Multivariate Analysis Based on GC-MS Fingerprint and Volatile Composition for the Quality Evaluation of Pu-Erh Green Tea

Characterization of volatile profile from different coriander (Coriandrum sativum L.) varieties via HS-SPME/GC-MS combined with E-nose analyzed by chemometrics

Headspace-solid phase microextraction/gas chromatography-mass spectrometry (HS-SPME/GC-MS) and electronic nose (E-nose) technologies were implemented to characterize the volatile profile of aerial part from 40 coriander varieties. A total of 207 volatile compounds were identified and quantified, including aldehydes, alcohols, terpenes, hydrocarbons, esters, ketones, acids, furans, phenols and others. E-nose results showed that W5S and W2W were representative sensors responding to coriander odor. Among all varieties, the number (21-30 species) and content (449.94-1050.55 μg/g) of aldehydes were the highest, and the most abundant analytes were (Z)-9-hexadecenal or (E)-2-tetratecenal, which accounted for approximately one-third of the total content. In addition, 37 components were determined the characteristic constituents with odor activity values (OAVs) ≥ 1, mainly presenting citrusy, fatty, soapy and floral smells. Hierarchical cluster analysis (HCA) and principal component analysis (PCA) could effectively distinguish different varieties. This study provided a crucial theoretical basis for flavor evaluation and quality improvement of coriander germplasm resources.

Determination of adulteration, geographical origins, and species of food by mass spectrometry

Food adulteration, mislabeling, and fraud, are rising global issues. Therefore, a number of precise and reliable analytical instruments and approaches have been proposed to ensure the authenticity and accurate labeling of food and food products by confirming that the constituents of foodstuffs are of the kind and quality claimed by the seller and manufacturer. Traditional techniques (e.g., genomics-based methods) are still in use; however, emerging approaches like mass spectrometry (MS)-based technologies are being actively developed to supplement or supersede current methods for authentication of a variety of food commodities and products. This review provides a critical assessment of recent advances in food authentication, including MS-based metabolomics, proteomics and other approaches.

Characterization of different grades of Jiuqu hongmei tea based on flavor profiles using HS-SPME-GC-MS combined with E-nose and E-tongue

In order to distinguish different grades of Jiuqu hongmei tea (black tea), four different grades of Jiuqu hongmei tea were used as materials in this study: Super Grade (SuG), First Grade (FG), Second Grade (SG), and Third Grade (TG). HS-SPME-GC-MS combined with electronic nose (E-nose) and electronic tongue (E-tongue) technology was used to detect and analyze tea samples. The results showed that 162 volatile substances were identified, mainly alcohols, followed by hydrocarbons, aldehydes, ketones and esters. Twenty-nine volatile compounds were found in all grades of tea samples. The results of heat map analysis showed that the relative contents of five volatile compounds in different grades of Jiuqu hongmei tea were positively correlated with the grades of Jiuqu hongmei tea. By orthogonal partial least squares discriminant analysis (OPLS-DA), 35 different compounds of SuG and FG, 30 different compounds of SG and TG, 34 different compounds of FG and SG were found. Overall, the results indicated that there were significant differences in volatile compounds among different grades of Jiuqu hongmei tea, and the use of HS-SPME-GC-MS combined with E-nose and E-tongue could provide a scientific reference method as an effective tool for detecting flavor characteristics of other types of black tea grades.

Real-time gas mass spectroscopy by multivariate analysis

Early and significant results for a real-time, column-free miniaturized gas mass spectrometer in detecting target species with partial overlapping spectra are reported. The achievements have been made using both nanoscale holes as a nanofluidic sampling inlet system and a robust statistical technique. Even if the presented physical implementation could be used with gas chromatography columns, the aim of high miniaturization requires investigating its detection performance with no aid. As a study case, in the first experiment, dichloromethane (CH₂Cl₂) and cyclohexane (C₆H₁₂) with concentrations in the 6-93 ppm range in single and compound mixtures were used. The nano-orifice column-free approach acquired raw spectra in 60 s with correlation coefficients of 0.525 and 0.578 to the NIST reference database, respectively. Then, we built a calibration dataset on 320 raw spectra of 10 known different blends of these two compounds using partial least square regression (PLSR) for statistical data inference. The model showed a normalized full-scale root-mean-square deviation (NRMSD) accuracy of [Formula: see text] and [Formula: see text] for each species, respectively, even in combined mixtures. A second experiment was conducted on mixes containing two other gasses, Xylene and Limonene, acting as interferents. Further 256 spectra were acquired on 8 new mixes, from which two models were developed to predict CH₂Cl₂ and C₆H₁₂, obtaining NRMSD values of 6.4% and 13.9%, respectively.

