Microbial degradation plastic quantitative analysis and evaluation method based on Raman spectrum technology

Abstract

The invention discloses a microbiological degradation plastic quantitative analysis and evaluation method based on a Raman spectrum technology, and relates to the technical field of microbiological degradation plastic determination.The method comprises the following steps that a marine sediment sample and a to-be-decomposed plastic sample are collected, and an experimental group culture medium and a control group culture medium for evaluating the plastic decomposition degree are manufactured; collecting the Raman spectrogram of the experimental group and the Raman spectrogram of the control group, and obtaining the plastic decomposition degree before and after plastic degradation by using a weight loss method; obtaining a relation curve graph of a peak intensity ratio and a plastic decomposition degree from the Raman spectrogram by adopting a peak intensity ratio method, constructing a marine microorganism degradation plastic evaluation model, analyzing the peak intensity ratio of the Raman spectrogram, and executing corresponding measures to deal with the evaluation result. A gravity sampling technology, a culture medium microorganism technology, a Raman spectrogram acquisition technology, a Raman spectrogram processing technology and a modern information technology are tightly combined, so that real-time and comprehensive monitoring on the degradation degree of the microorganisms on the plastic is achieved.

Description

Technical Field

[0001] The invention relates to the technical field of determination of microbial degradation of plastics, and in particular to a quantitative analysis and evaluation method for microbial degradation of plastics based on Raman spectroscopy technology. Background Art

[0002] With the increasing severity of the global plastic pollution problem, especially the serious marine pollution at this stage, the irrational discharge of plastics generated by human activities has destroyed the marine ecosystem. Therefore, the development of effective plastic degradation technology has become a common pursuit of the scientific research community and the industrial community. Microbial degradation, as an environmentally friendly method, uses specific microorganisms or their enzyme systems to decompose plastics and has potential application value. However, it is not easy to accurately evaluate the degradation effect of microorganisms on plastics, especially to conduct quantitative analysis. Traditional methods such as weight loss method and chemical analysis have the problems of being time-consuming, complicated to operate and difficult to achieve high-throughput screening. Quantitative analysis methods based on Raman spectroscopy technology provide a new solution. Raman spectroscopy is a non-destructive molecular structure analysis tool that can detect changes in chemical bonds inside substances, and these changes are often closely related to the physical and chemical properties of the material. When plastic is When microorganisms degrade, their polymer chains will break, resulting in changes in chemical composition and structure. These changes can be reflected in the changes in the position, intensity or shape of specific peaks in the Raman spectrum. By establishing a standard curve or mathematical model and correlating the spectral characteristics with the known degree of degradation, real-time monitoring and quantitative evaluation of the degradation process can be achieved. In addition, Raman spectroscopy technology also has the advantages of no need for sample pretreatment, rapid response, and strong repeatability. It is suitable for long-term continuous observation and large-scale sample screening. Combined with modern computing technology and data mining algorithms, it can further improve the analysis accuracy, deeply understand the mechanism of microbial-plastic interaction, and provide a scientific basis for optimizing degradation conditions. Therefore, the quantitative analysis and evaluation method of microbial degradation of plastics based on Raman spectroscopy technology not only helps to accelerate the discovery and application of new and efficient degradation strains, but also has important significance for promoting green and sustainable development.

[0003] Although the existing quantitative analysis and evaluation methods for microbial degradation of plastics based on Raman spectroscopy technology have made great progress, there are still some problems that need to be optimized. In the complex marine microbial community, the chemical structure and physical properties of the plastic itself increase the difficulty of evaluating the degree of microbial degradation. There is no unified standard method based on Raman spectroscopy for the evaluation of the degree of microbial degradation of plastics. Microbial degradation of plastics is a dynamic process, and the monitoring and data processing of Raman spectra face challenges. How to accurately extract degradation degree information from continuously changing Raman spectral data is a problem that needs to be solved urgently. Summary of the invention

[0004] To achieve the above objectives, the present invention is implemented by the following technical scheme: a method for quantitative analysis and evaluation of microbial degradation of plastics based on Raman spectroscopy technology, comprising the following steps:

[0005] Step 1: Collect marine sediment samples and samples of plastic to be decomposed, prepare experimental group culture medium and control group culture medium for evaluating the degree of plastic decomposition, and use Raman spectrometer to obtain Raman spectra of the experimental group and the control group;

[0006] Step 2: Baseline correction and spectrum smoothing are performed on the Raman spectra of the experimental group and the control group; the degree of plastic decomposition before and after plastic degradation is obtained using the weight loss method;

[0007] Step 3, using the peak intensity ratio method to obtain a curve diagram showing the relationship between the peak intensity ratio and the degree of plastic decomposition from the Raman spectrum;

[0008] Step 4: Use the random forest algorithm to build an assessment model for marine microbial degradation of plastics;

[0009] Step 5: Analyze the peak intensity ratio of the Raman spectrum and transmit the evaluation result to the client.

