UPLC-Q-TOF/MS-based untargeted metabolomics coupled with chemometrics approach for Tieguanyin tea with seasonal and year variations

Metabolomics applications for plant-based foods origin tracing, cultivars identification and processing: Feasibility and future aspects

Metabolomics, the systematic study of metabolites, is dedicated to a comprehensive analysis of all aspects of plant-based food research and plays a pivotal role in the nutritional composition and quality control of plant-based foods. The diverse chemical compositions of plant-based foods lead to variations in sensory characteristics and nutritional value. This review explores the application of the metabolomics method to plant-based food origin tracing, cultivar identification, and processing methods. It also addresses the challenges encountered and outlines future directions. Typically, when combined with other omics or techniques, synergistic and complementary information is uncovered, enhancing the classification and prediction capabilities of models. Future research should aim to evaluate all factors affecting food quality comprehensively, and this necessitates advanced research into influence mechanisms, metabolic pathways, and gene expression.

Formulation analysis of functional fragrance via polar-gradient extraction method and chemometrics pattern recognition

In this study, characteristic components of 15 natural flavors was analyzed by the polar-gradient extraction (PGE) technique in combination with GC-MS and chemometrics pattern recognition. The obtained results were utilized for the traceability of 4 functional fragrance formulations. The optimal PGE system consisting of 5 different polar solvents, was developed based on similarity-intermiscibility theory. Four chemometrics pattern recognition models including PCA, HCA, PLS-DA, and OPLS-DA were constructed based on the characteristic component database constituting 15 natural flavors. These models were used to trace 4 functional fragrance formulations. The experimental results obtained were found to be satisfactory and accurate. The combination of PGE technique and chemometric pattern recognition methods provides theoretical guidance for the analysis of characteristic components of natural flavors and the traceability of functional fragrance formulations. This approach can be promoted in various fields such as food, traditional Chinese medicine, and cosmetics.

Effect of the type of brewing water on the sensory and physicochemical properties of light-scented and strong-scented Tieguanyin oolong teas

Variations in the quality of brewing water profoundly impact tea flavor. This study systematically investigated the effects of four common water sources, including pure water (PW), mountain spring water (MSW), mineral water (MW) and natural water (NW) on the flavor of Tieguanyin tea infusion. Brewing with MW resulted in a flat taste and turbid aroma, mainly due to the low leaching of tea flavor components and complex interactions with mineral ions (mainly Ca2+, Mg2+). Tea infusions brewed with NW exhibited the highest relative contents of total volatile compounds, while those brewed with PW had the lowest. NW and MSW, with moderate mineralization, were conducive to improving the aroma quality of tea infusion and were more suitable for brewing both aroma types of Tieguanyin. These findings offer valuable insights into the effect of brewing water on the sensory and physicochemical properties of oolong teas.

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.

Quality markers of Guchang Zhixie pills based on multicomponent qualitative and quantitative analysis combined with network pharmacology and chemometric analysis

Traditional Chinese medicine Guchang Zhixie pills(GCZX) is one of the famous varieties of "Qin medicine" that has been extensively applied to treating irritable bowel syndrome(IBS). However, despite the acknowledged clinical advantages of GCZX there are significant constraints on its quality control and evaluation. The present study utilized UHPLC-Q-Exactive-Orbitrap-MS to analyze the chemical composition of GCZX. Additionally, network pharmacology approaches were utilized to explore the underlying mechanism by which blood components exert therapeutic effects in the treatment of IBS. Furthermore, the GCZX samples were evaluated for their quality on the basis of the qualitative results obtained from 25 batches of GCZX samples using fingerprinting; subsequently, multivariate statistical analysis methods were employed for further analysis. The results indicated the presence of 198 individual components. Among them, 17 prototype compounds were detected in the serum of rats that were administered with GCZX. The potential therapeutic mechanism of GCZX in the treatment of IBS may be associated with the modulation of the neurological system, the immunological system, and the inflammatory response. Moreover, a total of seven prominent peaks were identified after fingerprint analysis. The range of fingerprint similarity among the 25 batches of samples varied from 0.843 to 1.000. The application of chemometrics analysis successfully facilitated the categorical classification of 25 batches of GCZX into three distinct groups. Seven components hold significant importance and should be duly considered during the quality control process of GCZX. The present study can establish the Q-Markers of GCZX for IBS, thereby providing a foundation for investigating the theoretical underpinnings and elucidating the mechanisms underlying the therapeutic effects of GCZX in the treatment of IBS.

The Impact of Harvesting Mechanization on Oolong Tea Quality

Mechanization is the inevitable future of tea harvesting, but its impact on tea chemistry and quality remains uncertain. Our study examines untargeted metabolomic data from 185 oolong tea products (Tieguanyin) made from leaves harvested by hand or machine based on UPLC-QToF-MS analysis. The data revealed a minimum 50% loss for over half of the chemicals in the machine-harvested group, including catechins, theaflavin, gallic acid, chlorogenic acid, and kaempferol-3-gluocside. Integrating sensory evaluation, OPLS-DA identified the six most important metabolites as significant contributors to sensory decline caused by harvesting mechanization. Furthermore, our research validates the possibility of using DD-SIMCA modelling with untargeted metabolomic data for distinguishing handpicked from machine-harvested tea products. The model was able to achieve 93% accuracy. This study provides crucial insights into the chemical and sensory shifts during mechanization, along with tools to manage and monitor these changes.

