Application of gas chromatography–olfactometry (GC–O) in analysis and quality assessment of alcoholic beverages – A review

Identification and Screening of Trace and Multityped Solvents Using Transpiration-Driven Electrokinetic Generation Principle

Transpiration-driven electrokinetic power generators (TEPGs) hold promising potential for intelligent chemical sensing applications, enabling the efficient identification and screening of organic solvents. Here, we report a novel TEPG-based chemical sensor using MoS2-doped cellulose filter paper for efficient detection of poplar solvents like water, alcohols, and methanol. TEPGs operate by leveraging capillary-driven transpiration to induce solvent flow through porous materials, leading to ion migration and the formation of electrical double layers (EDLs) at the solid-liquid interfaces. This process generates a potential difference, enabling the conversion of the mechanical transpiration energy into electrical signals. Integrated with machine learning algorithms and IoT technologies, the sensor achieves real-time classification of the solvents. This TEPG-CS system offers enhanced sensitivity, reliability, and operational adaptability, overcoming the limitations of the traditional detection methods. This work has broad potential for environmental monitoring, industrial applications, and biomedical fields, offering another pathway for advanced solvent detection and classification systems.

Flavoromic analysis of wines using gas chromatography, mass spectrometry and sensory techniques

Various sensory perceptions drive the quality and typicality of wines, with the volatile profile playing a fundamental role in the characteristics of odor, aroma and consequently flavor, which combines the smell (odor and aroma), taste, and trigeminal sensations. Efforts have been made in both the field of instrumental and sensory analysis to understand the relationship of volatile compounds with sensory attributes in omics approaches. Gas chromatography (monodimensional and two-dimensional (heartcutting and comprehensive)) associated with mass spectrometry (GC/MS, GC-GC/MS and GCxGC/MS) and chemometric tools have contributed to foodomics analyses, specifically those linked to metabolomics/volatilomics. These tools, along with the elucidation of sensory properties (sensomics), lead to advanced results in the field of flavoromics. They also help to define the best practices in both vineyard management and winemaking that enable the production of high-quality wines. The objective of this review is to report the challenges of determining the volatile profile of wines, pointing out the ways that can be followed in successful identification and quantification of volatile compounds. The state of the art of sensory evaluation methods is also addressed, providing information that helps in choosing the most appropriate sensory method to be conducted with chromatographic analysis to achieve more in-depth results in the field of flavoromics.

Qualitative and Quantitative Sex-Related Differences in the Perception of Single Molecules from Coffee Headspace

One of the still-debated topics regarding the olfactory function concerns the presence or absence of sex-related differences in individuals. In this study, we checked for a relationship between the olfactory function of females and males and their ability to perceive single molecules, and researched how this can influence the intensity with which the complex odor formed by a set of single molecules is perceived. First, females and males were classified as normosmic or hyposmic based on the TDI olfactory score obtained using the Sniffin' Sticks test. Subsequently, the headspace of roasted coffee beans, as a complex olfactory stimulus, was broken down into single molecules by means of a chromatographic column; these were simultaneously conveyed to a mass spectrometer (for their subsequent classification) and to the human nose, which acts as a chemical sensor by means of an olfactometer port. The results obtained with this gas chromatography-olfactometry approach show both qualitative and quantitative differences between females and males, with females performing better than males. In addition, the odor intensity reported by females when sniffing pen #10, containing coffee aroma, is significantly higher than that reported by males. In conclusion, these data highlight that the human ability to perceive both single compounds and complex odors is strongly conditioned, not only by the olfactory function of individuals, but also by their sex.

Aroma determination in alcoholic beverages: Green MS-based sample preparation approaches

Aroma determination in alcoholic beverages has become a hot research topic due to the ongoing effort to obtain quality products, especially in a globalized market. Consumer satisfaction is mainly achieved by balancing several aroma compounds, which are mixtures of numerous volatile molecules enclosed in challenging matrices. Thus, sample preparation strategies for quality control and product development are required. They involve several steps including copious amounts of hazardous solvents or time-consuming procedures. This is bucking the trend of the ever-increasing pressure to reduce the environmental impact of analytical chemistry processes. Hence, the evolution of sample preparation procedures has directed towards miniaturized techniques to decrease or avoid the use of hazardous solvents and integrating sampling, extraction, and enrichment of the targeted analytes in fewer steps. Mass spectrometry coupled to gas or liquid chromatography is particularly well suited to address the complexity of these matrices. This review surveys advancements of green miniaturized techniques coupled to mass spectrometry applied on all categories of odor-active molecules in the most consumed alcoholic beverages: beer, wine, and spirits. The targeted literature consider progresses over the past 20 years.

Characterization of key odorants in 'Baimaocha' black teas from different regions

'Baimmaocha' is a distinctive resource for production of high-quality black tea, and its processed black tea has unique aroma characteristics. 190 volatile compounds were identified by comprehensive two-dimensional gas chromatography-olfactometry-quadrupole-time-of-flight mass spectrometry(GC × GC-O-Q-TOMS), and among them 23 compounds were recognized as key odorants contributing to forming different aroma characteristics in 'Baimaocha' black teas of Rucheng, Renhua, and Lingyun (RCBT, RHBT, LYBT). The odor activity value coupled with GC-O showed that methyl salicylate (RCBT), geraniol (RHBT), trans-β-ionone and benzeneacetaldehyde (LYBT) might be the most definitive aroma compounds identified from their respective regions. Furthermore, PLS analysis revealed three odorants as significant contributors to floral characteristic, four odorants related to fruity attribute, four odorants linked to fresh attribute, and three odorants associated with roasted attribute. These results provide novel insights into sensory evaluation and chemical substances of 'Baimaocha' black tea and provide a theoretical basis for controlling and enhancement tea aroma quality.

