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Development and testing of mid-infrared sensors for in-line process monitoring in biotechnology

机译:开发和测试用于生物技术在线过程监控的中红外传感器

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Three prototypes of mid-infrared (MIR) spectrometric sensor systems for simultaneous monitoring of ethanol and carbohydrates (in the present case glucose and fructose) in the course of biotechnological processes have been constructed based on recent developments in pyroelectric detection and fiber photonics. The sensors utilized were a grating spectrometer or a Fabry-Perot interferometer adjusted for the detection of analytes' characteristic absorbance bands in the spectral region of "fingerprints" between 1050 and 950 cm~(-1). The measurements were performed with an attenuated total reflection (ATR) probe connected to the spectrometer by a polycrystalline infrared fiber (PIR). Two probes with different ATR elements were tested: with a diamond crystal (for both spectrometers) and with a detachable PIR loop head (for grating spectrometer). The sensor performances were assessed and compared using partial least-squares (PLS) regression modeling and prediction statistics for two designed sample sets of binary ethanol-glucose and glucose-fructose aqueous solutions. The models based on the FT-1R spectroscopic analysis of the same designed samples using a diamond ATR probe (a "gold standard" method) were used as a benchmark. The system based on a grating spectrometer connected to an ATR probe with a PIR loop head was additionally tested under the process conditions of Saccharomyces cerevisiae fermentation. The resulting root mean-square errors of prediction were 4.74 and 13.33 g/L, for ethanol and glucose models, respectively. Simultaneously, NIR spectroscopy in the range 1100-2100 nm was used both for the analysis of designed samples and for the fermentation process monitoring. In the latter case a biomass content prediction model has been built along with those for ethanol and glucose. All tested full-spectroscopic and sensor-based methods of analysis have been compared and their practical applications discussed.
机译:基于热电检测和光纤光子学的最新发展,已构建了三个中红外(MIR)光谱传感器系统原型,用于在生物技术过程中同时监控乙醇和碳水化合物(在当前情况下为葡萄糖和果糖)。所使用的传感器是光栅光谱仪或Fabry-Perot干涉仪,该传感器经过调整,可检测1050至950 cm〜(-1)之间“指纹”的光谱区域中的分析物特征吸收带。使用通过多晶红外光纤(PIR)连接到光谱仪的衰减全反射(ATR)探头进行测量。测试了两种具有不同ATR元素的探头:带有钻石晶体(用于两个光谱仪)和可拆卸PIR回路头(用于光栅光谱仪)。使用部分最小二乘(PLS)回归建模和预测统计量对两种设计的二元乙醇-葡萄糖和葡萄糖-果糖水溶液样品集进行了传感器性能评估和比较。使用基于钻石ATR探针(“金标准”方法)对相同设计样品进行FT-1R光谱分析的模型作为基准。在啤酒酵母发酵的工艺条件下,还额外测试了基于光栅光谱仪的系统,该系统连接到带有PIR回路头的ATR探头。对于乙醇和葡萄糖模型,所得的预测均方根误差分别为4.74和13.33 g / L。同时,NIR光谱在1100-2100 nm范围内用于设计样品的分析和发酵过程的监测。在后一种情况下,已经建立了生物质含量预测模型以及乙醇和葡萄糖的预测模型。比较了所有经过测试的全光谱和基于传感器的分析方法,并讨论了它们的实际应用。

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