FTIR–ATR spectroscopy applied to quality control of grape-derived spirits

Investigation of Solid Phase Microextraction Gas Chromatography–Mass Spectrometry, Fourier Transform Infrared Spectroscopy and 1H qNMR Spectroscopy as Potential Methods for the Authentication of Baijiu Spirits

The baijiu spirit is often the focus of fraudulent activity due to the widely varying prices of the products. In this work, Solid Phase Microextraction Gas Chromatography (SPME GCMS), Fourier Transform Infrared (FTIR) Spectroscopy and 1H qNMR spectroscopy were evaluated as potential methods to authenticate baijiu samples. Data were collected for 30 baijiu samples produced by seven different distilleries. The data from the SPME GCMS and FTIR methods were treated by a Principal Component Analysis to identify clusters that would suggest chemical differences in the products from different distilleries. The results suggest that SPME GCMS has the potential to be a fully portable method for baijiu authentication. FTIR did not appear suitable for authentication but can be used to find the %ABV range of the sample. 1H quantitative NMR (1H qNMR) was utilized to quantify the ethanol concentrations and calculate the observable congener chemistry comprising ester, ethanol, methanol, fusel alcohol, and organic acids. Discrepancies in ethanol content were observed in three samples, and a lack of major congeners in two samples indicates the possible presence of a counterfeit product. Detailed and quantitative congener chemistry is obtainable by NMR and provides a possible fingerprint analysis for the authentication and quality control of baijiu style, producer, and the length of the ageing process.

Fourier transform infrared spectroscopy in monitoring the wine production

The complexity of the wine matrix makes monitoring of the winemaking process from the grapes to the final product crucial for the wine industry. In this context, analytical methodologies that can combine good accuracy, robustness, high sample throughput, “green character”, and by preference real-time analysis, are on-demand to create high-quality vitivinicultural products. In the last years, Fourier-transform Infrared Spectroscopy (FTIR) combined with chemometric analysis has been evaluated in several studies as an effective analytical tool for the wine sector. Some applications of FTIR spectroscopy have been already accepted by the wine industry, mainly for the prediction of basic oenological parameters, using portable and non-portable instruments, but still many others are waiting to be thoroughly developed. This literature review aims to provide a critical synopsis of the most important studies assessing grape and wine quality and authenticity, and to identify possible gaps for further research, meeting the needs of the modern wine industry and the expectations of most demanding consumers. The FTIR studies were grouped according to the main sampling material used - 1) leaves, stems, and berries; 2) grape must and wine applications - along with a summary of the basic limitations and future perspectives of this analytical technique.

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

Near-infrared spectroscopic (NIR) technique was used, for the first time, to predict volatile phenols content, namely guaiacol, 4-methyl-guaiacol, eugenol, syringol, 4-methyl-syringol and 4-allyl-syringol, of aged wine spirits (AWS). This study aimed to develop calibration models for the volatile phenol’s quantification in AWS, by NIR, faster and without sample preparation. Partial least square regression (PLS-R) models were developed with NIR spectra in the near-IR region (12,500–4000 cm⁻¹) and those obtained from GC-FID quantification after liquid-liquid extraction. In the PLS-R developed method, cross-validation with 50% of the samples along a validation test set with 50% of the remaining samples. The final calibration was performed with 100% of the data. PLS-R models with a good accuracy were obtained for guaiacol (r² = 96.34; RPD = 5.23), 4-methyl-guaiacol (r² = 96.1; RPD = 5.07), eugenol (r² = 96.06; RPD = 5.04), syringol (r² = 97.32; RPD = 6.11), 4-methyl-syringol (r² = 95.79; RPD = 4.88) and 4-allyl-syringol (r² = 95.97; RPD = 4.98). These results reveal that NIR is a valuable technique for the quality control of wine spirits and to predict the volatile phenols content, which contributes to the sensory quality of the spirit beverages.

