A microplastic rapid detection method and system based on spectral analysis technology

Abstract

The application discloses a microplastic rapid detection method and system based on a spectrum analysis technology, through development of vacuum filtration and density gradient centrifugation means, efficient separation and concentration of samples are realized; meanwhile, an automatic sample processing system is constructed, automatic equipment of filtering, digestion and separation steps is integrated, and time consumption of manual operation is reduced; in addition, based on a rapid screening technology of Nile red fluorescence dyeing, through specific fluorescent labeling of hydrophobic microplastics, microplastics are quickly positioned by using a fluorescence microscope, manual screening time is reduced, and detection efficiency is improved.

Description

Technical Field

[0001] This invention relates to the field of detection technology, and more specifically, to a rapid detection method and system for microplastics based on spectral analysis technology. Background Technology

[0002] Microplastics, as a new type of environmental pollutant, have been widely detected in oceans, freshwater, soil, and even the atmosphere worldwide. Due to their small size, large specific surface area, ease of adsorbing persistent organic pollutants and heavy metals, and ability to be ingested by organisms and thus transferred along the food chain, the potential risks posed by microplastic pollution to ecosystems and human health are increasingly attracting serious concern from the international community. Therefore, establishing rapid, accurate, and efficient methods for detecting microplastics is crucial for environmental monitoring, risk assessment, and pollution control. Summary of the Invention

[0003] To address at least one of the aforementioned technical problems, the present invention aims to provide a rapid detection method and system for microplastics based on spectral analysis technology, which can quickly detect the microplastic content in water samples.

[0004] The first aspect of this invention provides a rapid detection method for microplastics based on spectral analysis technology, comprising:

[0005] A water sample is obtained flowing through the sample cell, and the water sample is homogenized to obtain a pretreated water sample.

[0006] Based on a pre-set vacuum filtration device, the pre-treated water sample is filtered, and the residue on the filter membrane is collected.

[0007] The residue was mixed with a preset density gradient solution and subjected to density gradient centrifugation. The microplastic particles in the supernatant were collected to obtain the initial microplastic particles.

[0008] The initial microplastic particles were reacted with a pre-set Nile Red fluorescent dye solution to perform specific fluorescent labeling, resulting in fluorescently labeled microplastics.

[0009] Fluorescently labeled microplastics were rapidly located and imaged using a fluorescence microscope to obtain their spectral patterns.

[0010] Spectral analysis was performed on the spectral images of microplastics to estimate the number of microplastic particles in the corresponding water sample. The concentration of microplastic particles in the corresponding water sample was obtained by dividing the number of microplastic particles by the volume of the corresponding water sample.

[0011] If the concentration of microplastics in the water sample exceeds the preset concentration threshold, an alarm message will be triggered.

[0012] In this scheme, the density gradient solution used for density gradient centrifugation has a density range of [missing information]. The centrifugal force of density gradient centrifugation is Centrifugation time is 10-30 minutes.

[0013] In this scheme, the concentration of the Nile Red fluorescent dye solution is: The reaction temperature is The reaction time is 5-15 minutes; the fluorescence microscope uses a blue light excitation source with an excitation wavelength of [wavelength missing]. The emitted light wavelength range is .

[0014] In this solution, the pore size of the filter membrane is... The filter membrane material is polycarbonate, nitrocellulose, or glass fiber, and the vacuum filtration pressure is [insert pressure here]. .

[0015] In this solution, after collecting the residue on the filter membrane, the method further includes:

[0016] The residue is subjected to acid digestion using a pre-set first acidic solution to obtain the acid-digested residue; the pre-set first acidic solution is nitric acid or hydrogen peroxide, and its concentration is [missing information]. The acid digestion temperature is The digestion time is 10-20 minutes;

[0017] The residue after acid digestion is digested using a pre-defined protease or lipase to obtain the digested residue; the concentration of the pre-defined protease or lipase is [missing information]. The enzyme digestion temperature is The digestion time is 20-40 minutes.

[0018] In this scheme, the step of performing spectral analysis on the spectral image of microplastics to estimate the number of microplastic particles in the corresponding water sample specifically includes:

[0019] Extract the fluorescence intensity of each pixel in the spectral image of the microplastic;

[0020] Determine whether the fluorescence intensity of the pixel is greater than a preset fluorescence intensity threshold. If yes, save the fluorescence intensity of the pixel; otherwise, set the fluorescence intensity of the pixel to zero and mark the pixel as the background.

