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Vion C, Le Mao I, Yeramian N, Muro M, Bernard M, Da Costa G, Richard T, Marullo P. Targeted 1-H-NMR wine analyses revealed specific metabolomic signatures of yeast populations belonging to the Saccharomyces genus. Food Microbiol 2024; 120:104463. [PMID: 38431337 DOI: 10.1016/j.fm.2024.104463] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Revised: 01/02/2024] [Accepted: 01/03/2024] [Indexed: 03/05/2024]
Abstract
This study aimed to explore the non-volatile metabolomic variability of a large panel of strains (44) belonging to the Saccharomyces cerevisiae and Saccharomyces uvarum species in the context of the wine alcoholic fermentation. For the S. cerevisiae strains flor, fruit and wine strains isolated from different anthropic niches were compared. This phenotypic survey was achieved with a special focus on acidity management by using natural grape juices showing opposite level of acidity. A 1H NMR based metabolomics approach was developed for quantifying fifteen wine metabolites that showed important quantitative variability within the strains. Thanks to the robustness of the assay and the low amount of sample required, this tool is relevant for the analysis of the metabolomic profile of numerous wines. The S. cerevisiae and S. uvarum species displayed significant differences for malic, succinic, and pyruvic acids, as well as for glycerol and 2,3-butanediol production. As expected, S. uvarum showed weaker fermentation fitness but interesting acidifying properties. The three groups of S. cerevisiae strains showed different metabolic profiles mostly related to their production and consumption of organic acids. More specifically, flor yeast consumed more malic acid and produced more acetic acid than the other S. cerevisiae strains which was never reported before. These features might be linked to the ability of flor yeasts to shift their metabolism during wine oxidation.
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Affiliation(s)
- Charlotte Vion
- Biolaffort, Bordeaux, France; UMR 1366 Œnologie, Université de Bordeaux, INRAE, Bordeaux INP, BSA, ISVV, France
| | - Ines Le Mao
- UMR 1366 Œnologie, Université de Bordeaux, INRAE, Bordeaux INP, BSA, ISVV, France
| | - Nadine Yeramian
- Microbiology Division, Department of Biotechnology and Food Science, Faculty of Science-University of Burgos, Spain
| | - Maïtena Muro
- Biolaffort, Bordeaux, France; UMR 1366 Œnologie, Université de Bordeaux, INRAE, Bordeaux INP, BSA, ISVV, France
| | - Margaux Bernard
- Biolaffort, Bordeaux, France; UMR 1366 Œnologie, Université de Bordeaux, INRAE, Bordeaux INP, BSA, ISVV, France
| | - Grégory Da Costa
- UMR 1366 Œnologie, Université de Bordeaux, INRAE, Bordeaux INP, BSA, ISVV, France
| | - Tristan Richard
- UMR 1366 Œnologie, Université de Bordeaux, INRAE, Bordeaux INP, BSA, ISVV, France
| | - Philippe Marullo
- Biolaffort, Bordeaux, France; UMR 1366 Œnologie, Université de Bordeaux, INRAE, Bordeaux INP, BSA, ISVV, France.
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2
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Han J, Jiang J, Zhao X, Zhao X, Kong T, Li P, Gu Q. Comparative analysis of key precursors and metabolites involved in flavor formation of different rapid-fermented Chinese fish sauces based on untargeted metabolomics analysis. Food Chem 2024; 433:136998. [PMID: 37690140 DOI: 10.1016/j.foodchem.2023.136998] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Revised: 06/20/2023] [Accepted: 07/23/2023] [Indexed: 09/12/2023]
Abstract
Our study aimed to characterize the flavor precursors and metabolite profiles during fermentation of three rapid-fermented fish sauces (koji fermentation (YQ), insulation fermentation with koji (BWQ) and insulation fermentation with enzyme (BWE)) by a comparative metabolomics analysis. The total amount of free amino acids and free fatty acids in BWQ and BWE samples was significantly higher than that in YQ sample during fermentation, and C16:0, C22:6, C18:1, C14:1, C18:0 and C20:5 were deemed as key flavor precursors of three fish sauces. We identified 51, 47 and 45 differential metabolites as crucial components in YQ, BWE and BWQ samples. Specific metabolites in three samples were mainly related to amino acid metabolism, especially histidine, cysteine and methionine metabolism. Furthermore, 5 bacteria genera exhibited positive impacts on the generation of various flavor-related metabolites. This study provides a theoretical basis for targeted control of flavor and quality in the production of rapid-fermented fish sauce.
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Affiliation(s)
- Jiarun Han
- Key Laboratory for Food Microbial Technology of Zhejiang Province, College of Food Science and Biotechnology, Zhejiang Gongshang University, Hangzhou, Zhejiang 310018, People's Republic of China.
| | - Jialan Jiang
- Key Laboratory for Food Microbial Technology of Zhejiang Province, College of Food Science and Biotechnology, Zhejiang Gongshang University, Hangzhou, Zhejiang 310018, People's Republic of China
| | - Xin Zhao
- Key Laboratory for Food Microbial Technology of Zhejiang Province, College of Food Science and Biotechnology, Zhejiang Gongshang University, Hangzhou, Zhejiang 310018, People's Republic of China
| | - Xilian Zhao
- Key Laboratory for Food Microbial Technology of Zhejiang Province, College of Food Science and Biotechnology, Zhejiang Gongshang University, Hangzhou, Zhejiang 310018, People's Republic of China
| | - Tao Kong
- Key Laboratory for Food Microbial Technology of Zhejiang Province, College of Food Science and Biotechnology, Zhejiang Gongshang University, Hangzhou, Zhejiang 310018, People's Republic of China
| | - Ping Li
- Key Laboratory for Food Microbial Technology of Zhejiang Province, College of Food Science and Biotechnology, Zhejiang Gongshang University, Hangzhou, Zhejiang 310018, People's Republic of China
| | - Qing Gu
- Key Laboratory for Food Microbial Technology of Zhejiang Province, College of Food Science and Biotechnology, Zhejiang Gongshang University, Hangzhou, Zhejiang 310018, People's Republic of China.
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3
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Schartner M, Beck JM, Laboyrie J, Riquier L, Marchand S, Pouget A. Predicting Bordeaux red wine origins and vintages from raw gas chromatograms. Commun Chem 2023; 6:247. [PMID: 38052884 PMCID: PMC10698164 DOI: 10.1038/s42004-023-01051-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Accepted: 11/02/2023] [Indexed: 12/07/2023] Open
Abstract
Connecting chemical properties to various wine characteristics is of great interest to the science of olfaction as well as the wine industry. We explored whether Bordeaux wine chemical identities and vintages (harvest year) can be inferred from a common and affordable chemical analysis, namely, a combination of gas chromatography (GC) and electron ionization mass spectrometry. Using 12 vintages (within the 1990-2007 range) from 7 estates of the Bordeaux region, we report that, remarkably, nonlinear dimensionality reduction techniques applied to raw gas chromatograms recover the geography of the Bordeaux region. Using machine learning, we found that we can not only recover the estate perfectly from gas chromatograms, but also the vintage with up to 50% accuracy. Interestingly, we observed that the entire chromatogram is informative with respect to geographic location and age, thus suggesting that the chemical identity of a wine is not defined by just a few molecules but is distributed over a large chemical spectrum. This study demonstrates the remarkable potential of GC analysis to explore fundamental questions about the origin and age of wine.
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Affiliation(s)
| | | | - Justine Laboyrie
- Université de Bordeaux, ISVV, INRAE, UMR 1366 OENOLOGIE, 33140, Villenave d'Ornon, France
| | - Laurent Riquier
- Université de Bordeaux, ISVV, INRAE, UMR 1366 OENOLOGIE, 33140, Villenave d'Ornon, France
| | - Stephanie Marchand
- Université de Bordeaux, ISVV, INRAE, UMR 1366 OENOLOGIE, 33140, Villenave d'Ornon, France.
| | - Alexandre Pouget
- Département des neurosciences fondamentales, Université de Genève, Genève, Suisse.
