1
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Zhang L, Wang Z, Zhang C, Zhou S, Yuan C. Metabolomics analysis based on UHPLC-QqQ-MS/MS to discriminate grapes and wines from different geographical origins and climatological characteristics. Food Chem X 2024; 22:101396. [PMID: 38699585 PMCID: PMC11063387 DOI: 10.1016/j.fochx.2024.101396] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2024] [Revised: 04/15/2024] [Accepted: 04/16/2024] [Indexed: 05/05/2024] Open
Abstract
With the proliferation of the consumer's awareness of wine provenance, wines with unique origin characteristics are increasingly in demand. This study aimed to investigate the influence of geographical origins and climatological characteristics on grapes and wines. A total of 94 anthocyanins and 78 non-anthocyanin phenolic compounds in grapes and wines from five Chinese viticultural vineyards (CJ, WH, QTX, WW, and XY) were identified by UHPLC-QqQ-MS/MS. Chemometric methods PCA and OPLS-DA were established to select candidate differential metabolites, including flavonols, stilbenes, hydroxycinnamic acids, peonidin derivatives, and malvidin derivatives. CCA showed that malvidin-3-O-glucoside had a positive correlation with mean temperature, and quercetin-3-O-glucoside had a negative correlation with precipitation. In addition, enrichment analysis elucidated that the metabolic diversity in different origins mainly occurred in flavonoid biosynthesis. This study would provide some new insights to understand the effect of geographical origins and climatological characteristics on phenolic compounds in grapes and wines.
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Affiliation(s)
- Lin Zhang
- College of Enology, Northwest A&F University, Yangling 712100, China
| | - Zhaoxiang Wang
- College of Enology, Northwest A&F University, Yangling 712100, China
| | - Cui Zhang
- College of Enology, Northwest A&F University, Yangling 712100, China
- Xinjiang Bainian Manor Wines & Spirits Co., Ltd, China
| | - Shubo Zhou
- College of Enology, Northwest A&F University, Yangling 712100, China
| | - Chunlong Yuan
- College of Enology, Northwest A&F University, Yangling 712100, China
- Ningxia Helan Mountain's East Foothill Wine Experiment and Demonstration Station of Northwest A&F University, Yongning, Ningxia 750104, China
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2
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Lin X, Wu H, Huang G, Wu Q, Yao ZP. Rapid authentication of red wine by MALDI-MS combined with DART-MS. Anal Chim Acta 2023; 1283:341966. [PMID: 37977790 DOI: 10.1016/j.aca.2023.341966] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 09/23/2023] [Accepted: 10/25/2023] [Indexed: 11/19/2023]
Abstract
A simple, rapid and high-throughput approach was developed for authentication of red wine for the first time, by combining spectral results from matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) and direct analysis in real time mass spectrometry (DART-MS). By coupling with orthogonal partial least squares discrimination analysis (OPLS-DA), this approach enabled successful classification of 535 wines from 8 countries, with the correct classification rates of 100% on the calibration set and over 90% on the validation set for almost all countries, and 26 potential characteristic markers selected. Compared to one single technique, this approach allowed detection of more compound ions, and with better fitting and predictive performances. The satisfactory differentiation results of vintages and grape varieties further verified the robustness of the approach. This study demonstrated the feasibility of combining multiple mass spectrometric techniques for wine analysis, which can be extended to other fields or to combinations of other analytical techniques.