[0021] The spectral image of the microplastic is segmented based on a preset fluorescence intensity threshold to obtain the segmented spectral image;

[0022] Connectivity analysis was performed on the segmented spectral image to obtain the number of connected components, and the number of connected components was set as the value of the number of microplastic particles in the water sample.

[0023] In this scheme, the step of performing connected component analysis on the segmented spectral image to obtain the number of connected components specifically includes:

[0024] By traversing each pixel in the segmented spectral image, pixels belonging to the same connected region are assigned the same unique label, resulting in multiple independent connected regions.

[0025] Extract the regional attribute features and corresponding feature values ​​of any independent connected component. The regional attribute feature values ​​of the connected component include at least the area value, perimeter value, principal axis length value, and secondary axis length value.

[0026] Determine if the area value of a connected component is within a preset area value range. If it is, retain the corresponding connected component; otherwise, delete the corresponding connected component.

[0027] Determine the circularity and elongation of the corresponding connected region based on the area, perimeter, principal axis length, and secondary axis length values.

[0028] If the circularity of a connected component is within a preset circularity range and the elongation of the connected component is greater than a preset elongation threshold, then the corresponding connected component will be saved.

[0029] After traversing all independent connected components, the remaining connected components are obtained, and the number of corresponding connected components is counted.

[0030] A second aspect of the present invention provides a rapid detection system for microplastics based on spectral analysis technology, comprising: a water sample extraction module, a vacuum filtration module, a density gradient centrifugation module, a labeling module, a positioning and imaging module, and a spectral analysis module;

[0031] The water sample extraction module is used to collect water samples flowing through the sample pool and homogenize the water samples to obtain pre-treated water samples.

[0032] The vacuum filtration module includes a vacuum filtration device for filtering the pretreated water sample and collecting the residue on the filter membrane.

[0033] The density gradient centrifugation module is used to mix the residue with a preset density gradient solution, perform density gradient centrifugation separation, collect the microplastic particles in the supernatant, and obtain the initial microplastic particles.

[0034] The labeling module is used to react the initial microplastic particles with a preset Nile Red fluorescent dye solution to perform specific fluorescent labeling, thereby obtaining fluorescently labeled microplastics.

[0035] The positioning and imaging module is used to quickly locate and image fluorescently labeled microplastics using a fluorescence microscope to obtain spectral patterns of the microplastics.

[0036] The spectral analysis module is used to perform spectral analysis on the spectral image of microplastics, estimate the number of microplastic particles in the corresponding water sample, divide the number of microplastic particles in the corresponding water sample by the volume of the corresponding water sample to obtain the microplastic concentration value of the water sample, and if the microplastic concentration value of the water sample is greater than a preset concentration threshold, an alarm message is triggered.

[0037] In this scheme, the density gradient solution used for density gradient centrifugation has a density range of [missing information]. The centrifugal force of density gradient centrifugation is Centrifugation time is 10-30 minutes.

[0038] In this scheme, the concentration of the Nile Red fluorescent dye solution is: The reaction temperature is The reaction time is 5-15 minutes; the fluorescence microscope uses a blue light excitation source with an excitation wavelength of [wavelength missing]. The emitted light wavelength range is .

[0039] One or more technical solutions proposed in this application have at least the following technical effects:

[0040] By developing vacuum filtration and density gradient centrifugation techniques, efficient sample separation and concentration are achieved. Simultaneously, an automated sample processing system is constructed, integrating automated equipment for filtration, digestion, and separation steps to reduce manual operation time. Furthermore, a rapid screening technique based on Nile Red fluorescent staining is employed, using fluorescence microscopy to quickly locate hydrophobic microplastics through specific fluorescent labeling, reducing manual screening time and improving detection efficiency. Multi-directional analysis of connected domains further enhances the accuracy of microplastic particle identification. Attached Figure Description

[0041] Figure 1 A flowchart of a rapid detection method for microplastics based on spectral analysis technology according to the present invention is shown;

[0042] Figure 2 A block diagram of a rapid microplastic detection system based on spectral analysis technology according to the present invention is shown. Detailed Implementation

[0043] To better understand the above-mentioned objectives, features, and advantages of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that, unless otherwise specified, the embodiments and features described in these embodiments can be combined with each other.

[0044] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and therefore the scope of protection of the invention is not limited to the specific embodiments disclosed below.

