Tosi Simona, Rossi Maddalena, Tamburini Elena, Vaccari Giuseppe, Amaretti Alberto, Matteuzzi Diego
Chemistry Department, University of Ferrara, Via L. Borsari, 46, 44100 Ferrara, Italy.
Biotechnol Prog. 2003 Nov-Dec;19(6):1816-21. doi: 10.1021/bp034101n.
The application of NIR in-line to monitor and control fermentation processes was investigated. Determination of biomass, glucose, and lactic and acetic acids during fermentations of Staphylococcus xylosus ES13 was performed by an interactance fiber optic probe immersed into the culture broth and connected to a NIR instrument. Partial least squares regression (PLSR) calibration models of second derivative NIR spectra in the 700-1800 nm region gave satisfactory predictive models for all parameters of interest: biomass, glucose, and lactic and acetic acids. Batch, repeated batch, and continuous fermentations were monitored and automatically controlled by interfacing the NIR to the bioreactor control unit. The high frequency of data collection permitted an accurate study of the kinetics, supplying lots of data that describe the cultural broth composition and strengthen statistical analysis. Comparison of spectra collected throughout fermentation runs of S. xylosus ES13, Lactobacillus fermentum ES15, and Streptococcus thermophylus ES17 demonstrated the successful extension of a unique calibration model, developed for S. xylosus ES13, to other strains that were differently shaped but growing in the same medium and fermentation conditions. NIR in-line was so versatile as to measure several biochemical parameters of different bacteria by means of slightly adapted models, avoiding a separate calibration for each strain.
研究了近红外在线监测和控制发酵过程的应用。通过将浸入培养液中的交互光纤探头连接到近红外仪器，对木糖葡萄球菌ES13发酵过程中的生物量、葡萄糖、乳酸和乙酸进行了测定。700 - 1800 nm区域的二阶导数近红外光谱的偏最小二乘回归（PLSR）校准模型为所有感兴趣的参数（生物量、葡萄糖、乳酸和乙酸）提供了令人满意的预测模型。通过将近红外与生物反应器控制单元连接，对分批、重复分批和连续发酵进行了监测和自动控制。高频数据采集允许对动力学进行准确研究，提供了大量描述培养液成分的数据并加强了统计分析。对木糖葡萄球菌ES13、发酵乳杆菌ES15和嗜热链球菌ES17整个发酵过程中收集的光谱进行比较，结果表明，为木糖葡萄球菌ES13开发的独特校准模型成功扩展到了其他形状不同但在相同培养基和发酵条件下生长的菌株。近红外在线技术非常通用，通过稍微调整模型就可以测量不同细菌的多个生化参数，避免了对每个菌株进行单独校准。