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Affiliation(s)
- Xuewei Lin
- State Key Laboratory of Chemical Biology and Drug Discovery, and Department of Applied Biology and Chemical Technology, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong Special Administrative Region of China; Research Institute for Future Food, and Research Center for Chinese Medicine Innovation, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong Special Administrative Region of China; State Key Laboratory of Chinese Medicine and Molecular Pharmacology (Incubation), and Shenzhen Key Laboratory of Food Biological Safety Control, Hong Kong Polytechnic University Shenzhen Research Institute, Shenzhen, 518057, China
| | - Hao Wu
- Key Laboratory of the Ministry of Education for Coastal and Wetland Ecosystems, College of the Environment and Ecology, Xiamen University, Fujian, 361102, China
| | - Gefei Huang
- State Key Laboratory of Chemical Biology and Drug Discovery, and Department of Applied Biology and Chemical Technology, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong Special Administrative Region of China; Research Institute for Future Food, and Research Center for Chinese Medicine Innovation, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong Special Administrative Region of China; State Key Laboratory of Chinese Medicine and Molecular Pharmacology (Incubation), and Shenzhen Key Laboratory of Food Biological Safety Control, Hong Kong Polytechnic University Shenzhen Research Institute, Shenzhen, 518057, China
| | - Qian Wu
- State Key Laboratory of Chemical Biology and Drug Discovery, and Department of Applied Biology and Chemical Technology, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong Special Administrative Region of China; Research Institute for Future Food, and Research Center for Chinese Medicine Innovation, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong Special Administrative Region of China; State Key Laboratory of Chinese Medicine and Molecular Pharmacology (Incubation), and Shenzhen Key Laboratory of Food Biological Safety Control, Hong Kong Polytechnic University Shenzhen Research Institute, Shenzhen, 518057, China
| | - Zhong-Ping Yao
- State Key Laboratory of Chemical Biology and Drug Discovery, and Department of Applied Biology and Chemical Technology, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong Special Administrative Region of China; Research Institute for Future Food, and Research Center for Chinese Medicine Innovation, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong Special Administrative Region of China; State Key Laboratory of Chinese Medicine and Molecular Pharmacology (Incubation), and Shenzhen Key Laboratory of Food Biological Safety Control, Hong Kong Polytechnic University Shenzhen Research Institute, Shenzhen, 518057, China.
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3
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Jeppesen MJ, Powers R. Multiplatform untargeted metabolomics. MAGNETIC RESONANCE IN CHEMISTRY : MRC 2023; 61:628-653. [PMID: 37005774 PMCID: PMC10948111 DOI: 10.1002/mrc.5350 10.1002/mrc.5350] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Revised: 03/29/2023] [Accepted: 03/30/2023] [Indexed: 06/23/2024]
Abstract
Metabolomics samples like human urine or serum contain upwards of a few thousand metabolites, but individual analytical techniques can only characterize a few hundred metabolites at best. The uncertainty in metabolite identification commonly encountered in untargeted metabolomics adds to this low coverage problem. A multiplatform (multiple analytical techniques) approach can improve upon the number of metabolites reliably detected and correctly assigned. This can be further improved by applying synergistic sample preparation along with the use of combinatorial or sequential non-destructive and destructive techniques. Similarly, peak detection and metabolite identification strategies that employ multiple probabilistic approaches have led to better annotation decisions. Applying these techniques also addresses the issues of reproducibility found in single platform methods. Nevertheless, the analysis of large data sets from disparate analytical techniques presents unique challenges. While the general data processing workflow is similar across multiple platforms, many software packages are only fully capable of processing data types from a single analytical instrument. Traditional statistical methods such as principal component analysis were not designed to handle multiple, distinct data sets. Instead, multivariate analysis requires multiblock or other model types for understanding the contribution from multiple instruments. This review summarizes the advantages, limitations, and recent achievements of a multiplatform approach to untargeted metabolomics.
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Affiliation(s)
- Micah J. Jeppesen
- Department of Chemistry, University of Nebraska-Lincoln, Lincoln, NE 68588-0304, United States
- Nebraska Center for Integrated Biomolecular Communication, University of Nebraska-Lincoln, Lincoln, NE 68588-0304, United States
| | - Robert Powers
- Department of Chemistry, University of Nebraska-Lincoln, Lincoln, NE 68588-0304, United States
- Nebraska Center for Integrated Biomolecular Communication, University of Nebraska-Lincoln, Lincoln, NE 68588-0304, United States
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4
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Jeppesen MJ, Powers R. Multiplatform untargeted metabolomics. MAGNETIC RESONANCE IN CHEMISTRY : MRC 2023; 61:628-653. [PMID: 37005774 PMCID: PMC10948111 DOI: 10.1002/mrc.5350] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Revised: 03/29/2023] [Accepted: 03/30/2023] [Indexed: 06/19/2023]
Abstract
Metabolomics samples like human urine or serum contain upwards of a few thousand metabolites, but individual analytical techniques can only characterize a few hundred metabolites at best. The uncertainty in metabolite identification commonly encountered in untargeted metabolomics adds to this low coverage problem. A multiplatform (multiple analytical techniques) approach can improve upon the number of metabolites reliably detected and correctly assigned. This can be further improved by applying synergistic sample preparation along with the use of combinatorial or sequential non-destructive and destructive techniques. Similarly, peak detection and metabolite identification strategies that employ multiple probabilistic approaches have led to better annotation decisions. Applying these techniques also addresses the issues of reproducibility found in single platform methods. Nevertheless, the analysis of large data sets from disparate analytical techniques presents unique challenges. While the general data processing workflow is similar across multiple platforms, many software packages are only fully capable of processing data types from a single analytical instrument. Traditional statistical methods such as principal component analysis were not designed to handle multiple, distinct data sets. Instead, multivariate analysis requires multiblock or other model types for understanding the contribution from multiple instruments. This review summarizes the advantages, limitations, and recent achievements of a multiplatform approach to untargeted metabolomics.
