2006
DOI: 10.1007/s00216-006-0355-z
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Parallel factor analysis combined with PLS regression applied to the on-line monitoring of Pichia pastoris cultures

Abstract: Various key variables (biomass, substrate and product) of bioprocesses should be monitored in order to retrieve useful information on the system, with the biomass (the cell density) the principal target. Although several analytical methods have been adapted and used to monitor the evolution of cell density evolution in cultures, a general method for performing this determination has not yet been established, as each technique has its own advantages and drawbacks. In the present work, noninduced glycerol batch … Show more

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Cited by 31 publications
(22 citation statements)
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“…In such cases, multivariate chemometric techniques can be used to analyze the whole spectra. Principal components analysis (PCA) is normally employed to compress noisy and correlated data sets with minimal loss of information (Boehl et al, 2003;Surribas et al, 2006a;Haack et al, 2007;Rhee and Kang, 2007;Wolf et al, 2007). Partial least squares (PLS) regression appears to be the most popular chemometric method for calibrating 2D fluorescence maps with off-line bioprocess variables such as biomass, substrates and products of interest (Boehl et al, 2003;Lantz et al, 2006;Surribas et al, 2006b;Haack et al, 2007;Rhee and Kang, 2007).…”
Section: Introductionmentioning
confidence: 99%
“…In such cases, multivariate chemometric techniques can be used to analyze the whole spectra. Principal components analysis (PCA) is normally employed to compress noisy and correlated data sets with minimal loss of information (Boehl et al, 2003;Surribas et al, 2006a;Haack et al, 2007;Rhee and Kang, 2007;Wolf et al, 2007). Partial least squares (PLS) regression appears to be the most popular chemometric method for calibrating 2D fluorescence maps with off-line bioprocess variables such as biomass, substrates and products of interest (Boehl et al, 2003;Lantz et al, 2006;Surribas et al, 2006b;Haack et al, 2007;Rhee and Kang, 2007).…”
Section: Introductionmentioning
confidence: 99%
“…To determine the number of components, various numerical characteristics of the model can be used e.g. explained variance (%) (Surribas et al, 2006) and core consistency (corcondia) (%) (Divya and Mishra, 2007) -ideally, both values are 100 %. The results of PARAFAC modelling are relative concentrations (score) and spectral profiles (loadings) of components in the samples (Bro 1997).…”
Section: Multivariate Analysismentioning
confidence: 99%
“…Excitation and emission profiles can be assigned to fluorophores by comparison with recorded spectra of standards or with data reported in literature. Score values can be used to construct the calibration model describing the relationship between the concentration of the fluorophore and the score value (Surribas et al, 2006). In this work, PLS−regression was used.…”
Section: Multivariate Analysismentioning
confidence: 99%
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“…[20][21][22][23] However, this methodology was not employed to directly link the spectral resolution information to a biosynthetic pathway. Therefore, this is a new and complementary approach for the initial analysis of the biosynthesis of fluorescent natural products.…”
Section: Introductionmentioning
confidence: 99%