Participation of actors is essential for achievement of the United Nation’s (UN) Sustainable Development Goals (SDGs). With respect to sustainable agriculture the UN has introduced a collaborative framework for food systems transformation encompassing: 1) food system champions identification; 2) food systems assessment; 3) multi-stakeholder dialogue and action facilitation; and, 4) strengthen institutional capacity for food systems governance. The last two actions are the focus of this thesis.
The Newsletter of the Tropical Agriculture Platform (TAP) provides regular updates on activities by TAP and its partners, on the projects and on upcoming events. This issue specifically refers to the period from August to October 2021.
Contract farming has gained in importance in many developing countries. Previous studies analysed effects of contracts on smallholder farmers’ welfare, yet mostlywithout considering that different types of contractual relationships exist. Here, we examine associations between contract farming and farm household income in the oilpalm sector of Ghana, explicitly differentiating between two types of contracts,namely simple marketing contracts and more comprehensive resource-providing contracts.
Le projet RIVAGE veut favoriser l’adoption de pratiques alternatives pour gérer les impacts de la pollution diffuse dans le bassin versant de la rivière Pérou en Guadeloupe. Son objectif est de produire et partager les connaissances sur les processus, les impacts et les pratiques innovantes avec les acteurs du territoire. Pour faciliter la prise en compte des résultats, le projet a créé une « école-acteurs ». L’école-acteurs est un espace d’échanges autour des thématiques liées à la pollution diffuse agricole.
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.
Capacity development interventions are considered critical entry points for advancing gender equality in agricultural research systems. However, the impacts of capacity development programs are often difficult to track. Academic reviews highlight that insufficient attention is paid to the suitability of gender training programs to increase capacity and limited evidence is available on their longer-term impacts.
The application of ubiquitous computing has increased in recent years, especially due to the development of technologies such as mobile computing, more accurate sensors, and specific protocols for the Internet of Things (IoT). One of the trends in this area of research is the use of context awareness. In agriculture, the context involves the environment, for example, the conditions found inside a greenhouse.
The impact of global warming on crop growth periods and yields has been evaluated by using crop models, which need to provide various kinds of input datasets and estimate numerous parameters before simulation. Direct studies on the changes of climatic factors on the observed crop growth and yield could provide a more simple and intuitive way for assessing the impact of climate change on crop production.
Soil texture is a key soil property influencing many agronomic practices including fertilization and liming. Therefore, an accurate estimation of soil texture is essential for adopting sustainable soil management practices. In this study, we used different machine learning algorithms trained on vis–NIR spectra from existing soil spectral libraries (ICRAF and LUCAS) to predict soil textural fractions (sand–silt–clay %). In addition, we predicted the soil textural groups (G1: Fine, G2: Medium, and G3: Coarse) using routine chemical characteristics as auxiliary.
Recent Society 5.0 efforts by the Government of Japan are aimed at establishing a sustainable human-centered society by combining new technologies such as sensor networks, edge computing, Internet of Things (IoT) ecosystems, artificial intelligence (AI), big data, and robotics. Many research works have been carried out with an increasing emphasis on the fundamentals of wireless sensor networks (WSN) for different applications; namely precision agriculture, environment, medical care, security, and surveillance.