Abstract

Calibration models are generated and evaluated for the measurement of five different components in synthetic mixtures prepared in aqueous solutions. Mixtures of glucose, glutamine, ammonia, lactate, and glutamate were prepared to simulate concentration levels expected during routine bioreactor fermentation processes. Near-IR spectra were collected from these solutions over the spectral range from 5000 to 4000 cm−1. This spectral information was used to build individual multivariate calibration models for each analyte. Models were constructed on the basis of partial least-squares regression of raw and Fourier filtered absorbance spectra. Each analyte could be detected selectively with mean percent errors of prediction ranging from 4 to 8%.

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