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Affiliation(s)
- Micah J. Jeppesen
- Department of Chemistry, University of Nebraska-Lincoln, Lincoln, NE 68588-0304, United States
- Nebraska Center for Integrated Biomolecular Communication, University of Nebraska-Lincoln, Lincoln, NE 68588-0304, United States
| | - Robert Powers
- Department of Chemistry, University of Nebraska-Lincoln, Lincoln, NE 68588-0304, United States
- Nebraska Center for Integrated Biomolecular Communication, University of Nebraska-Lincoln, Lincoln, NE 68588-0304, United States
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5
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Lv Y, Wang JN, Jiang Y, Ma XM, Ma FL, Ma XL, Zhang Y, Tang LH, Wang WX, Ma GM, Yu YJ. Identification of Oak-Barrel and Stainless Steel Tanks with Oak Chips Aged Wines in Ningxia Based on Three-Dimensional Fluorescence Spectroscopy Combined with Chemometrics. Molecules 2023; 28:molecules28093688. [PMID: 37175098 PMCID: PMC10180402 DOI: 10.3390/molecules28093688] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Revised: 04/12/2023] [Accepted: 04/22/2023] [Indexed: 05/15/2023] Open
Abstract
With the increased incidence of wine fraud, a fast and reliable method for wine certification has become a necessary prerequisite for the vigorous development of the global wine industry. In this study, a classification strategy based on three-dimensional fluorescence spectroscopy combined with chemometrics was proposed for oak-barrel and stainless steel tanks with oak chips aged wines. Principal component analysis (PCA), partial least squares analysis (PLS-DA), and Fisher discriminant analysis (FDA) were used to distinguish and evaluate the data matrix of the three-dimensional fluorescence spectra of wines. The results showed that FDA was superior to PCA and PLS-DA in classifying oak-barrel and stainless steel tanks with oak chips aged wines. As a general conclusion, three-dimensional fluorescence spectroscopy can provide valuable fingerprint information for the identification of oak-barrel and stainless steel tanks with oak chips aged wines, while the study will provide some theoretical references and standards for the quality control and quality assessment of oak-barrel aged wines.