Enhancing Odor Analysis with Gas Chromatography-Olfactometry (GC-O): Recent Breakthroughs and Challenges

Gas chromatography-olfactometry (GC-O) has made significant advancements in recent years, with breakthroughs in its applications and the identification of its limitations. This technology is widely used for analyzing complex odor patterns. The review begins by explaining the principles of GC-O, including sample preparation, separation methods, and olfactory evaluation techniques. It then explores the diverse range of applications where GC-O has found success, such as food and beverage industries, environmental monitoring, perfume and aroma development, and forensic analysis. One of the major breakthroughs in GC-O analysis is the improvement in separation power and resolution of odorants. Techniques like rapid GC, comprehensive two-dimensional GC, and multidimensional GC have enhanced the identification and quantification of odor-active chemicals. However, GC-O also has limitations. These include the challenges in detecting and quantifying trace odorants, dealing with matrix effects, and ensuring the repeatability and consistency of results across laboratories. The review examines these limitations closely and discusses potential solutions and future directions for improvement in GC-O analysis. Overall, this review presents a comprehensive overview of the recent advances in GC-O, covering breakthroughs, applications, and limitations. It aims to promote the wider usage of GC-O analysis in odor analysis and related industries. Researchers, practitioners, and anyone interested in leveraging the capabilities of GC-O in analyzing complex odor patterns will find this review a valuable resource. The article highlights the potential of GC-O and encourages further research and development in the field.

Comparative key aroma compounds and sensory correlations of aromatic coconut water varieties: Insights from GC × GC-O-TOF-MS, E-nose, and sensory analysis

Aroma is a key criterion in evaluating aromatic coconut water. A comparison regarding key aroma compounds and sensory correlations was made between Thailand Aromatic Green Dwarf (THD) and Cocos nucifera L. cv. Wenye No. 4 coconut water using E-nose and GC × GC-O-TOF-MS combined with chemometrics. Twenty-one volatile components of coconut water were identified by GC × GC-O-TOF-MS, and 5 key aroma compounds were analyzed by relative odor activity value and aroma extract dilution analysis. Moreover, the combination of the E-nose with orthogonal partial least squares was highly effective in discriminating between the two coconut water samples and screened the key sensors responsible for this differentiation. Additionally, the correlation between volatile compounds and sensory properties was established using partial least squares. The key aroma compounds of coconut water exhibited positive correlations with the corresponding sensory properties.

Predicting and improving complex beer flavor through machine learning

The perception and appreciation of food flavor depends on many interacting chemical compounds and external factors, and therefore proves challenging to understand and predict. Here, we combine extensive chemical and sensory analyses of 250 different beers to train machine learning models that allow predicting flavor and consumer appreciation. For each beer, we measure over 200 chemical properties, perform quantitative descriptive sensory analysis with a trained tasting panel and map data from over 180,000 consumer reviews to train 10 different machine learning models. The best-performing algorithm, Gradient Boosting, yields models that significantly outperform predictions based on conventional statistics and accurately predict complex food features and consumer appreciation from chemical profiles. Model dissection allows identifying specific and unexpected compounds as drivers of beer flavor and appreciation. Adding these compounds results in variants of commercial alcoholic and non-alcoholic beers with improved consumer appreciation. Together, our study reveals how big data and machine learning uncover complex links between food chemistry, flavor and consumer perception, and lays the foundation to develop novel, tailored foods with superior flavors.

Development of a Fully Automated Method HS-SPME-GC-MS/MS for the Determination of Odor-Active Carbonyls in Wines: a "Green" Approach to Improve Robustness and Productivity in the Oenological Analytical Chemistry

The aim of this study was the optimization and validation of a green, robust, and comprehensive method for the determination of volatile carbonyl compounds (VCCs) in wines that could be added as a new quality control tool for the evaluation of a complete fermentation, correct winemaking style, and proper bottling and storage. A HS-SPME-GC-MS/MS method was optimized and automated using the autosampler to improve overall performance. A solvent-less technique and a strong minimization of all volumes were implemented to comply with the green analytical chemistry principles. There were as many as 44 VCC (mainly linear aldehydes, Strecker aldehydes, unsaturated aldehydes, ketones, and many other) analytes under investigation. All compounds showed a good linearity, and the LOQs were abundantly under the relevant perception thresholds. Intraday, 5-day interday repeatability, and recovery performances in a spiked real sample were evaluated showing satisfactory results. The method was applied to determine the evolution of VCCs in white and red wines after accelerated aging for 5 weeks at 50 °C. Furans and linear and Strecker aldehydes were the compounds that showed the most important variation; many VCCs increased in both classes of samples, whereas some showed different behaviors between white and red cultivars. The obtained results are in strong accordance with the latest models on carbonyl evolution related to wine aging.

