Rapid counting method for clostridium butyricum high-concentration bacterial liquid

Abstract

The invention discloses a rapid counting method for clostridium butyricum high-concentration bacterial liquid, and relates to the technical field of microbiological detection. In order to solve the problems that the overall detection period is relatively long, and the requirement on rapid detection of the bacterial count within 12-18 hours in production cannot be met; the operation of adding the blocking agent is complex and has high requirements on technicians, and misoperation may cause non-uniform oxygen-free environment, so that the growth of thalli and the counting accuracy are influenced. According to the method, the bacterial count of the clostridium butyricum high-concentration bacterial liquid can be rapidly detected within 12-18 hours, especially when the spore count exceeds 25 billion / ml or higher, high precision is still kept, sample treatment steps are simplified, dyeing and image analysis technologies are optimized, the detection time is effectively shortened, bacterial count data are ensured to be accurate, a reliable basis is provided for bacterial powder preparation in production, and the method is suitable for industrial production. The production efficiency and the product quality are improved.

Description

Technical Field

[0001] The invention relates to the technical field of microbial detection, and in particular to a method for quickly counting a high-concentration bacterial solution of Clostridium butyricum. Background Art

[0002] In the production process of Clostridium butyricum, it is very important to accurately and quickly determine the number of bacteria in a high-concentration bacterial liquid. For example, the patent application with publication number CN111733099A discloses a Clostridium butyricum culture method and a Clostridium butyricum counting method for counting live bacteria, which include the following steps: mixing the liquid Clostridium butyricum culture medium with the sample liquid in a culture container, leaving it to solidify, covering the upper surface of the solidified surface with a layer of barrier agent, leaving it to solidify to isolate the air, and then culturing at a constant temperature. This patent application adds a layer of barrier agent to the ordinary Clostridium butyricum culture medium, so that the culture dish can be placed in an ordinary environment for culture to achieve the purpose of providing an anaerobic environment for the growth of Clostridium butyricum, avoiding the use of anaerobic incubators, making the culture process easier to control, convenient and quick, and the counting results are accurate, which is convenient for producers and consumers to count and detect, and can improve the market environment of Clostridium butyricum preparations.

[0003] However, the above patent facilitates the cultivation of Clostridium butyricum in an anaerobic environment, but still has the following problems:

[0004] In the existing technology, due to the need for multiple steps such as cultivation and static solidification, the overall detection cycle is relatively long, which cannot meet the demand for rapid detection of bacterial counts within 12-18 hours in production; and the operation of adding barrier agents is complicated and requires high technical personnel. Operational errors may lead to uneven anaerobic environment, affecting the growth of bacteria and the accuracy of counting. Summary of the invention

[0005] The object of the present invention is to provide a method for quickly counting a high-concentration bacterial solution of Clostridium butyricum, which can quickly detect the bacterial count of a high-concentration bacterial solution of Clostridium butyricum within 12-18 hours, especially when the spore count exceeds 2.5 billion / ml or higher, it still maintains high accuracy, simplifies the sample processing steps, optimizes the staining and image analysis technology, effectively shortens the detection time, ensures the accuracy of bacterial count data, provides a reliable basis for the preparation of bacterial powder in production, improves production efficiency and product quality, and solves the problems raised in the above-mentioned background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] The method for rapid counting of high-concentration Clostridium butyricum liquid includes the following methods:

[0008] Step 1: Sample pretreatment: Take 1 ml of Clostridium butyricum fermentation broth, dilute the high-concentration Clostridium butyricum fermentation broth, and mix the bacterial broth of each dilution using a vortex oscillator;

[0009] Step 2: Sample fixation and staining: Take 100 μl of bacterial solution sample from each dilution, fix, wash and stain the bacterial solution sample;

[0010] Step 3: Image observation and acquisition: drop the stained bacterial solution onto a glass slide, cover it with a coverslip, and observe it using a fluorescence microscope. For each dilution of the bacterial solution sample, collect image data of at least 10 fields of view, where the area of ​​each field of view is fixed as a known parameter;

[0011] Step 4: Image processing and analysis: spore identification and counting are performed on the collected image data, and the bacterial concentration in the original Clostridium butyricum fermentation broth is calculated according to the dilution multiple and the field of view area;

[0012] Step 5: Verification of counting results: Use a standard bacterial solution of known concentration to perform the same treatment and counting, draw a standard bacterial solution curve, calibrate the counting results based on the standard bacterial solution curve, and compare the measurement results of different batches of fermentation broth, and verify the consistency based on the comparison results.

