The dynamic Raman spectra of a brand of red wine (aa) as the main research object were collected over a range of laser integration times (1–5 s) to observe the changing trends of molecules in the wine under experimental conditions. The three-dimensional Raman characteristic spectrum of this wine was then constructed further by two-dimensional correlation fusion analysis. The fluctuations of the three-dimensional Raman spectra were also evaluated using a similarity algorithm. The correlation coefficients were 0.977 ± 0.011 and 0.990 ± 0.006 based on synchronous and asynchronous two-dimensional correlation Raman spectroscopy, respectively. These results suggested that the samples of wine aa were highly self-similar and could be effectively distinguished from two different brands of red wine (bb and cc) based on their different spectral responses. Therefore, this method has the potential to supplement existing methods for the classification analysis of red wine.
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References
I. L. Francis and P. O. Williamson, Aust. J. Grape Wine Res., 21, 554–567 (2015).
H. X. Yu, L. Q. Sun, and J. Qi, Chin. J. Nat. Med., 12, 517–524 (2014).
D. W. Jeffery, M. D. Mercurio, M. J. Herderich, Y. Hayasaka, and P. A. Smith, J. Agric. Food Chem., 56, 2571–2580 (2008).
C. A. T. Dos Santos, R. N. M. J. Páscoa, and J. A. Lopes, Trends Anal. Chem., 88, 100–118 (2017).
M. Sha, Z. Y. Zhang, D. D. Gui, Y. B. Wang, L. L. Fu, and H. Y. Wang, Food Anal. Methods, 10, 3415–3423 (2017).
E. Borràs, J. Ferré, R. Boqué, M. Mestres, L. Aceña, and O. Busto, Anal. Chim. Acta, 891, 1–14 (2015).
I. Noda, J. Mol. Struct., 1124, 3–7 (2016).
I. Noda, J. Mol. Struct., 1124, 197–206 (2016).
I. Noda, J. Mol. Struct., 1124, 42–52 (2016).
I. Noda, J. Mol. Struct., 1124, 29–41 (2016).
I. Noda and Y. Ozaki, Two-Dimensional Correlation Spectroscopy — Applications in Vibrational and Optical Spectroscopy, John Wiley & Sons, Chichester, 1–195 (2005).
I. Noda, J. Mol. Struct., 1124, 53–60 (2016).
D. A. Magdas, F. Guyon, I. Feher, and S. C. Pinzaru, Food Control, 85, 385–391 (2018).
G. X. Wang, Wang, H. Y. Wang, H., Z. Y. Zhang, and J. Liu, Spectrosc. Spectra l Anal., 36, 729–735 (2016).
L. Mandrile, G. Zeppa, A. M. Giovannozzi, and A. M. Rossi, Food Chem., 211, 260–267 (2016).
C. Martin, J. Bruneel, F. Guyon, B. Médina, M. Jourdes, P. Teissedre, and F. Guillaume, Food Chem. , 181, 235–240 (2015).
Q. Wang, Z. Li, Z. Ma, and L. Liang, Sens. Actuators, B, 202, 426–432 (2014).
Z. Y. Zhang, M. Sha, and H. Y. Wang, J. Raman Spectrosc., 48, 1111–1115 (2017).
J. Chen, Q. Zhou, I. Noda, and S . Sun, Appl. Spectrosc., 63, 920–925 (2009).
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Published in Zhurnal Prikladnoi Spektroskopii, Vol. 87, No. 1, pp. 116–121, January–Febarury, 2020.
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Zhang, ZY., Liu, J. Dynamic Raman Fusion Spectroscopy for Rapid Quality Discriminant Analysis of Red Wine. J Appl Spectrosc 87, 99–104 (2020). https://doi.org/10.1007/s10812-020-00969-5
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DOI: https://doi.org/10.1007/s10812-020-00969-5