Identification of volatile compounds and metabolic pathway during ultrasound-assisted kombucha fermentation by HS-SPME-GC/MS combined with metabolomic analysis

The current work combines headspace solid phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC/MS) with multivariate analysis fusion metabonomics for examining metabolite profile changes. The correlation with metabolic pathways during the fermentation of kombucha tea were comprehensively explored. For optimizing the fermentation process, ultrasound-assisted factors were explored. A total of 132 metabolites released by fermented kombucha were detected by HS-SPME-GC/MS. We employed the principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) to present the relationship between aroma components and fermentation time, of which the first two principal components respectively accounted for 60.3% and 6.5% of the total variance. Multivariate statistical analysis showed that during the fermentation of kombucha tea, there were significant differences in the phenotypes of metabolites in the samples, and 25 characteristic metabolites were selected as biomarkers. Leaf alcohol was first proposed as the characteristic volatile in the fermentation process of kombucha. Furthermore, we addressed the generation pathways of characteristic volatiles, their formation mechanisms, and the transformational correlation among them. Our findings provide a roadmap for future kombucha fermentation processing to enhance kombucha flavor and aroma.

Non-targeted analysis of VOCs by HS-SPME-G C/MS coupled with chemometrics as a potential tool for authentication of White Kołuda oat goose

This study tested the possibility of using non-targeted analysis of volatile organic compounds by headspace solid-phase microextraction-gas chromatography-mass spectrometry coupled with chemometrics as a potential tool for differentiating leg meat of oat- and wheat-fed (ad libitum) White Kołuda geese. Thirty-six classification models were obtained for which the correct classification rate and classification accuracy for oatfed and wheat-fed geese were calculated based on a seven-fold cross-validation. Generally, the most advantageous method of the sample preparation was the high-temperature heat treatment version, whereas the highest correct classification rate was obtained when the chemometric analysis was carried out on the female, then male, and finally male + female variant of group comparisons (P<0.01). Furthermore, log-transformation appeared to be a slightly better data preprocessing technique in comparison to systematic ratio normalization. The obtained classification models can potentially differentiate the meat of oat-fattened from wheat-fattened White Kołuda geese.

Emerging applications of nano-optical sensors combined with near-infrared spectroscopy for detecting tea extract fermentation aroma under ultrasound-assisted sonication

The current innovative work combines nano-optical sensors with near-infrared spectroscopy for rapid detection and quantification of polyphenols and investigates the potential of the nano-optical sensor based on chemo-selective colorants to detect the dynamic changes in aroma components during the fermentation of tea extract. The procedure examined the influence of different ultrasound-assisted sonication factors on the changes in the consumption rate of polyphenols during the fermentation of tea extract versus non-sonication as a control group. The results showed that the polyphenol consumption rate improved under the ultrasound conditions of 28 kHz ultrasound frequency, 24 min treatment time, and 40 W/L ultrasonic power density. The metal-organic framework based nano-optical sensors reported here have more adsorption sites for enhanced adsorption of the volatile organic compounds. The polystyrene-acrylic microstructure offered specific surface area for the reactants. Besides, the employed porous silica nanospheres with higher porosity administered improved gas enrichment effect. The nano-optical sensor exhibits good performance with a "chromatogram" for the identification of aroma components in the fermentation process of tea extract. The proposed method respectively enhanced the consumption rate of polyphenol by 35.57%, 11.34% and 16.09% under the optimized conditions. Based on the established polyphenol quantitative prediction models, this work demonstrated the feasibility of using a nano-optical sensor to perform in-situ imaging of the fermentation degree of tea extracts subjected to ultrasonic treatment.