A colorimetric sensor array based on peroxidase activity nanozyme for the highly efficient differential sensing of tea polyphenols and Tieguanyin adulteration

Tieguanyin (TGY) is one of top ten famous teas in China, but in the process of brand building there is the phenomenon of falsehood, thus harming the interests of consumers. To solve theadulterate problem of TGY, a colorimetric sensor array (CSA) based onperoxidase activity of nanozyme was constructed. Nanozymes can catalyze 3,3',5,5'-tetramethylbenzidine (TMB) to 3,3',5,5'-tetramethyl -[1,1'-bis(cyclohexyl)]-2,2',5,5'-tetraene-4,4'-diimine (oxTMB), while the tea polyphenols (TPs) can inhibit this process, and the degree of inhibition varies significantly with the reaction time. We selected two nanozymesand three reaction time points to construct CSA. It can successfully distinguish TPsin TGY. The discriminative analysiscan achieve: (1)distinction between TGY and adulterated tea, (2)discrimination of TGY in various seasons and seasonal adulteration in different degrees. The method constructed in this work is promising for both the class and quality differentiation of TGY and other teas with TPs as the main activity.

Multilocus Distance-Regulated Sensor Array for Recognition of Polyphenols via Machine Learning and Indicator Displacement Assay

Developing new strategies to construct sensor arrays that can effectively distinguish multiple natural components with similar structures in mixtures is an exceptionally challenging task. Here, we propose a new multilocus distance-modulated indicator displacement assay (IDA) strategy for constructing a sensor array, incorporating machine learning optimization to identify polyphenols. An 8-element array, comprising two fluorophores and their six dynamic covalent complexes (C1-C6) formed by pairing two fluorophores with three distinct distance-regulated quenchers, has been constructed. Polyphenols with diverse spatial arrangements and combinatorial forms compete with the fluorophores by forming pseudocycles with quenchers within the complexes, leading to varying degrees of fluorescence recovery. The array accurately and effectively distinguished four tea polyphenols and 16 tea varieties, thereby demonstrating the broad applicability of the multilocus distance-modulated IDA array in detecting polyhydroxy foods and natural medicines.

Quality markers of Dajianzhong decoction based on multicomponent qualitative and quantitative analysis combined with network pharmacology and chemometric analysis

INTRODUCTION

Dajianzhong decoction (DJZD), a classic famous prescription, has a long history of medicinal application. Modern studies have demonstrated its clinical utility in the treatment of postoperative ileus (POI). But none of the current quality evaluation methods for this compound is associated with efficacy.

OBJECTIVES

This study aimed to identify the quality markers (Q-Markers) connected to the treatment of POI in DJZD.

METHODOLOGY

Ultra-performance liquid chromatography quadrupole Exactive Orbitrap mass spectrometry (UPLC-Q-Exactive Orbitrap-MS) was used to identify the main constituents in DJZD. Based on the qualitative results obtained by fingerprinting, chemical pattern recognition (CPR) was used to analyse the key components affecting the quality and finally to establish the network of the active ingredients in DJZD with POI.

RESULTS

A total of 64 chemical components were detected. After fingerprint analysis, 13 common peaks were identified. The fingerprint similarity of 15 batches of samples ranged from 0.860 to 1.000. CPR analysis was able to categorically classify 15 batches of DJZD into two groups. And gingerenone A, methyl-6-gingerdiol, 6-gingerol, and hydroxy-β-sanshool contributed to their grouping. Twelve common components interact with the therapeutic targets for treating POI. In addition, the mechanism of this prescription for treating POI may be related to the jurisdiction of the neurological system, the immunological system, and the inflammatory response.

CONCLUSIONS

This integrated approach can accurately assess and forecast the quality of DJZD, presume the Q-Markers of DJZD for POI, and lay the foundation for studying the theoretical underpinnings and exploring the mechanism of DJZD in the treatment of POI.

Metabolome expression in Eucryphia cordifolia populations: Role of seasonality and ecological niche centrality hypothesis

The ecological niche centrality hypothesis states that population abundance is determined by the position in the ecological niche, expecting higher abundances towards the center of the niche and lower at the periphery. However, the variations in the conditions that favor the persistence of populations between the center and the periphery of the niche can be a surrogate of stress factors that are reflected in the production of metabolites in plants. In this study we tested if metabolomic similarity and diversity in populations of the tree species Eucryphia cordifolia Cav. vary according to their position with respect to the structure of the ecological niche. We hypothesize that populations growing near the centroid should exhibit lower metabolites diversity than plants growing at the periphery of the niche. The ecological niche of the species was modeled using correlative approaches and bioclimatic variables to define central and peripheral localities from which we chose four populations to obtain their metabolomic information using UHPLC-DAD-QTOF-MS. We observed that populations farther away from the centroid tend to have higher metabolome diversity, thus supporting our expectation of the niche centrality hypothesis. Nonetheless, the Shannon index showed a marked variation in metabolome diversity at the seasonal level, with summer and autumn being the periods with higher metabolite diversity compared to winter and spring. We conclude that both the environmental variation throughout the year in combination with the structure of the ecological niche are relevant to understand the variation in expression of metabolites in plants.

