Untargeted metabolomic analysis of Chinese red wines for geographical origin traceability by UPLC-QTOF-MS coupled with chemometrics

Wine metabolome and sensory analyses demonstrate the oenological potential of novel grapevine genotypes for sustainable viticulture in warm climates

BACKGROUND

Genetic breeding is essential to develop grapevine genotypes adapted to warm climates and resistant to pathogens. Traditionally cultivated Vitis vinifera is susceptible to biotic and abiotic stresses. Winemakers and consumers, however, perceive wines from non-vinifera or hybrid cultivars as inferior. In this study, sensory analyses and comprehensive metabolite profiling by targeted and untargeted approaches were used to investigate the oenological potential of wines from grapes of genotypes developed throughout four breeding cycles to improve climate adaptation, sugar contents and berry color.

RESULTS

Novel genotypes had higher yields and the wines exhibited increased contents of polyphenols, including anthocyanins. Volatile monoterpenes in the wines decreased throughout breeding cycles in the absence of selective pressure. Polyphenol contents were higher in intermediate wines, with hydroxytyrosol contents reaching up to three times reported values. Mouthfeel attributes astringency, leafy taste, flavor and body, and persistency showed significant correlation with untargeted features. Supervised model-based analyses of the metabolome effectively discriminate wines from distinct genetic origins.

CONCLUSION

Taken together, the results demonstrate the potential of novel grapevine genotypes to a more sustainable viticulture and quality wine production in warm climates. Comprehensive metabolite profiling of the wines reveals that genotype clustering is dependent on the chemical class and that traits not submitted to selective pressure are also altered by breeding. Supervised multivariate models were effective to predict the genetic origin of the wines based on the metabolic profile, indicating the potential of the technique to identify biomarkers for wines from sustainable genotypes. © 2024 Society of Chemical Industry.

Unbiased Metabolomic and Chemometric profiles of three Sargassum polycystum extracts using GCMS and LCMS/MS: content analysis, correlation analysis and molecular docking

Sargassum polycystum (S. polycystum) is a brown macroalga with a high phytochemical content, making it a nutritious and bioactive food source. However, information on factors contributing to health benefits, like antioxidants and cytotoxicity, is less explored for Malaysian S. polycystum. In this study, three extracts of S. polycystum were characterized using a combination of analytical techniques. Despite similar carbohydrate content across all extracts, water extract exhibited the highest protein [21.90 ± 1.01 albumin equivalent (μg/mg)] and phenolic [7.73 ± 1.95 gallic acid equivalent (μg/mg)] contents. However, it displayed the lowest antioxidant and anticancer activities [half-maximal inhibitory concentration (IC50) of > 2000 μg/mL]. Interestingly, ethanolic extract demonstrated the strongest scavenging activity (IC50 of 397.90 ± 20.43 μg/mL) and selective anticancer activity against MCF7 breast cancer cells (IC50 of 338.63 ± 48.98 μg/mL). Untargeted metabolomic profiling confirmed the differences in the chemical composition of the extracts. Subsequently, correlation and docking analyses were used to identify the potential bioactive compounds within the extracts. The ethanolic extract is a rich source of these bioactive compounds with superior antioxidant and anticancer properties, highlighting the need for further research on its potential utility in the food industry.

Revealing the key antioxidant compounds and potential action mechanisms of Chinese Cabernet Sauvignon red wines by integrating UHPLC-QTOF-MS-based untargeted metabolomics, network pharmacology and molecular docking approaches

In recent years, red wine drinking has become more popular in China owing to its antioxidant effects. However, the key antioxidant compounds and their action mechanisms of Chinese red wines are still unclear. Herein, the antioxidant activities and chemical compositions of 45 Chinese Cabernet Sauvignon red wine samples were determined using chemical antioxidant assays and an UHPLC-QTOF-MS-based untargeted metabolomics method. The key antioxidant compounds in red wines and potential action mechanisms were revealed by integrating network pharmacology and molecular docking approaches. Results showed that there are 8 key antioxidant compounds in the red wine samples. These compounds are involved in several metabolic pathways in the body, particularly PI3K/AKT. What's more, they bind to the core antioxidant targets through hydrogen bonding and hydrophobic interaction. Among them, myricetin, laricitrin, 2,3,8-tri-O-methylellagic acid and AKT1 have the highest binding energies. This study could provide the theoretical basis for further investigation of physiological activities and functions of Chinese red wines.

