Dept. of Analytical Chemistry, Institute of Chemistry, University of Campinas, Campinas, SP, Brazil.
Biotechnol Prog. 2012 Nov-Dec;28(6):1598-604. doi: 10.1002/btpr.1615. Epub 2012 Sep 21.
This work presents the use of Raman spectroscopy and chemometrics for on-line control of the fermentation process of glucose by Saccharomyces cerevisiae. In a first approach, an on-line determination of glucose, ethanol, glycerol, and cells was accomplished using multivariate calibration based on partial least squares (PLS). The PLS models presented values of root mean square error of prediction (RMSEP) of 0.53, 0.25, and 0.02% for glucose, ethanol and glycerol, respectively, and RMSEP of 1.02 g L(-1) for cells. In a second approach, multivariate control charts based on multiway principal component analysis (MPCA) were developed for detection of fermentation fault-batch. Two multivariate control charts were developed, based on the squared prediction error (Q) and Hotelling's T(2) . The use of the Q control chart in on-line monitoring was efficient for detection of the faults caused by temperature, type of substrate and contamination, but the T(2) control chart was not able to monitor these faults. On-line monitoring by Raman spectroscopy in conjunction with chemometric procedures allows control of the fermentative process with advantages in relation to reference methods, which require pretreatment, manipulation of samples and are time consuming. Also, the use of multivariate control charts made possible the detection of faults in a simple way, based only on the spectra of the system.
本工作介绍了拉曼光谱和化学计量学在在线控制酿酒酵母葡萄糖发酵过程中的应用。在第一种方法中,使用基于偏最小二乘(PLS)的多元校正实现了对葡萄糖、乙醇、甘油和细胞的在线测定。PLS 模型对葡萄糖、乙醇和甘油的预测均方根误差(RMSEP)值分别为 0.53、0.25 和 0.02%,对细胞的 RMSEP 值为 1.02 g L(-1)。在第二种方法中,基于多向主成分分析(MPCA)的多元控制图被开发用于检测发酵故障批次。基于平方预测误差(Q)和 Hotelling 的 T(2),开发了两个多元控制图。Q 控制图在在线监测中对检测由温度、底物类型和污染引起的故障是有效的,但 T(2)控制图无法监测这些故障。拉曼光谱与化学计量学程序的在线监测允许用参考方法进行发酵过程的控制,参考方法需要预处理、样品操作且耗时。此外,多元控制图的使用使得仅基于系统的光谱就可以以简单的方式检测故障。