In a complete fermentation engineering experiment, real-time monitoring of key metabolic products (such as lysine and glucose) is essential for effective process control and optimization. During the three-day fermentation cycle, samples are collected and analyzed every four hours to determine the concentration of the target metabolites.

Traditional methods rely on manual operations, including sampling, filtration, dilution, and mixing with buffer solutions, followed by enzyme electrode measurements. This process is labor-intensive, complex, and difficult to automate, making continuous monitoring and precise process regulation challenging.

To address these limitations, we designed and constructed a low-cost, fully automated system for scheduled sampling and concentration analysis based on an ESP32 microcontroller. The system can automatically and quantitatively sample from the fermenter according to a predefined program, perform on-line filtration and dilution, and deliver the processed sample to a detection chamber equipped with enzyme electrodes for concentration measurement.

All measurement data are transmitted in real time via Wi-Fi to a local server, where users can remotely configure system parameters, visualize real-time data, and download historical records through a web interface. This design enables the digitalized and unmanned monitoring of the fermentation process, laying the foundation for intelligent bioprocess control.

The automatic quantitative sampling device consists of three main hardware modules:

①Main control and communication module: Responsible for coordinating fluidic operations, processing sensor data, and communicating with the local server.

②Fluidic processing module: Enables quantitative sampling, dilution, and mixing of the sample with buffer solution through precise flow control.

③Sensor processing module: Supports accurate sampling within the quantitative loop and real-time reading of analyte concentrations via enzyme electrodes.

In the co-production process of cadaverine and succinate, achieving real-time and accurate monitoring of key metabolic product concentrations is crucial for improving experimental precision and optimizing fermentation performance. The primary metabolites involved—lysine and succinate—undergo dynamic concentration changes that directly affect product yield and by-product formation.

However, conventional detection methods rely on manual sampling, sample dilution, and chemical or chromatographic analyses, which are labor-intensive and time-consuming. These limitations make it impossible to achieve direct, automated, and real-time monitoring within the fermenter.

To address this challenge, the present project aims to develop a high-efficiency, reliable automatic sampling device. The system is designed to:

1.Automatically collect fermentation samples at predefined time intervals or under specific process conditions;

2.Perform automated dilution according to the expected concentration ranges of different metabolites;

3.Ensure high precision and reproducibility throughout the sampling process;

4.Minimize manual intervention to realize fully autonomous online monitoring.

By integrating these capabilities, the device will significantly improve the reliability and temporal resolution of metabolic data acquisition, providing a robust foundation for subsequent process optimization, dynamic regulation, and data-driven control of the fermentation system.

We developed an automated system integrating quantitative sampling and dilution functionalities to enable online monitoring of target metabolite concentrations. The apparatus is constructed using peristaltic pumps, multi-port solenoid valves, and an ultrafiltration membrane, providing capabilities for sampling, filtration, precise quantification, dilution, and cleaning.

The operational workflow is as follows: the peristaltic pump withdraws fermentation broth, which passes through the ultrafiltration membrane to remove microbial cells and particulate impurities before entering the quantitative loop. Upon detection of a full liquid level by the integrated sensor, the system automatically actuates the valves, transferring the sample into the dilution chamber to complete quantitative sampling. Subsequently, sterile water is introduced for dilution, and sterile air is applied to ensure thorough mixing. The diluted sample is then re-quantified in the loop and conveyed by the peristaltic pump to the analytical module for measurement.

To ensure continuity and reproducibility of operations, the system incorporates an automated cleaning protocol: residual liquid in the dilution chamber is rapidly discharged after each sampling cycle, and the chamber walls are flushed with clean water, effectively preventing cross-contamination.

The system integrates online filtration, quantitative sampling, and automated dilution units, offering the following advantages:

1.The sampling and dilution processes are precisely controllable, ensuring high data consistency;

2.The ultrafiltration membrane effectively removes microbial cells and impurities, enhancing detection accuracy;

3.Equipped with automatic liquid discharge and cleaning mechanisms, facilitating repeated use;

4.The overall design is compact and highly automated, making it suitable for continuous online sampling and analysis during fermentation processes in laboratory settings.

After obtaining the diluted sample, accurate detection of the target metabolite concentrations is required. Enzyme electrode sensors necessitate thorough mixing of the sample with buffer solution to ensure stable electrochemical signals and measurement accuracy. Therefore, the system incorporates a dedicated reaction chamber capable of both accommodating the enzyme sensor and achieving efficient liquid-phase mixing.

The chamber is fabricated in-house using 3D printing with waterproof materials, providing good corrosion resistance and sealing performance. The bottom of the chamber features two independent inlets for the introduction of diluted sample and buffer solution, ensuring controlled and uniform fluid entry, while the top includes a discharge outlet for efficient removal of waste liquid.