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4
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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: 0] [Impact Index Per Article: 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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5
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Ghini V, Meoni G, Vignoli A, Di Cesare F, Tenori L, Turano P, Luchinat C. Fingerprinting and profiling in metabolomics of biosamples. PROGRESS IN NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY 2023; 138-139:105-135. [PMID: 38065666 DOI: 10.1016/j.pnmrs.2023.10.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Revised: 10/13/2023] [Accepted: 10/15/2023] [Indexed: 12/18/2023]
Abstract
This review focuses on metabolomics from an NMR point of view. It attempts to cover the broad scope of metabolomics and describes the NMR experiments that are most suitable for each sample type. It is addressed not only to NMR specialists, but to all researchers who wish to approach metabolomics with a clear idea of what they wish to achieve but not necessarily with a deep knowledge of NMR. For this reason, some technical parts may seem a bit naïve to the experts. The review starts by describing standard metabolomics procedures, which imply the use of a dedicated 600 MHz instrument and of four properly standardized 1D experiments. Standardization is a must if one wants to directly compare NMR results obtained in different labs. A brief mention is also made of standardized pre-analytical procedures, which are even more essential. Attention is paid to the distinction between fingerprinting and profiling, and the advantages and disadvantages of fingerprinting are clarified. This aspect is often not fully appreciated. Then profiling, and the associated problems of signal assignment and quantitation, are discussed. We also describe less conventional approaches, such as the use of different magnetic fields, the use of signal enhancement techniques to increase sensitivity, and the potential of field-shuttling NMR. A few examples of biomedical applications are also given, again with the focus on NMR techniques that are most suitable to achieve each particular goal, including a description of the most common heteronuclear experiments. Finally, the growing applications of metabolomics to foodstuffs are described.
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Affiliation(s)
- Veronica Ghini
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy; Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy
| | - Gaia Meoni
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy; Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy
| | - Alessia Vignoli
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy; Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy
| | - Francesca Di Cesare
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy; Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy
| | - Leonardo Tenori
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy; Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy; Consorzio Interuniversitario Risonanze Magnetiche Metallo Proteine (CIRMMP), Sesto Fiorentino, Italy
| | - Paola Turano
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy; Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy; Consorzio Interuniversitario Risonanze Magnetiche Metallo Proteine (CIRMMP), Sesto Fiorentino, Italy.
| | - Claudio Luchinat
- Consorzio Interuniversitario Risonanze Magnetiche Metallo Proteine (CIRMMP), Sesto Fiorentino, Italy; Giotto Biotech S.r.l., Sesto Fiorentino, Italy.
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6
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Denchai S, Sasomsin S, Prakitchaiwattana C, Phuenpong T, Homyog K, Mekboonsonglarp W, Settachaimongkon S. Influence of Different Types, Utilization Times, and Volumes of Aging Barrels on the Metabolite Profile of Red Wine Revealed by 1H-NMR Metabolomics Approach. Molecules 2023; 28:6716. [PMID: 37764490 PMCID: PMC10534683 DOI: 10.3390/molecules28186716] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Revised: 09/13/2023] [Accepted: 09/18/2023] [Indexed: 09/29/2023] Open
Abstract
It is well recognized that the aging process is a critical step in winemaking because it induces substantial chemical changes linked to the organoleptic properties and stability of the finished wines. Therefore, this study aimed to investigate the influence of different types, utilization times, and volumes of aging barrels on the metabolite profile of red wines, produced from Thai-grown Shiraz grapes, using a non-targeted proton nuclear magnetic resonance (1H-NMR) metabolomics approach. As a result, 37 non-volatile polar metabolites including alcohols, amino acids, organic acids, carbohydrates and low-molecular-weight phenolics were identified. Chemometric analysis allowed the discrimination of wine metabolite profiles associated with different types of aging containers (oak barrels vs. stainless-steel tanks), as well as the utilization times (2, 6 and >10 years old) and volumes (225, 500 and 2000 L) of the wooden barrels employed. Significant variations in the concentration of formate, fumarate, pyruvate, succinate, citrate, gallate, acetate, tyrosine, phenylalanine, histidine, γ-aminobutyrate, methionine and choline were statistically suggested as indicators accountable for the discrimination of samples aged under different conditions. These feature biomarkers could be applied to manipulate the use of aging containers to achieve the desired wine maturation profiles.
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Affiliation(s)
- Suwanan Denchai
- Program in Biotechnology, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand;
- Department of Food Technology, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand
| | - Suppached Sasomsin
- Innovation & Winemaking Division, Siam Winery Company Limited, Samut Sakhon 74000, Thailand;
| | | | - Thanitaporn Phuenpong
- Department of Food Technology, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand
| | - Kunaporn Homyog
- Center of Veterinary Diagnosis, Faculty of Veterinary Science, Mahidol University, Nakhon Pathom 73170, Thailand
| | - Wanwimon Mekboonsonglarp
- Scientific and Technological Research Equipment Center (STREC), Chulalongkorn University, Bangkok 10330, Thailand
| | - Sarn Settachaimongkon
- Department of Food Technology, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand
- Emerging Processes for Food Functionality Design Research Unit, Chulalongkorn University, Bangkok 10330, Thailand
- Omics Sciences and Bioinformatics Center, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand
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7
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Kharbach M, Alaoui Mansouri M, Taabouz M, Yu H. Current Application of Advancing Spectroscopy Techniques in Food Analysis: Data Handling with Chemometric Approaches. Foods 2023; 12:2753. [PMID: 37509845 PMCID: PMC10379817 DOI: 10.3390/foods12142753] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Revised: 06/30/2023] [Accepted: 07/18/2023] [Indexed: 07/30/2023] Open
Abstract
In today's era of increased food consumption, consumers have become more demanding in terms of safety and the quality of products they consume. As a result, food authorities are closely monitoring the food industry to ensure that products meet the required standards of quality. The analysis of food properties encompasses various aspects, including chemical and physical descriptions, sensory assessments, authenticity, traceability, processing, crop production, storage conditions, and microbial and contaminant levels. Traditionally, the analysis of food properties has relied on conventional analytical techniques. However, these methods often involve destructive processes, which are laborious, time-consuming, expensive, and environmentally harmful. In contrast, advanced spectroscopic techniques offer a promising alternative. Spectroscopic methods such as hyperspectral and multispectral imaging, NMR, Raman, IR, UV, visible, fluorescence, and X-ray-based methods provide rapid, non-destructive, cost-effective, and environmentally friendly means of food analysis. Nevertheless, interpreting spectroscopy data, whether in the form of signals (fingerprints) or images, can be complex without the assistance of statistical and innovative chemometric approaches. These approaches involve various steps such as pre-processing, exploratory analysis, variable selection, regression, classification, and data integration. They are essential for extracting relevant information and effectively handling the complexity of spectroscopic data. This review aims to address, discuss, and examine recent studies on advanced spectroscopic techniques and chemometric tools in the context of food product applications and analysis trends. Furthermore, it focuses on the practical aspects of spectral data handling, model construction, data interpretation, and the general utilization of statistical and chemometric methods for both qualitative and quantitative analysis. By exploring the advancements in spectroscopic techniques and their integration with chemometric tools, this review provides valuable insights into the potential applications and future directions of these analytical approaches in the food industry. It emphasizes the importance of efficient data handling, model development, and practical implementation of statistical and chemometric methods in the field of food analysis.
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Affiliation(s)
- Mourad Kharbach
- Department of Food and Nutrition, University of Helsinki, 00014 Helsinki, Finland
- Department of Computer Sciences, University of Helsinki, 00560 Helsinki, Finland
| | - Mohammed Alaoui Mansouri
- Nano and Molecular Systems Research Unit, University of Oulu, 90014 Oulu, Finland
- Research Unit of Mathematical Sciences, University of Oulu, 90014 Oulu, Finland
| | - Mohammed Taabouz
- Biopharmaceutical and Toxicological Analysis Research Team, Laboratory of Pharmacology and Toxicology, Faculty of Medicine and Pharmacy, University Mohammed V in Rabat, Rabat BP 6203, Morocco
| | - Huiwen Yu
- Shenzhen Hospital, Southern Medical University, Shenzhen 518005, China
- Chemometrics group, Faculty of Science, University of Copenhagen, Rolighedsvej 26, 1958 Frederiksberg, Denmark
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8
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Zhang S, Fang K, Ding Z, Wu J, Lin J, Xu D, Zhong J, Xia F, Feng J, Shen G. Untargeted Metabolomics Analysis Revealed the Difference of Component and Geographical Indication Markers of Panax notoginseng in Different Production Areas. Foods 2023; 12:2377. [PMID: 37372587 DOI: 10.3390/foods12122377] [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: 04/26/2023] [Revised: 05/31/2023] [Accepted: 06/13/2023] [Indexed: 06/29/2023] Open
Abstract
Panax notoginseng (P. notoginseng) has excellent medicinal and food dual-use characteristics. However, P. notoginseng with a unique origin label has become the target of fraud because of people confusing or hiding its origin. In this study, an untargeted nuclear magnetic resonance (NMR)-based metabolomics approach was used to discriminate the geographical origins of P. notoginseng from four major producing areas in China. Fifty-two components, including various saccharides, amino acids, saponins, organic acids, and alcohols, were identified and quantified through the NMR spectrum, and the area-specific geographical identification components were further screened. P. notoginseng from Yunnan had strong hypoglycemic and cardiovascular protective effects due to its high acetic acid, dopamine, and serine content, while P. notoginseng from Sichuan was more beneficial for diseases of the nervous system because of its high content of fumarate. P. notoginseng from Guizhou and Tibet had high contents of malic acid, notoginsenoside R1, and amino acids. Our results can help to distinguish the geographical origin of P. notoginseng and are readily available for nutritional recommendations in human consumption.
