The objective of this study is to evaluate the ability of soil physical characteristics (i.e., texture and moisture conditions) to better understand the breeding conditions of desert locust (DL). Though soil moisture and texture are well-known and necessary environmental conditions for DL breeding, in this study, we highlight the ability of model-derived soil moisture estimates to contribute towards broader desert locust monitoring activities.
FAO Eritrea, in partnership with the Ministry of Agriculture is implementing the national component of a global project entitled “Developing capacity in Agriculture Innovation System project: Scaling up the Tropical Agriculture Platform Framework”.
Ce catalogue décrit une série de solutions agricoles pour les zones arides du Sahel et de la Corne de l'Afrique, utiles pour l'adaptation au changement climatique et l'atténuation de ses effets. Il est basé sur les interventions du programme Technologies pour la transformation de l'Agriculture en Afrique (TAAT). Ce programme, dirigé par l'Institut International d'Agriculture Tropicale (IITA), est à l'origine de nouvelles approches pour le déploiement de technologies éprouvées auprès des agriculteurs africains.
The future of inclusive forestry in Nepal depends on forestry professionals who can recognise patriarchal roots of gender injustice as they operate in the ideologies and apparatus of forest governance, and who can resist those injustices through their work. This paper uses the notion of knowledge practices to explore the recognition of injustice amongst Nepal’s community forestry professionals, and the relationship between recognition and resistance, highlighting the inherently political nature of all knowledge practices.
This paper contends that the exclusion of millions of poor from agricultural development gains is inexorably linked to the innovation system features that have evolved over time. An oft repeated lament of the Government of India about the inadequacy of reforms in agricultural research and extension, is used to explore the structure and institutions of agricultural innovation. Three main components of the agricultural innovation system, are the agricultural research and extension actors, the farming communities, and policy making agencies.
Good governance of community fish refuge-rice field fishery (CFR-RFF) systems, which are a vital source of nutritious aquatic foods, is integral to the food and nutrition security of rural households in Cambodia. Intentional integration of nutrition and gender activities into CFR management has the potential to further bolster these outcomes. Using qualitative and quantitative data, we aimed to document the impacts of the nutrition and gender activities conducted alongside CFR management activities.
Where CGIAR breeding programs rely on the private sector for the multiplication and distribution of improved cultivars, persistent challenges have dampened their impact on varietal adoption and turnover rates. Part of the problem is that research and practice in CGIAR and among its national breeding program partners tend to treat the private sector as a vehicle for seed delivery, rather than as commercial businesses facing a range of unique constraints and threats.
1. Many coastal communities depend on ecosystems for goods and services that contribute to human well-being. As long-standing interactions between people and nature are modified by global environmental change, dynamic and diversified livelihood strategies that enable seasonal adaptation will be critical for vulnerable coastal communities. However, the success of such strategies depends on a range of poorly understood influences. 2.
Women play important roles at different nodes of both agricultural and off-farm value chains, but in many countries their contributions are either underestimated or limited by prevailing societal norms or gender-specific barriers. We use primary data collected in Asia (Bangladesh, Philippines) and Africa (Benin, Malawi) to examine the relationships between women’s empowerment, gender equality, and participation in a variety of local agricultural value chains that comprise the food system.
Plants are susceptive to various diseases in their growing phases. Early detection of diseases in plants is one of themost challenging problems in agriculture. If the diseases are not identified in the early stages, then they may ad-versely affect the total yield, resulting in a decrease in the farmers' profits. To overcome this problem, many re-searchers have presented different state-of-the-art systems based on Deep Learning and Machine Learningapproaches. However, most of these systems either use millions of training parameters or have low classificationaccuracies.