Metabolomics analysis of physicochemical properties associated with quality deterioration in insect-infested hawthorn berries

The sliced and dried hawthorn berries are easily infested by insects during storage. This study aimed to determine the effect of insect infestation on the quality of hawthorn berries and assess the change at metabolite level by analyzing physicochemical property and metabolomics profiling. A total of 184 shared differential metabolites were obtained, mainly including flavonoids, fatty acids, carboxylic acids and derivatives, and nitrogenous compounds. Through receiver operating characteristic curve assessment, 9 significant differential markers were screened out to distinguish insect infestation of hawthorn berries. Correlation analysis showed that the color, total organic acids, total phenolics, and total flavonoids were effective indicators for quality evaluation of insect infestation, and uric acid and hippuric acid can serve as biomarkers for the quality deterioration of hawthorn berries during storage. This study demonstrated that insect infestation could decrease the quality of hawthorn berries from macro and micro perspectives.

Aroma Identification and Traceability of the Core Sub-Producing Area in the Helan Mountain Eastern Foothills Using Two-Dimensional Gas Chromatography and Time-of-Flight Mass Spectrometry and Chemometrics

The combination of volatile compounds endows wines with unique aromatic characteristics and is closely related to their geographical origins. In the pursuit of origin identification and the subdivision of homogeneous production areas, clarifying the characteristics of production areas is of great significance for improving wine quality and commercial value. In this study, GC×GC-TOFMS technology was used to analyze the aroma characteristics of "Cabernet Sauvignon" wines from 26 wineries in the Helan (HL), Yinchuan (YC), Yongning (YN), Qingtongxia (QTX), and Hongsibu (HSP) sub-producing areas in the eastern foothills of Helan Mountain in Ningxia, China. The results indicate a gradual increase in relative humidity from the southern part of Ningxia, with the YN sub-region showing optimal fruit development and the QTX region having the highest maturity. A total of 184 volatile compounds were identified, with 36 compounds with an OAV > 1, crucial for the aroma profiles of primarily fermentation-derived alcohols and esters. An aromatic vector analysis revealed that "floral" and "fruity" notes are the primary characteristics of Cabernet Sauvignon wines from the Helan Mountain East region, with lower maturity aiding in the retention of these aromas. By constructing a reliable OPLS-DA model, it was determined that 15 substances (VIP > 1) played a crucial role in identifying production areas, among which phenylethyl alcohol and isoamyl alcohol were the main contributors. In addition, a Pearson correlation analysis showed a negative correlation between sunlight duration during the growing season and benzyl alcohol accumulation, while a significant positive correlation was observed during the ripening period. Due to the critical role of phenyl ethanol in identifying producing areas, this further demonstrates that sunshine conditions may be a key factor contributing to the differences in wine flavor across regions. This study offers a theoretical foundation for understanding the relationship between climatic factors and flavor characteristics, addressing the issue of wine homogenization in small production areas, clarifying typical style characteristics, and establishing a traceability technology system based on characteristic aroma.

Phenolic metabolites changes during baijiu fermentation through non-targeted metabonomic

To investigate the changes of phenolic metabolite during different grains fermentation stages of Chinse Baijiu, the ultra-performance liquid chromatography-quadrupole time of-flight mass spectrometry (UHPLC-QTOF-MS) was applied to identify and analyze the different phenolic metabolites, combined with principal component analysis and partial least squares discriminant analysis. Results indicated that significant differences in phenolic metabolites during different fermentation stages were found. Among the 231 phenolic metabolites detected, 36, 31, 19, 23, 14, and 50 differential phenolic metabolites were screened between different groups using partial least squares discriminant analysis. Twelve metabolic pathways with high correlation of differential phenolic metabolites and 23 main participating differential metabolites were identified through KEGG metabolic pathway enrichment analysis. The present study preliminarily revealed the differences of phenolic metabolites at different fermentation stages, and providing a theoretical basis for the further improving of the taste and quality of Chinese Baijiu.

