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Acharya, I
Al-Gaadi, K
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Authors
Al-Gaadi, K
Hassaballa, A.A
Tola, E
Madugundu, R
Kayad, A.G
Madugundu, R
Al-Gaadi, K
Tola, E
Kovacs, P
Maimaitijiang, M
Millett, B
Dorissant, L
Acharya, I
Janjua, U.U
Dilmurat, K
Topics
Precision Agriculture and Global Food Security
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Big Data, Data Mining and Deep Learning
Type
Oral
Poster
Year
2018
2022
2024
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Filter results3 paper(s) found.

1. Applying a Bivariate Frequency Ratio Technique for Potato High Yield Susceptibility Mapping

Spatial variation of soil characteristics and vegetation conditions are viewed as the most important indicators of crop yield status. Therefore, this study was designed to develop a crop yield prediction model through spatial autocorrelation between the actual yield of potato (Solanum tuberosum L.) crop and selected yield status indicators (soil N, EC, pH, texture and vegetation condition), where the vegetation condition was represented by the cumulative normalized difference vegetation index... K. Al-gaadi, A.A. Hassaballa, E. Tola, R. Madugundu, A.G. Kayad

2. Employment of the SSEB and CROPWAT Models to Estimate the Water Footprint of Potato Grown in Hyper-arid Regions of Saudi Arabia

Quantifying crops’ water footprint (WF) is essential for sustainable agriculture especially in arid regions, which suffers from harsh environmental conditions and severe shortage of freshwater resources such as Saudi Arabia. In this study, WF of irrigated potato crop was estimated for the implementation of precision agriculture techniques. The CROPWAT and the Simplified Surface Energy Balance (SSEB) approaches were adopted. Soil, plant, and yield samples were randomly collected from six... R. Madugundu, K. Al-gaadi, E. Tola

3. Simultaneously Estimating Crop Biomass and Nutrient Parameters Using UAS Remote Sensing and Multitask Learning

Rapid and accurate estimation of crop growth status and nutrient levels such as aboveground biomass, nitrogen, phosphorus, and potassium concentrations and uptake is critical with respect to precision agriculture and field-based crop monitoring. Recent developments in Uncrewed Aircraft Systems (UAS) and sensor technologies have enabled the collection of high spatial, spectral, and temporal remote sensing data over large areas at a lower cost. Coupled deep learning-based modeling approaches with... P. Kovacs, M. Maimaitijiang, B. Millett, L. Dorissant, I. Acharya, U.U. Janjua, K. Dilmurat