[0013] Furthermore, the step 1: sample pretreatment specifically includes:

[0014] Sample dilution: Take 1 ml of high-concentration Clostridium butyricum fermentation broth sample and use phosphate buffer to dilute the sample to a range suitable for microscopic observation and counting, wherein the sample concentration after dilution is a gradient dilution of 1 / 10, 1 / 100, and 1 / 1000 of the original concentration;

[0015] Even mixing: Use a vortex oscillator to thoroughly mix the bacterial solution after each dilution to ensure that the bacteria are evenly distributed in the bacterial solution sample.

[0016] Furthermore, in step 2, the bacterial liquid sample is fixed, washed and stained, specifically including:

[0017] Fixation: Add an equal volume of 4% formaldehyde solution to each 100 μl bacterial sample for fixation for 10 minutes. After fixation, remove the fixative and wash three times with phosphate buffer.

[0018] Staining treatment: After washing, add an equal volume of specific spore stain to the bacterial sample and stain at 37°C for 20 minutes. After staining, wash again three times with phosphate buffer to remove unbound stain.

[0019] Furthermore, the dyeing process specifically includes:

[0020] According to the sample type of the bacterial liquid sample, the initial specific spore stain concentration and initial staining time were set, and the staining temperature was controlled at 37°C;

[0021] The color change of the bacterial solution sample during the dyeing process is monitored in real time based on a spectrum analyzer, and a fluorescence intensity threshold is set. When the fluorescence intensity of the bacterial solution sample reaches the preset threshold, the dyeing is stopped and washing is performed;

[0022] If the preset threshold is not reached within the initial staining time, the staining time is increased and the staining agent concentration is gradually increased. Otherwise, the staining is terminated early.

[0023] Furthermore, the observation magnification of the fluorescence microscope is 1000 times.

[0024] Furthermore, the step 4 includes performing spore identification and counting on the collected image data, specifically comprising:

[0025] Image preprocessing: denoise the collected image data to eliminate the interference caused by stray light and tiny particles in the background, and convert the denoised image data into grayscale;

[0026] Threshold segmentation: Dynamically adjust the light intensity threshold according to the difference in local light intensity of the image, and extract the morphological features of each segmented area. Based on the morphological feature extraction results, separate the spores from the background and screen out the spore area;

[0027] Connected region marking and screening: The segmented regions are marked as connected regions, and each spore region is marked and numbered separately. The marked regions are screened according to morphological characteristics and fluorescence intensity parameters to eliminate non-target particles.

[0028] Furthermore, the threshold segmentation extracts the morphological features in the region by establishing a feature recognition model, which specifically includes:

[0029] Morphological feature model input: The segmented regional image is input into the pre-trained morphological feature recognition model, which is used to identify and extract the morphological features in each region;

[0030] Morphological feature calculation: Analyze the segmented area based on the morphological feature recognition model and extract the main morphological features of the area, including feature data of size, shape and fluorescence intensity;

[0031] Feature comparison and error rate calculation: The morphological feature recognition model compares the extracted feature data with the preset standard feature library and calculates the recognition error rate;

[0032] Feature validity judgment: compare the recognition error rate calculation result with the preset error threshold. If the recognition error rate is lower than the preset threshold, the morphological feature data output by the feature recognition model is judged as valid morphological feature data.

[0033] Feature data marking and classification: Based on the effective morphological feature data, the segmented areas are classified and marked.

[0034] Furthermore, the image processing analysis also includes:

[0035] The number of spores in at least 10 fields of view collected at the same dilution was counted, and the average number of spores in each field of view was calculated to reduce the error caused by local regional differences;

[0036] Determine the dilution factor of the sample, multiply the average number of spores at each dilution by the corresponding dilution factor, and thus deduce the actual number of spores per unit volume in the original fermentation broth;

[0037] The actual area of ​​the microscope field was determined, and the number of spores in each field was divided by the field area to obtain the spore density per unit area;

[0038] The spore concentration in the original Clostridium butyricum fermentation broth was determined based on the spore density and the dilution multiple of the bacterial solution sample. At the same time, the total number of spores per milliliter of the bacterial solution sample was obtained based on the spore density per unit area and the volume of the bacterial solution sample.