Metabolomics Approaches for the Comprehensive Evaluation of Fermented Foods: A Review

Fermentation is an important process that can provide new flavors and nutritional and functional foods, to deal with changing consumer preferences. Fermented foods have complex chemical components that can modulate unique qualitative properties. Consequently, monitoring the small molecular metabolites in fermented food is critical to clarify its qualitative properties and help deliver personalized nutrition. In recent years, the application of metabolomics to nutrition research of fermented foods has expanded. In this review, we examine the application of metabolomics technologies in food, with a primary focus on the different analytical approaches suitable for food metabolomics and discuss the advantages and disadvantages of these approaches. In addition, we summarize emerging studies applying metabolomics in the comprehensive analysis of the flavor, nutrition, function, and safety of fermented foods, as well as emphasize the applicability of metabolomics in characterizing the qualitative properties of fermented foods.

Non-Invasive Monitoring of Ethanol and Methanol Levels in Grape-Derived Pisco Distillate by Vibrational Spectroscopy

Handheld Raman and portable FT-IR spectroscopy devices were evaluated for fast and non-invasive determination of methanol and ethanol levels in Peruvian Pisco. Commercial Peruvian Pisco (n = 171) samples were kindly provided by the UNALM Alliance for Research in Alcohol and its Derivatives (Lima, Peru) and supplemented by purchases at grocery and online stores. Pisco spectra were collected on handheld Raman spectrometers equipped with either a 1064 nm or a 785 nm excitation laser and a portable infrared unit operating in transmission mode. The alcohol levels were determined by GC-MS. Calibration models used partial least-squares regression (PLSR) to develop prediction algorithms. GC-MS data revealed that 10% of Pisco samples had ethanol levels lower than 38%, indicating possible water dilution. Methanol levels ranged from 10 to 130 mg/100 mL, well below the maximum levels allowed for fruit brandies. Handheld Raman equipped with a 1064 nm excitation laser gave the best results for determining ethanol (SEP = 1.2%; RPre = 0.95) and methanol (SEP = 1.8 mg/100 mL; RPre = 0.93). Randomly selected Pisco samples were spiked with methanol (75 to 2800 mg/100 mL), and their Raman spectra were collected through their genuine commercial bottles. The prediction models gave an excellent performance (SEP = 98 mg/100 mL; RPre = 0.97), allowing for the non-destructive and non-contact determination of methanol and ethanol concentrations without opening the bottles.

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.

Absorbance Spectroscopy of Heads, Hearts and Tails Fractions in Fruit Spirits

There is a large economic interest to characterize heads, hearts and tails fractions during fruit spirit distillation by simple, fast, low-volume and low-cost analytical methods. This study evaluated the potential of ultraviolet (UV)-visible-infrared spectroscopy (230–1000 nm) to characterize and differentiate these distillate fractions. Heads, hearts and tails fractions of 10 different fruit spirits were separated by sensory evaluation and investigated by absorbance spectroscopy. Principal component analysis indicated that UV spectroscopy at a wavelength range from 230 to 310 nm had the highest potential to differentiate all three distillate fractions. While all tails fractions showed significantly different UV spectra, a clear differentiation between heads and hearts fractions was limited. However, an additional UV spectroscopy of 100 mL subfractions sampled during the shift from heads to hearts in three additional distillations did reveal significant differences. The calculated integrals of the according best-fit trendline functions of the spectra indicated a trend towards reduced area-under-the-curve and zero-point values during the shift. This could be a new lead to implement an analytical method for in-line process control during fruit spirit production.

A Sensor-Based Methodology to Differentiate Pure and Mixed White Tequilas Based on Fused Infrared Spectra and Multivariate Data Treatment

Mexican Tequila is one of the most demanded import spirits in Europe. Its fast-raising worldwide request makes counterfeiting a profitable activity affecting both consumers and legal distillers. In this paper, a sensor-based methodology based on a combination of infrared measurements (IR) and multivariate data analysis (MVA) is presented. The case study is about differentiating two categories of white Tequila: pure Tequila (or ‘100% agave’) and mixed Tequila (or simply, Tequila). The IR spectra were treated and fused with a low-level approach. Exploratory data analysis was performed using PCA and partial least squares (PLS), whilst the authentication analyses were carried out with PLS-discriminant analysis (DA) and soft independent modeling for class analogy (SIMCA) models. Results demonstrated that data fusion of IR spectra enhanced the outcomes of the authentication models capable of differentiating pure from mixed Tequilas. In fact, PLS-DA presented the best results which correctly classified all fifteen commercial validation samples. The methodology thus presented is fast, cheap, and of simple application in the Tequila industry.

