Analysis of Scotch Whisky by 1H NMR and chemometrics yields insight into its complex chemistry

Food for Thought: Optical Sensor Arrays and Machine Learning for the Food and Beverage Industry

Arrays of cross-reactive sensors, combined with statistical or machine learning analysis of their multivariate outputs, have enabled the holistic analysis of complex samples in biomedicine, environmental science, and consumer products. Comparisons are frequently made to the mammalian nose or tongue and this perspective examines the role of sensing arrays in analyzing food and beverages for quality, veracity, and safety. I focus on optical sensor arrays as low-cost, easy-to-measure tools for use in the field, on the factory floor, or even by the consumer. Novel materials and approaches are highlighted and challenges in the research field are discussed, including sample processing/handling and access to significant sample sets to train and test arrays to tackle real issues in the industry. Finally, I examine whether the comparison of sensing arrays to noses and tongues is helpful in an industry defined by human taste.

Recent advances in whiskey analysis for authentication, discrimination, and quality control

In order to safeguard authentic whiskey products from fraudulent or counterfeit practices, high throughput solutions that provide robust, rapid, and reliable solutions are required. The implementation of some analytical strategies is quite challenging or costly in routine analysis. Qualitative screening of whiskey products has been explored, but due to the nonspecificity of the chemical compounds, a more quantitative confirmatory technique is required to validate the result of the whiskey analysis. Hence, combining analytical and chemometric methods has been fundamental in whiskey sample differentiation and classification. A comprehensive update on the most relevant and current analytical techniques, including spectroscopic, chromatographic, and novel technologies employed within the last 5 years in whiskey analysis for authentication, discrimination, and quality control, are presented. Furthermore, the technical challenges in employing these analytical techniques, future trends, and perspectives are emphasized.

NMR-Based Metabolite Profiling and the Application of STOCSY toward the Quality and Authentication Assessment of European EVOOs

Extra virgin olive oil (EVOO) possesses a high-value rank in the food industry, thus making it a common target for adulteration. Hence, several methods have been essentially made available over the years. However, the issue of authentication remains unresolved with national and food safety organizations globally struggling to regulate and control its market. Over the course of this study, the aim was to determine the origin of EVOOs suggesting a high-throughput, state-of-the-art method that could be easily adopted. A rapid, NMR-based untargeted metabolite profiling method was applied and complemented by multivariate analysis (MVA) and statistical total correlation spectroscopy (STOCSY). STOCSY is a valuable statistical tool contributing to the biomarker identification process and was employed for the first time in EVOO analysis. Market samples from three Mediterranean countries of Spain, Italy, and Greece, blended samples from these countries, as well as monocultivar samples from Greece were analyzed. The NMR spectra were collected, with the help of chemometrics acting as "fingerprints" leading to the discovery of certain chemical classes and single biomarkers that were related to the classification of the samples into groups based on their origin.

Growth of Plasmonic Nanoparticles for Aging Cask-Matured Whisky

The maturation of spirit in wooden casks is key to the production of whisky, a hugely popular and valuable product, with the transfer and reaction of molecules from the wooden cask with the alcoholic spirit imparting color and flavor. However, time in the cask adds significant cost to the final product, requiring expensive barrels and decades of careful storage. Thus, many producers are concerned with what "age" means in terms of the chemistry and flavor profiles of whisky. We demonstrate here a colorimetric test for spirit "agedness" based on the formation of gold nanoparticles (NPs) by whisky. Gold salts were reduced by barrel-aged spirit and produce colored gold NPs with distinct optical properties. Information from an extinction profile, such as peak position, growth rate, or profile shape, was analyzed, and our assay output was correlated with measurements of the whisky sample makeup, assays for key functional groups, and spiking experiments to explore the mechanism in more detail. We conclude that age is not just a number, that the chemical fingerprint of key flavor compounds is a useful marker for determining whisky "age", and that our simple reduction assay could assist in defining the aged character of a whisky and become a useful future tool on the warehouse floor.

NMR Metabolite Profiling in the Quality and Authentication Assessment of Greek Honey—Exploitation of STOCSY for Markers Identification

Honey is a natural, healthy commodity and is probably among the most complex foods produced by nature. It is the oldest recorded and certainly the only natural sweetener that can be used by humans without any further processing. Nowadays, the increase in honey’s value, along with its growing list of healthy attributes, has made the present raw material a prime target for adulteration. In the current study, NMR-based metabolite profiling in combination with chemometrics was applied in the quality control of Greek honeys from northeastern Aegean islands. Moreover, statistical total correlation spectroscopy (STOCSY) was employed for the first time as a dereplication and structural elucidation tool in the honey biomarker identification process. A total of 10 compounds were successfully identified in honey total extracts via 1H NMR spectroscopy. Compounds such as 5-(hydroxymethyl)furfural, methyl syringate, a mono-substituted glycerol derivative and 3-hydroxy-4-phenyl-2-butanone, among others, were identified as potential biomarkers related to the botanical and geographical origin of the samples. High-Resolution Mass Spectrometry (HRMS) was used as an additional verification tool on the identified compounds.

