Mahler Lukas, Tasdemir Ebru, Nickisch-Hartfiel Anna, Mayer Christian, Jaeger Martin
Department of Physical Chemistry, University Duisburg-Essen, Essen, North Rhine-Westphalia, Germany.
Department of Chemistry and ILOC, Niederrhein University of Applied Sciences, Krefeld, North Rhine-Westphalia, Germany.
Biotechnol Bioeng. 2025 Mar;122(3):561-569. doi: 10.1002/bit.28901. Epub 2024 Dec 10.
The concept of sustainable production necessitates the utilization of waste and by-products as raw materials, the implementation of biotechnological processes, and the introduction of automated real-time monitoring for efficient use of resources. One example is the biocatalyzed conversion of the reusable by-product glycerin by acetic acid bacteria to dihydroxyacetone (DHA), which is of great importance to the cosmetic industry. The application of compact spectrometers enables the rapid measurement of samples while simultaneously reducing the consumption of resources and energy. Yet, this approach requires comprehensive data preprocessing and, on occasion, multivariate data analysis. For the process monitoring of the production of DHA, a low-field H nuclear magnetic resonance (NMR) spectrometer was implemented in on-line mode. Small-volume samples were taken from a bypass and transferred to the spectrometer by an autosampler. Complete analysis within minutes allowed real-time process control. To this purpose, reliable automated spectral preprocessing preceded the creation of a univariate model. The model enabled the acquisition of process knowledge from chemical kinetics and facilitated the tracking of both substrate and product concentrations, requiring independent calibration. As a second multivariate approach, principal component analysis was utilized to monitor the process in a semi-quantitative manner without the necessity for calibration. The results of this study are beneficial for real-time monitoring applications with the objective of exerting control over the process in question while minimizing expenditure.
可持续生产的概念要求将废物和副产品用作原材料，实施生物技术工艺，并引入自动化实时监测以有效利用资源。一个例子是利用醋酸菌将可重复使用的副产品甘油生物催化转化为二羟基丙酮（DHA），这对化妆品行业非常重要。紧凑型光谱仪的应用能够快速测量样品，同时减少资源和能源消耗。然而，这种方法需要全面的数据预处理，有时还需要进行多变量数据分析。为了对DHA生产过程进行监测，采用了低场H核磁共振（NMR）光谱仪进行在线模式。从小旁路采集小体积样品，并通过自动进样器将其转移到光谱仪中。几分钟内即可完成完整分析，从而实现实时过程控制。为此，在创建单变量模型之前进行了可靠的自动光谱预处理。该模型能够从化学动力学中获取过程知识，并有助于跟踪底物和产物浓度，这需要进行独立校准。作为第二种多变量方法，主成分分析被用于以半定量方式监测过程，而无需校准。本研究结果有利于实时监测应用，旨在对相关过程进行控制，同时尽量减少支出。