Apple Fermented Products: An Overview of Technology, Properties and Health Effects

As an easily adapted culture, with overloaded production in some parts of the globe, apples and their by-products are being redirected to pharmaceutical, canning and beverages industries, both alcoholic and non-alcoholic. Fermentation is generally considered to increase the bioavailability of bioactive compounds found in apple, by impacting, through a high degree of changes, the product’s properties, including composition and health-promoting attributes, as well as their sensory profile. Probiotic apple beverages and apple vinegar are generally considered as safe and healthy products by the consumers. Recently, contributions to human health, both in vivo and in vitro studies, of non-alcoholic fermented apple-based products have been described. This review highlighted the advances in the process optimization of apple-based products considering vinegar, cider, pomace, probiotic beverages and spirits’ technologies. The different processing impacts on physical-chemical, nutritional and sensory profiles of these products are also presented. Additionally, the harmful effects of toxic compounds and strategies to limit their content in cider and apple spirits are illustrated. New trends of fermented apple-based products applicability in tangential industries are summarized.

Methanol in Grape Derived, Fruit and Honey Spirits: A Critical Review on Source, Quality Control, and Legal Limits

Spirits are alcoholic beverages commonly consumed in European countries. Their raw materials are diverse and include fruits, cereals, honey, sugar cane, or grape pomace. The main aim of this work is to present and discuss the source, quality control, and legal limits of methanol in spirits produced using fruit and honey spirits. The impact of the raw material, alcoholic fermentation, and the distillation process and aging process on the characteristics and quality of the final distilled beverage are discussed. In addition, a critical view of the legal aspects related to the volatile composition of these distillates, the origin and presence of methanol, and the techniques used for quantification are also described. The methanol levels found in the different types of spirits are those expected based on the specific raw materials of each and, almost in all studies, respect the legal limits.

Application of 1H Nuclear Magnetic Resonance Spectroscopy as Spirit Drinks Screener for Quality and Authenticity Control

Due to legal regulations, the rise of globalised (online) commerce and the need for public health protection, the analysis of spirit drinks (alcoholic beverages >15% vol) is a task with growing importance for governmental and commercial laboratories. In this article a newly developed method using nuclear magnetic resonance (NMR) spectroscopy for the simultaneous determination of 15 substances relevant to assessing the quality and authenticity of spirit drinks is described. The new method starts with a simple and rapid sample preparation and does not need an internal standard. For each sample, a group of 1H-NMR spectra is recorded, among them a two-dimensional spectrum for analyte identification and one-dimensional spectra with suppression of solvent signals for quantification. Using the Pulse Length Based Concentration Determination (PULCON) method, concentrations are calculated from curve fits of the characteristic signals for each analyte. The optimisation of the spectra, their evaluation and the transfer of the results are done fully automatically. Glucose, fructose, sucrose, acetic acid, citric acid, formic acid, ethyl acetate, ethyl lactate, acetaldehyde, methanol, n-propanol, isobutanol, isopentanol, 2-phenylethanol and 5-(hydroxymethyl)furfural (HMF) can be quantified with an overall accuracy better than 8%. This new NMR-based targeted quantification method enables the simultaneous and efficient quantification of relevant spirit drinks ingredients in their typical concentration ranges in one process with good accuracy. It has proven to be a reliable method for all kinds of spirit drinks in routine food control.

