A method for improving the accuracy of microbial fuel cell toxicity sensing and a sensing detection system

Abstract

The application discloses a method for improving the accuracy of microbial fuel cell toxicity sensing, comprising the following steps: constructing a microbial fuel cell sensor, the sensor comprising a cathode and an anode, the anode being integrated with an ATP module and being provided with luminous bacteria; domesticating the anode biofilm, using a substrate solution with different substrate concentrations to domesticate, and obtaining a microbial fuel cell sensor with good performance after the output voltage of the sensor is stabilized; mixing a nutrient substrate and a toxicity sample to form an anode substrate of a test group, or not adding the toxicity sample to form an anode substrate of a blank group; after the electric signal is stabilized, the inhibition rate is calculated through the power generation amount per unit time, the ATP content change and the luminous intensity change, and the comprehensive inhibition rate of the toxicity sample to the microorganism is obtained through weighted calculation. The application can play a good multiple guarantee role in early warning of wastewater toxicity on electroactive microorganisms, and can avoid the alarm caused by the fluctuation of the electric signal, so that the water intake of a sewage treatment plant is stopped.

Description

Technical Field

[0001] This invention relates to the field of biosensing technology, specifically to a method and sensing system for improving the accuracy of toxicity sensing in microbial fuel cells. Background Technology

[0002] Biological treatment is currently the core technology in integrated wastewater treatment processes and a crucial step in reducing the concentration of toxic substances in wastewater. However, the efficiency of biological treatment depends on the activity of microorganisms. When wastewater contains toxic components, it can severely impact the operation of the biological treatment system, affecting the treatment effect of the wastewater treatment plant. Therefore, fast and accurate sensors are essential for the stable operation of biological treatment units.

[0003] Microbial fuel cells (MFCs) are a novel type of biosensor used to determine the inhibitory effect of wastewater on anaerobic microorganisms. They offer high sensitivity, fast detection speed, low cost, and online monitoring capabilities, showing promising application prospects. Electroactive microorganisms are highly sensitive to environmental changes. When influent contains toxic substances, the life activities of electrogenic bacteria weaken, resulting in changes in voltage or current, providing a rapid and effective indication. Wastewater containing antibiotics, organic matter, and heavy metals can inhibit microorganisms in biological treatment systems, reducing biological activity, damaging cell structure, and suppressing metabolic processes, thus affecting the effectiveness and stability of biological treatment. Therefore, scientifically and effectively assessing and controlling the toxic effects of wastewater plays a crucial role in maintaining the efficient and stable operation of integrated wastewater treatment systems. Summary of the Invention

[0004] The purpose of this invention is to provide a method and sensing system for improving the accuracy of toxicity sensing in microbial fuel cells. By utilizing a sensing technology that uses multiple signals of electro-optical-biochemical to indicate toxicity, biochemical signals, electrical signals, and optical signals that reflect microbial activity are used in concert to indicate toxicity, thereby reducing the probability of false positives in toxicity warnings, improving the accuracy of indicating toxicity by electroactive microorganisms, and making the results of toxicity evaluation using electroactive microorganisms more reliable.

[0005] To achieve the above objectives, the present invention is specifically implemented through the following technical solutions:

[0006] A method for improving the accuracy of toxicity sensing in microbial fuel cells includes the following steps:

[0007] S1. Construct a microbial fuel cell sensor, the sensor including a cathode and an anode, the anode integrating an ATP module and adding luminescent bacteria;

[0008] S2. The anode biofilm is acclimated using matrix solutions with different substrate concentrations. Once the sensor output voltage stabilizes, a high-performance microbial fuel cell sensor is obtained.

[0009] S3. Mix the nutrient matrix with the toxic substance sample to form the anode matrix of the test group, or do not add toxic substances to form the anode matrix of the blank group;

[0010] S4. After the electrical signal stabilizes, the inhibition rate is calculated by the change in electricity production per unit time, the change in ATP content, and the change in luminescence intensity. Then, the overall inhibition rate of the toxic substance on the microorganism is obtained by weighted calculation.

[0011] S5. Set an early warning level based on the comprehensive inhibition rate to guide countermeasures.

[0012] Based on the above scheme, in step S2, the matrix solution includes a buffer solution and a sodium acetate solution, and the acclimatization process is achieved by changing the matrix solution at intervals.