Difference in Aroma Components of Black Teas Processed on Different Dates in the Spring Season

Tea aroma greatly varies with the production date. This study investigated the aroma differences among black teas processed on different dates (March 23rd, April 8th, April 15th, April 27th, and May 7th) in the spring. A sensory evaluation showed that the black tea produced on April 15th had a strong and lasting sweet aroma and the highest score of 93.5. In total, 71 volatile compounds were identified, and alcohols were the predominant category, accounting for 60.98%. From March 23rd to May 7th, the total content of volatile compounds showed a parabolic change trend and reached its maximum on April 15th (715.27 μg/L); the flavor index first peaked on April 8th (23.25) and then gradually decreased. A multivariate statistical analysis showed that 39 volatile compounds were important, differential aroma components. An odor activity value (OAV) analysis showed that the predominant odorants were β-ionone, β-damascenone, linalool, (E)-β-ocimene, and geraniol, all with values larger than 100. The total OAVs of undesirable odorants decreased and reached their minimum (70.4) on April 27th, while the total OAVs of pleasant odorants and the ratio of pleasant/undesirable odorants showed inverse changes and reached their maximum (2182.1 and 31.0, respectively) on April 27th. Based on the significance of differences and OAVs, linalool, (E)-β-ocimene, geraniol, and (E,E)-2,4-nonadienal were considered as the key differential odorants. Combined with the sensory evaluation and the differences in aroma components, it was proposed that black teas produced around April 15th in the Hunan district are more likely to have a strong and lasting sweet aroma. This study will provide scientific guidance for the production of black tea in the Hunan district, China.

Changes in the aroma and key odorants from white garlic to black garlic using approaches of molecular sensory science: A review

Black garlic is a relatively new product that has become very popular in recent years. It is obtained by fermenting raw (white) garlic by the application of heat treatment. The undesirable pungent odor of the white garlic disappears and the black garlic product with a sweet-sour flavor is formed after various reactions during the applied heat process. As a result, black garlic is more preferred and easily consumed by the consumers compared to white garlic. This review aims to summarize the studies on the changes in the odorants during the heat treatment employed in the production of black garlic as well as the factors affecting the changes in the aroma and aroma-active compounds and the use of molecular sensory science (MSS) approach, which has been applied in recent years as a new method for the determination of the aroma compounds. This work revealed that the use of the MSS on the aroma changes in black garlic is quite limited in the literature. Thus, more studies are needed to understand the aroma changes that occur during the formation of black garlic from white garlic in more detail.

Model of Neuromorphic Odorant-Recognition Network

We propose a new model for a neuromorphic olfactory analyzer based on memristive synapses. The model comprises a layer of receptive neurons that perceive various odors and a layer of "decoder" neurons that recognize these odors. It is demonstrated that connecting these layers with memristive synapses enables the training of the "decoder" layer to recognize two types of odorants of varying concentrations. In the absence of such synapses, the layer of "decoder" neurons does not exhibit specificity in recognizing odorants. The recognition of the 'odorant' occurs through the neural activity of a group of decoder neurons that have acquired specificity for the odorant in the learning process. The proposed phenomenological model showcases the potential use of a memristive synapse in practical odorant recognition applications.

Style Characteristics Investigation of Quan-Xing Baijiu by Comparing Other Strong-Aroma Baijiu Brands in China

Quan-xing Baijiu, a famous brand with different style characteristics from traditional strong-aroma Baijiu, is considered superior due to its “jiao-xiang” (caramel) flavor and the “he-run” (soft, moistening, and harmonious) style. In this study, gas chromatography-olfactometry (GC-O) was used to analyze the special flavors of Quan-xing Baijiu. The flavor fingerprints of six traditional strong-aroma Baijiu were determined using fragrance, taste, and entirety style in order to establish the individual style of Quan-xing Baijiu. The results indicated that 3-methyl butanol, ethyl butyrate, ethyl hexanoate, ethyl acetate, and ethyl caprylate were the main important aroma compound, which contributed to the he-run style in Quan-xing Baijiu. A standard of Quan-xing Baijiu’s typical style was established by flavor fingerprint. Together with the concordance rate evaluation method, this standard can help determine the characteristics of Baijiu samples for quality control. A rate above 81% represents a typical product staleness and good stability, while a rate below 73% represents a nontypical Quan-xing Baijiu product.

Assessment of the ‘taro-like’ aroma of pumpkin fruit (Cucurbita moschata D.) via E-nose, GC–MS and GC-O analysis

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E-nose and GC–MS could distinguish the different pumpkin based on aroma profiles and volatile compounds.

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It’s the first time to study the key volatile compound associated with ‘taro-like’ aroma of pumpkin fruit.

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2-Acetyl-1-pyrroline is the key contributor to the ‘taro-like’ aroma of pumpkin fruit.

