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Authentication of fish oil (omega-3) supplements using class-oriented chemometrics and comprehensive two-dimensional gas chromatography coupled to mass spectrometry. Anal Bioanal Chem 2022; 415:2601-2611. [PMID: 36374319 DOI: 10.1007/s00216-022-04428-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2022] [Revised: 10/31/2022] [Accepted: 11/04/2022] [Indexed: 11/16/2022]
Abstract
Food supplement authentication is an important concern worldwide due to the ascending consumption related to health benefits and its lack of effective regulation in underdeveloped countries, making it a target of fraudulent activities. In this context, this study evaluated fish oil supplements by comprehensive two-dimensional gas chromatography coupled to mass spectrometry (GC×GC-MS) to obtain fingerprints, which were used to build predictive models for automated authentication of the most popular products sold in Brazil. The authentication process relied on a one-class classifier model using data-driven soft independent modeling of class analogy (DD-SIMCA). The output of the model was a binary classifier: certified IFOS fish oils and non-certified ones - regardless of the source of adulteration. The compositional analysis showed a significant variation in the samples, which validated the need for reliable statistical models. The DD-SIMCA algorithm is still incipient in GC×GC studies, but it proved to be an excellent tool for authenticity purposes, achieving a chemometric model with a sensitivity of 100%, specificity of 98.6%, and accuracy of 99.0% for fish oil authentication. Finally, orthogonalized partial least square discriminant analysis (OPLS-DA) was used to identify the features that distinguished the groups, which ascertained the results of the DD-SIMCA model that IFOS-certified oils are positively correlated to omega-3 fatty acids, including eicosapentaenoic acid (EPA, C20:5 n-3) and docosahexaenoic acid (DHA, C22:6 n-3).
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Dirong G, Nematbakhsh S, Selamat J, Chong PP, Idris LH, Nordin N, Fatchiyah F, Abdull Razis AF. Omics-Based Analytical Approaches for Assessing Chicken Species and Breeds in Food Authentication. Molecules 2021; 26:6502. [PMID: 34770913 PMCID: PMC8587031 DOI: 10.3390/molecules26216502] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Revised: 10/04/2021] [Accepted: 10/06/2021] [Indexed: 11/07/2022] Open
Abstract
Chicken is known to be the most common meat type involved in food mislabeling and adulteration. Establishing a method to authenticate chicken content precisely and identifying chicken breeds as declared in processed food is crucial for protecting consumers' rights. Categorizing the authentication method into their respective omics disciplines, such as genomics, transcriptomics, proteomics, lipidomics, metabolomics, and glycomics, and the implementation of bioinformatics or chemometrics in data analysis can assist the researcher in improving the currently available techniques. Designing a vast range of instruments and analytical methods at the molecular level is vital for overcoming the technical drawback in discriminating chicken from other species and even within its breed. This review aims to provide insight and highlight previous and current approaches suitable for countering different circumstances in chicken authentication.
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Affiliation(s)
- Goh Dirong
- Natural Medicines and Products Research Laboratory, Institute of Bioscience, Universiti Putra Malaysia (UPM), Serdang 43400, Selangor, Malaysia;
| | - Sara Nematbakhsh
- Laboratory of Food Safety and Food Integrity, Institute of Tropical Agriculture and Food Security, Universiti Putra Malaysia (UPM), Serdang 43400, Selangor, Malaysia; (S.N.); (J.S.); (N.N.)
| | - Jinap Selamat
- Laboratory of Food Safety and Food Integrity, Institute of Tropical Agriculture and Food Security, Universiti Putra Malaysia (UPM), Serdang 43400, Selangor, Malaysia; (S.N.); (J.S.); (N.N.)
- Department of Food Science, Faculty of Food Science and Technology, Universiti Putra Malaysia (UPM), Serdang 43400, Selangor, Malaysia
| | - Pei Pei Chong
- School of Biosciences, Faculty of Health and Medical Sciences, Taylor’s University, Subang Jaya 47500, Selangor, Malaysia;
| | - Lokman Hakim Idris
- Department of Veterinary Preclinical Sciences, Faculty of Veterinary Medicine, Universiti Putra Malaysia (UPM), Serdang 43400, Selangor, Malaysia;
| | - Noordiana Nordin
- Laboratory of Food Safety and Food Integrity, Institute of Tropical Agriculture and Food Security, Universiti Putra Malaysia (UPM), Serdang 43400, Selangor, Malaysia; (S.N.); (J.S.); (N.N.)
| | - Fatchiyah Fatchiyah
- Department of Biology, Faculty of Mathematic and Natural Science, Brawijaya University, JI. Veteran, Malang 65145, Indonesia;
| | - Ahmad Faizal Abdull Razis
- Natural Medicines and Products Research Laboratory, Institute of Bioscience, Universiti Putra Malaysia (UPM), Serdang 43400, Selangor, Malaysia;
- Laboratory of Food Safety and Food Integrity, Institute of Tropical Agriculture and Food Security, Universiti Putra Malaysia (UPM), Serdang 43400, Selangor, Malaysia; (S.N.); (J.S.); (N.N.)