Photosynthesis regulation, cell membrane stabilization and methylglyoxal detoxification seems major altered pathways under cold stress as revealed by integrated multi-omics meta-analysis

Climate change has altered cold weather patterns, resulting in irregular cold weather conditions, and changing the global plant distribution pattern affecting plant development processes resulting in severe yield losses. Although molecular mechanisms and interconnections are quite well studied, a cumulative understanding of plant responses to cold stress (CS) is still lacking. Through meta-analysis, integration of data at the multi-omics level and its correlation with known physiological changes to map and understand the global changes in response to CS was made. Meta-analysis was conducted using the metafor R package program based on physiological parameters like relative electrolytic leakage, malondialdehyde, soluble sugar, proline and antioxidant enzymes activity. Proline and soluble sugars showed the highest (> 1.5 mean fold) change over control thus qualifying as global markers for studying CS. Surprisingly most up-regulated (> 15-fold) DEGs corresponded with the dehydrin family and glyoxalase superfamily proteins. Functional annotations of DEGs corresponded with photosynthesis and glycolysis pathway. Proteins responsible for cell signalling and increased soluble sugars were common in all the datasets studied thus correlating with the transcriptome and proteomic data. Proline and soluble sugars were positively regulated in all the metabolomics datasets. This study supported the earlier known players like proline and soluble sugars. Surprisingly, a new player glyoxalase seems to be contributing in CS.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12298-023-01367-9.

Atmospheric solids analysis probe-mass spectrometry (ASAP-MS) as a rapid fingerprinting technique to differentiate the harvest seasons of Tieguanyin oolong teas

Atmospheric solids analysis probe-mass spectrometry (ASAP-MS), an ambient mass spectrometry technique, was used to differentiate spring and autumn Tieguanyin teas. Two configurations were used to obtain their chemical fingerprints - ASAP attached to a high-resolution quadrupole time-of-flight mass spectrometer (i.e., ASAP-QTOF) and to a single-quadrupole mass spectrometer (i.e., Radian™ ASAP™ mass spectrometer). Then, orthogonal projections to latent structures-discriminant analysis was conducted to identify features that held promise in differentiating harvest seasons. Four machine learning models - decision tree, linear discriminant analysis, support vector machine, and k-nearest neighbour - were built using these features, and high classification accuracy of up to 100% was achieved. The markers were putatively identified using their accurate masses and MS/MS fragmentation patterns from ASAP-QTOF. This approach was successfully transferred to the Radian ASAP MS, which is more deployable in the field. Overall, this study demonstrated the potential of ASAP-MS as a rapid fingerprinting tool for differentiating spring and autumn Tieguanyin.

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.

Metabolic Profiling and Potential Taste Biomarkers of Two Rambutans during Maturation

The metabolite-caused taste variation during rambutan maturation is unknown due to a lack of systematic investigation of all components. In this study, three growing stages, including unripe (S1), half-ripe (S2), and full-ripe (S3) BY2 and BY7 rambutans were compared and profiled by UPLC-MS/MS-based widely targeted metabolomics analysis. We demonstrated that the sugar-acid ratios of two rambutans were greatly improved between the S2 and S3 stages. A total of 821 metabolites were identified, including 232, 205, 204, and 12 differential metabolites (DMs) in BY2-S1 vs. BY2-S2, BY2-S2 vs. BY2-S3, BY7-S1 vs. BY7-S2, and BY7-S2 vs. BY7-S3, respectively. A correlation analysis showed that gamma-aminobutyric acid (GABA) could be the sugar-acid ratio biomarker of BY2 rambutan. Methionine (Met), alanine (Ala), and S-methyl-L-cysteine (SMC) could be total amino acid biomarkers of BY2 and BY7 rambutans. In addition, UPLC-MS/MS-based quantitative verification of the above biomarkers exhibited the same variations as metabolomics analysis. This study not only provides useful nutritive information on rambutans but also valuable metabolic data for rambutan breeding strategies.

Integrated Metabolomic and Transcriptomic Analysis Reveals That Amino Acid Biosynthesis May Determine Differences in Cold-Tolerant and Cold-Sensitive Tea Cultivars

Cold stress is one of the major abiotic stresses limiting tea production. The planting of cold-resistant tea cultivars is one of the most effective measures to prevent chilling injury. However, the differences in cold resistance between tea cultivars remain unclear. In the present study, we perform a transcriptomic and metabolomic profiling of Camellia sinensis var. "Shuchazao" (cold-tolerant, SCZ) and C. sinensis var. assamica "Yinghong 9" (cold-sensitive, YH9) during cold acclimation and analyze the correlation between gene expression and metabolite biosynthesis. Our results show that there were 51 differentially accumulated metabolites only up-regulated in SCZ in cold-acclimation (CA) and de-acclimation (DA) stages, of which amino acids accounted for 18%. The accumulation of L-arginine and lysine in SCZ in the CA stage was higher than that in YH9. A comparative transcriptomic analysis showed an enrichment of the amino acid biosynthesis pathway in SCZ in the CA stage, especially "arginine biosynthesis" pathways. In combining transcriptomic and metabolomic analyses, it was found that genes and metabolites associated with amino acid biosynthesis were significantly enriched in the CA stage of SCZ compared to CA stage of YH9. Under cold stress, arginine may improve the cold resistance of tea plants by activating the polyamine synthesis pathway and CBF (C-repeat-binding factor)-COR (cold-regulated genes) regulation pathway. Our results show that amino acid biosynthesis may play a positive regulatory role in the cold resistance of tea plants and assist in understanding the cold resistance mechanism differences among tea varieties.