[0013] Based on the above scheme, in step S4, if the change in electrical signal is less than 5%, the electrical signal is considered to be stable; the formulas for calculating the inhibition rates of changes in electricity production, ATP content, and luminescence intensity are as follows:

[0014] ACIR (Accelerated Power Generation Inhibition Rate) Q ACIR Q (%) = 100×(Q nor - ) / Q nor

[0015] Among them, Qnor is the electricity generated without toxic substances. It is the amount of electricity used to measure the duration of action after the addition of toxic substances;

[0016] ATP content inhibition rate (ACIR) A ACIR A (%) = 100 × (A) nor - ) / A nor

[0017] Among them, Anor is a stable ATP content that does not contain toxic substances. It is the ATP content after the toxic substance has been added and the time of its action has elapsed;

[0018] Acrylluminance suppression ratio (ACIR) F ACIR F (%) = 100×(F nor - ) / F nor

[0019] Wherein, Fnor is the luminescence intensity without toxic substances. It is the luminescence intensity after the toxic substance has been added and the reaction time has elapsed;

[0020] Overall inhibition rate (ACIR): ACIR(%) = (ACIR) Q +ACIR A +ACIR F ) / 3.

[0021] Based on the above scheme, in step S5, the warning level includes at least three levels (ACIR1, ACIR2, ACIR3), and corresponding countermeasures for different degrees of toxicity and hazard are given according to the comparison results with the comprehensive inhibition rate.

[0022] Based on the above scheme, the anode biofilm of the microbial fuel cell sensor is achieved by inoculating a matrix solution that has been cultured for more than one year, wherein the matrix solution is a mixture of buffer solution and sodium acetate solution.

[0023] Based on the above scheme, the toxic substance sample is mixed with the nutrient matrix and used as the anode matrix of the test group, while the anode matrix of the blank group is a nutrient matrix without toxic substances.

[0024] Based on the above scheme, the ATP module is used to monitor the changes in ATP content in the anolyte biofilm in real time, and the luminescent bacteria are used to reflect microbial activity through changes in luminescence intensity.

[0025] The present invention also provides a microbial fuel cell toxicity sensing and detection system, comprising:

[0026] The cathode is made of carbon felt;

[0027] The anode is formed by carbon felt to create an anode biofilm. The anode integrates an ATP module. After the battery output voltage stabilizes, luminescent bacteria are added.

[0028] The detection device is used to monitor power generation, ATP content, and luminescence intensity.

[0029] The processing module is used to calculate the inhibition rate and set the warning level.

[0030] Based on the above scheme, the anode biofilm is obtained by domestication at different substrate concentrations. The substrate solution in the domestication process includes a buffer solution and / or sodium acetate solution. The substrate solution is replaced at intervals. When the output voltage of the microbial fuel cell sensor stabilizes, the microbial fuel cell sensor that has been successfully domesticated at low temperature is obtained.

[0031] Based on the above scheme, the processing module calculates the comprehensive inhibition rate according to the inhibition rate of power generation, ATP content and luminescence intensity, and conducts a toxicity hazard assessment based on the preset warning levels (ACIR1, ACIR2, ACIR3).

[0032] The technical solution of this invention focuses on the power generation, bioactivity, and luminescence intensity of electroactive microorganisms. After the electrical signal stabilizes, the power generation over the treatment time is recorded and the inhibition rate is calculated. Changes in ATP content over the treatment time are recorded to calculate the inhibition rate of bioactivity. Changes in the luminescence intensity of luminescent bacteria are recorded to calculate the inhibition rate. Analysis of power generation, ATP content, and luminescence intensity changes is used to jointly characterize the inhibition of microorganisms. Compared to a single indicator, this significantly improves the accuracy of toxicity early warning. This method is sensitive and reliable, providing multiple safeguards for early warning of wastewater toxicity using electroactive microorganisms, and preventing the shutdown of wastewater treatment plants due to alarms caused by fluctuations in electrical signals. Attached Figure Description

[0033] Figure 1 This is a flowchart of the method for improving the accuracy of toxicity sensing in microbial fuel cells according to the present invention;

[0034] Figure 2 This is a schematic diagram of the microbial fuel cell toxicity sensing and detection system of the present invention;

[0035] Figure 3 There are problems with using only microbial fuel cell sensors;

[0036] Figure 4 A curve for early warning of toxic substances from a multi-signal toxicity sensor system;

[0037] Figure 5 This is the real-time detection result of 2,4-dichlorophenol biotoxicity from a multi-signal toxicity sensor system.

