Determination of organic acids for predicting sourness intensity of tea beverage by liquid chromatography-tandem mass spectrometry and chemometrics methods.

The contents of organic acids (OAs) in tea beverage and their relationship with taste intensity have not been fully understood. In this work, a rapid (10 min for a single run) and sensitive (limits of quantification: 0.0044-0.4486 µg/mL) method was developed and validated for the simultaneous determination of 17 OAs in four types of tea, based on liquid chromatography-tandem mass spectrometry with multiple reaction monitoring mode. The contents of 17 OAs in 96 tea samples were measured at levels between 0.01 and 11.80 g/kg (dried weight). Quinic acid, citric acid, and malic acid were determined as the major OAs in green, black, and raw pu-erh teas, while oxalic acid and tartaric acid exhibited the highest contents in ripe pu-erh tea. Taking the OAs composition as input features, a partial least squares regression model was proposed to predict the sourness intensity of tea beverages. The model achieved a root-mean-square error of 0.58 and a coefficient of determination of 0.84 for the testing set. The proposed model provides a theoretical way to evaluate the sensory quality of tea infusion based on its chemical composition.

Combinatory data-independent acquisition and parallel reaction monitoring method for revealing the lipid metabolism biomarkers of coronary heart disease and its comorbidities.

Disorders of lipid metabolism are a common cause of coronary heart disease (CHD) and its comorbidities. In this study, ultra-performance liquid chromatography-high-resolution mass spectrometry in data-independent acquisition (DIA) mode was applied to collect abundant tandem mass spectrometry data, which provided valuable information for lipid annotation. For the lipid isomers that could not be completely separated by chromatography, parallel reaction monitoring (PRM) mode was used for quantification. A total of 223 plasma lipid metabolites were annotated, and 116 of them were identified for their fatty acyl chain composition and location. In addition, 152 plasma lipids in patients with CHD and its comorbidities were quantitatively analyzed. Multivariate statistical analysis and metabolic pathway analysis demonstrated that glycerophospholipid and sphingolipid metabolism deserved more attention for CHD. This study proposed a method combining DIA and PRM for high-throughput characterization of plasma lipids. The results also improved our understanding of metabolic disorders of CHD and its comorbidities, which can provide valuable suggestions for medical intervention.

Electrochemiluminescence sensor based on cyclic peptides-recognition and Au nanoparticles assisted graphitic carbon nitride for glucose determination.

A glucose (Glu) sensor was designed by introducing synthetic cyclic peptides (CPs) as recognition receptors and Au nanoparticles assisted graphitic carbon nitride (AuNPs/g-C3N4) for electrochemiluminescence (ECL) enhancement. The synthetic CP receptor (cyclo-[-CNDNHCRDNDC-]) with natural active center of Glu binding protein can mimic the interactions between Glu and Glu binding protein to specifically capture Glu. The AuNPs were reduced on g-C3N4 and formed a new nanohybrid that can be applied as an ECL emitter. The AuNPs/g-C3N4 effectively ameliorated the ECL response of bare g-C3N4. The ECL enhancement mechanism was theoretically speculated through computer simulation. Glu quantification was conducted by recording ECL shifts induced by the binding of Glu to CPs. The linear detection range of the fabricated CPs-based ECL sensor was 1 to 100 mmol L-1, and the detection limit (LOD) was 0.57 nmol L-1 (S / N = 3). The CP-based ECL sensor also showed good specificity, repeatability, stability, and favorable recoveries in sample analysis. This work offer a promising analytical method for Glu assay in clinical diagnostics and bioprocess monitoring.

In situ ionic liquid dispersive liquid-liquid microextraction combined with ultra high performance liquid chromatography for determination of neonicotinoid insecticides in honey samples.

