Microplastic detection method, microplastic detection device, and program for microplastic detection device

Abstract

To enable accurate identification of microplastics contained in a sample.SOLUTION: A microplastic detection method is provided, comprising a staining step of staining microplastics in a sample using a phosphor, a fluorescence excitation step of irradiating the sample with fluorescence excitation light, an image capturing step of capturing an image of the sample irradiated with the fluorescence excitation light, and an identification step of identifying microplastics in the sample on the basis of the hue of the captured image.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to a method for detecting microplastics, a microplastics detection device, and a program for a microplastics detection device. [Background technology]

[0002] In recent years, environmental pollution caused by microplastics, which are plastics broken down into small particles in the environment, has been attracting attention. Patent Document 1 describes a detection method that can easily detect on the spot whether microplastics are present in a sample collected from a beach or the like. In this detection method, microplastics contained in a sample are stained with a fluorescent material such as Nile red, the fluorescent material is irradiated with fluorescent excitation light, the emitted fluorescence is captured by a camera, and the captured image is observed to know the location and number of microplastics in the collected sample. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] International Publication No. WO2022 / 114053 Summary of the Invention [Problem to be solved by the invention]

[0004] In the conventional microplastic detection method described above, the entire sample is first stained with the fluorescent material in order to stain the microplastics with the fluorescent material, and then the fluorescent material is washed and removed from substances other than the microplastics in the sample using a cleaning solution such as ethanol, but there is a problem in that it is difficult to completely remove the fluorescent material attached to wood chips, pebbles, etc. (hereinafter also referred to as wood chips, etc.) contained in the sample. Therefore, in the conventional detection method, the captured image is subjected to a binarization process using a predetermined threshold value, and the part of the sample from which the fluorescence is emitted is identified, but even with this method, it is difficult to completely distinguish between microplastics and other materials such as wood chips, and wood chips may be erroneously detected as microplastics.

[0005] The present invention has been made to solve the above-mentioned problems, and its main intended objective is to enable accurate identification of microplastics contained in a sample. [Means for solving the problem]

[0006] As a result of intensive research to solve the above problems, the present inventors have noticed that the ratio of the scattered light intensity and the fluorescent intensity generated when irradiated with fluorescent excitation light is different between microplastics and other wood chips, etc., and that the fluorescent emission intensity is high relative to the scattered light intensity in microplastics, whereas the scattered light intensity is high relative to the fluorescent emission intensity in wood chips, etc., and that there is a difference in color in the captured image between microplastics and other wood chips, etc. As a result of further research, the present inventors have found for the first time that, while it is difficult to clearly distinguish between microplastics and wood chips using the conventional binarization process in which the brightness, which is the sum of the scattered light intensity and the fluorescent intensity, is used as a parameter, it is possible to accurately distinguish between microplastics and other wood chips, etc. by processing using the hue as a parameter, and have arrived at the present invention.

[0007] That is, the microplastic detection method of the present invention is characterized by comprising a staining step of staining microplastics in a sample with a fluorescent material, a fluorescence excitation step of irradiating the sample with fluorescence excitation light, an imaging step of imaging the sample irradiated with the fluorescence excitation light, and an identification step of identifying the microplastics from the sample based on the hue of the captured image.

[0008] According to this method, by identifying microplastics based on the hue of the captured image, it is possible to identify microplastics with greater accuracy than methods based on the brightness of the image, such as conventional binarization processing.

[0009] As a specific embodiment of the detection method, in the identification step, it is preferable to identify the microplastics by extracting a color area having a specific range of hues.

[0010] As a specific aspect of the detection method, it is preferable that the number or area of ​​the microplastics is calculated in the identification step.

[0011] In order to make the phosphor emit strong fluorescent light, the phosphor is preferably Nile Red.

[0012] The detection method preferably further comprises, after the staining step, a washing step of washing the sample with a washing solution containing hydrogen peroxide. Washing the sample with a cleaning solution containing hydrogen peroxide makes it easy to remove fluorescent substances attached to wood chips and other substances other than microplastics in the sample. Specifically, hydrogen peroxide not only breaks down fluorescent substances such as Nile Red, but also breaks down the wood chips themselves into smaller particles, allowing it to thoroughly break down fluorescent substances attached to the complex and intricate surfaces of the wood chips and remove them efficiently.

