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.

Teicoplanin aglycone media and carboxypeptidase Y: Tools for finding low-abundance D-amino acids and epimeric peptides.

D-amino acids and epimeric peptides/proteins can play crucial biological roles and adversely affect protein folding and oligopeptide aggregation in age-related pathologies in humans. This has ignited interest in free D-amino acids as well as those incorporated in peptides/proteins and their effects in humans. However, such stereoisomeric analytes are often elusive and in low abundance with few existing methodologies capable of scouting for and identifying them. In this work, we examine the feasibility of using teicoplanin aglycone, a macrocyclic antibiotic, which has been reported to strongly retain D-amino acids and peptides with a D-amino acid on the C-terminus, for use as a solid phase extraction (SPE) medium. The HPLC retention factors of L-/D-amino acids and C-terminus modified D-amino acid-containing peptides and their L-amino acid exclusive counterparts on teicoplanin aglycone are presented. Retention curve differences between amino acids and peptides highlight regions of solvent composition that can be utilized for their separation. This approach is particularly useful when coupled with enzymatic hydrolysis via carboxypeptidase Y to eliminate all L-amino acid exclusive peptides. The remaining peptides with carboxy-terminal D-amino acids are then more easily concentrated and identified.

Handling multiblock data in wine authenticity by sequentially orthogonalized one class partial least squares.

New approach to deal with food authentication by modelling methods based on data recorded from different sources is proposed and called OC-PLS, combines an orthogonalization step between the different data sets to eliminate redundant information followed by definition of an acceptance area for a target class by OC-PLS. The proposed method was evaluated in two case studies. The first study used a controlled scenario with simulated data. In the second case study, the approach was applied using UV-VIS and IR data, in order to differentiate Slovak Tokaj Selection wines of high quality from other lower market value wines from the Slovak Tokaj wine region. In both cases, better results were reached than when individual blocks of data were achieved. The proposed method proved to be effective in properly exploring common and distinct information in each data block. The best compromise between sensitivity and selectivity in the prediction step was achieved.

Slovak Tokaj wines classification with respect to geographical origin by means of one class approaches.

Tokaj wines could be produced only in so called Tokaj/Tokay wine region that falls within two countries Slovakia and Hungary. Thus, wines bearing Tokaj appellation must be produced only in Hungary and Slovakia by traditional process. Unfortunately, some counterfeit wines from neighbour region in Ukraine could be found in market. The aim of this work is to explore a simple UV-VIS spectrum to recognise true Tokaj/Tokay wines from counterfeits and try to differentiate wines based on their country of origin. This type of question can be duly answered using one class classification approach. Two different approaches, Data Driven Soft Independent Modelling of Class Analogy - DD-SIMCA and One-Class Partial Least Squares - OC-PLS were tested and evaluated for this purpose. In both cases, rigorous way models were built and optimized using only samples of the target class. A set of external samples containing samples from target class and non-target were used to validate the models ability to recognize Slovak samples and reject non-Slovak samples. Model based on DD-SIMCA showed better performance (97% correct rating) compared to OC-PLS models (80% correct rating). Comparing both approaches in terms of sensitivity and specificity, both exhibit high sensitivity (low false negative rate: DD-SIMCA 95% and OC-PLS 100%), however the OC-PLS based model showed low specificity (40%) while DD-SIMCA showed high specificity (100%) rejecting all samples out of Slovak origin. Therefore, the results found in this study show that it is possible to successfully combine UV-VIS spectra and DD-SIMCA models to discriminate Tokaj wine samples of Slovak origin from others. Equally important is environmentally friendly (fast, simple, absence of solvents) classification method in line with green chemistry.

A fast and inexpensive approach to characterize Slovak Tokaj selection wines using infrared spectroscopy and chemometrics.