Comprehensive Flavor Analysis of Volatile Components During the Vase Period of Cut Lily (Lilium spp. 'Manissa') Flowers by HS-SPME/GC-MS Combined With E-Nose Technology

Volatile compounds could affect the flavor and ornamental quality of cut flowers, but the flavor change occurring during the vase period of the cut flower is unclear. To clarify the dynamic changes during the vase period of cut lily (Lilium spp. 'Manissa') flowers, comprehensive flavor profiles were characterized by the electronic nose (E-nose) and headspace solid-phase microextraction gas chromatography-mass spectrometry (HS-SPME/GC-MS). The response value of sensor W2W was significantly higher than other sensors, and its response value reached the highest on day 4. A total of 59 volatiles were detected in cut lilies by HS-SPME/GC-MS, mainly including aldehydes, alcohols, and esters. There were 19 volatiles with odor activity values (OAVs) greater than 1. Floral and fruity aromas were stronger, followed by a pungent scent. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) could effectively discriminate lily samples derived from different vase times on the basis of E-nose and HS-SPME-GC-MS. In summary, our study investigates the flavor change profile and the diversity of volatile compounds during the vase period of cut lilies, and lilies on day 4 after harvest exhibited excellent aroma and flavor taking into consideration of the flavor intensity and diversity. This provided theoretical guidance for the assessment of scent volatiles and flavor quality during the vase period of cut lily flowers and will be helpful for the application of cut lilies during the postharvest process.

Mass spectrometry in food authentication and origin traceability

Food authentication and origin traceability are popular research topics, especially as concerns about food quality continue to increase. Mass spectrometry (MS) plays an indispensable role in food authentication and origin traceability. In this review, the applications of MS in food authentication and origin traceability by analyzing the main components and chemical fingerprints or profiles are summarized. In addition, the characteristic markers for food authentication are also reviewed, and the advantages and disadvantages of MS-based techniques for food authentication, as well as the current trends and challenges, are discussed. The fingerprinting and profiling methods, in combination with multivariate statistical analysis, are more suitable for the authentication of high-value foods, while characteristic marker-based methods are more suitable for adulteration detection. Several new techniques have been introduced to the field, such as proton transfer reaction mass spectrometry, ambient ionization mass spectrometry (AIMS), and ion mobility mass spectrometry, for the determination of food adulteration due to their fast and convenient analysis. As an important trend, the miniaturization of MS offers advantages, such as small and portable instrumentation and fast and nondestructive analysis. Moreover, many applications in food authentication are using AIMS, which can help food authentication in food inspection/field analysis. This review provides a reference and guide for food authentication and traceability based on MS.

The Effect of Catabolic Transformations of Proteins and Fats on the Quality and Nutritional Value of Raw Ripened Products from Zlotnicka Spotted and Zlotnicka White Meat

The aim of the study was to compare the advancement of the ripening as well as catabolic changes in proteins and fats of Zlotnicka Spotted (ZS) and Zlotnicka White (ZW) meat and their impact on the quality and nutritional value of ready-to-eat products. The meat of the breeds ZS and ZW differed not only in the basic chemical composition but also in the susceptibility to catabolic transformations of proteins and lipids, which translated into a separate technological and nutritional quality as well as the profile of volatile odor compounds. Loins due to their compact histological structure, low pH (5.4) and decreased water activity (0.92–0.93) were characterized by a lower number of coagulase-negative cocci (3.3 log cfu/g) compared to hams. The products of both breeds differed in the content of selected neutral glucogenic amino acids with a pI in the range of 5.6–6.1 mainly. The content of biogenic amines was therefore completely dependent on the metabolic potential of acidifying bacteria. Larger number of lactic acid bacilli (7.5–7.7 log cfu/g) and lactic acid cocci (7.9–8.3 log cfu/g), as well as a higher content of saturated (55.2–53.7%) and polyunsaturated fatty acids (6.4–7.0%) shaped the final pH of hams (5.3). Presence of aldehydes, ketones and alcohols indicated existing fat oxidation despite the small values of the TBA index of hams (1.1 mg/kg) and loins (0.4–0.6 mg/kg). The volatile compounds that differentiated products of ZS and ZW formed by the oxidation and microbial activity, were, primarily: octanal, 1-hydroxypropan- 2-one, 3-methylpentan-2-one, propane-1,2-diol, 2,5-dimethylfuran and 3-hydroxybutan- 2-one, butane-2,3-dione, butane-1,2-diol, respectively.

