FTIR-chemometric analytical methodology as a tool for clustering oils from centenarian olive trees grown in the Côa Valley region

Bibliographic Details
Main Author: Pascoal-Ferreira, P.
Publication Date: 2021
Other Authors: Peres, António M., Silva, Kevin, Santamaria-Echart, Arantzazu, Barreiro, M.F., Pereira, J.A., Baptista, Paula, Rodrigues, Nuno
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10198/26893
Summary: The centenarian olive trees are part of the historical and cultural heritage of the Côa Valley region where a significant number of these specimens can be found. They have high importance in olive grove heritage; however, their genetic and phenotypic diversity is still poorly studied. The identification of olive tree varieties is not an easy task, being required a morphological characterisation complemented with genetics, making this identification a time-consuming and expensive procedure. Recently, Fourier Transform Infrared (FTIR) spectroscopy start to be widely used in several studies in the food field, becoming a powerful analytical tool for the analysis of edible oils and fats1. This technique has numerous advantages, allowing a fast and non-destructive analysis, and requiring minimal sample preparation. In this context, FTIR has been applied to classify and identify different fats2, detection of virgin olive oils adulteration3, determination of trans fatty acids4 and evaluation of oil mixtures' composition in foods5, all this based on the spectral profiles 6. Considering that there is a great diversity of centenarian olive trees in which the varieties are unknown, the objective of this work was to use the FTIR technique to identify groups of olive oils with similar chemical characteristics, thus reducing the time and required amount of samples for analysis. Therefore, FTIR was applied to 99 olive oils from centenarian olive trees in the Côa Valley region. FTIR analysis was carried out using an MB300 FTIR from ABB (Zurich, Switzerland) operating in attenuated total reflectance (ATR) mode using a horizontal cell equipped with a diamond crystal. The spectra acquisition was done using 32 scans/min at a resolution of 4 cm-1, being the reading range comprised between 4000 and 500 cm-1. Spectra were acquired and treated using the software Horizon MB version 3.4. The background was acquired every two consecutive assays. Finally, raw transmittance data (in %) of the different olive oils were used for the statistical analysis. A hierarchical clustering dendogram was applied to evaluate the possibility of grouping the 99 olive oils studied according to the full FTIR spectra by computing the distance (dissimilarity) among the olive oils, using the Euclidean distance Ward method for matrix computation. The dendogram (Figure 1) allowed identifying dissimilarities based on the olive oils’ FTIR spectra, enabling to establish 4 main clusters, for a 2nd node cut establishing responding to a distance around 35. Since FTIR spectroscopy is sensitive to different aspects including the olive variety and considering that all the olive oils were extracted under similar conditions and from olives harvested in the same geographical regions, the observed variations can be tentatively attributed to the olive variety or to a similarity of the oils’ chemical composition. The clustering analysis allowed partitioning a large dataset of olive oils into smaller groups based on similar spectra characteristics, enabling the future practical and feasible evaluation of selected oils belonging to each of the 4 established clusters, avoiding the need to evaluate each one of the 99 olive oils.
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spelling FTIR-chemometric analytical methodology as a tool for clustering oils from centenarian olive trees grown in the Côa Valley regionOlive oilOlive treesResearch Subject Categories::FORESTRY, AGRICULTURAL SCIENCES and LANDSCAPE PLANNING::Product scienceThe centenarian olive trees are part of the historical and cultural heritage of the Côa Valley region where a significant number of these specimens can be found. They have high importance in olive grove heritage; however, their genetic and phenotypic diversity is still poorly studied. The identification of olive tree varieties is not an easy task, being required a morphological characterisation complemented with genetics, making this identification a time-consuming and expensive procedure. Recently, Fourier Transform Infrared (FTIR) spectroscopy start to be widely used in several studies in the food field, becoming a powerful analytical tool for the analysis of edible oils and fats1. This technique has numerous advantages, allowing a fast and non-destructive analysis, and requiring minimal sample preparation. In this context, FTIR has been applied to classify and identify different fats2, detection of virgin olive oils adulteration3, determination of trans fatty acids4 and evaluation of oil mixtures' composition in foods5, all this based on the spectral profiles 6. Considering that there is a great diversity of centenarian olive trees in which the varieties are unknown, the objective of this work was