‘Taro-like’ aroma is a pleasant flavor and value-added trait in pumpkin species imparted by unknown key volatile compounds. In this study, we used the electronic nose (E-nose), gas chromatography-mass spectrometry (GC–MS), and GC-Olfactometry (GC-O) to study the aroma profile, volatile compounds, and key contributors, respectively. By E-nose and GC–MS, we found significant differences in the aroma profiles and volatile compounds between fruits from five samples with/without ‘taro-like’ aroma. According to the analysis of differential volatile compounds obtained from GC–MS and the GC-O analysis of the sample with ‘taro-like’ aroma, we found that 2-acetyl-1-pyrroline representing the ‘taro’ odor was only identified in the sample with ‘taro-like’ aroma. Therefore, we conclude that 2-acetyl-1-pyrroline is the key contributor to the 'taro-like' aroma. Moreover, the relationship between 2-acetyl-1-pyrroline and ‘taro-like’ aroma was further verified via other pumpkin samples. Our results provide a theoretical basis for understanding the aroma characteristics of pumpkin fruit.

Determination of Odor Air Quality Index (OAQII) Using Gas Sensor Matrix

This article presents a new way to determine odor nuisance based on the proposed odor air quality index (OAQII), using an instrumental method. This indicator relates the most important odor features, such as intensity, hedonic tone and odor concentration. The research was conducted at the compost screening yard of the municipal treatment plant in Central Poland, on which a self-constructed gas sensor array was placed. It consisted of five commercially available gas sensors: three metal oxide semiconductor (MOS) chemical sensors and two electrochemical ones. To calibrate and validate the matrix, odor concentrations were determined within the composting yard using the field olfactometry technique. Five mathematical models (e.g., multiple linear regression and principal component regression) were used as calibration methods. Two methods were used to extract signals from the matrix: maximum signal values from individual sensors and the logarithm of the ratio of the maximum signal to the sensor baseline. The developed models were used to determine the predicted odor concentrations. The selection of the optimal model was based on the compatibility with olfactometric measurements, taking the mean square error as a criterion and their accordance with the proposed OAQII. For the first method of extracting signals from the matrix, the best model was characterized by RMSE equal to 8.092 and consistency in indices at the level of 0.85. In the case of the logarithmic approach, these values were 4.220 and 0.98, respectively. The obtained results allow to conclude that gas sensor arrays can be successfully used for air quality monitoring; however, the key issues are data processing and the selection of an appropriate mathematical model.

Effect of Chia Seed as Egg Replacer on Quality, Nutritional Value, and Sensory Acceptability of Sponge Cake

This study aimed to make a cake by incorporating chia seed flour (CSF) at 0, 3, 5, and 7% with egg replacement at 0, 25, 50, and 100%, respectively. The addition of CSF increased the total proteins, fats, and mineral contents. However, cake volume, uniformity, and symmetry were lowered significantly ( $p>0.05$ ) at an elevated level (5% and 7%) of CSF. Similarly, the cake depicted relatively higher textural hardness, springiness, cohesiveness, and chewiness upon addition of CSF. The higher substitution of CSF resulted in darker crust and crumb with lower sensory acceptability by the panelists, though the 3% CSF addition did not compromise the cake acceptance. Nonetheless, there were a significant rise in total phenolics and better antioxidant activity with CSF, measured as free radical scavenging activity. Most importantly, a massive rise in unsaturated fatty acids (ω-3, ω-6) and the simultaneous decline in total cholesterol were detected with increasing substitution of CSF.

Cholesteric Molecular Tweezer Artificial Receptor for Rapid and Highly Selective Detection of Ag+ in Food Samples

Chiral cholesteric molecular tweezer 7a was synthesized, and its recognition properties for Ag⁺, Al³⁺, Ca²⁺ etc., were investigated by UV and fluorescence spectra. The results showed that in ethanol/Tris (1/1, v/v, pH 7.0) buffer solution, the host molecular tweezer 7a had a specific recognition ability for Ag⁺, the detection limit was up to 1 × 10⁻⁶ mol/L, and other metal ions had little effect on Ag⁺ recognition. At the same time, the naked-eye detection of Ag⁺ was realized by the light red color of the complex solution. Furthermore, the mechanism of recognition of Ag⁺ by molecular tweezer 7a was studied by a nuclear magnetic titration test and computer molecular simulation, and a rapid detection method of Ag⁺ using host molecular tweezer 7a was established. Through the determination of Ag⁺ in milk powder, quinoa and other food samples, it was proved that this novel method had a good application prospect for the detection of Ag⁺ in food.

Optimization and Validation of a Headspace Solid-Phase Microextraction with Comprehensive Two-Dimensional Gas Chromatography Time-of-Flight Mass Spectrometric Detection for Quantification of Trace Aroma Compounds in Chinese Liquor (Baijiu)

The detection of trace aroma compounds in samples with complex matrices such as Chinese liquor (Baijiu) requires a combination of several methods, which makes the analysis process very complicated. Therefore, a headspace solid-phase microextraction (HS-SPME) method coupled with two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC-TOFMS) was developed for the quantitation of a large number of trace compounds in Baijiu. Optimization of extraction conditions via a series of experiments revealed that dilution of the alcohol content of 8 mL of Baijiu to 5%, followed by the addition of 3.0 g of NaCl and subsequent SPME extraction with DVB/CAR/PDMS fiber coating over 45 min at 45 °C was the most suitable. To check the matrix effects, various model Baijiu matrices were investigated in detail. The quantitative method was established through an optimized model synthetic solution, which can identify 119 aroma compounds (esters, alcohols, fatty acids, aldehydes and ketones, furans, pyrazines, sulfur compounds, phenols, terpenes, and lactones) in the Baijiu sample. The developed procedure provided high recovery (86.79–117.94%), good repeatability (relative standard deviation < 9.93%), high linearity (R² > 0.99), and lower detection limits than reported methods. The method was successfully applied to study the composition of volatile compounds in different types of Baijiu. This research indicated that the optimized HS-SPME–GC×GC-TOFMS method was a valid and accurate procedure for the simultaneous determination of different types of trace compounds in Baijiu. This developed method will allow an improved analysis of other samples with complex matrices.

