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Bayesian Fusion Model Enhanced Codfish Classification Using Near Infrared and Raman Spectrum

文献类型： 外文期刊

作者： Xu, Yi 1 ; Koidis, Anastasios 4 ; Tian, Xingguo 1 ; Xu, Sai 5 ; Xu, Xiaoyan 1 ; Wei, Xiaoqun 1 ; Jiang, Aimin 1 ; Lei, Hongtao 1 ;

作者机构： 1.South China Agr Univ, Coll Food Sci, Nation Local Joint Engn Res Ctr Precis Machining &, Guangdong Prov Key Lab Food Qual & Safety, Guangzhou 510642, Peoples R China

2.Coll Light Ind & Engn, Sichuan Technol & Business Coll, Chengdu 611800, Peoples R China

3.Guangdong Lab Lingnan Modern Agr, Guangzhou 510642, Peoples R China

4.Queens Univ Belfast, Inst Global Food Secur, 19 Chlorine Gardens, Belfast BT9 5DJ, North Ireland

5.Guangdong Acad Agr Sci, Publ Monitoring Ctr Agr Prod, Guangzhou 510642, Peoples R China

关键词： codfish; authenticity; Raman spectrum; near infrared spectrum; Bayes information fusion

期刊名称：FOODS （ 影响因子：5.561； 五年影响因子：5.94 ）

ISSN：

年卷期： 2022 年 11 卷 24 期

页码：

收录情况： SCI

摘要： In this study, a Bayesian-based decision fusion technique was developed for the first time to quickly and non-destructively identify codfish using near infrared (NIRS) and Raman spectroscopy (RS). NIRS and RS spectra from 320 codfish samples were collected, and separate partial least squares discriminant analysis (PLS-DA) models were developed to establish the relationship between the raw data and cod identity for each spectral technique. Three decision fusion methods: decision fusion, data layer or feature layer, were tested and compared. The decision fusion model based on the Bayesian algorithm (NIRS-RS-B) was developed on the optimal discrimination features of NIRS and RS data (NIRS-RS) extracted by the PLS-DA method whereas the other fusion models followed conventional, non-Bayesian approaches. The Bayesian model showed enhanced classification metrics (92% sensitivity, 98% specificity, 98% accuracy) that were significantly superior to those demonstrated by any of other two spectroscopic methods (NIRS, RS) and the two data fusion methods (data layer fused, NIRS-RS-D, or feature layer fused, NIRS-RS-F). This novel proposed approach can provide an alternative classification for codfish and potentially other food speciation cases.

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