An efficient in situ ionic liquid dispersive liquid-liquid microextraction followed by ultra-performance liquid chromatography was developed to determine four neonicotinoid insecticides in wild and commercial honey samples. In this method, a hydrophobic ionic liquid 1-butyl-3-methylimidazolium hexafluorophosphate, formed by in situ reaction between potassium hexafluorophosphate and 1-butyl-3-methylimidazolium bromide in sample solution, was used as the extraction solvent. In comparison with the traditional dispersive liquid-liquid microextraction method, the developed method required no dispersive solvent. To achieve high extraction efficiency and enrichment factor, the effects of various experimental parameters were studied in detail. Under the optimized conditions, the limits of detection and quantification were in the ranges of 0.30-0.62 and 1.20-2.50 µg/L, respectively. The method showed high enrichment factors (74-115) with the recoveries between 81.0 and 103.4%. The proposed method was finally applied to different wild and commercial honey samples.

Combined application of chromatographic techniques for the separation of phenolic compounds from Stenoloma chusanum Ching.

High-speed countercurrent chromatography combined with preparative high-performance liquid chromatography was successfully used to separate seven phenolic compounds from Stenoloma chusanum Ching. A biphasic solvent system composed of hexane/ethyl acetate/methanol/water (1:2:1:2, v/v) was used for the first step high-speed countercurrent chromatography separation in elution-extrusion mode. A mobile phase composed of acetonitrile (18%) and pure water (82%) was used for further preparative high-performance liquid chromatography purification. In total, the combined separation yielded seven compounds, including 3,4-dihydroxy benzoic acid, 3,4-dihydroxy benzaldehyde, esculetin, caffeic acid, syringic acid, luteolin, and apigenin, at a purity of over 90%. Esculetin was separated from Stenoloma chusanum Ching for the first time. The results suggest that the proposed combination method is a useful strategy for separating compounds from complex samples.

GC-MS Fingerprinting Combined with Chemometric Methods Reveals Key Bioactive Components in Acori Tatarinowii Rhizoma.

This present study aims to identify the key bioactive components in acorus tatarinowii rhizoma (ATR), a traditional Chinese medicine (TCM) with various bioactivities. Partial least squares regression (PLSR) was employed to describe the relationship between the radical scavenging activity and the volatile components. The PLSR model was improved by outlier elimination and variable selection and was evaluated by 10-fold cross-validation and external validation in this study. Based on the PLSR model, eleven chemical components were identified as the key bioactive components by variable importance in projection. The final PLS regression model with these components has good predictive ability. The Q² was 0.8284, and the root mean square error for prediction was 2.9641. The results indicated that the eleven components could be a pattern to predict the radical scavenging activity of ATR. In addition, we did not find any specific relationship between the radical scavenging ability and the habitat of the ATRs. This study proposed an efficient strategy to predict bioactive components using the combination of quantitative chromatography fingerprints and PLS regression, and has potential perspective for screening bioactive components in complex analytical systems, such as TCM.

A new method for wavelength interval selection that intelligently optimizes the locations, widths and combinations of the intervals.

In this study, a new algorithm for wavelength interval selection, known as interval variable iterative space shrinkage approach (iVISSA), is proposed based on the VISSA algorithm. It combines global and local searches to iteratively and intelligently optimize the locations, widths and combinations of the spectral intervals. In the global search procedure, it inherits the merit of soft shrinkage from VISSA to search the locations and combinations of informative wavelengths, whereas in the local search procedure, it utilizes the information of continuity in spectroscopic data to determine the widths of wavelength intervals. The global and local search procedures are carried out alternatively to realize wavelength interval selection. This method was tested using three near infrared (NIR) datasets. Some high-performing wavelength selection methods, such as synergy interval partial least squares (siPLS), moving window partial least squares (MW-PLS), competitive adaptive reweighted sampling (CARS), genetic algorithm PLS (GA-PLS) and interval random frog (iRF), were used for comparison. The results show that the proposed method is very promising with good results both on prediction capability and stability. The MATLAB codes for implementing iVISSA are freely available on the website: .

Separation of nine compounds from Salvia plebeia R.Br. using two-step high-speed counter-current chromatography with different elution modes.