[0045] Figure 1 A flowchart of a rapid detection method for microplastics based on spectral analysis technology according to the present invention is shown.

[0046] like Figure 1 As shown, this invention discloses a rapid detection method for microplastics based on spectral analysis technology, comprising:

[0047] S101, Obtain a water sample flowing through the sample cell, and homogenize the water sample to obtain a pretreated water sample;

[0048] S102, based on a preset vacuum filtration device, filters the pretreated water sample and collects the residue on the filter membrane;

[0049] S103, mix the residue with a preset density gradient solution, perform density gradient centrifugation, collect the microplastic particles in the supernatant, and obtain the initial microplastic particles.

[0050] S104, the initial microplastic particles are reacted with a pre-set Nile Red fluorescent dye solution to perform specific fluorescent labeling, and fluorescently labeled microplastics are obtained;

[0051] S105, using a fluorescence microscope to quickly locate and image fluorescently labeled microplastics, obtaining the spectral pattern of the microplastics;

[0052] S106, Perform spectral analysis on the spectral image of microplastics, estimate the number of microplastic particles in the corresponding water sample, and divide the number of microplastic particles in the corresponding water sample by the volume of the corresponding water sample to obtain the microplastic concentration value of the water sample.

[0053] S107, If the microplastic concentration of the water sample is greater than the preset concentration threshold, an alarm message will be triggered.

[0054] According to an embodiment of the present invention, homogenizing the water sample converts it into a homogeneous liquid suitable for subsequent instrument analysis, removes large particulate impurities to prevent clogging of the subsequent filtration device; then, the pretreated water sample is filtered by a vacuum filtration device to quickly trap a large number of suspended particles in the sample on the filter membrane, achieving concentration from large volume to small volume, and further shortening the total detection time.

[0055] Furthermore, the step of rapidly locating and imaging fluorescently labeled microplastics using a fluorescence microscope to obtain the spectral pattern of the microplastics specifically includes: the stage of the fluorescence microscope, driven by the control system, performs high-speed, field-by-field scanning of the entire filter membrane area carrying the sample according to a pre-programmed checkerboard or serpentine path; at each field of view, the system automatically performs focusing and acquires a high-resolution digital image of the fluorescence channel using a CCD camera; finally, image stitching software seamlessly stitches together the images of all adjacent fields of view to generate a complete panoramic fluorescence image covering the entire filter membrane area; during the scanning and imaging process or after the panoramic image is generated, each field of view or panoramic image is analyzed to identify all suspected fluorescent targets of microplastics and accurately record their pixel coordinates in the panoramic image coordinate system; simultaneously, based on the microscope objective magnification and camera pixel size, the pixel coordinates are converted into mechanical coordinates with the stage as the reference system to form a spectral pattern containing all target position information, thus completing the rapid location and imaging of the fluorescently labeled microplastics.

[0056] According to an embodiment of the present invention, the density gradient solution used in the density gradient centrifugation has a density range of [missing information]. The centrifugal force of density gradient centrifugation is Centrifugation time is 10-30 minutes.

[0057] It should be noted that polypropylene and polyethylene have densities of approximately 0.9-0.98, and are suspended in the low-density region; polyvinyl chloride has a density of approximately 1.3-1.4, and is suspended in the intermediate-density region; polyethylene terephthalate has a density of approximately 1.3-1.4, and is suspended in the intermediate-density region; polytetrafluoroethylene (PTFE) has a density that can reach over 2.0, and will settle in the high-density region. The density gradient solution has a density range of... This ensures coverage of most common microplastics found in water samples. Too low a density will prevent effective separation of high-density plastics, while too high a density may lead to salt precipitation, increasing cost and processing difficulty. The unit of density is... .

[0058] According to an embodiment of the present invention, the concentration of the Nile Red fluorescent dye solution is: The reaction temperature is The reaction time is 5-15 minutes; the fluorescence microscope uses a blue light excitation source with an excitation wavelength of [wavelength missing]. The emitted light wavelength range is .

[0059] It should be noted that the reaction temperature and reaction time are inversely proportional. By strictly controlling the reaction temperature, the diffusion and binding of dye molecules in the Nile Red fluorescent dye solution to the particle surface are enhanced, thereby reducing the time required for rapid detection of microplastics in the corresponding stage. Nile Red's absorption peak is in the blue light region, therefore... It has the highest excitation efficiency; its emitted light is greenish-yellow light, and it is collected... The emitted light can capture the fluorescence signal emitted by the microplastic to the greatest extent, while effectively filtering out excitation light scattering and some background autofluorescence.