HS-SPME-GC-MS untargeted metabolomics reveals key volatile compound changes during Liupao tea fermentation

This study used headspace solid-phase microextraction-gas chromatography-mass spectrometry and multivariate statistical analysis to comprehensively analyze the volatile components in Liupao tea samples throughout fermentation. In total, 1009 volatile organic compounds were detected and identified, including terpenoids, heterocyclic compounds, esters, ketones, hydrocarbons, alcohols, aromatics, and acids. Principal component and hierarchical cluster analyses, characterize the volatile components of Liupao tea samples were characterized at various fermentation stages. Orthogonal partial least squares discriminant analysis identified 248 differentiating compounds (VIP ≥ 1, P < 0.05, and |Log2FC| ≥ 1.0) during fermentation. K-means clustering analysis showed that 11 metabolites increased significantly throughout the fermentation process, whereas 31 metabolites decreased continuously. Annotation of these differential compounds revealed significant changes in sensory flavor characteristics in "green, sweet, fruity, floral, and woody" flavors. The results demonstrated significant variations in the volatile components of Liupao tea fermentation, along with notable changes in flavor characteristics.

Discrimination and prediction of Qingzhuan tea storage year using quantitative chemical profile combined with multivariate analysis: Advantages of MRMHR based targeted quantification metabolomics

The duration of storage significantly influences the quality and market value of Qingzhuan tea (QZT). Herein, a high-resolution multiple reaction monitoring (MRMHR) quantitative method for markers of QZT storage year was developed. Quantitative data alongside multivariate analysis were employed to discriminate and predict the storage year of QZT. Furthermore, the content of the main biochemical ingredients, catechins and alkaloids, and free amino acids (FAA) were assessed for this purpose. The results show that targeted marker-based models exhibited superior discrimination and prediction performance among four datasets. The R2Xcum, R2Ycum and Q2cum of orthogonal projection to latent structure-discriminant analysis discrimination model were close to 1. The correlation coefficient (R2) and the root mean square error of prediction of the QZT storage year prediction model were 0.9906 and 0.63, respectively. This study provides valuable insights into tea storage quality and highlights the potential application of targeted markers in food quality evaluation.

Geographical identification of Chinese wine based on chemometrics combined with mineral elements, volatile components and untargeted metabonomics

Identifying the geographic origin of a wine is of great importance, as origin fakery is commonplace in the wine industry. This study analyzed the mineral elements, volatile components, and metabolites in wine using inductively coupled plasma-mass spectrometry, headspace solid phase microextraction gas chromatography-mass spectrometry, and ultra-high-performance liquid chromatography-quadrupole-exactive orbitrap mass spectrometry. The most critical variables (5 mineral elements, 13 volatile components, and 51 metabolites) for wine origin classification were selected via principal component analysis and orthogonal partial least squares discriminant analysis. Subsequently, three algorithms-K-nearest neighbors, support vector machine, and random forest -were used to model single and fused datasets for origin identification. These results indicated that fused datasets, based on feature variables (mineral elements, volatile components, and metabolites), achieved the best performance, with predictive rates of 100% for all three algorithms. This study demonstrates the effectiveness of a multi-source data fusion strategy for authenticity identification of Chinese wine.