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Affiliation(s)
- Yi Lv
- Key Laboratory of Quality and Safety of Wolfberry and Wine for State Administration for Market Regulation, Ningxia Food Testing and Research Institute, Yinchuan 750004, China
| | - Jia-Nan Wang
- College of Pharmacy, Ningxia Medical University, Yinchuan 750004, China
- Key Laboratory of Ningxia Minority Medicine Modernization, Ministry of Education, Yinchuan 750004, China
| | - Yuan Jiang
- Key Laboratory of Quality and Safety of Wolfberry and Wine for State Administration for Market Regulation, Ningxia Food Testing and Research Institute, Yinchuan 750004, China
| | - Xue-Mei Ma
- Key Laboratory of Quality and Safety of Wolfberry and Wine for State Administration for Market Regulation, Ningxia Food Testing and Research Institute, Yinchuan 750004, China
| | - Feng-Lian Ma
- College of Pharmacy, Ningxia Medical University, Yinchuan 750004, China
- Key Laboratory of Ningxia Minority Medicine Modernization, Ministry of Education, Yinchuan 750004, China
| | - Xing-Ling Ma
- College of Pharmacy, Ningxia Medical University, Yinchuan 750004, China
- Key Laboratory of Ningxia Minority Medicine Modernization, Ministry of Education, Yinchuan 750004, China
| | - Yao Zhang
- Key Laboratory of Quality and Safety of Wolfberry and Wine for State Administration for Market Regulation, Ningxia Food Testing and Research Institute, Yinchuan 750004, China
| | - Li-Hua Tang
- Key Laboratory of Quality and Safety of Wolfberry and Wine for State Administration for Market Regulation, Ningxia Food Testing and Research Institute, Yinchuan 750004, China
| | - Wen-Xin Wang
- College of Pharmacy, Ningxia Medical University, Yinchuan 750004, China
- Key Laboratory of Ningxia Minority Medicine Modernization, Ministry of Education, Yinchuan 750004, China
| | - Gui-Mei Ma
- College of Pharmacy, Ningxia Medical University, Yinchuan 750004, China
- Key Laboratory of Ningxia Minority Medicine Modernization, Ministry of Education, Yinchuan 750004, China
| | - Yong-Jie Yu
- College of Pharmacy, Ningxia Medical University, Yinchuan 750004, China
- Key Laboratory of Ningxia Minority Medicine Modernization, Ministry of Education, Yinchuan 750004, China
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6
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Could Collected Chemical Parameters Be Utilized to Build Soft Sensors Capable of Predicting the Provenance, Vintages, and Price Points of New Zealand Pinot Noir Wines Simultaneously? Foods 2023; 12:foods12020323. [PMID: 36673415 PMCID: PMC9857561 DOI: 10.3390/foods12020323] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2022] [Revised: 12/26/2022] [Accepted: 12/29/2022] [Indexed: 01/12/2023] Open
Abstract
Soft sensors work as predictive frameworks encapsulating a set of easy-to-collect input data and a machine learning method (ML) to predict highly related variables that are difficult to measure. The machine learning method could provide a prediction of complex unknown relations between the input data and desired output parameters. Recently, soft sensors have been applicable in predicting the prices and vintages of New Zealand Pinot noir wines based on chemical parameters. However, the previous sample size did not adequately represent the diversity of provenances, vintages, and price points across commercially available New Zealand Pinot noir wines. Consequently, a representative sample of 39 commercially available New Zealand Pinot noir wines from diverse provenances, vintages, and price points were selected. Literature has shown that wine phenolic compounds strongly correlated with wine provenances, vintages and price points, which could be used as input data for developing soft sensors. Due to the significance of these phenolic compounds, chemical parameters, including phenolic compounds and pH, were collected using UV-Vis visible spectrophotometry and a pH meter. The soft sensor utilising Naive Bayes (belongs to ML) was designed to predict Pinot noir wines' provenances (regions of origin) based on six chemical parameters with the prediction accuracy of over 75%. Soft sensors based on decision trees (within ML) could predict Pinot noir wines' vintages and price points with prediction accuracies of over 75% based on six chemical parameters. These predictions were based on the same collected six chemical parameters as aforementioned.
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7
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Li S, Du D, Wang J, Wei Z. Application progress of intelligent flavor sensing system in the production process of fermented foods based on the flavor properties. Crit Rev Food Sci Nutr 2022; 64:3764-3793. [PMID: 36259959 DOI: 10.1080/10408398.2022.2134982] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
Fermented foods are sensitive to the production conditions because of microbial and enzymatic activities, which requires intelligent flavor sensing system (IFSS) to monitor and optimize the production process based on the flavor properties. As the simulation system of human olfaction and gustation, IFSS has been widely used in the field of food with the characteristics of nondestructive, pollution-free, and real-time detection. This paper reviews the application of IFSS in the control of fermentation, ripening, and shelf life, and the potential in the identification of quality differences and flavor-producing microbes in fermented foods. The survey found that electronic nose (tongue) is suitable to monitor fermentation process and identify food authenticity in real time based on the changes of flavor profile. Gas chromatography-ion mobility spectrometry and nuclear magnetic resonance technology can be used to analyze the flavor metabolism of fermented foods at various production stages and explore the correlation between flavor substances and microorganisms.