[0039] Furthermore, drawing a standard bacterial solution curve in step 5 specifically includes:

[0040] The standard Clostridium butyricum solution with known concentration is subjected to the same treatment steps as the Clostridium butyricum fermentation solution sample to be tested, including dilution, mixing, microscopic observation and spore counting;

[0041] Wherein, the bacterial concentration of the Clostridium butyricum standard bacterial solution covers the concentration measurement range of the Clostridium butyricum fermentation broth sample to be tested;

[0042] A standard curve is drawn with the actual bacterial concentration of the standard bacterial solution as the horizontal axis and the bacterial concentration obtained by counting as the vertical axis.

[0043] Furthermore, step five: verification of counting results, further includes: performing repeated measurements of the Clostridium butyricum standard bacterial solution and the Clostridium butyricum fermentation broth samples to be tested from the same batch for no less than three times, and obtaining the average value and standard deviation of the Clostridium butyricum standard bacterial solution and the Clostridium butyricum fermentation broth samples to be tested from the same batch based on the measurement results.

[0044] Compared with the prior art, the present invention has the following beneficial effects:

[0045] By simplifying the sample pretreatment steps, optimizing the sample fixation and staining process, accurate image observation and acquisition, and efficient image processing and analysis, the bacterial count of high-concentration Clostridium butyricum bacterial solution can be quickly detected within 12-18 hours, especially when the spore count exceeds 2.5 billion / ml or higher, it still maintains high accuracy. It not only significantly shortens the detection cycle and improves production efficiency, but also simplifies the sample processing steps and optimizes the staining and image analysis technology, effectively shortens the detection time, reduces the complexity of the operation steps, reduces the technical requirements, ensures the uniformity of the bacterial growth environment, ensures the accuracy of the bacterial count data, provides a reliable basis for the preparation of bacterial powder in production, improves production efficiency and product quality, thereby improving the accuracy and repeatability of bacterial counts, and provides reliable technical support for quality control in the production process. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 The present invention is a flow chart of the method for rapid counting of Clostridium butyricum high-concentration bacterial solution. DETAILED DESCRIPTION

[0047] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0048] In order to solve the technical problems that the overall detection cycle is long and cannot meet the demand for rapid detection of bacterial counts within 12-18 hours in production; the operation of adding barrier agents is complicated and requires high technical personnel, and operational errors may lead to uneven anaerobic environment, affecting the growth of bacteria and the accuracy of counting, please refer to Figure 1 , this embodiment provides the following technical solutions:

[0049] The method for rapid counting of high-concentration Clostridium butyricum liquid includes the following methods:

[0050] Step 1: Sample pretreatment: Take 1 ml of Clostridium butyricum fermentation broth, dilute the high-concentration Clostridium butyricum fermentation broth, and mix the bacterial broth of each dilution on a vortex oscillator, specifically including:

[0051] Sample dilution: Take 1 ml of high-concentration Clostridium butyricum fermentation broth sample and use phosphate buffer to dilute the sample to a range suitable for microscopic observation and counting. The sample concentrations after dilution are 1 / 10, 1 / 100, and 1 / 1000 of the original concentration in order to ensure the activity of the bacterial broth and the uniformity of dilution;

[0052] Even mixing: Use a vortex oscillator to fully mix the bacterial solution after each dilution to ensure that the bacteria in the bacterial solution sample are evenly distributed and reduce counting errors;

[0053] Step 2: Sample fixation and staining: Take 100 μl of bacterial solution sample from each dilution, fix, wash and stain the bacterial solution sample;

[0054] Step 3: Image observation and acquisition: Add the stained bacterial solution to the slide, cover with a cover glass to avoid bubbles, ensure a clear field of view, and observe using a fluorescence microscope with an observation magnification of 1000 times. Collect image data of at least 10 fields of view for each dilution of the bacterial solution sample, where the area of ​​each field of view is fixed as a known parameter;

[0055] Step 4: Image processing and analysis: spore identification and counting are performed on the collected image data, and the bacterial concentration in the original Clostridium butyricum fermentation broth is calculated according to the dilution multiple and the field of view area;

[0056] Step 5: Verification of counting results: Use a standard bacterial solution of known concentration to perform the same treatment and counting, draw a standard bacterial solution curve, calibrate the counting results based on the standard bacterial solution curve, and compare the measurement results of different batches of fermentation broth, and verify the consistency based on the comparison results.