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Affiliation(s)
- Shijia Zhang
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361005, China
| | - Kexin Fang
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361005, China
| | - Zenan Ding
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361005, China
| | - Jinxia Wu
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361005, China
| | - Jianzhong Lin
- Technology Center of Xiamen Customs, Xiamen 361012, China
| | - Dunming Xu
- Technology Center of Xiamen Customs, Xiamen 361012, China
| | - Jinshui Zhong
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361005, China
| | - Feng Xia
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361005, China
| | - Jianghua Feng
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361005, China
| | - Guiping Shen
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361005, China
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9
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Bambina P, Spinella A, Lo Papa G, Chillura Martino DF, Lo Meo P, Corona O, Cinquanta L, Conte P. 1H NMR-Based Metabolomics to Assess the Impact of Soil Type on the Chemical Composition of Nero d'Avola Red Wines. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2023; 71:5823-5835. [PMID: 36940311 DOI: 10.1021/acs.jafc.2c08654] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
In this study, the soil effect on the micro-component composition of Nero d'Avola wines obtained from different locations was investigated through 1H NMR-based metabolomics. Two different approaches were applied: the targeted (TA) and the non-targeted one (NTA). The former differentiated the wines by profiling (i.e., by identifying and quantifying) a number of different metabolites. The latter provided wine fingerprinting by processing the entire spectra with multivariate statistical analysis. NTA also allowed investigation of the hydrogen bond network inside wines via the analysis of 1H NMR chemical shift dispersions. Results showed that the differences among wines were due not only to the concentrations of various analytes but also to the characteristics of the H-bond network where different solutes were involved. The H-bond network affects both gustatory and olfactory perceptions by modulating the way how solutes interact with the human sensorial receptors. Moreover, the aforementioned H-bond network is also related to the soil properties from which the grapes were taken. Therefore, the present study can be considered a good attempt to investigate terroir, i.e., the relationship between wine quality and soil characteristics.
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Affiliation(s)
- Paola Bambina
- Department of Agricultural, Food and Forestry Sciences, University of Palermo, V.le delle Scienze 13, 90128 Palermo, Italy
| | - Alberto Spinella
- Advanced Technologies Network Center (ATeN Center), University of Palermo, via F. Marini 14, 90128 Palermo, Italy
| | - Giuseppe Lo Papa
- Department of Agricultural, Food and Forestry Sciences, University of Palermo, V.le delle Scienze 13, 90128 Palermo, Italy
| | - Delia Francesca Chillura Martino
- Department of Biological, Chemical and Pharmaceutical Sciences and Technologies, University of Palermo, V.le delle Scienze 16, 90128 Palermo, Italy
| | - Paolo Lo Meo
- Department of Biological, Chemical and Pharmaceutical Sciences and Technologies, University of Palermo, V.le delle Scienze 16, 90128 Palermo, Italy
| | - Onofrio Corona
- Department of Agricultural, Food and Forestry Sciences, University of Palermo, V.le delle Scienze 13, 90128 Palermo, Italy
| | - Luciano Cinquanta
- Department of Agricultural, Food and Forestry Sciences, University of Palermo, V.le delle Scienze 13, 90128 Palermo, Italy
| | - Pellegrino Conte
- Department of Agricultural, Food and Forestry Sciences, University of Palermo, V.le delle Scienze 13, 90128 Palermo, Italy
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10
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Pirnau A, Feher I, Sârbu C, Hategan AR, Guyon F, Magdas DA. Application of fuzzy algorithms in conjunction with 1 H-NMR spectroscopy to differentiate alcoholic beverages. JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE 2023; 103:1727-1735. [PMID: 36541578 DOI: 10.1002/jsfa.12402] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Revised: 09/29/2022] [Accepted: 12/21/2022] [Indexed: 06/17/2023]
Abstract
BACKGROUND Recent statistics from the European Commission indicate that wine is one of the commodities most commonly subject to food fraud. In this context, the development of reliable classification models to differentiate alcoholic beverages requires, besides sensitive analytical tools, the use of the most suitable data-processing methods like those based on advanced statistical tools or artificial intelligence. RESULTS The present study aims to establish a new, innovative approach for the differentiation of alcoholic beverages (wines and fruit distillates), which is able to increase the discrimination rate of the models that have been developed. A data dimensionality reduction step was applied to proton nuclear magnetic resonance (1 H-NMR) profiles. This stage consisted of the application of fuzzy principal component analysis (FPCA) prior to the development of classification models through discriminant analysis. The enhancement of the model's classification potential by the application of FPCA in comparison with principal component analysis (PCA) was discussed. CONCLUSION The association of 1 H-NMR spectroscopy and an appropriate statistical approach provided a very effective tool for the differentiation of alcoholic beverages. To develop reliable metabolomic approaches for the differentiation of wines and fruit distillates, 1 H-NMR spectroscopic data were exploited in conjunction with fuzzy algorithms to reduce data dimensionality. The study proved the greater efficiency of using FPCA scores in comparison with those obtained through the widely applied PCA. The proposed approach enabled wines to be distinguished perfectly according to their geographical origins, cultivar, and vintage, and this could be used for wine classification. Moreover, 100% correctly classified samples were also achieved for the botanical and geographical differentiation of fruit distillates. © 2022 Society of Chemical Industry.
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Affiliation(s)
- Adrian Pirnau
- National Institute for Research and Development of Isotopic and Molecular Technologies, Cluj-Napoca, Romania
| | - Ioana Feher
- National Institute for Research and Development of Isotopic and Molecular Technologies, Cluj-Napoca, Romania
| | - Costel Sârbu
- Faculty of Chemistry and Chemical Engineering, Babeş-Bolyai University, Cluj-Napoca, Romania
| | - Ariana Raluca Hategan
- National Institute for Research and Development of Isotopic and Molecular Technologies, Cluj-Napoca, Romania
| | | | - Dana Alina Magdas
- National Institute for Research and Development of Isotopic and Molecular Technologies, Cluj-Napoca, Romania
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11
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Wang Z, Chen X, Liu Q, Zhang L, Liu S, Su Y, Ren Y, Yuan C. Untargeted metabolomics analysis based on LC-IM-QTOF-MS for discriminating geographical origin and vintage of Chinese red wine. Food Res Int 2023; 165:112547. [PMID: 36869536 DOI: 10.1016/j.foodres.2023.112547] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Revised: 01/24/2023] [Accepted: 01/29/2023] [Indexed: 02/05/2023]
Abstract
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.
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Affiliation(s)
- Zhaoxiang Wang
- College of Enology, Northwest A&F University, Yangling 712100, China
| | - Xiaoyi Chen
- College of Enology, Northwest A&F University, Yangling 712100, China
| | - Qianqian Liu
- College of Enology, Northwest A&F University, Yangling 712100, China
| | - Lin Zhang
- College of Enology, Northwest A&F University, Yangling 712100, China
| | - Shuai Liu
- College of Enology, Northwest A&F University, Yangling 712100, China
| | - Yingyue Su
- College of Enology, Northwest A&F University, Yangling 712100, China
| | - Yamei Ren
- College of Food Science and Engineering, 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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12
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Sobolev AP, Ingallina C, Spano M, Di Matteo G, Mannina L. NMR-Based Approaches in the Study of Foods. Molecules 2022; 27:7906. [PMID: 36432006 PMCID: PMC9697393 DOI: 10.3390/molecules27227906] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Revised: 11/07/2022] [Accepted: 11/14/2022] [Indexed: 11/17/2022] Open
Abstract
In this review, the three different NMR-based approaches usually used to study foodstuffs are described, reporting specific examples. The first approach starts with the food of interest that can be investigated using different complementary NMR methodologies to obtain a comprehensive picture of food composition and structure; another approach starts with the specific problem related to a given food (frauds, safety, traceability, geographical and botanical origin, farming methods, food processing, maturation and ageing, etc.) that can be addressed by choosing the most suitable NMR methodology; finally, it is possible to start from a single NMR methodology, developing a broad range of applications to tackle common food-related challenges and different aspects related to foods.
