Multi-analyte quantification in bioprocesses by FTIR spectroscopy using Partial Least Squares Regression and Multivariate Curve Resolution

KOCH C; POSCH A; GOICOECHEA HC; HERWIG C; LENDL B

ANALYTICA CHIMICA ACTA

ELSEVIER SCIENCE BV

Lugar: Amsterdam; Año: 2014 vol. 807 p. 103 - 110

0003-2670

This paper presents the quantification of Penicillin V and phenoxyacetic acid, a precursor, inline 14 during Pencillium chrysogenum fermentations by FTIR spectroscopy and Partial Least Squares (PLS) 15 Regression and Multivariate Curve Resolution ? Alternating Least Squares (MCR-ALS). First, the 16 applicability of an attenuated total reflection FTIR fiber optic probe was assessed offline by 17 measuring standards of the analytes of interest and investigating matrix effects of the fermentation 18 broth. Then measurements were performed inline during four fed-batch fermentations with online 19 HPLC for the determination of Penicillin V and phenoxyacetic acid as reference analysis. PLS and 20 MCR-ALS models were built using these data and validated by comparison of single analyte spectra 21 with the selectivity ratio of the PLS models and the extracted spectral traces of the MCR-ALS models, 22 respectively. The achieved root mean square errors of cross-validation for the PLS regressions were 0.22 g L-1 for Penicillin V and 0.32 g L-1 23 for phenoxyacetic acid and the root mean square errors of prediction for MCR-ALS were 0.23 g L-1 for Penicillin V and 0.15 g L-1 24 for phenoxyacetic acid. A general 25 work-flow for building and assessing chemometric regression models for the quantification of 26 multiple analytes in bioprocesses by FTIR spectroscopy is given.