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| Filter results4 paper(s) found. |
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1. FARMER CHARLIE: PRECISION AGRICULTURE AT SMALLHOLDER FARMERS’ SERVICEPreliminary research and an ongoing project in Nigeria showed that agriculture is a crucial activity in the country. It is mainly carried out in small, family-owned farms: in fact, 88% of Nigeria farmers work on less than 0.5 ha. Lack of resources, of readily available information and the impact of climate on agricultural activities lead to low yields and high-cost farm inputs (FAO, 2020). The availability of agricultural data and weather forecast information could play an essential role in improving... B. Bonnardel, G. Cursoli |
2. Nutrient Quality Studies of Fluted Pumpkin (Telfairia Occidentalis Hook. F) Leaves as Influence by Fertilizer Micro-dosing and TimeThe nutrient qualities of vegetables have been noted to be affected by agronomic practices. The study evaluated the effect of fertilizer micro-dosing and time of application on nutrient quality of fluted pumpkin. The field experiment was carried out during 2017/2018 cropping season at the Teaching and Research Farm, Obafemi Awolowo University (O.A.U), Ile-Ife, situated within the forest zone (latitude 070 28’N and longitude 040 33’East and 224 m above sea level). The experiment was... |
3. 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 |
4. 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 |