A review on proteomic and genomic biomarkers for gelatin source authentication: Challenges and future outlook

Garcia-Vaquero, Marco; Mirzapour‐Kouhdasht, Armin

doi:10.1016/j.heliyon.2023.e16621

Cited by 9 publications

(2 citation statements)

References 99 publications

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“…Since most skin gelatines originate from porcine and bovine (Rather et al, 2022), some gelatine manufacturers commit food fraud via fraudulent adulteration, substitution and mislabeling of the source (Zia et al, 2020) due to the high demand and escalated cost to produce gelatine from various sources. This action was evident in previously reported food fraud on marshmallows, gumdrops, and Turkish delights containing declared halal gelatine (Garcia-Vaquero & Mirzapour-Kouhdasht, 2023). It could undermine the customers' right to consume gelatine-based products, especially for populations with certain religious beliefs.…”

Section: Introductionmentioning

confidence: 99%

Incorporation of Partial Least Squares-Discriminant Analysis with Ultra-High-Performance Liquid Chromatography Diode-Array Detector for Authentication of Skin Gelatine Sources

Abdullah Sani,

Mohd Ismail,

Azid

et al. 2024

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This research seeks to (1) authenticate sources of skin gelatine by combining putative 17 aminoacids (AAs) analysis with chemometrics by Ultra-High-Performance Liquid ChromatographyDiode-Array Detector (UHPLC-DAD) and (2) create AA profiles in skin gelatines. Theclassification capability of partial least square-discriminant analysis (PLS-DA) models wasassessed to determine the most effective discriminant model. Principal component analysis(PCA) with quartimax rotation was utilised to accurately organise gelatine clusters and assign thesignificantly contributing AAs to each cluster. The PLS-DA model with 13 AAs (PLS-DAVIPAA)outperformed the PLS-DA model with 17 AAs (PLS-DAAA) because its R2Y (0.938), R2X (0.881),and Q2 (0.929) values were greater. With 13 significant AAs, the PLS-DAVIPAA model obtainedcluster classification accuracy of 100% on training and cross-validation datasets and 93.3% ontesting and verification datasets. The chemical structure of gelatines may shed light on theinteractions between AAs. Following six quartimax rotations, the gelatines were groupedcorrectly. The PCA showed the dominant presence of these AAs: L-Valine, L-Phenylalanine andL-Tyrosine in porcine gelatine; Glycine, L-Threonine, L-Arginine, L-Methionine, L-Histidine andL-Serine in fish gelatine; and L-Hydroxyproline, L-Leucine and L-Proline in bovine gelatine. Theauthority could use this technique to set a standard for authenticating skin gelatine samples.

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Section: Introductionmentioning

confidence: 99%

Incorporation of Partial Least Squares-Discriminant Analysis with Ultra-High-Performance Liquid Chromatography Diode-Array Detector for Authentication of Skin Gelatine Sources

Abdullah Sani,

Mohd Ismail,

Azid

et al. 2024

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“…One of the contaminations of non-halal materials comes from pork products in meat products and their derivatives. Pork fat can be identified through DNA analysis using polymerase chain reaction (PCR), DNA barcoding, loop-mediated isothermal amplification (LAMP), and biosensor method [5], [6]. The DNA method is reported as capable of accurately detecting pork DNA,…”

Section: Introductionmentioning

confidence: 99%

Identification of Fat in Pork Using Fourier Transform Infrared Spectrum and GC-MS

Yulirohyami,

Maulidatunnisa,

Pusparani

et al. 2023

Ind. J. Chem. Anal

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Halal food safety issues receive serious attention. Methods for analyzing contamination of non-halal ingredients, such as lard, must be developed to assist in the halal authentication process for food. This study was conducted to compare the fat profile of pork thighs using FT-IR and GC-MS. The pork is dried in the oven and then extracted using n-hexane. The resulting fat was characterized by FT-IR. Determination of fatty acids was carried out by GC-MS using a derivatization technique. Based on the results of the study showed that the infrared pattern of lard can be identified from the difference in absorption intensity. Pork fat has a higher unsaturated fatty acid content than beef and chicken. Infrared spectra can confirm the presence of -C=C- bonds at 3005, 1745, 1116, 1550, and 722 cm-1. The FTIR data shows that there are larger unsaturated fatty acid groups in pork fat than in beef and chicken fat. This procedure is a non-destructive method that can be carried out quickly, and cheaply, and can be developed into a routine procedure for halal authentication of food. Based on the results of unsaturated fatty acid testing with GC-MS it can show the content of oleic acid (C18:1) contained in pork. The results of mapping the content of free fatty acids in pork can be used to complete halal authentication data easily and quickly.

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A review of microbial responses to biochar addition in anaerobic digestion system: Community, cellular and genetic level findings

Zhao,

Hu,

et al. 2024

Bioresource Technology

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A review on proteomic and genomic biomarkers for gelatin source authentication: Challenges and future outlook

Cited by 9 publications

References 99 publications

Incorporation of Partial Least Squares-Discriminant Analysis with Ultra-High-Performance Liquid Chromatography Diode-Array Detector for Authentication of Skin Gelatine Sources

Incorporation of Partial Least Squares-Discriminant Analysis with Ultra-High-Performance Liquid Chromatography Diode-Array Detector for Authentication of Skin Gelatine Sources

Identification of Fat in Pork Using Fourier Transform Infrared Spectrum and GC-MS

A review of microbial responses to biochar addition in anaerobic digestion system: Community, cellular and genetic level findings

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