On the side of the chamber, a concentration sensor based on enzyme membrane decomposition principles is installed to process the sample and measure the electrical signal in real time, thereby obtaining metabolite concentration information. Additionally, a magnetic stirring system is integrated at the bottom of the chamber to promote efficient mixing of the sample and buffer during measurement, ensuring the stability and reliability of sensor readings.

This design not only enables precise handling and measurement of the sample but also provides a key hardware foundation for automated online monitoring, making it broadly applicable for dynamic monitoring and process optimization of target metabolites during fermentation.

Through fluid dynamics simulations and related experiments, the inlet and outlet channel layout, as well as the coupling between the stirring and sensing components, were optimized to achieve a balance between mass transfer efficiency and flow field stability.

Simulation results indicate that the chamber exhibits uniform and high turbulent kinetic energy, an enhanced mass transfer coefficient compared with conventional designs, and a velocity uniformity coefficient of 0.82, with no significant dead zones, demonstrating excellent mixing performance. Furthermore, the fluidic characteristics are highly compatible with the enzyme membrane decomposition-based detection principle, ensuring the accuracy of lysine and glucose measurements (RSD < 2%) and a response time of less than 30 s, fully meeting laboratory-scale detection requirements.

For optimal performance, it is recommended to maintain a stirring speed of 500-800 r/min (corresponding to Re_m = 2250-3600) and an inlet flow rate of 1-2 mL/min (corresponding to channel Re = 600-1200).

The sensor's working electrode is immobilized with a specific enzyme membrane, such as lysine oxidase. When the target substrate (lysine) contacts the enzyme membrane, it undergoes a catalyzed oxidation reaction, which can be summarized as: $$\text{Lysine} + O_2 + H_2O \rightarrow \alpha\text{-ketoadipic acid semialdehyde} + NH_3 + H_2O_2$$

This reaction consumes oxygen and produces hydrogen peroxide (H₂O₂), providing the primary signal for subsequent electrochemical detection.

The produced H₂O₂ diffuses to the electrode surface and undergoes oxidation under a constant anodic potential (typically +0.6 to +0.7 V vs. Ag/AgCl):$$H_2O_2\to O_2+2H^++2e^-$$

This electron transfer generates a small current, the magnitude of which is proportional to the H₂O₂ concentration. Since the H₂O₂ concentration is directly determined by the enzymatic reaction rate, and the reaction rate is linearly proportional to the substrate concentration [S] within a certain range, the measured current can be considered a direct reflection of the substrate concentration.

The dose-response relationship of the sensor can be described using a Michaelis-Menten-type equation:$$I=\frac{I_{\mathrm{max}}\times[S]}{K_{M}^{\prime}+[S]}$$

where III is the steady-state current, \(I_\text{max}\) is the maximum saturation current, [S]is the substrate concentration, and \({K}^{,}\) is the apparent Michaelis constant. In the low-concentration region (\([S] \ll K'_M\)), this relationship can be approximated as linear:$$I=k\times[S]$$

where \({k}\) is the sensor sensitivity coefficient, ensuring that trace levels of substrate can be accurately detected.

Since the current generated by the electrochemical reaction is extremely weak (typically at the nA level), the system incorporates a transimpedance amplifier-based signal conditioning circuit to convert the microcurrent proportionally into a measurable voltage signal. The voltage signal is then digitized by the ADC embedded in the ESP32 main controller, enabling high-precision, real-time calculation of metabolite concentrations.

This workflow ensures efficient, reliable, and reproducible transduction from enzymatic reaction to digital output, providing a robust technical foundation for real-time monitoring of critical metabolites, such as lysine, during laboratory-scale fermentation processes.

To enable automated flow control and fail-safe monitoring, a low-cost, highly reliable liquid presence sensor (Figure 10) was developed in-house. The sensor functions as a resistive detector: in air, the resistance between the metal probes is effectively infinite, whereas when a liquid (aqueous solution) passes through, its conductivity lowers the resistance significantly, allowing detection of liquid presence.

In the quantitative sampling process, the liquid presence sensor plays a critical role in level detection. During operation, the pump first draws liquid into the quantitative loop. Once the loop is filled, the sensor detects the presence of liquid, causing a significant change in the output signal, indicating that the liquid has reached the desired level. At this point, the system automatically switches the solenoid valve pathway, pumping the liquid out of the quantitative loop to achieve precise volumetric sampling.

The liquid presence sensor offers the advantages of low cost and rapid response. Additionally, the current passing through the sensor is extremely small, ensuring that it does not interfere with subsequent enzyme electrode measurements or other detection steps, thereby maintaining the stability and reliability of the entire automated sampling and analysis system.