Nine compounds were successfully separated from Salvia plebeia R.Br. using two-step high-speed counter-current chromatography with three elution modes. Elution-extrusion counter-current chromatography was applied in the first step, while classical counter-current chromatography and recycling counter-current chromatography were used in the second step. Three solvent systems, n-hexane/ethyl acetate/ethanol/water (4:6.5:3:7, v/v), methyl tert-butyl ether/ethyl acetate/n-butanol/methanol/water (6:4:1:2:8, v/v) and n-hexane/ethyl acetate/methanol/water (5:5.5:5:5, v/v) were screened and optimized for the two-step separation. The separation yielded nine compounds, including caffeic acid (1), 6-hydroxyluteuolin-7-glucoside (2), 5,7,3',4'-tetrahydroxy-6-methoxyflavanone-7-glucoside (3), nepitrin (4), rosmarinic acid (5), homoplantaginin (6), nepetin (7), hispidulin (8), and 5,6,7,4'-tertrahydroxyflavone (9). To the best of our knowledge, 5,7,3',4'-tetrahydroxy-6-methoxyflavanone-7-glucoside and 5,6,7,4'-tertrahydroxyflavone have been separated from Salvia plebeia R.Br. for the first time. The purities and structures of these compounds were identified by high-performance liquid chromatography, electrospray ionization mass spectrometry, (1)H and (13)C NMR spectroscopy. This study demonstrates that high-speed counter-current chromatography is a useful and flexible tool for the separation of components from a complex sample.

An antifouling electrochemical aptasensor based on a polydopamine-polyzwitterion copolymer for tetracycline analysis.

Matrix interference resulting from the nonspecific adsorption of non-target components, particularly proteins (fouling), onto sensor surfaces poses a persistent challenge in electrochemical detection of food hazards. The development of antifouling sensor surfaces presents a viable approach to mitigate nonspecific adsorption. In this study, a novel antifouling electrochemical aptasensor, utilizing a zwitterionic polymer, was developed for the sensitive, accurate, and selective detection of tetracycline (TC) in milk. This sensor employs a poly (dopamine)-poly (sulfobetaine methacrylate) (PDA-PSBMA) antifouling copolymer, which is synthesized through an in-situ initiated copolymerization of dopamine on the sensor's surface. Subsequently, the thiol-containing aptamers were immobilized onto the PDA-PSBMA coating through a Michael addition reaction with the poly(dopamine). The resulting antifouling electrochemical aptasensor exhibited robust antifouling performance in various single protein solutions and diluted milk samples, coupled with sensitive and selective recognition of TC. The sensor demonstrated a broad linear response range of 0.1-1000.0 ng mL-1 and a low limit of detection (LOD) of 68.0 pg mL-1. The antifouling electrochemical aptasensor proved effective in assaying TC in diluted milk, with recoveries ranging from 100.0 % to 104.4 %, eliminating the need for additional pretreatments due to its exceptional resistance to nonspecific adhesion.

Organoleptic modulation functions and physiochemical characteristics of mannoproteins: Possible correlations and precise applications in modulating color evolution and orthonasal perception of wines.

Mannoproteins have traditionally been recognized as effective wine organoleptic modulators, however, ambiguous understanding of the relationship between their organoleptic functions and physiochemical characteristics often lead to inappropriate application in winemaking. To reveal the possible role the physiochemical characteristics of mannoproteins play in modulating wine color and aroma properties, three water-soluble mannoproteins (MP1, MP2, MP3) with different physiochemical characteristics have been prepared, and accelerated red wine aging, malvidin pigments formation experiments, accelerated aroma release experiments have been designed to observe their organoleptic modulating functions in this research. Results suggest that the phenolic/chromatic stability of red wines could be enhanced by MP3, probably due to its low steric hindrance potential, high reactivity, and good hydro-alcoholic stability conferred by its high Mannan/Glucan ratio (8.68), abundant hydrophobic/hydrophilic amino acids (65.29 % of total protein), and low/medium molecular weight level (30.71-57.77 kDa), respectively, which protected the phenolic compounds and promoted the formation of pyranoanthocyanins. Mannoproteins could modulate the volatility of aroma compounds by expelling or retention effects, which depended on the duration of mannoprotein application (the expelling effect was firstly observed possibly because of the significant adsorption of free H2O by MPs) and the types of mannoproteins. MP1 and MP2 were prone to retain and expel aroma compounds, respectively, probably due to their medium/high molecular weight levels (60.48-135.39 kDa) that conferred abundant interacting sites, and the high proportion of hydrophobic and hydrophilic components in MP1 (97.71 % polysaccharides of total mannoprotein, 34.58 % hydrophobic amino acids of total protein) and MP2 (97.96 % polysaccharides of total mannoprotein, 28.36 % hydrophobic amino acids of total protein) guaranteed a relatively higher interacting frequency with aroma compounds and free H2O molecules, respectively.