[0010] A further improvement of the technical solution of the present invention is that in step 1, the process of collecting microbial samples of marine sediments and samples of plastic to be decomposed includes:

[0011] Place the gravity sampler in the seawater, let it sink to the seabed sediment layer by gravity, and collect microbial samples from the marine sediments; collect plastic waste from the sea surface and the seashore, use scissors to cut it into 1mm plastic fragments, and obtain plastic samples to be decomposed.

[0012] A further improvement of the technical solution of the present invention is that in step 1, the process of preparing the experimental group culture medium and the control group culture medium for evaluating the degree of plastic decomposition includes:

[0013] A1. Prepare seawater culture medium and water culture medium, sterilize them at high temperature, cool the sterilized seawater culture medium and water culture medium to 45° C., and dispense them into sterile containers of the same size for standby use;

[0014] A2. Dilute and homogenize the collected marine sediment samples, use a centrifuge to remove large particles of impurities in the marine microbial suspension, retain the suspended microbial cells, and obtain a uniformly distributed marine microbial sample suspension; place the plastic sample to be decomposed in a high-pressure sterilizer and place it at 121°C for 15 minutes to obtain a sterile plastic sample;

[0015] A3. Take 100 ml of seawater culture medium, add 1 ml of marine microbial suspension, put sterile plastic fragments into the culture medium, and obtain the experimental group for evaluating the degree of microbial decomposition; take 100 ml of clean water culture medium, put sterile plastic samples, and obtain the control group for evaluating the degree of microbial decomposition;

[0016] A4. The experimental group for evaluating the degree of microbial decomposition and the control group were cultured under the same environmental conditions.

[0017] A further improvement of the technical solution of the present invention is that in step 1, the process of obtaining the Raman spectrum of the experimental group and the Raman spectrum of the control group using a Raman spectrometer includes:

[0018] Turn on the Raman spectrometer and preheat the instrument for 30 minutes. Adjust the parameters of the Raman spectrometer according to the standard sample silicon wafer at 520.7 cm -1 There is a sharp and high-intensity Raman peak at the center. The Raman spectrometer was calibrated using a silicon wafer sample. The culture medium of the experimental group after 1 day, 7 days, and 28 days of culture was placed in the sample chamber of the Raman spectrometer. Five spectra were collected for the plastic fragments in the culture medium of the experimental group and the culture medium of the control group, respectively. The spectral data of each spectrum collection was recorded, and the spectral data included Raman shift and Raman scattered light intensity. After the collection was completed, the spectral data collected five times were averaged to obtain Raman spectra of the experimental group and the control group.

[0019] A further improvement of the technical solution of the present invention is that in step 2, the process of performing baseline correction processing on the Raman spectrum of the experimental group and the Raman spectrum of the control group includes:

[0020] B1. Using Haar wavelet transform, select three decomposition layers, discretize the Raman shift-Raman scattered light intensity data of the Raman spectra of the experimental group and the control group, and set the Raman shift range to [x 1 , x n ], the Raman scattered light intensity is y = [y 1 ,y 2 , ..., y n ];

[0021] B2. The first-level decomposition calculation process is as follows:

[0022]

[0023] Where k is a discrete index and the approximate function cA 1 is the low-frequency information of the spectrum, including the smooth part of the signal and the baseline information, and the detail function cD 1 It is the high-frequency information of the spectrum, including characteristic peaks and noise;

[0024] B3, the second level decomposition is the approximate coefficient cA obtained by the first level decomposition 1 As the input signal, repeat the above decomposition process to calculate cA 2 and cD 2 The third level decomposition is the approximate coefficient cA obtained by the second level decomposition 2 As input signal, calculate and obtain cA 3 and cD 3；

[0025] B4. According to the actual spectral characteristics and noise level, set a threshold T and approximate function cA j If the absolute value of [k] is less than T, it is set to zero. The baseline coefficient can be removed by trying different thresholds and observing the effect of the corrected spectrum;

[0026] B5. Use the redundant coefficients to reconstruct the spectrum. The process of reconstructing the spectrum according to the reconstruction formula of wavelet decomposition is as follows:

[0027]

[0028] Wherein, y′ is the reconstructed spectral data. The approximate coefficients obtained in the above process are substituted to obtain the Raman spectra of the experimental group and the Raman spectra of the control group after removing the baseline.