[0038] In the diagram, 1-anode; 2-cathode; 3-ATP module; 4-ATP detection module; 5-luminescence detection module; 6-ATP detector; 7-luminescence intensity detector; 8-processing module. Detailed Implementation

[0039] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments.

[0040] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0041] like Figures 1 to 5 As shown, a method for improving the accuracy of toxicity sensing in microbial fuel cells according to the present invention includes the following steps:

[0042] S1. Construct a microbial fuel cell sensor, the sensor including a cathode and an anode, the anode integrating an ATP module and adding luminescent bacteria;

[0043] S2. The anode biofilm is acclimated using matrix solutions with different substrate concentrations. Once the sensor output voltage stabilizes, a high-performance microbial fuel cell sensor is obtained.

[0044] S3. Mix the nutrient matrix with the toxic substance sample to form the anode matrix of the test group, or do not add toxic substances to form the anode matrix of the blank group;

[0045] S4. After the electrical signal stabilizes, the inhibition rate is calculated by the change in electricity production per unit time, the change in ATP content, and the change in luminescence intensity. Then, the overall inhibition rate of the toxic substance on the microorganism is obtained by weighted calculation.

[0046] S5. Set an early warning level based on the comprehensive inhibition rate to guide countermeasures.

[0047] The microbial fuel cell of this invention includes an anode 1 and a cathode 2. The anode biofilm is acclimated at a suitable substrate concentration in the anode reaction tank of the microbial fuel cell. An ATP module 3 is installed on the anode 1. An ATP detection module 4 and a luminescence detection module 5 are installed inside the anode reaction tank. The ATP detection module 4 is connected to an ATP detector 6 outside the anode reaction tank, and the luminescence detection module 5 is connected to a luminescence intensity detector 7. The ATP detector 6 and the luminescence intensity detector 7 are respectively connected to a processing module 8. The processing module 8 obtains the ATP content change signal and the luminescence intensity change signal. The processing module 8 is connected to the anode 1 and the cathode 2 of the microbial fuel cell to detect the power generation signal of the microbial fuel cell.

[0048] After the battery output voltage stabilizes, luminescent bacteria are added, resulting in a high-performance microbial fuel cell sensor with a suitable microbial community. Once the output electrical signal of the microbial fuel cell stabilizes, it can be used for toxicity testing. After the toxicity test, the inhibition rate is calculated based on changes in power production, ATP content, and luminescence intensity to characterize the extent of microbial inhibition. The weighted calculation of the inhibition rate based on changes in power production, ATP content, and luminescence intensity over the treatment time is used to characterize the extent of damage to the microorganisms caused by the toxic substance.

[0049] In some embodiments, in step S2, the anode biofilm of the sensor is inoculated with a substrate solution that has been cultured for more than one year. The substrate solution includes a buffer solution and a sodium acetate solution. The acclimation process is achieved by changing the substrate solution at intervals. The acclimation process is as follows: the anode biofilm of the microbial fuel cell sensor is acclimated at different substrate concentrations, and the substrate solution is changed at intervals. When the output voltage of the microbial fuel cell sensor stabilizes, the microbial fuel cell sensor that has been successfully acclimated at low temperature is obtained.

[0050] In some preferred embodiments, step S3 specifically includes: adding a nutrient matrix and a toxic substance sample to a container to form a mixture, which serves as the anode matrix and is defined as the test group; and using a nutrient matrix sample without toxic substances as the anode matrix and defined as the blank group. The mixture from the above steps is connected to a pipeline and then to the anode chamber of a dual-chamber fuel cell via a peristaltic pump; the cathode matrix is ​​connected to the cathode chamber of the dual-chamber fuel cell via a peristaltic pump; the anode and cathode of the microbial fuel cell are connected to an electrical signal detection device via metal sheets, and the electrical signal detection device is connected to a computer to record changes in electrical signals for toxicity evaluation. Preferably, the electrical signal detection device is set to a constant external resistance mode; the ATP detection module is connected to the ATP detection device; and the luminescence intensity detection module is connected to the luminescence intensity detection device.

