Evidence map›Paper›PMID 38228131›Full record

ArticleAnimal bioscience2024

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

Anjar Windarsih, Nor Kartini Abu Bakar, Abdul Rohman, Nancy Dewi Yuliana, Dachriyanus Dachriyanus

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Article in Animal bioscience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

5 authors.

Anjar WindarsihDepartment of Chemistry, Faculty of Science, Universiti Malaya, Kuala Lumpur 50603, Malaysia.
Nor Kartini Abu BakarDepartment of Chemistry, Faculty of Science, Universiti Malaya, Kuala Lumpur 50603, Malaysia.
Abdul RohmanDepartment of Pharmaceutical Chemistry, Faculty of Pharmacy, Universitas Gadjah Mada, Yogyakarta 55281, Indonesia.
Nancy Dewi YulianaDepartment of Food Science and Technology, IPB University, Bogor 16680, Indonesia.
Dachriyanus DachriyanusFaculty of Pharmacy, Andalas University, Padang 25175, Indonesia.

Funding

Universitas Gadjah Mada 1650/UN1/DITLIT/PT.01.03/2024
6 · The paper itself

Abstract

objectiveThe 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.

methodsLiquid chromatography-high resolution mass spectrometry (LC-HRMS) using untargeted approach combined with chemometrics was applied for analysis non-halal meats in BMr.

resultsThe 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 (R2>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).

conclusionA 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.

Indexed as

Beef MeatChemometricsHalal AuthenticationLC-HRMSUntargeted Metabolomics

Identifiers

PMID38228131
PMCPMC11065716

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