Back to Search Start Over

Accurate Identification and Quantification of Chinese Yam Powder Adulteration Using Laser-Induced Breakdown Spectroscopy.

Authors :
Zhao Z
Wang Q
Xu X
Chen F
Teng G
Wei K
Chen G
Cai Y
Guo L
Source :
Foods (Basel, Switzerland) [Foods] 2022 Apr 22; Vol. 11 (9). Date of Electronic Publication: 2022 Apr 22.
Publication Year :
2022

Abstract

As a popular food, Chinese yam (CY) powder is widely used for healthy and commercial purposes. Detecting adulteration of CY powder has become essential. In this work, chemometric methods combined with laser-induced breakdown spectroscopy (LIBS) were developed for identification and quantification of CY powder adulteration. Pure powders (CY, rhizome of winged yam (RY) and cassava (CS)) and adulterated powders (CY adulterated with CS) were pressed into pellets to obtain LIBS spectra for identification and quantification experiments, respectively. After variable number optimization by principal component analysis and random forest (RF), the best model random forest-support vector machine (RF-SVM) decreased 48.57% of the input variables and improved the accuracy to 100% in identification. Following the better feature extraction method RF, the Gaussian process regression (GPR) method performed the best in the prediction of the adulteration rate, with a correlation coefficient of prediction (R <subscript>p</subscript> <superscript>2</superscript> ) of 0.9570 and a root-mean-square error of prediction (RMSEP) of 7.6243%. Besides, the variable importance of metal elements analyzed by RF revealed that Na and K were significant due to the high metabolic activity and maximum metal content of CY powder, respectively. These results demonstrated that chemometric methods combined with LIBS can identify and quantify CY powder adulteration accurately.

Details

Language :
English
ISSN :
2304-8158
Volume :
11
Issue :
9
Database :
MEDLINE
Journal :
Foods (Basel, Switzerland)
Publication Type :
Academic Journal
Accession number :
35563939
Full Text :
https://doi.org/10.3390/foods11091216