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| Filter results6 paper(s) found. |
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1. SmartAfriHub for SmartAgriculture capacity buidling in AfricaDigital Innovation Hubs (DIH) are multi-actor ecosystems that support farming communities in their digital transformation by providing a broad variety of services from a one-stop shop. DIHs purpose is to provide a social space for community of practices; provide access to digital technologies and competencies; provide access to infrastructure and tests digital innovations (“test before invest”); provide development playground... K. Charvat, C. Miderho , A. Obot, T. Löytty, H. Kubickova |
2. Spectral assessment of chickpea morpho-physiological traits from space, air and groundChickpea (Cicer arietinum) is an important grain legume in semi-arid regions and water-stress is a major constraint to its productivity. Area under chickpea cultivation is growing but climate change toward greater aridity results in higher precipitation instability and risks yields. The ability to assess water potential can support irrigation decisions. Thus, improved ability to spatially assess plants water status can promote more efficient irrigation. The current... I. Herrmann, R. Sadeh, A. Avneri, Y. Tubul, R. Lati, S. Abbo, D.J. Bonfil, Z. Peleg |
3. Analysis, design and development of a web and mobile application for fertilizer olive orchards recommendationsFarmer’s fertilization practices (FFP) in olive intensive or super intensive orchards must be improved to a better control of fertilization costs, to increase olive yielding, to maintain soil fertility and to avoid environment pollution. Indeed, a large category of fertilizer users apply fertilizers arbitrary (66%) without any knowledge about the adequate nutrient requirements of a such planting system. To improve the FFP in intensive and super intensive olive orchards, and in the frame... A. Larbi, H. Boulal, H. El arbi, W. Ben hamouda |
4. Mapping African soils at 30m resolution - iSDAsoil - Western Time Zones“iSDAsoil” combines remote sensing data and other geospatial information with carefully stratified point samples subjected to spectral analysis and traditional wet chemistry reference analysis. State of the art machine learning techniques were used to create digital maps of 17 agronomically important soil properties at 3 depths, including estimates of uncertainty. iSDAsoil is designed to encourage sharing and we hope that the owners of other soil and agronomic data, in industry... J. Crouch, K. Shephard, M. Miller, J. Collinson, P. Singh, P. Pypers, R. Van den bosch, C. Van beek, M. Chernet, S. Aston |
5. Mapping African soils at 30m resolution - iSDAsoil - Eastern Time Zones“iSDAsoil” combines remote sensing data and other geospatial information with carefully stratified point samples subjected to spectral analysis and traditional wet chemistry reference analysis. State of the art machine learning techniques were used to create digital maps of 17 agronomically important soil properties at 3 depths, including estimates of uncertainty. iSDAsoil is designed to encourage sharing and we hope that the owners of other soil and agronomic data, in industry... C. Van beek, M. Chernet, S. Aston, M. Miller, J. Collinson, K. Shephard, J. Crouch, T. Terhoeven-urselmans |
6. Assessment of Nitrogen and Phosphorus Content (NP) in Citrus Trees Using UAV-imagery Derived Vegetation Indices and Machine Learning AlgorithmsMonitoring nutrient status of citrus trees is fundamental to ensure optimum fruit yield and quality. However, this task is traditionally time-consuming and laborious. Unmanned Aerial Vehicles (UAVs), with their high temporal and spatial resolution imagery, are demonstrating a great potential to substitute traditional methods in assessing nutrient status of several crops, including citrus. In this study, we evaluated the performance of vegetation indices (VIs) derived from UAV multispectral images... Z. Abail, H. Benaouda, M. Chikhaoui, H. Benyahia, O. Iben halima, M. Baraka, A. Douaik, H. Iaaich, A. Zouahri, F. Omari |