Aroma and taste analysis of pickled tea from spontaneous and yeast-enhanced fermentation by mass spectrometry and sensory evaluation.

Anaerobically fermented pickled tea (PT) can be produced by spontaneous fermentation (SF) or yeast-enhanced fermentation (YF). Aroma and taste characteristics of PT during YF and SF were investigated using sensory evaluation, odour activity, aroma character impact values, HS-SPME-GC-MS, UPLC-QQQ-MS/MS, and spectrophotometry, annotating 198 volatile and 115 non-volatile components. The main contributing volatile components were ß-ionone, and 1-octanol, promoted by YF and SF, and yielding floral and fruity aromas respectively. Additionally, compared with SF, YF promoted the formation of citronellol yielding a floral aroma, inhibited the stale aroma of methoxybenzenes, and reduced bitter, astringent, and sour tastes. Furthermore, partial least-squares regression analysis identified the main components related to the 'acides aroma' of PT as linalool oxide, n-decanoic acid, hexanoic acid, 3,7-dimethyl-2,6-octadienoic acid, 3-methyl-1-dodecyn-3-ol, and nerolidol. This application could be used as methodology for the comprehensive analysis of tea aroma and taste and these results can act as guidelines for PT production and quality control.

Development and comparison of parallel reaction monitoring and data-independent acquisition methods for quantitative analysis of hydrophilic compounds in white tea.

In the present work, parallel reaction monitoring (PRM) and data-independent acquisition (DIA) methods were developed for the accurate quantitation of amino acids, alkaloids nucleosides and nucleotides in tea. The quality peaks were significantly enhanced by optimizing the LC elution procedure, HCD voltage, MS resolution, and scanning event. Both methods were validated with good liner linearity (0.004-200 µg/mL), LODs (0.001-0.309 µg/mL for PRM and 0.001-0.564 µg/mL for DIA). Applied to white tea sample, the contents of these hydrophilic compounds were range from 34,655.39 to 70,586.14 mg/kg, and caffeine (32,529.02 mg/kg) and theanine (5483.46 mg/kg) were determined as the most abundant ones. Based on the quantitation data set, the white tea samples from Puer, Lincang and Xishuangbanna were clearly discriminated using multivariate data analysis. The results of the present works show that PRM and DIA have great potential in quantitative analysis of multiple hydrophilic compounds in food samples.

Engineering an Antifouling Electrochemical Sensing Platform Based on an All-in-One Peptide and a Hierarchical ß-Bi2O3-Au Microsphere for Vancomycin Detection in Food.

Challenges associated with interference aroused by nonspecific attachment of foulants in the food matrix steered the development of sensor surfaces capable of antifouling capacity. In this study, an antifouling electrochemical sensing platform based on an all-in-one peptide (DOPA3-PPPPEKDQDKKaa) with anchoring, antifouling, and recognition functions and a hierarchical ß-Bi2O3-Au microsphere was proposed for vancomycin (Van) detection in food. The ß-Bi2O3-Au with excellent conductivity was synthesized and introduced as an electrode modifier to accelerate electron transfer on the sensor surface, enhancing sensing response. Mussel organism-inspired oligo DOPA, that is, oligo 3,4-dihydroxyphenylalanine, was employed as the anchoring segment of the all-in-one peptide, which is versatile for surfaces with different materials. PPPPEKDQDK and Kaa as antifouling and recognition segments confer abilities to resist nonspecific adsorption of foulants and specifically bind Van on the sensor surface, respectively. Notably, the excellent antifouling performance of the proposed sensor has been verified in protein solutions, carbohydrate solutions, and even in diluted milk and honey. Molecular dynamics simulation was carried out to explain the antifouling mechanism of the all-in-one peptide. The proposed sensor can detect Van sensitively and selectively with a relatively wide linear range (0.1-100 ng mL-1) and a limit of detection (LOD) as low as 0.038 ng mL-1 and support the quantification of Van in milk, milk powder, and honey samples with satisfactory recoveries within 105.3-110.8%. This antifouling electrochemical sensing platform offers a feasible strategy to reduce matrix interference, which guarantees the accurate detection of Van in food samples.