[0057] In this embodiment, by simplifying the sample pretreatment steps, optimizing the sample fixation and staining process, precise image observation and acquisition, and efficient image processing and analysis, a rapid and accurate counting of the number of bacteria in a high-concentration bacterial solution is achieved in a short time, and the number of bacteria in a high-concentration bacterial solution of Clostridium butyricum can be quickly detected within 12-18 hours, especially when the spore count exceeds 2.5 billion / ml or higher, high accuracy is still maintained, which not only significantly shortens the detection cycle and improves production efficiency, but also reduces the complexity of the operating steps, reduces technical requirements, ensures the uniformity of the bacterial growth environment, thereby improving the accuracy and repeatability of bacterial counting, and provides reliable technical support for quality control in the production process.

[0058] In this embodiment, the bacterial liquid sample is fixed, washed and stained in step 2, which specifically includes:

[0059] Fixation: Add an equal volume of 4% formaldehyde solution to each 100 μl bacterial sample for fixation for 10 minutes. After fixation, remove the fixative and wash three times with phosphate buffer.

[0060] Staining treatment: After washing, add an equal volume of specific spore stain, such as Malachite Green stain or fluorescent dye, to the bacterial sample. The concentration of Malachite Green stain is 0.5% (w / v). Stain at 37°C for 20 minutes. After staining, wash again three times with phosphate buffer to remove unbound stain and ensure the stability of the stained bacterial sample. Specifically include:

[0061] According to the sample type of the bacterial liquid sample, the initial specific spore stain concentration and initial staining time were set, and the staining temperature was controlled at 37°C;

[0062] The color change of the bacterial solution sample during the dyeing process is monitored in real time based on a spectrum analyzer, and a fluorescence intensity threshold is set. When the fluorescence intensity of the bacterial solution sample reaches the preset threshold, the dyeing is stopped and washing is performed;

[0063] If the preset threshold value is not reached within the initial dyeing time, the dyeing time is increased and the dye concentration is gradually increased, for example, by 0.1% each time. Otherwise, the dyeing is terminated in advance.

[0064] In this embodiment, by using 4% formaldehyde solution to fix the bacterial liquid sample, the fixation process can be completed quickly to ensure the stability of the bacterial structure, the dyeing process is monitored in real time by using a spectrum analyzer, and the dyeing time and dye concentration are adjusted according to the fluorescence intensity threshold to ensure the uniformity and stability of the dyeing effect, and by setting the initial dye concentration and dyeing time and adjusting them according to actual conditions, the method can adapt to the needs of different sample types and bacterial liquid concentrations, improve the efficiency and accuracy of bacterial liquid sample processing, reduce the time of experimental operation, enhance the controllability of the dyeing process, and improve the reliability of the counting results.

[0065] In this embodiment, the step 4 performs spore identification and counting on the collected image data, specifically including:

[0066] Image preprocessing: De-noise the collected image data to eliminate the interference caused by stray light and tiny particles in the background, and convert the de-noised image data into grayscale to simplify the subsequent image segmentation and feature extraction steps and facilitate subsequent analysis;

[0067] Threshold segmentation: Dynamically adjust the light intensity threshold according to the difference in local light intensity of the image to adapt to the lighting conditions under different fields of view, accurately distinguish spores from the background area, and extract the morphological features of each segmented area, such as size, shape and fluorescence intensity. Based on the morphological feature extraction results, the spores are separated from the background and the spore area is screened out. Spores usually appear as regular circles or ellipses and have high fluorescence intensity.

[0068] Connected region marking and screening: The segmented regions are marked as connected regions, and each spore region is individually marked and numbered to ensure the independent identification of each target region. The marked regions are screened according to morphological characteristics and fluorescence intensity parameters to eliminate non-target particles, such as debris or background noise and other non-spore structures.