Impact of Drying Processes on the Nutritional Composition, Volatile Profile, Phytochemical Content and Bioactivity of Salicornia ramosissima J. Woods

Salicornia ramosissima J. Woods is a halophyte plant recognized as a promising natural ingredient and will eventually be recognized a salt substitute (NaCl). However, its shelf-life and applicability in several food matrices requires the use of drying processes, which may have an impact on its nutritional and functional value. The objective of this study was to evaluate the effect of oven and freeze-drying processes on the nutritional composition, volatile profile, phytochemical content, and bioactivity of S. ramosissima using several analytical tools (LC-DAD-ESI-MS/MS and SPME-GC-MS) and bioactivity assays (ORAC, HOSC, and ACE inhibition and antiproliferative effect on HT29 cells). Overall, results show that the drying process changes the chemical composition of the plant. When compared to freeze-drying, the oven-drying process had a lower impact on the nutritional composition but the phytochemical content and antioxidant capacity were significantly reduced. Despite this, oven-dried and freeze-dried samples demonstrated similar antiproliferative (17.56 mg/mL and 17.24 mg/mL, respectively) and antihypertensive (24.56 mg/mL and 18.96 mg/mL, respectively) activities. The volatile composition was also affected when comparing fresh and dried plants and between both drying processes: while for the freeze-dried sample, terpenes corresponded to 57% of the total peak area, a decrease to 17% was observed for the oven-dried sample. The oven-dried S. ramosissima was selected to formulate a ketchup and the product formulated with 2.2% (w/w) of the oven-dried plant showed a good consumer acceptance score. These findings support the use of dried S. ramosissima as a promising functional ingredient that can eventually replace the use of salt.

Use of headspace GC/MS combined with chemometric analysis to identify the geographic origins of black tea

Some black teas demand high market prices. Black tea samples (306) collected from 10 geographic origins, including China (Guxi, Likou, Jinzipai, Guichi, Dongzhi, Changning, Wuyishan, Shaowu), India (Darjeeling), and Sri Lanka (Kandy), were analyzed using headspace volatilization followed by GC/MS (HS-GC/MS). Forty-eight volatile compounds were identified. The aroma compounds were mainly identified as alcohols, aldehydes, ketones, and esters. Analysis of either full-spectrum data or 22 tea compounds shared among the samples with k-Nearest Neighbor (k-NN) and Random Forest (RF) models discriminated all origins at 100% using KNN and 95% with RF using either data set. The discrimination rates using 2 key aroma compounds (linalool and geraniol) by k-NN were 100% for nine origins, with the rate for Guxi area at 89%, because 3 samples were classified to Jinzipai. The findings support the use of HS-GC/MS combined with chemometrics as a tool to identify the origin of black tea.

Composition of Volatile Compounds in Heat-Treated Meat from Polish Native Sheep Breeds Using HS-SPME-GC/MS – Chemometric Classification Based on Breed and Age

In order to characterize the volatile compounds composition of lamb meat, 3 groups of baked leg muscle samples from two Polish native sheep breeds: Świniarka aged 9 months (S9), Wrzosówka aged 9 months (W9), and Wrzosówka aged 7 months (W7), were analyzed by HS-SPME-GC/MS, followed by multivariate statistics comprising the F-ratio method for variables pre-selection, and PCA-LDA analysis. Ninety seven volatile compounds were determined, out of which 74 were identified. The largest classes of volatile compounds were aldehydes and furans followed by alcohols, hydrocarbons, ketones, and sulfur and nitrogen compounds. Statistically significant differences between the S9, W9, and W7 groups were observed for 11 volatiles, i.e.: pentanal; hexanal; 1,3-octadiene; benzaldehyde; 3-ethyl-2-methyl-1,3-hexadiene; 3-octen-2-one; 2-octenal; 2-hexylfuran; tetradecanal; pentadecanal; hexadecanal. The HS-SPME-GC/MS method coupled with chemometrics, based on the relative intensity spectral data of these volatiles, proved to be an effective tool for the discrimination of lambs according to breed and age. The classification accuracy value for the S9, W9, and W7 groups was 100%.

Development and comprehensive HS-SPME/GC-MS analysis optimization, comparison, and evaluation of different cabbage cultivars (Brassica oleracea L. var. capitata L.) volatile components

Seven parameters of the headspace solid phase micro-extraction (HS-SPME) for extracting volatile compounds from cabbage were optimized comprehensively for the first time. A total of 75 volatiles were identified and quantified in 10 cabbage cultivars, mainly including aldehydes, hydrocarbons, esters, isothiocyanates, alcohols, ethers, nitriles and thiazoles. Dimethyl ether was the most abundant volatile. There were 24 volatiles with the odour activity values (OAVs) greater than 1 making large contributions to the cabbage flavor. Pungent aroma was the strongest odour, followed by green and fruity aromas. In short, the overall OAV of purple cabbages were generally higher than that of green cabbage. The volatile profile of 10 cabbage cultivars could be distinguished on the basis of radar fingerprint chart (RFC), hierarchical cluster analysis (HCA) and principal component analysis (PCA). Therefore, this study not only developed a feasible method to distinguish different cabbage cultivars, but also established a theoretical basis for the genetic improvement of cabbage flavor.