[0029] A further improvement of the technical solution of the present invention is that in step 2, the process of performing spectral smoothing on the Raman spectrum of the experimental group and the Raman spectrum of the control group includes:

[0030] Using Savitzky-Go, we selected a window size of 7 and a second-order polynomial, and for each data point y of the Raman spectra of the experimental group and the control group i , take this data point as the center and select y i-3 ,y i-2 ,y i ,y i+1 ,y i+2 ,y i+3 For the data points within the seven window sizes, a second-order polynomial is fitted to the seven data points, and the fitting polynomial is set to p(x)=a 0 +a 1 x+a 2 x 2 , by determining the coefficients a of the polynomial least squares method 0 , a 1 , a 2 , so that the error between the fitting polynomial and the selected data points is minimized. The error calculation process is as follows:

[0031]

[0032] Through the above calculation results, the characteristic peaks and background noise before and after the spectrum smoothing are compared. The more prominent the characteristic peaks are, the lower the background noise is, and the better the smoothing effect is. The window size is adjusted according to the comparison results to obtain the Raman spectra of the experimental group and the control group after the spectrum smoothing.

[0033] A further improvement of the technical solution of the present invention is that in step 2, the process of obtaining the degree of decomposition of the plastic before and after plastic degradation by using the weight loss method includes:

[0034] Use a milligram-level electronic scale to weigh the weight of the control group culture medium on the first day, and then weigh the weight of the experimental group culture medium on the first, seventh, and 28th days. The weight loss rate is used to describe the degree of plastic decomposition. The calculation process is as follows:

[0035]

[0036] Among them, G0 is the weight loss rate, G i is the weight of the culture medium of the control group on day 1, i.e. the initial weight, G j is the weight of the culture medium in the experimental group, j=1, 2, 3, that is, the remaining weight.

[0037] A further improvement of the technical solution of the present invention is that in step 3, the process of obtaining a curve diagram of the relationship between the peak intensity ratio and the degree of plastic decomposition from the Raman spectrum using the peak intensity ratio method includes:

[0038] The characteristic peak intensity I in the Raman spectrum of the experimental group was measured using GRAMS spectral analysis software exp The characteristic peak intensity I in the Raman spectrum of the control group con , calculate the peak intensity ratio R by the formula:

[0039]

[0040] Draw a two-dimensional coordinate system with the plastic decomposition degree as the horizontal coordinate and the peak intensity ratio as the vertical coordinate, and use Origin software to perform curve fitting to obtain m=a 0 t+b 0 The fitting curve of 0 and b 0 is the fitting coefficient, m is the peak intensity ratio, t is the degree of plastic decomposition, and a curve graph showing the relationship between the peak intensity ratio and the degree of plastic decomposition is obtained.

[0041] A further improvement of the technical solution of the present invention is that in step 4, the process of constructing an evaluation model for marine microbial degradation of plastics using a random forest algorithm includes:

[0042] The peak intensity ratio of each sample and its corresponding plastic decomposition degree were used as the data set. 60% of the data set was divided into a training set, 20% into a test set, and 20% into a validation set. The number of decision trees for the random forest model was determined to be 100, with a maximum depth of 3. The model was trained using the training set.

[0043] During the training process, a subset of training data was extracted from the training set. When constructing each tree, the feature was selected from the corresponding peak intensity ratio feature according to the degree of plastic decomposition as the split point. Each tree grew once it split until it reached the set maximum depth of 3, thus constructing a preliminary random forest model.

[0044] The validation set was used to verify the fit of the relationship between the output peak intensity ratio and the degree of plastic decomposition. The mean square error (MSE) was used to calculate the error between the model prediction result and the actual degree of plastic decomposition. The model parameters were adjusted until the error was within the preset range. The test set was used to evaluate the random forest model after verification and parameter adjustment, and the generalization ability of the model was evaluated to obtain an assessment model for marine microbial degradation of plastics.

