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| Filter results6 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. Enhancing the Use of Appropriate Fertilizers for Improving Rice and Maize Production in TanzaniaMost soils under maize and rice production in Tanzania are characterized by low soil fertility. Fertilizer recommendations were developed in Tanzania to improve soil productivity but most of them are for N and P nutrients. The recommendations do not cover secondary and micro nutrients because the data for these nutrients are very few to establish response functions. In year 2017 to 2019, trials were conducted in 769 farmers’ field in Tanzania to determine soil fertility status and the response... C.J. Senkoro |
4. The Use of Unmanned Aerial Vehicle (UAV) Remotely Sensed Data and Biophysical Variables to Predict Maize Above-Ground Biomass (AGB) in Small-Scale Farming SystemsConsidering the current and projected increase in human population, approaches to optimize crop productivity to meet the rising demand are paramount. Timely and accurate maize Above Ground Biomass (AGB) measurements allow for development of models that can precisely predict yield prior to harvesting, useful for food production management and sustenance. The development of Unmanned Aerial Vehicles (UAVs) as a new generation of robust remote sensing platforms, mounted with high-resolution sensors... C. Dlamini, J. Odindi, O. Mutanga, T. Matongera |
5. Enhancing the Estimation of Equivalent Water Thickness in Neglected and Underutilized Taro Crops Using UAV Acquired Multispectral Thermal Image Data and Index-Based Image SegmentationDue to the impact of climate variability and change, smallholder farmers are increasingly faced with the challenge of sustaining crop production. Taro, recognized as a future smart neglected and underutilized crop due to its resilience to abiotic stresses, has emerged as valuable for diversifying crop farming systems and sustaining local livelihoods. Nonetheless, a significant research gap exists in spatially explicit information on the water status of taro, contributing to the paradox of its... S. Ndlovu, J. Odindi, M. Sibanda, O. Mutanga |
6. High-Throughput Field Phenotyping of Ascochyta Blight Disease Severity in Chickpea Using Multispectral ImagingAscochyta blight (AB) caused by Ascochyta rabiei (Pass.) Labr. is an important and widespread disease of chickpea (Cicer arietinum L.) worldwide. The disease is particularly severe under cool and humid weather conditions, leading to crop losses at all stages of chickpea growth. Screening for resistant cultivars remains the most effective, economical and ecological method of disease management. However, traditional phenotyping methods that relying on trained experts are... F. Ibn El Mokhtar, S. Krimibencheqroun , , A. Harkani , H. Houmairi , O. Idrissi , E. Abdellah , E. Abdellah |