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Quantitative Analysis of Al Inflour Products by Laser-Induced Breakdown Spectroscopy Combined with Partial Least Squares
Abstract
Based on partial least squares (PLS) analysis, the effects of different smoothing points and different preprocessing methods on the accuracy and precision of the PLS model were compared and analyzed. The results show that the PLS quantitative model has the best effect when using 11-point smoothing combined with standard normal variables (SNVs) as the preprocessing method. The coefficients of determination (Rc2, Rp2) of the model training set and prediction set are 0.9900 and 0.9996, respectively. The root means square errors (RMSECV, RMSEP) are 11.7 and 5.23, respectively, and the average relative error of prediction is only 2.96%, which indicates a high prediction accuracy rate and accuracy. This work demonstrates that LIBS technology has broad application prospects for the quantitative detection of specific ingredients in flour products and provides a basis for the real-time monitoring and evaluation of food safety.
Keywords
Laser-induced breakdown spectroscopy,
flour products,
quantitative analysis,
aluminum element,
partial least squares
Supporting agencies: The authors are grateful to the Jiangxi Province Education Department (No. S202110410073) for financial support.
About the Authors
Q. Ding
College of Engineering at Jiangxi Agricultural University
China
China
Nanchang
M. Yao
College of Engineering at Jiangxi Agricultural University
China
China
Nanchang
Sh. Wu
College of Engineering at Jiangxi Agricultural University
China
China
Nanchang
M. Zeng
College of Engineering at Jiangxi Agricultural University
China
China
Nanchang
N. Xue
College of Engineering at Jiangxi Agricultural University
China
China
Nanchang
D. Wu
College of Engineering at Jiangxi Agricultural University
China
China
Nanchang
J. Xu
College of Engineering at Jiangxi Agricultural University
China
China
Nanchang
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Review
For citations:
Ding Q., Yao M., Wu Sh., Zeng M., Xue N., Wu D., Xu J. Quantitative Analysis of Al Inflour Products by Laser-Induced Breakdown Spectroscopy Combined with Partial Least Squares. Zhurnal Prikladnoii Spektroskopii. 2022;89(4):548-554.
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