A digital image smartphone-based approach to Slovak Tokaj wine authentication chemometric assisted.

The authentication of Slovak wines in comparison to other similar wines from various geographical regions, namely Hungary, France, Austria, and Ukraine, was conducted using the OC-PLS, DD-SIMCA, and PLS-DM models, all of them operating in rigorous way. The study involved 63 samples, of which 41 originated from Slovakia, covering diverse wine types such as varietal wines, cuvée selections (different "putnový"), and essence. To capture digital images under controlled conditions, a custom-made cardboard box with white inner surfaces was devised and equipped with a smartphone. During the training phase, sensitivities of 96%, 100%, and 96% were attained for OC-PLS, DD-SIMCA, and PLS-DM, respectively. In the subsequent stages of validation and testing for DD-SIMCA and PLS-DM, the proposed methods displayed optimal efficiency, achieving both sensitivity and specificity rates of 100%. However, such results were not achieved in the case of OC-PLS, which exhibited efficiency levels of 90% in validation and 80% in testing.

Region of interest selection in heterogeneous digital image: Wine age prediction by comprehensive two-dimensional gas chromatography.

This study integrates genetic algorithm (GA) with partial least squares regression (PLSR) and various variable selection methods to identify impactful regions of interest (ROI) in heterogeneous 2D chromatogram images for predicting wine age. As wine quality and aroma evolve over time, transitioning from youthful fruitiness to mature, complex flavors, which leads to alterations in the composition of essential aroma-contributing compounds. Chromatograms are segmented into subimages, and the GA-PLSR algorithm optimizes combinations based on grayscale, red-green-blue (RGB), and hue-saturation-value (HSV) histograms. The selected subimage histograms are further refined through interval selection, highlighting the compounds with the most significant influence on wine aging. Experimental validation involving 38 wine samples demonstrates the effectiveness of this approach. Cross-validation reduces the PLS model error from 2.8 to 2.4 years within a 10 × 10 subset, and during prediction, the error decreases from 2.5 to 2.3 years. The study presents a novel approach utilizing the selection of ROI for efficient processing of 2D chromatograms focusing on predicting wine age.

A non-target geographical origin screening of botrytized wines through comprehensive two-dimensional gas chromatography coupled with high-resolution mass spectrometry.

One of the most effective methods for gaining insight into the composition of trace-level volatile organic characteristics of wine products is through the use of a comprehensive two-dimensional gas chromatography-high resolution mass spectrometry (GC × GC-HRMS) technique. The vast amount of data generated by this method, however, can often be overwhelming requiring exhaustive and time-consuming analysis to identify significant statistical characteristics. The use of advanced chemometric software can achieve the same or even higher efficiency. This study aimed to identify differences based on geographical locations by analyzing the volatile organic compounds in the composition of botrytized wines from Slovakia, Hungary, France, and Austria. The volatile organic compounds were extracted by solid-phase microextraction and analyzed using GC × GC-HRMS. The data obtained from the analysis underwent Fisher-ratio (F-ratio) tile-based analysis to identify statistically significant differences. Principal component analysis demonstrated a significant distinction between wine samples based on geographical location, using only 10 statistically significant features with the highest F-ratio. In the samples, the following compounds were analyzed: methyl-octadecanoate, 2-cyanophenyl-ß-phenylpropionate, α-ionone, n-octanoic acid, 1,2-dihydro-1,1,6-trimethyl-naphthalene, methyl-hexadecanoate, ethyl-pentadecanoate, ethyl-decanoate, and γ-nonalactone. These, all play an important role in cluster pattern observed on principal component analysis results. Additionally, hierarchical cluster analysis confirmed this.

Aroma Compounds in Essential Oils: Analyzing Chemical Composition Using Two-Dimensional Gas Chromatography-High Resolution Time-of-Flight Mass Spectrometry Combined with Chemometrics.

Analyzing essential oils is a challenging task for chemists because their composition can vary depending on various factors. The separation potential of volatile compounds using enantioselective two-dimensional gas chromatography coupled with high-resolution time-of-flight mass spectrometry (GC×GC-HRTOF-MS) with three different stationary phases in the first dimension was evaluated to classify different types of rose essential oils. The results showed that selecting only ten specific compounds was enough for efficient sample classification instead of the initial 100 compounds. The study also investigated the separation efficiencies of three stationary phases in the first dimension: Chirasil-Dex, MEGA-DEX DET-ß, and Rt-ßDEXsp. Chirasil-Dex had the largest separation factor and separation space, ranging from 47.35% to 56.38%, while Rt-ßDEXsp had the smallest, ranging from 23.36% to 26.21%. MEGA-DEX DET-ß and Chirasil-Dex allowed group-type separation based on factors such as polarity, H-bonding ability, and polarizability, whereas group-type separation with Rt-ßDEXsp was almost imperceptible. The modulation period was 6 s with Chirasil-Dex and 8 s with the other two set-ups. Overall, the study showed that analyzing essential oils using GC×GC-HRTOF-MS with a specific selection of compounds and stationary phase can be effective in classifying different oil types.

Optimization of enantiomer separation in flow-modulated comprehensive two-dimensional gas chromatography by response surface methodology coupled to artificial neural networks: Wine analysis case study.

In spite of extensive applications of flow modulated comprehensive two-dimensional gas chromatography (FM-GG × GC) in different research areas, its application in the field of chiral separation is very limited. From a practical point of view, the establishment of experimental parameters for enantiomer separations is possibly more demanding in this case. Since the carrier gas flows in both dimensions, it affects not only the separation parameters, but also the fill/flush volumes of the modulator and its working efficiency. In this context, a multivariate design of experiment was applied to find the optimum experimental parameters of a reversed fill/flush (RFF) modulator for enantiomer separation of organic compounds present in botrytized wine samples. The results were described both with response surface methodology and artificial neural networks (ANN). The enantiomeric composition of chiral compounds present in the botrytized wines was used to identify their geographical origin, by principal component analysis (PCA). In addition, the developed one-class partial least squares (OC-PLS) model enabled recognition of the wine samples from the Tokaj wine region with 93% effectiveness in the presence of other samples.

Classification of Botrytized Wines Based on Producing Technology Using Flow-Modulated Comprehensive Two-Dimensional Gas Chromatography.

The enantiomeric ratio of chiral compounds is known as a useful tool to estimate wine quality as well as observe an influence of wine-producing technology. The incorporation of flow-modulated comprehensive two-dimensional gas chromatography in this type of analysis provides a possibility to improve the quality of results due to the enhancement of separation capacity and resolution. In this study, flow-modulated comprehensive two-dimensional gas chromatography was incorporated in enantioselective analysis to determine the influence of winemaking technology on specific features of botrytized wines. The samples included Tokaj essences (high-sugar wines), Tokaj botrytized wines and varietal wines (Furmint, Muscat Lunel, Lipovina) and wines maturated on grape peels. The obtained data was processed with hierarchic cluster analysis to reveal variations in composition and assess classification ability for botrytized wines. A significant difference between the samples was observed for the enantiomeric distribution of ethyl lactate and presence of monoterpene alcohols. The varietal wines were successfully separated from the other types, which showed more similar results and could be divided with additional parameters. We observed a correlation between the botrytized wines and the varietal wines fermented with grape skins. As to the essences produced from juice of botrytized grapes, the results were quite similar to those of the botrytized wines, even though monoterpenes were not detected in the extracts.