[0060] According to an embodiment of the present invention, the pore size of the filter membrane is The filter membrane material is polycarbonate, nitrocellulose, or glass fiber, and the vacuum filtration pressure is [insert pressure here]. .

[0061] It should be noted that the current academic definition of microplastics is usually limited to 1 micrometer. The pore size ensures the capture of submicron-sized plastic particles, improving the accuracy of microplastic particle acquisition. The pressure of vacuum filtration drives the filtration process; too low a pressure results in slow filtration, especially for turbid water samples containing colloids or fine particles, potentially preventing completion within a reasonable time. Too high a pressure may force some elastic microplastic particles (such as PE fibers) to deform and squeeze the filter membrane, or cause the membrane to rupture. Therefore, controlling the vacuum filtration pressure within a certain range is crucial. scope.

[0062] According to an embodiment of the present invention, after collecting the residue on the filter membrane, the method further includes:

[0063] The residue is subjected to acid digestion using a pre-set first acidic solution to obtain the acid-digested residue; the pre-set first acidic solution is nitric acid or hydrogen peroxide, and its concentration is [missing information]. The acid digestion temperature is The digestion time is 10-20 minutes;

[0064] The residue after acid digestion is digested using a pre-defined protease or lipase to obtain the digested residue; the concentration of the pre-defined protease or lipase is [missing information]. The enzyme digestion temperature is The digestion time is 20-40 minutes.

[0065] It should be noted that water samples usually contain a large amount of organic matter, such as plankton, algae, and plant and animal remains. This organic matter can also be non-specifically stained with Nile Red, producing severe fluorescence background interference. Through the digestion step, this organic matter is purposefully removed while inorganic matter and stable microplastics are retained, thereby improving the accuracy of microplastic particle analysis.

[0066] According to an embodiment of the present invention, the step of performing spectral analysis on the spectral image of microplastics to estimate the number of microplastic particles in the corresponding water sample specifically includes:

[0067] Extract the fluorescence intensity of each pixel in the spectral image of the microplastic;

[0068] Determine whether the fluorescence intensity of the pixel is greater than a preset fluorescence intensity threshold. If yes, save the fluorescence intensity of the pixel; otherwise, set the fluorescence intensity of the pixel to zero and mark the pixel as the background.

[0069] The spectral image of the microplastic is segmented based on a preset fluorescence intensity threshold to obtain the segmented spectral image;

[0070] Connectivity analysis was performed on the segmented spectral image to obtain the number of connected components, and the number of connected components was set as the value of the number of microplastic particles in the water sample.

[0071] It should be noted that the preset fluorescence intensity threshold is dynamically determined based on the fluorescence intensity of the background area, and its formula is as follows: ,in This indicates the preset fluorescence intensity threshold. This represents the average fluorescence intensity of the historical background region. It is a constant, and its value ranges from 2 to 3; The standard deviation of fluorescence intensity in the historical background region is used; for example, if this sampling is the fifth sampling, then the fluorescence intensity of the historical background region is the fluorescence intensity of the background region in the first to fourth samplings. If it is the first sampling, then... This represents the initial value of fluorescence intensity, determined experimentally using purified water.

[0072] According to an embodiment of the present invention, the step of performing connected component analysis on the segmented spectral image to obtain the number of connected components specifically includes:

[0073] By traversing each pixel in the segmented spectral image, pixels belonging to the same connected region are assigned the same unique label, resulting in multiple independent connected regions.

[0074] Extract the regional attribute features and corresponding feature values ​​of any independent connected component. The regional attribute feature values ​​of the connected component include at least the area value, perimeter value, principal axis length value, and secondary axis length value.

[0075] Determine if the area value of a connected component is within a preset area value range. If it is, retain the corresponding connected component; otherwise, delete the corresponding connected component.

[0076] Determine the circularity and elongation of the corresponding connected region based on the area, perimeter, principal axis length, and secondary axis length values.

[0077] If the circularity of a connected component is within a preset circularity range and the elongation of the connected component is greater than a preset elongation threshold, then the corresponding connected component will be saved.

[0078] After traversing all independent connected components, the remaining connected components are obtained, and the number of corresponding connected components is counted.

