Introduction

Innovative method for assessing the quality of cork, capable of detecting the TCA risk quickly and economically. TCA is one of the main causes of organoleptic alteration in wine and can cause serious economic damage by ruining the quality of the bottled wine. The damage it causes can lead to important image repercussions and costly lawsuits for producers. For this reason, its identification is essential in the production of cork stoppers. However, identifying the TCA is not simple, especially in industrial production, because it requires high sensitivity and has high costs. The method in question allows to considerably improve the state of the art, thanks to the combination of FT-NIR spectrometry and predictive models. In fact, with this technique it is possible to evaluate and classify each single cap with times compatible with the industrial chain. The invention therefore takes the form of a considerable progress in the quality analysis of cork in the industrial field.

Technical features

The technology allows to classify cork stoppers in relation to the risk of TCA pollution, using the combination of two elements. The first is the spectroscopic analysis carried out with the near infrared (FT-NIR), which allows to obtain a characteristic spectrum which acts as a “fingerprint” of the analyzed sample. This technique allows non-destructive analysis of the sample, which can be both qualitative and quantitative. It lends itself to being easily implemented on the line instrumentation. The second element is the statistical processing of data by multivariate techniques. They allow the construction of a predictive model that can be used in online product evaluation and selection. The invention was tested using a laboratory FT-NIR spectrometer and applying data processing systems that allowed to build a statistical model capable of classifying cork in relation to the risk of pollution by TCA

Possible Applications

• Analysis of the quality of cork.

Advantages

• Possibility of providing cork factories a quality control system applicable to all production;
• Reduction of the costs of analysis;
• Reduction of raw material waste;
• Control of production costs;
• Improvement of overall quality.