Project description:Distilled liquors are important products, both culturally and economically. Chemically, as a complex mixture, distilled liquor comprises various chemical compounds in addition to ethanol. However, the chemical components of distilled liquors are still insufficiently understood and compositional differences and similarities of distilled liquors from different cultures have never been compared. For the first time, both volatile organic compounds (VOCs) and non-VOCs in distilled liquors were profiled using mass spectrometry-based metabolomic approaches. A total of 879 VOCs and 268 non-VOCs were detected in 24 distilled liquors including six typical Chinese baijiu and 18 typical Western liquors. Principal component analysis and a correlation network revealed important insights into the compositional differences and similarities of the distilled liquors that were assessed. Ethyl esters, a few benzene derivatives, and alcohols were shared by most distilled liquors assessed, suggesting their important contribution to the common flavor and mouthfeel of distilled liquors. Sugars and esters formed by fatty alcohol differ significantly between the assessed Chinese baijiu and Western liquors, and are potential marker compounds that could be used for their discrimination. Factors contributing to the differences in chemical composition are proposed. Our results improve our understanding of the chemical components of distilled liquors, which may contribute to more rigorous quality control of alcoholic beverages.
Project description:Volatile thiols give a unique flavor to foods and they have been extensively studied due to their effects on sensory properties. The analytical assay of volatile thiols in food is hindered by the complexity of the matrix, and by both their high reactivity and their typically low concentrations. A new ultraperformance liquid chromatography (UPLC) strategy has been developed for the identification and quantification of volatile thiols in Chinese liquor (Baijiu). 4,4'-Dithiodipyridine reacted rapidly with eight known thiols to form derivatives, which provided a diagnostic fragment ion (m/z 143.5) for tandem mass spectrometry (MS/MS). To screen for new thiols, Baijiu samples were analyzed by means of UPLC-MS/MS screening for compounds exhibiting the diagnostic fragment ion (m/z X→143.5). New peaks with precursor ions of m/z 244, 200 and 214 were detected. Using UPLC with quadrupole-time-of-flight mass spectrometry (UPLC-Q-TOF-MS) and authentic standards, ethyl 2-mercaptoacetate, 1-butanethiol, and 1-pentanethiol were identified in Baijiu for the first time. Commercial Baijiu samples were analyzed with the new method and the distribution of 11 thiols was revealed in different Baijiu aroma-types. The aroma contribution of these thiols was evaluated by their odoractivity values (OAVs), with the result that 7 of 11 volatile thiols had OAVs > 1. In particular, methanethiol, 2-furfurylthiol, and 2-methyl-3-furanthiol had relatively high OAVs, indicating that they contribute significantly to the aroma profile of Baijiu.
Project description:Carboxyl compounds have a significant influence on the flavor of Chinese Baijiu. However, because of the structural diversity and low concentration, the deep profiling of carboxyl compounds in Chinese Baijiu is still challenging. In this work, a systematic method for comprehensive analysis of carboxyl compounds in Chinese Baijiu was established. After derivatized under optimized conditions, 197 p-dimethylaminophenacyl bromide-derived carboxylic compounds were annotated by multidimensional information including accurate mass, predicted tR, in-silico MS/MS, and diagnostic ions for the first time. In addition, 48 of the 197 carboxyl compounds were positively identified, and three of them were newly identified in Chinese Baijiu. Moreover, we found the number and the concentration of carboxyl compounds in sauce-flavor Baijiu were more abundant than in strong-flavor Baijiu. This work provides a novel method for the analysis of carboxyl compounds in Baijiu and other complex samples.
Project description:Sauce-flavor Baijiu is one of the most complex and typical types of traditional Chinese liquor, whose trace components have an important impact on its taste and quality. Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) is one of the most favorable analytical tools to reveal trace molecular components in complex samples. This study analyzed the chemical diversity of several representative sauce-flavor Baijiu using the combination of electrospray ionization (ESI) and FT-ICR MS. The results showed that ESI+ and ESI- exhibited different chemical features characteristic of trace components. Overall, sauce-flavor Baijiu was dominated by CHO class compounds, and the main specific compound types were aliphatic, highly unsaturated with low oxygen, and peptide-like compounds. The mass spectral parameters resolved by FT-ICR MS of several well-known brands were relatively similar, whereas the greatest variability was observed from an internally supplied brand. This study provides a new perspective on the mass spectrometry characteristics of trace components of sauce-flavor Baijiu and offers a theoretical foundation for further optimization of the gradients in Baijiu.
