A new FT‐IR method combined with multivariate analysis for the classification of vinegars from different raw materials and production processes

Abstract

The discriminative ability combined with other advantages (e.g. rapid and non-destructive analysis, low cost) makes this new FT-IR method a promising tool for the classification and/or differentiation of vinegars.

Comparison of Anti-obesity Effects of Spirit Vinegar and Natural Fermented Vinegar Products on the Differentiation of 3T3-L1 Cells and Obese Rats Fed a High-fat Diet

“…Vinegar is a typical fermented food with a unique aroma and sour taste that contains small amounts of volatile and nonvolatile organic acids, sugars, amino acids, and esters [4,5]. Since ancient times, vinegar has been widely used in Korea not only for seasoning but also for detoxification and recovery from fatigue and hangovers in the private sector [6].…”

Prediction of sugars and acids in Chinese rice wine by mid-infrared spectroscopy

“…Some interested compounds, such as tannins and anthocyanins, were also successfully quantified (Fernandez & Agosin, 2007;Soriano, Perez-Juan, Vicario, Gonzalez, & Perez-Coello, 2007). In addition, MIR spectroscopy has already been applied for the classification purpose to differentiate wines or vinegars according to origin, grape variety as well as manufacturing technique (Bevin, Dambergs, Fergusson, & Cozzolino, 2008;Guerrero, Mejias, Marin, Lovillo, & Barroso, 2010). On-line monitoring of sugars, alcohols, and organic acids during fermentation based on MIR spectra was also reported (Mazarevica, Diewok, Baena, Rosenberg, & Lendl, 2004;Nieuwoudt, Pretorius, Bauer, Nel, & Prior, 2006).…”

Independent components analysis to increase efficiency of discriminant analysis methods (FDA and LDA): Application to NMR fingerprinting of wine

“…It can be seen that standard PCA/LDA generally outperforms PCA/FDA regarding classification of important wine parameters. The average correct classification rate varied between 64% and 88% for calibration sets and between 43±4% and 76±7% for validation sets when the standard PCA/FDA procedure 12 was used. LDA provided better average correct classification rates, namely, 89-90% for calibration and 79-89% for independent test set validation (Table 1).…”

“…Different authors have applied DA methods to continuous and discrete signals such as spectra, chromatograms or stable isotope data [6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22]. Numerous applications have been developed in infrared (IR) spectroscopy using the absorbances at various wavelengths as discriminant variables [6][7][8][9][10][11][12][13].…”

“…Numerous applications have been developed in infrared (IR) spectroscopy using the absorbances at various wavelengths as discriminant variables [6][7][8][9][10][11][12][13]. Moreover, there are several applications for modeling of fluorescence, NMR data and electronic nose signals [14][15][16][17][18][19].…”