Abstract
Aim: This research primarily focuses on exploring the suitability of near infrared (NIR) spectroscopy with multivariate data analysis as a tool to classify commercial wines depending on the aging process. It is aimed at discriminating between wines aged in barrels and those obtained using alternative products (chips).Methods and Results: Around 75 commercial barrel-aged red wines issued from the appellation “Valpolicella” (Italy) were analyzed. Moreover, 15 wines were aged at the experimental winery of the Research Centre of Viticulture and Enology in Asti using different types of commercial oak chips. Wines were analyzed in transmittance using NIR regions of the electromagnetic spectrum. Principal component analysis (PCA) and partial least squares (PLS) analyses were used to classify wines: a preliminary step was carried out using PCA that showed interesting groups in the whole data set. Next, in order to test if combined explanatory variables made it possible to discriminate treatments and how they are useful to predict which group a new observation will belong to, an orthogonal partial least squares discriminant analysis (OPLS-DA) was carried out. Several wine groups were considered, defined by factors including the aging process, the type of oak used for aging (wood barriques, barrels or chips) and the wine typologies (differing for some enological parameters).Conclusions: Overall, OPLS-DA models correctly classified >90 % of the wines. These results demonstrate the potential of combining spectroscopy with chemometric data analysis as a rapid method to classify wines according to their aging process. Nevertheless, the development of a mathematical model for predictive purposes is a complex task: indeed, large databases for different wines should be constructed, and other spectral IR zones might be evaluated for improving the method performance in determining wine aging process.Significance and impact of the study: This study contributes to the development of an easy-to-use and easily applicable NIR method for correlating the infrared “fingerprint” spectrum with the aging process in wines, aimed at implementing a technique able to discriminate wines aged with different wood types, that can be progressively used in the laboratory for routine fraud inspection.
Highlights
Wine is generally sold with labeling information regarding its characteristics - including the grape variety used, the appellation or grape growing region, the vintage or age - and price and consumer expectations are often determined based on these data
The work was based on the collection of a number of wine samples whose origin was certain, including any information regarding the type of refinement the wine had undergone
Commercial wines aged in barriques, barrels and in steel tanks were recovered (Table 1) and compared with wines aged ad hoc with 15 different types of oak chips (Table 2)
Summary
Wine is generally sold with labeling information regarding its characteristics - including the grape variety used, the appellation or grape growing region, the vintage or age - and price and consumer expectations are often determined based on these data. Failure to fulfill the wine appellation regulations, and allowing a less valuable wine to be put on the market in place of a quality one, is one of these cases (Takeoka and Ebeler, 2011) For many wines, these rules constrain to a specific aging time in wood and a specific aging mode (barriques, barrels, etc.) that is not necessarily respected. This happens because the traditional aging process is associated with high financial costs, due to the price of the containers and the long refinement time (Pérez-Coello and Díaz-Maroto, 2009) In this context, the use of oak alternatives provides the winemaker with a way to lower the costs related to traditional refinement in barrels while adding to their wine a woody touch without the need to use barrels. This could lead to fraud if such wine is offered as barrel- aged wine (Cano-Lopez et al, 2008; Ortega-Heras et al, 2010), as false use of quality indications by unauthorized parties is detrimental to consumers and legitimate producers
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