[0079] It should be noted that the step of determining the circularity and elongation of the corresponding connected region based on the area value, perimeter value, principal axis length value, and secondary axis length value specifically includes: setting the circularity to... Its formula is ,in Indicates the circularity of the connected component i. This represents the area of ​​the connected region i. Let E represent the perimeter of the connected region i; let the elongation be E, and its formula is: ,in This represents the length of the connected component i. This represents the length of the principal axis of the connected component i. The secondary axis length represents the length of the connected component i; the primary axis length is the longest dimension contained in the corresponding connected component, and the secondary axis length is the longest dimension perpendicular to the primary axis length.

[0080] According to an embodiment of the present invention, after deleting the corresponding connected component, the method further includes: extracting the area value of the deleted connected component; if the area value of the deleted connected component is less than the minimum value in a preset area value range, then setting the corresponding deleted connected component as a background region; if the area value of the deleted connected component is greater than the maximum value in a preset area value range, then extracting the shape of the corresponding deleted connected component; comparing and analyzing the shape of the deleted connected component with a preset connected component shape to obtain a shape similarity value; if the shape similarity value is less than a preset similarity threshold, then extracting the area of ​​the deleted connected component and dividing the area of ​​the deleted connected component by a preset average area to obtain a first microplastic particle revision value; if the shape similarity value is greater than or equal to the preset similarity threshold, then segmenting the deleted connected component into overlapping regions to obtain a second microplastic particle revision value; adding the first microplastic particle revision value or the second microplastic particle revision value to the corresponding microplastic particle quantity value in the water sample to obtain a revised microplastic particle quantity value.

[0081] It should be noted that the preset average area is the average area of ​​the connected regions preserved in the current water sample; the preset shape of the connected regions is clustered.

[0082] According to an embodiment of the present invention, the step of segmenting the deleted connected components into overlapping regions if the shape similarity value is greater than or equal to a preset similarity threshold specifically includes: extracting each pixel in the deleted connected components, and performing Euclidean distance transformation on the pixels to generate a distance transformation map. The value of each foreground pixel is the Euclidean distance from that point to the nearest background pixel; in the distance transform map Find local maxima in the matrix and use these local maxima to form a seed point set for each sub-particle within the overlapping region. Using the seed point set A as a label, the distance transformation graph is... Perform a watershed transformation to segment the overlapping regions in the deleted connected components, resulting in multiple segmented connected components. Then, extract the area, circularity, and elongation of the segmented connected components. If the segmented connected components meet the corresponding requirements, restore and save the segmented connected components.

[0083] It should be noted that the distance transformation graph mentioned above... The step of finding local maxima involves using a 3x3 or 5x5 sliding window to find the maximum value point within the window, which is the local maximum point; the step of transforming the distance map... The steps for performing the watershed transformation are as follows: the distance transformation map is treated as a topographic map, with high-value areas corresponding to "peaks" and address areas corresponding to "valleys". Water is "injected" starting from each seed point, and the water level gradually rises. When the water from different seeds is about to converge, "watershed" boundaries are established at these locations. This process then divides the overlapping areas in the deleted connected components, resulting in multiple segmented connected components.

[0084] According to an embodiment of the present invention, the method further includes: adding a known quantity of microplastic-free water sample to a known volume V of water sample. Microplastic standard samples; after steps S101-S106, the quantity of recycled microplastic standard samples is obtained. After m repeated experiments, the average recovery rate was obtained. ,in Indicates the number of microplastic standards recovered in multiple repeated experiments. The average value of the estimated number of microplastic particles in the water sample is divided by the average recovery rate to obtain the revised number of microplastic particles, wherein m is greater than or equal to 2.

[0085] Figure 2 A block diagram of a rapid microplastic detection system based on spectral analysis technology according to the present invention is shown.

[0086] like Figure 2 As shown, the second aspect of the present invention provides a rapid detection system for microplastics based on spectral analysis technology, comprising: a water sample extraction module, a vacuum filtration module, a density gradient centrifugation module, a labeling module, a positioning and imaging module, and a spectral analysis module;

[0087] The water sample extraction module is used to collect water samples flowing through the sample pool and homogenize the water samples to obtain pre-treated water samples.

[0088] The vacuum filtration module includes a vacuum filtration device for filtering the pretreated water sample and collecting the residue on the filter membrane.

[0089] The density gradient centrifugation module is used to mix the residue with a preset density gradient solution, perform density gradient centrifugation separation, collect the microplastic particles in the supernatant, and obtain the initial microplastic particles.

