NIR and MIR spectral feature information fusion strategy for multivariate quantitative analysis of tobacco components

• Published in: Chemometrics and intelligent laboratory systems Vol. 253; p. 105222
• Main Authors: Wang, Honghong, Wu, Qiong, Yang, Wuye, Yu, Jie, Wu, Ting, Xiong, Zhixin, Du, Yiping
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 15.10.2024
• Subjects: Mid-infrared spectroscopy; Near-infrared spectroscopy; Spectral fusion technology; Tobacco components; Wavelength selection algorithm; Spectral fusion technology; Tobacco components; Mid-infrared spectroscopy; Wavelength selection algorithm; Near-infrared spectroscopy
• ISSN: 0169-7439
• DOI: 10.1016/j.chemolab.2024.105222

The determination of total nicotine, total sugar, reducing sugar and total nitrogen contents in tobacco is of great significance to tobacco quality evaluation and formulation design. To quickly detect the content of 4 components of tobacco, using near-infrared (NIR) and mid-infrared (MIR) spectral data from 129 solid samples of tobacco powder provided by Shanghai Tobacco Group Co., Ltd., Two NIR-MIR spectral fusion techniques are studied, that is, fusion technology 1 is to establish a model by fusing feature variables after variable selection of each spectrum. The fusion technology 2 is to first fuse the NIR-MIR spectral data and then select the variables to establish the model. Both fusion technologies use successive projections algorithm (SPA), competitive adaptive reweighted sampling (CARS), backward interval PLS (biPLS), forward interval PLS (fiPLS), synergy interval PLS (siPLS), and interval interaction moving window partial least squares (iMWPLS) algorithms to filter wavelength variables. The results showed that for total nicotine and total sugar, the PLSR model established by fusion technology method 2 combined with iMWPLS algorithm is the best, and its RMSEP decreases from 0.2314 to 1.3225 to 0.0821 and 0.8079 respectively compared with the full spectrum fusion method, which is superior to the single NIR and MIR models and NIR-MIR fusion technology 1. For reducing sugars, the simple full-spectrum fusion model has the best analytical ability and the lowest RMSEP, which is superior to the single NIR-MIR models and all models established by two spectral fusion techniques combined with six wavelength selection algorithms. For total nitrogen, the prediction effect of fusion technology 1 combined with iMWPLS algorithm model was significantly improved compared with single NIR and MIR models and NIR-MIR fusion technology 2, and its RMSEP was 0.0634. The results showed that the two NIR-MIR spectral fusion techniques made full use of the complementary information provided by NIR and MIR spectroscopy, and successfully applied them to the rapid detection of total nicotine, total sugar, reducing sugar and total nitrogen content in tobacco, which provided a new method and idea for the rapid detection of tobacco components. •Combination of NIR and MIR spectroscopies to predict the tobacco components.•Using two NIR and MIR spectral feature information fusion strategies.•Comparative analysis of the results of six wavelength selection algorithms in fusion strategies.•Fusion spectroscopy combined with wavelength selection algorithm significantly improves model performance.