Metabolomics analysis based on UHPLC-QqQ-MS/MS to discriminate grapes and wines from different geographical origins and climatological characteristics

With the proliferation of the consumer's awareness of wine provenance, wines with unique origin characteristics are increasingly in demand. This study aimed to investigate the influence of geographical origins and climatological characteristics on grapes and wines. A total of 94 anthocyanins and 78 non-anthocyanin phenolic compounds in grapes and wines from five Chinese viticultural vineyards (CJ, WH, QTX, WW, and XY) were identified by UHPLC-QqQ-MS/MS. Chemometric methods PCA and OPLS-DA were established to select candidate differential metabolites, including flavonols, stilbenes, hydroxycinnamic acids, peonidin derivatives, and malvidin derivatives. CCA showed that malvidin-3-O-glucoside had a positive correlation with mean temperature, and quercetin-3-O-glucoside had a negative correlation with precipitation. In addition, enrichment analysis elucidated that the metabolic diversity in different origins mainly occurred in flavonoid biosynthesis. This study would provide some new insights to understand the effect of geographical origins and climatological characteristics on phenolic compounds in grapes and wines.

GC/MS-based untargeted metabolomics reveals the differential metabolites for discriminating vintage of Chenxiang-type baijiu

The "outstanding and unique aged aroma" of Chinese Chenxiang-type baijiu (CXB)-Daoguang 25 (DG25) mainly originates from a "extraordinary storage technology" of Mujiuhai (a wooden container), so it is mysterious and interesting. In this study, an untargeted GC/MS-based metabolomics was used to reveals the volatile differential metabolites for discriminating six different vintages of DG25 combing with chemometrics. A total of 100 volatile metabolites (including unknowns) were extracted and identified, including esters (41%), alcohols (10%) and acids (7%) so on. Finally, 33 differential metabolites were identified as aging-markers. Among them, 25 aging-markers showed a downtrend, including 17 esters such as ethyl acetate, ethyl hexanoate and ethyl palmitate so on. Moreover, it was interesting and to further study that furans showed a significant downtrend. Statistically speaking, ethyl benzoate played an important role in discriminating vintage of 1Y and 3Y, and the other 24 differential metabolites with downtrend discriminating the unstored (0Y-aged) DG25. Eight differential metabolites, such as ethyl octanoate, benzaldehyde, 3-methylbutanol and 1,1-diethoxyaccetal so on increased during aging of DG25, and they played a statistical role in discriminating the 5Y-, 10Y- and 20Y-aged DG25. This study provides a theoretical basis way for the formation mechanism of aging aroma for CXB.

Tracing the geographical origin of endangered fungus Ophiocordyceps sinensis, especially from Nagqu, using UPLC-Q-TOF-MS

Ophiocordyceps sinensis (OS), known as "soft gold", played an important role in local economic development. OS from different producing areas was difficult to be discriminated by the appearance. Nagqu OS, a distinguished and safeguarded geographical indication product, commands a premium price in market. The real claim of OS geographical origins is urgently required. Here, 81 OS samples were collected from Tibetan Plateau in China to explore markers for tracing origins. OS from Xigazê can be distinguished by dark color of head of caterpillar. Then 57 samples, a fully representative training-sample set, were used to set up OPLS-DA models by nontargeted metabolomics from UPLC-QTOF-MS. Certain markers were successfully identified and validation using 21 blind test samples confirmed that the markers can trace the geographical origin of OS, especially Nagqu samples. It was affirmed that UPLC-QTOF-MS-based untargeted metabolomics coupled with OPLS-DA was a reliable strategy to trace the geographical origins of OS.

A comparative UHPLC-QTOF-MS/MS-based metabolomics approach reveals the metabolite profiling of wolfberry sourced from different geographical origins

Wolfberry, known as Goji berry, is the fruit of Lycium barbarum L. (LB). As a famous functional food and TCM, the cost and efficacy of LB are closely linked to its geographical origin. The present study aimed to establish an effective method for distinguishing LB from different geographical origins. By employing UHPLC-QTOF-MS/MS combined with multivariate analysis, the metabolite profiling of LB (199 batches) obtained from Ningxia, Gansu, Qinghai, and Xinjiang, was evaluated. The results demonstrated that the method effectively distinguished LB from the four regions, with a total of 148 different metabolites being detected. Subsequent assessment using heat maps, Venn analysis, receiver operating characteristics curves and dot plots revealed 21 of these metabolites exhibited exceptional sensitivity and specificity, with under-curve values approaching 1, thus indicating their potential as biomarkers for LB. These findings strongly support the suitability of UHPLC-QTOF-MS/MS-based metabolomics as an effective approach to identify the source of LB.

