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| Filter results4 paper(s) found. |
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1. Crop water requirements, biomass and grain yields estimation for Sulla (Hedysarum coronarium L.) using cropwat in semi-arid regions of TunisiaDwindling water resources and increasing food requirements require greater efficiency in water use, both in rainfed and in irrigated agriculture. Regulated deficit irrigation provides a means of reducing water consumption while minimizing adverse effects on yield. With the current water shortage in Africa improving crop water use is vital especially in the arid and semi-arid regions. Models can play a useful role in developing practical recommendations for optimizing crop production under... R. Hajri, M. Rezghui, M. Mechri, M. Ben Younes |
2. 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 |
3. Application of Remote Sensing Technologies for Monitoring within Field Soil and Crop Growth Variability... N. Majozi |
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 |