[0051] Based on the above embodiments, preferably, the anode matrix needs to be purged with nitrogen for more than 40 minutes before adding the toxic substance; more preferably, the flow rate of the peristaltic pump is 1~10 ml / min, and the microorganisms in the anode chamber are taken from bacterial solutions with a culture period of more than 1 year, to ensure that the microbial community structure of the sensor is relatively stable, which is conducive to the stability of the results of the toxicity sensor.

[0052] More preferably, in step S3, the microbial fuel cell is cultured at a constant temperature, and the electrical signal error of the microbial fuel cell is less than 5% for 3 cycles. In the toxicity test of the same batch, the performance curves of the microbial fuel cell are similar.

[0053] In some embodiments, in step S4, if the change in electrical signal is less than 5%, the electrical signal is considered to be stable, reaching the endpoint of the toxicity test calculation. After the addition of the toxic substance, if the change in electrical signal is less than 5%, the microbial biological activity is considered to be stable, reaching the endpoint of the toxicity test calculation, which is also the endpoint for calculating changes in ATP content and luminescence intensity. Further, signal stability means that the electrical signal error of the microbial fuel cell over three cycles is less than 5%.

[0054] After the electrical signal stabilized, the amount of electricity produced during the treatment time was recorded, and the inhibition rate of the electricity produced was calculated. The change in ATP content during the treatment time was also recorded, and the inhibition rate of biological activity was calculated. The changes in electricity production, ATP content, and luminescence intensity were analyzed to jointly characterize the inhibition of the microorganisms. The treatment time was calculated from the time the toxic substance was added until the change in the electrical signal was less than 5%. The electrical signal of Qnor was the same as the treatment time after the toxic substance was added.

[0055] The formulas for calculating the inhibition rates of changes in electricity production, ATP content, and luminescence intensity are as follows:

[0056] ACIR (Accelerated Power Generation Inhibition Rate) Q ACIR Q (%) = 100×(Q nor - ) / Q nor

[0057] Among them, Qnor is the electricity generated without toxic substances. It is the amount of electricity used to measure the duration of action after the addition of toxic substances;

[0058] ATP content inhibition rate (ACIR) A ACIR A (%) = 100 × (A) nor - ) / A nor

[0059] Among them, Anor is a stable ATP content that does not contain toxic substances. It is the ATP content after the toxic substance has been added and the time of its action has elapsed;

[0060] Acrylluminance suppression ratio (ACIR) F ACIR F (%) = 100×(F nor - ) / F nor

[0061] Wherein, Fnor is the luminescence intensity without toxic substances. It is the luminescence intensity after the toxic substance has been added and the reaction time has elapsed;

[0062] Overall inhibition rate (ACIR): ACIR(%) = (ACIR) Q +ACIR A +ACIR F ) / 3.

[0063] Based on the above scheme, in step S5, the warning level includes at least three levels (ACIR1, ACIR2, ACIR3), and corresponding countermeasures for different degrees of toxicity and hazard are given according to the comparison results with the comprehensive inhibition rate.

[0064] In a specific embodiment, the processing module presets three values, ACIR1, ACIR2, and ACIR3, and compares them with ACIR:

[0065] When ACIR < ACIR1, it indicates that there are no substances in the water that inhibit microbial activity;

[0066] When ACIR1≤ACIR<ACIR2, it indicates the presence of toxic substances in the water, but the toxicity is not strong, and attention should be paid to this.

[0067] When ACIR2≤ACIR<ACIR3, it indicates the presence of toxic substances in the water, which are highly toxic and require attention and appropriate measures.

[0068] When ACIR ≥ ACIR3, it indicates the presence of highly toxic substances in the water, requiring emergency measures.

[0069] In a specific embodiment, in step S5, ACIR1=5%, ACIR2=30%, and ACIR3=50%.

[0070] The present invention also provides a microbial fuel cell toxicity sensor, comprising:

[0071] Cathode 2 is made of carbon felt;

[0072] Anode 1 is formed by carbon felt to create an anode biofilm. The anode integrates an ATP module 3. After the battery output voltage stabilizes, luminescent bacteria are added. The ATP module 3 is used to monitor the changes in ATP content in the anode biofilm in real time, and the luminescent bacteria are used to reflect microbial activity through changes in luminescence intensity.