Insight into the effect of cultivar and altitude on the identification of EnshiYulu tea grade in untargeted metabolomics analysis

The accurate identification of tea grade is crucial to the quality control of tea. However, existing methods lack sufficient generalization ability in identifying tea grades due to the effect of temporal and spatial factors. In this study, we analyzed the effect of cultivar and altitude on EnshiYulu (ESYL) tea grades and established a robust model to evaluate their quality. Principal component analysis (PCA) revealed that differences in variety and elevation can mask grade differences. Orthogonal projection to latent structure-discriminant analysis (OPLS-DA) was used for grade identification of samples from different altitudes. For ESYL tea samples above and below 800 m altitude, 75 and 35 grade differentiated metabolites were discovered, with 14 common differentiated metabolites. Based on reconstructed OPLS-DA models, the grades of multi-altitude sources ESYL were discriminated with a rate > 85%. These results demonstrate the potential of a grade discrimination model based on common differential metabolites, which exhibits generalization ability.

Differential analysis of volatiles in five types of mosquito-repellent products by chemometrics combined with headspace GC-Orbitrap HRMS nontargeted detection

This paper reports a method for the differential analysis of volatile chemical components in five novel types of mosquito-repellent products based on chemometrics combined with headspace gas chromatography-Orbitrap high-resolution mass spectrometry (HS-GC-Orbitrap HRMS) nontargeted screening. A total of 358 unknown substances were detected in 30 samples under specific headspace conditions. Through principal component analysis and orthogonal partial least-squares discriminant analysis, 36 significantly different substances with variable importance in the projection values greater than 1 were further screened, and these substances were accurately identified by GC-Orbitrap HRMS. Most substances were found for the first time in mosquito-repellent products. The clustered heat map, Venn diagram and peak area histogram showed that the mosquito-repellent products had similar volatile composition, and the volatile species and content of different types of mosquito-repellent products significantly varied. Substances, such as eucalyptol, d-limonene, α-pinene, β-pinene, dl-menthol and methyl salicylate, may be the main sources of odour in mosquito-repellent products. This work explored the characteristic volatile components in mosquito-repellent products and comparatively analysed the chemical composition of different types of products. It can be generalised to consumer products as a case study and has positive implications for promoting product quality and safety and improving production processes.

UHPLC-QTOF-MS-based untargeted metabolomic authentication of Chinese red wines according to their grape varieties

Wine is a very popular alcoholic drink owing to its health benefits of antioxidant effects. However, profits-driven frauds of wine especially false declarations of variety frequently occurred in markets. In this work, an UHPLC-QTOF-MS-based untargeted metabolomics method was developed for metabolite profiling of 119 bottles of Chinese red wines from four varieties (Cabernet Sauvignon, Merlot, Cabernet Gernischt, and Pinot Noir). The metabolites of red wines from different varieties were assessed using orthogonal partial least-squares discriminant analysis (OPLS-DA) and analyzed using KEGG metabolic pathway analysis. Results showed that the differential compounds among different varieties of red wines are mainly flavonoids, phenols, indoles and amino acids. The KEGG metabolic pathway analysis showed that indoles metabolism and flavonoids metabolism are closely related to wine varieties. Based on the differential compounds, OPLS-DA models could identify external validation wine samples with a total correct rate of 90.9 % in positive ionization mode and 100 % in negative ionization mode. This study indicated that the developed untargeted metabolomics method based on UHPLC-QTOF-MS is a potential tool to identify the varieties of Chinese red wines.

μ-PESI-based MS profiling combined with untargeted metabolomics analysis for rapid identification of red wine geographical origin

BACKGROUND

The commercial value of red wine is strongly linked to its geographical origin. Given the large global market, there is great demand for high-throughput screening methods to authenticate the geographical source of red wine. However, only limited techniques have been established up to now.

