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: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=684652
• 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.***

监控工业过程中的各种参数的能力可以提高产品质量、过程效率和可持续性，并最终降低成本。在生物过程中，产品的复杂性给过程监控带来了许多挑战。其中包含化学信息以及与产品功能相关的信息。收集此复杂数据集后的部分挑战是“破译”数据以提供有关感兴趣变量的信息。破译是通过应用来完成的。我们选择了两种光学和统计工具。我们将把我们在液体样品分析和荧光分析方面的成功扩展到粉末样品，重点是为生产富含蛋白质和淀粉的新型无溶剂分离工艺。近年来，人们对豆类或豆类蛋白质的兴趣大幅增加，因为这些来源脂肪含量低，而且传统加工方法是水和蛋白质，因此探索这种新方法的动力有很多。活力密集，因此无溶剂工艺可提高可持续性，并具有帮助保留提取蛋白质的天然功能的额外好处，从而扩大了潜在的替代工业用途的范围。油籽，但很少对这些原材料进行二次加工以生产更高价值的部分，从而导致大量经济机会和就业发展的损失。拟议的研究旨在研究一种将多个传感器的数据与该过程融合的新方法。案例研究的结果将是一个优化的过程。以及一套技术，使我们能够确定产品的可能的替代工业应用。****该研究将扩展到开发一种数据收集和处理的在线方法，并应用于天然有机物（NOM）因为它与饮用水处理有关，气候变化和风暴事件的影响引起了人们对更好的工具的兴趣，这些工具可以监测对原水的影响，并寻找基于信息的可能的控制策略，而不是完全基于专家的结合。两个传感器将增加可用化学信息的数量，并允许与重要参数相关联重大健康问题（例如消毒副产物、基因和细胞毒性以及污染事件）。这项研究将影响我们及时监管和监测饮用水中这些产品的新要求的能力。***