Chinese Journal of Agrometeorology ›› 2022, Vol. 43 ›› Issue (02): 137-147.doi: 10.3969/j.issn.1000-6362.2022.02.005

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Hyperspectral Estimation of Chlorophyll Content in Winter Wheat Leaves under Low Temperature Stress

LI Wei-yi,SUN Ming-xin,ZENG Feng-ling,WANG Feng-wen   

  1. College of Resources and Environment,Anhui Agricultural University,Hefei 230036, China
  • Received:2021-07-03 Online:2022-02-20 Published:2022-01-15

Abstract: For real-time monitoring of chlorophyll content in wheat under low temperature adversity, leaf spectral reflectance and SPAD (Soil and Plant Analyzer Development, SPAD) values were measured in 12 varieties of winter wheat at the seedling stage using a cold wave cooling process. Observations on December 28, 2020 (maximum/minimum temperature of 15℃/3℃) were used as pre-stress data, and observations on December 31 (maximum/minimum temperature of 1℃/−9℃) were used as post-low temperature stress data to analyze the patterns of changes in the raw spectra and SPAD values of wheat leaves before and after low temperature stress. The inverse model of chlorophyll content of wheat leaves before and after low-temperature stress was developed using the original spectral data, first-order spectral derivatives and three vegetation indices as independent variables and cross-validated, respectively. The results showed that: (1) compared with the pre-stress period, the overall SPAD of wheat leaves showed an increasing trend after low temperature stress, the spectral reflectance decreased in the visible light region where chlorophyll absorption was better, and the leaves showed freezing characteristics. (2) The accuracy of the two hybrid models constructed before and after low temperature stress was poor after cross-validation, indicating that the model for estimating chlorophyll content of wheat at room temperature was not applicable to the estimation of chlorophyll content of wheat after low temperature stress. (3) Among the hybrid models constructed using spectral data for the inversion of chlorophyll content in winter wheat under low temperature stress, the model with the first-order spectral derivative at 694 nm was the most effective, with an R2 of 0.694 and a RMSE of 3.191, indicating that the use of the characteristic spectral bands of wheat leaves for the estimation of chlorophyll content under low temperature stress was the most effective. The results can be used as a reference for non-destructive monitoring of chlorophyll content in multiple varieties of winter wheat.

Key words: Winter wheat, Low temperature stress, Hyper-spectrum, Chlorophyll content, Inverse model