Fuzzy Divisive Hierarchical Associative-Clustering Applied to Different Varieties of White Wines According to Their Multi-Elemental Profiles
Wine data are usually characterized by high variability, in terms of compounds and concentration ranges. Chemometric methods can be efficiently used to extract and exploit the meaningful information contained in such data. Therefore, the fuzzy divisive hierarchical associative-clustering (FDHAC) met...
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| Published in: | Molecules (Basel, Switzerland) Vol. 25; no. 21; p. 4955 |
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| Main Authors: | , , , , |
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| Abstract | Wine data are usually characterized by high variability, in terms of compounds and concentration ranges. Chemometric methods can be efficiently used to extract and exploit the meaningful information contained in such data. Therefore, the fuzzy divisive hierarchical associative-clustering (FDHAC) method was efficiently applied in this study, for the classification of several varieties of Romanian white wines, using the elemental profile (concentrations of 30 elements analyzed by ICP-MS). The investigated wines were produced in four different geographical areas of Romania (Transylvania, Moldova, Muntenia and Oltenia). The FDHAC algorithm provided not only a fuzzy partition of the investigated white wines, but also a fuzzy partition of considered characteristics. Furthermore, this method is unique because it allows a 3D bi-plot representation of membership degrees corresponding to wine samples and elements. In this way, it was possible to identify the most specific elements (in terms of highest, smallest or intermediate concentration values) to each fuzzy partition (group) of wine samples. The chemical elements that appeared to be more powerful for the differentiation of the wines produced in different Romanian areas were: K, Rb, P, Ca, B, Na. |
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| AbstractList | Wine data are usually characterized by high variability, in terms of compounds and concentration ranges. Chemometric methods can be efficiently used to extract and exploit the meaningful information contained in such data. Therefore, the fuzzy divisive hierarchical associative-clustering (FDHAC) method was efficiently applied in this study, for the classification of several varieties of Romanian white wines, using the elemental profile (concentrations of 30 elements analyzed by ICP-MS). The investigated wines were produced in four different geographical areas of Romania (Transylvania, Moldova, Muntenia and Oltenia). The FDHAC algorithm provided not only a fuzzy partition of the investigated white wines, but also a fuzzy partition of considered characteristics. Furthermore, this method is unique because it allows a 3D bi-plot representation of membership degrees corresponding to wine samples and elements. In this way, it was possible to identify the most specific elements (in terms of highest, smallest or intermediate concentration values) to each fuzzy partition (group) of wine samples. The chemical elements that appeared to be more powerful for the differentiation of the wines produced in different Romanian areas were: K, Rb, P, Ca, B, Na. |
| Author | Cristea, Gabriela Sârbu, Costel Feher, Ioana Magdas, Dana Alina Voica, Cezara |
| AuthorAffiliation | 1 National Institute for Research and Development of Isotopic and Molecular Technologies, 67-103 Donath, 400293 Cluj-Napoca, Romania; cezara.voica@itim-cj.ro (C.V.); gabriela.cristea@itim-cj.ro (G.C.) 2 Faculty of Chemistry and Chemical Engineering, Babeş-Bolyai University, 11 Arany Janos, 400028 Cluj-Napoca, Romania; csarbu@chem.ubbcluj.ro |
| AuthorAffiliation_xml | – name: 2 Faculty of Chemistry and Chemical Engineering, Babeş-Bolyai University, 11 Arany Janos, 400028 Cluj-Napoca, Romania; csarbu@chem.ubbcluj.ro – name: 1 National Institute for Research and Development of Isotopic and Molecular Technologies, 67-103 Donath, 400293 Cluj-Napoca, Romania; cezara.voica@itim-cj.ro (C.V.); gabriela.cristea@itim-cj.ro (G.C.) |
| Author_xml | – sequence: 1 givenname: Ioana orcidid: 0000-0002-2232-1644 surname: Feher fullname: Feher, Ioana organization: National Institute for Research and Development of Isotopic and Molecular Technologies, 67-103 Donath, 400293 Cluj-Napoca, Romania – sequence: 2 givenname: Dana Alina orcidid: 0000-0001-8101-9843 surname: Magdas fullname: Magdas, Dana Alina organization: National Institute for Research and Development of Isotopic and Molecular Technologies, 67-103 Donath, 400293 Cluj-Napoca, Romania – sequence: 3 givenname: Cezara surname: Voica fullname: Voica, Cezara organization: National Institute for Research and Development of Isotopic and Molecular Technologies, 67-103 Donath, 400293 Cluj-Napoca, Romania – sequence: 4 givenname: Gabriela orcidid: 0000-0001-8171-7473 surname: Cristea fullname: Cristea, Gabriela organization: National Institute for Research and Development of Isotopic and Molecular Technologies, 67-103 Donath, 400293 Cluj-Napoca, Romania – sequence: 5 givenname: Costel orcidid: 0000-0001-9374-2078 surname: Sârbu fullname: Sârbu, Costel organization: Faculty of Chemistry and Chemical Engineering, Babeş-Bolyai University, 11 Arany Janos, 400028 Cluj-Napoca, Romania |
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| Keywords | fuzzy associative-clustering elemental profile white wines ICP-MS analysis |
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Intell. Lab Syst contributor: fullname: Zehl |
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| SubjectTerms | Agricultural management Chemical elements Chemical partition Cluster Analysis Clustering Cultivars elemental profile Fertilizers Food Analysis Food products fuzzy associative-clustering Fuzzy Logic Fuzzy sets Geography ICP-MS analysis Scientific imaging white wines Wine - analysis Wines |
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| Title | Fuzzy Divisive Hierarchical Associative-Clustering Applied to Different Varieties of White Wines According to Their Multi-Elemental Profiles |
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