[0090] The labeling module is used to react the initial microplastic particles with a preset Nile Red fluorescent dye solution to perform specific fluorescent labeling, thereby obtaining fluorescently labeled microplastics.

[0091] The positioning and imaging module is used to quickly locate and image fluorescently labeled microplastics using a fluorescence microscope to obtain spectral patterns of the microplastics.

[0092] The spectral analysis module is used to perform spectral analysis on the spectral image of microplastics, estimate the number of microplastic particles in the corresponding water sample, divide the number of microplastic particles in the corresponding water sample by the volume of the corresponding water sample to obtain the microplastic concentration value of the water sample, and if the microplastic concentration value of the water sample is greater than a preset concentration threshold, an alarm message is triggered.

[0093] According to an embodiment of the present invention, the vacuum filtration device includes a vacuum pump, a filter membrane support, and a filtrate collector. The vacuum pump provides power, the filter membrane support carries the sample and the filter membrane, and the filtrate collector collects the filtrate, resulting in residue on the filter membrane. The density gradient centrifugation module includes a centrifuge, a density gradient solution separator, and a sample tube. The centrifuge is the core power component. The solution dispenser is key to achieving automation, allowing for precise and repeatable configuration and addition of solutions of different densities to form a gradient, avoiding tedious and difficult-to-standardize manual operations. The sample tube serves as the reaction container.

[0094] In this scheme, the density gradient solution used for density gradient centrifugation has a density range of [missing information]. The centrifugal force of density gradient centrifugation is Centrifugation time is 10-30 minutes.

[0095] In this scheme, the concentration of the Nile Red fluorescent dye solution is: The reaction temperature is The reaction time is 5-15 minutes; the fluorescence microscope uses a blue light excitation source with an excitation wavelength of [wavelength missing]. The emitted light wavelength range is .

[0096] In this solution, the pore size of the filter membrane is... The filter membrane material is polycarbonate, nitrocellulose, or glass fiber, and the vacuum filtration pressure is [insert pressure here]. .

[0097] In this solution, after collecting the residue on the filter membrane, the method further includes:

[0098] The residue is subjected to acid digestion using a pre-set first acidic solution to obtain the acid-digested residue; the pre-set first acidic solution is nitric acid or hydrogen peroxide, and its concentration is [missing information]. The acid digestion temperature is The digestion time is 10-20 minutes;

[0099] The residue after acid digestion is digested using a pre-defined protease or lipase to obtain the digested residue; the concentration of the pre-defined protease or lipase is [missing information]. The enzyme digestion temperature is The digestion time is 20-40 minutes.

[0100] In this scheme, the step of performing spectral analysis on the spectral image of microplastics to estimate the number of microplastic particles in the corresponding water sample specifically includes:

[0101] Extract the fluorescence intensity of each pixel in the spectral image of the microplastic;

[0102] Determine whether the fluorescence intensity of the pixel is greater than a preset fluorescence intensity threshold. If yes, save the fluorescence intensity of the pixel; otherwise, set the fluorescence intensity of the pixel to zero and mark the pixel as the background.

[0103] The spectral image of the microplastic is segmented based on a preset fluorescence intensity threshold to obtain the segmented spectral image;

[0104] Connectivity analysis was performed on the segmented spectral image to obtain the number of connected components, and the number of connected components was set as the value of the number of microplastic particles in the water sample.

[0105] In this scheme, the step of performing connected component analysis on the segmented spectral image to obtain the number of connected components specifically includes:

[0106] By traversing each pixel in the segmented spectral image, pixels belonging to the same connected region are assigned the same unique label, resulting in multiple independent connected regions.

[0107] Extract the regional attribute features and corresponding feature values ​​of any independent connected component. The regional attribute feature values ​​of the connected component include at least the area value, perimeter value, principal axis length value, and secondary axis length value.

[0108] Determine if the area value of a connected component is within a preset area value range. If it is, retain the corresponding connected component; otherwise, delete the corresponding connected component.

[0109] Determine the circularity and elongation of the corresponding connected region based on the area, perimeter, principal axis length, and secondary axis length values.

[0110] If the circularity of a connected component is within a preset circularity range and the elongation of the connected component is greater than a preset elongation threshold, then the corresponding connected component will be saved.

[0111] After traversing all independent connected components, the remaining connected components are obtained, and the number of corresponding connected components is counted.

