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Stój A, Czernecki T, Domagała D. Authentication of Polish Red Wines Produced from Zweigelt and Rondo Grape Varieties Based on Volatile Compounds Analysis in Combination with Machine Learning Algorithms: Hotrienol as a Marker of the Zweigelt Variety. Molecules 2023; 28:1961. [PMID: 36838950 PMCID: PMC9967794 DOI: 10.3390/molecules28041961] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2023] [Revised: 02/10/2023] [Accepted: 02/16/2023] [Indexed: 02/22/2023] Open
Abstract
The aim of this study was to determine volatile compounds in red wines of Zweigelt and Rondo varieties using HS-SPME/GC-MS and to find a marker and/or a classification model for the assessment of varietal authenticity. The wines were produced by using five commercial yeast strains and two types of malolactic fermentation. Sixty-seven volatile compounds were tentatively identified in the test wines; they represented several classes: 9 acids, 24 alcohols, 2 aldehydes, 19 esters, 2 furan compounds, 2 ketones, 1 sulfur compound and 8 terpenes. 3,7-dimethyl-1,5,7-octatrien-3-ol (hotrienol) was found to be a variety marker for Zweigelt wines, since it was detected in all the Zweigelt wines, but was not present in the Rondo wines at all. The relative concentrations of volatiles were used as an input data set, divided into two subsets (training and testing), to the support vector machine (SVM) and k-nearest neighbor (kNN) algorithms. Both machine learning methods yielded models with the highest possible classification accuracy (100%) when the relative concentrations of all the test compounds or alcohols alone were used as input data. An evaluation of the importance value of subsets consisting of six volatile compounds with the highest potential to distinguish between the Zweigelt and Rondo varieties revealed that SVM and kNN yielded the best classification models (F-score of 1, accuracy of 100%) when 3-ethyl-4-methylpentan-1-ol or 3,7-dimethyl-1,5,7-octatrien-3-ol (hotrienol) or subsets containing one or both of them were used. Moreover, the best SVM model (F-score of 1) was built with a subset containing 2-phenylethyl acetate and 3-(methylsulfanyl)propan-1-ol.
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Affiliation(s)
- Anna Stój
- Department of Biotechnology, Microbiology and Human Nutrition, Faculty of Food Science and Biotechnology, University of Life Sciences, 8 Skromna Street, 20-704 Lublin, Poland
| | - Tomasz Czernecki
- Department of Biotechnology, Microbiology and Human Nutrition, Faculty of Food Science and Biotechnology, University of Life Sciences, 8 Skromna Street, 20-704 Lublin, Poland
| | - Dorota Domagała
- Department of Applied Mathematics and Computer Science, Faculty of Production Engineering, University of Life Sciences in Lublin, 28 Głęboka Street, 20-612 Lublin, Poland
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Dou X, Zhang L, Yang R, Wang X, Yu L, Yue X, Ma F, Mao J, Wang X, Zhang W, Li P. Mass spectrometry in food authentication and origin traceability. MASS SPECTROMETRY REVIEWS 2022:e21779. [PMID: 35532212 DOI: 10.1002/mas.21779] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/28/2021] [Revised: 03/10/2022] [Accepted: 04/15/2022] [Indexed: 06/14/2023]
Abstract
Food authentication and origin traceability are popular research topics, especially as concerns about food quality continue to increase. Mass spectrometry (MS) plays an indispensable role in food authentication and origin traceability. In this review, the applications of MS in food authentication and origin traceability by analyzing the main components and chemical fingerprints or profiles are summarized. In addition, the characteristic markers for food authentication are also reviewed, and the advantages and disadvantages of MS-based techniques for food authentication, as well as the current trends and challenges, are discussed. The fingerprinting and profiling methods, in combination with multivariate statistical analysis, are more suitable for the authentication of high-value foods, while characteristic marker-based methods are more suitable for adulteration detection. Several new techniques have been introduced to the field, such as proton transfer reaction mass spectrometry, ambient ionization mass spectrometry (AIMS), and ion mobility mass spectrometry, for the determination of food adulteration due to their fast and convenient analysis. As an important trend, the miniaturization of MS offers advantages, such as small and portable instrumentation and fast and nondestructive analysis. Moreover, many applications in food authentication are using AIMS, which can help food authentication in food inspection/field analysis. This review provides a reference and guide for food authentication and traceability based on MS.