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Affiliation(s)
- Siying Li
- Department of Biosystems Engineering, Zhejiang University, Hangzhou, China
| | - Dongdong Du
- Department of Biosystems Engineering, Zhejiang University, Hangzhou, China
| | - Jun Wang
- Department of Biosystems Engineering, Zhejiang University, Hangzhou, China
| | - Zhenbo Wei
- Department of Biosystems Engineering, Zhejiang University, Hangzhou, China
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8
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Jiang M, Chattopadhyay AN, Rotello VM. Cell-Based Chemical Safety Assessment and Therapeutic Discovery Using Array-Based Sensors. Int J Mol Sci 2022; 23:3672. [PMID: 35409032 PMCID: PMC8998465 DOI: 10.3390/ijms23073672] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2022] [Revised: 03/22/2022] [Accepted: 03/25/2022] [Indexed: 12/11/2022] Open
Abstract
Synthetic chemicals are widely used in food, agriculture, and medicine, making chemical safety assessments necessary for environmental exposure. In addition, the rapid determination of chemical drug efficacy and safety is a key step in therapeutic discoveries. Cell-based screening methods are non-invasive as compared with animal studies. Cellular phenotypic changes can also provide more sensitive indicators of chemical effects than conventional cell viability. Array-based cell sensors can be engineered to maximize sensitivity to changes in cell phenotypes, lowering the threshold for detecting cellular responses under external stimuli. Overall, array-based sensing can provide a robust strategy for both cell-based chemical risk assessments and therapeutics discovery.
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Affiliation(s)
| | | | - Vincent M. Rotello
- Department of Chemistry, University of Massachusetts Amherst, 710 North Pleasant Street, Amherst, MA 01003, USA; (M.J.); (A.N.C.)
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9
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Yu H, Zheng D, Xie T, Xie J, Tian H, Ai L, Chen C. Comprehensive two-dimensional gas chromatography mass spectrometry-based untargeted metabolomics to clarify the dynamic variations in the volatile composition of Huangjiu of different ages. J Food Sci 2022; 87:1563-1574. [PMID: 35262917 DOI: 10.1111/1750-3841.16047] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Revised: 11/14/2021] [Accepted: 12/20/2021] [Indexed: 01/17/2023]
Abstract
Aging plays an important role in the formation of aroma characteristics of Huangjiu, a traditional Chinese alcoholic beverage. Comprehensive two-dimensional gas chromatography mass spectrometry (GC×GC-qMS)-based untargeted metabolomics combined with a multivariate analysis was used to investigate the dynamic variations in the aroma profile of Huangjiu during aging process and to establish the relationship between the changing volatile metabolite profiles and the age-dependent sensory attributes. A total of 144 volatile metabolites were identified by GC×GC-qMS and 63 were selected as critical metabolites based on variable importance in projection values and p-values. Based on the results of principal component analysis, orthogonal partial least-squares discriminant analysis, and hierarchical clustering analysis, the samples of six different ages were divided into three groups: 1Y and 3Y samples, 5Y and 8Y samples, and 10Y and 15Y samples. The partial least-squares analysis results further revealed the relationship between the aromas attributes and variations of these volatile compounds. The high esters, aldehydes, and lactones contents contributed to the high intensities of the sweet and ester aroma attributes of the aged Huangjiu, while the high alcohols and ethyl esters contents contributed to the alcoholic and fruity aroma attributes of the newly brewed Huangjiu. These results improve our understanding of the chemical nature of the aroma characteristics of aged Huangjiu. PRACTICAL APPLICATION: Huangjiu is often labeled with its age as a measure of quality, which influences consumers' choice. Dynamic variations in volatile compounds of Huangjiu during aging and its contribution to the aroma characteristics of Huangjiu were figured out, which will assist the industry to produce better quality aged Huangjiu for consumers.