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Affiliation(s)
- Anatoly P. Sobolev
- Magnetic Resonance Laboratory “Segre-Capitani”, Institute for Biological Systems, CNR, Via Salaria, Km 29.300, 00015 Monterotondo, Italy
| | - Cinzia Ingallina
- Laboratory of Food Chemistry, Department of Chemistry and Technology of Drugs, Sapienza University of Rome, P.le Aldo Moro 5, 00185 Rome, Italy
| | - Mattia Spano
- Laboratory of Food Chemistry, Department of Chemistry and Technology of Drugs, Sapienza University of Rome, P.le Aldo Moro 5, 00185 Rome, Italy
| | - Giacomo Di Matteo
- Laboratory of Food Chemistry, Department of Chemistry and Technology of Drugs, Sapienza University of Rome, P.le Aldo Moro 5, 00185 Rome, Italy
| | - Luisa Mannina
- Laboratory of Food Chemistry, Department of Chemistry and Technology of Drugs, Sapienza University of Rome, P.le Aldo Moro 5, 00185 Rome, Italy
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13
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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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14
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Le Mao I, Da Costa G, Bautista C, De Revel G, Richard T. Application of 1H NMR metabolomics to French sparkling wines. Food Control 2022. [DOI: 10.1016/j.foodcont.2022.109423] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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15
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van Mever M, Fabjanowicz M, Mamani‐Huanca M, López‐Gonzálvez Á, Płotka‐Wasylka J, Ramautar R. Profiling of polar ionogenic metabolites in Polish wines by capillary electrophoresis-mass spectrometry. Electrophoresis 2022; 43:1814-1821. [PMID: 35560354 PMCID: PMC9790660 DOI: 10.1002/elps.202200066] [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: 03/16/2022] [Revised: 05/05/2022] [Accepted: 05/06/2022] [Indexed: 12/30/2022]
Abstract
The composition of wine is determined by a complex interaction between environmental factors, genetic factors (i.e., grape varieties), and winemaking practices (including technology and storage). Metabolomics using NMR spectroscopy, GC-MS, and/or LC-MS has shown to be a useful approach for assessing the origin, authenticity, and quality of various wines. Nonetheless, the use of additional analytical techniques with complementary separation mechanisms may aid in the deeper understanding of wine's metabolic processes. In this study, we demonstrate that CE-MS is a very suitable approach for the efficient profiling of polar ionogenic metabolites in wines. Without using any sample preparation or derivatization, wine was analyzed using a 10-min CE-MS workflow with interday RSD values for 31 polar and charged metabolites below 3.8% and 23% for migration times and peak areas, respectively. The utility of this workflow for the global profiling of polar ionogenic metabolites in wine was evaluated by analyzing different cool-climate Polish wine samples.
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Affiliation(s)
- Marlien van Mever
- Leiden Academic Centre for Drug ResearchLeiden UniversityLeidenThe Netherlands
| | - Magdalena Fabjanowicz
- Department of Analytical ChemistryFaculty of ChemistryGdańsk University of TechnologyGdańskPoland
| | - Maricruz Mamani‐Huanca
- Centro de Metabolómica y Bioanálisis (CEMBIO)Facultad de FarmaciaUniversidad San Pablo‐CEUCEU UniversitiesBoadilla del MonteSpain
| | - Ángeles López‐Gonzálvez
- Centro de Metabolómica y Bioanálisis (CEMBIO)Facultad de FarmaciaUniversidad San Pablo‐CEUCEU UniversitiesBoadilla del MonteSpain
| | - Justyna Płotka‐Wasylka
- Department of Analytical ChemistryChemical Faculty and BioTechMed CenterGdańsk University of TechnologyGdańskPoland
| | - Rawi Ramautar
- Leiden Academic Centre for Drug ResearchLeiden UniversityLeidenThe Netherlands
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16
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Li W, Zhao F, Xie X, Yang J, Pan J, Qu H. Quantitative profiling of comprehensive composition in compound herbal injections: An NMR approach applied on Shenmai injection. PHYTOCHEMICAL ANALYSIS : PCA 2022; 33:1045-1057. [PMID: 35750658 DOI: 10.1002/pca.3158] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Revised: 05/24/2022] [Accepted: 06/12/2022] [Indexed: 06/15/2023]
Abstract
INTRODUCTION Compound herbal injections (CHIs) can be regarded as a significant innovation in the modernisation of herbal medicine. Therefore, improving the quality control level of CHIs has always been an active research topic in traditional herbal medicine. OBJECTIVES In this study, Shenmai injection was used as a representative sample for investigating the ability of proton nuclear magnetic resonance (1 H NMR) in the quality evaluation of CHIs. METHODS A quantitative 1 H NMR method was developed to simultaneously determine the contents of total ginsenosides, polysorbate 80, and 20 primary metabolites in Shenmai injection. Multivariate statistical analysis was combined to compare differences between samples from different manufacturers. RESULTS It was found that the combined measurement uncertainty of each component is less than 1.61%, which demonstrates the reliability of the method. Furthermore, the components determined by this method account for up to 92.64% of the total solids, which is an unprecedented success in the analysis of Shenmai injection. In the end, the method was applied to the quality comparison of Shenmai injection from six manufacturers. The results showed that the differences among the samples from the six manufacturers were reflected in multiple types of components. CONCLUSION This study fully demonstrates the superiority of the quantitative 1 H NMR method in comprehensive composition profiling of CHIs, which is conducive to improving the quality control level of Shenmai injection. Further, the present study can be used as a reference study for the research on the quality and safety of CHIs.
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Affiliation(s)
- Wenzhu Li
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China
- State Key Laboratory of Component-Based Chinese Medicine, Innovation Center in Zhejiang University, Hangzhou, China
| | - Fang Zhao
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China
- State Key Laboratory of Component-Based Chinese Medicine, Innovation Center in Zhejiang University, Hangzhou, China
| | - Xinyuan Xie
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China
- State Key Laboratory of Component-Based Chinese Medicine, Innovation Center in Zhejiang University, Hangzhou, China
| | - Jiayu Yang
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China
- State Key Laboratory of Component-Based Chinese Medicine, Innovation Center in Zhejiang University, Hangzhou, China
| | - Jianyang Pan
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China
- State Key Laboratory of Component-Based Chinese Medicine, Innovation Center in Zhejiang University, Hangzhou, China
| | - Haibin Qu
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China
- State Key Laboratory of Component-Based Chinese Medicine, Innovation Center in Zhejiang University, Hangzhou, China
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17
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López-Rituerto E, Sørensen KM, Savorani F, Engelsen SB, Avenoza A, Peregrina JM, Busto JH. Monitoring of the Rioja red wine production process by 1 H-NMR spectroscopy. JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE 2022; 102:3808-3816. [PMID: 34921687 DOI: 10.1002/jsfa.11729] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/10/2021] [Revised: 12/14/2021] [Accepted: 12/18/2021] [Indexed: 06/14/2023]
Abstract
BACKGROUND As an inherently quantitative and unbiased analytical technique, proton nuclear magnetic resonance (1 H-NMR) provides an excellent method to monitor the quality of food and beverages, and a sensitive and informative tool to study the winemaking process. RESULTS By using NMR, it is possible to monitor quantitative changes in wine metabolites (amino acids, organic acids and some phenolic compounds) during the winemaking process, including wine ageing. This study shows an increase in the concentration of the phenols at the beginning of alcoholic fermentation, as well as a stabilization and slight increase in gallic acid and a slight decrease in resveratrol during the oak barrel ageing step. CONCLUSION This study demonstrates the potential of NMR as a process analytical technology (PAT) tool in the wine industry, by monitoring amino acids, organic acids and three polyphenols - gallic acid, catechin and resveratrol - during the winemaking process. This study of the time course evolution of wine has been conducted in a commercial winery rather than an experimental laboratory, demonstrating the capacity of this technique in commercial winemaking production. © 2021 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.
