Combining the fractional order derivative and machine learning for leaf water content estimation of spring wheat using hyper-spectral indices.

Specifically, the NDVI and RVI calculated at orders 0–0.8 showed a decreasing trend followed by an increasing trend in the correlation coefficient of LWC and displayed the highest correlation at order 0.8, with absolute correlation coefficients of 0.68 and 0.71, respectively.

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The reflectance changed due to the difference in leaf water content, and a decreasing trend was observed in spectral reflectance with an increase in leaf water content.

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