[0013] In the cleaning step, in order to efficiently remove phosphor attached to wood chips, etc. while preventing excessive decolorization of microplastics, it is preferable to immerse the materials in a cleaning solution at room temperature containing 2.5 w / v% to 3.5 w / v% hydrogen peroxide for 24 hours or more. In this case, if the immersion time is too short (for example, 6 hours or less), the fluorescent material adhering to the wood chips and the like cannot be sufficiently removed, which may cause erroneous determination in the identification step.

[0014] In addition, in the cleaning step, in order to efficiently remove fluorescent substances attached to wood chips, etc. while preventing excessive decolorization of microplastics, the sample may be boiled for 0.5 to 2 hours in a cleaning solution containing 2.5 w / v% to 3.5 w / v% hydrogen peroxide. In this case, if the boiling time is too short (e.g., less than 0.5 hours), the fluorescent material attached to the wood chips, etc. cannot be sufficiently removed, which may lead to erroneous judgment in the identification step. On the other hand, if the boiling time is too long (e.g., more than 2 hours), the fluorescent material attached to the microplastics is removed, making it difficult for fluorescence to be generated, and it may become impossible to identify the microplastics in the identification step.

[0015] In addition, in the imaging step, it is preferable to image the sample through a filter that transmits both the scattered light scattered by the sample and the fluorescence generated from the fluorescent material, and has a higher transmittance for the fluorescence than for the scattered light. In this way, the difference in hue between microplastics, whose fluorescent light intensity is greater than the scattered light intensity, and wood chips and the like, whose scattered light intensity is greater than the fluorescent light intensity, can be increased in the captured image, making it possible to detect microplastics more accurately.

[0016] The microplastic detection device of the present invention is also characterized by having a sample mounting section on which a sample containing microplastics stained with a fluorescent material is mounted, a fluorescence light source that irradiates the sample with fluorescence excitation light, a camera that images the sample irradiated with the fluorescence excitation light, and an identification section that identifies the microplastics from the sample based on the hue of the image obtained from the camera.

[0017] In addition, the program for the microplastic detection device of the present invention is for a microplastic detection device that irradiates a sample containing microplastics stained with a fluorescent material with fluorescent excitation light, images the sample, and detects the microplastics contained in the sample based on the captured image, and is characterized in that it causes a computer to perform the function of an identification unit that identifies the microplastics from the sample based on the hue of the captured image.

[0018] Such a microplastic detection device and its program can achieve the same effects as the microplastic detection method of the present invention described above. Effect of the Invention

[0019] According to the present invention, it becomes possible to accurately identify microplastics contained in a sample. [Brief description of the drawings]

[0020] [Figure 1] FIG. 1 is a schematic cross-sectional view of a microplastic detection device in one embodiment of the present invention. [Diagram 2] FIG. 2 is a schematic cross-sectional view of the microplastic detection device in the same embodiment. [Diagram 3] 4 is a diagram illustrating optical characteristics of a long-pass filter in the embodiment. FIG. [Figure 4] FIG. 2 is a functional block diagram of the microplastic detection device in the same embodiment. [Diagram 5]1 is a flowchart illustrating a process for dyeing microplastics in the embodiment. [Figure 6] 1 is a flowchart illustrating the process of identifying microplastics in a sample in the same embodiment. [Figure 7] 13 is a graph showing the emission characteristics of Nile Red when irradiated with excitation light of each wavelength in the embodiment. [Figure 8] FIG. 2 is a diagram showing an image of a sample captured by the microplastic detection device of the same embodiment. [Figure 9] A figure showing an image after color extraction processing has been applied to a captured image by the microplastic detection device of the same embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0021] Hereinafter, a microplastic detection device 100 according to one embodiment of the present invention will be described with reference to the drawings.

[0022] The microplastic detection device 100 of this embodiment is intended to be taken to a sampling site, such as a beach, and is capable of detecting microplastics contained in a sample W collected at the sampling site on the spot. Microplastics refer to plastic particles or plastic fragments with a diameter of, for example, less than 5 mm.

