PLS-R Calibration Models for Wine Spirit Volatile Phenols Prediction by Near-Infrared Spectroscopy

Simultaneous Determination of Ethanol and Methanol in Wines Using FTIR and PLS Regression

Accurate quantification of ethanol and methanol is essential for regulatory compliance and product quality assurance. Fourier Transform Infrared Spectroscopy (FTIR) offers rapid, non-destructive analysis with minimal sample preparation, making it a promising tool for wine analysis. In this exploratory study, the use of FTIR and PLS regression for the simultaneous quantification of ethanol and methanol in wine samples of 11 different Portuguese mono-varietal wines and different vintages deriving from the same winery in Lisbon was investigated. A model was developed, demonstrating the feasibility of FTIR and PLS regression for the simultaneous quantification of ethanol and methanol in wine samples through dedicated models; it showed good prediction capacity for ethanol determination but poorer performance for methanol quantification. The model could be reliable enough for quality control in wine production, but to improve its performance should be enhanced in the future with more samples from different origins, wine types, and a wider concentration range in the case of methanol.

Theoretical insight of reactive oxygen species scavenging mechanism in lignin waste depolymerization products

Apart from natural products and synthesis, phenolic compounds can be produced from the depolymerization of lignin, a major waste in biofuel and paper production. This process yields a plethora of aryl propanoid phenolic derivatives with broad biological activities, especially antioxidant properties. Due to its versatility, our study focuses on investigating the antioxidant mechanisms of several phenolic compounds obtained from renewable and abundant resources, namely, syringol (Hs), 4-allylsyringol (HAs), 4-propenylsyringol (HPns), and 4-propylsyringol (HPs). Employing the density functional theory (DFT) approach in conjunction with the QM-ORSA protocol, we aim to explore the reactivity of these compounds in neutralizing hydroperoxyl radicals in physiological and non-polar media. Kinetic and thermodynamic parameter calculations on the antioxidant activity of these compounds were also included in this study. Additionally, our research utilizes the activation strain model (ASM) for the first time to explain the reactivity of the HT and RAF mechanisms in the peroxyl radical scavenging process. It is predicted that HPs has the best rate constant in both media (1.13 × 108 M-1 s-1 and 1.75 × 108 M-1 s-1, respectively). Through ASM analysis, it is observed that the increase in the interaction energy due to the formation of intermolecular hydrogen bonds during the reaction is an important feature for accelerating the hydrogen transfer process. Furthermore, by examining the physicochemical and toxicity parameters, only Hs is not suitable for further investigation as a therapeutic agent because of potential toxicity and mutagenicity. However, overall, all compounds are considered potent HOO˙ scavengers in lipid-rich environments compared to previously studied antioxidants.

The Use of a Droplet Collar Accessory Attached to a Portable near Infrared Instrument to Identify Methanol Contamination in Whisky

The aim of this study was to evaluate the ability of a droplet collar accessory attached to a portable near-infrared (NIR) instrument to characterize the artificial contamination of methanol in commercial whisky samples. Unadulterated samples (n = 12) were purchased from local bottle shops where adulterated samples were created by adding methanol (99% pure methanol) at six levels (0.5%, 1%, 2%, 3%, 4% and 5% v/v) to the commercial whisky samples (controls). Samples were analyzed using a drop collar accessory attached to a MicroNIR Onsite instrument (900-1650 nm). Partial least squares (PLS) cross-validation statistics obtained for the prediction of all levels of methanol (from 0 to 5%) addition were considered adequate when the whole adulteration range was used, coefficient of determination in cross-validation (R2cv: 0.95) and standard error in cross of validation (SECV: 0.35% v/v). The cross-validation statistics were R2cv: 0.97, SECV: 0.28% v/v after the 0.5% and 1% v/v methanol addition was removed. These results showed the ability of using a new sample presentation attachment to a portable NIR instrument to analyze the adulteration of whisky with methanol. However, the low levels of methanol adulteration (0.5 and 1%) were not well predicted using the NIR method evaluated.

FT-Raman Methodology Applied to Study the Effect of Time and Type of Seasoning in the Crafting of Sherry Casks® Used in the Aging of Brandy De Jerez

Brandy de Jerez is a grape-derived spirit produced in Southern Spain with specific characteristics that come from the casks where it is produced, which must have previously contained some type of Sherry wine for at least 12 months. These casks are known as Sherry Cask®. In this work, Brandies de Jerez aged for different aging times (0, 3, 6 and 12 months) in casks seasoned with three different types of Sherry wines (Fino, Oloroso and Amontillado) have been studied. The samples have been analyzed using FT-Raman spectroscopy, and their chemical characterization has also been realized by studying their total content of organic acid, volatile compounds, and phenolic and furanic compounds. Their chemical study showed that the main differences between the studied samples were due to the duration and the type of seasoning performed. However, the spectra obtained through FT-Raman presented noticeable differences according to cask seasoning time and the Sherry wine used for the process. A PCA (Principal Component Analysis) confirmed that the Brandies de Jerez presented significant differences depending on the seasoning time and type that the casks were subjected to. A PLS-R (Partial Least Squares Regression) study enabled establishing a close correlation between specific regions of the FT-Raman spectra and cask seasoning time.

Non-Invasive Digital Technologies to Assess Wine Quality Traits and Provenance through the Bottle

Due to increased fraud rates through counterfeiting and adulteration of wines, it is important to develop novel non-invasive techniques to assess wine quality and provenance. Assessment of quality traits and provenance of wines is predominantly undertaken with complex chemical analysis and sensory evaluation, which tend to be costly and time-consuming. Therefore, this study aimed to develop a rapid and non-invasive method to assess wine vintages and quality traits using digital technologies. Samples from thirteen vintages from Dookie, Victoria, Australia (2000–2021) of Shiraz were analysed using near-infrared spectroscopy (NIR) through unopened bottles to assess the wine chemical fingerprinting. Three highly accurate machine learning (ML) models were developed using the NIR absorbance values as inputs to predict (i) wine vintage (Model 1; 97.2%), (ii) intensity of sensory descriptors (Model 2; R = 0.95), and (iii) peak area of volatile aromatic compounds (Model 3; R = 0.88). The proposed method will allow the assessment of provenance and quality traits of wines without the need to open the wine bottle, which may also be used to detect wine fraud and provenance. Furthermore, low-cost NIR devices are available in the market with required spectral range and sensitivity, which can be affordable for winemakers and retailers and can be used with the machine learning models proposed here.

Using Vis-NIR Spectroscopy for Predicting Quality Compounds in Foods

Over the past four decades, near-infrared reflectance spectroscopy (NIRS) has become one of the most attractive and used technique for analysis as it allows for fast and simultaneous qualitative and quantitative characterization of a wide variety of food samples [...].