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Affiliation(s)
- Haiyan Yu
- Department of Food Science and Technology, Shanghai Institute of Technology, Shanghai, China
| | - Danwei Zheng
- Department of Food Science and Technology, Shanghai Institute of Technology, Shanghai, China
| | - Tong Xie
- Department of Food Science and Technology, Shanghai Institute of Technology, Shanghai, China
| | - Jingru Xie
- Department of Food Science and Technology, Shanghai Institute of Technology, Shanghai, China
| | - Huaixiang Tian
- Department of Food Science and Technology, Shanghai Institute of Technology, Shanghai, China
| | - Lianzhong Ai
- School of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai, China
| | - Chen Chen
- Department of Food Science and Technology, Shanghai Institute of Technology, Shanghai, China
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Khakimov B, Bakhytkyzy I, Fauhl-Hassek C, Engelsen SB. Non-volatile molecular composition and discrimination of single grape white of chardonnay, riesling, sauvignon blanc and silvaner using untargeted GC-MS analysis. Food Chem 2022; 369:130878. [PMID: 34469837 DOI: 10.1016/j.foodchem.2021.130878] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2020] [Revised: 07/25/2021] [Accepted: 08/14/2021] [Indexed: 01/12/2023]
Abstract
This study developed and applied a GC-MS method aiming at molecular fingerprinting of 120 commercial single grape white wines (Chardonnay, Riesling, Sauvignon Blanc and Silvaner) for possible authentication according to grape variety. The method allowed detection of 372 peaks and tentative identification of 146 metabolites including alcohols, organic acids, esters, amino acids and sugars. The grape variety effect explained 8.3% of the total metabolite variation. Univariate tests showed two-thirds of the metabolites being different between grape varieties. Partial least squares-discriminant analysis based classification models were developed for each grape variety and a panel of classifiers (42 metabolites) was established. All the classification models for grape variety showed a high certainty (>91%) for an independent test set. Riesling contained the highest relative concentrations of sugars and organic acids, while concentrations of hydroxytyrosol and gallic acid, common antioxidants in wine, decreased in the order of Chardonnay > Riesling > Sauvignon Blanc > Silvaner.
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Affiliation(s)
- Bekzod Khakimov
- Department of Food Science, University of Copenhagen, Rolighedsvej 26, Frederiksberg 1958, Denmark.
| | - Inal Bakhytkyzy
- Department of Analytical Chemistry, Chemical Faculty, Gdansk University of Technology, 11/12 Narutowicza St., 80-233 Gdansk, Poland
| | - Carsten Fauhl-Hassek
- German Federal Institute for Risk Assessment, Head of Unit Product Identity, Supply Chains and Traceability Department Safety in the Food Chain, Max-Dohrn-Straße 8-10, 10589 Berlin, Germany
| | - Søren Balling Engelsen
- Department of Food Science, University of Copenhagen, Rolighedsvej 26, Frederiksberg 1958, Denmark
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11
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Laliwala A, Svechkarev D, Sadykov MR, Endres J, Bayles KW, Mohs AM. Simpler Procedure and Improved Performance for Pathogenic Bacteria Analysis with a Paper-Based Ratiometric Fluorescent Sensor Array. Anal Chem 2022; 94:2615-2624. [PMID: 35073053 PMCID: PMC10091516 DOI: 10.1021/acs.analchem.1c05021] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Bacterial infections are the leading cause of morbidity and mortality in the world, particularly due to a delay in treatment and misidentification of the bacterial species causing the infection. Therefore, rapid and accurate identification of these pathogens has been of prime importance. The conventional diagnostic techniques include microbiological, biochemical, and genetic analyses, which are time-consuming, require large sample volumes, expensive equipment, reagents, and trained personnel. In response, we have now developed a paper-based ratiometric fluorescent sensor array. Environment-sensitive fluorescent dyes (3-hydroxyflavone derivatives) pre-adsorbed on paper microzone plates fabricated using photolithography, upon interaction with bacterial cell envelopes, generate unique fluorescence response patterns. The stability and reproducibility of the sensor array response were thoroughly investigated, and the analysis procedure was refined for optimal performance. Using neural networks for response pattern analysis, the sensor was able to identify 16 bacterial species and recognize their Gram status with an accuracy rate greater than 90%. The paper-based sensor was stable for up to 6 months after fabrication and required 30 times lower dye and sample volumes as compared to the analogous solution-based sensor. Therefore, this approach opens avenues to a state-of-the-art diagnostic tool that can be potentially translated into clinical applications in low-resource environments.