Discrimination of the harvesting season of green tea by alcohol/salt-based aqueous two-phase systems combined with chemometric analysis

The flavor and aroma quality of green tea are closely related to the harvest season. The aim of this study was to identify the harvesting season of green tea by alcohol/salt-based aqueous two-phase system (ATPS) combined with chemometric analysis. In this paper, the single factor experiments (SFM) and response surface methodology (RSM) optimization were designed to investigate and select the optimal ATPS. A total of 180 green tea samples were studied in this work, including 86 spring tea and 94 autumn tea. After the active components in green tea samples were extracted by the optimal ethanol/(NH₄)₂SO₄ ATPS, the qualitative and quantitative analysis was realized based on HPLC-DAD combined with alternating trilinear decomposition-assisted multivariate curve resolution (ATLD-MCR) algorithm, with satisfactory spiked recoveries (86.00 %-112.45 %). The quantitative results obtained from ATLD-MCR model were subjected to chemometric pattern recognition analysis. The constructed partial least squares-discriminant analysis (PLS-DA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) models showed better results than the principal component analysis (PCA) model, and the R²X_cum values (>0.835) and R²Y_cum (>0.937) were close to 1, the Q²_cum values were greater than 0.75 (>0.933), and the differences between R²Y_cum and Q²_cum were not larger than 0.2, indicating excellent cross-validation prediction performance of the models. Furthermore, the classification results based on the hierarchical clustering analysis (HCA) were consistent with the PCA, PLS-DA and OPLS-DA results, establishing a good correlation between tea active components and the harvesting seasons of green tea. Overall, the combination of ATPS and chemometric methods is accurate, sensitive, fast and reliable for the qualitative and quantitative determination of tea active components, providing guidance for the quality control of green tea.

Nontargeted metabolomic analysis of four different parts of Actinidia arguta by UPLC-Q-TOF-MSE

Actinidia arguta, an edible berry plant with high nutritional values, has been widely used in Asian countries as a food and traditional medicinal herb. The well-recognized health-promoting properties of A. arguta were associated with its bioactive components in its different botanical parts. To rapidly screen and identify chemical components and simultaneously determine the potential metabolites from different parts of A. arguta, UPLC-Q-TOF-MS^E coupled with UNIFI platform and multivariate statistical analysis approach was established in this study. As a result, a total of 107 components were identified from the four different parts of A. arguta, in which 31 characteristic chemical markers were discovered among them, including 12, 8, 6, and 5 compounds from the fruits, leaves, roots, and stems, respectively. These results suggested that the combination of UPLC-Q-TOF-MS^E and metabolomic analysis is a powerful method to rapidly screen characteristic markers for the quality control of A. arguta.

Metabolomic analysis reveals the quality characteristics of Yi Gong tea leaves at different harvesting periods

To obtain a theoretical reference for understanding the changes in metabolites of Yigong tea leaves during different harvesting periods and to determine the optimal harvesting period, we performed a metabolome comparison using UPLC-Q-Exactive MS on Yigong tea leaves from different harvesting periods. The results indicated that a total of 41 metabolites were significantly altered during the growth of Yi Gong tea leaves. These involved 7 amino acids and their derivatives, 16 flavonols and flavonol glycosides, 4 organic acids, 3 catechins, 3 carbohydrates, 7 fatty acid esters, 1 terpene, and 3 substances from others. In particular, the levels of arginine and glutamine were higher in early-harvested tea leaves than in late-harvested tea leaves; the levels of flavonoids and flavonols were higher in late-harvested tea leaves. Metabolic pathway analysis revealed that the caffeine metabolism and the flavonoid biosynthesis perform key roles in Yigong tea leaves from different harvesting periods. PRACTICAL APPLICATIONS: At present, the application of metabolomics in tea research is focused on the study of pesticide residues, processing processes, environmental stresses, and regional differences. This study is to focus on the effect of the tea harvesting period on tea quality through metabolomics. Through metabolomics, we can better determine the optimal tea harvesting period, and this study can improve the quality of this tea product and may be able to bring some favourable favorable contributions contribution to the local tea marketing in the future.

A Comprehensive Investigation of Macro-Composition and Volatile Compounds in Spring-Picked and Autumn-Picked White Tea

The flavour of white tea can be influenced by the season in which the fresh leaves are picked. In this study, the sensory evaluation results indicated that spring-picked white tea (SPWT) was stronger than autumn-picked white tea (APWT) in terms of the taste of umami, smoothness, astringency, and thickness as well as the aromas of flower and fresh. To explore key factors of sensory differences, a combination of biochemical composition determination, widely targeted volatilomics (WTV) analysis, multivariate statistical analysis, and odour activity value (OAV) analysis was employed. The phytochemical analysis showed that the free amino acid, tea polyphenol, and caffeine contents of SPWTs were significantly higher than those of APWTs, which may explain the higher umami, smoothness, thickness, and astringency scores of SPWTs than those of APWTs. The sabinene, (2E, 4E)-2, 4-octadienal, (-)-cis-rose oxide, caramel furanone, trans-rose oxide, and rose oxide contents were significantly higher in SPWTs than in APWTs, which may result in stronger flowery, fresh, and sweet aromas in SPWTs than in APWTs. Among these, (2E,4E)-2,4-octadienal and (-)-cis-rose oxide can be identified as key volatiles. This study provides an objective and accurate basis for classifying SPWTs and APWTs at the metabolite level.

