Comparison of Raman and Mid-Infrared Spectroscopy for Real-Time Monitoring of Yeast Fermentations: A Proof-of-Concept for Multi-Channel Photometric Sensors

Abstract

Raman and mid-infrared (MIR) spectroscopy are useful tools for the specific detection of molecules, since both methods are based on the excitation of fundamental vibration modes. In this study, Raman and MIR spectroscopy were applied simultaneously during aerobic yeast fermentations of Saccharomyces cerevisiae. Based on the recorded Raman intensities and MIR absorption spectra, respectively, temporal concentration courses of glucose, ethanol, and biomass were determined. The chemometric methods used to evaluate the analyte concentrations were partial least squares (PLS) regression and multiple linear regression (MLR). In view of potential photometric sensors, MLR models based on two (2D) and four (4D) analyte-specific optical channels were developed. All chemometric models were tested to predict glucose concentrations between 0 and 30 g L−1, ethanol concentrations between 0 and 10 g L−1, and biomass concentrations up to 15 g L−1 in real time during diauxic growth. Root-mean-squared errors of prediction (RMSEP) of 0.68 g L−1, 0.48 g L−1, and 0.37 g L−1 for glucose, ethanol, and biomass were achieved using the MIR setup combined with a PLS model. In the case of Raman spectroscopy, the corresponding RMSEP values were 0.92 g L−1, 0.39 g L−1, and 0.29 g L−1. Nevertheless, the simple 4D MLR models could reach the performance of the more complex PLS evaluation. Consequently, the replacement of spectrometer setups by four-channel sensors were discussed. Moreover, the advantages and disadvantages of Raman and MIR setups are demonstrated with regard to process implementation.

Design of a Multimodal Imaging System and Its First Application to Distinguish Grey and White Matter of Brain Tissue. A Proof-of-Concept-Study

“…In contrast, short laser wavelengths cause fluorescence signal that interferes with the Raman spectrum [24]. This is why an excitation wavelength in the red or NIR region is recommended for Raman spectroscopy of fluorescent biological material [23,25]. Another approach is the reduction of the detection volume with a confocal detection principle [18].…”

Monitoring E. coli Cell Integrity by ATR-FTIR Spectroscopy and Chemometrics: Opportunities and Caveats

“…In addition to detection of the onset of leakiness and lysis, predicting the concentrations of target analytes, such as extracellular protein or DNA, by in-line spectroscopy can facilitate advanced, model-based process control [1]. PLSR is a well-established chemometric tool for MIR spectroscopy and has been frequently used for the quantification of small organic metabolites or inorganic medium components in bioprocesses [5][6][7][8][9]. In the present study, however, PLSR performed poorly for the prediction of extracellular SpA, AP, or DNA and was therefore not found suitable for monitoring.…”

“…Many biomolecules display specific spectral features in the MIR range, particularly in the fingerprint region (900-1800 cm −1 ) [2,3]. Thus, on-line MIR spectroscopy provides valuable information for bioprocess monitoring [4], although up-stream applications have mostly been focused on the quantification of small organic metabolites or inorganic medium components so far [5][6][7][8][9]. However, the fact that the secondary structure and amino acid composition affect the protein spectrum has been exploited to distinguish the product from HCP in downstream applications [10][11][12].…”

Real-time and on-line parallel detection of key fermentation process parameters by near-infrared spectroscopy in different environments

“…Moreover, some sensors may be affected by the characteristics of strain, the rheological properties of fermentation broth, the aseptic requirement, so as the on-line detection of various substances and products in the fermentation broth cannot be realized. At present, a variety of online detection technologies have been used in microbial fermentation, including near-infrared spectroscopy, low eld nuclear magnetic technology, raman spectroscopy, viable cell sensor, electronic nose and so on (Zhao et al, 2016;Schalk et al, 2019). Wang et al, (2016) used low eld nuclear magnetism to realize real-time and accurate dynamic analysis of cellular lipids of Chlorella protothecoides.…”