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Affiliation(s)
- Eva López-Rituerto
- Consejería de Agricultura, Ganadería, Mundo Rural, Territorio y Población de La Rioja, Dirección General de Agricultura y Ganadería, Servicio de Investigación Agraria y Sanidad Vegetal, Estación Enológica de Haro, Haro, Spain
| | - Klavs M Sørensen
- Chemometrics and Analytical Technology, Department of Food Science, University of Copenhagen, Frederiksberg C, Denmark
| | - Francesco Savorani
- Department of Applied Science and Technology (DISAT), Polytechnic University of Turin, Turin (TO), Italy
| | - Søren B Engelsen
- Chemometrics and Analytical Technology, Department of Food Science, University of Copenhagen, Frederiksberg C, Denmark
| | - Alberto Avenoza
- Departamento de Química, Centro de Investigación en Síntesis Química (CISQ), Universidad de La Rioja, Logroño, Spain
| | - Jesús M Peregrina
- Departamento de Química, Centro de Investigación en Síntesis Química (CISQ), Universidad de La Rioja, Logroño, Spain
| | - Jesús H Busto
- Departamento de Química, Centro de Investigación en Síntesis Química (CISQ), Universidad de La Rioja, Logroño, Spain
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18
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Application of Chitosan-Lignosulfonate Composite Coating Film in Grape Preservation and Study on the Difference in Metabolites in Fruit Wine. COATINGS 2022. [DOI: 10.3390/coatings12040494] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
In order to solve the global problem of fruit rotting due to microbial infection and water loss after harvest, which leads to a large amount of food waste, this experiment uses degradable biological composite coating to prolong the preservation period of grapes. Chitosan (CH) and Lignosulfonate (LS) were used as Bio-based film materials, CH films, 1% CH/LS films and 2% CH/LS biomass composite films were synthesized by the classical casting method and applied to grape preservation packaging. Its preservation effect was tested by grape spoilage rate, water loss rate, hardness, soluble solids, titratable acid, and compared with plastic packaging material PE film. At the same time, 1H NMR technology combined with pattern recognition analysis (PCA) and partial least squares discriminant analysis (PLS-DA) was used to determine the nuclear magnetic resonance (NMR) of Cabernet Sauvignon, Chardonnay and Italian Riesling wines from the eastern foothills of Helan Mountain to explore the differences in metabolites of wine. The results of preservation showed that the grapes quality of CH films and 2% CH/LS coating package is better than the control group, the decay rates decreased from 37.71% to 21.63% and 18.36%, respectively, the hardness increased from 6.83 to 10.4 and 12.78 and the soluble solids increased from 2.1 in the control group to 3.0 and 3.2. In terms of wine metabolites, there are similar types of metabolites between cabernet Sauvignon dry red wine and Chardonnay and Italian Riesling dry white wine, but there are significant differences in content. The study found that 2% CH/LS coating package could not only reduce the spoilage rate of grapes, inhibit the consumption of soluble solids and titratable acids, but also effectively extend the shelf life of grapes by 6 days.
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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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20
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QU Q, JIN L. Application of nuclear magnetic resonance in food analysis. FOOD SCIENCE AND TECHNOLOGY 2022. [DOI: 10.1590/fst.43622] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
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21
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NMR Tracing of Food Geographical Origin: The Impact of Seasonality, Cultivar and Production Year on Data Analysis. SEPARATIONS 2021. [DOI: 10.3390/separations8120230] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
The traceability of typical foodstuffs is necessary to protect high quality of traditional products. It is well-known that several factors could influence metabolites content in certified foods, but soil composition, altitude, latitude and coded production protocols constitute the territorial conditions responsible for the peculiar organoleptic and nutritional properties of labelled foods. Instead, regardless of origin, seasonality, cultivar, collection year can affect all agricultural products, so it is appropriate to include them in data analysis in order to obtain a correct interpretation of the differences linked to growing areas alone. Therefore, it is useful to use a flexible all-round technique, and NMR spectroscopy coupled with multivariate statistical analysis is considered a powerful means of assessing food authenticity. The purpose of this review is to investigate the relevance of year, cultivar, and seasonal period in the determination of food geographical origin using NMR spectroscopy. The strategy for testing these three factors may differ from author to author, but a preliminary study of cultivar or collection year effects on NMR spectra is the most popular method before starting the geographical characterization of samples. In summary, based on the available literature, the most significant influence is due to cultivar, followed by harvesting year, however seasonality is not considered a source of variability in data analysis.
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Le Mao I, Martin-Pernier J, Bautista C, Lacampagne S, Richard T, Da Costa G. 1H-NMR Metabolomics as a Tool for Winemaking Monitoring. Molecules 2021; 26:6771. [PMID: 34833863 PMCID: PMC8621607 DOI: 10.3390/molecules26226771] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Revised: 11/02/2021] [Accepted: 11/05/2021] [Indexed: 11/16/2022] Open
Abstract
The chemical composition of wine is known to be influenced by multiple factors including some viticulture practices and winemaking processes. 1H-NMR metabolomics has been successfully applied to the study of wine authenticity. In the present study, 1H-NMR metabolomics in combination with multivariate analysis was applied to investigate the effects of grape maturity and enzyme and fining treatments on Cabernet Sauvignon wines. A total of forty wine metabolites were quantified. Three different stages of maturity were studied (under-maturity, maturity and over-maturity). Enzyme treatments were carried out using two pectolytic enzymes (E1 and E2). Finally, two proteinaceous fining treatments were compared (vegetable protein, fining F1; pea protein and PVPP, fining F2). The results show a clear difference between the three stages of maturity, with an impact on different classes of metabolites including amino acids, organic acids, sugars, phenolic compounds, alcohols and esters. A clear separation between enzymes E1 and E2 was observed. Both fining agents had a significant effect on metabolite concentrations. The results demonstrate that 1H-NMR metabolomics provides a fast and robust approach to study the effect of winemaking processes on wine metabolites. These results support the interest to pursue the development of 1H-NMR metabolomics to investigate the effects of winemaking on wine quality.
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Affiliation(s)
| | | | | | | | - Tristan Richard
- University of Bordeaux, INRAE, Bordeaux INP, UR OENO, EA 4577, USC 1366, F-33140 Villenave d’Ornon, France; (I.L.M.); (J.M.-P.); (C.B.); (S.L.); (G.D.C.)
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Grapevine and Wine Metabolomics-Based Guidelines for FAIR Data and Metadata Management. Metabolites 2021; 11:metabo11110757. [PMID: 34822415 PMCID: PMC8618349 DOI: 10.3390/metabo11110757] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Revised: 10/29/2021] [Accepted: 10/30/2021] [Indexed: 01/12/2023] Open
Abstract
In the era of big and omics data, good organization, management, and description of experimental data are crucial for achieving high-quality datasets. This, in turn, is essential for the export of robust results, to publish reliable papers, make data more easily available, and unlock the huge potential of data reuse. Lately, more and more journals now require authors to share data and metadata according to the FAIR (Findable, Accessible, Interoperable, Reusable) principles. This work aims to provide a step-by-step guideline for the FAIR data and metadata management specific to grapevine and wine science. In detail, the guidelines include recommendations for the organization of data and metadata regarding (i) meaningful information on experimental design and phenotyping, (ii) sample collection, (iii) sample preparation, (iv) chemotype analysis, (v) data analysis (vi) metabolite annotation, and (vii) basic ontologies. We hope that these guidelines will be helpful for the grapevine and wine metabolomics community and that it will benefit from the true potential of data usage in creating new knowledge being revealed.
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Zamora Obando HR, Duarte GHB, Simionato AVC. Metabolomics Data Treatment: Basic Directions of the Full Process. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2021; 1336:243-264. [PMID: 34628635 DOI: 10.1007/978-3-030-77252-9_12] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/10/2023]
Abstract
The present chapter describes basic aspects of the main steps for data processing on mass spectrometry-based metabolomics platforms, focusing on the main objectives and important considerations of each step. Initially, an overview of metabolomics and the pivotal techniques applied in the field are presented. Important features of data acquisition and preprocessing such as data compression, noise filtering, and baseline correction are revised focusing on practical aspects. Peak detection, deconvolution, and alignment as well as missing values are also discussed. Special attention is given to chemical and mathematical normalization approaches and the role of the quality control (QC) samples. Methods for uni- and multivariate statistical analysis and data pretreatment that could impact them are reviewed, emphasizing the most widely used multivariate methods, i.e., principal components analysis (PCA), partial least squares-discriminant analysis (PLS-DA), orthogonal partial least square-discriminant analysis (OPLS-DA), and hierarchical cluster analysis (HCA). Criteria for model validation and softwares used in data processing were also approached. The chapter ends with some concerns about the minimal requirements to report metadata in metabolomics.
