偏最小二乘回归
规范化(社会学)
数学
特征选择
统计
主成分分析
模式识别(心理学)
人工智能
计算机科学
社会学
人类学
作者
Kai Wei,Geer Teng,Qianqian Wang,Xiangjun Xu,Zhifang Zhao,Haida Liu,Mengyu Bao,Yongyue Zheng,Tianzhong Luo,Bingheng Lu
出处
期刊:Foods
[Multidisciplinary Digital Publishing Institute]
日期:2023-04-20
卷期号:12 (8): 1710-1710
被引量:19
标识
DOI:10.3390/foods12081710
摘要
Fritillaria has a long history in China, and it can be consumed as medicine and food. Owing to the high cost of Fritillaria cirrhosa, traders sometimes mix it with the cheaper Fritillaria thunbergii powder to make profit. Herein, we proposed a laser-induced breakdown spectroscopy (LIBS) technique to test the adulteration present in the sample of Fritillaria cirrhosa powder. Experimental samples with different adulteration levels were prepared, and their LIBS spectra were obtained. Partial least squares regression (PLSR) was adopted as the quantitative analysis model to compare the effects of four data standardization methods, namely, mean centring, normalization by total area, standard normal variable, and normalization by the maximum, on the performance of the PLSR model. Principal component analysis and least absolute shrinkage and selection operator (LASSO) were utilized for feature extraction and feature selection, and the performance of the PLSR model was determined based on its quantitative analysis. Subsequently, the optimal number of features was determined. The residuals were corrected using support vector regression (SVR). The mean absolute error and root mean square error of prediction obtained from the quantitative analysis results of the combined LASSO-PLSR-SVR model for the test set data were 5.0396% and 7.2491%, respectively, and the coefficient of determination R2 was 0.9983. The results showed that the LIBS technique can be adopted to test adulteration in the sample of Fritillaria cirrhosa powder and has potential applications in drug quality control.
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