Isotopic Characterization of 100% Agave Tequila (Silver, Aged and Extra-Aged Class) for Its Use as an Additional Parameter in the Determination of the Authenticity of the Beverage Maturation Time

Isotopic ratios of δ¹³C_VPDB and δ¹⁸O_VSMOW have been used as an additional parameter to ensure the authenticity of the aging time of 100% agave tequila. For this purpose, 120 samples were isotopically analyzed (40 silver class, 40 aged class, and 40 extra-aged classes). The samples were obtained through a stratified sampling by proportional allocation, considering tequila producers from the main different regions of Jalisco, Mexico (Valles 41%, Altos Sur 31%, Cienega 16%, and Centro 12%). The results showed that the δ¹³C_VPDB was found in an average of −12.85 ‰ for all the analyzed beverages, with no significant difference between them. Since for all the tested samples the Agave tequilana Weber blue variety was used as source of sugar to obtain alcohol, those results were foreseeable, and confirm the origin of the sugar source. Instead, the results for δ¹⁸O_VSMOW showed a positive slope linear trend for the aging time (silver class 19.52‰, aged class 20.54‰, extra-aged class 21.45‰), which is associated with the maturation process, there are oxidation reactions that add congeneric compounds to the beverage, these can be used as tracers for the authenticity of the aging time. Additionally, the experimental data showed homogeneity in the beverages regardless of the production region, evidencing the tequila industry’s high-quality standards. However, a particular case occurs with the δ¹⁸O_VSMOW data for the silver class samples, in which a clear trend is noted with the altitude of the region of origin; therefore, this information suggests that this analytical parameter could be useful to authenticate the regional origin of beverage.

Differences in New Zealand Hop Cultivars Based on Their Unique Volatile Compounds: An Integrated Fingerprinting and Chemometrics Approach

Hop aroma characteristics originate from hop essential oils, which have complex chemical profiles that remain poorly understood, particularly for New Zealand hops. The aim of this study was to determine volatile compounds that distinguish New Zealand hop cultivars. Untargeted fingerprinting methods based on headspace gas chromatography mass spectrometry (GC-MS) were used to analyse nine hop cultivars. A total of 61 volatile compounds were identified as compounds that differentiated the commercial hop varieties using advanced chemometrics and feature selection techniques. Similarities in volatile composition were found between Wakatu, Wai-iti™ and Kohatu^®, which are rich in alcohols. Another grouping was found between Waimea™ and Nelson Sauvin™, where ketones and esters were commonly found. Rakau™ was distinct from the other eight cultivars, distinguished by 2-methylbutyl 3-methylbutanoate and methanethiol hexanoate. Riwaka™ contained the greatest number of discriminating volatile compounds when compared to other cultivars, which was dominated by terpenoids, such as geranyl 2-methylbutanoate, perillene and D-limonene. The chemical fingerprinting approach successfully identified volatile compounds that had not been previously found in New Zealand hop cultivars and that discriminated the commercial cultivars. The data obtained in the present study further extend the knowledge of New Zealand hops and will help facilitate targeted breeding.

Comparative Evaluation of Key Aroma-Active Compounds in Sweet Osmanthus (Osmanthus fragrans Lour.) with Different Enzymatic Treatments

Sweet osmanthus (Osmanthus fragrans Lour.) (OF) is one of the ten most famous flowers in China for its unique and delicate fragrance. A combined solid-phase microextraction and solvent-assisted flavor evaporation method was used to accurately capture the overall aromatic profile and characterize the predominant odorants of fresh osmanthus with the help of gas chromatography (GC)-olfactometry and comprehensive two-dimensional GC-quadrupole time-of-flight mass spectrometry (GC × GC-QTOF-MS). Twenty-six volatiles were identified for the first time in OF. A total of 23 potent odorants, dominated by monoterpene oxides and C₆ aliphatic aldehydes, were identified. The efficacy of pectinase, β-glucosidase, and their combination on the aroma enhancement of OF was evaluated by quantitation of the target aroma components using GC-triple quadrupole-MS. The total concentration of key aroma components increased in all three enzyme treatment groups, and the increase was more significant in two β-glucosidase-treated groups. Changes in odor activity values and odor spectrum values of key odorants indicated that the pectinase-treated sample had more prominent floral, green, and potato-like scents. In contrast, the β-glucosidase-treated sample had more dominant floral, woody, almond-like, and fruity notes but less green odor, which was confirmed by sensory evaluation. β-Glucosidase and pectinase complement one another very well, and together, promote a remarkable aroma enhancement in OF.

