|JOSHI, RAHUL - Chungnam National University
|JOSHI, RITU - Chungnam National University
|KIM, GEONWOO - Orise Fellow
|FAQEERZADA, MOHAMMAD - Chungnam National University
|AMANAH, HANIM - Chungnam National University
|KIM, JUNTAE - Chungnam National University
|CHO, BYOUNG-KWAN - Chungnam National University
Submitted to: Korean Journal of Agricultural Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/11/2021
Publication Date: 5/18/2021
Citation: Joshi, R., Joshi, R., Kim, G., Faqeerzada, M.A., Amanah, H., Kim, J., Kim, M.S., Cho, B. 2021. Quantitative analysis of glycerol concentration in red wine combining Fourier transform infrared spectroscopy and multivariate analysis. Korean Journal of Agricultural Science. 48:299-310. https://doi.org/10.7744/kjoas.20210023.
Interpretive Summary: The taste and mouthfeel of wine can be significantly affected by the wine’s concentration of glycerol, a byproduct of sugar fermentation. Glycerol in wine may be present naturally or as the result of adulteration. This study used Fourier Transform Infrared (FTIR) spectroscopy with multivariate regression analysis to rapidly and nondestructively assess a selection of red wines from Chile, Australia, and Italy that were prepared with glycerol in concentrations ranging from 0.1% to 15 % by volume. The method demonstrated high accuracy for quantitative glycerol determination, suggesting feasible use as an alternative to conventional analysis methods that are unsuitable for high-volume quality screening of wine due to their sample-destructive and time-consuming nature. With additional studies, this research will help wine producers and distributors by providing an improved means by which they can authenticate and detect adulteration of wines to ensure product quality and maintain consumer confidence.
Technical Abstract: Glycerol is a non-volatile compound that contributes significantly to the quality of wine by providing sweetness and richness of taste. In addition, it is the third most important by-product of alcoholic fermentation in terms of quantity, after ethanol and carbon dioxide. Here, we use FT-IR spectroscopy in combination with multivariate regression analysis to build a model for the quantitative prediction of glycerol concentration in wine samples. In this study, samples of three varieties of red wine originating from different countries were adulterated with glycerol in concentrations ranging from 0.1 to 15% (v/v), and subjected to analysis together with pure wine samples. We utilized a net analyte signal (NAS)-based methodology called HLA/GO for predicting glycerol concentrations based on the FT-IR spectral data of the samples. The calibration and validation sets were designed to evaluate the performance of the multivariate method. The results showed high coefficients of determination and low root mean square errors for both the calibration set (0.987 and 0.56%, respectively) and the validation set (0.984 and 0.62%, respectively). The model was validated in terms of sensitivity, selectivity, and limits of detection and quantification, confirming that this model can be used as a fast and non-destructive method for glycerol determination in wine for quality assurance and other applications.