[0069] In this example, precise image processing and analysis were used to significantly improve the accuracy of spore counting, reduce human errors, reduce manual operation time, speed up counting, and meet the needs of rapid detection in production. Standardized image processing steps ensured the consistency of results between different batches and different operators, and enhanced the repeatability of the experiment.

[0070] In this embodiment, the threshold segmentation extracts the morphological features in the region by establishing a feature recognition model, which specifically includes:

[0071] Morphological feature model input: The segmented region image is input into the pre-trained morphological feature recognition model. The morphological feature recognition model is used to identify and extract the morphological features in each region. The input data includes key parameters such as the contour information, grayscale value, and fluorescence intensity distribution of the segmented region.

[0072] Morphological feature calculation: Analyze the segmented area based on the morphological feature recognition model and extract the main morphological features of the area, including feature data of size, shape and fluorescence intensity;

[0073] In this embodiment, the physical size of the bacteria is determined by calculating the area and perimeter of the segmented region; the shape of the target region is determined by extracting parameters such as roundness, ellipticity, and aspect ratio. Spores usually have high roundness or ellipticity; the mean, peak, and distribution of the fluorescence intensity in the region are calculated. Since the fluorescence signal of the spores is strong, the model will screen out high-intensity areas based on the fluorescence intensity characteristics;

[0074] Feature comparison and error rate calculation: The morphological feature recognition model compares the extracted feature data with the preset standard feature library and calculates the recognition error rate. The calculation of the recognition error rate is based on the following parameters:

[0075] The number of real feature data identified: determine the number of real spore regions successfully identified by the morphological feature recognition model;

[0076] Non-target area misdetection rate: the number of non-spore areas misidentified as spores by the statistical morphological feature recognition model;

[0077] Target area missed detection rate: the number of real spore areas mistakenly identified as non-target areas by the statistical morphological feature recognition model;

[0078] Feature validity judgment: compare the recognition error rate calculation result with the preset error threshold. If the recognition error rate is lower than the preset threshold, the morphological feature data output by the feature recognition model is judged as valid morphological feature data.

[0079] Feature data labeling and classification: Based on the effective morphological feature data, the segmented areas are classified and labeled. Each area is assigned a specific label, such as "spore" or "non-spore", for subsequent statistical analysis and concentration calculation.

[0080] In this embodiment, the feature recognition model ensures that the morphological feature extraction of the segmented area has high accuracy and consistency, and can effectively identify spores and eliminate interference, thereby improving the reliability of the entire image processing and analysis process.

[0081] In this embodiment, the image processing analysis further includes:

[0082] The number of spores in at least 10 fields of view collected at the same dilution was counted, and the average number of spores in each field of view was calculated to reduce the error caused by local regional differences;

[0083] Determine the dilution factor of the sample, multiply the average number of spores at each dilution by the corresponding dilution factor, and thus deduce the actual number of spores per unit volume in the original fermentation broth;

[0084] The actual area of ​​the microscope field was determined, and the number of spores in each field was divided by the field area to obtain the spore density per unit area;

[0085] The spore concentration in the original Clostridium butyricum fermentation broth is determined based on the spore density and the dilution multiple of the bacterial solution sample. At the same time, the total number of spores per milliliter of the bacterial solution sample is obtained based on the spore density per unit area and the volume of the bacterial solution sample.

[0086] In this example, it is assumed that 10 large squares were counted under a microscope, each with a volume of 0.1 μL, and a total of 300 spores were observed;

[0087] If the total dilution factor is 1000, then the calculation formula is:

[0088]

[0089] Where, bacterial concentration represents the number of colony-forming units present per milliliter of the original sample, and 1000 represents the factor for converting μL to mL;

[0090] In this embodiment, by counting the number of spores in at least 10 fields of view and calculating the average value, the counting error caused by uneven distribution of samples or local area differences can be effectively reduced, the representativeness of the overall counting results is improved, random errors and systematic errors are reduced, the accuracy of spore counting is improved, and the spore concentration and distribution are accurately understood, which is helpful to optimize fermentation conditions, improve production efficiency and product quality, and the accuracy and reliability of the bacterial concentration calculation are ensured from the local microscope field of view data to the overall sample concentration.