Screening of Different Ageing Technologies of Wine Spirit by Application of Near-Infrared (NIR) Spectroscopy and Volatile Quantification

The traditional ageing of wine spirits is done in wooden barrels, however, high costs have led to the search for alternative technologies, such as the use of stainless steel tanks with wooden staves and the application of micro-oxygenation. This work evaluates the changes in the major volatile compounds of wine spirits aged for 6, 12 and 18 months in wooden barrels and stainless steel tanks with micro-oxygenation. For both ageing technologies, two types of wood (Limousin oak and Portuguese chestnut wood) were used. The samples were analysed concerning their alcohol strength (electronic densimetry) and volatile composition, namely of methanol, acetaldehyde, ethyl acetate and other major volatile compounds ((GC-FID) and near-infrared spectroscopy (NIR)). The results show that the ageing technology was more influential than the wood species for the volatile composition of wine spirits, namely acetaldedehyde, methanol, 2-methylpropan-1-ol and 2+3-methylbutan-1-ol. However, the opposite behaviour was found for the spectral data. The ageing process was accelerated by using the alternative ageing technology, especially with chestnut wood staves. The most informative spectral regions to discriminate samples were around 6859 cm−1 and from 5200 cm−1 to 4200 cm−1. NIR is a promising technique to identify different technologies and different wood species used in the ageing process of wine spirits.

Application of Functional Data Analysis and FTIR-ATR Spectroscopy to Discriminate Wine Spirits Ageing Technologies

Fourier transform infrared spectroscopy (FTIR) with Attenuated Total Reflection (ATR) combined with functional data analysis (FDA) was applied to differentiate aged wine spirits according to the ageing technology (traditional using 250 L wooden barrels versus alternative using micro-oxygenation and wood staves applied in 1000 L stainless steel tanks), the wood species used (chestnut and oak), and the ageing time (6, 12, and 18 months). For this purpose, several features of the wine spirits were examined: chromatic characteristics resulting from the CIELab method, total phenolic index, concentrations of furfural, ellagic acid, vanillin, and coniferaldehyde, and total content of low molecular weight phenolic compounds determined by HPLC. FDA applied to spectral data highlighted the differentiation between all groups of samples, confirming the differentiation observed with the analytical parameters measured. All samples in the test set were differentiated and correctly assigned to the aged wine spirits by FDA. The FTIR-ATR spectroscopy combined with FDA is a powerful methodology to discriminate wine spirits resulting from different ageing technologies.

FT-RAMAN methodology for the monitoring of honeys' spirit distillation process

Honey spirit is an alcoholic beverage produced by fermentation followed by distillation of the honey must, which has distinct organoleptic characteristics derived mostly from the raw material used. In order to accurately monitor the quality of the product throughout the distillation process (head, heart and tail stages), FT-RAMAN spectroscopy was applied. Dark honey, light honey and honey obtained following waxes' wash was used to produce honey spirit. The pH, alcoholic strength, methanol content, acetaldehyde content, ethyl acetate content and higher alcohols content were evaluated during the distillation process. The FT-RAMAN technique was used to obtain spectral information for all fractions collected during beverage production. The results suggest that the honey spirit had good quality concerning the volatile composition and methanol was not detected in any sample. FT-RAMAN is promising for the online monitoring of the distillation process in order to improve the final quality of this beverage.

Application of FTIR-ATR to discriminate peach nectars with higher and lower sugar contents

Abstract Fruit juice does not have the same nutritional value as fresh fruit with regards to the vitamin, mineral and dietary fibre contents and the antioxidant properties. However, it can be part of a healthy diet if it is produced with the minimal addition of sugar. This study aimed to evaluate the performance of the FTIR-ATR technique to discriminate the authenticity (concerning the addition of other pulps) and amount of sugar in peach nectars. This technique is usually used in food analysis because it does not require sample preparation, is quick and allows for the determination of several parameters with a single sample aliquot. The nutritional information provided on the labels of 69 samples of 23 different brands of commercial peach juice, was analysed. The differences in the nutritional composition and in the ingredients were determined according to an analysis of the labels. The largest differences observed between the samples were the sugar contents, the percentages of pulp and the addition of other pulps. All samples were analysed by FTIR-ATR equipped with a controlled temperature flow-through cell. The spectral multivariate analysis suggested it was possible to identify differences in the amount of sugar present and identify the presence of fruit pulps other than peach.