Comparative analysis of Fenghuang Dancong, Tieguanyin, and Dahongpao teas using headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry and chemometric methods

Fenghuang Dancong, Tieguanyin, and Dahongpao teas are belonged to semi-fermented oolong teas and are famous for their unique aroma. However, reports regarding the systematic comparison, differentiation, and classification of the volatile components of these three types of oolong teas are lacking. In this study, we aimed to establish a method for distinguishing these three types of oolong teas. The volatile components in a total of 21 tea samples of these three types of oolong teas were extracted, determined, and identified by headspace solid-phase microextraction (HS-SPME) combined with gas chromatography-mass spectrometry (GC-MS). In addition, chemometric methods such as hierarchical cluster analysis (HCA), principal component analysis (PCA), and orthogonal partial least squares discriminant analysis (OPLS-DA) were used for distinguishing and classifying the three types of oolong teas on the basis of the similarities and differences in the volatile components. The results showed that 125 volatile components were extracted and identified from the three types of oolong teas, among which 53 volatile components overlapped among the samples. The results of HCA indicated that the samples of each of the three types of oolong teas could be placed in one category when the t value was 220. The results of PCA and OPLS-DA showed that the volatile components such as dehydrolinalool, linalool oxide II, linalool, α-farnesene, linalool oxide I, β-ocimene, nerolidol, cis-3-butyric acid folate, myrcene, and (Z)-hexanoic acid-3-hexenyl ester are the characteristic components, which can be used to distinguish the three types of oolong teas. We developed a simple, fast, and efficient method for distinguishing three types of oolong teas and provided a feasible technique for the identification of oolong tea types.

Nontargeted metabolomics coupled with multivariate modelling techniques for discrimination of Cyclocarya paliurus (Batal.) Ijinskaja leaves from different geographic altitudes

Altitude-associated nutrition-compositional evaluation is critical for quality control and value determination of plants. Herein, an exploratory study was applied to investigate the differences in the metabolites of Cyclocarya paliurus (CP) leaves from different altitudes (200-1000 m) using a UPLC-QTOF-MS-based metabolomics method, employed to create models for discrimination of CP leaves. On the one hand, 70 metabolites exhibiting significant distinctions within various components in different altitude environments were detected and identified, of which majority showed a close connection. High altitude environments with a decrease in temperature accompanied by enhanced UV-B radiation significantly influenced the profile of flavonoids and organic acids. On the other hand, the PLS-DA model (R² = 0.994 and Q² = 0.990) with the VIP variable selection method and P-value were selected to characterize fifteen potential differential metabolites. Moreover, the DD-SIMCA model involving the above-mentioned differential compounds showed both good specificity and accuracy of 100%. These results provide guidance for the discrimination of CP leaves from different geographic altitudes, which may be extended to improve the growing conditions of CP leaves.

Discrimination and characterization of the volatile profiles of five Fu brick teas from different manufacturing regions by using HS–SPME/GC–MS and HS–GC–IMS

Although aroma is one of the most essential factors determining the quality of Fu brick tea (FBT), the aroma profiles of FBTs from different manufacturing areas are rarely investigated. The aroma profiles of FBTs manufactured in five typical provinces of China were comprehensively analyzed on the basis of headspace gas chromatography–ion mobility spectrometry (HS–GC–IMS), headspace solid-phase microextraction gas chromatography–mass spectrometry (HS–SPME–GC–MS), sensory evaluation, odor activity value (OAV), and relative odor activity value (ROAV). HS–GC–IMS and HS–SPME–GC–MS identified 63 and 93 volatile organic compounds (VOCs), respectively. Multivariate statistical analysis indicated that the FBTs from different production regions had remarkably varied aromas. HS–SPME–GC–MS revealed that 27 VOCs (OAV >1) contributed to the overall aroma of the samples, of which 15 key differential compounds can effectively distinguish the aroma profiles of different FBTs. FBT from Shaanxi manifested a strong floral and fruity aroma; that from Hunan had a floral, grassy, and pine-woody aroma; that from Guizhou presented a grassy and herbal aroma; that from Guangxi exhibited a sweet, floral, and minty aroma; and that from Zhejiang possessed various fruit flavors and floral fragrance. OAV analysis identified the biomarkers responsible for the variation in the aroma characteristics of diverse FBTs. These biomarkers included linalool, 6-methyl-5-hepten-2-one, α-ionone, hexanal, and ethyl hexanoate. Sensory evaluation demonstrated that the infusion color and aroma of FBT samples from different provinces also greatly varied. Network correlation analysis revealed that Aspergillus and Eurotium were the crucial microorganisms for the metabolism and formation of VOCs. These findings provide new insight into the VOCs and fragrance features of FBTs produced in different regions of China.

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Volatiles in Fu brick tea from five provinces of China were comprehensively analyzed.

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A total of 63 and 93 VOCs were identified by GC-IMS and GC-MS, respectively.

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Aroma profiles of Fu brick tea from five regions were greatly different.

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15 key volatiles were proposed to discriminate Fu brick tea from different regions.

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The correlations between the key VOCs and fungal community were analyzed.

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

Identifying geographical origins of red wines made in specific regions is of significance since the false claim of geographical origins has been frequently exposed in China's wine industry. In this work, an untargeted metabolomic approach based on UPLC-QTOF-MS was established to discriminate geographical origins of Chinese red wines. The principal component analysis (PCA) showed significant differences between wine samples from three famous geographical origins in China. The metabolites contributing to the differentiation were screened by orthogonal partial least squares-discriminant analysis (OPLS-DA) with pairwise modeling. 40 and 46 differential metabolites in positive and negative ionization modes were putatively identified as chemical markers. Furthermore, heatmap visualization and OPLS-DA models were constructed based on these identified markers and external verification wine samples from different regions were successfully discriminated, with recognition rate up to 96.7%. This study indicated that UPLC-QTOF-MS-based untargeted metabolomics has great potential for the geographical origin traceability of Chinese red wines.