[0045] A further improvement of the technical solution of the present invention is that in step 5, the process of analyzing the peak intensity ratio of the Raman spectrum and transmitting the evaluation result to the client includes:

[0046] The marine microbial degradation plastic assessment model is deployed into the system, and the peak intensity ratio corresponding to the Raman spectrum is input;

[0047] The marine microbial degradation plastic assessment model outputs the corresponding degree of plastic decomposition and wirelessly transmits the assessment results to the client, which then intervenes and processes them.

[0048] Beneficial effects of the present invention: Compared with the conventional Raman spectroscopy-based quantitative analysis and evaluation method for microbial degradation of plastics, the present invention closely combines the gravity sampling technology, culture medium microbial technology, Raman spectroscopy acquisition technology, and Raman spectroscopy processing technology in the system with modern information technology, accurately captures the sample peak intensity ratio, and achieves real-time and comprehensive monitoring of the degree of plastic degradation by microorganisms. The Raman spectroscopy baseline correction and spectral smoothing data preprocessing are used to obtain the fitting relationship curve between the sample peak intensity ratio and the degree of plastic decomposition. The corresponding degree of plastic decomposition is accurately obtained by calculation, and combined with the random forest model, A marine microbial plastic degradation assessment model was constructed to monitor the degradation of microorganisms in real time, solving the problem that there is no unified standard method based on Raman spectroscopy for assessing the degree of microbial degradation of plastics in complex marine microbial communities. Microbial degradation of plastics is a dynamic process, and the monitoring and data processing of Raman spectra also face challenges. The method of the present invention ensures that the quantitative analysis and assessment standards of microbial degradation of plastics using Raman spectroscopy technology can be refined within a more precise range, making the monitored data a more accurate indicator under the same conditions. The development and application of this method have significantly enhanced the level of intelligence in the quantitative analysis and assessment process of microbial degradation of plastics using Raman spectroscopy technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0050] Figure 1 This is a flow chart of a method for quantitative analysis and evaluation of microbial degradation of plastics based on Raman spectroscopy technology of the present invention;

[0051] Figure 2 This is the Raman spectrum of the PET standard sample;

[0052] Figure 3 The Raman peak of PET represents the crystalline phase, 1095 cm -1 and the Raman peak of the amorphous phase is 1117 cm -1 Schematic diagram of the fitting;

[0053] Figure 4 This is a quantitative characterization relationship diagram of the crystallinity of PET after degradation in different time periods. DETAILED DESCRIPTION

[0054] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are 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.

[0055] like Figure 1 As shown, the present invention provides a method for quantitative analysis and evaluation of microbial degradation of plastics based on Raman spectroscopy technology, comprising the following steps:

[0056] Step 1: Collect marine sediment samples and samples of plastic to be decomposed, prepare experimental group culture medium and control group culture medium for evaluating the degree of plastic decomposition, and use Raman spectrometer to obtain Raman spectra of the experimental group and the control group;

[0057] Step 2: Baseline correction and spectrum smoothing are performed on the Raman spectra of the experimental group and the control group; the degree of plastic decomposition before and after plastic degradation is obtained using the weight loss method;

[0058] Step 3, using the peak intensity ratio method to obtain a curve diagram showing the relationship between the peak intensity ratio and the degree of plastic decomposition from the Raman spectrum;

[0059] Step 4: Use the random forest algorithm to build an assessment model for marine microbial degradation of plastics;

[0060] Step 5: Analyze the peak intensity ratio of the Raman spectrum and transmit the evaluation result to the client.

[0061] In step 1, the process of collecting microbial samples from marine sediments and samples of plastic to be decomposed includes:

[0062] Place the gravity sampler in the seawater, let it sink to the seabed sediment layer by gravity, and collect microbial samples from the marine sediments; collect plastic waste from the sea surface and the seashore, use scissors to cut it into 1mm plastic fragments, and obtain plastic samples to be decomposed.

