## 4 Conclusions  
A fiber-optical Raman and an MIR-ATR spectrometer setup were used for real-time measurement of glucose, ethanol, and biomass during yeast fermentations and were compared with regard to their suitability for bioprocess monitoring. MLR and PLS regression models were developed in order to link the measured Raman intensity and MIR-ATR absorption spectra to the corresponding analyte concentrations. For both spectroscopic setups, the time-dependent concentration courses of glucose, ethanol, and biomass were registered with a temporal resolution of one minute. Raman and MIR spectroscopy exhibited similar RMSEC and RMSEP values for a given analyte and multivariate regression model. The extension of the relatively inaccurate 2D MLR models by two more channels to 4D MLR models improved the results significantly. By selecting four analyte-specific optical channels, the 4D MLR models could even reach the performance of the more complex PLS evaluation of Raman and MIR spectra.  
The evaluation of measurement data by simple MLR models allows simulating the analytical performance (RMSEC, RMSEP) of fictive photometer setups and compact sensors with few optical channels (spectral ranges). Furthermore, it can be estimated whether miniaturized and low-priced multi-channel Raman or MIR-ATR sensors can replace spectrometers without loss of accuracy, provided that the optical performance (light intensity, detector sensitivity, etc.) of both setups is comparable. Such a mathematical procedure opens up new possibilities for cost-efficient photometric hardware concepts. Instead of the common, but expensive Raman spectrometer systems with Peltier-cooled CCD-lines, appropriate filter units in the respective wavenumber ranges in combination with single detectors such as avalanche photodiodes (APDs) or multi-pixel photon counters (MPPCs) can be established. A Raman sensor based on MPPCs was developed by [PERSON] et al. [47] for applications in explosive atmospheres. This photometric sensor is designed for only two spectral ranges. To implement such a photometric sensor for fermentation monitoring, further work on extending the sensor to four channels is required. In the case of MIR spectroscopy, a four-channel MIR-ATR sensor equipped with an IR emitter as a light source, a ZnSe ATR prism, four thermopile detectors, and four optical bandpass filters has already been realized [10]. In order to monitor the diavicic yeast fermentation at lower glucose concentrations than in [21], the sensor's sensitivity and specificity should be improved.  
However, this study has shown that for Raman and MIR spectroscopy, respectively, only four optical channels and consequently simple MLR models are sufficient to monitor glucose, ethanol, and biomass during aerobic yeast fermentations under the described cultivation conditions.  
Conceptualization, R.S. and T.B.; investigation, R.S., A.H., and T.B.; methodology, R.S., G.I., and T.B.; software, G.I.; visualization, R.S. and A.H.; writing, original draft, R.S., A.H., and T.B.; writing, review and editing, F.B., M.R., N.G., and F.-J.M.  
The article processing charge was funded by the Baden-Wurttemberg Ministry of Science, Research and Culture and the Mannheim University of Applied Sciences in the funding programme Open Access Publishing.  
We gratefully acknowledge support from the Albert and Anneliese Konanz-Foundation of the Mannheim University of Applied Sciences. We would also like to thank the Institute for Technical Microbiology (Mannheim University of Applied Sciences, Germany), especially [PERSON] and [PERSON], for providing the HPLC system.  
The authors declare no conflict of interest.