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Application of Multivariate Analysis of Broadband Transmission Spectra for Calibration of Physico-Chemical Parameters of Wines
Author(s) -
М. А. Ходасевич,
Е. А. Скорбанова,
М. В. Роговая
Publication year - 2019
Publication title -
pribory i metody izmerenij
Language(s) - English
Resource type - Journals
eISSN - 2414-0473
pISSN - 2220-9506
DOI - 10.21122/2220-9506-2019-10-2-198-206
Subject(s) - calibration , multivariate statistics , tartaric acid , wine , analytical chemistry (journal) , chemistry , biological system , mathematics , statistics , chromatography , citric acid , food science , biology
The use of multivariate processing of spectral information has recently been favored due to the express nature of this method, the ease of use of mathematical packages, and the lack of the need to add chemical reagents. The aim of the work is using the methods of multivariate analysis of broadband transmission spectra to calibrate the physicochemical parameters of wines and to improve the accuracy of this calibration by selecting spectral variables. Using the interval projection to latent structures of the transmission spectra in the range of 220– 2500 nm, the physicochemical characteristics of the varietal unblended Moldovan wine are calibrated. Interval methods of multivariate data analysis allow signifi reducing the root mean square calibration error in comparison with the broadband multivariate methods. Residual predictive deviations exceed the threshold value of 2.5 for K, Ca, Mg, oxalic, malic and succinic acids, 2,3-butylene glycol, ash and phenolic compounds for red wines and Mg, tartaric, citric and lactic acids, 2,3-butylene glycol, ash, phenolic compounds and soluble salts for white wines. These values demonstrate good calibration quality. The application of the proposed method for calibrating the physicochemical parameters of wines makes it possible to replace traditional methods with spectral measurements, which are available not only in laboratory but also in the fi and characterized by small values of the root mean square error of calibration.

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