to use the FTIR technique to identify groups of olive oils with similar chemical characteristics, thus reducing the time and required amount of samples for analysis. Therefore, FTIR was applied to 99 olive oils from centenarian olive trees in the Côa Valley region. FTIR analysis was carried out using an MB300 FTIR from ABB (Zurich, Switzerland) operating in attenuated total reflectance (ATR) mode using a horizontal cell equipped with a diamond crystal. The spectra acquisition was done using 32 scans/min at a resolution of 4 cm-1, being the reading range comprised between 4000 and 500 cm-1. Spectra were acquired and treated using the software Horizon MB version 3.4. The background was acquired every two consecutive assays. Finally, raw transmittance data (in %) of the different olive oils were used for the statistical analysis. A hierarchical clustering dendogram was applied to evaluate the possibility of grouping the 99 olive oils studied according to the full FTIR spectra by computing the distance (dissimilarity) among the olive oils, using the Euclidean distance Ward method for matrix computation. The dendogram (Figure 1) allowed identifying dissimilarities based on the olive oils’ FTIR spectra, enabling to establish 4 main clusters, for a 2nd node cut establishing responding to a distance around 35. Since FTIR spectroscopy is sensitive to different aspects including the olive variety and considering that all the olive oils were extracted under similar conditions and from olives harvested in the same geographical regions, the observed variations can be tentatively attributed to the olive variety or to a similarity of the oils’ chemical composition. The clustering analysis allowed partitioning a large dataset of olive oils into smaller groups based on similar spectra characteristics, enabling the future practical and feasible evaluation of selected oils belonging to each of the 4 established clusters, avoiding the need to evaluate each one of the 99 olive oils.The authors are grateful to the Foundation for Science and Technology (FCT, Portugal) for financial support by national funds FCT/MCTES to CIMO (UIDB/00690/2020) and to Associate Laboratory for Green Chemistry-LAQV (UIDB/50006/2020). Nuno Rodrigues and Aran Santamaria-Echar thanks to National funding by FCT- Foundation for Science and Technology, P.I., through the institutional scientific employment program-contract. Funding: This work was financially supported by the project “COA/BRB/0035/2019” OLIVECOA - Centenarian olive trees of Côa Valley region: rediscovering the past to valorise the future funded by the Foundation for Science and Technology (FCT, Portugal).Universidade da MadeiraBiblioteca Digital do IPBPascoal-Ferreira, P.Peres, António M.Silva, KevinSantamaria-Echart, ArantzazuBarreiro, M.F.Pereira, J.A.Baptista, PaulaRodrigues, Nuno2023-02-10T15:29:01Z20212021-01-01T00:00:00Zconference objectinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/10198/26893engPascoal-Ferreira, P.; Peres, António M.; Silva, Kevin; Santamaria-Echart, Arantzazu; Barreiro, M.F.; Pereira, J.A.; Baptista, Paula; Rodrigues, Nuno (2021). FTIR-chemometric analytical methodology as a tool for clustering oils from centenarian olive trees grown in the Côa Valley region. In José S. Câmara; Jorge A. M. Pereira; Rosa Perestrelo Gouveia (Eds.) Livro de Resumos do XV Encontro de Química dos Alimentos: Estratégias para a Excelência, Autenticidade, Segurança e Sustentabilidade Alimentar. Funchal978-989-8805-68-3info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-02-25T12:17:54Zoai:bibliotecadigital.ipb.pt:10198/26893Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T11:45:37.980611Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv FTIR-chemometric analytical methodology as a tool for clustering oils from centenarian olive trees grown in the Côa Valley region
title FTIR-chemometric analytical methodology as a tool for clustering oils from centenarian olive trees grown in the Côa Valley region
spellingShingle FTIR-chemometric analytical methodology as a tool for clustering oils from centenarian olive trees grown in the Côa Valley region
Pascoal-Ferreira, P.
Olive oil
Olive trees
Research Subject Categories::FORESTRY, AGRICULTURAL SCIENCES and LANDSCAPE PLANNING::Product science
title_short FTIR-chemometric analytical methodology as a tool for clustering oils from centenarian olive trees grown in the Côa Valley region
title_full FTIR-chemometric analytical methodology as a tool for clustering oils from centenarian olive trees grown in the Côa Valley region
title_fullStr FTIR-chemometric analytical methodology as a tool for clustering oils from centenarian olive trees grown in the Côa Valley region
title_full_unstemmed FTIR-chemometric analytical methodology as a tool for clustering oils from centenarian olive trees grown in the Côa Valley region
title_sort FTIR-chemometric analytical methodology as a tool for clustering oils from centenarian olive trees grown in the Côa Valley region
author Pascoal-Ferreira, P.
author_facet Pascoal-Ferreira, P.
Peres, António M.
Silva, Kevin
Santamaria-Echart, Arantzazu
Barreiro, M.F.
Pereira, J.A.
