El Curso Masivo en Línea (MOOC) gratis sobre la Gestión de Datos Abiertos en Agricultura y Nutrición fue creado originalmente en el año 2016. El curso fue dado 5 veces entre Noviembre del 2017 y noviembre del 2018, alcanzando a más de 5000 personas mundialmente, antes de ser hecho disponible para su uso sin restricciones.
Ce cours en ligne massif (MOOC) gratuit sur la gestion des données ouvertes en agriculture et nutrition a été créé en 2016. Déjà en 2017 et 2018, plus de 5000 participants de partout dans le monde ont déjà suivi cette formation, laquelle est maintenant disponible pour une utilisation gratuite et sans restriction.
This free Massive Open Online Course (MOOC) on Open Data Management in Agriculture and Nutrition was first created in 2016. The course was delivered 5 times between November 2017 and November 2018, reaching over 5000 people globally, before being made available for unrestricted use
Global Open Data for Agriculture and Nutrition (GODAN) and The Haller Foundation joined forces in 2016 when the UK based charity released version one of the Haller Farmers App.
Accurate and timely crop mapping is crucial for environment assessment, food security and agricultural production. However, for the areas with high landscape heterogeneity and frequent cloudy and rainy weather, the insufficient high-quality satellite images limit the accuracy of crop classification. The recently launched Chinese GF-6 wide field-of-view camera (WFV) with a revisit cycle of 4-day and spatial resolution of 16-meter shows great potential for agricultural monitoring.
La transition agroécologique requiert de transformer la manière d’accompagner les agriculteurs dans leurs changements de pratiques. Les champs-écoles sont des dispositifs participatifs pertinents pour cela, car ils accroissent les capacités des agriculteurs à expérimenter, à produire des connaissances et à construire eux-mêmes des innovations. Il est toutefois nécessaire de veiller à la qualité de mise en œuvre de ces dispositifs, ce qui a des implications pour les acteurs de la recherche et du développement.
Ornamental plants are constantly being improved by new technologies and cultivation systems to provide new, high-quality plant material for one of the most demanding markets in the horticulture sector. In addition, the ornamental production sector faces several challenges, such as an increase in costs of production, new and old pests and diseases, climate change and the need to adapt to environmental stresses, the need for conservation and environmental protection, and competition with other food and energy crops in terms of areas and natural resources.
The determination of bunch features that are relevant for bunch weight estimation is an important step in automatic vineyard yield estimation using image analysis. The conversion of 2D image features into mass can be highly dependent on grapevine cultivar, as the bunch morphology varies greatly. This paper aims to explore the relationships between bunch weight and bunch features obtained from image analysis considering a multicultivar approach.
The digital transformation in agriculture introduces new challenges in terms of data, knowledge and technology adoption due to critical interoperability issues, and also challenges regarding the identification of the most suitable data sources to be exploited and the information models that must be used.
The spatial and temporal variability of soil properties (fluid composition, structure, and water content) and hydrogeological properties employed for sustainable precision agriculture can be obtained from geoelectrical resistivity methods. For sustainable precision agricultural practices, site-specific information is paramount, especially during the planting season.