Spectralprint techniques coupled with chemometric tools for vinegar classifications

[Display omitted] •First study to classify vinegar by agronomic method of raw material cultivation.•Vinegar classification by type of raw materials and aging time.•NMR with PLS-DA had the best performance, followed by FT-IR with UV–vis and NIR.•Vinegar classification according to the agronomic culti...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Food chemistry 2023-06, Vol.410, p.135373-135373, Article 135373
Hauptverfasser: Avanzi Barbosa Mascareli, Vinícius, Galvan, Diego, Craveiro de Andrade, Jelmir, Lelis, Carini, Adam Conte-Junior, Carlos, Michelino Gaeta Lopes, Giancarlo, César de Macedo Júnior, Fernando, Aparecida Spinosa, Wilma
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:[Display omitted] •First study to classify vinegar by agronomic method of raw material cultivation.•Vinegar classification by type of raw materials and aging time.•NMR with PLS-DA had the best performance, followed by FT-IR with UV–vis and NIR.•Vinegar classification according to the agronomic cultivation mode is more complex.•Spectralprint techniques with chemometrics were useful for vinegar quality control. Vinegar is a versatile product used for food preservation, cooking, healthcare, and cleaning. In this study, 80 vinegar of different raw materials, aging time, and for the first time by the agronomic method of raw material cultivation were classified by spectralprint techniques with chemometrics. Datasets were obtained by proton nuclear magnetic resonance (1H NMR), Fourier transforms mid-infrared (FT-IR), near-infrared (NIR), and ultraviolet–visible (UV–vis); then evaluated by common dimension (ComDim) and partial least squares-discriminant analysis (PLS-DA). NMR with PLS-DA had the best prediction performance compared to other techniques, with accuracy values between 92.3 and 100 %, followed by FT-IR and UV–vis of 80.8 and 96.0 % and NIR between 69.2 and 84.0 %. The results indicated that the classification of vinegar according to the agronomic cultivation method is more complex than aging time or raw material. However, any of these spectralprint techniques have demonstrated that they can be used in the classification of vinegar.
ISSN:0308-8146
1873-7072
DOI:10.1016/j.foodchem.2022.135373