Analysis of Volatile Profile and Aromatic Characteristics of Raw Pu-erh Tea during Storage Based on GC-MS and Odor Activity Value.

Volatile constituents are critical to the flavor of tea, but their changes in raw Pu-erh tea (RAPT) during storage have not been clearly understood. This work aimed to investigate the volatile composition and their changes at various storage durations. The volatile profile of RAPT was determined using headspace solid-phase microextraction in combination gas chromatography-mass spectrometry. A total of 130 volatile compounds were identified in RAPT samples, and 64 of them were shared by all samples. The aroma attributes of RAPT over a storage period ranging from 0 to 10 years were assessed through the combination of odor activity value (OAV), aroma characteristic influence(ACI) value, and multivariate statistical analysis. The results revealed that RAPT exhibited a distinct floral and fruity aroma profile after storage for approximately 3-4 years. A notable shift in aroma was observed after 3-4 years of storage, indicating a significant turning point. Furthermore, the likely notable shift after 10 years of storage may signify the second turning point. According to the odor activity value (OAV ≥ 100), eight key volatile compounds were identified: linalool, α-terpineol, geraniol, trans-ß-ionone, α-ionone, (E,E)-2,4-heptadienal, 1-octanol, and octanal. Combining OAV (≥100) and ACI (≥1), five compounds, namely linalool, (E,E)-2,4-heptadienal, (Z)-3-hexen-1-ol, 2,6,10,10-tetramethyl-1-oxaspiro [4.5]dec-6-ene, and octanal, were identified as significant contributors to the aroma. The results offer a scientific foundation and valuable insights for understanding the volatile composition of RAPT and their changes during storage.

Nontargeted screening of aldehydes and ketones by chemical isotope labeling combined with ultra-high performance liquid chromatography-high resolution mass spectrometry followed by hybrid filtering of features.

Aldehydes and ketones are important carbonyl compounds that are widely present in foodstuffs, biological organisms and human living environment. However, it is still challenging to comprehensively detect and capture them using liquid chromatography - mass spectrometry. In this work, a chemical isotope labeling (CIL) coupled with ultra-high performance liquid chromatography - high resolution mass spectrometry (UHPLC-HRMS) strategy was developed for the capture and detection of this class of compounds. 2,4-Dinitrophenylhydrazine (DNPH) and isotope-labeled DNPH (DNPH-d3) were utilized to selectively label the target analytes. To address the difficulties in processing UHPLC-HRMS data, a post-acquisition data processing method called MSFilter was proposed to facilitate the screening and identification aldehydes and ketones in complex matrices. The MSFilter consists of four independent filters, namely statistical characteristic-based filtering, mass defect filtering, CIL paired peaks filtering, and diagnostic fragmentation ion filtering. These filters can be used individually or in combination to eliminate unrelated interfering MS features and efficiently detect DNPH-labeled aldehydes and ketones. The results of a mixture containing 48 model compounds showed that although all individual filtering methods could significantly reduce more than 95% of the raw MS features with acceptable recall rates above 85%, but they had relatively high false positive ratios of over 90%. In comparison, the hybrid filtering method combining four filters is able to eliminate massive interfering features (> 99.5%) with a high recall rate of 81.25% and a much lower false positive ratio of 15.22%. By implementing the hybrid filtering method in MSFilter, a total of 154 features were identified as potential signals of CCs from the original 45,961 features of real tobacco samples, of which 70 were annotated. We believe that the proposed strategy is promising to analyze the potential CCs in complex samples by UHPLC-HRMS.

Headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry (HS-SPME-GC-MS) and odor activity value (OAV) to reveal the flavor characteristics of ripened Pu-erh tea by co-fermentation.

