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| Filter results9 paper(s) found. |
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1. Mapping African soils at 30m resolution - iSDAsoil: leveraging spatial agronomy in farm-level advisory for smallholdersField level soil data has been the foundation of agronomic advisory, but traditional methods involving on-farm sampling are too expensive for a large proportion of African smallholders. Building on the work of the African Soil Information Service (AfSIS), Innovative Solutions for Decision Agriculture (iSDA) and partners have created an agronomic soil database which covers the entire African continent at a spatial resolution of 30 m. “iSDAsoil” combines remote sensing data and other... J. Crouch |
2. USE OF DRONE IN PRECISION AGRICULTURE IN SENEGALIn Senegal more precisely in the valley of the Senegal River, we have introduced drones for use in precision agriculture. These Drones are used in phytosanitary treatment and fertilizer spreading. Thus we also test in the monitoring of plots, in particular to detect deficiencies in fertilizer, stresses and diseases. We have started with some producers in the treatment of rice plots with post-emergence herbicide and the results have been satisfactory, even going as far as a reduction in the doses... O. Aidara |
3. 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 |
4. MAPPING AND ASSESSING AFRICAN SOILS FERTILITY USING HIGH-RESOLUTION REMOTE SENSING AND MACHINE LEARNING APPROACHES: STATE-OF-THE-ART AND PERSPECTIVESAfrica is far from exploiting its true agricultural potential. United Nations Food and Agriculture Organization (FAO) indicates that the continent has 60% of non-cultivated lands worldwide. While soil fertility is well highlighted as one of the major limiting factors, only limited information is available on soil nutrient contents and nutrient availability in the African soils. Soil fertility of agricultural fields is related to many physical and chemical properties, such as texture, organic matter... M. Hmimou, A. Laamrani, F. Sehbaoui, A. Chehbouni, S. Khabba, D. Dhiba |
5. EFFECT OF INTERCROPPING SORGHUM WITH COWPEA AND NITROGEN APPLICATION ON GROWTH AND YIELD OF SORGHUM (Sorghum bicolor (L.) MOENCH)Despite the development of improved varieties, the yield of sorghum has remained significantly low in dryland environments due to low soil fertility and inappropriate cropping practices. However, implementation of precision agriculture (PA) within the context of companion cropping with legumes and fine-tuning the supply of fertilizer nitrogen (N) has the potential to increase sorghum yield in these environments. Nonetheless, the effect sorghum-cowpea compatibility, fertilizer N use and their interaction... P.E. Moi , O.M. Kitonyo, G.N. Chemining’wa, J.M. Kinama |
6. 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 |
7. 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 |
8. Modelling Fertigation and Micro-Climate Parameters for Greenhouse Tomato (Solanum Lycopersicum L.)Amidst the hiking price of fertilizer and projected water scarcity across the world, it is imperative to explore the interaction between fertilizer, irrigation and genotype notwithstanding the micro-climate parameters so as to maximize yield while protecting the environment. The Decision Support System for Agrotechnology Transfer (DSSAT) is a model which employs all these input factors to help predict yield and thereby make an informed decision. The study sort to calibrate and validate the... Y.K. Agbemabiese, P. Abubakari, P.K. Dzomeku, I. Shaibu |
9. High-Throughput Field Phenotyping of Ascochyta Blight Disease Severity in Chickpea Using Multispectral ImagingAscochyta blight (AB) caused by Ascochyta rabiei (Pass.) Labr. is an important and widespread disease of chickpea (Cicer arietinum L.) worldwide. The disease is particularly severe under cool and humid weather conditions, leading to crop losses at all stages of chickpea growth. Screening for resistant cultivars remains the most effective, economical and ecological method of disease management. However, traditional phenotyping methods that relying on trained experts are... F. Ibn el mokhtar, S. Krimibencheqroun , , A. Harkani , H. Houmairi , O. Idrissi , E. Abdellah , E. Abdellah |