[0112] This invention discloses a rapid detection method and system for microplastics based on spectral analysis technology. It achieves efficient sample separation and concentration through the development of vacuum filtration and density gradient centrifugation. Simultaneously, it constructs an automated sample processing system, integrating automated equipment for filtration, digestion, and separation steps, reducing manual operation time. Furthermore, based on Nile Red fluorescent staining, a rapid screening technology is employed. By specifically fluorescently labeling hydrophobic microplastics, microplastics can be quickly located using a fluorescence microscope, reducing manual screening time and improving detection efficiency.

[0113] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods, such as: multiple units or components can be combined, or integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed can be through some interfaces, and the indirect coupling or communication connection between devices or units can be electrical, mechanical, or other forms.

[0114] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units. They may be located in one place or distributed across multiple network units. Some or all of the units may be selected to achieve the purpose of this embodiment according to actual needs.

[0115] In addition, in the various embodiments of the present invention, each functional unit can be integrated into one processing unit, or each unit can be a separate unit, or two or more units can be integrated into one unit; the integrated unit can be implemented in hardware or in the form of hardware plus software functional units.

[0116] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0117] Alternatively, if the integrated units of this invention are implemented as software functional modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of this invention, or the parts that contribute to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, ROM, RAM, magnetic disks, or optical disks.

Claims

1. A method for rapid detection of microplastics based on spectroscopic analysis technology, characterized in that, The method comprises the following steps: acquiring a water sample flowing through a sample cell and homogenizing the water sample to obtain a pretreated water sample; filtering the pretreated water sample based on a preset vacuum filtration device to collect residues on a filter membrane; mixing the residues with a preset density gradient solution to perform density gradient centrifugal separation, collecting microplastic particles in supernatant to obtain initial microplastic particles; reacting the initial microplastic particles with a preset Nile red fluorescent dye solution to perform specific fluorescent labeling to obtain fluorescently labeled microplastics; rapidly positioning and imaging the fluorescently labeled microplastics by a fluorescence microscope to obtain a spectral image of the microplastics; performing spectral analysis on the spectral image of the microplastics to estimate a number value of microplastic particles in the corresponding water sample, and dividing the number value of the microplastic particles in the corresponding water sample by a volume of the corresponding water sample to obtain a microplastic concentration value of the water sample; if the microplastic concentration value of the water sample is greater than a preset concentration threshold, triggering an alarm information; the step of performing spectral analysis on the spectral image of the microplastics to estimate the number value of the microplastic particles in the corresponding water sample specifically comprises: extracting a fluorescence intensity of each pixel point in the spectral image of the microplastics; judging whether the fluorescence intensity of the pixel point is greater than a preset fluorescence intensity threshold, if yes, saving the fluorescence intensity of the pixel point, if no, setting the fluorescence intensity of the pixel point to zero and marking the pixel point as background; segmenting the spectral image of the microplastics based on the preset fluorescence intensity threshold to obtain a segmented spectral image; performing connected domain analysis on the segmented spectral image to obtain a number of connected domains and setting the number of connected domains as the number value of the microplastic particles in the water sample; the step of performing connected domain analysis on the segmented spectral image to obtain the number of connected domains specifically comprises: traversing each pixel in the segmented spectral image, assigning the same unique label to the pixels belonging to the same connected region to obtain a plurality of independent connected domains; extracting regional attribute features and corresponding feature values of any one independent connected domain, the regional attribute feature values of the connected domain at least including area value, perimeter value, major axis length value and minor axis length value; judging whether the area value of the connected domain is in a preset area value range, if yes, retaining the corresponding connected domain, if no, deleting the corresponding connected domain; determining the circularity and elongation of the corresponding connected domain according to the area value, perimeter value, major axis length value and minor axis length value; if the circularity of the connected domain is in a preset circularity range and the elongation of the connected domain is greater than a preset elongation threshold, saving the corresponding connected domain; after traversing all independent connected domains, obtaining remaining connected domains and counting the number of the corresponding connected domains; After the corresponding connected domain is deleted, further comprising: extracting the area value of the deleted connected domain, if the area value of the deleted connected domain is less than the minimum value in the preset area value range, the corresponding deleted connected domain is set as a background region; if the area value of the deleted connected domain is greater than the maximum value in the preset area value range, the shape of the corresponding deleted connected domain is extracted; the shape of the deleted connected domain is compared and analyzed with the preset connected domain shape to obtain a shape similarity value; if the shape similarity value is less than a preset similarity threshold value, the area of the deleted connected domain is extracted, and the area of the deleted connected domain is divided by the preset average area to obtain a first microplastic particle revision value; if the shape similarity value is greater than or equal to the preset similarity threshold value, the deleted connected domain is subjected to overlapping region segmentation to obtain a second microplastic particle revision value; the first microplastic particle revision value or the second microplastic particle revision value is added to the microplastic particle quantity value in the corresponding water sample to obtain a revised microplastic particle quantity value; If the shape similarity value is greater than or equal to a preset similarity threshold, the step of performing overlapping region segmentation on the deleted connected domain, specifically comprising: extracting each pixel point in the deleted connected domain, and performing Euclidean distance transformation on the pixel point to generate a distance transformation graph , wherein the value of each foreground pixel point is the Euclidean distance from the point to the nearest background pixel; finding local maximum points in the distance transformation graph , and taking the local maximum points to form a seed point set of each sub-particle in the overlapping region ; taking the seed point set A as a marker to perform watershed transformation on the distance transformation graph , to segment the overlapping region in the deleted connected domain to obtain a plurality of segmented connected domains, and then extracting the area value, circularity and elongation of the segmented connected domains; if the segmented connected domain meets the corresponding requirements, the segmented connected domain is restored and saved.

