Infrared spectroscopy combined with chemometrics as a convenient method to detect adulterations in cooking/stretching process in commercial cheese
dc.authorid | DOGAN, Muhammed Ali/0000-0002-5524-7567 | |
dc.authorid | Ayvaz, Huseyin/0000-0001-9705-6921 | |
dc.authorid | Ozturk, Mustafa/0000-0002-3919-897X | |
dc.authorid | MENEVSEOGLU, AHMED/0000-0003-2454-7898 | |
dc.contributor.author | Ozturk, Mustafa | |
dc.contributor.author | Dogan, Muhammed Ali | |
dc.contributor.author | Menevseoglu, Ahmed | |
dc.contributor.author | Ayvaz, Huseyin | |
dc.date.accessioned | 2025-01-27T20:31:23Z | |
dc.date.available | 2025-01-27T20:31:23Z | |
dc.date.issued | 2022 | |
dc.department | Çanakkale Onsekiz Mart Üniversitesi | |
dc.description.abstract | Stretching and kneading of the curd during fresh Kashar cheese manufacturing must take place in hot water; dry cooking/stretching of the curd with the assistance of emulsifying salts is not allowed. However, some producers in recent years tend to label their processed cheese as Kashar cheese resulting in unfair economic gain and consumer deception. Near-infrared (NIR) diffuse reflectance and mid-infrared (MIR) attenuated total reflectance (ATR) spectroscopy were assessed for the fast and convenient identification of these two types of cheese. Soft independent modeling of class analogy (SIMCA) models of both NIR and MIR-ATR spectra were developed; the latter gave superior separation due to the greater inter-class distance originating from better-resolved peaks associated with phosphates (6.7 for MIR-ATR versus 3.2 for NIR). Information Theory determined two and three variables were enough for MIR and NIR spectral data classification, respectively; quadratic discriminant and support vector machine provided 100% accuracy for class prediction. (C) 2021 Published by Elsevier Ltd. | |
dc.identifier.doi | 10.1016/j.idairyj.2021.105312 | |
dc.identifier.issn | 0958-6946 | |
dc.identifier.issn | 1879-0143 | |
dc.identifier.scopus | 2-s2.0-85124267716 | |
dc.identifier.scopusquality | Q1 | |
dc.identifier.uri | https://doi.org/10.1016/j.idairyj.2021.105312 | |
dc.identifier.uri | https://hdl.handle.net/20.500.12428/23123 | |
dc.identifier.volume | 128 | |
dc.identifier.wos | WOS:000819670700004 | |
dc.identifier.wosquality | Q2 | |
dc.indekslendigikaynak | Web of Science | |
dc.indekslendigikaynak | Scopus | |
dc.language.iso | en | |
dc.publisher | Elsevier Sci Ltd | |
dc.relation.ispartof | International Dairy Journal | |
dc.relation.publicationcategory | info:eu-repo/semantics/openAccess | |
dc.rights | info:eu-repo/semantics/closedAccess | |
dc.snmz | KA_WoS_20250125 | |
dc.subject | Fluorescence Spectroscopies | |
dc.subject | Midinfrared Spectroscopy | |
dc.subject | Mozzarella Cheese | |
dc.subject | Fat | |
dc.subject | Prediction | |
dc.subject | Rheology | |
dc.subject | Quality | |
dc.title | Infrared spectroscopy combined with chemometrics as a convenient method to detect adulterations in cooking/stretching process in commercial cheese | |
dc.type | Article |