Tokaj wines (Hungaricum) are botrytized wines acknowledged for the unique organoleptic properties bestowed by botrytized grape berries during production. Excluding these berries during wine production or manipulating the sugar content of low-grade wines to imitate high-grade wines are some recent suspicious activities that threaten the wine quality. Advanced methods such as spectroscopy and sensor-based devices have been lauded for rapid, reliable, and cost-effective analysis, but there has been no report of their application to monitor grape must concentrate adulteration in botrytized wines. The study aimed to develop models to rapidly discriminate lower grade Tokaj wines, "Forditas I" and "Forditas II," that were artificially adulterated with grape must concentrate to match the sugar content of high-grade Tokaj wines using an electronic tongue (e-tongue) and two near infrared spectrometers (NIRS). Data were evaluated with the following chemometrics: principal component analysis (PCA), discriminant analysis (LDA), partial least square regression (PLSR), and aquaphotomics (a novel approach). There was a noticeable pattern of separation in PCA for all three instruments and 100% classification of adulterated and nonadulterated wines in LDA using the e-tongue. Aquagrams from the aquaphotomics approach showed important water absorption bands capable of being markers of Tokaj wine quality. PLSR models showed coefficient of determination (R 2 CV) of 0.98 (e-tongue), 0.97 (benchtop NIRS), 0.87 (handheld NIRS), and low root mean squared errors of cross-validation. All three instruments could discriminate, classify, and predict grape must concentrate adulteration in Tokaj with a high accuracy and low error. The methods can be applied for routine quality checks of botrytized wines.Practical Application: Tokaj wines (Hungaricum) are botrytized wines acknowledged for the unique organoleptic properties bestowed by botrytized grape berries during production. Excluding these berries during wine production or manipulating the sugar content of low-grade wines to imitate high-grade wines are some recent suspicious activities that threaten the wine quality. Using advanced instruments, the electronic tongue, benchtop near infrared spectroscopy, and a handheld near infrared spectroscopy, we could discriminate, classify, and predict grape must concentrate adulteration in Tokaj with a high accuracy and low error. The models in our study can be applied for routine quality checks of botrytized wines.
In this work, the application of an electronic tongue (ET) based on a specifi c ion-selective sensor array for discrimination of different white wine types is presented. The electronic tongue equipped with specifi c sensor array containing seven IFSET sensors was used to analyze wine samples. The obtained ET responses were evaluated using different pattern recognition methods. Principal component analysis (PCA) provides the possibility to identify some initial patterns. Linear discriminant analysis (LDA) was used to build models to separate white wine samples based on wine regions and grape cultivars. The results showed that every group was distinguished from each other with no misclassifi cation error. Furthermore, the sequence of the wine sample groups was similar to the increasing total acidity content. Partial least square (PLS) regression was used to build models for the prediction of the main chemical compositions of the wine samples based on the electronic tongue results. The closest correlation (R 2 =0.93) was found in case of 'total acidity', and the prediction error (RMSEP) was 6.9%. The pH of the wine samples was predicted with good correlation (R 2 =0.89) but higher prediction error (RMSEP=10.71%) from the electronic tongue results. The ET combining these statistical methods can be applied to determine the origin and variety of the wine samples in easy and quick way.
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