Mountain agricultural systems (MASs) are multifunctional and multidimensional sociocultural systems. They are constantly influenced by many factors whose intensity and impacts are unpredictable. The recent Hindu Kush–Himalayan Assessment Report highlighted the need to integrate mountain perspectives into governance decisions on sustaining resources in the Hindu Kush–Himalayan region, emphasizing the importance of sustainable MASs.
Here, it is described a new participatory protocol for assessing the climate-smartness of agricultural interventions in smallholder practices. This identifies farm-level indicators (and indices) for the food security and adaptation pillars of CSA. It also supports the participatory scoring of indicators, enabling baseline and future assessments of climate-smartness to be made. The protocol was tested among 72 farmers implementing a variety of CSA interventions in the climate-smart village of Lushoto, Tanzania.
This guide is the second in a series of documents designed to support agencies implementing participatory agroenterprise development program operating within defined geographical areas.
This note is a preview on the agricultural innovation systems (AIS) assessment methdology which is being tested in the nine countries of the European Union-funded TAP-AIS DeSIRA project. It presents the rationale, the steps, ethe expected outputs and outcomes.
Continually increasing food demand from a still–growing human population and the need for environmentally–friendly strategies for sustainable agricultural development require innovation and further enhancement of cropping systems’ factor productivity. The system of rice intensification (SRI) has been proposed as a suitable strategy to improve rice yields with reduced input requirements, most notably water and seed, while enhancing soil and water quality because agrochemical applications can be cut back.
The Colombian Ministry of Agriculture Colombia, an international research center and a national farmers’ organization developed a data-driven agricultural program that: (i) compiles information from multiple sources; (ii) interprets that data; and (iii) presents the knowledge to farmers through the local advisory services. Data was collected from multiple sources, including small-scale farmers. Machine learning algorithms combined with expert opinion defined how variation in weather, soils and management practices interact and affect maize yield of small-scale farmers.
The Farmer Field School (FFS) approach has been very successful and witnessed a strong expansion in many areas beyond crop production. Notwithstanding this success, the adoption of FFS in national extension often remains problematic and FFS activities have often been implemented in the margin of national institutions with strong reliance on donor funding. The creation of an enabling environment for institutional support is essential for expanding the effort, improving quality, and strengthening impact and continuity of the FFSs.
Several posters have been created on the occasion of the 5th TAP Partners Assembly (Laos, 20-22 September 2017) to show recent activities and achievements in the eight pilot countries of the CDAIS project.
The level of agricultural productivity in Sub-Saharan Africa remains far below the global average. This is partly due to the scarce use of production- and process-enhancing technologies. This study aims to explore the driving forces and effects of adopting innovative agricultural technologies in food value chains (FVC). These enhancing FVC technologies are referred to as upgrading strategies (UPS) and are designed to improve specific aspects of crop production, postharvest processing, market interaction, and consumption.
Indicator-based tools are widely used for the assessment of farm sustainability, but analysts still face methodological and conceptual issues, including data availability, the complexity of the concept of sustainability and the heterogeneity of agricultural systems. This study contributes to this debate through the illustration of a procedure for farm sustainability assessment focussed on the case study of the South Milan Agricultural Park, Italy. The application is based on a set of environmental, social and economic indicators retrieved from the literature review.