2. The method for rapid detection of microplastics based on spectral analysis technology according to claim 1, characterized in that, The density gradient solution used in the density gradient centrifugation has a density range of , the centrifugal force of the density gradient centrifugation is , and the centrifugation time is 10-30 minutes.

3. The method according to claim 1, wherein, The concentration of the Nile red fluorescent dye solution is , the reaction temperature is , the reaction time is 5-15 minutes; the fluorescence microscope uses a blue light excitation light source, the excitation wavelength is , and the emission light wavelength range is .

4. The method according to claim 1, wherein, The pore size of the filter membrane is , the filter membrane material is polycarbonate, nitrocellulose or glass fiber, and the pressure of vacuum filtration is .

5. The method according to claim 1, wherein, After collecting the residues on the filter membrane, further comprising: The residue is subjected to acid digestion based on a preset first acid solution to obtain the residue after acid digestion; the preset first acid solution is nitric acid or hydrogen peroxide, the concentration of which is , the acid digestion temperature is , and the digestion time is 10-20 minutes; The residue after acid digestion is subjected to enzymatic digestion based on a preset protease or lipase, to obtain a residue after digestion; the concentration of the preset protease or lipase is , the enzymatic digestion temperature is , and the digestion time is 20-40 minutes.

6. A microplastic rapid detection system based on spectral analysis technology, characterized in that, The microplastic rapid detection system comprises a water sample extraction module, a vacuum filtration module, a density gradient centrifugation module, a labeling module, a positioning and imaging module, and a spectral analysis module. The water sample extraction module is used to collect the water sample flowing through the sample cell and homogenize the water sample to obtain a pretreated water sample. The vacuum filtration module comprises a vacuum filtration device for filtering the pretreated water sample and collecting the residues on the filter membrane. The density gradient centrifugation module is used to mix the residues with a preset density gradient solution, perform density gradient centrifugation separation, collect microplastic particles in the supernatant, and obtain initial microplastic particles. The labeling module is used to react the initial microplastic particles with a preset Nile red fluorescent dye solution for specific fluorescent labeling to obtain fluorescently labeled microplastics. The positioning and imaging module is used to quickly position and image the fluorescently labeled microplastics by a fluorescence microscope to obtain a spectral image of the microplastics. The spectral analysis module is used to perform spectral analysis on the spectral image of the microplastics, estimate the microplastic particle quantity value in the corresponding water sample, divide the microplastic particle quantity value in the corresponding water sample by the volume of the corresponding water sample to obtain the microplastic concentration value of the water sample, and determine that the microplastic concentration value of the water sample is greater than a preset concentration threshold value, and then trigger an alarm information.

7. The microplastic rapid detection system based on spectral analysis technology according to claim 6, characterized in that, The density gradient solution used in the density gradient centrifugation has a density range of , the centrifugal force of the density gradient centrifugation is , and the centrifugation time is 10-30 minutes.

8. The rapid microplastics detection system based on spectral analysis technology according to claim 6, characterized in that, The concentration of the Nile red fluorescent dye solution is , the reaction temperature is , the reaction time is 5-15 minutes; the fluorescence microscope uses a blue light excitation light source, the excitation wavelength is , and the emission light wavelength range is .

Images