The composition of phenolic compounds plays an important role in food science and nutrition; thus, there is a need of a new method of analysis that is able to speed up the monitoring of product quality parameters. In this view, the amount of selected color components of 145 commercial red wines (total wine color, polymeric pigments, total anthocyanins, and copigmentation index) was investigated using Fourier transform mid-infrared spectroscopy (MIR) combined with partial least squares (PLS) regression. The feasibility of several preprocessing algorithms (first and second derivative, standard normal variate, and direct orthogonal signal correction) was compared in terms of coefficient of determination (R2) and root mean square error of prediction using an independent test set of wines. The composition of red wines showed great difference in terms of total color (5.07±1.95 AU at 520 nm) compared to copigmentation index (0.66± 0.58 AU at 520 nm). The best prediction model was obtained using direct orthogonal signal correction (DOSC) preprocessing. In particular, the prediction of total wine color, total anthocyanins, and polymeric pigments showed a good fitting (R2≥0.82), whereas copigmentation index was more difficult to be predicted by FTIR (R2=0.57). This preliminary study showed the potential of MIR spectroscopy with DOSC–PLS algorithm to successfully analyze selected color components of red wine on a large number of samples in short time with almost no sample preparation and no chemical waste is created.

FT-IR spectroscopy and direct orthogonal signal correction preprocessing applied to selected phenolic compounds in red wines

LAGHI, LUCA;VERSARI, ANDREA;PARPINELLO, GIUSEPPINA PAOLA;
2011

Abstract

The composition of phenolic compounds plays an important role in food science and nutrition; thus, there is a need of a new method of analysis that is able to speed up the monitoring of product quality parameters. In this view, the amount of selected color components of 145 commercial red wines (total wine color, polymeric pigments, total anthocyanins, and copigmentation index) was investigated using Fourier transform mid-infrared spectroscopy (MIR) combined with partial least squares (PLS) regression. The feasibility of several preprocessing algorithms (first and second derivative, standard normal variate, and direct orthogonal signal correction) was compared in terms of coefficient of determination (R2) and root mean square error of prediction using an independent test set of wines. The composition of red wines showed great difference in terms of total color (5.07±1.95 AU at 520 nm) compared to copigmentation index (0.66± 0.58 AU at 520 nm). The best prediction model was obtained using direct orthogonal signal correction (DOSC) preprocessing. In particular, the prediction of total wine color, total anthocyanins, and polymeric pigments showed a good fitting (R2≥0.82), whereas copigmentation index was more difficult to be predicted by FTIR (R2=0.57). This preliminary study showed the potential of MIR spectroscopy with DOSC–PLS algorithm to successfully analyze selected color components of red wine on a large number of samples in short time with almost no sample preparation and no chemical waste is created.
Laghi L.; Versari A.; Parpinello G.P.; Nakaji Y.D.; Boulton R.B.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11585/106803
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