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dc.creatorCalderon-Santoyo,Montserrat
dc.creatorChalier,Pascale
dc.creatorChevalier-Lucia,Dominique
dc.creatorGhommidh,Charles
dc.creatorRagazzo-Sanchez,Juan Arturo
dc.date2010-07-01
dc.date.accessioned2019-05-03T12:44:44Z
dc.date.available2019-05-03T12:44:44Z
dc.identifierhttps://scielo.conicyt.cl/scielo.php?script=sci_arttext&pid=S0717-34582010000400008
dc.identifier.urihttp://revistaschilenas.uchile.cl/handle/2250/85137
dc.descriptionAn electronic nose (E-nose) coupled to gas chromatography was tested to monitor alcoholic fermentation by Saccharomyces cerevisiae ICV-K1 and Saccharomyces cerevisiae T306, two strains well-known for their use in oenology. The biomass and ethanol concentrations and conductance changes were measured during cultivations and allowed to observe the standard growth phases for both yeast strains. The two strains were characterized by a very similar tendency in biomass or ethanol production during the fermentation. E-nose was able to establish a kinetic of the production of aroma compounds production and which was then easy to associate with the fermentation phases. Principal Component Analysis (PCA) showed that the data collected by E-nose during the fermentation mainly contained cultivation course information. Discriminant factorial analysis (DFA) was able to clearly identify differences between the two strains using the four main principal components of PCA as input data. Nevertheless, the electronic nose responses being mainly influenced by cultivation course, a specific data treatment limiting the time influence on data was carried out and permitted to achieve an overall performance of 83.5%.
dc.formattext/html
dc.languageen
dc.publisherPontificia Universidad Católica de Valparaíso
dc.rightsinfo:eu-repo/semantics/openAccess
dc.sourceElectronic Journal of Biotechnology v.13 n.4 2010
dc.subjectalcoholic fermentation
dc.subjectdiscrimination
dc.subjectelectronic nose
dc.subjectgas sensor
dc.subjectyeasts
dc.titleIdentification of Saccharomyces cerevisiae strains for alcoholic fermentation by discriminant factorial analysis on electronic nose signals


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