[0091] In this embodiment, drawing the standard bacterial solution curve in step 5 specifically includes:

[0092] The standard Clostridium butyricum solution with known concentration is subjected to the same treatment steps as the Clostridium butyricum fermentation solution sample to be tested, including dilution, mixing, microscopic observation and spore counting;

[0093] Wherein, the bacterial concentration of the Clostridium butyricum standard bacterial solution covers the concentration measurement range of the Clostridium butyricum fermentation broth sample to be tested;

[0094] The standard curve is drawn with the actual bacterial concentration of the standard bacterial solution as the horizontal axis and the bacterial concentration obtained by counting as the vertical axis;

[0095] Among them, the standard bacterial solution of Clostridium butyricum and the Clostridium butyricum fermentation broth samples to be tested from the same batch are repeatedly measured for no less than three times, and the average value and standard deviation of the standard bacterial solution of Clostridium butyricum and the Clostridium butyricum fermentation broth samples to be tested from the same batch are obtained based on the measurement results to ensure the stability and repeatability of the results.

[0096] In this embodiment, by subjecting a standard bacterial solution of known concentration to the same processing steps as the sample to be tested, the consistency of the experimental conditions is ensured, making the establishment of the standard curve more reliable, and repeated measurements and calculations of the mean value and standard deviation help to identify and reduce errors in the experimental process, improve the reliability of the data, ensure the accuracy and reliability of the experimental data, and facilitate the optimization of laboratory operation procedures.

[0097] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A method for rapid counting of Clostridium butyricum high-concentration bacterial solution, characterized in that: The following methods are included: Step 1: Sample pretreatment: Take 1 ml of Clostridium butyricum fermentation broth, dilute the high-concentration Clostridium butyricum fermentation broth, and mix the bacterial broth of each dilution using a vortex oscillator; Step 2: Sample fixation and staining: Take 100 μl of bacterial solution sample from each dilution, fix, wash and stain the bacterial solution sample; Step 3: Image observation and acquisition: drop the stained bacterial solution onto a glass slide, cover it with a coverslip, and observe it using a fluorescence microscope. For each dilution of the bacterial solution sample, collect image data of at least 10 fields of view, where the area of ​​each field of view is fixed as a known parameter; Step 4: Image processing and analysis: spore identification and counting are performed on the collected image data, and the bacterial concentration in the original Clostridium butyricum fermentation broth is calculated according to the dilution multiple and the field of view area; Step 5: Verification of counting results: Use a standard bacterial solution of known concentration to perform the same treatment and counting, draw a standard bacterial solution curve, calibrate the counting results based on the standard bacterial solution curve, and compare the measurement results of different batches of fermentation broth, and verify the consistency based on the comparison results.

2. The method for rapid counting of Clostridium butyricum high-concentration bacterial solution according to claim 1, characterized in that: The step 1: sample pretreatment, specifically includes: Sample dilution: Take 1 ml of high-concentration Clostridium butyricum fermentation broth sample and use phosphate buffer to dilute the sample to a range suitable for microscopic observation and counting, wherein the sample concentration after dilution is a gradient dilution of 1 / 10, 1 / 100, and 1 / 1000 of the original concentration; Even mixing: Use a vortex oscillator to thoroughly mix the bacterial solution after each dilution to ensure that the bacteria are evenly distributed in the bacterial solution sample.

3. The method for rapid counting of Clostridium butyricum high-concentration bacterial solution according to claim 1, characterized in that: In the step 2, the bacterial liquid sample is fixed, washed and stained, which specifically includes: Fixation: Add an equal volume of 4% formaldehyde solution to each 100 μl bacterial sample for fixation for 10 minutes. After fixation, remove the fixative and wash three times with phosphate buffer. Staining treatment: After washing, add an equal volume of specific spore stain to the bacterial sample and stain at 37°C for 20 minutes. After staining, wash again three times with phosphate buffer to remove unbound stain.

