Abstract

Variable (or wavelength) selection plays an important role in the quantitative analysis of near-infrared (NIR) spectra. A method based on a genetic algorithm interval partial least squares regression (GA<i>i</i>PLS) combined successive projections algorithm (SPA) was proposed for variable selection in NIR spectroscopy. GA<i>i</i>PLS was used to select informative interval regions among the spectrum, and then SPA was employed to select the most informative variables and to minimize collinearity between those variables in the model. The performance of the proposed method was compared with the full-spectrum model, conventional interval partial least squares regression (<i>i</i>PLS), and backward interval partial least squares regression (B<i>i</i>PLS) for modeling the NIR data sets of pigments in cucumber leaf samples. The multiple linear regression (MLR) model was obtained with eight variables for chlorophylls and five variables for carotenoids selected by SPA. When the SPA model was applied to the prediction of the validation set, the correlation coefficients of the predicted value by MLR and the measured value for the validation data set (<i>r</i>_p) of chlorophylls and carotenoids were 0.917 and 0.932, respectively. Results show that the proposed method was able to select important wavelengths from the NIR spectra and makes the prediction more robust and accurate in quantitative analysis.

Rapid detection of talc content in flour based on near-infrared spectroscopy combined with feature wavelength selection

Changhao Bao, Changhao Zeng, Jinming Liu, and Dongjie Zhang
Appl. Opt. 61(19) 5790-5798 (2022)

High accuracy determination of copper in copper concentrate with double genetic algorithm and partial least square in laser-induced breakdown spectroscopy

Haochen Li, Meizhen Huang, and Huidi Xu
Opt. Express 28(2) 2142-2155 (2020)

Rapid detection of carbon-nitrogen ratio for anaerobic fermentation feedstocks using near-infrared spectroscopy combined with BiPLS and GSA

Jinming Liu, Nan Li, Feng Zhen, Yonghua Xu, Wenzhe Li, and Yong Sun
Appl. Opt. 58(18) 5090-5097 (2019)

Nondestructive detection model of soluble solids content of an apple using visible/near-infrared spectroscopy combined with CARS and MPGA

Yong Chen, Chaoyuan Cui, and Yun Wu
Appl. Opt. 60(27) 8400-8407 (2021)

Rapid determination of the main components of corn based on near-infrared spectroscopy and a BiPLS-PCA-ELM model

Lili Xu, Jinming Liu, Chunqi Wang, Zhijiang Li, and Dongjie Zhang
Appl. Opt. 62(11) 2756-2765 (2023)