Baptista, Paula
Rodrigues, Nuno
author_role author
author2 Peres, António M.
Silva, Kevin
Santamaria-Echart, Arantzazu
Barreiro, M.F.
Pereira, J.A.
Baptista, Paula
Rodrigues, Nuno
author2_role author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv Biblioteca Digital do IPB
dc.contributor.author.fl_str_mv Pascoal-Ferreira, P.
Peres, António M.
Silva, Kevin
Santamaria-Echart, Arantzazu
Barreiro, M.F.
Pereira, J.A.
Baptista, Paula
Rodrigues, Nuno
dc.subject.por.fl_str_mv Olive oil
Olive trees
Research Subject Categories::FORESTRY, AGRICULTURAL SCIENCES and LANDSCAPE PLANNING::Product science
topic Olive oil
Olive trees
Research Subject Categories::FORESTRY, AGRICULTURAL SCIENCES and LANDSCAPE PLANNING::Product science
description The centenarian olive trees are part of the historical and cultural heritage of the Côa Valley region where a significant number of these specimens can be found. They have high importance in olive grove heritage; however, their genetic and phenotypic diversity is still poorly studied. The identification of olive tree varieties is not an easy task, being required a morphological characterisation complemented with genetics, making this identification a time-consuming and expensive procedure. Recently, Fourier Transform Infrared (FTIR) spectroscopy start to be widely used in several studies in the food field, becoming a powerful analytical tool for the analysis of edible oils and fats1. This technique has numerous advantages, allowing a fast and non-destructive analysis, and requiring minimal sample preparation. In this context, FTIR has been applied to classify and identify different fats2, detection of virgin olive oils adulteration3, determination of trans fatty acids4 and evaluation of oil mixtures' composition in foods5, all this based on the spectral profiles 6. Considering that there is a great diversity of centenarian olive trees in which the varieties are unknown, the objective of this work was to use the FTIR technique to identify groups of olive oils with similar chemical characteristics, thus reducing the time and required amount of samples for analysis. Therefore, FTIR was applied to 99 olive oils from centenarian olive trees in the Côa Valley region. FTIR analysis was carried out using an MB300 FTIR from ABB (Zurich, Switzerland) operating in attenuated total reflectance (ATR) mode using a horizontal cell equipped with a diamond crystal. The spectra acquisition was done using 32 scans/min at a resolution of 4 cm-1, being the reading range comprised between 4000 and 500 cm-1. Spectra were acquired and treated using the software Horizon MB version 3.4. The background was acquired every two consecutive assays. Finally, raw transmittance data (in %) of the different olive oils were used for the statistical analysis. A hierarchical clustering dendogram was applied to evaluate the possibility of grouping the 99 olive oils studied according to the full FTIR spectra by computing the distance (dissimilarity) among the olive oils, using the Euclidean distance Ward method for matrix computation. The dendogram (Figure 1) allowed identifying dissimilarities based on the olive oils’ FTIR spectra, enabling to establish 4 main clusters, for a 2nd node cut establishing responding to a distance around 35. Since FTIR spectroscopy is sensitive to different aspects including the olive variety and considering that all the olive oils were extracted under similar conditions and from olives harvested in the same geographical regions, the observed variations can be tentatively attributed to the olive variety or to a similarity of the oils’ chemical composition. The clustering analysis allowed partitioning a large dataset of olive oils into smaller groups based on similar spectra characteristics, enabling the future practical and feasible evaluation of selected oils belonging to each of the 4 established clusters, avoiding the need to evaluate each one of the 99 olive oils.
publishDate 2021
dc.date.none.fl_str_mv 2021
2021-01-01T00:00:00Z
2023-02-10T15:29:01Z
dc.type.driver.fl_str_mv conference object
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10198/26893
url http://hdl.handle.net/10198/26893
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Pascoal-Ferreira, P.; Peres, António M.; Silva, Kevin; Santamaria-Echart, Arantzazu; Barreiro, M.F.; Pereira, J.A.; Baptista, Paula; Rodrigues, Nuno (2021). FTIR-chemometric analytical methodology as a tool for clustering oils from centenarian olive trees grown in the Côa Valley region. In José S. Câmara; Jorge A. M. Pereira; Rosa Perestrelo Gouveia (Eds.) Livro de Resumos do XV Encontro de Química dos Alimentos: Estratégias para a Excelência, Autenticidade, Segurança e Sustentabilidade Alimentar. Funchal
978-989-8805-68-3
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade da Madeira
publisher.none.fl_str_mv Universidade da Madeira
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
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instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
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reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
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