A nutrition-sensitive food system is one that goes beyond staple grain productivity and places emphasis on the consumption of micronutrient-rich nonstaples through a variety of market and nonmarket interventions. A nutrition-sensitive approach not only considers policies related to macrolevel availability and access to nutritious food, but it also focuses on household- and individual-level determinants of improved nutrition. In addition to agriculture, intrahousehold equity, behavior change, food safety, and access to clean water and sanitation are integral components of the food system.
In this review, we examine the debate surrounding the role for organic agriculture in future food production systems. Typically represented as a binary organic–conventional question, this debate perpetuates an either/or mentality. We question this framing and examine the pitfalls of organic–conventional cropping systems comparisons. The review assesses current knowledge about how these cropping systems compare across a range of metrics related to four sustainability goals: productivity, environmental health, economic viability, and quality of life.
We look at the trade-off between smallholder cocoa intensification and the ecosystem in Indonesia and investigate the determinants of environmental efficiency in cocoa production. In our analysis, we apply a distance output function that includes cocoa production and the abundance of native rainforest plants as outputs. Our data set, based on a household and environment survey conducted in 2015, allows us to analyze 208 cocoa producers with both measured and self-reported data. We find that the intensification of cocoa farms results in higher ecosystem degradation.
Capacity development interventions in support of agricultural innovation are more effective when based on systematic and participatory assessments of existing skills and capacity needs. Recognizing that, an instrument has been developed in the context of the Capacity Development for Agricultural Innovation Systems (CDAIS) project. It consists of a capacity scoring tool that allows assessing innovation capacities, identifying strengths and weaknesses and monitoring capacity changes over time. This paper describes the scoring tool and provides guidelines on how to apply it successfully.
This concept note has been developed within the context of the EU-funded CDAIS project, which is jointly implemented by AGRINATURA-EEIG and the Food and Agriculture Organization of the United Nations (FAO) to support the TAP Action Plan in eight pilot countries in Africa (Angola, Burkina Faso, Ethiopia, Rwanda), Asia (Bangladesh, Laos) and Central America (Guatemala, Honduras) .
This training manual was prepared under the EU-funded project Capacity Development for Agricultural Innovation Systems (CDAIS), a global partnership (Agrinatura, FAO and 8 pilot countries) that aims to strengthen the capacity of countries and key stakeholders to innovate in complex agricultural systems, thereby achieving improved rural livelihoods.
CDAIS is a global partnership that aims to strengthen the capacity of countries and key stakeholders to innovate in the context of complex agricultural systems, to improve rural livelihoods. The goal of the Capacity Development for Agricultural Innovation Systems (CDAIS) project is to promote innovation that meets the needs of small farmers, small and medium-sized agribusiness, and consumers.
The timeline tool is generally put to use when stakeholders embark upon the self-assessment phase of their innovation partnership. Stakeholders are asked to recall moments they feel were significant for the partnership, from its beginning to the present and to reflect upon how the partnership has evolved since it began.
The capacity-focused problem tree pinpoints a core capacity issue, along with its causes and effects. It helps clarify the precise capacity-development objectives that the intervention aims to achieve. The focus should be on functional capacity, but room should be left to acknowledge technical capacity issues too.
This tool enables participants to become cognisant of the functional capacities discovered through the capacity scoring questionnaire, and test the limits of these capacities through simulations or role-playing (e.g. problem-solving, collaboration, information sharing, and engagement). The simulation game leads to an intuitive understanding of innovation capacities and of the importance of the enabling environment, helping participants to learn about the significance of these capacities.