Project description:Dipeptides in sauce-flavor Baijiu Daqu are protein degradation products during the fermentation of Daqu, which are believed to play a crucial role in the flavor and quality of Baijiu. Herein, we integrated dansyl chloride derivatization with ultrahigh-performance liquid chromatography coupled with high-resolution mass spectrometry (UHPLC-HRMS) for comprehensively profiling dipeptides in Daqu. The derivatization efficiency was higher than 99.1 % for all 17 dipeptide standards under the optimized derivatization conditions. In total, 118 dipeptides were detected in Daqu. The method was validated and the analytical characteristics including the linearity (spanned across 2-4 orders of magnitude), precision (1.2-19.9 %), limit of detection (varied from 1.1 to 53.4 pmol/mL) and the stability (3.6-15.8 %) are satisfactory. The usefulness of the method was examined by studying the distribution characteristics of dipeptides in Daqu under different production conditions. The present method provides an effective and robust strategy for comprehensively analyzing dipeptide compounds in complex biological samples.
Project description:Luzhoulaojiao liquor is a type of Chinese liquor that dates back hundreds of years, but whose precise chemical composition remains unknown. This paper describes the screening of the liquor and the identification of its compounds using comprehensive two-dimensional gas chromatography/time-of-flight mass spectrometry (GC × GC/TOF-MS). Samples were prepared by both liquid-liquid extraction and solid-phase microextraction, which facilitated the detection of thousands of compounds in the liquor, thus demonstrating the superior performance of the proposed method over those reported in previous studies. A total of 320 compounds were common to all 18 types of Luzhoulaojiao liquor studied here, and 13 abundant and potentially bioactive compounds were further quantified. The results indicated that the high-performance method presented here is well suited for the detection and identification of compounds in liquors. This study also contributes to enriching our knowledge of the contents of Chinese liquors.
Project description:Chromatographic fingerprinting has been perceived as an essential tool for assessing quality and chemical equivalence of traditional Chinese medicine. However, this pattern-oriented approach still has some weak points in terms of chemical coverage and robustness. In this work, we proposed a multiple reaction monitoring (MRM)-based fingerprinting method in which approximately 100 constituents were simultaneously detected for quality assessment. The derivative MRM approach was employed to rapidly design MRM transitions independent of chemical standards, based on which the large-scale fingerprinting method was efficiently established. This approach was exemplified on QiShenYiQi Pill (QSYQ), a traditional Chinese medicine-derived drug product, and its robustness was systematically evaluated by four indices: clustering analysis by principal component analysis, similarity analysis by the congruence coefficient, the number of separated peaks, and the peak area proportion of separated peaks. Compared with conventional ultraviolet-based fingerprints, the MRM fingerprints provided not only better discriminatory capacity for the tested normal/abnormal QSYQ samples, but also higher robustness under different chromatographic conditions (i.e., flow rate, apparent pH, column temperature, and column). The result also showed for such large-scale fingerprints including a large number of peaks, the angle cosine measure after min-max normalization was more suitable for setting a decision criterion than the unnormalized algorithm. This proof-of-concept application gives evidence that combining MRM technique with proper similarity analysis metrices can provide a highly sensitive, robust and comprehensive analytical approach for quality assessment of traditional Chinese medicine.