Identification of Aroma Composition and Key Odorants Contributing to Aroma Characteristics of White Teas

The identification of aroma composition and key odorants contributing to aroma characteristics of white tea is urgently needed, owing to white tea's charming flavors and significant health benefits. In this study, a total of 238 volatile components were identified in the three subtypes of white teas using headspace solid-phase microextraction (HS-SPME) combined with comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry (GC × GC-TOFMS). The multivariate statistical analysis demonstrated that the contents of 103 volatile compounds showed extremely significant differences, of which 44 compounds presented higher contents in Baihaoyinzhen and Baimudan, while the other 59 compounds exhibited higher contents in Shoumei. The sensory evaluation experiment carried out by gas chromatography-olfactometry/mass spectrometry (GC-O/MS) revealed 44 aroma-active compounds, of which 25 compounds were identified, including 9 alcohols, 6 aldehydes, 5 ketones, and 5 other compounds. These odorants mostly presented green, fresh, floral, fruity, or sweet odors. Multivariate analyses of chemical characterization and sensory evaluation results showed that high proportions of alcohols and aldehydes form the basis of green and fresh aroma characteristic of white teas, and phenylethyl alcohol, γ-Nonalactone, trans-β-ionone, trans-linalool oxide (furanoid), α-ionone, and cis-3-hexenyl butyrate were considered as the key odorants accounting for the different aroma characteristics of the three subtypes of white tea. The results will contribute to in-depth understand chemical and sensory markers associated with different subtypes of white tea, and provide a solid foundation for tea aroma quality control and improvement.

Gas Chromatography Olfactometry (GC-O) for the (Semi)Quantitative Screening of Wine Aroma

This review discusses the different approaches developed by researchers in the last 40 years for the qualitative and semi-quantitative screening of odorants, with special emphasis in wine aroma profiling. In the first part, the aims and possibilities of Gas chromatography-olfactometry (GC-O) as odour-screening and aroma profiling technique are discussed. The critical difference between approaches is whether the ranking of odorants is carried out on an extract containing all the odorants present in the product, or on an extract representative of the odorants contained in the vapour phases that cause the odour and flavour. While the second alternative is more direct and can be more efficient, it requires a good understanding of the factors affecting orthonasal olfaction, handling volatiles (purging, trapping, eluting, and separating) and about the sensory assessment of GC effluents. The review also includes an updated list compiling all the odorants detected in wine by GC-O, including retention indexes and odour descriptions with a general guideline for the identification of odorants.

Role of gas chromatography and olfactometry to understand the wine aroma: Achievements denoted by multidimensional analysis

The human nose has been used as a detector in gas chromatography analysis to evaluate odoriferous compounds related to aroma and quality of wine. Several olfactometric techniques are available to access the description, intensity, and/or duration of the odor of each compound. Olfactometry can be associated with one-dimensional gas chromatography or multidimensional gas chromatography, including heart-cut gas chromatography and comprehensive two-dimensional gas chromatography. Multidimensional gas chromatography may help to resolve coeluted compounds and detect important trace components for the aroma. The identification of odor-active compounds may help to differentiate wines according to terroir, grapes cultivars used in winemaking or types of aging, understand the role of fungal infection of grapes for wine quality, find the best management practices in vineyard and vinification to obtain the greatest quality. In addition, when the instrumental techniques are combined with sensory analysis, even more accurate information may be obtained regarding the overall wine aroma. This review discloses the state of the art of olfactometric methods and the analytical techniques used to investigate odor-active compounds such as one-dimensional gas chromatography, multidimensional gas chromatography, and comprehensive two-dimensional gas chromatography. The advances in knowledge of wine aroma achieved with the use of these techniques in the target and profiling approaches were also discussed.

GC-MS/O for the characterization of odours from cheese-production wastewater: A case study

The foul odour of cheese-production wastewater is a common problem in areas surrounding dairy wastewater treatment plants. For successful odour management, a better understanding of the key odorants and how to handle them during wastewater treatment is needed. This paper documents the results of using gas chromatography-mass spectrometry coupled with olfactometry (GC-MS/O) to analyze odours emanating from a possibly overloaded treatment plant in Czechia. Using a DB5 capillary column, 20 compounds were detected and identified, nonanal (FD_geomean 152) and octen-3-ol (FD_geomean 2048) having the most pungent odours.

HS-SPME and SDE combined with GC-MS and GC-O for characterization of flavor compounds in Zhizhonghe Wujiapi medicinal liquor

Volatile compounds in Chinese medicinal liquor, Zhizhonghe Wujiapi (WJP liquor), were extracted by headspace-solid-phase microextraction (HS-SPME) and simultaneous distillation and extraction (SDE), respectively, and identified and quantified by gas chromatography-mass spectrometry (GC-MS) and gas chromatography-olfactometry (GC-O). Results showed that a total of 133 volatile compounds (i.e., 99 by HS-SPME, 67 by SDE, and 33 by both) including esters, alcohols, acids, aldehydes, ketones, furans, terpenes, and other miscellaneous compounds were identified by GC-MS. A total of 66 aroma active compounds were further recognized by GC-O, and 43 of them were confirmed as key aroma compounds owing to their high OAV values. After making a simulated reconstitute by mixing 31 characterized aroma compounds (OAVs ≥ 1) based on their measured concentrations, the aroma profile of the reconstitute showed a good similarity to the aroma of the original WJP liquor. Omission test further corroborated 25 key aroma-active compounds in the WJP liquor. The analysis of the volatile components of this special Chinese medicinal liquor is expected to provide some insights in terms of its quality improvement and aroma profile optimization.