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Affiliation(s)
- Xinjing Dou
- Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan, China
| | - Liangxiao Zhang
- Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Wuhan, China
- Laboratory of Quality and Safety Risk Assessment for Oilseed Products (Wuhan), Ministry of Agriculture and Rural Affairs, Wuhan, China
| | - Ruinan Yang
- Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan, China
| | - Xiao Wang
- Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan, China
| | - Li Yu
- Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan, China
- Quality Inspection and Test Center for Oilseeds Products, Ministry of Agriculture and Rural Affairs, Wuhan, China
| | - Xiaofeng Yue
- Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
| | - Fei Ma
- Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan, China
- Quality Inspection and Test Center for Oilseeds Products, Ministry of Agriculture and Rural Affairs, Wuhan, China
- Nanjing University of Finance and Economics, Collaborative Innovation Center for Modern Grain Circulation and Safety, Nanjing, China
| | - Jin Mao
- Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
- Laboratory of Quality and Safety Risk Assessment for Oilseed Products (Wuhan), Ministry of Agriculture and Rural Affairs, Wuhan, China
| | - Xiupin Wang
- Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan, China
- Quality Inspection and Test Center for Oilseeds Products, Ministry of Agriculture and Rural Affairs, Wuhan, China
| | - Wen Zhang
- Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan, China
- Quality Inspection and Test Center for Oilseeds Products, Ministry of Agriculture and Rural Affairs, Wuhan, China
- Nanjing University of Finance and Economics, Collaborative Innovation Center for Modern Grain Circulation and Safety, Nanjing, China
| | - Peiwu Li
- Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Wuhan, China
- Laboratory of Quality and Safety Risk Assessment for Oilseed Products (Wuhan), Ministry of Agriculture and Rural Affairs, Wuhan, China
- Quality Inspection and Test Center for Oilseeds Products, Ministry of Agriculture and Rural Affairs, Wuhan, China
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Kalogiouri NP, Samanidou VF. Liquid chromatographic methods coupled to chemometrics: a short review to present the key workflow for the investigation of wine phenolic composition as it is affected by environmental factors. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2021; 28:59150-59164. [PMID: 32577971 DOI: 10.1007/s11356-020-09681-5] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/06/2020] [Accepted: 06/10/2020] [Indexed: 06/11/2023]
Abstract
The guarantee of wine authenticity arises great concern because of its nutritional and economic importance. Phenolic fingerprints have been used as a source of chemical information for various authentication issues, including botanical and geographical origin, as well as vintage age. The local environment affects wine production and especially its phenolic metabolites. Integrated analytical methodologies combined with chemometrics can be applied in wine fingerprinting studies for the determination and establishment of phenolic markers that contain comprehensive and standardized information about the wine profile and how it can be affected by various environmental factors. This review summarizes all the recent trends in the generation of chemometric models that have been developed for treating chromatographic data and have been used for the investigation of critical wine authenticity issues, revealing phenolic markers responsible for the botanical, geographical, and vintage age classification of wines. Overall, the current review suggests that chromatographic methodologies are promising and powerful techniques that can be used for the accurate determination of phenolic compounds in difficult matrices like wine, highlighting the advantages of the applications of supervised chemometric tools over unsupervised for the construction of prediction models that have been successfully used for the classification based on their territorial and botanical origin.
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Affiliation(s)
- Natasa P Kalogiouri
- Laboratory of Analytical Chemistry, Department of Chemistry, Aristotle University of Thessaloniki, 54124, Thessaloniki, Greece.
