基于最优光谱指数的大豆叶片叶绿素含量反演模型研究

doi:10.3964/j.issn.1000-0593(2021)06-1912-08

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Abstract The accurate acquisition and prediction of chlorophyll content can provide a theoretical basis for precise management of crop planting. Optimal spectral index was used to establish the soybean chlorophyll content inversion model in this paper. The hyperspectral and chlorophyll content data of soybean flower bud differentiation were obtained. Firstly, seven typical spectral indices related to chlorophyll content were constructed, namely ratio index (RI), difference index (DI), normalized difference vegetation index (NDVI), modified simple ratio index (mSR), modified normalized difference index (mNDI), soil-adjusted vegetation index (SAVI) and triangular vegetation index (TVI), respectively. First derivative (FD) processing was performed on the original hyper spectrum, and then the original and first derivative hyper spectrum are combined with all wavelengths in the full spectrum wavelength range to calculate 14 spectral indices. Then use the correlation matrix method to select the optimal spectral index. The correlation analysis was conducted between the spectral index calculated by all wavelength combinations and chlorophyll content. The maximum value of the correlation coefficient was taken as the index to extract the 14 optimal wavelength combinations, and the corresponding spectral index value was calculated as the optimal spectral index. Finally, the optimal spectral indices were divided into three groups as model input variables combined with the three methods of Partial least squares regression (PLS), Least squares support vector machine regression (LSSVM), and LASSO regression to model, then compare and analyze the results. The coefficients of determination R²_c, R²_p and the root mean square error RMSEC and RMSEP as model evaluation indicators, then soybean chlorophyll content inversion model with the highest accuracy, were finally selected. The results show that the 14 optimal spectral index wavelength combinations are RI (728, 727), DI (735, 732), NDVI (728, 727), mSR (728, 727), mNDI (728, 727), SAVI (728, 727), TVI (1 007, 708), FDRI (727, 708), FDDI (727, 788), FDNDVI (726, 705), FDmSR (726, 705), FDmNDI (726, 705), FDSAVI (727, 788) and FDTVI (760, 698), the maximum correlation coefficient with chlorophyll content are all greater than 0.8. The method to establish the optimal chlorophyll inversion model was the LSSVM modeling method combined with the first derivative spectral index (combination 2). The R²_c=0.751 8, R²_p=0.836 0, RMSEC=1.361 2, RMSEP=1.220 4, indicating that the model had high accuracy and could provide a reference for monitoring the growth status of soybean in a large area.

Key words：Soybean; Optimal spectral index; Chlorophyll content; Inversion model

Received: 2020-07-24 Accepted: 2020-10-16

ZTFLH:

S565.1

Corresponding Authors: SUI Yuan-yuan E-mail: suiyuan@jlu.edu.cn

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https://www.gpxygpfx.com/EN/10.3964/j.issn.1000-0593(2021)06-1912-08 OR https://www.gpxygpfx.com/EN/Y2021/V41/I06/1912