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| Filter results4 paper(s) found. |
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1. IMPACT OF SENSOR-BASED PRECISION NITROGEN MANAGEMENT ON WHEAT YIELD AND NITROGEN USE EFFICIENCYOptical sensors are promising new technology for precision nitrogen management in crops. Fertilizer N management for wheat (Cultivar: Giza 171) using optical sensor (GreenSeeker®) was evaluated at the Experimental Farm of Faculty of Agriculture, Cairo University, Giza Governorate, Egypt. The experiment was laid out in randomized block design with three replications during two successive winter seasons (2017/2018 and 2018/2019) to quantify the relationship between N uptake at jointing growth... A.A. Soaud, E.A. El-metwally , A.M. Ali, R.K. Sayed |
2. 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 |
3. Development of a Decision Support Tool to Derive Site-specific Nutrient Management Recommendations for Maize Production Using Machine LearningAgriculture is the main source of food and income for rural communities in developing countries, especially in Africa. Given current population growth, pressures on agricultural systems will continue to increase. Many countries have agricultural economies that are highly dependent on agricultural productivity. For example, several variables can influence fertilization for optimal grain yields. Quantifying the effects and relative importance of soil properties such as soil type, pH, Olsen-P, climate,... O. Ennaji, L. Vergutz, A. El Allali |
4. Implementing Field-Based High Throughput Plant Phenotyping: The Open Source Way... Y. Kassim |