Color discrimination and gas chromatography-mass spectrometry fingerprint based on chemometrics analysis for the quality evaluation of Schizonepetae Spica

Schizonepetae Spica (SS), the dried spike of Schizonepeta tenuifolia Briq., is a traditional Chinese medicinal herb. According to the color of persistent calyx, SS is categorized into two classes: the yellowish-green-type and the brownish-type. Based on the chemometrics analysis of gas chromatography-mass spectrometry (GC-MS), a novel model of identifying and evaluating the quality of SS in different colors was constructed for the first time in this work. 20 batches SS samples of different colors were collected and used to extract essential oils. The average essential oils yield of SS in yellowish-green color was significantly higher than that of SS in brownish color from the same origin (p<0.05). The GC-MS fingerprints of 20 batches SS samples whose correlation coefficients were over 0.964 demonstrated SS samples were consistent to some extent in spite of slightly different chemical indexes. A total of 39 common volatiles compounds were identified. Hierarchical clustering analysis (HCA), principal component analysis (PCA) and partial least-squares discriminate analysis (PLS-DA) were developed to distinguish SS samples characterized by different colors. Consistent results were obtained to show that SS samples could be successfully grouped according to their color. Finally, 4,5,6,7-tetrahydro-3,6-dimethyl-benzofuran and pulegone were detected as the key variables for discriminating SS samples of different colors and for quality control. The obtained results proved that SS of good quality were often yellowish-green and those of poor quality were often brownish.

Comparison of volatile profiles and bioactive components of sun-dried Pu-erh tea leaves from ancient tea plants on Bulang Mountain measured by GC-MS and HPLC

To explore the volatile profiles and the contents of ten bioactive components (polyphenols and caffeine) of sun-dried Pu-erh tea leaves from ancient tea plants on Bulang Mountain, 17 samples of three tea varieties were analyzed by headspace-solid phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS) and high-performance liquid chromatography (HPLC). A total of 75 volatile components were tentatively identified. Laomaner (LME), Laobanzhang (LBZ), and other teas on Bulang Mountain (BL) contained 70, 53, and 71 volatile compounds, respectively. Among the volatile compounds, alcohols (30.2%-45.8%), hydrocarbons (13.7%-17.5%), and ketones (12.4%-23.4%) were qualitatively the most dominant volatile compounds in the different tea varieties. The average content of polyphenol was highest in LME (102.1 mg/g), followed by BL (98.7 mg/g) and LBZ (88.0 mg/g), while caffeine showed the opposite trend, 27.3 mg/g in LME, 33.5 mg/g in BL, and 38.1 mg/g in LBZ. Principal component analysis applied to both the volatile compounds and ten bioactive components showed a poor separation of samples according to varieties, while partial least squares-discriminant analysis (PLS-DA) showed satisfactory discrimination. Thirty-four volatile components and five bioactive compounds were selected as major discriminators (variable importance in projection (VIP) >1) among the tea varieties. These results suggest that chromatographic data combined with multivariate analysis could provide a useful technique to characterize and distinguish the sun-dried Pu-erh tea leaves from ancient tea varieties on Bulang Mountain.

Analysis of the Volatile Components in Selaginella doederleinii by Headspace Solid Phase Microextraction-Gas Chromatography-Mass Spectrometry

