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| Filter results5 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. The effectiveness of Neem materials and biochar as nitrification inhibitors in reducing nitrate leaching in a compost-amended Ferric LuvisolNitrate produced after mineralization from compost may be prone to leaching especially in Tropical sandy soils, because of increased rate of nitrification and the porous nature of such soils. This may result in low N use efficiency and adverse environmental effects. Inorganic nitrification inhibitors are costly and mostly unavailable in Ghana. The use of simple but effective local materials as nitrification inhibitors is therefore a priority area of research. Two of such materials may be neem... H. Abeka |
3. Unmanned Aerial Vehicles (UAVs) for Phenotypic Traits Estimation & Yellow Rust Disease Severity Assessment in Small-scale Wheat Breeding Trials in EthiopiaRemote Sensing (RS) platforms; like the Unmanned Aerial Vehicles (UAVs) are recently gaining traction in agricultural data collection systems and used for various phenotyping of breeding field trials and capturing different biophysical, biochemical and sanitary traits which can be used to predict and explain the resulting yield and selecting better verities. Compared to the conventional phenotyping usually done by visual scoring and manual measurements which is time consuming/back breakings, susceptible... T. Anberbir, G. Mamo , A. Dabi |
4. An Ensemble-Based Deep Learning Approach for Early and Accurate Wheat Disease DetectionCrop diseases are the primarily cause for yield loss and a factor for food security issue around the globe. Crop diseases caused by pathogens pose a significant threat to global food security, the challenge become worst particularly in developing countries like Ethiopia. Rapid population growth and accurate disease identification is crucial for timely intervention and minimizing crop losses. However, traditional methods often rely on expert analysis, which can be time-consuming and resource-intensive.... T. Aboneh, P. Rorissa |
5. Design and Development of a LoRa Communication System for Scalable Smart Irrigation SystemsSmart irrigation is a promising tool to optimize irrigation water use but is still faced with challenges related to usability and applicability attributed to several constraints such as high initial costs, complex user interface, poor connectivity, limited farm coverage, etc. This study aimed to solve some of these issues through the development and testing of a LoRa communication system using a Raspberry Pi 4, LoRa HAT concentrator, and Strega smart valve at the Makerere University Agricultural... J. Wanyama , J. Ikabat, I. Kabenge, P. Hess, P. Nakawuka, E. Bwambale , J. Muyonga, S. Felicioni, A. Bühlmann, T. Anken |