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

开发基于光谱的生物过程监测和生物产品表征方法

• 批准号: RGPIN-2016-03786
• 负责人: Legge, Raymond
• 金额: $ 2.4万
• 依托单位: University of Waterloo
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2016
• 资助国家: 加拿大
• 起止时间: 2016-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=614631
• 关键词: Development; Spectroscopically; based; Approaches; Bioprocess

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.

在工业保护中监测各种参数的能力，质量不适，最终在生物过程中降低成本。为了“破译”的数据，我们选择了对型号的信息通过写出的样本分析分析分析和对粉末样品的一些荧光，用于生产蛋白质并从铣削的农业材料中淀粉淀粉，由于对Bean或脉冲蛋白的兴趣在最近的一年中增加了这种新颖的方法，因为最近一年的兴趣增加了，因为它的兴趣增加了这些来源在这里是脂肪的，并有帮助的蛋白质的额外好处，以帮助加拿大的工业用途。为了产生价值果实，是为了损失大量的经济机会和工作的融合方法。 这项旨在开发数据收集和处理的方法，并将其用于饮用水处理的自然物质和风暴事件的影响。要查看基于信息的可能的策略，可以将两个传感器与可用的融合信息相结合，并恢复重要的参数（例如，生产力，Geno -and to to tosections，Geno and Geno and thenotoxics and theTotoxics and thenotoxics and thentotoxics and污染事件）及时在饮用水中调节和监视这些产品。