Evaluation of water status of wheat genotypes to aid prediction of yield on sodic soils using UAV-thermal imaging and machine learningSumanta Das, Yash P. Dang, Neal W. Menzies et al.|Agricultural and Forest Meteorology|2021Cited by 63
Improving Biomass and Grain Yield Prediction of Wheat Genotypes on Sodic Soil Using Integrated High-Resolution Multispectral, Hyperspectral, 3D Point Cloud, and Machine Learning TechniquesMalini Roy Choudhury, Yash P. Dang, Sumanta Das et al.|Remote Sensing|2021Cited by 55
UAV-Thermal imaging and agglomerative hierarchical clustering techniques to evaluate and rank physiological performance of wheat genotypes on sodic soilSumanta Das, Yash P. Dang, Jack Christopher et al.|ISPRS Journal of Photogrammetry and Remote Sensing|2021Cited by 44
UAV-thermal imaging: A technological breakthrough for monitoring and quantifying crop abiotic stress to help sustain productivity on sodic soils – A case review on wheatSumanta Das, Yash P. Dang, Scott Chapman et al.|Remote Sensing Applications Society and Environment|2021Cited by 40
Detection of calcium, magnesium, and chlorophyll variations of wheat genotypes on sodic soils using hyperspectral red edge parametersMalini Roy Choudhury, Yash P. Dang, Jack Christopher et al.|Environmental Technology & Innovation|2022Cited by 32