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| Filter results6 paper(s) found. |
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1. CropSAT – opportunities for applications in precision agriculture in AfricaThe present paper aims at describing the CropSAT system, a Sentinel-2-based interactive decision support system (DSS) that provides vegetation index (VI) maps free-of-charge all across the globe for different applications in precision agriculture. We summarize research results from the ongoing developmental process and pointing to opportunities for development and application in precision agriculture in Africa. The DSS was initially developed in a research project at the Swedish University of... O. Alshihabi, I. Nouiri, M. Mechri, H. Angar, K. Piikki, J. Martinsson, M. Söderström |
2. Potato Yield Prediction Using Multi-temporal Sentinel-2 Data and Multiple Linear RegressionTraditional potato growth models have a number of flaws, i.e., the cost of data collection, quality of input data, and the absence of spatial information in some cases. To address these challenges, we created a multiple linear regression model (MLRM) that uses the multi-temporal Sentinel-2 derived indices to predict potato yield. Along the growing season (from October 2019 to February 2020) eight Sentinel-2 imageries were collected, afterwards, the normalized difference vegetation index (NDVI)... M.E. Amin, M.A. Abdelfattah, E.S. Mohamed, A.A. Belal, M. Nabil, A.G. Mahmoud |
3. Productivity and Profitability of Maize (Zea Mays L.) As Affected by Planting and Fertilization Schemes on the Ferralsols of Southern TogoA sustainable improvement of crop productivity and profitability in the current context of climate change and land degradation is necessary to meet the food and cash needs of a ceaselessly growing population. In order to help achieve this aim, we carried out a 2-year experiment (2020 and 2021) at the University of Lomé Agronomic Experiment Station. The experiment was set up in a split-plot design, composed of eight (08) treatments in three (03) replicates each. Two planting schemes (SC1=... M. Mazinagou, M.J. Sogbedji, A. N'gbendema |
4. Determination of Major Limiting Nutrients and Site-specific Fertilizer Recommendation Towards Optimizing Rice Production in the Irrigated Perimeter of the Zio Valley (Togo)Adoption of appropriate inorganic fertilization schemes is essential to improving fertilizer use efficiency and crop performance. This study aims to contribute to the improvement of rice yields in the irrigated perimeter of the Zio Valley in Togo through appropriate inorganic fertilization. Nutrient omission trials were set up during November 2020 to March 2021 and May to September 2021, with producers identified in the four (04) villages (Mission Tove, Ziowonou, Kovie and Assome) located in the... A. N'gbendema, M.J. Sogbedji, M. Mazinagou |
5. Rice Production System and Major Nutrients Balance Assessment in Rice Cropping in the Irrigated Perimeter of the Zio ValleyKnowledge of cropping systems and farming practices are essential towards improving crop yields. This study aims to characterize rice production systems, analyse fertilization practices and assess the impact of irrigated rice on the balance of major nutrients in Zio valley. The characterization of production systems and fertilization practices were carried out through a survey of a sample of 192 randomly selected producers, i.e. 34% of the total number of farmers in the four (4) villages of the... A. N'gbendema, M.J. Sogbedji, M. Mazinagou |
6. Assessment of Nitrogen Fertilization in Tunisian Wheat Production Using Proximal and Remote SensingThe cereal sector in Tunisia covers wide areas in the country from sub-humid to semi-arid zones; most of the fields are rainfed. The sector is suffering from climate change impacts in term of rainfall amount and pattern. Water management policy in the country prioritizes allocating surface water to domestic uses than irrigation. On the other hand irrigation using groundwater (e.g. in Kairouan) continue to over use the water table with an average drawdown of 5 m/year. Because of this, low efficiency... M. Mechri, O. Alshihabi, H. Angar, I. Nouiri, M. Landolsi, M. Söderström, K. Persson, S. Phillips |
