives an introduction of the project “Capacity Development for Analysis and Strengthening of Agricultural Innovation Systems in Central Asia and Turkey”, out of which the current publication reports about one of the project outputs achieved.
This book documents a unique series of 19 case studies where agricultural biotechnologies were used to serve the needs of smallholders in developing countries. They cover different regions, production systems, species and underlying socio-economic conditions in the crop (seven case studies), livestock (seven) and aquaculture/fisheries (five) sectors. Most of the case studies involve a single crop, livestock or fish species and a single biotechnology.
In this paper, presented at the 8th European IFSA Symposium ( Workshop 6: "Change in knowledge systems and extension services: Role of the new actors") in 2008, the authors discuss a conceptual framework that understands innovation processes as the outcome of collaborative networks where information is exchanged and learning processes happen. They argue that technical and economic factors used to analyse drivers and barriers alone are not sufficient to understand innovation processes.