Elucidating the composition profiles of alcoholic fermentations by use of ALS methodology

Alcoholic fermentation runs under Saccharomyces cerevisiae yeasts were conducted on culture medium batches containing glucose as carbon source. Spectral changes during the process were monitored in-line with a near infrared (NIR) immersion probe. Data were analysed by using a multivariate curve resolution-alternating least-squares (MCR-ALS) method. Different regions of the NIR spectrum were examined in order to ensure optimum application of the ALS algorithm and elucidation of the chemical rank for the system. The ambiguity inherent in the ALS algorithm was resolved by using various combinations of inequality and equality constraints. Some combinations were found to perform quite well in terms of explained variance and lack of fit, even in the absence of information in the form of equality constraints. The resulting model exposed a highly significant relationship between the ALS response and the reference concentration. Application of the model to alcoholic fermentation runs performed under similar conditions resulted in also similar analytical figures of merit. This allows the MCR-ALS method to be used to obtain the analyte profiles as a function of time and the spectral profiles in evolving alcoholic fermentations.