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Affiliation(s)
- Aayushi Laliwala
- Department of Pharmaceutical Sciences, University of Nebraska Medical Center, Omaha, Nebraska 68198-6858, United States
| | - Denis Svechkarev
- Department of Pharmaceutical Sciences, University of Nebraska Medical Center, Omaha, Nebraska 68198-6858, United States
| | - Marat R. Sadykov
- Department of Pathology and Microbiology, University of Nebraska Medical Center, Omaha, Nebraska 68198-5900, United States
| | - Jennifer Endres
- Department of Pathology and Microbiology, University of Nebraska Medical Center, Omaha, Nebraska 68198-5900, United States
| | - Kenneth W. Bayles
- Department of Pathology and Microbiology, University of Nebraska Medical Center, Omaha, Nebraska 68198-5900, United States
| | - Aaron M. Mohs
- Department of Pharmaceutical Sciences, University of Nebraska Medical Center, Omaha, Nebraska 68198-6858, United States
- Fred and Pamela Buffet Cancer Center, University of Nebraska Medical Center, Omaha, Nebraska 68198-5900, United States
- Department of Biochemistry and Molecular Biology, University of Nebraska Medical Center, Omaha, Nebraska 68198-6858, United States
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12
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Sasaki Y, Lyu X, Tang W, Wu H, Minami T. Polythiophene-Based Chemical Sensors: Toward On-Site Supramolecular Analytical Devices. BULLETIN OF THE CHEMICAL SOCIETY OF JAPAN 2021. [DOI: 10.1246/bcsj.20210265] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Affiliation(s)
- Yui Sasaki
- Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505, Japan
| | - Xiaojun Lyu
- Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505, Japan
| | - Wei Tang
- Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505, Japan
| | - Hao Wu
- Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505, Japan
| | - Tsuyoshi Minami
- Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505, Japan
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13
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Li T, Zhou Z, Zhang K, Ma W, Chen W, Tu P, Li J, Song Q, Song Y. Direct infusion-tandem mass spectrometry combining with data mining strategies enables rapid chemome characterization of medicinal plants: A case study of Polygala tenuifolia. J Pharm Biomed Anal 2021; 204:114281. [PMID: 34333452 DOI: 10.1016/j.jpba.2021.114281] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Revised: 07/22/2021] [Accepted: 07/22/2021] [Indexed: 12/20/2022]
Abstract
Data-independent MS2 spectrum acquisition after fragmenting the precursor ion cohort with 1 Da bin, termed as MS/MSALL ®, offers an opportunity to achieve rapid chemome characterization when being coupled with direct infusion (DI). Some post-acquisition data processing strategies, such as mass defect filtering (MDF), diagnostic fragment ion filtering (DFIF), and neutral loss filtering (NLF), facilitate data extraction from massive dataset, and moreover, molecular weight (MW) imprinting allows rapid capturing those reported components. Here, DI-MS/MSALL ® was employed to acquire cubic spectral dataset, and the strategies such as MW imprinting, MDF, DFIF, and NLF, were subsequently applied to filter the structural information. The integrated pipeline was utilized for the chemome characterization of Polygala tenuifolia, a famous edible medicinal plant. To aid information filtering, an in-house chemical library was built by comprehensively collecting structural information from some available databases. A single analytical run was completed within 5 min. For MS1 spectrum processing, MW imprinting was firstly applied to capture the compounds in the chemical library, and "five-point" MDF frames were employed to pursue saponins, oligosaccharide esters, and xanthones. Regarding MS2 spectral plot, DFIF and NLF were deployed to search information-of-interest. Structural identification was accomplished by carefully correlating precursor ions and MS2 spectra, applying the well-defined mass cracking rules, and referring to literature information as well as available databases. A total of 109 compounds, mainly saponins (40 ones), oligosaccharide esters (29 ones), and xanthones (19 ones), were captured and structurally annotated. MS1 spectra were also implemented for chemome comparison between Polygala tenuifolia and several similar plants belonging to Polygala genus, resulting in the observation of significant inter- and intra-species differences. Above all, DI-MS/MSALL ® is a promising choice for high-throughput chemome profiling of, but not limited to, medicinal plants, in particular when being integrated with post-acquisition data processing strategies.
