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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. 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 |
3. Monitoring Corn (Zea mays) Yield using Sentinel-2 and Machine Learning for Precision Agriculture ApplicationsCurrently, there is a growing demand to apply precision agriculture (PA) management practices at agricultural fields expecting more efficient and more profitable management. One of PA principal components for site-specific management is crop yield monitoring which varies temporally between seasons and spatially within-field. In this study, we investigated the possibility of monitoring within-field variability of corn grain yield in a 22ha field located in Ferarra, North Italy. Archived yield data... A. Kayad, M. Sozzi, F. Pirotti, F. Marinello, L. Sartori, S. Gatto |
4. Monitoring irrigation water use at large scale irrigated areas using remote sensing in water scarce environmentIncreasing pressure on available water resources in semi-arid region will affect the availability of water for irrigated agriculture. In this context, adoption of innovative and cost-effective tools for water management and analysis of water use patterns in irrigated areas is required for an efficient and sustainable use of water resources. This study aims to evaluate a remote sensing-based approach which allows estimation of the temporal and spatial distribution of crop evapotranspiration... M. Kharrou, V. Simonneaux, M. Le page, S. Er-raki, G. Boulet, J. Ezzahar, S. Khabba, A. Chehbouni |
5. Chlorophyll Meter Based Precision Nitrogen Management in Maize Grown in Alluvial Soil in EgyptPrecision nitrogen (N) management is essential for profitable crop production and to minimize N losses to the environment that are a consequence of an excessive N supply. Chlorophyll meter-based N management can help to achieve high N use efficiency, as aquick and non-destructive spectral characteristics of leaves, which can be used to diagnose plant N deficiency and graduate N fertilization with improve N use efficiency. Field experiments were conducted during two consecutive years, 2019 and... A. Soaud, S. Abou-zeid , A. Ali, D. Hassan |
6. Self-developed Small Robot for Tomato Plants DetectionA mobile (robot) measuring station for tomato plant detection has been developed, equipped with different sensors and a self-developed hardware and software background. The development aims are the applications in precision crop production: artificial intelligence- based detection, imaging, data collection, automation, and remote sensing. The robot is fault- free in field conditions and is therefore a key development tool for precision farming and digital agriculture. The measurement system developed... B. Ambrus, G. Teschner, M. Neményi, A. Nyéki |
7. Implementing Field-Based High Throughput Plant Phenotyping: The Open Source Way... Y. Kassim |