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Affiliation(s)
- Hans Rolando Zamora Obando
- Department of Analytical Chemistry, Institute of Chemistry, University of Campinas, Campinas, SP, Brazil
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26
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Tabago MKAG, Calingacion MN, Garcia J. Recent advances in NMR-based metabolomics of alcoholic beverages. FOOD CHEMISTRY: MOLECULAR SCIENCES 2021; 2:100009. [PMID: 35415632 PMCID: PMC8991939 DOI: 10.1016/j.fochms.2020.100009] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/09/2020] [Revised: 11/30/2020] [Accepted: 12/27/2020] [Indexed: 01/14/2023]
Abstract
NMR-based techniques can be used for establishing metabolic “fingerprint” . Biomarkers for discrimination of wine varietals were identified. COSY and DOSY techniques may aid in assigning phenolic compounds and disaccharides. NMR-based metabolomic studies of alcoholic beverages remain limited in Asia.
Alcoholic beverages have a complex chemistry that can be influenced by their alcoholic content, origin, fermentation process, additives, and contaminants. The complex composition of these beverages leave them susceptible to fraud, potentially compromising their authenticity, quality, and market value, thus increasing risks to consumers’ health. In recent years, intensive studies have been carried out on alcoholic beverages using different analytical techniques to evaluate the authenticity, variety, age, and fermentation processes that were used. Among these techniques, NMR-based metabolomics holds promise in profiling the chemistry of alcoholic beverages, especially in Asia where metabolomics studies on alcoholic beverages remain limited.
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Development of a Wine Metabolomics Approach for the Authenticity Assessment of Selected Greek Red Wines. Molecules 2021; 26:molecules26102837. [PMID: 34064666 PMCID: PMC8150368 DOI: 10.3390/molecules26102837] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Revised: 05/06/2021] [Accepted: 05/08/2021] [Indexed: 12/27/2022] Open
Abstract
Wine metabolomics constitutes a powerful discipline towards wine authenticity assessment through the simultaneous exploration of multiple classes of compounds in the wine matrix. Over the last decades, wines from autochthonous Greek grape varieties have become increasingly popular among wine connoisseurs, attracting great interest for their authentication and chemical characterization. In this work, 46 red wine samples from Agiorgitiko and Xinomavro grape varieties were collected from wineries in two important winemaking regions of Greece during two consecutive vintages and analyzed using ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-QToF-MS). A targeted metabolomics methodology was developed, including the determination and quantification of 28 phenolic compounds from different classes (hydroxycinnamic acids, hydroxybenzoic acids, stilbenes and flavonoids). Moreover, 86 compounds were detected and tentatively identified via a robust suspect screening workflow using an in-house database of 420 wine related compounds. Supervised chemometric techniques were employed to build an accurate and robust model to discriminate between two varieties.
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Crook AA, Zamora-Olivares D, Bhinderwala F, Woods J, Winkler M, Rivera S, Shannon CE, Wagner HR, Zhuang DL, Lynch JE, Berryhill NR, Runnebaum RC, Anslyn EV, Powers R. Combination of two analytical techniques improves wine classification by Vineyard, Region, and vintage. Food Chem 2021; 354:129531. [PMID: 33756314 DOI: 10.1016/j.foodchem.2021.129531] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2020] [Revised: 01/29/2021] [Accepted: 03/02/2021] [Indexed: 12/13/2022]
Abstract
Three important wine parameters: vineyard, region, and vintage year, were evaluated using fifteen Vitis vinifera L. 'Pinot noir' wines derived from the same scion clone (Pinot noir 667). These wines were produced from two vintage years (2015 and 2016) and eight different regions along the Pacific Coast of the United States. We successfully improved the classification of the selected Pinot noir wines by combining an untargeted 1D 1H NMR analysis with a targeted peptide based differential sensing array. NMR spectroscopy was used to evaluate the chemical fingerprint of the wines, whereas the peptide-based sensing array is known to mimic the senses of taste, smell, and palate texture by characterizing the phenolic profile. Multivariate and univariate statistical analyses of the combined NMR and differential sensing array dataset classified the genetically identical Pinot noir wines on the basis of distinctive metabolic signatures associated with the region of growth, vineyard, and vintage year.
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Affiliation(s)
- Alexandra A Crook
- Department of Chemistry, University of Nebraska-Lincoln, Lincoln NE 65888, United States
| | - Diana Zamora-Olivares
- Department of Chemistry, The University of Texas at Austin, Austin, TX 78712, United States; Texas Institute for Discovery Education in Science and Freshman Research Initiative, The University of Texas at Austin, Austin, TX 78712, United States
| | - Fatema Bhinderwala
- Department of Chemistry, University of Nebraska-Lincoln, Lincoln NE 65888, United States; Nebraska Center for Integrated Biomolecular Communication, University of Nebraska-Lincoln, Lincoln NE 68588, United States; Department of Structural Biology, University of Pittsburgh, School of Medicine, 3501 Fifth Avenue, Pittsburgh, PA 15261, United States
| | - Jade Woods
- Department of Chemistry, University of Nebraska-Lincoln, Lincoln NE 65888, United States
| | - Michelle Winkler
- Texas Institute for Discovery Education in Science and Freshman Research Initiative, The University of Texas at Austin, Austin, TX 78712, United States
| | - Sebastian Rivera
- Texas Institute for Discovery Education in Science and Freshman Research Initiative, The University of Texas at Austin, Austin, TX 78712, United States
| | - Cassandra E Shannon
- Texas Institute for Discovery Education in Science and Freshman Research Initiative, The University of Texas at Austin, Austin, TX 78712, United States
| | - Holden R Wagner
- Texas Institute for Discovery Education in Science and Freshman Research Initiative, The University of Texas at Austin, Austin, TX 78712, United States
| | - Deborah L Zhuang
- Texas Institute for Discovery Education in Science and Freshman Research Initiative, The University of Texas at Austin, Austin, TX 78712, United States
| | - Jessica E Lynch
- Texas Institute for Discovery Education in Science and Freshman Research Initiative, The University of Texas at Austin, Austin, TX 78712, United States
| | - Nathan R Berryhill
- Texas Institute for Discovery Education in Science and Freshman Research Initiative, The University of Texas at Austin, Austin, TX 78712, United States
| | - Ron C Runnebaum
- Department of Viticulture and Enology, and Department of Chemical Engineering, University of California-Davis, Davis, CA 95616, United States.
| | - Eric V Anslyn
- Department of Chemistry, The University of Texas at Austin, Austin, TX 78712, United States.
| | - Robert Powers
- Department of Chemistry, University of Nebraska-Lincoln, Lincoln NE 65888, United States; Nebraska Center for Integrated Biomolecular Communication, University of Nebraska-Lincoln, Lincoln NE 68588, United States.
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Rubel Mozumder NHM, Hwang KH, Lee MS, Kim EH, Hong YS. Metabolomic understanding of the difference between unpruning and pruning cultivation of tea (Camellia sinensis) plants. Food Res Int 2021; 140:109978. [PMID: 33648213 DOI: 10.1016/j.foodres.2020.109978] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2020] [Revised: 11/26/2020] [Accepted: 12/09/2020] [Indexed: 12/15/2022]
Abstract
Tea (Camellia sinensis) leaf quality depends on several factors such as plucking seasons, cultivation practices, and climatic conditions, which affect the chemical compositions of tea leaves. Pruning has been practiced as one of the common cultivation managements in tea cultivation and is hypothesized to exhibit metabolic differences from unpruned tea plants. Although metabolomics studies provide immense information about production of distinct tea products, the metabolic physiology of the plants cultivated under unpruning conditions is poorly understood. Therefore, in the present study, we explored the metabolic characteristics of tea leaves obtained from unpruned tea plants collected at different plucking seasons in a single year and in a given plucking time in the three successive years, through 1H NMR-based metabolomics approach. Seasonal variations in diverse tea leaf metabolites both in pruned and unpruned tea plants were observed along with marked metabolic differences in tea leaves collected from pruned and unpruned tea plants in a given plucking time. Particularly, in abnormal year of vintage with high rainfall in 2018, high synthesis of glucose followed by high accumulations of catechin, including its derivatives, in unpruned tea, demonstrated intense active photosynthesis compared to pruned tea plants, indicating different metabolic responses of pruned and unpruned tea plants to similar climatic conditions. The current study highlights the important role of tea cultivation practices in tea plants for better management of leaf quality and the strong metabolic dependence on climatic conditions in a given vintage.
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Affiliation(s)
- N H M Rubel Mozumder
- Division of Food and Nutrition, Chonnam National University, Yongbong-ro, Buk-gu, Gwangju 61186, Republic of Korea
| | - Kyeong Hwan Hwang
- Basic Research & Innovation Division, R&D Center, AmorePacific Corporation, Kyeonggi-do 17074, Republic of Korea
| | - Min-Seuk Lee
- Osulloc Tea R&D Center, Osulloc Farm Corporation, Jeju 63521, Republic of Korea
| | - Eun-Hee Kim
- Center for Research Equipment, Korea Basic Science Institute, Cheongwon-Gu, Cheongju-Si, Chungbuk 28119, Republic of Korea
| | - Young-Shick Hong
- Division of Food and Nutrition, Chonnam National University, Yongbong-ro, Buk-gu, Gwangju 61186, Republic of Korea.
