Fermentation processes are essential to produce various food products, including yogurts, beers, and more. It relies on microorganisms to carry out controlled reactions, using nutrients in the feed to for the development of versatile food products, making meticulous monitoring of fermentation processes essential to human health and safety.
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What is Spectroscopy?
Spectroscopy is defined as the study of the interaction of electromagnetic radiation or light with matter to study and reveal information at the sub-atomic level.1 During spectroscopic analysis, light is split into the spectrum of its constituent wavelengths. However, the spectrum is not just merely the splitting of light into bands of different colors; rather, each band represents a specific energy level.2
The major types of spectroscopic analysis used by food experts include Near-Infrared spectroscopy (NIR), Mid-Infrared spectroscopy (MIR), and Raman spectroscopy.
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Advantages of Spectroscopy for Fermentation Monitoring
Automated measurements and coupled control loops play a crucial role in optimizing the fermentation processes and ensuring product quality. Accurate real-time monitoring of fermentation parameters is essential for accelerating bioprocess development and ensuring an optimized shelf life of the final product.Top of FormBottom of Form
Real-time monitoring of fermentation processes through spectroscopy allows experts to capture the spectral signatures of multiple analytes within a single spectrum, enabling fast and efficient multiplexed quantification. The electromagnetic/light bands obtained as a result of the spectroscopic analysis are used by food experts to convert complex information into useful quantitative metrics essential for the control of fermentation processes.3 Furthermore, the recent trend of shifting towards data-oriented monitoring schemes has been useful in developing frameworks for predictive analytics specifically optimized for fermentation.
How Real-Time Monitoring Using Spectroscopy Works?
Real-time monitoring using spectroscopy involves the use of highly sensitive and extremely precise sensors, essential for the continuous collection of spectral data during the fermentation process. These sensors precisely detect molecular vibrations as spectral data, with each component, such as gases and dissolved analytes, exhibiting a unique spectral signature. Optimized algorithms, powered by chemometrics, analyze the spectral data to estimate concentrations of key metabolites such as sugars and organic acids. This data is used by analytics frameworks for adjusting fermentation parameters like temperature to optimize conditions. The control loop framework is key for improving consistency, and minimizing waste products leading to cost-efficient manufacturing.4, 5
Industrial Applications
Yogurt Fermentation Monitoring Using Near-Infrared Spectroscopy
The lactic fermentation of milk leads to the production of milk, involving the conversion of milk sugar-lactose into lactic acid by the lactic acid bacteria (LAB). pH is lowered during the formation of yogurt and is the most critical parameter. However, various other factors are crucial for the quality of the final product. Experts have used NIR spectroscopy to monitor the progress of yogurt formation and monitoring the coagulation of yogurt.
UHT sterilized 500 mL milk was pre-warmed to a temperature of 38 ℃. The sample was fermented at 38 ℃ with absorption spectra collected after every 15 minutes. OPUS software was used to capture spectral data.
RAW NIR absorption spectra revealed a trend of increasing absorption as the fermentation process continued. The acid coagulation of milk by LAB caused an increase in the size of casein micelles, which are phosphor-proteins present in the milk.
The real-time monitoring revealed that as the milk pH drops from 6.6 to 5.3 due to the conversion of lactose into lactic acid by LAB, calcium and phosphate are released from the casein micelles. However, the micelle diameter remains roughly the same during this stage. As the pH drops from 5.3 to 4.6, the aggregates begin to shrink, eventually forming individual casein particles alongside fat globules and whey. These newly formed structures are larger than the original casein micelles and fat globules.
The main absorbance changes observed during fermentation occur around the spectral regions of 970 nm, 1450 nm, and 1840 nm. Real-time monitoring using NIR spectroscopy revealed the process of syneresis by various peaks on the spectrum.
Syneresis is a crucial process that occurs when the gel-matrix of the yogurt can’t retain any water, leading to the separation of the liquid state. The physico-chemical changes and variations were carefully captured by the NIR spectra, making it an essential tool for monitoring the fermentation process, particularly during the formation of yogurt and cheese.6
Real-Time Monitoring in Brewing: Raman Spectroscopy for Wine Fermentation Monitoring
Experts have demonstrated the use of Raman spectroscopy for real-time monitoring of changes during wine fermentation. Wine fermentation involves the use of yeast to convert sugars into ethanol and CO2.
