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Estimation of water content in corn leaves using hyperspectral data based on fractional order Savitzky-Golay derivation coupled with wavelength selection
High throughput phenotyping of canopy water mass and canopy temperature in well-watered and drought stressed tropical maize hybrids in the vegetative stage
Evaluation of different water absorption bands, indices and multivariate models for water-deficit stress monitoring in rice using visible-near infrared spectroscopy
Investigating the impacts of different degrees of deficit irrigation and nitrogen interactions on assimilate translocation, yield, and resource use efficiencies in winter wheat
A new approach for estimating the three-dimensional spatiotemporal distribution of wheat canopy water content based on multi-source data and machine learning
An interpretable machine learning framework to predict Relative Water Content by using hyperspectral data in Phaseolus vulgaris L. under different irrigation conditions
A Machine Learning Approach to Monitor the Physiological and Water Status of an Irrigated Peach Orchard under Semi-Arid Conditions by Using Multispectral Satellite Data
Additional file 1 of Improving the prediction performance of leaf water content by coupling multi-source data with machine learning in rice (Oryza sativa L.)
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