Classification of organic olives based on chemometric analysis of elemental data
The aim of this study was to discriminate organic from conventional olive samples based on the levels of macro and trace elements, combined with chemometric techniques. Ten elements (Na, K, Ca, Fe, Mg, Cu, Zn, Se, S and P) were determined in organic (n=30) and conventional (n=30) olive samples by...
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| Autores principales: | , , , , |
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| Formato: | Artículo |
| Lenguaje: | Inglés |
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Elsevier
2021
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| Acceso en línea: | http://repositorio.unne.edu.ar/handle/123456789/27961 |
| Aporte de: |
| id |
I48-R184-123456789-27961 |
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| record_format |
dspace |
| institution |
Universidad Nacional del Nordeste |
| institution_str |
I-48 |
| repository_str |
R-184 |
| collection |
RIUNNE - Repositorio Institucional de la Universidad Nacional del Nordeste (UNNE) |
| language |
Inglés |
| topic |
Olive Multivariate classification ICP-OES Chemometrics |
| spellingShingle |
Olive Multivariate classification ICP-OES Chemometrics Hidalgo, Melisa Jazmín Pozzi, María T. Furlong, Octavio J. Marchevsky, Eduardo Jorge Pellerano, Roberto Gerardo Classification of organic olives based on chemometric analysis of elemental data |
| topic_facet |
Olive Multivariate classification ICP-OES Chemometrics |
| description |
The aim of this study was to discriminate organic from conventional olive samples based on the levels of macro
and trace elements, combined with chemometric techniques. Ten elements (Na, K, Ca, Fe, Mg, Cu, Zn, Se, S and
P) were determined in organic (n=30) and conventional (n=30) olive samples by inductively coupled plasma
optical emission spectrometry analysis (ICP-OES). The classification of samples was performed by using a wellknown
chemometric techniques, linear discriminant analysis (LDA), partial least square-discriminant analysis
(PLS-DA), support vector machine-discriminant analysis (SVM-DA), k-nearest neighbors (k-NN) and random
forest (RF). The k-NN technique showed the best performance in discriminating organic from conventional
samples (Accuracy: 94%) using all chemical variables. After variable reduction, an accuracy of 83% was found
by using only the elements K and P. The use of a fingerprint based on multielemental levels associated with
classification chemometric techniques may be used as a simple method to authenticate organic olive samples. |
| format |
Artículo |
| author |
Hidalgo, Melisa Jazmín Pozzi, María T. Furlong, Octavio J. Marchevsky, Eduardo Jorge Pellerano, Roberto Gerardo |
| author_facet |
Hidalgo, Melisa Jazmín Pozzi, María T. Furlong, Octavio J. Marchevsky, Eduardo Jorge Pellerano, Roberto Gerardo |
| author_sort |
Hidalgo, Melisa Jazmín |
| title |
Classification of organic olives based on chemometric analysis of elemental data |
| title_short |
Classification of organic olives based on chemometric analysis of elemental data |
| title_full |
Classification of organic olives based on chemometric analysis of elemental data |
| title_fullStr |
Classification of organic olives based on chemometric analysis of elemental data |
| title_full_unstemmed |
Classification of organic olives based on chemometric analysis of elemental data |
| title_sort |
classification of organic olives based on chemometric analysis of elemental data |
| publisher |
Elsevier |
| publishDate |
2021 |
| url |
http://repositorio.unne.edu.ar/handle/123456789/27961 |
| work_keys_str_mv |
AT hidalgomelisajazmin classificationoforganicolivesbasedonchemometricanalysisofelementaldata AT pozzimariat classificationoforganicolivesbasedonchemometricanalysisofelementaldata AT furlongoctavioj classificationoforganicolivesbasedonchemometricanalysisofelementaldata AT marchevskyeduardojorge classificationoforganicolivesbasedonchemometricanalysisofelementaldata AT pelleranorobertogerardo classificationoforganicolivesbasedonchemometricanalysisofelementaldata |
| bdutipo_str |
Repositorios |
| _version_ |
1764820539001536513 |