The Tokaj Selection wines (hungarian equivalent "Aszú") are typical noble sweet wines produced in Tokaj wine region that falls within two countries, Slovakia and Hungary. Taking into account the economic importance and uniqueness of these wines, in this work, a new, fast and inexpensive method that combines infrared spectroscopy and multivariate models for characterization Slovak Tokaj Selection wines was developed. At first, sample authentication via one class models (dd-SIMCA) considered Slovak Tokaj Selection wines as target class. The non-target sample was considered to be only a Tokaj sample of Slovak origin. The resulting model was able to properly recognize samples of the target class with high sensitivity and specificity. Subsequently, the putna index was predicted via PLS models. RMSEP equals 0.44; REPpred of 9.6 and R2 0.95 was found in prediction step.

Volatile composition and enantioselective analysis of chiral terpenoids in Tokaj varietal wines.

The present work compares VOC profiles of 37 Tokaj varietal wines produced from Furmint, Lipovina and Muskát zltý grape varieties determined by SPME-GC-MS. The identified VOCs underwent treatment using one-way ANOVA and PCA for determination of compounds capable to distinguish wines based on grapevine variety. The presence of high concentration of terpenoids was characteristic for Muskát zltý wines, while Furmint and Lipovina expressed quite high similarity, nevertheless Lipovina was characterized by higher relative concentration of 1,1,6-trimethyl-1,2-dihydronaphtalene. Enantioselective analysis of the dominant terpenoids (limonene, linalool, hotrienol and α-terpineol) was performed by heartcut-2D-GC: R form was dominant for limonene and linalool and S enantiomer for hotrienol and α-terpineol. Statistical analysis (ANOVA) confirmed R-linalool as the most significant compound responsible for the main differences between studied varietal wines. LDA identified both total linalool and R-linalool as the only significant (p ≤ 0.05) sorting keys to distinguish investigated varietal wines. Both models allow perfect distinguishing of Muskát zltý from Lipovina and Furmint (p ≤ 0.05) with posterior probability of re-identification 100% but low distinction of Lipovina and Furmint from each other. The probability of posterior re-identification of Lipovina raised from 76.9 to 84.6% and total probability from 86.5 to 89.2% when using dominant enantiomer concentration as sorting variable.

Enhancing supercritical fluid chromatographic efficiency: Predicting effects of small aqueous additives.

Supercritical fluid chromatography is becoming more prevalent, particularly in industry. This is due to the inexpensive, and more importantly, environmentally benign carbon dioxide that is used as the major component of the mobile phase. Water is minimally miscible with carbon dioxide at temperatures and pressures commonly used in SFC. However, the introduction of a polar alcohol modifier component increases the solubility of water in carbon dioxide. Previously, the addition of small amounts of water in the mobile phase was shown to provide significant gains in efficiency in chiral supercritical fluid chromatography, especially with polar stationary phases. In this work, we report the effect of the addition of small amounts of water on efficiency and retention factor with four different SFC stationary phases used for achiral analysis namely FructoShell-N (native cyclofructan-6), SilicaShell (bare silica), PoroShell 120 EC C18 (octadecyl silica) and Xselect C18 SB. This is the first reported use of FructoShell-N, a cyclofructan derivatized phase for SFC applications. We devised a predictive test to determine which analytes show an increase in efficiency using their known chemical constants (logKow, pKa, PSA and Hsum). We also use discriminant analysis to elucidate the most important analyte parameters that contribute to "water enhanced" efficiency gains.

Spectrophotometric Determination of Ru(IV) Using 5-Hydroxyimino-4-imino-1,3-thiazolidin-2-one as a Novel Analytical Reagent.

The interaction of Ru(IV) ions with a novel analytical reagent - 5-hydroxyimino-4-imino-1,3-thiazolidin-2-one, by spectrophotometric method was investigated. The complex is formed at pH 5.0 in acetate buffer medium after heating in the boiling water bath (~371 K) for 25 min. The complex has maximum absorption at 350 nm and is stable for 24 h. Beer's law is valid over the concentration range of 0.5-6.1 µg mL-1 for Ru(IV). The molar absorptivity at µ = 350 nm is 6.21 × 103 L mol-1 cm-1. The limit of detection of this method is 0.2 µg mL-1. The interfering effect of various cations and anions on the spectrophotometric determination of the Ru(IV) were investigated. The proposed method was successfully applied to the determination of Ru(IV) in alloys.