[0063] In step 1, the process of preparing the experimental group culture medium and the control group culture medium for evaluating the degree of plastic decomposition includes:

[0064] A1. Prepare seawater culture medium and water culture medium, sterilize them at high temperature, cool the sterilized seawater culture medium and water culture medium to 45° C., and dispense them into sterile containers of the same size for standby use;

[0065] A2. Dilute and homogenize the collected marine sediment samples, use a centrifuge to remove large particles of impurities in the marine microbial suspension, retain the suspended microbial cells, and obtain a uniformly distributed marine microbial sample suspension; place the plastic sample to be decomposed in a high-pressure sterilizer and place it at 121°C for 15 minutes to obtain a sterile plastic sample;

[0066] A3. Take 100 ml of seawater culture medium, add 1 ml of marine microbial suspension, put sterile plastic fragments into the culture medium, and obtain the experimental group for evaluating the degree of microbial decomposition; take 100 ml of clean water culture medium, put sterile plastic samples, and obtain the control group for evaluating the degree of microbial decomposition;

[0067] A4. The experimental group for evaluating the degree of microbial decomposition and the control group were cultured under the same environmental conditions.

[0068] In step 1, the process of obtaining the Raman spectra of the experimental group and the Raman spectra of the control group using a Raman spectrometer includes:

[0069] Turn on the Raman spectrometer and preheat the instrument for 30 minutes. Adjust the parameters of the Raman spectrometer according to the standard sample silicon wafer at 520.7 cm -1 There is a sharp and high-intensity Raman peak at the center. The Raman spectrometer was calibrated using a silicon wafer sample. The culture medium of the experimental group after 1 day, 7 days, and 28 days of culture was placed in the sample chamber of the Raman spectrometer. Five spectra were collected for the plastic fragments in the culture medium of the experimental group and the culture medium of the control group, respectively. The spectral data of each spectrum collection was recorded, and the spectral data included Raman shift and Raman scattered light intensity. After the collection was completed, the spectral data collected five times were averaged to obtain Raman spectra of the experimental group and the control group.

[0070] In step 2, the process of performing baseline correction on the Raman spectra of the experimental group and the Raman spectra of the control group includes:

[0071] B1. Using Haar wavelet transform, select three decomposition layers, discretize the Raman shift-Raman scattered light intensity data of the Raman spectra of the experimental group and the control group, and set the Raman shift range to [x 1 , x n ], the Raman scattered light intensity is y = [y 1 ,y 2 , ..., y n ];

[0072] B2. The first-level decomposition calculation process is as follows:

[0073]

[0074] Where k is a discrete index and the approximate function cA1 is the low-frequency information of the spectrum, including the smooth part of the signal and the baseline information, and the detail function cD 1 It is the high-frequency information of the spectrum, including characteristic peaks and noise;

[0075] B3, the second level decomposition is the approximate coefficient cA obtained by the first level decomposition 1 As the input signal, repeat the above decomposition process to calculate cA 2 and cD 2 The third level decomposition is the approximate coefficient cA obtained by the second level decomposition 2 As input signal, calculate and obtain cA 3 and cD 3；

[0076] B4. According to the actual spectral characteristics and noise level, set a threshold T and approximate function cA j If the absolute value of [k] is less than T, it is set to zero. The baseline coefficient can be removed by trying different thresholds and observing the effect of the corrected spectrum;

[0077] B5. Use the redundant coefficients to reconstruct the spectrum. The process of reconstructing the spectrum according to the reconstruction formula of wavelet decomposition is as follows:

[0078]

[0079] Wherein, y′ is the reconstructed spectral data. The approximate coefficients obtained in the above process are substituted to obtain the Raman spectra of the experimental group and the Raman spectra of the control group after removing the baseline.

[0080] In step 2, the process of performing spectral smoothing on the Raman spectra of the experimental group and the Raman spectra of the control group includes:

[0081] Using Savitzky-Go, we selected a window size of 7 and a second-order polynomial, and for each data point y of the Raman spectra of the experimental group and the control group i , take this data point as the center and select y i-3 ,y i-2 ,y i ,y i+1 ,y i+2 ,y i+3 For the data points within the seven window sizes, a second-order polynomial is fitted to the seven data points, and the fitting polynomial is set to p(x)=a 0 +a 1 x+a 2 x 2 , by determining the coefficients a of the polynomial least squares method 0 , a 1 , a 2, so that the error between the fitting polynomial and the selected data points is minimized. The error calculation process is as follows:

[0082]

[0083] Through the above calculation results, the characteristic peaks and background noise before and after the spectrum smoothing are compared. The more prominent the characteristic peaks are, the lower the background noise is, and the better the smoothing effect is. The window size is adjusted according to the comparison results to obtain the Raman spectra of the experimental group and the control group after the spectrum smoothing.