Sensory active substances causing off-odour in liquid whey during storage

Liquid whey is a nutritious product with high water activity and neutral pH. Therefore, it is very susceptible to microbiological spoilage that results in undesirable off-odors. Additionally, minimally processed foods are the recent trend so setting an appropriate shelf life is essential. The commonly used microbiological methods are lengthy and time-demanding, so a quick and early identification of microbial degradation would be a significant benefit. Here we tested a solid-phase microextraction, gas chromatography with mass spectrometry coupled with olfactometry analysis (SPME-GC-MS/O) on samples of sweet unpasteurized liquid whey stored at 6 °C, 12 °C and 25 °C for a week. We compared the common methods – plate methods, measurement of pH, and dry matter determination with our proposed SPME-GC-MS/O. We have identified seven sensory active compounds while octanoic acid and a compound not reliably identified by the MS detector (with main m/z observed 133 (100), 151 (65), and 135 (26)) being the most prominent. Microbiological methods proved irreplaceable for proper setting of storage conditions (with the growth of coliforms being significant (p <0.001) at 25 °C). However, SPME-GC-MS/O was able to identify volatile substances responsible for off-odors and can be used as a powerful tool to detect the cause of undesirable chemical and microbial changes in whey beverages.

Identification of key odorants in complex mixtures occurring in nature

Covering: up to 2019Soon after the birth of gas chromatography, mass spectrometry and olfactometry were used as detectors, which allowed impressive development to be achieved in the area of odorant determinations. Since the mid-80s, structured methods of gas chromatography-olfactometry have appeared, allowing the determination of which odor constituents play a key role in materials. Progressively, numerous strategies have been proposed for sample preparation from raw materials, the representativeness evaluation of extracts, the identification of odor constituents, their quantification, and subsequently, the recombination of the key odorants to mimic the initial odor. However, the multiplicity of options at each stage of the analysis leads to a confusing landscape in this field, and thus, the present review aims at critically presenting the available options. For each step, the most frequently used alternatives are described, together with their strengths and weaknesses based on theoretical and experimental justifications according to the literature. These techniques are exemplified by many applications in the literature on aromas, fragrances and essential oils, with the initial focus on wine odorants, followed by a short overview on the molecular diversity of key odorants, which illustrates most of the facets and complexities of odor studies, including the issues raised by odorant interactions such as synergies.

Addition of yogurt to wort for the production of spirits: Evaluation of the spirit aroma over a two-year period

Triggered by the development of lactic acid bacteria (LAB) during the production of Scotch whisky, this study examined the influence of yeast and LAB inoculation on whisky flavor. Four new spirits were produced using the same process. LAB were added as a form of a Greek yogurt's live culture. In each category (barley and rye), one sample was fermented with Greek yogurt while the other was fermented without it. The spirits were matured and analyzed at five different points. Results from gas chromatography-mass spectrometry (GC-MS) analysis showed basic volatile compounds, along with some important extra compounds with yogurt culture. The most obvious differences were observed in the concentration of butanoic acid, a characteristic acid in spirits undergoing lactic acid fermentation: to identify esters such as ethyl butanoate, ethyl isobutanoate, isoamyl butanoate, and 2-phenylethyl butanoate, they are not typical compounds in whisky.

Chemical Characterization of Electronic Cigarette (e-cigs) Refill Liquids Prior to EU Tobacco Product Directive Adoption: Evaluation of BTEX Contamination by HS-SPME-GC-MS and Identification of Flavoring Additives by GC-MS-O

The present study focused on the determination of benzene, toluene, ethylbenzene and xylenes (BTEX) concentration levels in 97 refill liquids for e-cigs selected by the Italian National Institute of Health as representative of the EU market between 2013 and 2015 prior to the implementation of the European Union (EU) Tobacco Product Directive (TPD). Most of the e-liquids investigated (85/97) were affected by BTEX contamination, with few exceptions observed (levels below the limit of quantification (LOQ) of headspace-solid phase micro extraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS) methodology). Across brands, concentration levels ranged from 2.7 to 30,200.0 µg/L for benzene, from 1.9 to 447.8 µg/L for ethylbenzene, from 1.9 to 1,648.4 µg/L for toluene and from 1.7 to 574.2 µg/L for m,p,o-xylenes. The variability observed in BTEX levels is likely to be related to the variability in contamination level of both propylene glycol and glycerol and flavoring additives included. No correlation was found with nicotine content. Moreover, on a limited number of e-liquids, gas chromatography-mass spectrometry-olfactometry (GC-MS-O) analysis was performed, allowing the identification of key flavoring additives responsible of specific flavor notes. Among them, diacetyl is a flavoring additive of concern for potential toxicity when directly inhaled into human airways. The data reported are eligible to be included in the pre-TPD database and may represent a reference for the ongoing evaluation on e-liquids safety and quality under the current EU Legislation.