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Affiliation(s)
- Ting Li
- Modern Research Center for Traditional Chinese Medicine, School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 100029, China
| | - Zhizi Zhou
- Department of Genetics and Endocrinology, Guangzhou Women and Children's Medical Center, Guangzhou, 510000, China
| | - Ke Zhang
- Modern Research Center for Traditional Chinese Medicine, School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 100029, China
| | - Wen Ma
- State Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Sciences, Peking University, Beijing, 100191, China
| | - Wei Chen
- Modern Research Center for Traditional Chinese Medicine, School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 100029, China
| | - Pengfei Tu
- Modern Research Center for Traditional Chinese Medicine, School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 100029, China
| | - Jun Li
- Modern Research Center for Traditional Chinese Medicine, School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 100029, China
| | - Qingqing Song
- Modern Research Center for Traditional Chinese Medicine, School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 100029, China.
| | - Yuelin Song
- Modern Research Center for Traditional Chinese Medicine, School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 100029, China.
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14
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Ranaweera RKR, Capone DL, Bastian SEP, Cozzolino D, Jeffery DW. A Review of Wine Authentication Using Spectroscopic Approaches in Combination with Chemometrics. Molecules 2021; 26:molecules26144334. [PMID: 34299609 PMCID: PMC8307441 DOI: 10.3390/molecules26144334] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Revised: 07/12/2021] [Accepted: 07/14/2021] [Indexed: 11/25/2022] Open
Abstract
In a global context where trading of wines involves considerable economic value, the requirement to guarantee wine authenticity can never be underestimated. With the ever-increasing advancements in analytical platforms, research into spectroscopic methods is thriving as they offer a powerful tool for rapid wine authentication. In particular, spectroscopic techniques have been identified as a user-friendly and economical alternative to traditional analyses involving more complex instrumentation that may not readily be deployable in an industry setting. Chemometrics plays an indispensable role in the interpretation and modelling of spectral data and is frequently used in conjunction with spectroscopy for sample classification. Considering the variety of available techniques under the banner of spectroscopy, this review aims to provide an update on the most popular spectroscopic approaches and chemometric data analysis procedures that are applicable to wine authentication.
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Affiliation(s)
- Ranaweera K. R. Ranaweera
- Department of Wine Science and Waite Research Institute, The University of Adelaide, PMB 1, Glen Osmond, SA 5064, Australia; (R.K.R.R.); (D.L.C.); (S.E.P.B.)
| | - Dimitra L. Capone
- Department of Wine Science and Waite Research Institute, The University of Adelaide, PMB 1, Glen Osmond, SA 5064, Australia; (R.K.R.R.); (D.L.C.); (S.E.P.B.)
- Australian Research Council Training Centre for Innovative Wine Production, The University of Adelaide, PMB 1, Glen Osmond, SA 5064, Australia
| | - Susan E. P. Bastian
- Department of Wine Science and Waite Research Institute, The University of Adelaide, PMB 1, Glen Osmond, SA 5064, Australia; (R.K.R.R.); (D.L.C.); (S.E.P.B.)
- Australian Research Council Training Centre for Innovative Wine Production, The University of Adelaide, PMB 1, Glen Osmond, SA 5064, Australia
| | - Daniel Cozzolino
- Queensland Alliance for Agriculture and Food Innovation (QAAFI), The University of Queensland, Hartley Teakle Building, Brisbane, QLD 4072, Australia;
| | - David W. Jeffery
- Department of Wine Science and Waite Research Institute, The University of Adelaide, PMB 1, Glen Osmond, SA 5064, Australia; (R.K.R.R.); (D.L.C.); (S.E.P.B.)
- Australian Research Council Training Centre for Innovative Wine Production, The University of Adelaide, PMB 1, Glen Osmond, SA 5064, Australia
- Correspondence: ; Tel.: +61-8-8313-6649
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15
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Khrapov A, Prakh A, Antonenko M. The influence of agricultural practices in vineyards on the predisposition of wines to crystalline turbidities. BIO WEB OF CONFERENCES 2021. [DOI: 10.1051/bioconf/20213406005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
On the example of the Cabernet-Sauvignon variety, the dependence of the physicochemical parameters of grape must and the wine materials produced from it, on the formation of the grape bush (Cordon or Guyot) and green operations (chasing the upper leaves, pinching, removing stepsons) is shown. The influence of the listed factors on the predisposition of wines to crystalline turbidities is shown.
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