Dynamic Variation of Amino Acid Contents and Identification of Sterols in Xinyang Mao Jian Green Tea

As important biomolecules in Camellia sinensis L., amino acids (AAs) are considered to contribute to the overall green tea sensory quality and undergo dynamic changes during growth. However, limited by analytical capacity, detailed AAs composition in different growth stages remains unclear. To address this question, we analyzed the dynamic changes of 23 AAs during leaf growth in Xinyang Mao Jian (XYMJ) green tea. Using amino acid analyzer, we demonstrated that most AAs are abundant on Pure Brightness Day and Grain Rain Day. After Grain Rain, 23 AAs decreased significantly. Further analysis shows that theanine has a high level on the day before Spring Equinox and Grain Rain, accounting for 44–61% of the total free AAs content in tea leaves. Glu, Pro, and Asp are the second most abundant AAs. Additionally, spinasterol and 22,23-dihydrospinasterol are first purified and identified in ethanol extract of XYMJ by silica gel column chromatography method. This study reveals the relationship between plucking days and the dynamic changes of AAs during the growth stage and proves the rationality of the traditional plucking days of XYMJ green tea.

Metabolomics combined with proteomics provides a novel interpretation of the compound differences among Chinese tea cultivars (Camellia sinensis var. sinensis) with different manufacturing suitabilities

Different tea cultivars differ in their manufacturing suitability. In this study, metabolomics and proteomics were applied to investigate the metabolite and protein differences in fresh leaves from 23 Chinese tea cultivars suitable for manufacturing green, white, oolong, and black teas. The combined analysis revealed 115 differential metabolites and significant differences in the biosynthesis pathways for amino acids, phenylpropanoids, flavonoids, and terpenoids, and in the peroxidases abundances among these four groups. Green tea cultivars had higher abundances of amino acids and amino acids biosynthesis-related enzymes but lower abundances of flavanols and flavonoids biosynthesis-related enzymes. Black tea cultivars presented higher abundances of flavanols, flavanol-O-glycosides, flavonoids biosynthesis-related enzymes, and peroxidases. Oolong tea cultivars showed higher abundances of enzymes involved in terpenoids biosynthesis. Our study provides a novel interpretation of the manufacturing suitability of tea cultivars from the perspective of both metabolites and proteins and will be helpful for cultivar breeding.

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.

Discriminant Analysis of Pu-Erh Tea of Different Raw Materials Based on Phytochemicals Using Chemometrics

Pu-erh tea processed from the sun-dried green tea leaves can be divided into ancient tea (AT) and terrace tea (TT) according to the source of raw material. However, their similar appearance makes AT present low market identification, resulting in a disruption in the tea market rules of fair trade. Therefore, this study analyzed the classification by principal component analysis/hierarchical clustering analysis and conducted the discriminant model through stepwise Fisher discriminant analysis and decision tree analysis based on the contents of water extract, phenolic components, alkaloid, and amino acids, aiming to investigate whether phytochemicals coupled with chemometric analyses distinguish AT and TT. Results showed that there were good separations between AT and TT, which was caused by 16 components with significant (p < 0.05) differences. The discriminant model of AT and TT was established based on six discriminant variables including water extract, (+)-catechin, (−)-epicatechin, (−)-epigallocatechin, theacrine, and theanine. Among them, water extract comprised multiple soluble solids, representing the thickness of tea infusion. The model had good generalization capability with 100% of performance indexes according to scores of the training set and model set. In conclusion, phytochemicals coupled with chemometrics analyses are a good approach for the identification of different raw materials.

Impact of prolonged withering on phenolic compounds and antioxidant capability in white tea using LC-MS-based metabolomics and HPLC analysis: Comparison with green tea

Contents of 20 bioactive compounds in 12 teas produced in Xinyang Region were determined by high performance liquid chromatography. Ultra-high performance liquid chromatography-quadrupole time of flight-mass spectrometry was developed for untargeted metabolomics analysis. Antioxidant activities were measured by 4 various assays. Those teas could be completely divided into green and white tea through principal component analysis, hierarchical cluster analysis and orthonormal partial least squares-discriminant analysis (R²Y = 0.996 and Q² = 0.982, respectively). The prolonged withering generated 472 differentiated metabolites between white and green tea, prompted significant decreases (variable importance in the projection > 1.0, p-value < 0.05 and fold change > 1.50) of most catechins and 8 phenolic acids to form 4 theaflavins, and benefited for the accumulation of 17 flavonoids and flavonoid glycosides, 8 flavanone and their derivatives, 20 free amino acids, 12 sugars and 1 purine alkaloid. Additionally, kaempferol and taxifolin contributed to 1,1-diphenyl-2-picrylhydrazyl (DPPH) scavenging ability of white tea.

Evolution of volatiles and quality of Chinese steamed bread during storage at different temperatures

The aim of this work is to investigate the evolution of volatiles and quality of CSB during 4 d of storage at 4 °C and 25 °C, respectively. Rapidly increasing hardness and decreasing resilience were observed in CSB after 1 d of storage at 4 °C. However, relative soft CSB was found after 1 d of storage at 25 °C as a result of the lower rate of retrogradation. Volatiles were monitored by gas chromatography-mass spectrometer. Significant (P < 0.05) decrease of 4 esters and 2-pentylfuran were observed with prolonged storage time for CSB stored at both 4 °C and 25 °C. PCA analysis indicated that the storage temperature of 4 °C was beneficial to remain CSB volatiles during long storage time (2-4 d). These findings might be beneficial to retain more volatiles and quality and finally extend shelf-life of CSB.