4. The method for rapid counting of Clostridium butyricum high-concentration bacterial solution according to claim 3, characterized in that: The dyeing process specifically includes: According to the sample type of the bacterial liquid sample, the initial specific spore stain concentration and initial staining time were set, and the staining temperature was controlled at 37°C; The color change of the bacterial solution sample during the dyeing process is monitored in real time based on a spectrum analyzer, and a fluorescence intensity threshold is set. When the fluorescence intensity of the bacterial solution sample reaches the preset threshold, the dyeing is stopped and washing is performed; If the preset threshold is not reached within the initial staining time, the staining time is increased and the staining agent concentration is gradually increased. Otherwise, the staining is terminated early.

5. The method for rapid counting of Clostridium butyricum high-concentration bacterial solution according to claim 1, characterized in that: The observation magnification of the fluorescence microscope was 1000 times.

6. The method for rapid counting of Clostridium butyricum high-concentration bacterial solution according to claim 1, characterized in that: The step 4 performs spore identification and counting on the collected image data, specifically including: Image preprocessing: denoise the collected image data to eliminate the interference caused by stray light and tiny particles in the background, and convert the denoised image data into grayscale; Threshold segmentation: Dynamically adjust the light intensity threshold according to the difference in local light intensity of the image, and extract the morphological features of each segmented area. Based on the morphological feature extraction results, separate the spores from the background and screen out the spore area; Connected region marking and screening: The segmented regions are marked as connected regions, and each spore region is marked and numbered separately. The marked regions are screened according to morphological characteristics and fluorescence intensity parameters to eliminate non-target particles.

7. The method for rapid counting of Clostridium butyricum high-concentration bacterial solution according to claim 6, characterized in that: The threshold segmentation extracts the morphological features in the region by establishing a feature recognition model, specifically including: Morphological feature model input: The segmented regional image is input into the pre-trained morphological feature recognition model, which is used to identify and extract the morphological features in each region; Morphological feature calculation: Analyze the segmented area based on the morphological feature recognition model and extract the main morphological features of the area, including feature data of size, shape and fluorescence intensity; Feature comparison and error rate calculation: The morphological feature recognition model compares the extracted feature data with the preset standard feature library and calculates the recognition error rate; Feature validity judgment: compare the recognition error rate calculation result with the preset error threshold. If the recognition error rate is lower than the preset threshold, the morphological feature data output by the feature recognition model is judged as valid morphological feature data. Feature data marking and classification: Based on the effective morphological feature data, the segmented areas are classified and marked.

8. The method for rapid counting of Clostridium butyricum high-concentration bacterial solution according to claim 1, characterized in that: The image processing analysis further includes: The number of spores in at least 10 fields of view collected at the same dilution was counted, and the average number of spores in each field of view was calculated; Determine the dilution factor of the sample, multiply the average number of spores at each dilution by the corresponding dilution factor, and thus deduce the actual number of spores per unit volume in the original fermentation broth; The actual area of ​​the microscope field was determined, and the number of spores in each field was divided by the field area to obtain the spore density per unit area; The spore concentration in the original Clostridium butyricum fermentation broth was determined based on the spore density and the dilution multiple of the bacterial solution sample. At the same time, the total number of spores per milliliter of the bacterial solution sample was obtained based on the spore density per unit area and the volume of the bacterial solution sample.

9. The method for rapid counting of Clostridium butyricum high-concentration bacterial solution according to claim 1, characterized in that: Drawing the standard bacterial solution curve in step 5 specifically includes: The standard Clostridium butyricum solution with known concentration is subjected to the same treatment steps as the Clostridium butyricum fermentation solution sample to be tested, including dilution, mixing, microscopic observation and spore counting; Wherein, the bacterial concentration of the Clostridium butyricum standard bacterial solution covers the concentration measurement range of the Clostridium butyricum fermentation broth sample to be tested; A standard curve is drawn with the actual bacterial concentration of the standard bacterial solution as the horizontal axis and the bacterial concentration obtained by counting as the vertical axis.

10. The method for rapid counting of Clostridium butyricum high-concentration bacterial solution according to claim 1, characterized in that: Step 5: Verification of counting results, further comprising: performing repeated measurements of the Clostridium butyricum standard bacterial solution and the Clostridium butyricum fermentation broth samples to be tested from the same batch for no less than three times, and obtaining the average value and standard deviation of the Clostridium butyricum standard bacterial solution and the Clostridium butyricum fermentation broth samples to be tested from the same batch based on the measurement results.

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