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.
La plateforme d’innovation (PI) est une approche multi-acteurs pour des solutions aux problèmes complexes. Elle est d’actualité en Afrique Subsaharienne confrontée à de nombreux défis agricoles. Cette étude utilise une perspective systémique pour comprendre le processus de génération et de diffusion d’innovation relative à la post-récolte du riz local au Bénin. La collecte des données quantitatives et qualitatives a été faite avec des questionnaire et guides d’entretien auprès de 300 femmes étuveuses de riz, membres de la PI à Malanville, et sélectionnées de façon aléatoire et stratifiée.
A fragmented digital agriculture ecosystem has been linked to the slow scale-out of digital platforms and other digital technology solutions for agriculture. This has undermined the prospects of digitalizing agriculture and increasing sectoral outcomes in sub-Saharan African countries. We conceptualized an aggregator platform for digital services in agriculture as a special form of digital platforms that can enhance the value and usage of digital technologies at the industry level. Little is known about how such a platform can create value as a new service ecology in agriculture.
Animal-source foods (ASF), such as fish, provide a critical source of nutrients for dietary quality and optimal growth of children. In sub-Saharan Africa, children often consume monotonous cereal-based diets, a key determinate of malnutrition such as stunting. Identifying existing sources of ASF for children’s diets will inform the development of nutritious food systems for vulnerable groups.
Aquatic foods are increasingly being recognized as having an important role to play in an environmentally sustainable and nutritionally sufficient food system. Proposals for increasing aquatic food production often center around species, environments, and ambitious hi-tech solutions that mainly will benefit the 16% of the global population living in high-income countries.
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.
Fish is a key source of income, food, and nutrition in Zambia, although unlike in the past, capture fisheries no longer meet the national demand for fish. Supply shortfalls created an opportunity to develop the aquaculture sector in Zambia, which is now one of the largest producers of farmed fish (Tilapia spp.) on the continent. In its present form, the aquaculture sector exhibits a dichotomy.
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.
L’objectif de cet article est d’explorer les défis et les contraintes de l’adoption des technologies de l’agriculture de précision, en se plaçant du point de vue des entreprises opérant dans le secteur des nouvelles technologies agricoles. L’étude s’appuie sur une approche qualitative moyennant une analyse de contenu issue de huit entretiens semi-directifs.
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.