Sidike et al. (2026) Three-Dimensional Optimized Spectral Indices for Leaf Water Content Assessment in Arid Oasis Fruit Orchards

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Identification

• Journal: Forests
• Year: 2026
• Date: 2026-09-18
• Authors: Ainiwaer Sidike, Mamat Sawut, Jiaxi Liang, Reheman Rouzi, Weichen Tian, Shanshan Liu
• DOI: 10.3390/f17091113

Research Groups

• Institute of Agricultural Engineering, Chinese Academy of Agricultural Sciences (CAAS)
• College of Information Science and Technology, China Agricultural University (CAU)

Short Summary

This study developed a machine learning-based approach to estimate leaf water content (LWC) in fruit orchards using unmanned aerial vehicle (UAV) multispectral imagery. The optimal model achieved high accuracy with a coefficient of determination (R2) of 0.90-0.94.

Objective

• Investigate the relationship between spectral indices and LWC, and develop an accurate estimation model for LWC in fruit orchards.

Study Configuration

• Spatial Scale: Field scale, focusing on individual fruit tree species.
• Temporal Scale: A single growing season was studied to capture seasonal variations in LWC.

Methodology and Data

• Models used: Random Forest Regression (RFR), Support Vector Regression (SVR), Quantile Polynomial Regression (QPR)
• Data sources: UAV multispectral imagery, leaf water content measurements

Main Results

• The three-band spectral indices TBI1 and TBI8 exhibited higher correlations with LWC than two-band indices.
• The RFR algorithm-based model using the TBI1 spectral index achieved the best performance (R2 = 0.90-0.94, RMSE = 3.18%-3.69%).

Contributions

• This study provides a novel approach to estimating LWC in fruit orchards using UAV multispectral imagery and machine learning algorithms.
• The results highlight the potential of three-band spectral indices and RFR algorithm-based models for improving LWC estimation accuracy.

Funding

• National Key Research and Development Program of China (2018YFD0200300)
• Chinese Academy of Agricultural Sciences (CAAS) Youth Innovation Fund (2021XQ-15)

Citation

@article{Sidike2026ThreeDimensional,
  author = {Sidike, Ainiwaer and Sawut, Mamat and Liang, Jiaxi and Rouzi, Reheman and Tian, Weichen and Liu, Shanshan},
  title = {Three-Dimensional Optimized Spectral Indices for Leaf Water Content Assessment in Arid Oasis Fruit Orchards},
  journal = {Forests},
  year = {2026},
  doi = {10.3390/f17091113},
  url = {https://doi.org/10.3390/f17091113}
}