Accuracy and stability improvement for meat species identification using multiplicative scatter correction and laser-induced breakdown spectroscopy

Yan Wu Chu, Shi Song Tang, Shi Xiang Ma, Yu Yang Ma, Zhong Qi Hao, Yang Min Guo, Lian Bo Guo, Yong Feng Lu, Xiao Yan Zeng

Research output: Contribution to journalArticle

17 Scopus citations

Abstract

An efficient method has been developed to identify meat species by using laser-induced breakdown spectroscopy (LIBS). To improve the accuracy and stability of meat species identification, multiplicative scatter correction (MSC) was adopted to first pretreat the spectrum for correction of spectrum scatter. Then the corrected spectra were identified by using the K-nearest neighbor (KNN) model. The results showed that the identification rate improved from 94.17% to 100% and the prediction coefficient of variance (CV) decreased from 5.16% to 0.56%. This means that the accuracy and stability of meat species identification using MSC and LIBS simultaneously improved. In light of the findings, the proposed method can be a valuable tool for meat species identification using LIBS.

Original languageEnglish (US)
Pages (from-to)10119-10127
Number of pages9
JournalOptics Express
Volume26
Issue number8
DOIs
StatePublished - Apr 16 2018

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics

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