Selaginella doederleinii (SD) is a perennial medicinal herb widely distributed in China. In this study, the volatile components of SD from two regions (24 batches), namely Zhejiang and Guizhou, were determined by combining headspace solid phase microextraction and gas chromatography-mass spectrometry (HS-SPME/GC-MS). After investigating different influence factors, the optimal conditions for extraction were as follows: The sample amount of 1 g, the polydimethylsiloxane-divinylbenzene (PDMS-DVB) fiber of 65 µm, the extraction time of 20 min, and the extraction temperature of 100 °C. Based on the above optimum conditions, 58 volatiles compounds, including 20 terpenes, 11 alkanes, 3 alcohols, 6 ketones, 3 esters, 11 aldehydes, 1 ether, 1 aromatic, 1 phenol, and 1 furan, were found and identified in SD. Furthermore, hierarchical cluster analysis and principal component analysis were successfully applied to distinguish the chemical constituents of SD from two regions. Additionally, anethol, zingerone, 2,4-di-tert-butylphenol, ledene, hexyl hexanoate, α-cadinol, phytone, hinesol, decanal, octadecene, cedren, 7-tetradecene, copaene, β-humulene, 2-butyl-2-octenal, tetradecane, cedrol, calacorene, 6-dodecanone, β-caryophyllene, 4-oxoisophorone, γ-nonanolactone, 2-pentylfuran, 1,2-epoxyhexadecane, carvacrol, n-pentadecane, diisobutyl phthalate, farnesene, n-heptadecane, linalool, 1-octen-3-ol, phytane, and β-asarone were selected as the potential markers for discriminating SD from 24 habitats in Zhejiang and Guizhou by partial least squares discrimination analysis (PLS-DA). This study revealed the differences in the components of SD from different regions, which could provide a reference for the future quality evaluation.

Grade Identification of Tieguanyin Tea Using Fluorescence Hyperspectra and Different Statistical Algorithms

In order to rapidly and nondestructively identify tea grades, fluorescence hyperspectral imaging (FHSI) technology was proposed in this paper. A total of 309 Tieguanyin tea samples with three different grades were collected and the fluorescence hyperspectral data was acquired by hyperspectrometer (400 to 1000 nm). The characteristic wavelengths were respectively selected by Bootstrapping Soft Shrinkage (BOSS), Variable Iterative Space Shrinkage Approach (VISSA) and Model Adaptive Space Shrinkage (MASS) algorithms. Then, Support Vector Machine (SVM) was applied to establishing the relationship between the characteristic peaks, the full spectra, three characteristic spectra and the labels of tea grades. The results showed that VISSA-SVM model had the best classification performance, but the model precision can still be improved. Thus, Artificial Bee Colony (ABC) algorithm was introduced to optimize the parameters of SVM model. The accuracy and Kappa coefficient of test set of VISSA-ABC-SVM model were improved to 97.436% and 0.962, respectively. Therefore, the combination of fluorescence hyperspectra with VISSA-ABC-SVM model can accurately identify the grade of Tieguanyin tea. PRACTICAL APPLICATION: The rapid and accurate nondestructive tea grade identification method contributes to the construction of the tea online grade detection system. FHSI technology can solve the shortcomings of the reported methods and improved the identification accuracy of tea grades. It can be applied to the rapid detection of tea quality by tea companies, tea market, tea farmers and other demanders.

Rapidly monitoring the quality of flavoring essence based on microwave-induced plasma ionization mass spectrometry and multivariate statistical analysis

Microwave-induced plasma ionization mass spectrometry (MIPI-MS) combined with multivariate statistical analysis was first applied to rapidly monitor the quality of tobacco flavoring essence. A small isolation and reaction chamber was set up between the ion source and the injection port of mass spectrometer to effectively eliminate the interference of external environment in the process of analyzing samples. The improved experimental apparatus (MIPI-MS) could achieve online and high-throughput analysis, with minimal sample preparation steps. Further, two types of tobacco flavoring essences with the similar appearance and physicochemical parameters were employed to verify the usability of the promising method in the field of quality monitoring. Firstly, the mass spectral fingerprint of each essence was established by the improved MIPI-MS method within 2 min. Then, two multivariate statistical processes were carried out to analyze mass spectral data. The similarity results indicated that the thresholds of tobacco flavoring essences from different batches were 1.512 and 2.638, respectively. The first three principal components of the established PLS-DA described 93.6% of the total variability, and provided a visualized comparison for the two types of flavoring materials. Finally, the adulterated samples were successfully distinguished by employing the two multivariate statistical processes.