The Raman spectra of wine showed intense peaks around 3200 cm -1, related to water while the peaks between 1000 and 1600 cm -1 were related to CH-OH and sugars. The intense bands at 8300 cm -1 and 2950 cm -1 were observed after 1 day, which prove the presence of ethanol, and are useful to quantify the fermentation activity of yeast.
The real-time spectral data transformed by the algorithm revealed that the initial sugar concentration ranged from 50 g/L to 65 g/L. During alcoholic fermentation, yeast enzymes converted the sugar into ethanol and glycerol until the enzymes were fully used up. By the end of the process, ethanol levels reached between 11.6% v/v and 13.5% v/v, while the glycerol content was around 3% v/v.7
The readings proved that Raman spectroscopy successfully provided qualitative and quantitative information regarding sugar consumption, along with alcohol production proving itself to be a viable monitoring technology in the brewing industry.
Other Products
Additionally, experts have also used spectroscopy for the determination of glucose content and its consumption during microbial fermentation. The microbial fermentation process is essential in the biomedical fields and food industry.
The RS2000 portable spectroscopy device from JINSP was used, featuring an integrated high-performance spectrometer.
The experts have used the SO42- (1624 cm -1) response peak as the standard and by using the dimensionality reduction analysis in multi-variate analysis, they extracted the representative characteristic peaks.
During the real-time monitoring process, the standard curve was created by dividing the average value of the variable importance in projection (VIP) data from the top 10 variables by the peak height of the internal standard. This resulted in a linear correlation coefficient of r = 0.995, clearly showing the accuracy and reliability of the method.8
The spectroscopy methods are highly sensitive, accurate, and non-destructive making them a highly preferred technique. With the integration of modern rapid data-processing software, the spectroscopy processes have progressed rapidly. With the use of machine learning (ML) algorithms, exceptional insights are being extracted more rapidly, and allowing for the detection of multiple processes simultaneously.
Further Reading
- Barth, A. (2022). Introduction to Spectroscopy. Stockholm University. [Online]. Available at: https://www.su.se/polopoly_fs/1.521101.1602178917!/menu/standard/file/Introduction%20to%20Spectroscopy.pdf [Accessed on: May 03, 2025].
- Cosmos, Swinburne University of Technology. (2021). Spectroscopy: The SAO Encyclopedia of Astronomy. [Online]. Available at: https://astronomy.swin.edu.au/cosmos/*/Spectroscopy [Accessed on: May 03, 2025].
- Klaverdijk, M. et. al. (2025). Single compound data supplementation to enhance transferability of fermentation specific Raman spectroscopy models. Analytical and Bioanalytical Chemistry. 417. 1873–1884. Available at: https://doi.org/10.1007/s00216-025-05768-5
- Scarff, M. et. al. (2006). Near infrared spectroscopy for bioprocess monitoring and control: current status and future trends. Critical Reviews in Biotechnology, 26(1), 17-39. Available at: https://doi.org/10.1080/07388550500513677
- Pollard, D. et. al. (2001). Real-time analyte monitoring of a fungal fermentation, at pilot scale, using in situ mid-infrared spectroscopy. Bioprocess and Biosystems Engineering. 24. 13-24. Available at: https://doi.org/10.1007/s004490100226
- Muncan, J. et. al. (2021). Real-Time Monitoring of Yogurt Fermentation Process by Aquaphotomics Near-Infrared Spectroscopy. Sensors, 21(1). 177. Available at: https://doi.org/10.3390/s21010177
- Wang, Q. et. al. (2014). Real time monitoring of multiple components in wine fermentation using an on-line auto-calibration Raman spectroscopy. Sensors and Actuators B: Chemical, 202, 426-432. Available at: https://doi.org/10.1016/j.snb.2014.05.109
- Shuai, L. et. al. (2024). Study on Real-Time Detection of Glucose Concentration in Microbial Fermentation Process by Raman Spectroscopy. JINSP. [Online]. Available at: https://www.jinsptech.com/news/study-on-real-time-detection-of-glucose-concentration-in-microbial-fermentation-process-by-raman-spectroscopy/ [Accessed on: May 05, 202
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