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February 23, 2026Agricultural Water ManagementOpen Access

Optimization study on diagnostic methods for winter wheat water stress using UAV-borne thermal infrared imagery

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Authors

SMShou-Chen MaZGZhen-Hao GaoJDJia-Ju Dong

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Overview

Shows improved water stress evaluation in winter wheat, indicating a need for precise irrigation strategies.

Key Points

  • The aim is to enhance the accuracy of water stress assessment in winter wheat by optimizing diagnostic methods.
  • Utilized UAV thermal infrared imagery combined with visible imagery to extract canopy temperature.
  • Applied multi-gradient extreme pixel elimination ratios for optimal temperature extraction.
  • Calculated interval-specific Crop Water Stress Index (CWSI F) and performed regression analysis.
  • Employed entropy weight method for integrating physiological indicators into a linear weighted model.
  • Extreme pixel removal improved consistency between UAV-retrieved and in-situ measured temperatures.
  • Optimal CWSI F values showed significant differences across growth stages and physiological indicators.
  • CWSI F reflected crop water status more efficiently than traditional methods.
  • Higher R² and lower nRMSE between optimal CWSI F and plant water content indicated improved diagnostic accuracy.

Cite This Study

Ma et al. (2026) studied this question.

synapsesocial.com/papers/699bee551c6c6bad5397ffachttps://doi.org/10.1016/j.agwat.2026.110242
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