GC-MS Fingerprints Profiling Using Machine Learning Models for Food Flavor Prediction

Food flavor quality evaluation is attracting continuous attention, but a suitable evaluation system is severely lacking. Gas chromatography-mass spectrometry/olfactometry (GC-MS/O) is widely used to solve the food flavor evaluation problem, but the olfactometry evaluation is unfeasible to be carried out in large batches and is unreliable due to potential issue of an operator or systematic laboratory effect. Thus, a novel fingerprint modeling and profiling process was proposed based on several machine learning models including convolutional neural network (CNN). The fingerprint template was created by the data analysis of existing GC-MS spectrum dataset. Then the fingerprint image generation program was applied for structuring the complex instrumental data. Food olfactometry result was obtained by a machine learning method based on CNN using fingerprint image as the input. The case study on peanut oil samples demonstrated the model accuracy of around 93%. By structure optimization and further dataset expansion, the whole process has the potential to be utilized by sensory laboratories for aroma analysis instead of humans.

Emerging Technologies Based on Artificial Intelligence to Assess the Quality and Consumer Preference of Beverages

Beverages is a broad and important category within the food industry, which is comprised of a wide range of sub-categories and types of drinks with different levels of complexity for their manufacturing and quality assessment. Traditional methods to evaluate the quality traits of beverages consist of tedious, time-consuming, and costly techniques, which do not allow researchers to procure results in real-time. Therefore, there is a need to test and implement emerging technologies in order to automate and facilitate those analyses within this industry. This paper aimed to present the most recent publications and trends regarding the use of low-cost, reliable, and accurate, remote or non-contact techniques using robotics, machine learning, computer vision, biometrics and the application of artificial intelligence, as well as to identify the research gaps within the beverage industry. It was found that there is a wide opportunity in the development and use of robotics and biometrics for all types of beverages, but especially for hot and non-alcoholic drinks. Furthermore, there is a lack of knowledge and clarity within the industry, and research about the concepts of artificial intelligence and machine learning, as well as that concerning the correct design and interpretation of modeling related to the lack of inclusion of relevant data, additional to presenting over- or under-fitted models.

Identification and analysis of odor-active substances from PVC-overlaid MDF

This study sought to identify volatile organic compounds (VOCs) and examine the characteristics of odor-active substances from polyvinyl chloride (PVC)-overlaid medium density fiberboard (MDF). A microchamber thermal extractor was used for sampling, gas chromatography-mass spectrometry was used to identify VOCs, and gas chromatography-olfactometry-mass spectrometry was used to analyze odor-active substances from PVC-overlaid MDF over 28 days. The results showed that 38 VOCs were identified from PVC-overlaid MDF, while only 23 odor-active substances were detected by gas chromatography-olfactometry, which indicated that some VOCs did not generate odor. The main VOCs released by PVC-overlaid MDF were aromatic hydrocarbons, ketones, and esters. There was a strong correlation between concentration and odor intensity of the main VOCs. When the total amount of odor-active substances was not significantly different, the overall odor intensity was determined by the intensity of the key odorants. The greater the intensity of the key odorants, the greater the overall odor intensity. There were eight main classes of odors from PVC-overlaid MDF: aromatic, fresh scent, fruity, sour, sweet, grassy, pungent, and special scent. Among them, the main odor characteristics were aromatic, sour, and fresh scent, which were primarily generated by toluene, ethylbenzene, phenanthrene, and dibutyl phthalate.

Characterization of the Key Aroma Compounds in Aged Chinese Rice Wine by Comparative Aroma Extract Dilution Analysis, Quantitative Measurements, Aroma Recombination, and Omission Studies

The aroma compounds in young and aged Chinese rice wines (rice wines) with a clear difference in their overall aroma profiles were analyzed by comparative aroma extract dilution analysis (cAEDA). In AEDA, more aroma-active regions with flavor dilution (FD) factors of ≥64 were detected in the aged rice wine than in the young rice wine. A total of 43 odorants were further identified and quantitated. The odor activity values (OAVs) revealed 33 aroma compounds with OAVs of ≥1 in young or aged rice wine. Among these aroma compounds with relatively higher OAVs, 3-methylbutanoic acid, 1,1-diethoxyethane, vanillin, 3-methylbutanal, sotolon, benzaldehyde, 4-vinylguaiacol, methional, and 2,3-butanedione showed significant differences between young and aged rice wines. This difference was confirmed through a quantitative analysis of 34 rice wine samples with ages of 0-15 years. Then, the aroma profile of the aged rice wine was successfully simulated through an aroma recombination model. Omission models suggested that sotolon, vanillin, 3-methylbutanal, and benzaldehyde played key roles in the overall aroma of aged rice wine.

Chemical and Sensory Characterization of Cabernet Sauvignon Wines from the Chinese Loess Plateau Region

In this study, the aroma profiles of Cabernet Sauvignon wines from a new grape growing region, Loess Plateau, China, were established by gas chromatography–olfactometry, gas chromatography–mass spectrometry and sensory analysis. The sensory profiles of wines form five different young vineyards in the Loess Plateau region were obtained by descriptive analysis. Blackcurrant (p < 0.01), pear and dried plum (p < 0.05), mushroom, smoked and green pepper (p < 0.1) had significant differences on the five vineyards. A total of 76 odor-active aroma compounds were identified in the wines, and 45 volatile compounds were selected as those having the greatest impact on the aroma components and these were quantitated by five different methods. In addition, the correlation model of the Loess Plateau region’s sensory characteristics and aroma compounds was established by partial least squares regression (PLSR) to determine the influence of various aroma active substances on aroma attributes.