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| Filter results5 paper(s) found. |
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1. Using Site-Specific Management Zones for Potato Crop Management, East Nile Delta, EgyptThe field management zones (MZ) delineated using soil electrical conductivity (EC) and topographic parameters are the basis for site-specific crop management (SSCM). The objective of this paper was to delineation site-specific management zones of 155 feddans (67.2 ha) of a potato pivot field at East of Nile Delta, Egypt for use in smart farming based on spatial variability of soil and plant properties, yield and topographic attributes. The salinity measurement in the field... A.B. Belal, E.S. Mohamed, M.E. Jalhoum, M. zahran, M.A. Abdellatif, M.S. Emam, E.A. Hendway |
2. Leaf-proximal Hyperspectral Data and Multivariate Modelling Approaches to Estimate Phosphorus and Potassium Content of Wheat LeavesThe assessment of plant nutrient status to provide sufficient fertilization for rapid and continuous uptake by plants has been based on visual diagnosis in the field, which is quick but demands a lot of experience and has low operability. Visible near-infrared spectroscopy (VNIS) has shown to be a quick, non-destructive, accurate, and cost-effective analytical method in precision agriculture. In this study, we assessed the potential of this technology to predict phosphorus and potassium content... Y. El-mejjaouy, B. Dumont, P. Vermeulen, A. Oukarroum, B. Mercatoris |
3. The Future of Farming: Bringing Biophotonics and Machine Learning to Revolutionize AgricultureThe future of farming is set to be revolutionized by biophotonics and machine learning. Biophotonics is the study of the interaction of light and living matter, and machine learning is a form of artificial intelligence that allows computers to learn from data. Together, these two technologies will allow for more precise and efficient farming, as well as greater yields and less wastage. Biophotonics will allow for more precise targeting of crops with pesticides and herbicides, as well as more efficient... S. Ndlovu |
4. Optimizing Durum Wheat Nitrogen Nutrition Index (NNI) Prediction Through Sentinel-2 Vegetation Index IntegrationNitrogen is crucial for durum wheat growth and productivity, but excess or insufficient levels can harm both the environment and farmers' finances. Remote sensing offers rapid, cost-effective, and nondestructive ways to assess crop nutrition, with vegetation indices (VIs) indicating plant health. This study aims to enhance the accuracy of durum wheat nitrogen status prediction by investigating modified formulations of Nitrogen Nutrition Index (NNI) coupled with various vegetation indices (VIs),... N. Boughattas, K. Marwa, Z. Mohamed, A. Sawsen, A. Soumaya, H. Hafedh, H. Imen, T. Youssef |
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 |