| | - Victoria F Samanidou
- Laboratory of Analytical Chemistry, Department of Chemistry, Aristotle University of Thessaloniki, 54124, Thessaloniki, Greece
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Cassago ALL, Artêncio MM, de Moura Engracia Giraldi J, Da Costa FB. Metabolomics as a marketing tool for geographical indication products: a literature review. Eur Food Res Technol 2021; 247:2143-2159. [PMID: 34149310 PMCID: PMC8204615 DOI: 10.1007/s00217-021-03782-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Revised: 05/20/2021] [Accepted: 05/22/2021] [Indexed: 12/30/2022]
Abstract
Geographical indication (GI) is used to identify a product's origin when its characteristics or quality are a result of geographical origin, which includes agricultural products and foodstuff. Metabolomics is an “omics” technique that can support product authentication by providing a chemical fingerprint of a biological system, such as plant and plant-derived products. The main purpose of this article is to verify possible contributions of metabolomic studies to the marketing field, mainly for certified regions, through an integrative review of the literature and maps produced by VOSviewer software. The results indicate that studies based on metabolomics approaches can relate specific food attributes to the region’s terroir and know-how. The evidence of this connection, marketing of GIs and metabolomics methods, is viewed as potential tool for marketing purposes (e.g., to assist communication of positive aspects and quality), and legal protection. In addition, our results provide a taxonomic categorization that can guide future marketing research involving metabolomics. Moreover, the results are also useful to government agencies to improve GIs registration systems and promotion strategies.
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Affiliation(s)
- Alvaro Luis Lamas Cassago
- Department of Pharmaceutical Sciences, University of São Paulo (USP), School of Pharmaceutical Sciences of Ribeirão Preto, Av. do Café s/n, Ribeirão Preto, SP 14040-903 Brazil
| | - Mateus Manfrin Artêncio
- Department of Business Administration, University of São Paulo, School of Economics, Business Administration and Accounting of Ribeirão Preto, Av. Bandeirantes, 3900, Ribeirão Preto, SP 14040-905 Brazil
| | - Janaina de Moura Engracia Giraldi
- Department of Business Administration, University of São Paulo, School of Economics, Business Administration and Accounting of Ribeirão Preto, Av. Bandeirantes, 3900, Ribeirão Preto, SP 14040-905 Brazil
| | - Fernando Batista Da Costa
- Department of Pharmaceutical Sciences, University of São Paulo (USP), School of Pharmaceutical Sciences of Ribeirão Preto, Av. do Café s/n, Ribeirão Preto, SP 14040-903 Brazil
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Jiménez-Carvelo AM, González-Casado A, Bagur-González MG, Cuadros-Rodríguez L. Alternative data mining/machine learning methods for the analytical evaluation of food quality and authenticity - A review. Food Res Int 2019; 122:25-39. [PMID: 31229078 DOI: 10.1016/j.foodres.2019.03.063] [Citation(s) in RCA: 123] [Impact Index Per Article: 24.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2019] [Revised: 03/25/2019] [Accepted: 03/26/2019] [Indexed: 12/31/2022]
Abstract
In recent years, the variety and volume of data acquired by modern analytical instruments in order to conduct a better authentication of food has dramatically increased. Several pattern recognition tools have been developed to deal with the large volume and complexity of available trial data. The most widely used methods are principal component analysis (PCA), partial least squares-discriminant analysis (PLS-DA), soft independent modelling by class analogy (SIMCA), k-nearest neighbours (kNN), parallel factor analysis (PARAFAC), and multivariate curve resolution-alternating least squares (MCR-ALS). Nevertheless, there are alternative data treatment methods, such as support vector machine (SVM), classification and regression tree (CART) and random forest (RF), that show a great potential and more advantages compared to conventional ones. In this paper, we explain the background of these methods and review and discuss the reported studies in which these three methods have been applied in the area of food quality and authenticity. In addition, we clarify the technical terminology used in this particular area of research.
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Affiliation(s)
- Ana M Jiménez-Carvelo
- Department of Analytical Chemistry, Faculty of Science, University of Granada, C/ Fuentenueva s/n, E-18071 Granada, Spain.
| | - Antonio González-Casado
- Department of Analytical Chemistry, Faculty of Science, University of Granada, C/ Fuentenueva s/n, E-18071 Granada, Spain
| | - M Gracia Bagur-González
- Department of Analytical Chemistry, Faculty of Science, University of Granada, C/ Fuentenueva s/n, E-18071 Granada, Spain
| | - Luis Cuadros-Rodríguez
- Department of Analytical Chemistry, Faculty of Science, University of Granada, C/ Fuentenueva s/n, E-18071 Granada, Spain
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