[0084] In step 2, the process of obtaining the degree of plastic decomposition before and after plastic degradation using the weight loss method includes:

[0085] Use a milligram-level electronic scale to weigh the weight of the control group culture medium on the first day, and then weigh the weight of the experimental group culture medium on the first, seventh, and 28th days. The weight loss rate is used to describe the degree of plastic decomposition. The calculation process is as follows:

[0086]

[0087] Among them, G0 is the weight loss rate, G i is the weight of the culture medium of the control group on day 1, i.e. the initial weight, G j is the weight of the culture medium in the experimental group, j=1, 2, 3, that is, the remaining weight.

[0088] In step 3, the process of obtaining a curve diagram of the relationship between the peak intensity ratio and the degree of plastic decomposition from the Raman spectrum using the peak intensity ratio method includes:

[0089] The characteristic peak intensity I in the Raman spectrum of the experimental group was measured using GRAMS spectral analysis software exp The characteristic peak intensity I in the Raman spectrum of the control group con , calculate the peak intensity ratio R by the formula:

[0090]

[0091] Draw a two-dimensional coordinate system with the plastic decomposition degree as the horizontal coordinate and the peak intensity ratio as the vertical coordinate, and use Origin software to perform curve fitting to obtain m=a 0 t+b 0 The fitting curve of 0 and b 0 is the fitting coefficient, m is the peak intensity ratio, t is the degree of plastic decomposition, and a curve graph showing the relationship between the peak intensity ratio and the degree of plastic decomposition is obtained.

[0092] In step 4, the process of constructing a marine microbial degradation plastic assessment model using the random forest algorithm includes:

[0093] The peak intensity ratio of each sample and its corresponding plastic decomposition degree were used as the data set. 60% of the data set was divided into a training set, 20% into a test set, and 20% into a validation set. The number of decision trees for the random forest model was determined to be 100, with a maximum depth of 3. The model was trained using the training set.

[0094] During the training process, a subset of training data was extracted from the training set. When constructing each tree, the feature was selected from the corresponding peak intensity ratio feature according to the degree of plastic decomposition as the split point. Each tree grew once it split until it reached the set maximum depth of 3, thus constructing a preliminary random forest model.

[0095] The validation set was used to verify the fit of the relationship between the output peak intensity ratio and the degree of plastic decomposition. The mean square error (MSE) was used to calculate the error between the model prediction result and the actual degree of plastic decomposition. The model parameters were adjusted until the error was within the preset range. The test set was used to evaluate the random forest model after verification and parameter adjustment, and the generalization ability of the model was evaluated to obtain an assessment model for marine microbial degradation of plastics.

[0096] In step 5, the process of analyzing the peak intensity ratio of the Raman spectrum and transmitting the evaluation result to the client includes:

[0097] The marine microbial degradation plastic assessment model is deployed into the system, and the peak intensity ratio corresponding to the Raman spectrum is input;

[0098] The marine microbial degradation plastic assessment model outputs the corresponding degree of plastic decomposition and wirelessly transmits the assessment results to the client, which then intervenes and processes them.

[0099] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A quantitative analysis and evaluation method for microbial degradation of plastics based on Raman spectroscopy technology, comprising the following steps: Step 1: Collect marine sediment samples and samples of plastic to be decomposed, prepare experimental group culture medium and control group culture medium for evaluating the degree of plastic decomposition, and use Raman spectrometer to obtain Raman spectra of the experimental group and the control group; Step 2: Baseline correction and spectrum smoothing are performed on the Raman spectra of the experimental group and the Raman spectra of the control group; Using the weight loss method, the degree of plastic decomposition before and after plastic degradation was obtained; Step 3, using the peak intensity ratio method to obtain a curve diagram showing the relationship between the peak intensity ratio and the degree of plastic decomposition from the Raman spectrum; Step 4: Use the random forest algorithm to build an assessment model for marine microbial degradation of plastics; Step 5: Analyze the peak intensity ratio of the Raman spectrum and transmit the evaluation result to the client.