RESULTS

Herein, a sensitive and robust method, namely probe electrospray ionization mass spectrometry (μ-PESI-MS), was established to achieve rapid analysis at approximately 1.2 min per sample without any pretreatment. A scotch near the needle tip provides a fixed micro-volume for each analysis to achieve satisfactory ion signal reproducibility (RSD < 26.7%). In combination with a machine learning algorithm, 16 characteristic ions were discovered from thousands of detected ions and were utilized for differentiating red wine origin. Among them, the relative abundances of two characteristic metabolites (trigonelline and proline) correlated with geographical conditions (sun exposure and water stress) were identified, providing the rationale for differentiation of the geographical origin.

CONCLUSION

The proposed μ-PESI-MS-based method demonstrates a promising high-throughput determination capability in red wine traceability.

Discriminating geographical origins and determining active substances of water caltrop shells through near-infrared spectroscopy and chemometrics

Near-infrared spectroscopy (NIRS) combined with chemometric methods were used to discriminate the geographical origins of the water caltrop shells from different regions of China. Two active substances, the total phenolic content (TPC) and total flavonoid content (TFC) in the water caltrop shells were determined through the technique as well. Principal component analysis (PCA) combined with linear discriminant analysis (LDA) was adopted to build the geographical discriminant model. Quantitative analysis models of TPC and TFC were built using partial least squares (PLS) regression. 1st derivative and randomization test (RT) methods were used to optimize the quantitative analysis models. It was found that the geographical discriminant model can correctly recognize the water caltrop shells from different regions of China with a total accuracy of 93.33%. The values of TPC and TFC obtained by the optimized models and the standard method are close. The coefficient of determination (R2) and the ratio of prediction to deviation for the two substances were 0.91, 0.89 and 3.02, 3.02, respectively. The results demonstrated the feasibility of NIRS combined with chemometric methods for the geographical discrimination of water caltrop shells and the quantitative analysis of TPC and TFC in water caltrop shells.

Revealing the chemical differences and their application in the storage year prediction of Qingzhuan tea by SWATH-MS based metabolomics analysis

It's generally believed that the longer the storage, the better the quality of dark tea, but the chemical differences of Qingzhuan tea (QZT) with different storage years is still unclear. Herein, in this work, an untargeted metabolomic approach based on SWATH-MS was established to investigate the differential compounds of QZT with 0-9 years' storage time. These QZT samples were roughly divided into two categories by principal component analysis (PCA). After orthogonal projections to latent structures discriminant analysis (OPLS-DA), 18 differential compounds were putatively identified as chemical markers for the storage year variation of QZT. Heatmap visualization showed that the contents of catechins, fatty acids, and some phenolic acids significantly reduced, flavonoid glycosides, triterpenoids, and 8-C N-ethyl-2-pyrrolidinone-substituted flavan-3-ols (EPSFs) increased with the increase of storage time. Furthermore, these chemical markers were verified by the peak areas corresponding to MS2 ions from SWATH-MS. Based on the extraction chromatographic peak areas of MS and MS2 ions, a duration time prediction model was built for QZT with correlation coefficient R2 of 0.9080 and 0.9701, and RMSEP value of 0.85 and 1.24, respectively. This study reveals the chemical differences of QZT with different storage years and provides a theoretical basis for the quality evaluation of stored dark tea.

Geographical discrimination of Flos Trollii by GC-MS and UHPLC-HRMS-based untargeted metabolomics combined with chemometrics

For centuries, Flos Trollii has been consumed as functional tea and a folk medicine in China's north and northwest zones. The quality of Flos Trollii highly depends on the producing zones. Unfortunately, few studies have been reported on the geographical discrimination of Flos Trollii. This work comprehensively investigated Flos Trollii compounds with an integration strategy combining gas chromatography-mass spectrometry (GC-MS) and ultrahigh-performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS) with chemometrics to explore the differences between Flos Trollii obtained from various origins of China. About 71 volatile and 22 involatile markers were identified with GC-MS and UHPLC-HRMS, respectively. Geographical discrimination models were synthetically investigated based on the identified markers. The results indicated that the UHPLC-HRMS coupled with the fisher discrimination model provided the best prediction capability (>97%). This study provides a new solution for Flos Trollii discrimination.

