Development of Spectroscopically-based Approaches for Bioprocess Monitoring and Bioproduct Characterization

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The ability to monitor various parameters in an industrial process enables improvements in product quality, process efficiency, sustainability and, ultimately, to reduce costs. In bioprocesses, the complex nature of the products presents numerous challenges for process monitoring. Optical sensors can capture data, which contains chemical information and, information related to product functionality. Part of the challenge after collection of this complex data set is to “decipher” the data to provide the information on the variable(s) of interest. Deciphering is accomplished through the application of mathematical and statistical tools. We have chosen two optical sensor techniques, fluorescence and near infrared (NIR) spectroscopy. We will extend our success with liquid sample analysis and fluorescence to powder samples, with a focus on a novel, solvent-free separation process developed for the production of protein- and starch-enriched fractions from milled agricultural material, e.g. bean flour. There are numerous incentives to exploring this novel approach, as interest in bean or pulse proteins has increased substantially in recent years, as these sources are low in fat and excellent nutritionally. Conventional processes are water and energy intensive, so a solvent-free process offers improvements in sustainability, with the additional benefit of helping to preserve the native functionality of the extracted proteins; thus expanding the roster of potential alternate industrial uses. Canada's agriculture sector is known for its export of pulses and oilseeds, but little secondary processing of these raw materials to produce higher value fractions is conducted resulting in loss of significant economic opportunities and job development. The proposed research aims to examine a novel approach of fusing the data from multiple sensors with this process, as a case study. The outcome will be an optimized process and a suite of techniques, allowing us to identify possible, alternate industrial applications of the products.****The research will be extended to develop an on-line approach of data collection and processing, with application to natural organic matter (NOM) as it relates to drinking water treatment. The effects of climate change and storm events are driving an interest in better tools for monitoring the impact on raw water and for looking at possible control strategies that are information based, rather than exclusively expert based. Combining the two sensors will enhance the amount of chemical information available and allow correlation with important parameters of significant health concern, (e.g. disinfection by-products, geno- and cytotoxicity and contamination events). This research will impact our ability to conform or comply with emerging requirements for regulating and monitoring these products in drinking water in a timely fashion.***