Abstract
Accurate real-time process control is necessary to increase process efficiency, and optical sensors offer a competitive solution because they provide diverse system information in a noninvasive manner. We used an innovative scattered light sensor for the online monitoring of biomass during lactic acid production in a membrane bioreactor system because biomass determines productivity in this type of process. The upper limit of the measurement range in fermentation broth containing Bacillus coagulans was ~2.2 g·L−1. The specific cell growth rate (µ) during the exponential phase was calculated using data representing the linear range (cell density ≤ 0.5 g·L−1). The results were consistently and reproducibly more accurate than offline measurements of optical density and cell dry weight, because more data were gathered in real-time over a shorter duration. Furthermore, µmax was measured under different filtration conditions (transmembrane pressure 0.3–1.2 bar, crossflow velocity 0.5–1.5 m·s−1), showing that energy input had no significant impact on cell growth. Cell density was monitored using the sensor during filtration and was maintained at a constant level by feeding with glucose according to the fermentation kinetics. Our novel sensor is therefore suitable for integration into control strategies for continuous fermentation in membrane bioreactor systems.
Highlights
Bioprocess control is integral to modern biotechnology because it can improve reproducibility and system stability while reducing operating costs
Our study has confirmed that the novel AFG scattered light sensor is suitable for the online monitoring and control of Lactic acid (LA) production in a membrane bioreactor (MBR) system
The linear correlation between the optical signal and the biomass concentration at values up to ~0.4 g L1 allows the quantitative determination of cell growth rates using the data from the AFG sensor
Summary
Bioprocess control is integral to modern biotechnology because it can improve reproducibility and system stability while reducing operating costs. Real-time process monitoring using sensor techniques facilitates bioprocess control by providing system information during the process, which can be used to regulate the corresponding system output. In addition to conventional sensors, optical sensors are competitive candidates for bioprocess control. In contrast to conventional offline measurement, online bioprocess monitoring using optical sensors is a noninvasive and nondestructive approach that does not interfere with cell metabolism and does not require periodic sampling, reducing the risk of contamination [8,9]. Optical sensors must meet the specific requirements for each process, e.g., target parameters, data frequency, calibration, linearity, measurement range and longevity. Optical sensors must overcome challenges specific to individual processes, such as the fouling of optical surfaces by the adhesion of microorganisms and/or proteins, and interference caused by medium components or gas bubbles. The appropriate sensor must be selected and characterized according to the process to ensure accurate measurement
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