Comparative Analysis of the Physicochemical Properties and Metabolites of Farinose and Crisp Lotus Roots (Nelumbo nucifera Gaertn.) with Different Geographical Origins

Lotus roots are widely consumed vegetables because of their great taste and abundant nutrients, but their quality varies with the environments and cultivar. This study systematically compared farinose (Elian No. 5) and crisp (Elian No. 6) lotus root cultivars from three geographical origins. Pasting and texture characteristics verified that Elian No. 5 possessed lower hardness and lower ability to withstand shear stress and heating during cooking compared with Elian No. 6. Untargeted metabolite profiling was first performed using ultrahigh-performance liquid chromatography coupled with electrospray ionization quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS) combined with a Zeno trap. In total, 188 metabolites were identified based on the matching chemistry database. Multivariate analysis demonstrated that lotus roots from different cultivars and origins could be adequately distinguished. Sixty-one differential metabolites were identified among three Elian No. 5 samples, and 28 were identified among three Elian No. 6 samples. Isoscopoletin, scopoletin, and paprazine were the most differential metabolites between Elian No. 5 and Elian No. 6. These results can inform future research on the discrimination and utilization of lotus roots.

The metabolism and dissipation behavior of tolfenpyrad in tea: A comprehensive risk assessment from field to cup

The metabolites of pesticides usually require rational risk assessment. In the present study, the metabolites of tolfenpyrad (TFP) in tea plants were identified using UPLC-QToF/MS analysis, and the transfer of TFP and its metabolites from tea bushes to consumption was studied for a comprehensive risk assessment. Four metabolites, PT-CA, PT-OH, OH-T-CA, and CA-T-CA, were identified, and PT-CA and PT-OH were detected along with dissipation of the parent TFP under field conditions. During processing, 3.11-50.00 % of TFP was further eliminated. Both PT-CA and PT-OH presented a downward trend (7.97-57.89 %) during green tea processing but an upward trend (34.48-124.17 %) during black tea manufacturing. The leaching rate (LR) of PT-CA (63.04-101.03 %) from dry tea to infusion was much higher than that of TFP (3.06-6.14 %). As PT-OH was no longer detected in tea infusions after 1 d of TFP application, TFP and PT-CA were taken into account in the comprehensive risk assessment. The risk quotient (RQ) assessment indicated a negligible health risk, but PT-CA posed a greater potential risk than TFP to tea consumers. Therefore, this study provides guidance for rational TFP application and suggests the sum of TFP and PT-CA residues as the maximum residual limit (MRL) in tea.

Identification of Oak-Barrel and Stainless Steel Tanks with Oak Chips Aged Wines in Ningxia Based on Three-Dimensional Fluorescence Spectroscopy Combined with Chemometrics

With the increased incidence of wine fraud, a fast and reliable method for wine certification has become a necessary prerequisite for the vigorous development of the global wine industry. In this study, a classification strategy based on three-dimensional fluorescence spectroscopy combined with chemometrics was proposed for oak-barrel and stainless steel tanks with oak chips aged wines. Principal component analysis (PCA), partial least squares analysis (PLS-DA), and Fisher discriminant analysis (FDA) were used to distinguish and evaluate the data matrix of the three-dimensional fluorescence spectra of wines. The results showed that FDA was superior to PCA and PLS-DA in classifying oak-barrel and stainless steel tanks with oak chips aged wines. As a general conclusion, three-dimensional fluorescence spectroscopy can provide valuable fingerprint information for the identification of oak-barrel and stainless steel tanks with oak chips aged wines, while the study will provide some theoretical references and standards for the quality control and quality assessment of oak-barrel aged wines.