[0073] The detection device is used to monitor electricity production, ATP content, and luminescence intensity; specifically, the electrical signal detection device is set to constant external resistance mode; the ATP detection module 4 is connected to the ATP detector 6; and the luminescence detection module 5 is connected to the luminescence intensity detector 7.

[0074] Processing module 8, which is connected to the cathode, anode and detection device respectively, is used to calculate the inhibition rate and set the warning level.

[0075] In some embodiments, the anode biofilm is obtained by acclimation at different substrate concentrations, and the substrate solution in the acclimation process includes a buffer solution and / or a sodium acetate solution; the substrate solution is replaced at intervals, and the microbial fuel cell sensor is considered to have successfully acclimated at low temperature when the output voltage of the microbial fuel cell sensor stabilizes.

[0076] In this embodiment, the processing module calculates the overall inhibition rate based on the inhibition rate of power generation, ATP content and luminescence intensity, and conducts a toxicity hazard assessment based on preset warning levels (ACIR1, ACIR2, ACIR3).

[0077] Figure 5 The results of real-time detection of 2,4-dichlorophenol biotoxicity were obtained by detecting 10 mg / L, 50 mg / L and 100 mg / L of 2,4-dichlorophenol using electrical signals, biochemical signals and luminescent signals, respectively. The final inhibition rates were 42%, 82% and 96%, respectively.

[0078] The beneficial effects of the technical solution of the present invention are mainly reflected in:

[0079] Multi-parameter integrated detection combines three indicators—power generation (electrical signal), ATP content (bioactivity), and luminescence intensity (microbial metabolism)—to construct a multi-dimensional toxicity assessment system, thereby improving the comprehensiveness of detection.

[0080] The ATP module is used in conjunction with luminescent bacteria. By integrating an ATP detection module into the anode and adding luminescent bacteria, dual monitoring of microbial activity (ATP content and luminescence intensity) is achieved, enhancing the sensitivity and accuracy of toxicity responses.

[0081] By utilizing biofilm acclimatization optimization, an anode biofilm (combined with buffer and sodium acetate) is acclimatized at different substrate concentrations to establish a highly adaptable and stable microbial community, ensuring that the sensor maintains good performance in toxicity tests.

[0082] Weighted overall inhibition rate calculation and graded early warning, based on inhibition rate (ACIR) of power generation, ATP content and luminescence intensity. Q ACIR A ACIR F The system performs weighted calculations (ACIR) and combines them with preset ACIR1 / ACIR2 / ACIR3 warning levels to achieve graded assessment and response to the hazards of toxic substances.

[0083] By rationally combining biochemical, electrical, and optical signals that reflect microbial activity to indicate toxic effects, the probability of false positives in toxicity warnings is reduced, the accuracy of electroactive microorganisms in indicating toxic effects is improved, and the results of toxicity evaluation using electroactive microorganisms are made more reliable.

[0084] The specific embodiments described in this invention are merely illustrative of the invention and are not intended to limit it. Those skilled in the art can make modifications to these embodiments without contributing any inventive step after reading this specification, but such modifications are protected by patent law as long as they fall within the scope of the claims of this invention.

Claims

1. A method for improving the accuracy of toxicity sensing in microbial fuel cells, characterized in that, Includes the following steps: S1. Construct a microbial fuel cell sensor, the sensor including a cathode and an anode, the anode integrating an ATP module and adding luminescent bacteria; S2. An anode biofilm is formed by inoculating the anode, and the anode biofilm is acclimated using matrix solutions with different substrate concentrations. After the sensor output voltage stabilizes, a high-performance microbial fuel cell sensor is obtained. S3. Mix the nutrient matrix with the toxic substance sample to form the anode matrix of the test group, or do not add toxic substances to form the anode matrix of the blank group; S4. After the electrical signal stabilizes, the inhibition rate is calculated by the change in electricity production per unit time, the change in ATP content, and the change in luminescence intensity. Then, the overall inhibition rate of the toxic substance on the microorganism is obtained by weighted calculation. The formulas for calculating the inhibition rates of changes in electricity production, ATP content, and luminescence intensity are as follows: ACIR (Accelerated Power Generation Inhibition Rate) Q ACIR Q (%) = 100×(Q nor - ) / Q nor Among them, Qnor is the electricity generated without toxic substances. It is the amount of electricity used to measure the duration of action after the addition of toxic substances; ATP content inhibition rate ACIR A ACIR A (%) = 100 × (A) nor - ) / A nor Among them, Anor is a stable ATP content that does not contain toxic substances. It is the ATP content after the toxic substance has been added and the time of its action has elapsed; ACIR (Accenture Intensity Reduction Ratio) F ACIR F (%) = 100×(F nor - ) / F nor Wherein, Fnor is the luminescence intensity without toxic substances. It is the luminescence intensity after the toxic substance has been added and the reaction time has elapsed; Overall inhibition rate ACIR: ACIR(%) = (ACIR) Q +ACIR A +ACIR F ) / 3; S5. Set an early warning level based on the comprehensive inhibition rate to guide countermeasures.

