Non-invasive wine authentication method using near-infrared spectroscopy through the bottle

Abstract

Wine fraud is currently a massive problem within the wine industry, with counterfeiting and adulteration the most frequent practices, which have led the industry to lose billions of dollars annually. Hence, the importance of developing rapid, accurate, and non-invasive techniques to identify signs of fraud, such as wine provenance and quality traits. This study aimed to develop a non-invasive technique using a hand-held near-infrared (NIR) spectroscopy device (1596-2396 nm) to measure wines through the bottle. Machine learning models based on artificial neural networks were developed using the NIR absorbance values as inputs to predict the wine vintage (classification Model 1) and intensity ..