Untargeted metabolomics using liquid chromatography-high resolution mass spectrometry and chemometrics for analysis of non-halal meats adulteration in beef meat

被引:1
|
作者
Windarsih, Anjar [1 ,2 ]
Abu Bakar, Nor Kartini [1 ]
Rohman, Abdul [3 ,4 ]
Yuliana, Nancy Dewi [5 ]
Dachriyanus, Dachriyanus [6 ]
机构
[1] Univ Malaya, Fac Sci, Dept Chem, Kuala Lumpur 50603, Malaysia
[2] Natl Res & Innovat Agcy BRIN, Res Ctr Food Technol & Proc PRTPP, Yogyakarta 55861, Indonesia
[3] Univ Gadjah Mada, Fac Pharm, Dept Pharmaceut Chem, Yogyakarta 55281, Indonesia
[4] Univ Gadjah Mada, Inst Halal Ind & Syst PUIPT IHIS, Ctr Excellence, Yogyakarta 55281, Indonesia
[5] IPB Univ, Dept Food Sci & Technol, Bogor 16680, Indonesia
[6] Andalas Univ, Fac Pharm, Padang 25175, Indonesia
关键词
Beef Meat; Chemometrics; Halal Authentication; LC-HRMS; Untargeted Metabolomics; FTIR SPECTROSCOPY;
D O I
10.5713/ab.23.0238
中图分类号
S8 [畜牧、 动物医学、狩猎、蚕、蜂];
学科分类号
0905 ;
摘要
Objective: The adulteration of raw beef (BMr) with dog meat (DMr) and pork (PMr) becomes a serious problem because it is associated with halal status, quality, and safety of meats. This research aimed to develop an effective authentication method to detect non -halal meats (dog meat and pork) in beef using metabolomics approach. Methods: Liquid chromatography -high resolution mass spectrometry (LC-HRMS) using untargeted approach combined with chemometrics was applied for analysis non -halal meats in BMr. Results: The untargeted metabolomics approach successfully identified various metabolites in BMr DMr, PMr, and their mixtures. The discrimination and classification between authentic BMr and those adulterated with DMr and PMr were successfully determined using partial least square -discriminant analysis (PLS-DA) with high accuracy. All BMr samples containing non -halal meats could be differentiated from authentic BMr. A number of discriminating metabolites with potential as biomarkers to discriminate BMr in the mixtures with DMr and PMr could be identified from the analysis of variable importance for projection value. Partial least square (PLS) and orthogonal PLS (OPLS) regression using discriminating metabolites showed high accuracy (R 2 >0.990) and high precision (both RMSEC and RMSEE <5%) in predicting the concentration of DMr and PMr present in beef indicating that the discriminating metabolites were good predictors. The developed untargeted LC-HRMS metabolomics and chemometrics successfully identified non -halal meats adulteration (DMr and PMr) in beef with high sensitivity up to 0.1% (w/w). Conclusion: A combination of LC-HRMS untargeted metabolomic and chemometrics promises to be an effective analytical technique for halal authenticity testing of meats. This method could be further standardized and proposed as a method for halal authentication of meats.
引用
收藏
页码:918 / 928
页数:11
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