Chemometric assisted Fourier Transform Infrared (FTIR) Spectroscopic analysis of fruit wine samples: Optimizing the initialization and convergence criteria in the non-negative factor analysis algorithm for developing a robust classification model

The present work proposes certain optimization in the non-negative factor analysis (NNFA) algorithm to ensure an efficient analysis of the Fourier transformation infrared (FTIR) spectral data sets of the fruit wine samples. The first optimization deals with initialization of the variables in a controlled fashion that would ensure a reasonably good quality initial estimate to implement NNFA algorithm. It prevents NNFA algorithm from itinerating with random numbers that essentially have no chemical relevance. The second implemented optimization involves eliminating the alternate least square of convergence and allowing the algorithm to iterate until the iteration limit is reached. This criterion avoids the algorithm to have premature convergence and ensures that model provide the solutions which corresponds to the global minima. The application of NNFA with suggested optimizations are found to capture the subtle differences in the spectral profiles and classify the fruit wine samples that are essentially complex mixtures of several chemicals in unknown proportions. The proposed approach is also found to perform better than principal component analysis on practical grounds. In summary, the current work provides a simple, sensitive and cost-effective approach using optimized NNFA and FTIR spectroscopy for classifying the fruit wine samples.

Simultaneous Determination of Two Alcohols and One Anionic Surfactant in Commercial Liquid Cleaners Using Partial Least Square Regression by Fourier Transform Infrared Spectrometry

A simple, fast, efficient, and reagent free procedure without any chemical pretreatment has developed for simultaneous analysis of sodium lauryl ether sulfate (SLES), ethanol and isopropanol in some commercial cleaners. This determination was carried out using attenuated total reflectance Fourier transform infrared spectrometry (ATR-FTIR) and multivariate analysis. Partial least-squares (PLS) statistical method for quantitative analysis was used to determine the spectra of three components in a mixture of liquid household detergents. The statistical parameters such as Root Mean Square Error of Calibration (RMSEC), Root Mean Square Error of Cross Validation (RMSECV), Standard Errors of Prediction (SEP) and square correlation coefficient (R2) were obtained 0.07, 0.18, 0.16 (v/v%), 0.15, 0.32, 0.69 (v/v%), 0.22, 0.34, 0.57 (v/v%) and 0.9995, 0.9996 and 0.9998 for SLES, isopropanol and ethanol respectively. Good agreements were achieved between our results and the reference and standard values.

Use of FTIR spectroscopy and chemometrics for the classification of carobs origin

Carob samples from seven different Mediterranean countries (Cyprus, Greece, Italy, Spain, Turkey, Jordan and Palestine) were analyzed using Fourier Transform Infrared (FTIR) spectroscopy. Seed and flesh samples of indigenous and foreign cultivars, both authentic and commercial, were examined. The spectra were recorded in transmittance mode from KBr pellets. The data were compressed and further processed statistically using multivariate chemometric techniques, including Principal Component Analysis (PCA), Cluster Analysis (CA), Partial Least Squares (PLS) and Orthogonal Partial Least Square-Discriminant Analysis (OPLS-DA). Specifically, unsupervised PCA framed the importance of the variety of carobs, while supervised analysis highlighted the contribution of the geographical origin. Best classification models were achieved with PLS regression on first derivative spectra, giving an overall correct classification. Thus, the applied methodology enabled the differentiation of carobs flesh and seed per their origin. Our results appear to suggest that this method is a rapid and powerful tool for the successful discrimination of carobs origin and type.

Physicochemical characterization of Lavandula spp. honey with FT-Raman spectroscopy

This study aimed to evaluate the potential of FT-Raman spectroscopy in the prediction of the chemical composition of Lavandula spp. monofloral honey. Partial Least Squares (PLS) regression models were performed for the quantitative estimation and the results were correlated with those obtained using reference methods. Good calibration models were obtained for electrical conductivity, ash, total acidity, pH, reducing sugars, hydroxymethylfurfural (HMF), proline, diastase index, apparent sucrose, total flavonoids content and total phenol content. On the other hand, the model was less accurate for pH determination. The calibration models had high r² (ranging between 92.8% and 99.9%), high residual prediction deviation - RPD (ranging between 4.2 and 26.8) and low root mean square errors. These results confirm the hypothesis that FT-Raman is a useful technique for the quality control and chemical properties' evaluation of Lavandula spp honey. Its application may allow improving the efficiency, speed and cost of the current laboratory analysis.