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Comparison of partial least squares-discriminant analysis and soft independent modeling of class analogy methods for classification of Saccharomyces cerevisiae cells based on mid-infrared spectroscopy

2021-03-02Journal article Restricted access
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dc.contributor.authorSampaio, Pedro
dc.contributor.authorCalado, Cecília
dc.date.accessioned2021-04-22T14:40:52Z
dc.date.available2021-04-22T14:40:52Z
dc.date.issued2021-03-02
dc.description.abstractSaccharomyces cerevisiae is a widely studied and highly utilized eukaryotic organism, ideally suited to high throughput metabolic analysis, being a powerful model for understanding basic cell biology. This study compares the models developed by two supervised methods, such as the partial least squares-discriminant analysis (PLS-DA) and soft independent modeling of class analogy (SIMCA), using mid-infrared (MIR) spectra registered during the growth of S. cerevisiae in bioreactor. The spectra were analyzed using the principal component analysis (PCA), with resolution in five different classes, which were well defined in terms of their biochemical parameters. The SIMCA model showed a significant fitting, 99%, validation, 98%, and prediction parameters, 97%, comparatively with PLS-DA model. Regarding accuracy, sensitivity, and specificity parameters, a value between 83% and 100% was achieved for both methods, but the SIMCA method showed significant specificity and sensitivity values, 98%-100%, representing a suitable classification tool of yeast cells. According to these results, the MIR spectra associated with chemometric tools can be considered a valued strategy for a classification and detailed analysis for an accurate control, allowing to predict the evolution of the corrected process in advance, avoiding losses of time and costs associated with new fermentations, identifying a significant number of samples in any biotechnological process.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationSAMPAIO, Pedro Sousa; CALADO, Cecília R. C. – Comparison of partial least squares-discriminant analysis and soft independent modeling of class analogy methods for classification of Saccharomyces cerevisiae cells based on mid-infrared spectroscopy. Journal of Chemometrics. ISSN 0886-9383. Vol. 35, N.º 5 (2021), pp. 1-13pt_PT
dc.identifier.doi10.1002/cem.3340pt_PT
dc.identifier.eissn1099-128X
dc.identifier.issn0886-9383
dc.identifier.urihttp://hdl.handle.net/10400.21/13223
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherWileypt_PT
dc.relation.publisherversionhttps://analyticalsciencejournals.onlinelibrary.wiley.com/doi/epdf/10.1002/cem.3340pt_PT
dc.subjectChemometricspt_PT
dc.subjectMid-infrared spectroscopypt_PT
dc.subjectPartial least squares-discriminant analysispt_PT
dc.subjectPrincipal component analysispt_PT
dc.subjectSoft independent modeling of class analogiespt_PT
dc.titleComparison of partial least squares-discriminant analysis and soft independent modeling of class analogy methods for classification of Saccharomyces cerevisiae cells based on mid-infrared spectroscopypt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage13pt_PT
oaire.citation.issue5
oaire.citation.startPage1pt_PT
oaire.citation.titleJournal of Chemometricspt_PT
oaire.citation.volume35
person.familyNameSampaio
person.familyNameCalado
person.givenNamePedro
person.givenNameCecília
person.identifier1251979
person.identifier130332
person.identifier.ciencia-idAF12-6ABA-43D8
person.identifier.ciencia-id9418-E320-3177
person.identifier.orcid0000-0003-2917-4904
person.identifier.orcid0000-0002-5264-9755
person.identifier.ridE-2102-2014
person.identifier.scopus-author-id24178064100
person.identifier.scopus-author-id6603163260
rcaap.rightsclosedAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication303f3e22-ec1a-4243-9ded-98c647776e6a
relation.isAuthorOfPublicatione8577257-c64c-4481-9b2b-940fedb360cc
relation.isAuthorOfPublication.latestForDiscoverye8577257-c64c-4481-9b2b-940fedb360cc

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