Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/12134
Title: Detection of vinegar adulteration with spirit vinegar and acetic acid using UV–visible and Fourier transform infrared spectroscopy
Authors: Çavdaroğlu, Çağrı
Özen, Banu
Izmir Institute of Technology
Izmir Institute of Technology
Keywords: Adulteration
Artificial neural networks
Chemometrics
Issue Date: Jun-2022
Publisher: Elsevier
Abstract: Vinegar is one of the commonly adulterated food products, and variations in product and adulterant spectrum make the detection of adulteration a challenging task. This study aims to determine adulteration of grape vinegars with spirit vinegar and synthetic acetic acid using different spectroscopic methods. For this purpose, grape vinegars were mixed separately with spirit vinegar and diluted synthetic acetic acid (4%) at 1–50% (v/v) ratios. Spectra of vinegars and mixtures were obtained with UV–visible and Fourier-transform infrared (FTIR) spectrometers. Data were evaluated with various chemometric methods and artificial neural networks (ANN). Correct classification rates of at least 94.3% and higher values were obtained by the evaluation of both spectroscopic data along with their combination with chemometric methods and ANN for discrimination of non-adulterated and adulterated vinegars. UV–vis and FTIR spectroscopy can be rapid and accurate ways of detecting adulteration in vinegars regardless of adulterant type.
URI: https://doi.org/10.1016/j.foodchem.2022.132150
https://hdl.handle.net/11147/12134
Appears in Collections:Food Engineering / Gıda Mühendisliği
PubMed İndeksli Yayınlar Koleksiyonu / PubMed Indexed Publications Collection
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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