2. The method for quantitative analysis and evaluation of microbial degradation of plastics based on Raman spectroscopy according to claim 1, characterized in that: In step 1, the process of collecting microbial samples from marine sediments and samples of plastic to be decomposed includes: Place the gravity sampler in the seawater and let it sink to the seabed sediment layer by gravity to collect microbial samples from the marine sediments; Collect plastic waste from the sea surface and the beach, use scissors to cut it into 1mm plastic fragments, and obtain plastic samples to be decomposed.

3. The method for quantitative analysis and evaluation of microbial degradation of plastics based on Raman spectroscopy according to claim 2, characterized in that: In the step 1, the process of preparing the experimental group culture medium and the control group culture medium for evaluating the degree of plastic decomposition includes: A1. Prepare seawater culture medium and water culture medium, sterilize them at high temperature, cool the sterilized seawater culture medium and water culture medium to 45° C., and dispense them into sterile containers of the same size for standby use; A2. Dilute and homogenize the collected marine sediment samples, use a centrifuge to remove large particles of impurities in the marine microbial suspension, retain the suspended microbial cells, and obtain a uniformly distributed marine microbial sample suspension; place the plastic sample to be decomposed in a high-pressure sterilizer and place it at 121°C for 15 minutes to obtain a sterile plastic sample; A3. Take 100 ml of seawater culture medium, add 1 ml of marine microbial suspension, put sterile plastic fragments into the culture medium, and obtain the experimental group for evaluating the degree of microbial decomposition; take 100 ml of clean water culture medium, put sterile plastic samples, and obtain the control group for evaluating the degree of microbial decomposition; A4. The experimental group for evaluating the degree of microbial decomposition and the control group were cultured under the same environmental conditions.

4. The method for quantitative analysis and evaluation of microbial degradation of plastics based on Raman spectroscopy according to claim 3, characterized in that: In the step 1, the process of obtaining the Raman spectra of the experimental group and the Raman spectra of the control group using a Raman spectrometer includes: Turn on the Raman spectrometer and preheat the instrument for 30 minutes. Adjust the parameters of the Raman spectrometer according to the standard sample silicon wafer at 520.7 cm -1 There is a sharp and high-intensity Raman peak at the center. The Raman spectrometer was calibrated using a silicon wafer sample. The culture medium of the experimental group after 1 day, 7 days, and 28 days of culture was placed in the sample chamber of the Raman spectrometer. Five spectra were collected for the plastic fragments in the culture medium of the experimental group and the culture medium of the control group, respectively. The spectral data of each spectrum collection was recorded, and the spectral data included Raman shift and Raman scattered light intensity. After the collection was completed, the spectral data collected five times were averaged to obtain Raman spectra of the experimental group and the control group.

5. The method for quantitative analysis and evaluation of microbial degradation of plastics based on Raman spectroscopy according to claim 4, characterized in that: In the step 2, the process of performing baseline correction processing on the Raman spectra of the experimental group and the Raman spectra of the control group includes: B1. Using Haar wavelet transform, select three decomposition layers, discretize the Raman shift-Raman scattered light intensity data of the Raman spectra of the experimental group and the control group, and set the Raman shift range to [x1, x n ], the Raman scattered light intensity is y = [y1, y2, ..., y n ]; B2. The first-level decomposition calculation process is as follows: Among them, k is a discrete index, the approximate function cA1 is the low-frequency information of the spectrum, including the smooth part of the signal and the baseline information, and the detail function cD1 is the high-frequency information of the spectrum, including the characteristic peak and noise; B3, the second-level decomposition uses the approximate coefficient cA1 obtained by the first-level decomposition as the input signal, repeats the above decomposition process, calculates cA2 and cD2, and the third-level decomposition uses the approximate coefficient cA2 obtained by the second-level decomposition as the input signal, calculates and obtains cA3 and cD3; B4. According to the actual spectral characteristics and noise level, set a threshold T and approximate function cA j If the absolute value of [k] is less than T, it is set to zero. The baseline coefficient can be removed by trying different thresholds and observing the effect of the corrected spectrum; B5. Use the redundant coefficients to reconstruct the spectrum. The process of reconstructing the spectrum according to the reconstruction formula of wavelet decomposition is as follows: Where y' is the reconstructed spectral data. Substitute the approximate coefficients to obtain the Raman spectra of the experimental group and the control group after removing the baseline.