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Solovyev PA, Fauhl-Hassek C, Riedl J, Esslinger S, Bontempo L, Camin F. NMR spectroscopy in wine authentication: An official control perspective. Compr Rev Food Sci Food Saf 2021; 20:2040-2062. [PMID: 33506593 DOI: 10.1111/1541-4337.12700] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2020] [Revised: 11/30/2020] [Accepted: 12/23/2020] [Indexed: 12/14/2022]
Abstract
Wine authentication is vital in identifying malpractice and fraud, and various physical and chemical analytical techniques have been employed for this purpose. Besides wet chemistry, these include chromatography, isotopic ratio mass spectrometry, optical spectroscopy, and nuclear magnetic resonance (NMR) spectroscopy, which have been applied in recent years in combination with chemometric approaches. For many years, 2 H NMR spectroscopy was the method of choice and achieved official recognition in the detection of sugar addition to grape products. Recently, 1 H NMR spectroscopy, a simpler and faster method (in terms of sample preparation), has gathered more and more attention in wine analysis, even if it still lacks official recognition. This technique makes targeted quantitative determination of wine ingredients and nontargeted detection of the metabolomic fingerprint of a wine sample possible. This review summarizes the possibilities and limitations of 1 H NMR spectroscopy in analytical wine authentication, by reviewing its applications as reported in the literature. Examples of commercial and open-source solutions combining NMR spectroscopy and chemometrics are also examined herein, together with its opportunities of becoming an official method.
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Affiliation(s)
- Pavel A Solovyev
- Department of Food Quality and Nutrition, Research and Innovation Center, Fondazione Edmund Mach (FEM), via E. Mach 1, San Michele all'Adige, 38010, Italy
| | - Carsten Fauhl-Hassek
- German Federal Institute for Risk Assessment, Department Safety in the Food Chain, Unit Product Identity, Supply Chains and Traceability, Max-Dohrn Strasse, 8-10, Berlin, 10589, Germany
| | - Janet Riedl
- German Federal Institute for Risk Assessment, Department Safety in the Food Chain, Unit Product Identity, Supply Chains and Traceability, Max-Dohrn Strasse, 8-10, Berlin, 10589, Germany
| | - Susanne Esslinger
- German Federal Institute for Risk Assessment, Department Safety in the Food Chain, Unit Product Identity, Supply Chains and Traceability, Max-Dohrn Strasse, 8-10, Berlin, 10589, Germany
| | - Luana Bontempo
- Department of Food Quality and Nutrition, Research and Innovation Center, Fondazione Edmund Mach (FEM), via E. Mach 1, San Michele all'Adige, 38010, Italy
| | - Federica Camin
- Department of Food Quality and Nutrition, Research and Innovation Center, Fondazione Edmund Mach (FEM), via E. Mach 1, San Michele all'Adige, 38010, Italy.,Center Agriculture Food Environment (C3A), University of Trento, via Mach 1, San Michele all'Adige, Tennessee, 38010, Italy
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Barátossy G, Berinkeiné Donkó M, Csikorné Vásárhelyi H, Héberger K, Rácz A. Comprehensive Classification and Regression Modeling of Wine Samples Using 1H NMR Spectra. Foods 2020; 10:foods10010064. [PMID: 33396655 PMCID: PMC7824661 DOI: 10.3390/foods10010064] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Revised: 12/21/2020] [Accepted: 12/22/2020] [Indexed: 11/16/2022] Open
Abstract
Recently, 1H NMR (nuclear magnetic resonance) spectroscopy was presented as a viable option for the quality assurance of foods and beverages, such as wine products. Here, a complex chemometric analysis of red and white wine samples was carried out based on their 1H NMR spectra. Extreme gradient boosting (XGBoost) machine learning algorithm was applied for the wine variety classification with an iterative double cross-validation loop, developed during the present work. In the case of red wines, Cabernet Franc, Merlot and Blue Frankish samples were successfully classified. Three very common white wine varieties were selected and classified: Chardonnay, Sauvignon Blanc and Riesling. The models were robust and were validated against overfitting with iterative randomization tests. Moreover, four novel partial least-squares (PLS) regression models were constructed to predict the major quantitative parameters of the wines: density, total alcohol, total sugar and total SO2 concentrations. All the models performed successfully, with R2 values above 0.80 in almost every case, providing additional information about the wine samples for the quality control of the products. 1H NMR spectra combined with chemometric modeling can be a good and reliable candidate for the replacement of the time-consuming traditional standards, not just in wine analysis, but also in other aspects of food science.
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Affiliation(s)
- Gábor Barátossy
- National Food Chain Safety Office, Directorate of Oenology and Alcoholic Beverages, Budaörsi út 141-145, H-1118 Budapest, Hungary; (G.B.); (M.B.D.); (H.C.V.)
| | - Mária Berinkeiné Donkó
- National Food Chain Safety Office, Directorate of Oenology and Alcoholic Beverages, Budaörsi út 141-145, H-1118 Budapest, Hungary; (G.B.); (M.B.D.); (H.C.V.)
| | - Helga Csikorné Vásárhelyi
- National Food Chain Safety Office, Directorate of Oenology and Alcoholic Beverages, Budaörsi út 141-145, H-1118 Budapest, Hungary; (G.B.); (M.B.D.); (H.C.V.)
| | - Károly Héberger
- Department of Plasma Chemistry, Institute of Materials and Environmental Chemistry, Research Centre for Natural Sciences, Magyar Tudósok krt. 2, H-1117 Budapest, Hungary;
| | - Anita Rácz
- Department of Plasma Chemistry, Institute of Materials and Environmental Chemistry, Research Centre for Natural Sciences, Magyar Tudósok krt. 2, H-1117 Budapest, Hungary;
- Correspondence:
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Lau H, Laserna AKC, Li SFY. 1H NMR-based metabolomics for the discrimination of celery (Apium graveolens L. var. dulce) from different geographical origins. Food Chem 2020; 332:127424. [PMID: 32619947 DOI: 10.1016/j.foodchem.2020.127424] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2020] [Revised: 06/05/2020] [Accepted: 06/23/2020] [Indexed: 11/24/2022]
Abstract
Celery (Apium graveolens L. var dulce) is a widely cultivated vegetable which is popularly consumed due to its nutrient content and contains bioactive metabolites with positive effects on human physiology. In this study, 1H NMR spectroscopy coupled with multivariate statistical analyses was used to distinguish celery stem and leaf samples from different geographical origins. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were employed to investigate the differences between celery extracts from three geographical origins: Australia, Taiwan and China. Sugars, amino acids and organic acids were found to contribute significantly to the differentiation between origins, with mannitol identified as an important discriminating metabolite. It was demonstrated that NMR-based metabolomics is an effective approach for establishing reliable metabolomic fingerprints and profiles, enabling the identification of metabolite biomarkers for the possible discrimination of geographical origin.
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Affiliation(s)
- Hazel Lau
- Department of Chemistry, National University of Singapore, 3 Science Drive 3, Singapore 117543, Singapore
| | | | - Sam Fong Yau Li
- Department of Chemistry, National University of Singapore, 3 Science Drive 3, Singapore 117543, Singapore; NUS Environmental Research Institute (NERI), #02-01, T-Lab Building (TL), 5A Engineering Drive 1, Singapore 117411, Singapore.
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Carbohydrate composition of red wines during early aging and incidence on spoilage by Brettanomyces bruxellensis. Food Microbiol 2020; 92:103577. [PMID: 32950161 DOI: 10.1016/j.fm.2020.103577] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2020] [Revised: 03/30/2020] [Accepted: 06/21/2020] [Indexed: 01/16/2023]
Abstract
Wine is generally considered as hostile medium in which spoilage microbes have to manage with many abiotic factors among which low nutrient content. Wines elaborated in 8 wineries were sampled during the first summer of aging over two consecutive vintages, and analysed for carbohydrate composition. This revealed the systematic presence of many carbohydrates including those useful for the spoilage yeast Brettanomyces bruxellensis. However, during the first summer of aging, the changes in wine carbohydrate composition were low and it was difficult to assess how much carbohydrate composition contributed to wine spoilage by B. bruxellensis. Subsequent laboratory experiments in inoculated wines showed that the sugars preferentially consumed in wine by the spoilage yeast are d-glucose, d-fructose, and trehalose, whatever the yeast strain considered. The addition of these sugars to red wines accelerates the yeast growth and the volatile phenols formation. Although probably not the only promoting factor, the presence of high amounts of metabolisable sugars thus really increases the risk of "brett" spoilage.
