Abstract

We describe the first application of dispersive Raman spectroscopy using a diode laser exciting at 780 nm and a charge-coupled device (CCD) detector to the noninvasive, on-line determination of the biotransformation by yeast of glucose to ethanol. Software was developed which automatically removed the effects of cosmic rays and other noise, normalized the spectra to an invariant peak, then removed the "baseline" arising from interference by fluorescent impurities, to obtain the "true" Raman spectra. Variable selection was automatically performed on the parameters of relevant Raman peaks (height, width, position of top and center, area and skewness), and a small subset used as the input to cross-validated models based on partial least-squares (PLS) regression. The multivariate calibration models so formed were sufficiently robust to be able to predict the concentration of glucose and ethanol in a completely different fermentation with a precision better than 5%. Dispersive Raman spectroscopy, when coupled with the appropriate chemometrics, is a very useful approach to the noninvasive, on-line determination of the progress of microbial fermentations.

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