Fingerprints of volatile flavor compounds from southern stinky tofu brine with headspace solid-phase microextraction/gas chromatography-mass spectrometry and chemometric methods

It is difficult to produce southern stinky tofu, a famous traditional Chinese snack, at industry scale due to the complex composition of its brine. In this study, the fingerprints of organic volatile flavor compounds in the southern stinky tofu brine samples from five manufacturers were studied using headspace solid-phase microextraction/gas chromatography-mass spectrometry (HS-SPME/GC-MS) with the aid of chemometric methods. The fingerprints were obtained by HS-SPME/GC-MS and analyzed with the time shift alignment method, Shannon entropy, correlation coefficient, and principal component analysis. The results show that the time shifts in the samples can be accurately corrected by the time shift alignment method despite unexpected interferences. The fingerprint information was evaluated by Shannon entropy, while the similarities and differences in the fingerprints were investigated by correlation coefficient. Moreover, the identification of stinky tofu manufacturers can be achieved by principal component analysis. The predominant volatile compounds in southern stinky tofu brines were indole, 3-methylindole, phenol, and 4-methylphenol. Therefore, the established fingerprinting of volatile compounds for the brines by combining HS-SPME/GC-MS with chemometric methods was a simple and reliable method.

Identification of key aromatic compounds in Congou black tea by partial least-square regression with variable importance of projection scores and gas chromatography-mass spectrometry/gas chromatography-olfactometry

BACKGROUND

Gas chromatography-olfactometry (GC-O) is the most frequently used method to estimate the sensory contribution of single odorant, but disregards the interactions between volatiles. In order to select the key volatiles responsible for the aroma attributes of Congou black tea (Camellia sinensis), instrumental, sensory and multivariate statistical approaches were applied.

RESULTS

Using sensory analysis, nine panellists developed eight descriptors: floral, sweet, fruity, green, roasted, oil, spicy, and off-odour. Linalool, (E)-furan linalool oxide, (Z)-pyran linalool oxide, methyl salicylate, β-myrcene, and phenylethyl alcohol, which were identified from the most representative samples by the GC-O procedure, were the essential aroma-active compounds in the formation of basic Congou black tea aroma. In addition, 136 volatiles were identified by gas chromatography-mass spectrometry (GC-MS), among which 55 compounds were determined as the key factors for six sensory attributes by partial least-square regression (PLSR) with variable importance of projection scores.

CONCLUSION

Our results demonstrated that headspace solid-phase microextraction/GC-MS/GC-O was a fast approach for isolation and quantification aroma-active compounds. The PLSR method was also considered to be a useful tool in selecting important variables for sensory attributes. These two strategies, which allowed us to comprehensively evaluate the sensorial contribution of a single volatile from different perspectives, can be applied to related products for comprehensive quality control. © 2018 Society of Chemical Industry.

Rapid differentiation of Chinese hop varieties (Humulus lupulus) using volatile fingerprinting by HS-SPME-GC-MS combined with multivariate statistical analysis

BACKGROUND

Hops impart flavor to beer, with the volatile components characterizing the various hop varieties and qualities. Fingerprinting, especially flavor fingerprinting, is often used to identify 'flavor products' because inconsistencies in the description of flavor may lead to an incorrect definition of beer quality. Compared to flavor fingerprinting, volatile fingerprinting is simpler and easier.

RESULTS

We performed volatile fingerprinting using head space-solid phase micro-extraction gas chromatography-mass spectrometry combined with similarity analysis and principal component analysis (PCA) for evaluating and distinguishing between three major Chinese hops. Eighty-four volatiles were identified, which were classified into seven categories. Volatile fingerprinting based on similarity analysis did not yield any obvious result. By contrast, hop varieties and qualities were identified using volatile fingerprinting based on PCA. The potential variables explained the variance in the three hop varieties. In addition, the dendrogram and principal component score plot described the differences and classifications of hops.

CONCLUSION

Volatile fingerprinting plus multivariate statistical analysis can rapidly differentiate between the different varieties and qualities of the three major Chinese hops. Furthermore, this method can be used as a reference in other fields. © 2018 Society of Chemical Industry.

Modern analytical methods for the detection of food fraud and adulteration by food category

This review provides current information on the analytical methods used to identify food adulteration in the six most adulterated food categories: animal origin and seafood, oils and fats, beverages, spices and sweet foods (e.g. honey), grain-based food, and others (organic food and dietary supplements). The analytical techniques (both conventional and emerging) used to identify adulteration in these six food categories involve sensory, physicochemical, DNA-based, chromatographic and spectroscopic methods, and have been combined with chemometrics, making these techniques more convenient and effective for the analysis of a broad variety of food products. Despite recent advances, the need remains for suitably sensitive and widely applicable methodologies that encompass all the various aspects of food adulteration. © 2017 Society of Chemical Industry.

