Rapid detection of the presence, activity and concentration of microbial transglutaminase in yogurt using infrared spectroscopy combined with chemometrics

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dc.authorid0000-0002-3919-897X
dc.contributor.authorSicramaz, Hatice
dc.contributor.authorAyvaz, Huseyin
dc.contributor.authorMenevseoglu, Ahmed
dc.contributor.authorYaaqob, Mysa Ahmed Hasan Ayash
dc.contributor.authorDogan, Muhammed Ali
dc.contributor.authorOzturk, Mustafa
dc.date.accessioned2026-02-03T12:02:43Z
dc.date.available2026-02-03T12:02:43Z
dc.date.issued2025
dc.departmentÇanakkale Onsekiz Mart Üniversitesi
dc.description.abstractThe goal of this study was to develop a rapid method by using near-infrared (NIR) diffuse reflectance and midinfrared (MIR) spectroscopy to detect the use, status (active or inactive), and concentration of microbial transglutaminase (mTGase) in yogurt. Control samples were manufactured without mTGase. Two different levels of mTGase concentration were employed: 1 and 2 units. Half of the enzyme-added samples were inactivated after yogurt manufacture to detect the active/inactive status of mTGase. Both for NIR and MIR, analyzed via the soft independent modeling of class analogy (SIMCA) and Partial Least Squares Discriminant Analysis (PLS-DA) approaches were able to classify the control sample from active mTGase-containing yogurts and enzyme status, but could not differentiate enzyme concentrations. Machine learning effectively determined mTGase presence, activity, and concentrations. In conclusion, NIR and MIR spectroscopy, combined with chemometric methods, successfully detected mTGase in yogurt, with machine learning outperforming SIMCA and PLS-DA in identifying enzyme levels.
dc.identifier.doi10.1016/j.ifset.2025.104225
dc.identifier.issn1466-8564
dc.identifier.issn1878-5522
dc.identifier.scopus2-s2.0-105015442286
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.1016/j.ifset.2025.104225
dc.identifier.urihttps://hdl.handle.net/20.500.12428/34848
dc.identifier.volume105
dc.identifier.wosWOS:001582732100001
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherElsevier Sci Ltd
dc.relation.ispartofInnovative Food Science & Emerging Technologies
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WOS_20260130
dc.subjectCross-linking
dc.subjectDairy
dc.subjectAcid gels
dc.subjectSIMCA
dc.subjectMachine learning
dc.titleRapid detection of the presence, activity and concentration of microbial transglutaminase in yogurt using infrared spectroscopy combined with chemometrics
dc.typeArticle

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