Academic Journal
Data fusion using multiple factor analysis coupled with non-linear pattern recognition (fuzzy k-means) : application to Chenin blanc
| Τίτλος: | Data fusion using multiple factor analysis coupled with non-linear pattern recognition (fuzzy k-means) : application to Chenin blanc |
|---|---|
| Συγγραφείς: | Mafata, M., Brand, J., Buica, A. |
| Στοιχεία εκδότη: | International Viticulture and Enology Society |
| Έτος έκδοσης: | 2022 |
| Συλλογή: | Stellenbosch University: SUNScholar Research Repository |
| Θεματικοί όροι: | Chenin blanc (Wine grape), White wines -- Analysis, Wine and wine making -- Chemistry, Multisensor data fusion, Cluster analysis -- Data processing |
| Περιγραφή: | The original publication is available at: https://oeno-one.eu ; Patterns in data obtained from wine chemical and sensory evaluations are difficult to decipher using classical statistics. Coupling data fusion with machine learning techniques could assist in solving these issues and lead to new hypotheses. The current study investigated the applicability of classical and machine learning pattern recognition approaches for oenological applications. A sample set of 23 Chenin blanc wines made from young (< 35 years) and old (> 35 years) vines were analysed (recently bottled (Year 1) and after two years of storage (Year 2)). Sensory (sorting) and chemical (NMR: nuclear magnetic resonance and HRMS: high-resolution mass spectrometry) data were collected. Multiple factor analysis (MFA) was used for the data fusion. Cluster analysis was performed by agglomerative hierarchical clustering (AHC) and fuzzy k-means. Optimal cluster conditions were found for both methods and the cophenetic coefficient was used to assess the confidence of fit. Given the large number of variables, the models were complex. Inconsistent clustering patterns were observed when varying clustering conditions, indicating high similarity between samples. Overall, fuzzy k-means resolved clustering patterns better than AHC and, coupled with data fusion, improved the interpretation of the complex oenological data. ; https://oeno-one.eu/article/view/5374 ; Publisher’s version |
| Τύπος εγγράφου: | article in journal/newspaper |
| Περιγραφή αρχείου: | 13 pages; application/pdf |
| Γλώσσα: | English |
| Relation: | https://scholar.sun.ac.za/handle/10019.1/133116 |
| DOI: | 10.20870/oeno-one.2022.56.3.5374 |
| Διαθεσιμότητα: | https://doi.org/10.20870/oeno-one.2022.56.3.5374 https://scholar.sun.ac.za/handle/10019.1/133116 |
| Rights: | Authors retain copyright |
| Αριθμός Καταχώρησης: | edsbas.8FF71300 |
| Βάση Δεδομένων: | BASE |
| FullText | Text: Availability: 0 CustomLinks: – Url: https://doi.org/10.20870/oeno-one.2022.56.3.5374# Name: EDS - BASE (ns324271) Category: fullText Text: View record from BASE |
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| Items | – Name: Title Label: Title Group: Ti Data: Data fusion using multiple factor analysis coupled with non-linear pattern recognition (fuzzy k-means) : application to Chenin blanc – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Mafata%2C+M%2E%22">Mafata, M.</searchLink><br /><searchLink fieldCode="AR" term="%22Brand%2C+J%2E%22">Brand, J.</searchLink><br /><searchLink fieldCode="AR" term="%22Buica%2C+A%2E%22">Buica, A.</searchLink> – Name: Publisher Label: Publisher Information Group: PubInfo Data: International Viticulture and Enology Society – Name: DatePubCY Label: Publication Year Group: Date Data: 2022 – Name: Subset Label: Collection Group: HoldingsInfo Data: Stellenbosch University: SUNScholar Research Repository – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Chenin+blanc+%28Wine+grape%29%22">Chenin blanc (Wine grape)</searchLink><br /><searchLink fieldCode="DE" term="%22White+wines+--+Analysis%22">White wines -- Analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Wine+and+wine+making+--+Chemistry%22">Wine and wine making -- Chemistry</searchLink><br /><searchLink fieldCode="DE" term="%22Multisensor+data+fusion%22">Multisensor data fusion</searchLink><br /><searchLink fieldCode="DE" term="%22Cluster+analysis+--+Data+processing%22">Cluster analysis -- Data processing</searchLink> – Name: Abstract Label: Description Group: Ab Data: The original publication is available at: https://oeno-one.eu ; Patterns in data obtained from wine chemical and sensory evaluations are difficult to decipher using classical statistics. Coupling data fusion with machine learning techniques could assist in solving these issues and lead to new hypotheses. The current study investigated the applicability of classical and machine learning pattern recognition approaches for oenological applications. A sample set of 23 Chenin blanc wines made from young (< 35 years) and old (> 35 years) vines were analysed (recently bottled (Year 1) and after two years of storage (Year 2)). Sensory (sorting) and chemical (NMR: nuclear magnetic resonance and HRMS: high-resolution mass spectrometry) data were collected. Multiple factor analysis (MFA) was used for the data fusion. Cluster analysis was performed by agglomerative hierarchical clustering (AHC) and fuzzy k-means. Optimal cluster conditions were found for both methods and the cophenetic coefficient was used to assess the confidence of fit. Given the large number of variables, the models were complex. Inconsistent clustering patterns were observed when varying clustering conditions, indicating high similarity between samples. Overall, fuzzy k-means resolved clustering patterns better than AHC and, coupled with data fusion, improved the interpretation of the complex oenological data. ; https://oeno-one.eu/article/view/5374 ; Publisher’s version – Name: TypeDocument Label: Document Type Group: TypDoc Data: article in journal/newspaper – Name: Format Label: File Description Group: SrcInfo Data: 13 pages; application/pdf – Name: Language Label: Language Group: Lang Data: English – Name: NoteTitleSource Label: Relation Group: SrcInfo Data: https://scholar.sun.ac.za/handle/10019.1/133116 – Name: DOI Label: DOI Group: ID Data: 10.20870/oeno-one.2022.56.3.5374 – Name: URL Label: Availability Group: URL Data: https://doi.org/10.20870/oeno-one.2022.56.3.5374<br />https://scholar.sun.ac.za/handle/10019.1/133116 – Name: Copyright Label: Rights Group: Cpyrght Data: Authors retain copyright – Name: AN Label: Accession Number Group: ID Data: edsbas.8FF71300 |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.20870/oeno-one.2022.56.3.5374 Languages: – Text: English Subjects: – SubjectFull: Chenin blanc (Wine grape) Type: general – SubjectFull: White wines -- Analysis Type: general – SubjectFull: Wine and wine making -- Chemistry Type: general – SubjectFull: Multisensor data fusion Type: general – SubjectFull: Cluster analysis -- Data processing Type: general Titles: – TitleFull: Data fusion using multiple factor analysis coupled with non-linear pattern recognition (fuzzy k-means) : application to Chenin blanc Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Mafata, M. – PersonEntity: Name: NameFull: Brand, J. – PersonEntity: Name: NameFull: Buica, A. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Type: published Y: 2022 Identifiers: – Type: issn-locals Value: edsbas |
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