A Review on the Foodomics Based on Liquid Chromatography Mass Spectrometry

Due to the globalization of food production and distribution, the food chain has become increasingly complex, making it more difficult to evaluate unexpected food changes. Therefore, establishing sensitive, robust, and cost-effective analytical platforms to efficiently extract and analyze the food-chemicals in complex food matrices is essential, however, challenging. LC/MS-based metabolomics is the key to obtain a broad overview of human metabolism and understand novel food science. Various metabolomics approaches (e.g., targeted and/or untargeted) and sample preparation techniques in food analysis have their own advantages and limitations. Selecting an analytical platform that matches the characteristics of the analytes is important for food analysis. This review highlighted the recent trends and applications of metabolomics based on "foodomics" by LC-MS and provides the perspectives and insights into the methodology and various sample preparation techniques in food analysis.

Supervised Statistical Learning Prediction of Soybean Varieties and Cultivation Sites Using Rapid UPLC-MS Separation, Method Validation, and Targeted Metabolomic Analysis of 31 Phenolic Compounds in the Leaves

Soybean (Glycine max; SB) leaf (SL) is an abundant non-conventional edible resource that possesses value-adding bioactive compounds. We predicted the attributes of SB based on the metabolomes of an SL using targeted metabolomics. The SB was planted in two cities, and SLs were regularly obtained from the SB plant. Nine flavonol glycosides were purified from SLs, and a validated simultaneous quantification method was used to establish rapid separation by ultrahigh-performance liquid chromatography-mass detection. Changes in 31 targeted compounds were monitored, and the compounds were discriminated by various supervised machine learning (ML) models. Isoflavones, quercetin derivatives, and flavonol derivatives were discriminators for cultivation days, varieties, and cultivation sites, respectively, using the combined criteria of supervised ML models. The neural model exhibited higher prediction power of the factors with high fitness and low misclassification rates while other models showed lower. We propose that a set of phytochemicals of SL is a useful predictor for discriminating characteristics of edible plants.

Study on changes in pigment composition during the blooming period of safflower based on plant metabolomics and semi-quantitative analysis

Red and yellow pigments are the major ingredients of safflower, often used to color food and cosmetics. Carthamin was the main component of red pigment and hydroxysafflor yellow A and anhydrosafflower yellow B were representative components of yellow pigment. Plant metabolomics and semi-quantitative analysis were used to analyze the changes of pigment composition during the blooming period, especially these characteristic components. Carthamin, hydroxysafflor yellow A, anhydrosafflower yellow B, and other components were screened out as differential metabolites based on plant metabolomics. Then semi-quantitative analysis was used to quantify these three representative components of pigments. Experimental results showed that the content of pigments has dynamic changes along with flowering, in the early blooming period, yellow pigment accumulated much and red pigment was low in content. In the middle period, the accumulation rate of the yellow pigment slowed down and content was stabilized. In the next step, the content of yellow pigments gradually decreased, and the content of red pigments gradually increased. Later, the level of yellow pigment decreased significantly, and the accumulation rate of red pigment increased significantly. Last, the appearance color of safflower was red, with yellow parts barely visible, and accumulation of red pigment was the highest and of the yellow pigment was the lowest in content.

Authentication of Geographical Origin in Hainan Partridge Tea (Mallotus obongifolius) by Stable Isotope and Targeted Metabolomics Combined with Chemometrics

Partridge tea (Mallotus oblongifolius (Miq.) Müll.Arg.) is a local characteristic tea in Hainan, the southernmost province of China, and the quality of partridge tea may be affected by the producing areas. In this study, stable isotope and targeted metabolomics combined chemometrics were used as potential tools for analyzing and identifying partridge tea from different origins. Elemental analysis-stable isotope ratio mass spectrometer and liquid chromatography-tandem mass spectrometrywas used to analyze the characteristics of C/N/O/H stable isotopes and 54 chemical components, including polyphenols and alkaloids in partridge tea samples from four regions in Hainan (Wanning, Wenchang, Sanya and Baoting). The results showed that there were significant differences in the stable isotope ratios and polyphenol and alkaloid contents of partridge tea from different origins, and both could accurately classify partridge tea from different origins. The correct separation and clustering of the samples were observed by principal component analysis and the cross-validated Q² values by orthogonal partial least squares discriminant analysis (OPLS-DA) were 0.949 (based on stable isotope) and 0.974 (based on polyphenol and alkaloid), respectively. Potential significance indicators for origin identification were screened out by OPLS-DA and random forest algorithm, including three stable isotopes (δ¹³C, δ D, and δ¹⁸O) and four polyphenols (luteolin, protocatechuic acid, astragalin, and naringenin). This study can provide a preliminary guide for the origin identification of Hainan partridge tea.

Potential hypoglycemic metabolites in dark tea fermented by Eurotium cristatum based on UPLC-QTOF-MS/MS combining global metabolomic and spectrum-effect relationship analyses

The preventive and therapeutic effects of dark tea fermented by Eurotium cristatum (DTE) in glucose metabolism have been demonstrated. However, few studies have investigated comprehensive changes in the chemical composition and activity in DTE before and after fermentation. In this study, the metabolic profiling of raw samples and fermented samples was determined by ultra-performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS/MS). Furthermore, a systematic analytical strategy combining global metabolomics and the spectrum-effect relationship based on α-glucosidase inhibition was employed for screening discriminant metabolites. As a result, 15 discriminant metabolites were identified in DTE samples. Among them, 10 metabolites (4 fatty acids, 1 dyphylline derivative, 3 lysophosphatidylcholines, and 2 triterpenes) increased in relative contents and the contents of the other 5 polyphenol metabolites decreased after fermentation. These metabolites were critical constituents possibly associated with DTE's hypoglycemic activity, which also might be suitable as quality evaluation indicators. This study provided a worthy insight into the exploration of representative active constituents or quality indicators of DTE.