- Department of Food Science, Faculty of Food Science and Technology, Universiti Putra Malaysia (UPM), Serdang 43400, Selangor, Malaysia
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He Y, Bai X, Xiao Q, Liu F, Zhou L, Zhang C. Detection of adulteration in food based on nondestructive analysis techniques: a review. Crit Rev Food Sci Nutr 2020; 61:2351-2371. [PMID: 32543218 DOI: 10.1080/10408398.2020.1777526] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
Abstract
In recent years, people pay more and more attention to food quality and safety, which are significantly relating to human health. Food adulteration is a world-wide concerned issue relating to food quality and safety, and it is difficult to be detected. Modern detection techniques (high performance liquid chromatography, gas chromatography-mass spectrometer, etc.) can accurately identify the types and concentrations of adulterants in different food types. However, the characteristics as expensive, low efficient and complex sample preparation and operation limit the use of these techniques. The rapid, nondestructive and accurate detection techniques of food adulteration is of great and urgent demand. This paper introduced the principles, advantages and disadvantages of the nondestructive analysis techniques and reviewed the applications of these techniques in food adulteration screen in recent years. Differences among these techniques, differences on data interpretation and future prospects were also discussed.
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Affiliation(s)
- Yong He
- College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, Zhejiang, China.,Ministry of Agriculture and Rural Affairs, Key Laboratory of Spectroscopy Sensing, Hangzhou, Zhejiang, China
| | - Xiulin Bai
- College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, Zhejiang, China.,Ministry of Agriculture and Rural Affairs, Key Laboratory of Spectroscopy Sensing, Hangzhou, Zhejiang, China
| | - Qinlin Xiao
- College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, Zhejiang, China.,Ministry of Agriculture and Rural Affairs, Key Laboratory of Spectroscopy Sensing, Hangzhou, Zhejiang, China
| | - Fei Liu
- College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, Zhejiang, China.,Ministry of Agriculture and Rural Affairs, Key Laboratory of Spectroscopy Sensing, Hangzhou, Zhejiang, China
| | - Lei Zhou
- College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, Zhejiang, China.,Ministry of Agriculture and Rural Affairs, Key Laboratory of Spectroscopy Sensing, Hangzhou, Zhejiang, China
| | - Chu Zhang
- College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, Zhejiang, China.,Ministry of Agriculture and Rural Affairs, Key Laboratory of Spectroscopy Sensing, Hangzhou, Zhejiang, China
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Visani V, Netto JMS, Honorato RS, de Araújo MCU, Honorato FA. Screening analysis of garlic-oil capsules by infrared spectroscopy and chemometrics. Microchem J 2017. [DOI: 10.1016/j.microc.2017.04.011] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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Durbin-Watson partial least-squares regression applied to MIR data on adulteration with edible oils of different origins. Food Chem 2016; 213:791-798. [DOI: 10.1016/j.foodchem.2016.07.016] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2016] [Revised: 06/26/2016] [Accepted: 07/04/2016] [Indexed: 11/23/2022]
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Martelo-Vidal MJ, Vázquez M. Classification of red wines from controlled designation of origin by ultraviolet-visible and near-infrared spectral analysis. CIÊNCIA E TÉCNICA VITIVINÍCOLA 2014. [DOI: 10.1051/ctv/20142901035] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
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Hernández-Martínez M, Gallardo-Velázquez T, Osorio-Revilla G, Almaraz-Abarca N, Castañeda-Pérez E. Application of MIR-FTIR spectroscopy and chemometrics to the rapid prediction of fish fillet quality. CYTA - JOURNAL OF FOOD 2014. [DOI: 10.1080/19476337.2014.889213] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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Nunes CA. Vibrational spectroscopy and chemometrics to assess authenticity, adulteration and intrinsic quality parameters of edible oils and fats. Food Res Int 2014. [DOI: 10.1016/j.foodres.2013.08.041] [Citation(s) in RCA: 125] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
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