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Detection of Pork in Beef Meatballs Using LC-HRMS Based Untargeted Metabolomics and Chemometrics for Halal Authentication.
Molecules. 2022 Nov 29; 27(23)M

Abstract

Adulteration of high-quality meat products using lower-priced meats, such as pork, is a crucial issue that could harm consumers. The consumption of pork is strictly forbidden in certain religions, such as Islam and Judaism. Therefore, the objective of this research was to develop untargeted metabolomics using liquid chromatography-high resolution mass spectrometry (LC-HRMS) combined with chemometrics for analysis of pork in beef meatballs for halal authentication. We investigated the use of non-targeted LC-HRMS as a method to detect such food adulteration. As a proof of concept using six technical replicates of pooled samples from beef and pork meat, we could show that metabolomics using LC-HRMS could be used for high-throughput screening of metabolites in meatballs made from beef and pork. Chemometrics of principal component analysis (PCA) was successfully used to differentiate beef meatballs and pork meatball samples. Partial least square-discriminant analysis (PLS-DA) clearly discriminated between halal and non-halal beef meatball samples with 100% accuracy. Orthogonal projection to latent structures-discriminant analysis (OPLS-DA) perfectly discriminated and classified meatballs made from beef, pork, and a mixture of beef-pork with a good level of fitness (R2X = 0.88, R2Y = 0.71) and good predictivity (Q2 = 0.55). Partial least square (PLS) and orthogonal PLS (OPLS) were successfully applied to predict the concentration of pork present in beef meatballs with high accuracy (R2 = 0.99) and high precision. Thirty-five potential metabolite markers were identified through VIP (variable important for projections) analysis. Metabolites of 1-(1Z-hexadecenyl)-sn-glycero-3-phosphocholine, acetyl-l-carnitine, dl-carnitine, anserine, hypoxanthine, linoleic acid, and prolylleucine had important roles for predicting pork in beef meatballs through S-line plot analysis. It can be concluded that a combination of untargeted metabolomics using LC-HRMS and chemometrics is promising to be developed as a standard analytical method for halal authentication of highly processed meat products.

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Authors+Show Affiliations

Windarsih A
Department of Chemistry, Faculty of Science, Universiti Malaya, Kuala Lumpur 50603, Malaysia. Research Center for Food Technology and Processing (PRTPP), National Research and Innovation Agency (BRIN), Yogyakarta 55861, Indonesia.
Riswanto FDO
Division of Pharmaceutical Analysis and Medicinal Chemistry, Faculty of Pharmacy, Campus III Paingan, Universitas Sanata Dharma, Yogyakarta 55282, Indonesia.
Bakar NKA
Department of Chemistry, Faculty of Science, Universiti Malaya, Kuala Lumpur 50603, Malaysia.
Yuliana ND
Department of Food Science and Technology, IPB University, Bogor 16680, Indonesia.
Dachriyanus
Faculty of Pharmacy, Andalas University, Padang 25175, Indonesia.
Rohman A
Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Universitas Gadjah Mada, Yogyakarta 55281, Indonesia. Center of Excellence, Institute for Halal Industry and Systems (PUI-PT IHIS), Universitas Gadjah Mada, Yogyakarta 55281, Indonesia.

MeSH

CattleAnimalsSwineRed MeatMeat ProductsMeatMass SpectrometryMetabolomicsChromatography, Liquid

Pub Type(s)

Journal Article

Language

eng

PubMed ID

36500423

Citation

Windarsih, Anjar, et al. "Detection of Pork in Beef Meatballs Using LC-HRMS Based Untargeted Metabolomics and Chemometrics for Halal Authentication." Molecules (Basel, Switzerland), vol. 27, no. 23, 2022.
Windarsih A, Riswanto FDO, Bakar NKA, et al. Detection of Pork in Beef Meatballs Using LC-HRMS Based Untargeted Metabolomics and Chemometrics for Halal Authentication. Molecules. 2022;27(23).
Windarsih, A., Riswanto, F. D. O., Bakar, N. K. A., Yuliana, N. D., Dachriyanus, ., & Rohman, A. (2022). Detection of Pork in Beef Meatballs Using LC-HRMS Based Untargeted Metabolomics and Chemometrics for Halal Authentication. Molecules (Basel, Switzerland), 27(23). https://doi.org/10.3390/molecules27238325
Windarsih A, et al. Detection of Pork in Beef Meatballs Using LC-HRMS Based Untargeted Metabolomics and Chemometrics for Halal Authentication. Molecules. 2022 Nov 29;27(23) PubMed PMID: 36500423.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Detection of Pork in Beef Meatballs Using LC-HRMS Based Untargeted Metabolomics and Chemometrics for Halal Authentication. AU - Windarsih,Anjar, AU - Riswanto,Florentinus Dika Octa, AU - Bakar,Nor Kartini Abu, AU - Yuliana,Nancy Dewi, AU - Dachriyanus,, AU - Rohman,Abdul, Y1 - 2022/11/29/ PY - 2022/10/02/received PY - 2022/11/18/revised PY - 2022/11/24/accepted PY - 2022/12/11/entrez PY - 2022/12/12/pubmed PY - 2022/12/15/medline KW - beef meatballs KW - chemometrics KW - halal authentication KW - pork KW - untargeted metabolomics JF - Molecules (Basel, Switzerland) JO - Molecules VL - 27 IS - 23 N2 - Adulteration of high-quality meat products using lower-priced meats, such as pork, is a crucial issue that could harm consumers. The consumption of pork is strictly forbidden in certain religions, such as Islam and Judaism. Therefore, the objective of this research was to develop untargeted metabolomics using liquid chromatography-high resolution mass spectrometry (LC-HRMS) combined with chemometrics for analysis of pork in beef meatballs for halal authentication. We investigated the use of non-targeted LC-HRMS as a method to detect such food adulteration. As a proof of concept using six technical replicates of pooled samples from beef and pork meat, we could show that metabolomics using LC-HRMS could be used for high-throughput screening of metabolites in meatballs made from beef and pork. Chemometrics of principal component analysis (PCA) was successfully used to differentiate beef meatballs and pork meatball samples. Partial least square-discriminant analysis (PLS-DA) clearly discriminated between halal and non-halal beef meatball samples with 100% accuracy. Orthogonal projection to latent structures-discriminant analysis (OPLS-DA) perfectly discriminated and classified meatballs made from beef, pork, and a mixture of beef-pork with a good level of fitness (R2X = 0.88, R2Y = 0.71) and good predictivity (Q2 = 0.55). Partial least square (PLS) and orthogonal PLS (OPLS) were successfully applied to predict the concentration of pork present in beef meatballs with high accuracy (R2 = 0.99) and high precision. Thirty-five potential metabolite markers were identified through VIP (variable important for projections) analysis. Metabolites of 1-(1Z-hexadecenyl)-sn-glycero-3-phosphocholine, acetyl-l-carnitine, dl-carnitine, anserine, hypoxanthine, linoleic acid, and prolylleucine had important roles for predicting pork in beef meatballs through S-line plot analysis. It can be concluded that a combination of untargeted metabolomics using LC-HRMS and chemometrics is promising to be developed as a standard analytical method for halal authentication of highly processed meat products. SN - 1420-3049 UR - https://www.unboundmedicine.com/medline/citation/36500423/Detection_of_Pork_in_Beef_Meatballs_Using_LC_HRMS_Based_Untargeted_Metabolomics_and_Chemometrics_for_Halal_Authentication_ DB - PRIME DP - Unbound Medicine ER -