Identification of Compounds Contributing to Trigeminal Pungency of Baijiu by Sensory Evaluation, Quantitative Measurements, Correlation Analysis, and Sensory Verification Testing

Pungency is one of the most important mouthfeel characteristics that is primarily related to the sensory quality of distilled spirits. However, the chemical basis of pungency is still unclear. A set of Baijiu samples with different levels of pungency was characterized by sensory analysis and volatile compound analyses. Several esters, aldehydes, and acids significantly correlated with pungency. Ethyl hexanoate, ethyl acetate, 3-methylbutyl hexanoate, acetaldehyde, acetal, and 3-methylbutanal were confirmed to be the strongest contributors to the pungency of Baijiu by the two-alternative forced-choice test. Sensory recombination testing further revealed that the contribution of esters to pungency was much higher than that of the aldehydes, and acid compounds at low concentrations suppress the pungency perception. In this study, the importance of esters in the pungency of distilled spirits is first reported. The results provide an instructive basis for further research into optimizing the quality of products.

NMR Tracing of Food Geographical Origin: The Impact of Seasonality, Cultivar and Production Year on Data Analysis

The traceability of typical foodstuffs is necessary to protect high quality of traditional products. It is well-known that several factors could influence metabolites content in certified foods, but soil composition, altitude, latitude and coded production protocols constitute the territorial conditions responsible for the peculiar organoleptic and nutritional properties of labelled foods. Instead, regardless of origin, seasonality, cultivar, collection year can affect all agricultural products, so it is appropriate to include them in data analysis in order to obtain a correct interpretation of the differences linked to growing areas alone. Therefore, it is useful to use a flexible all-round technique, and NMR spectroscopy coupled with multivariate statistical analysis is considered a powerful means of assessing food authenticity. The purpose of this review is to investigate the relevance of year, cultivar, and seasonal period in the determination of food geographical origin using NMR spectroscopy. The strategy for testing these three factors may differ from author to author, but a preliminary study of cultivar or collection year effects on NMR spectra is the most popular method before starting the geographical characterization of samples. In summary, based on the available literature, the most significant influence is due to cultivar, followed by harvesting year, however seasonality is not considered a source of variability in data analysis.

Antifungal Activity against Fusarium oxysporum of Botanical End-Products: An Integration of Chemical Composition and Antifungal Activity Datasets to Identify Antifungal Bioactives

Plants produce various compounds as defensive barriers to naturally control fungal diseases. Among them, vascular wilt caused by Fusarium oxysporum is one of the most destructive diseases in crops, causing relevant economic losses. The application of synthetic fungicides is the most used management for this disease. However, this kind of method also involves adverse environmental impacts. Therefore, alternative methods are continuously being developed as a strategy to be involved in integrated pest management programs. Thus, as part of our research on antifungals of plant origin, a group of botanical extracts was assessed for the respective inhibitory effect on mycelium and conidia of F. oxysporum. Mycelial growth inhibition was measured in 12-well plates containing amended semi-solid medium, whereas conidial susceptibility was determined through microdilution. The identification of the bioactive compounds among test extracts was performed using an indirect approach, consisting of the integration of chemical composition and antifungal activity datasets through single-Y orthogonal partial least squares (OPLS) regression. Results showed that Piper aduncum extract was the most potent mycelial growth inhibitor whereas P. elongatum exhibited the best effect on conidia susceptibility. The active compounds identified through statistical integration and subsequent isolation were piperaduncin C, asebogenin and (-)-methyllinderatin. These findings indicated that the integrative, indirect approach is useful for the identification of bioactive metabolites from botanical extracts to be further used as biological protective agents against this phytopathogen.

A flavoromics strategy for the differentiation of different types of Baijiu according to the non-volatile organic acids

Non-volatile organic acids (NVOAs) in 12 main flavor types of Baijiu were analyzed by a derivatization method combined with GC-MS and 38 NVOAs were quantified. Meanwhile, a flavoromics strategy based on the contents of NVOAs in the 12 flavor types of Baijiu was successfully used to the differentiation of Baijiu. PLS-DA models (explained variation, predictive capability) were used to consider different categories: fermentation process (0.931, 0.870), starter (0.921, 0.834), fermentation container (0.899, 0.810) and raw material (0.951, 0.909). Based on the selected categories, suitable separations were achieved, and the classification ability of these models were nearly 100%. As a result, the model demonstrated its ability to perfectly distinguish different types of Baijiu. Seventeen potential markers were identified by variable importance in projection method and were further processed using heatmap and hierarchical cluster analysis, indicating that the NVOAs had great discrimination power to differentiate Baijiu.

Recent advances in NMR-based metabolomics of alcoholic beverages

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NMR-based techniques can be used for establishing metabolic “fingerprint” .