6. The method for quantitative analysis and evaluation of microbial degradation of plastics based on Raman spectroscopy according to claim 5, characterized in that: In the step 2, the process of performing spectral smoothing on the Raman spectrum of the experimental group and the Raman spectrum of the control group includes: Using Savitzky-Go, we selected a window size of 7 and a second-order polynomial, and for each data point y of the Raman spectra of the experimental group and the control group i , take this data point as the center and select y i-3 ,y i-2 ,y i ,y i+1 ,y i+2 ,y i+3 For the data points within the seven window sizes, a second-order polynomial is fitted for the seven data points, and the fitting polynomial is set to p(x)=a0+a1x+a2x 2 , by determining the coefficients a0, a1, a2 of the polynomial least squares method, the error between the fitting polynomial and the selected data point is minimized. The calculation process of the error is as follows: Through the above calculation results, the characteristic peaks and background noise before and after the spectrum smoothing are compared, the smoothing effect is analyzed, the window size is adjusted according to the comparison results, and the Raman spectra of the experimental group and the control group after the spectrum smoothing are obtained.

7. The method for quantitative analysis and evaluation of microbial degradation of plastics based on Raman spectroscopy according to claim 6, characterized in that: In step 2, the process of obtaining the degree of plastic decomposition before and after plastic degradation by using the weight loss method includes: Use a milligram-level electronic scale to weigh the weight of the control group culture medium on the first day, and then weigh the weight of the experimental group culture medium on the first day, the seventh day, and the 28th day. The weight loss rate is used to describe the degree of plastic decomposition. The calculation process is as follows: Among them, G0 is the weight loss rate, G i is the weight of the culture medium of the control group on day 1, i.e. the initial weight, G j is the weight of the culture medium in the experimental group, j=1, 2, 3, that is, the remaining weight.

8. The method for quantitative analysis and evaluation of microbial degradation of plastics based on Raman spectroscopy according to claim 7, characterized in that: In the step 3, the process of obtaining a curve diagram of the relationship between the peak intensity ratio and the degree of plastic decomposition from the Raman spectrum using the peak intensity ratio method includes: The characteristic peak intensity I in the Raman spectrum of the experimental group was measured using GRAMS spectral analysis software exp The characteristic peak intensity I in the Raman spectrum of the control group con , calculate the peak intensity ratio R by the formula: Draw a two-dimensional coordinate system with the degree of plastic decomposition as the horizontal coordinate and the peak intensity ratio as the vertical coordinate. Use Origin software to perform curve fitting to obtain the fitting curve of m=a0t+b0, where a0 and b0 are fitting coefficients, m is the peak intensity ratio, and t is the degree of plastic decomposition. Obtain a curve graph of the relationship between the peak intensity ratio and the degree of plastic decomposition.

9. The method for quantitative analysis and evaluation of microbial degradation of plastics based on Raman spectroscopy according to claim 8, characterized in that: In step 4, the process of constructing a marine microbial degradation plastic assessment model using a random forest algorithm includes: The peak intensity ratio of each sample and its corresponding plastic decomposition degree were used as the data set. 60% of the data set was divided into a training set, 20% into a test set, and 20% into a validation set. The number of decision trees for the random forest model was determined to be 100, with a maximum depth of 3. The model was trained using the training set. During the training process, a subset of training data was extracted from the training set. When constructing each tree, the feature was selected from the corresponding peak intensity ratio feature according to the degree of plastic decomposition as the split point. Each tree grew once it split until it reached the set maximum depth of 3, thus constructing a preliminary random forest model. The fitting degree of the relationship between the output peak intensity ratio and the degree of plastic decomposition was verified through the validation set, and the error between the model prediction result and the actual degree of plastic decomposition was calculated using the mean square error (MSE). The model parameters were adjusted until the error was controlled within the preset range. The random forest model after validation and parameter adjustment was evaluated using the test set to evaluate the generalization ability of the model and obtain an evaluation model for the degradation of plastic by marine microorganisms.

10. The method for quantitative analysis and evaluation of microbial degradation of plastics based on Raman spectroscopy according to claim 9, characterized in that: In step 5, the process of analyzing the peak intensity ratio of the Raman spectrum and transmitting the evaluation result to the client includes: The marine microbial degradation plastic assessment model is deployed into the system, and the peak intensity ratio corresponding to the Raman spectrum is input; The marine microbial degradation plastic assessment model outputs the corresponding degree of plastic decomposition and wirelessly transmits the assessment results to the client, which then intervenes and processes them.

Images