Project description:This paper proposes the combination of headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) and chemometrics as a method to detect the age of Chinese liquor (Baijiu). Headspace conditions were optimized through single-factor optimization experiments. The optimal sample preparation involved diluting Baijiu with saturated brine to 15% alcohol by volume. The sample was equilibrated at 70 °C for 30 min, and then analyzed with 200 μL of headspace gas. A total of 39 Baijiu samples from different vintages (1998-2019) were collected directly from pottery jars and analyzed using HS-GC-IMS. Partial least squares regression (PLSR) analysis was used to establish two discriminant models based on the 212 signal peaks and the 93 identified compounds. Although both models were valid, the model based on the 93 identified compounds discriminated the ages of the samples more accurately according to the goodness of fit value (R2) and the root mean square error of prediction (RMSEP), which were 0.9986 and 0.244, respectively. Nineteen compounds with variable importance for prediction (VIP) scores > 1, including 11 esters, 4 alcohols, and 4 aldehydes, played vital roles in the model established by the 93 identified compounds. Overall, we determined that HS-GC-IMS combined with PLSR could serve as a rapid and accurate method for detecting the age of Baijiu.
Project description:Nowadays, the quality of natural products is an issue of great interest in our society due to the increase in adulteration cases in recent decades. Coffee, one of the most popular beverages worldwide, is a food product that is easily adulterated. To prevent fraudulent practices, it is necessary to develop feasible methodologies to authenticate and guarantee not only the coffee's origin but also its variety, as well as its roasting degree. In the present study, a C18 reversed-phase liquid chromatography (LC) technique coupled to high-resolution mass spectrometry (HRMS) was applied to address the characterization and classification of Arabica and Robusta coffee samples from different production regions using chemometrics. The proposed non-targeted LC-HRMS method using electrospray ionization in negative mode was applied to the analysis of 306 coffee samples belonging to different groups depending on the variety (Arabica and Robusta), the growing region (e.g., Ethiopia, Colombia, Nicaragua, Indonesia, India, Uganda, Brazil, Cambodia and Vietnam), and the roasting degree. Analytes were recovered with hot water as the extracting solvent (coffee brewing). The data obtained were considered the source of potential descriptors to be exploited for the characterization and classification of the samples using principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA). In addition, different adulteration cases, involving nearby production regions and different varieties, were evaluated by pairs (e.g., Vietnam Arabica-Vietnam Robusta, Vietnam Arabica-Cambodia and Vietnam Robusta-Cambodia). The coffee adulteration studies carried out with partial least squares (PLS) regression demonstrated the good capability of the proposed methodology to quantify adulterant levels down to 15%, accomplishing calibration and prediction errors below 2.7% and 11.6%, respectively.
Project description:The brain functions through chemical interactions between many different cell types, including neurons and glia. Acquiring comprehensive information on complex, heterogeneous systems requires multiple analytical tools, each of which have unique chemical specificity and spatial resolution. Multimodal imaging generates complementary chemical information via spatially localized molecular maps, ideally from the same sample, but requires method enhancements that span from data acquisition to interpretation. We devised a protocol for performing matrix-assisted laser desorption/ionization (MALDI)-Fourier transform ion cyclotron resonance-mass spectrometry imaging (MSI), followed by infrared (IR) spectroscopic imaging on the same specimen. Multimodal measurements from the same tissue provide precise spatial alignment between modalities, enabling more advanced image processing such as image fusion and sharpening. Performing MSI first produces higher quality data from each technique compared to performing IR imaging before MSI. The difference is likely due to fixing the tissue section during MALDI matrix removal, thereby preventing analyte degradation occurring during IR imaging from an unfixed specimen. Leveraging the unique capabilities of each modality, we utilized pan sharpening of MS (mass spectrometry) ion images with selected bands from IR spectroscopy and midlevel data fusion. In comparison to sharpening with histological images, pan sharpening can employ a plethora of IR bands, producing sharpened MS images while retaining the fidelity of the initial ion images. Using Laplacian pyramid sharpening, we determine the localization of several lipids present within the hippocampus with high mass accuracy at 5 ?m pixel widths. Further, through midlevel data fusion of the imaging data sets combined with k-means clustering, the combined data set discriminates between additional anatomical structures unrecognized by the individual imaging approaches. Significant differences between molecular ion abundances are detected between relevant structures within the hippocampus, such as the CA1 and CA3 regions. Our methodology provides high quality multiplex and multimodal chemical imaging of the same tissue sample, enabling more advanced data processing and analysis routines.