Untargeted metabolomics analysis based on LC-IM-QTOF-MS for discriminating geographical origin and vintage of Chinese red wine

Identifying wine geographical origin and vintage is vital due to the abundance of fraudulent activity associated with wine mislabeling of region and vintage. In this study, an untargeted metabolomic approach based on liquid chromatography/ion mobility quadrupole time-of-flight mass spectrometry (LC-IM-QTOF-MS) was used to discriminate wine geographical origin and vintage. Wines were well discriminated according to region and vintage with orthogonal partial least squares-discriminant analysis (OPLS-DA). The differential metabolites subsequently were screened by OPLS-DA with pairwise modeling. 42 and 48 compounds in positive and negative ionization modes were screened as differential metabolitesfor the discrimination of different wine regions, and 37 and 35 compounds were screened for wine vintage. Furthermore, new OPLS-DA models were performed using these compounds, and the external verification trial showed excellent practicality with an accuracy over 84.2%. This study indicated that LC-IM-QTOF-MS-based untargeted metabolomics was a feasible tool for wine geographical origin and vintage discrimination.

UHPLC-QTOF-MS-based untargeted metabolomics and mineral element analysis insight into the geographical differences of Chrysanthemum morifolium Ramat cv. "Hangbaiju" from different origins

Chrysanthemum morifolium Ramat cv. "Hangbaiju" (HBJ), known as one of the "eight flavors of Zhejiang", is commonly used as a classical tea material for both food and medicine over three thousand years in China. The quality of HBJ is closely related to its geographical origins. However, the mechanism underlying the geographical differences of HBJ remains to be elucidated. In this study, an untargeted metabolomic strategy based on UHPLC-QTOF-MS was established to discover the differential metabolites in HBJ samples from four different origins and explore the possible relationship with mineral elements in planting soils by chemometric analysis. Eight compounds were screened and identified as the key differential metabolites in HBJ samples from different origins. Among them, four important pharmacodynamic compounds including L-arginine, rutin, chlorogenic acid and apigenin-7-O-glucoside are the most abundant in HBJ samples from Tongxiang region, which suggests that HBJ planted in Tongxiang has higher medicinal values. Pearson correlation analysis revealed that the contents of soil mineral elements are positively correlated with those of chlorogenic acid, rutin, apigenin-7-O-glucoside in HBJ samples. Furthermore, an interrelationship model based on random forest algorithm was established to successfully predict the contents of differential metabolites in HBJ samples by soil mineral elements. All these results indicated that the contents of differential metabolites in HBJ samples seemed to be affected by soil mineral elements and therefore resulted in the geographical differences of HBJ.

Characterization of wine volatile compounds from different regions and varieties by HS-SPME/GC-MS coupled with chemometrics

HS-SPME/GC-MS and aroma descriptive analysis were used to gain insights into the volatile and sensory details of 99 red wine samples collected from four varieties in five regions. The general volatile fingerprints of Cabernet Sauvignon and Merlot wine samples in Xinjiang and Ningxia regions were similar, even though chemometric models could not discriminate between them. The main drivers of the diversity were secondary metabolites of grape such as terpenes, benzene-derivatives, and ketones. Fermentation-derivatives (esters and alcohols) were also responsible for region and variety-related differences in wines. Analysis of volatile compounds also showed that the primary factor accounting for diversity in wines in this study was region rather than variety. These results highlight the sensory attributes and volatiles of different regions and varieties, and provide a quantitative basis for screening for differential metabolites and potential markers in wines.

Food metabolomics: Latest hardware-developments for nontargeted food authenticity and food safety testing

The analytical requirements for food testing have increased significantly in recent years. On the one hand, because food fraud is becoming an ever-greater challenge worldwide, and on the other hand because food safety is often difficult to monitor due to the far-reaching trade chains. In addition, the expectations of consumers on the quality of food have increased, and they are demanding extensive information. Cutting-edge analytical methods are required to meet these demands. In this context, non-targeted metabolomics strategies using mass and nuclear magnetic resonance spectrometers (mass spectrometry [MS]) have proven to be very suitable. MS-based approaches are of particular importance as they provide a comparatively high analytical coverage of the metabolome. Accordingly, the efficiency to address even challenging issues is high. A variety of hardware developments, which are explained in this review, have contributed to these advances. In addition, the potential of future developments is highlighted, some of which are currently not yet commercially available or only used to a comparatively small extent but are expected to gain in importance in the coming years.