Introduction: Pu-erh tea is a geographical indication product of China. The characteristic flavor compounds produced during the fermentation of ripened Pu-erh tea have an important impact on its quality. Methods: Headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry (HS-SPME-GC-MS) and odor activity value (OAV) is used for flavor analysis. Results: A total of 135 volatile compounds were annotated, of which the highest content was alcohols (54.26%), followed by esters (16.73%), and methoxybenzenes (12.69%). Alcohols in ripened Pu-erh tea mainly contribute flower and fruit sweet flavors, while methoxybenzenes mainly contribute musty and stale flavors. The ripened Pu-erh tea fermented by Saccharomyces: Rhizopus: Aspergillus niger mixed in the ratio of 1:1:1 presented the remarkable flavor characteristics of flower and fruit sweet flavor, and having better coordination with musty and stale flavor. Discussion: This study demonstrated the content changes of ripened Pu-erh tea's flavor compounds in the fermentation process, and revealed the optimal fermentation time. This will be helpful to further understand the formation mechanism of the characteristic flavor of ripened Pu-erh tea and guide the optimization of the fermentation process of ripened Pu-erh tea.

Mass defect filtering combined with molecular networking to profile flavonoids in citrus fruit based on liquid chromatography-high resolution mass spectrometry platform: Citrus sinensis (L.) Osbeck as a case study.

Citrus flavonoids are attracting great interest due to their well-known beneficial effects, but many of them have not been characterized. In this work, ultra-high liquid chromatography coupled to high resolution mass spectrometry (UHPLCHRMS) was used for profiling flavonoids in citrus fruit. We proposed a strategy combining mass defect filtering (MDF) and MS/MS-based molecular networking (MMN) to handle complex UHPLC-HRMS data. The proposed strategy was explained and validated in the fruit of Citrus sinensis (L.) Osbeck, and when specific mass and mass defect windows were pre-defined, MDF enable removal of considerable un-related and/or interference MS1 peaks. In citrus fruit, the number of MS1 peaks in positive and negative modes were reduced by 70.80% (from 15,113 to 4413) and 55.30% (from 5617 to 2511), respectively, and thus the potential MS features of flavonoids were retained and exposed. After MDF, an MS/MS similarity-based MMN map was constructed to cluster flavonoids with similar chemical structures. MMN facilitated the annotation of 65 unknown citrus flavonoids by using only 21 pre-identified flavonoids as references. The compounds comprised 42 polymethoxylated flavonoids, 17 flavones, 24 flavanones, and 3 flavonols. Eleven of them had not been previously reported in Citrus sinensis (L.) Osbeck to our knowledge. Results of the current work indicated that the combination of MDF and MMN is a useful strategy for removing interference MS1 peaks and performing the structural annotation of unkonwn compounds in complex samples.

[Comprehensive analysis of chemical constituents of tea flowers by ultra-performance liquid chromatography-high resolution mass spectrometry combined with integrated filtering strategy].