Metabolic Profiles of Brassica juncea Roots in Response to Cadmium Stress

Brassica juncea has great application potential in phytoremediation of cadmium (Cd)-contaminated soil because of its excellent Cd accumulating and high biomass. In this study, we compared the effects of Cd under 48 h and 7 d stress in roots of Brassica juncea using metabolite profiling. The results showed that many metabolic pathways and metabolites in Brassica juncea roots were altered significantly in response to Cd stress. We found that significant differences in levels of amino acids, organic acids, carbohydrates, lipids, flavonoids, alkaloids, and indoles were induced by Cd stress at different times, which played a pivotal role in the adaptation of Brassica juncea roots to Cd stress. Meanwhile, Brassica juncea roots could resist 48 h Cd stress by regulating the biosynthesis of amino acids, linoleic acid metabolism, aminoacyl-tRNA biosynthesis, glycerophospholipid metabolism, ABC transporters, arginine biosynthesis, valine, leucine and isoleucine biosynthesis, and alpha-linolenic acid metabolism; however, they regulated alpha-linolenic acid metabolism, glycerophospholipid metabolism, ABC transporters, and linoleic acid metabolism to resist 7 d Cd stress. A metabolomic expedition to the response of Brassica juncea to Cd stress will help to comprehend its tolerance and accumulation mechanisms of Cd.

Easy fabrication of aminated graphene oxide functionalized magnetic nanocomposite for efficient preconcentration of phenolic acids prior to HPLC determination: Application in tea-derived wines

In this study, aminated graphene oxide functionalized magnetic nanocomposite (AGMN) was facilely synthesized by one-pot hydrothermal approach and acted as the extraction phase of magnetic solid phase extraction (MSPE) of phenolic acids (PAs). Characterization results revealed that the AGMN possessed satisfying saturation magnetism and abundant functional groups. Under the optimal extraction parameters, the proposed AGMN/MSPE presented high enrichment capability to PAs. Sensitive and dependable method for measurement of PAs in wine was proposed by the combination of AGMN/MSPE and HPLC/DAD. Limits of detection and limits of quantification were in the ranges of 0.031-0.23 μg/L and 0.10-0.78 μg/L, respectively, and the RSDs for approach precision varied from 1.8% to 8.9%. Recoveries at low, medium and high fortified levels varied from 84.6% to 116%. The suggested method was used to quantify investigated PAs in ten kinds of Tieguanyin tea-derived wines, and found the contents of PAs in wines were related to the quality of tea-leaves and alcohol content.

Analysis of Differentiated Chemical Components between Zijuan Purple Tea and Yunkang Green Tea by UHPLC-Orbitrap-MS/MS Combined with Chemometrics

Zijuan tea (Camellia sinensis var. assamica cv. Zijuan) is a unique purple tea. Recently, purple tea has drawn much attention for its special flavor and health benefits. However, the characteristic compounds of purple tea compared with green tea have not been reported yet. The present study employed a non-targeted metabolomics approach based on ultra-high performance liquid chromatography (UHPLC)-Orbitrap-tandem mass spectrometry (MS/MS) for comprehensive analysis of characteristic metabolites between Zijuan purple tea (ZJT) and Yunkang green tea (YKT). Partial least squares-discriminant analysis (PLS-DA) indicated that there are significant differences in chemical profiles between ZJT and YKT. A total of 66 major differential metabolites included catechins, proanthocyanins, flavonol and flavone glycosides, phenolic acids, amino acids and alkaloids were identified in ZJT. Among them, anthocyanins are the most characteristic metabolites. Nine glycosides of anthocyanins and six glycosides of proanthocyanins were found to be significantly higher in ZJT than that in YKT. Subsequently, pathway analysis revealed that ZJT might generate anthocyanins and proanthocyanins through the flavonol and flavone glycosides. Furthermore, quantitative analysis showed absolutely higher concentrations of total anthocyanins in ZJT, which correlated with the metabolomics results. This study presented the comprehensive chemical profiling and the characterized metabolites of ZJT. These results also provided chemical evidence for potential health functions of ZJT.

Using Sensory Wheels to Characterize Consumers' Perception for Authentication of Taiwan Specialty Teas

In the context of fair trade and protection of consumer rights, the aim of this study was to combat adulteration, counterfeiting, and fraud in the tea market, and rebuild the image of high-quality Taiwan teas. Experts at the Tea Research and Extension Station, Taiwan (TRES), are engaged in promotion of the systems of origin identification (AOC) and grading for authentication of Taiwan's premium teas. From tea evaluation competitions (bottom-up quality campaign), the flavor descriptions and consumers' perceptions were deconvoluted and characterized for the eight Taiwan specialty teas, namely, Bi-Luo-Chun, Wenshan Paochong, High-Mountain Oolong, Dongding Oolong, Tieh-Kuan-Yin, Red Oolong, Oriental Beauty, and Taiwan black tea. Then, according to the manufacturing processes, producing estates and flavor characters, the specialty teas were categorized into six sensory wheels. The flavor descriptors of the sensory wheels were also recognized in consumers' feedback. In recent years, the performance of international trade in tea also demonstrates that the policy guidelines for authentication of specialty teas are helpful to the production and marketing. Furthermore, the development of sensory wheels of Taiwan's specialty teas is the cornerstone to the establishment of the Taiwan-tea assortment and grading system (TAGs) for communication with the new generation consumers, enthusiasts, sellers, and producers.