Analysis of Volatile Compounds by Advanced Analytical Techniques and Multivariate Chemometrics

Smelling is one of the five senses, which plays an important role in our everyday lives. Volatile compounds are, for example, characteristics of food where some of them can be perceivable by humans because of their aroma. They have a great influence on the decision making of consumers when they choose to use a product or not. In the case where a product has an offensive and strong aroma, many consumers might not appreciate it. On the contrary, soft and fresh natural aromas definitely increase the acceptance of a given product. These properties can drastically influence the economy; thus, it has been of great importance to manufacturers that the aroma of their food product is characterized by analytical means to provide a basis for further optimization processes. A lot of research has been devoted to this domain in order to link the quality of, e.g., a food to its aroma. By knowing the aromatic profile of a food, one can understand the nature of a given product leading to developing new products, which are more acceptable by consumers. There are two ways to analyze volatiles: one is to use human senses and/or sensory instruments, and the other is based on advanced analytical techniques. This work focuses on the latter. Although requirements are simple, low-cost technology is an attractive research target in this domain; most of the data are generated with very high-resolution analytical instruments. Such data gathered based on different analytical instruments normally have broad, overlapping sensitivity profiles and require substantial data analysis. In this review, we have addressed not only the question of the application of chemometrics for aroma analysis but also of the use of different analytical instruments in this field, highlighting the research needed for future focus.

Green tea flavour determinants and their changes over manufacturing processes

Flavour determinants in tea infusions and their changes during manufacturing processes were studied using Camellia sinensis cultivars 'Bai-Sang Cha' ('BAS') possessing significant floral scents and 'Fuding-Dabai Cha' ('FUD') with common green tea odour. Metabolite profiling based on odour activity threshold revealed that 'BAS' contained higher levels of the active odorants β-ionone, linalool and its two oxides, geraniol, epoxylinalool, decanal and taste determinant catechins than 'FUD' (p<0.05). Enhanced transcription of some terpenoid and catechin biosynthetic genes in 'BAS' suggested genetically enhanced production of those flavour compounds. Due to manufacturing processes, the levels of linalool and geraniol decreased whereas those of β-ionone, linalool oxides, indole and cis-jasmone increased. Compared with pan-fire treatment, steam treatment reduced the levels of catechins and proportion of geraniol, linalool and its derivatives, consequently, reducing catechin-related astringency and monoterpenol-related floral scent. Our study suggests that flavour determinant targeted modulation could be made through genotype and manufacturing improvements.

Comparative analysis of volatiles difference of Yunnan sun-dried Pu-erh green tea from different tea mountains: Jingmai and Wuliang mountain by chemical fingerprint similarity combined with principal component analysis and cluster analysis

BACKGROUND

Modern instrumental analysis technology can provide various chemical data and information on tea samples. Unfortunately, it remains difficult to extract the useful information. We describe the use of chemical fingerprint similarities, combined with principal component and cluster analyses, to distinguish and recognize Pu-erh green teas, which from two tea mountains, Wuliang and Jingmai, in the Pu-erh district of Yunnan province. The volatile components of all 20 Pu-erh green teas (10 Wuliang and 10 Jingmai teas) were extracted and identified by headspace solid-phase micro extraction (HS-SPME) combined with gas chromatography-mass spectrometry (GC-MS).

RESULTS

Sixty-three volatiles (including alcohols, hydrocarbons, ketones, and aldehydes) were identified in the 20 Pu-erh green teas, and differences in compound compositions between them were also observed. Through fingerprint similarity, combined with principal component and cluster analyses, the 20 Pu-erh green teas were differentiated successfully based on their volatile characteristics.

CONCLUSIONS

This study demonstrates that the GC-MS combined with chemical fingerprint and unsupervised pattern recognition method is suitable for the investigation of the volatile profiling and evaluating the quality and authenticity of teas related to the different origins.Graphical abstractDifferentiate Pu-erh green teas from different tea mountains by using chemical fingerprint similarity and multivariate statistical methods.

Application of gas chromatography-mass spectrometry and chemometrics methods for assessing volatile profiles of Pu-erh tea with different processing methods and ageing years

A method was developed based on head-space solid phase microextraction/gas chromatography-mass spectrometry (HS-SPME/GC-MS) combined with multivariate statistical methods to assess volatile profiles in different types of Pu-erh teas.