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| Filter results5 paper(s) found. |
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1. Just a moment; the need for streamlining precision agriculture data in AfricaPrecision agriculture (PA) data sources in the era of digital agriculture are diverse in terms of the range of technology options and the types of data they generate. These include proximal sensors, unmanned aerial vehicle (UAV), satellites, farm machinery mounted sensors and robotics to generate static data or real time information (e.g., yield monitoring). Government institutions, scientists and private sectors take the lion’s share in generating PA data at innovation, validation and dissemination... T.B. Gobezie, A. Biswas |
2. Crop monitoring and forecasting system based on cloud data and capabilitiesVarious systems for crop monitoring & forecasting, using satellite images and meteorological data, exist around the world. Their complexity differs from one system to another, according to the temporal and spatial scale and according to the objectives assigned to them. Among the well known are the European Monitoring Agricultural ResourceS system, the USDA system of the Foreign Agricultural Service, the Moroccan CGMS system, the Belgian CGMS system and the Chinese CropWatch system. The... |
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. Spatial soil loss risk assessment for proper intervention: a case of Neri watershed in Omo Gibe basin, Southwestern EthiopiaSoil erosion is one of the biggest global environmental problems resulting in both on-site and offsite effects. It contributes negatively to agricultural production, quality of source water for drinking, ecosystem health in land and aquatic environments, and aesthetic value of landscapes. This study was conducted in Neri watershed, part of Omo Gibe basin with area of 465.46 km2. RUSLE model supported by a GIS framework is used to assess the average annual soil loss, and create a soil erosion hazard... A. Hegano |
5. A Comparative Estimation of Maize Leaf Moisture Content on Smallholder Farming Systems Using Unmanned Aerial Vehicle (UAV) Based Proximal Remote SensingUnderstanding maize moisture conditions is necessary for crop monitoring and developing early warning systems to optimise agricultural production in smallholder farms. Therefore, this study evaluated the utility of UAV derived multispectral imagery and machine learning techniques in estimating maize leaf moisture indicators; equivalent water thickness (EWT), fuel moisture content (FMC) and specific leaf area (SLA). The results illustrated that both NIR and red-edge derived spectral variables were... S. Ndlovu |