2. The method for improving the accuracy of toxicity sensing in microbial fuel cells according to claim 1, characterized in that, In step S2, the matrix solution includes a buffer solution and a sodium acetate solution, and the acclimatization process is achieved by changing the matrix solution at intervals.

3. The method for improving the accuracy of toxicity sensing in microbial fuel cells according to claim 1, characterized in that, In step S4, if the change in electrical signal is less than 5%, the electrical signal is considered to be stabilizing.

4. The method for improving the accuracy of toxicity sensing in microbial fuel cells according to claim 1, characterized in that, In step S5, the warning level includes at least three levels: ACIR1, ACIR2, and ACIR3, and corresponding countermeasures for different degrees of toxicity and hazard are given based on the comparison results with the comprehensive inhibition rate.

5. The method for improving the accuracy of toxicity sensing in microbial fuel cells according to claim 1, characterized in that, In step S2, the anode biofilm of the microbial fuel cell sensor is achieved by inoculating a substrate solution that has been cultured for more than one year. The substrate solution is a mixture of buffer solution and sodium acetate solution.

6. The method for improving the accuracy of toxicity sensing in microbial fuel cells according to claim 1, characterized in that, The toxic substance sample was mixed with the nutrient matrix and used as the anode matrix for the experimental group, while the anode matrix for the blank group was a nutrient matrix that did not contain the toxic substance.

7. The method for improving the accuracy of toxicity sensing in microbial fuel cells according to claim 1, characterized in that, The ATP module is used to monitor changes in ATP content in the anolyte biofilm in real time, and the luminescent bacteria are used to reflect microbial activity through changes in luminescence intensity.

8. A microbial fuel cell toxicity sensing and detection system, characterized in that, include: The cathode is made of carbon felt; The anode is formed by carbon felt to create an anode biofilm. The anode integrates an ATP module. After the battery output voltage stabilizes, luminescent bacteria are added. The detection device is used to monitor power generation, ATP content, and luminescence intensity. The processing module is used to calculate the inhibition rate and set the warning level; The processing module calculates the overall inhibition rate based on the inhibition rate of power generation, ATP content and luminescence intensity, and conducts a toxicity hazard assessment based on the preset warning levels ACIR1, ACIR2 and ACIR3. The formulas for calculating the inhibition rates of changes in electricity production, ATP content, and luminescence intensity are as follows: ACIR (Accelerated Power Generation Inhibition Rate) Q ACIR Q (%) = 100×(Q nor - ) / Q nor Among them, Q nor It is the amount of electricity generated without toxic substances. It is the amount of electricity used to measure the duration of action after the addition of toxic substances; ATP content inhibition rate ACIR A ACIR A (%) = 100 × (A) nor - ) / A nor Among them, A nor It is a stable ATP content that does not contain toxic substances. It is the ATP content after the toxic substance has been added and the time of its action has elapsed; ACIR (Accenture Intensity Reduction Ratio) F ACIR F (%) = 100×(F nor - ) / F nor Among them, F nor It is the luminous intensity without toxic substances. It is the luminescence intensity after the toxic substance has been added and the reaction time has elapsed; Overall inhibition rate ACIR: ACIR(%) = (ACIR) Q +ACIR A +ACIR F ) / 3.

9. The microbial fuel cell toxicity sensing and detection system according to claim 8, characterized in that, The anode biofilm is obtained through domestication at different substrate concentrations. The substrate solution during the domestication process includes a buffer solution and / or a sodium acetate solution. The substrate solution is replaced at intervals. Once the output voltage of the microbial fuel cell sensor stabilizes, the microbial fuel cell sensor that has been successfully domesticated at low temperature is obtained.

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