Raman spectroscopy for wine analyses: A comparison with near and mid infrared spectroscopy.

Routine wine analysis are commonly employed to ensure the quality and safety standards, and to meet consumers' demands and legal requirements. In the last decades, efforts have been done in order to replace the traditional analytical techniques by vibrational spectroscopic techniques such as near infrared (NIR) and mid infrared (MIR) spectroscopy. The potential of these techniques has already been proved by several studies that revealed their ability for the determination of several wine parameters with high levels of precision and accuracy. Raman spectroscopy, (which is also a vibrational technique), was much less explored in the wine industry. In this work, the ability of Raman spectroscopy for routine wine analysis was evaluated and compared to NIR and MIR spectroscopy. Several calibration models were developed aiming the quantitative assessment of alcoholic strength, density, total acidity, volatile acidity, total sugars and pH in white wines. For this purpose, partial least squares (PLS) regression was employed, enabling the correlation between reference results and spectral information obtained by NIR, MIR and Raman spectroscopy. Results revealed the better performance of MIR spectroscopy for the measurement of alcoholic strength (R2P = 0.99, RMSEP=1.77%, and RER=56.41), and total acidity (R2P = 0.98, RMSEP=2.02%, and RER=49.46). Raman spectroscopy was pointed out as the most suitable for the determination of total sugars (R2P = 0.97, RMSEP=5.12%, RER=19.52), and pH (R2P = 0.90, RMSEP=4.92%, RER=20.34). The three techniques presented similar results in what referred the assessment of density (R2P = 0.96, 0.98, and 0.97, RMSEP=4.72%, 3.90%, and 3.80%, for Raman, MIR, and NIR respectively). None of the three techniques seemed to be suitable for the accurate determination of volatile acidity (R2P <0.78, RMSEP>14.32%, and RER<6.98).

Merging vibrational spectroscopic data for wine classification according to the geographic origin.

The wine making procedure is no longer a secret and it is nowadays well described and repeated around the world. Nevertheless, wines present unique features, strongly associated with their geographic origin. Classification systems were developed to catalogue wines according to the provenance, and are currently established by official authorities in order to ensure wine authenticity. The use of near-infrared (NIR), mid-infrared (MIR) and Raman spectroscopy for tracing the origin of wine samples, has been reported with different levels of success. This work evaluated and compared the performance of these techniques, as well as their joint use, in terms of geographic origin classification. NIR, MIR and Raman spectra of wine samples belonging to four Portuguese wine regions (Vinhos Verdes, Lisboa, Açores and Távora-Varosa) were analyzed by partial least squares discriminant analysis (PLS-DA). Results revealed the better suitability of MIR spectroscopy (87.7% of correct predictions) over NIR (60.4%) and Raman (60.8%). The joint use of spectral sets did not improve the predictive ability of the models. The best models were achieved by combining MIR and NIR spectra resulting in 86.7% of correct predictions. Multiblock partial least squares (MB-PLS) models were developed to further explore the combination of spectral data. Although these models did not improve the percentage of correct predictions, they demonstrated the higher contribution of MIR spectroscopic data, in the development of the models.