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| Filter results7 paper(s) found. |
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1. Precision Farming Technology to Increase Soil and Crop Productivity in Egypt Using Remote Sensing and GISPrecision farming or site-specific land management is a new approach for development the agriculture processes to increase the soil and crop productivity with saving efforts and costs. Precision farming includes many techniques such as Global Position Systems (GPS), Geographic Information Systems (GIS), Remote Sensing (RS), Yield Monitors, Internet of Things (IOT), Variable Rate Application (VRA), Yield Mapping, Site-Specific Management Zones (SSMZ) and Crop Modeling. SSMZ delineation can be improved... A. Belal, M. Elsayed , M.E. Jalhoum, M. abdelatif , E. Hendawy , M. Emam, M. Zahran |
2. Decision Support System for Precision Agriculture management Case study : El Salihiya –east Nile delta, Egypt.Soil is a complex mixture of living organisms and organic material, along with soil minerals. the main objective of this work is develop a new methods to improve the agricultural management .The current study relies on developing a decision-making model for agricultural operations to manage potato crops in the El Salihiya area using field data,laboratory analysis and field sensor measurements. The precision agriculture decision support system entitled (EGYPADS) was designed and developed... A. Belal , S. abd el-kader, B. Mamdouh , M. A el-shirbeny, M. abdellatif1, M. Jalhoum , M. Zahran, E.S. Mohamed |
3. Development of Canopy Mapping System of Asian pears (Pyrus pyrifolia Naka) Using Terrestrial Laser ScanningIn this paper, the canopy mapping system (CMS) of Asian pears for estimating yield during Bud thinning and Pruning operations using point cloud data was proposed. Bud thinning and Pruning in Asian pear (Pyrus pyrifolia Naka) is necessary to ensure quality and yield but is time-consuming and heavily depends on work knowledge. This study described a method of estimating the number of fruits through the length of a branch based on remote sensing. The CMS would be useful to support more efficient... E. Morimoto, J. Lee, K. Nonami, I. Matumura, M. Ikebe, S. Sato |
4. Irrigation Water Management for Potato crop under Pivot Irrigation System using Remote sensing techniquesWhen water application records low efficiency, the water losses increased. Irrigation systems often ignore soil variability and water applied uniformly on the field; hence, the water losses amplified. Which means more water application, more energy demand, and more money expenses. El-Salhia region contains a big agricultural farm located at the South Eastern of Nile delta. The field NO 34 was chosen to be investigated under the pivot central sprinkler irrigation system which cultivated with... |
5. Potato Yield Prediction Using Multi-temporal Sentinel-2 Data and Multiple Linear RegressionTraditional potato growth models have a number of flaws, i.e., the cost of data collection, quality of input data, and the absence of spatial information in some cases. To address these challenges, we created a multiple linear regression model (MLRM) that uses the multi-temporal Sentinel-2 derived indices to predict potato yield. Along the growing season (from October 2019 to February 2020) eight Sentinel-2 imageries were collected, afterwards, the normalized difference vegetation index (NDVI)... M.E. Amin, M.A. Abdelfattah, E.S. Mohamed, A.A. Belal, M. Nabil, A.G. Mahmoud |
6. Implementing Field-Based High Throughput Plant Phenotyping: The Open Source Way... Y. Kassim |
7. 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 |