@article{gray_peretti_lamb_2013, title={Real-time monitoring of high-gravity corn mash fermentation using in situ raman spectroscopy}, volume={110}, ISSN={["1097-0290"]}, DOI={10.1002/bit.24849}, abstractNote={In situ Raman spectroscopy was employed for real-time monitoring of simultaneous saccharification and fermentation (SSF) of corn mash by an industrial strain of Saccharomyces cerevisiae. An accurate univariate calibration model for ethanol was developed based on the very strong 883 cm(-1) C-C stretching band. Multivariate partial least squares (PLS) calibration models for total starch, dextrins, maltotriose, maltose, glucose, and ethanol were developed using data from eight batch fermentations and validated using predictions for a separate batch. The starch, ethanol, and dextrins models showed significant prediction improvement when the calibration data were divided into separate high- and low-concentration sets. Collinearity between the ethanol and starch models was avoided by excluding regions containing strong ethanol peaks from the starch model and, conversely, excluding regions containing strong saccharide peaks from the ethanol model. The two-set calibration models for starch (R(2) = 0.998, percent error = 2.5%) and ethanol (R(2) = 0.999, percent error = 2.1%) provide more accurate predictions than any previously published spectroscopic models. Glucose, maltose, and maltotriose are modeled to accuracy comparable to previous work on less complex fermentation processes. Our results demonstrate that Raman spectroscopy is capable of real time in situ monitoring of a complex industrial biomass fermentation. To our knowledge, this is the first PLS-based chemometric modeling of corn mash fermentation under typical industrial conditions, and the first Raman-based monitoring of a fermentation process with glucose, oligosaccharides and polysaccharides present.}, number={6}, journal={BIOTECHNOLOGY AND BIOENGINEERING}, author={Gray, Steven R. and Peretti, Steven W. and Lamb, H. Henry}, year={2013}, month={Jun}, pages={1654–1662} }
 @article{gray_rawsthorne_dirks_phister_2011, title={Detection and enumeration of Dekkera anomala in beer, cola, and cider using real-time PCR}, volume={52}, ISSN={["1472-765X"]}, DOI={10.1111/j.1472-765x.2011.03008.x}, abstractNote={Aims: In this article, a quantitative real-time PCR assay for detection and enumeration of the spoilage yeast Dekkera anomala in beer, cola, apple cider, and brewing wort is presented as an improvement upon existing detection methods, which are very time-consuming and not always accurate. Methods and Results: Primers were designed to exclude other organisms common in these beverages, and the assay was linear over 6 log units of cell concentrations. The addition of large amounts of non-target yeast DNA did not affect the efficiency of this assay. A standard curve of known DNA was established by plotting the Ct values obtained from the QPCR against the log of plate counts on yeast peptone dextrose medium and unknowns showed exceptional correlation when tested against this standard curve. The assay was found to detect D. anomala at levels of 10–14 CFU ml−1 in either cola or beer and at levels of 9·4–25·0 CFU ml−1 in apple cider. The assay was also used to follow the growth of D. anomala in brewing wort. Conclusions: The results indicate that real-time PCR is an effective tool for rapid, accurate detection and quantitation of D. anomala in beer, cola and apple cider. Significance and Impact of the Study: This method gives a faster and more efficient technique to screen beer, cola, and cider samples and reduce spoilage by D. anomala. Faster screening may allow for significant reduction in economic loss because of reduced spoilage.}, number={4}, journal={LETTERS IN APPLIED MICROBIOLOGY}, author={Gray, S. R. and Rawsthorne, H. and Dirks, B. and Phister, T. G.}, year={2011}, month={Apr}, pages={352–359} }