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Biomarkers for discrimination of wine varietals were identified.

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COSY and DOSY techniques may aid in assigning phenolic compounds and disaccharides.

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NMR-based metabolomic studies of alcoholic beverages remain limited in Asia.

Alcoholic beverages have a complex chemistry that can be influenced by their alcoholic content, origin, fermentation process, additives, and contaminants. The complex composition of these beverages leave them susceptible to fraud, potentially compromising their authenticity, quality, and market value, thus increasing risks to consumers’ health. In recent years, intensive studies have been carried out on alcoholic beverages using different analytical techniques to evaluate the authenticity, variety, age, and fermentation processes that were used. Among these techniques, NMR-based metabolomics holds promise in profiling the chemistry of alcoholic beverages, especially in Asia where metabolomics studies on alcoholic beverages remain limited.

Comparative NMR Metabolomics Profiling between Mexican Ancestral & Artisanal Mezcals and Industrialized Wines to Discriminate Geographical Origins, Agave Species or Grape Varieties and Manufacturing Processes as a Function of Their Quality Attributes

The oenological industry has benefited from the use of Nuclear Magnetic Resonance (¹H-NMR) spectroscopy in combination with Multivariate Statistical Analysis (MSA) as a foodomics tool for retrieving discriminant features related to geographical origins, grape varieties, and further quality controls. Said omics methods have gained such attention that Intergovernmental Organizations and Control Agencies are currently recommending their massive use amongst countries as quality compliances for tracking standard and degradation parameters, fermentation products, polyphenols, amino acids, geographical origins, appellations d’origine contrôlée and type of monovarietal strains in wines. This study presents, for the first time, a ¹H-NMR/MSA profiling of industrial Mexican wines, finding excellent statistical features to discriminate between oenological regions and grape varieties with supervised Orthogonal Projections to Latent Structures Discriminant Analysis (OPLS-DA). In a comparative way, it is applied with the ¹H-NMR/OPLS-DA workflow for the first time in ancestral and artisanal Mexican mezcals with promising results to discriminate between regions, agave species and manufacturing processes. The central aim of this comparative study is to extrapolate the know-how of wine-omics into the non-professionalized mezcal industry for establishing the NMR acquisition, preprocessing and statistical analysis basis to implement novel, non-invasive and highly reproducible regional, agave species and manufacturing-quality controls.

Through-bottle whisky sensing and classification using Raman spectroscopy in an axicon-based backscattering configuration

Non-intrusive detection systems have the potential to characterise materials through various transparent glass and plastic containers. Food and drink adulteration is increasingly problematic, representing a serious health risk as well as an economic issue. This is of particular concern for alcoholic spirits such as Scotch whisky which are often targeted for fraudulent activity. We have developed a Raman system with a novel geometry of excitation and collection, exploiting the beam propagation from an axicon lens, which results in an annular beam at the bottle surface before focusing within the sample. This facilitates the efficient acquisition of Raman signals from the alcoholic spirit contained inside the bottle, while avoiding the collection of auto-fluorescence signals generated by the bottle wall. Therefore, this technique provides a way of non-destructive and non-contact detection to precisely analyse the contents without the requirement to open the bottle.

Effects of solutes on the alcohol-stimulative taste of vodkas

Quantitative analyses of chemical components and sensory tests were carried out on vodka samples to test for stimulative taste of ethanol. Proton nuclear magnetic resonance (¹H NMR) spectra of the vodkas were measured with 600 MHz NMR. The effects of salts on the alcohol-stimulative taste were investigated for 15% (v/v) EtOH-H₂O solution. ¹H NMR spectroscopy results showed that a magnesium salt could reduce the stimulative taste of ethanol organoleptically and, at the same time, strengthen the hydrogen-bonding structure of water-ethanol, although the effect of the magnesium could not be clarified quantitatively in the products of vodka. It was also suggested that a change in the water-ethanol hydrogen-bonding structure could lead to a reduction in the stimulative taste of ethanol in vodka.

NMR-Based Metabolic Profiling of Edible Olives-Determination of Quality Parameters

Edible olive drupes (from Olea europaea L.) are a high-value food commodity with an increasing production trend over the past two decades. In an attempt to prevent fraud issues and ensure quality, the International Olive Council (IOC) issued guidelines for their sensory evaluation. However, certain varieties, geographical origins and processing parameters are omitted. The aim of the present study was the development of a method for the quality assessment of edible olives from the Konservolia, Kalamon and Chalkidikis cultivars from different areas of Greece processed with the Spanish or Greek method. A rapid NMR-based untargeted metabolic profiling method was developed along with multivariate analysis (MVA) and applied for the first time in edible olives' analysis complemented by the aid of statistical total correlation spectroscopy (STOCSY). Specific biomarkers, related to the classification of olives based on different treatments, cultivars and geographical origin, were identified. STOCSY proved to be a valuable aid towards the assignment of biomarkers, a bottleneck in untargeted metabolomic approaches.