Download the Conference Proceedings
Proceedings
Authors
| Filter results4 paper(s) found. |
|---|
1. Excellence in Agronomy 2030: A new CGIAR-wide initiative to deliver agronomy solutions at scaleRequired increases in crop production and productivity in sub-Saharan Africa (SSA) will not happen without the increased use of appropriate agronomic practices. While several thousand new varieties of nearly all key crops have been produced in the past decade, recent increases in yields in specific countries have only happened when such varieties received the right agro-inputs and management. That said, agronomy is often highlighted as an area that has not delivered impact at scale in SSA, or... B. Vanlauwe, T. Amede, F. Baudron, P. Chivenge, M. Devare, K. Saito, J. Kihara, V. Nangia, P. Pypers, K. Shepherd, E. Vandamme |
2. La fertilité indigène du sol : un élément catalyseur de l’agriculture de précisionDans le contexte actuel de la dégradation des ressources naturelles et des problèmes de disponibilité et d'accessibilité des intrants agricoles, l'agriculture de précision dont le point d'entrée est la connaissance de la fertilité endogène du sol s'impose. Des essais soustractifs ont été conduits pendant deux ans (2018-2019) à la Station d'Expérimentations Agronomiques de l'Université... K. William, J. Sogbedji, M. Lare |
3. 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... |
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 |