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Polyphenols: Natural Antioxidants to Be Used as a Quality Tool in Wine Authenticity. APPLIED SCIENCES-BASEL 2020. [DOI: 10.3390/app10175908] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Polyphenols are a diverse group of compounds possessing various health-promoting properties that are of utmost importance for many wine sensory attributes. Apart from genetic and environmental parameters, the implementation of specific oenological practices as well as the subsequent storage conditions deeply affect the content and nature of the polyphenols present in wine. However, polyphenols are effectively employed in authenticity studies. Provision of authentic wines to the market has always been a prerequisite meaning that the declarations on the wine label should mirror the composition and provenance of this intriguing product. Nonetheless, multiple cases of intentional or unintentional wine mislabeling have been recorded alarming wine consumers who demand for strict controls safeguarding wine authenticity. The emergence of novel platforms employing instrumentation of exceptional selectivity and sensitivity along with the use of advanced chemometrics such as NMR (nuclear magnetic resonance)- and MS (mass spectrometry)-based metabolomics is considered as a powerful asset towards wine authentication.
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Mascellani A, Hoca G, Babisz M, Krska P, Kloucek P, Havlik J. 1H NMR chemometric models for classification of Czech wine type and variety. Food Chem 2020; 339:127852. [PMID: 32889133 DOI: 10.1016/j.foodchem.2020.127852] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2020] [Revised: 08/13/2020] [Accepted: 08/14/2020] [Indexed: 02/06/2023]
Abstract
A set of 917 wines of Czech origin were analysed using nuclear magnetic resonance spectroscopy (NMR) with the aim of building and evaluating multivariate statistical models and machine learning methods for the classification of 6 types based on colour and residual sugar content, 13 wine grape varieties and 4 locations based on 1H NMR spectra. The predictive models afforded greater than 93% correctness for classifying dry and medium dry, medium, and sweet white wines and dry red wines. The trained Random Forest (RF) model classified Pinot noir with 96% correctness, Blaufränkisch 96%, Riesling 92%, Cabernet Sauvignon 77%, Chardonnay 76%, Gewürtztraminer 60%, Hibernal 60%, Grüner Veltliner 52%, Pinot gris 48%, Sauvignon Blanc 45%, and Pálava 40%. Pinot blanc and Chardonnay, varieties that are often mistakenly interchanged, were discriminated with 71% correctness. The findings support chemometrics as a tool for predicting important features in wine, particularly for quality assessment and fraud detection.
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Affiliation(s)
- Anna Mascellani
- Department of Food Science, Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague, Kamycka 129, 165 00 Prague 6 - Suchdol, Czech Republic
| | - Gokce Hoca
- Department of Food Science, Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague, Kamycka 129, 165 00 Prague 6 - Suchdol, Czech Republic
| | - Marek Babisz
- The National Wine Centre, Zamek 1, 691 42 Valtice, Czech Republic
| | - Pavel Krska
- The National Wine Centre, Zamek 1, 691 42 Valtice, Czech Republic
| | - Pavel Kloucek
- Department of Food Science, Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague, Kamycka 129, 165 00 Prague 6 - Suchdol, Czech Republic
| | - Jaroslav Havlik
- Department of Food Science, Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague, Kamycka 129, 165 00 Prague 6 - Suchdol, Czech Republic.
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How Chemical and Sensorial Markers Reflect Gentian Geographic Origin in Chardonnay Wine Macerated with Gentiana lutea Roots? Foods 2020; 9:foods9081061. [PMID: 32764291 PMCID: PMC7466338 DOI: 10.3390/foods9081061] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2020] [Revised: 07/24/2020] [Accepted: 07/27/2020] [Indexed: 01/03/2023] Open
Abstract
A Burgundian Chardonnay wine was enriched with Gentiana lutea root powders originating from two French mountain sites (Massif Central and Jura) in order to prepare semi-dry gentian aromatized Chardonnay wine-based drinks. These novel alcoholic beverages were chemically and sensorially characterized for evaluating if the gentian geographic origin influenced bitter and elemental and volatile composition and sensory profiles in the final products. For that, the chemical fingerprint of gentian powders and wines were carried by headspace solid phase microextraction gas chromatography coupled to mass spectrometry (HS-SPME-GC), liquid chromatography coupled to diode array detector (LC-DAD) and inductive coupled plasma optical emission spectroscopy (ICP-OES). The mineral and volatile analysis show that the geographic distinction is more obvious in gentian powders compared to gentian macerated wines. Interestingly the maceration process in Chardonnay wine involves extraction processes revealing statistical distinctions in other chemical markers of gentian origin, like for amarogentin and loganic acid or some mineral elements such as barium and aluminum that affect undoubtedly bitterness perception and sensory properties in macerated wines compared to unmacerated wine. Additionally, the gentian volatile 2-methoxy-3-sec-butylpyrazine and the Chardonnay wine volatile ethyl-9-decenoate differentiated, respectively by extraction and powder adsorption mechanisms could be responsible of more subtle sensory differentiations between macerated wines from two distinct gentian origins.
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Li L, Jiang M, Li Y, Su J, Li L, Qu X, Fan L. 1H-NMR Metabolomics Analysis of the Effect of Rubusoside on Serum Metabolites of Golden Hamsters on a High-Fat Diet. Molecules 2020; 25:molecules25061274. [PMID: 32168894 PMCID: PMC7143983 DOI: 10.3390/molecules25061274] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2020] [Revised: 03/02/2020] [Accepted: 03/03/2020] [Indexed: 01/30/2023] Open
Abstract
Rubusoside is a natural sweetener and the active component of Rubus suavissimus. The preventive and therapeutic effect of rubusoside on high-fat diet-induced (HFD) serum metabolite changes in golden hamsters was analyzed by 1H-NMR metabolomics to explore the underlying mechanism of lipid metabolism regulation. 1H-NMR serum metabolomics analyses revealed a disturbed amino acid-, sugar-, fat-, and energy metabolism in HFD animals. Animals supplemented with rubusoside can partly reverse the metabolism disorders induced by high-fat diet and exerted good anti-hypertriglyceridemia effect by intervening in some major metabolic pathways, involving amino acid metabolism, synthesis of ketone bodies, as well as choline and 4-hydroxyphenylacetate metabolism. This study indicates that rubusoside can interfere with and normalize high-fat diet-induced metabolic changes in serum and could provide a theoretical basis to establish rubusoside as a potentially therapeutic tool able to revert or prevent lipid metabolism disorders.
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Affiliation(s)
- Li Li
- School of Pharmacy, Guangxi University of Chinese Medicine, Nanning 530001, China; (L.L.); (M.J.); (Y.L.); (L.L.)
| | - Manjing Jiang
- School of Pharmacy, Guangxi University of Chinese Medicine, Nanning 530001, China; (L.L.); (M.J.); (Y.L.); (L.L.)
| | - Yaohua Li
- School of Pharmacy, Guangxi University of Chinese Medicine, Nanning 530001, China; (L.L.); (M.J.); (Y.L.); (L.L.)
| | - Jian Su
- Guangxi Scientific Research Center of Traditional Chinese Medicine, Guangxi University of Chinese Medicine, Nanning 530001, China;
| | - Li Li
- School of Pharmacy, Guangxi University of Chinese Medicine, Nanning 530001, China; (L.L.); (M.J.); (Y.L.); (L.L.)
| | - Xiaosheng Qu
- National Engineering Laboratory of Southwest Endangered Medicinal Resources Development, Guangxi Botanical Garden of Medicinal Plants, Nanning 530023, China
- Correspondence: (X.Q.); (L.F.); Tel./Fax: +86-771-560-1290 (X.Q.); +86-771-495-3513 (L.F.)
| | - Lanlan Fan
- School of Pharmacy, Guangxi University of Chinese Medicine, Nanning 530001, China; (L.L.); (M.J.); (Y.L.); (L.L.)
- Correspondence: (X.Q.); (L.F.); Tel./Fax: +86-771-560-1290 (X.Q.); +86-771-495-3513 (L.F.)
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38
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Luo Y, Kong L, Xue R, Wang W, Xia X. Bitterness in alcoholic beverages: The profiles of perception, constituents, and contributors. Trends Food Sci Technol 2020. [DOI: 10.1016/j.tifs.2019.12.026] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/09/2023]
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