Tea flowers and fresh tea leaves are biological products of tea, but tea flower is often regarded as waste during tea production, resulting in notable waste of tea flower resources. At present, analysis of the chemical components in tea flowers focuses on single types of chemical components such as amino acids and tea polyphenols, and there are only a few reports on the simultaneous analysis of numerous chemical components in tea flowers. Researchers are not completely clear about the types and amounts of the chemical components in tea flowers; this has hindered the in-depth development and effective utilization of tea flowers. In this study, ultra-performance liquid chromatography-high resolution mass spectrometry (UPLC-HRMS) was used to detect the chemical constituents of tea flowers. This technique was combined with the integrated filtering strategy (IFS) of nitrogen rule filtering (NRF), mass defect filtering (MDF), and diagnostic fragment ion filtering (DFIF) for screening the characteristic mass spectra of the target chemical components. Furthermore, the chemical constituents of tea flowers were annotated with information about the retention time, MS fragmentation, and MS/MS fragmentation. All the qualitative chemical components were divided into six categories with a total of 137 chemical constituents, including 3 alkaloids, 38 flavonoids, 31 phenolic acids and their derivatives, 37 catechins and their derivatives, 18 amino acids, and 10 other components. The internal standard method was used to quantify all the qualitative chemical components. The quantitative results showed that the amounts of the six kinds of chemical components in tea flowers were as follows: amino acids, 9371.42 µg/g; catechins and their derivatives, 9068.43 µg/g; phenolic acids and their derivatives, 8696.92 µg/g; alkaloids, 4392.52 µg/g; flavonoids, 1192.88 µg/g; and others, 139.94 µg/g. Quality control samples were used to evaluate the stability of the instrument and the repeatability of the tested data. Nine representative chemical components with high, medium, and low contents in tea were selected, and the relative standard deviation (RSD) of the results was used to evaluate the repeatability of the data. These nine chemical constituents are selected from amino acids, alkaloids, flavonoids, phenolic acids and their derivatives, catechins and their derivatives, and other components, and the response intensities were different. The relative standard deviations of the nine chemical components were in the range of 2.11% to 12.17%. The above results demonstrated the good stability of the instrument and excellent repeatability of the test data. Chlorogenic acid components (CGAs) and glycosylated quercetin components (GQs) were used as two representative components to explain the entire process of extracting the target compounds by IFS. CGAs comprise a class of special esters formed by the esterification of cinnamic acid derivatives with quinic acid as the parent structure. The most common cinnamic acid derivatives are p-coumaric acid, caffeic acid, and ferulic acid. On the one hand, according to the above information and the different positions and degree of quinic acid esterification, the CGAs were structurally classified as monosubstituted CGAs (Mono-CGAs), disubstituted CGAs (Di-CGAs), and trisubstituted CGAs (Tri-CGAs), and three different mass defect filtering windows were set. Therefore, 751 possible target components were selected from 3537 mass spectra in accordance with the nitrogen rule. On the other hand, 22 target components in accordance with the nitrogen rule were obtained by further screening the m/z 191.0551 ion as the diagnostic fragment ion of the CGAs. Combining the overall analytical data with the above mass defect filtering and diagnostic fragment ion filtering screening results, nine target CGAs were selected and characterized based on the MS information. This study reveals the types and amounts of the chemical components accumulated in tea flowers, thus providing valuable information and serving as data reference for the in-depth development and effective utilization of tea flowers.

Targeted identification of glycosylated flavones and isomers in green tea through integrated ion-filtering strategy and mass-fragmentation characteristics based on the UPLC-Q-Orbitrap-MS/MS platform.

Glycosylated flavones (GFs) are important components of green tea and have various structures and isomers. The annotation of GFs' chemical structures is challenging. Ultrahigh-performance liquid chromatography-high resolution mass spectrometry can provide informative mass ions for GF annotation. However, distinguishing the mass features of GFs from those of thousands of ions is difficult. In this study, integrated ion-filtering strategies for O- and C-glycosyl flavones were constructed, and the mass-fragmentation characteristics were summarized from GF standards. Ultimately, 29 GFs with different types of aglycones and glycosides, connection modes, and locations were annotated. According to principal component analysis and t-test results, significant differences were observed in the contents of 16 components in the two kinds of tea. Among them, the contents of 11 GFs in autumn teas were significantly higher than those in spring teas. This study provided an efficient strategy for isomer annotation in food analysis.

Development and validation of an efficient HILIC-QQQ-MS/MS method for quantitative and comparative profiling of 45 hydrophilic compounds in four types of tea (Camellia sentences).

Hydrophilic constituents are significant for the taste and nutrition of tea, but their simultaneous quantification remains challenging due to the lack of efficient methods. Based on the hydrophilic interaction chromatography coupled with triple quadrupole-tandem mass spectrometry, this work developed and validated an efficient (8.5 min per run), sensitive (LOQ: 0.002-0.493 µg/mL) and accurate method. This method was successfully used to determine the contents of 45 hydrophilic constituents in Yunnan large-leaf tea. Umami amino acids and umami-enhanced nucleotides generally exhibited higher content in green tea and Pu-erh raw tea. By contrast, a few number of amino acids (e.g., proline and γ-aminobutyric acid) and most alkaloids and nucleosides showed significantly higher contents in black tea or Pu-erh ripen tea. By performing the orthogonal partial least squares discriminant analysis, classification models for distinguishing four types of tea, and green tea from Pu-erh raw tea were established.