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| Filter results5 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. SIMULATION OF CASSAVA YIELD UNDER DIFFERENT CLIMATIC SCENARIOS IN KILEMBWE, SOUTH-KIVU PROVINCE EASTERN DR CONGOClimate variability and change are projected to significantly impact agricultural production across Africa. This study assessed the effects of climate variability and change on cassava yield in Kilembwe, South-Kivu province Eastern DR Congo. The assessment relies on the DSSAT crop model simulation of cassava under current and future climate. The period 1980–2010 was used to represent the baseline, while future projection covers three periods including the near future (2010–2039), mid-century... A.B. Yamungu, A. Egeru, M.J. Majaliwa, B.M. Dossa |
3. 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 |
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 |