[0023] Specifically, as shown in Figures 1 and 2, this microplastic detection device 100 is equipped with a housing 1 having a sample mounting section 11 therein for mounting a sample W, a fluorescence light source 2 for irradiating the mounted sample W with fluorescence excitation light, and an information processing terminal 3 having a camera 31 for capturing an image of the sample W. The sample W mounted on the sample mounting section 11 is, for example, sand containing microplastics and wood chips collected on the beach, and the microplastics have been dyed with a fluorescent material by previously carrying out a dyeing process described below. The microplastic detection device 100 can detect microplastics contained in the sample W by irradiating the sample W with fluorescence excitation light, capturing an image of the fluorescence emitted from the fluorescent material, and processing the captured image.

[0024] The housing 1 has a rectangular parallelepiped shape and is portable in size and weight. The sample mounting portion 11 is provided on the upper surface of the bottom plate 1a of the housing 1. This sample mounting portion 11 may be, for example, a circular or rectangular thin cell, a thin glass plate, an acrylic plate, or the like, and an adhesive member such as a double-sided tape may be provided on the mounting surface of these for the sample W to prevent the mounted sample W from shifting position.

[0025] The fluorescence light source 2 is provided on one side of the lower surface of the upper plate 1b of the housing 1. This fluorescence light source 2 is configured to irradiate the surface of the sample W placed on the sample placement portion 11 with broad fluorescence excitation light having an upper wavelength limit of approximately 550 nm.

[0026] This fluorescence light source 2 is composed of, for example, a green LED 21 and an optical filter 22 (short-pass filter) that is provided on the optical path of the green LED 21 and transmits light with a wavelength of approximately 550 nm or less. The upper limit of the wavelength of this fluorescence light source 2 is not limited to 550 nm, but may be in the range of 400 nm to 600 nm. Furthermore, the fluorescence excitation light may not only be broad light, but also single-wavelength light emitted from the LED 21 or the like. In that case, the optical filter 22 is not necessary.

[0027] On the other hand, a window 1c is opened on the other side of the upper plate 1b of the housing 1, and an optical filter 4 (long-pass filter) that transmits fluorescence and blocks some of the excitation light for fluorescence is provided below the window 1c. This long-pass filter 4 is provided in front of the camera 31 in a removable or movably manner by a removable mechanism (not shown). This long-pass filter 4 may be any filter that transmits light with a wavelength of at least 600 nm to 700 nm or more, and in this embodiment, it transmits light with a wavelength of at least about 625 nm or more.

[0028] In order to simplify and reduce the device configuration, in this embodiment, the long-pass filter 4 is not an expensive optical filter that almost completely blocks scattered light and reflected light from the sample W and transmits only the fluorescence, but one having a broader transmission wavelength range is used, as shown in FIG. 3 as an example. This long-pass filter 4 transmits both the scattered light scattered by the sample W and the fluorescence generated from the phosphor, and has an optical characteristic that the transmittance for the fluorescence from the phosphor is higher than the transmittance for the scattered light from the sample W, so that it not only transmits the fluorescence but also transmits the scattered light from the sample W to a certain extent. For example, the transmittance of this long-pass filter 4 in the wavelength range of the fluorescence from the phosphor is preferably 3 times or more, more preferably 5 times or more, and even more preferably 7 times or more than the transmittance in the wavelength range of the scattered light from the sample W. As a result, the image captured by the camera 31 through the filter 4 is a dull green overall, making it easier to compare with the image captured without the filter 4. That is, if the long-pass filter 4 is used to transmit only the fluorescent light and block the scattered light almost completely, the captured image will be completely dark with only red dots indicating the fluorescence being scattered therein, making it difficult to compare with an image captured without the filter 4. The long-pass filter 4 is, for example, a film made of cellophane. The microplastic detection device 100 of this embodiment is equipped with only one long-pass filter 4, but may be equipped with multiple filters.

[0029] The information processing terminal 3 is a so-called smartphone that integrally comprises a camera 31, a display 32, and a computer main body 33, and is placed on a camera holding part 12 provided on the upper surface of the upper plate 1b of the housing 1. As shown in Fig. 2, this camera holding part 12 has an L-shaped protrusion 121 that is a positioning structure, and when the smartphone is placed with two sides abutting against this protrusion 121, the face of the camera 31 faces the window 1c, and is configured to be able to capture an image of the fluorescence emitted from the microplastics of the sample W. Note that this information processing terminal 3 is not limited to a smartphone and may be a tablet terminal or the like.

[0030] The camera 31 is a two-dimensional area sensor (here, a CCD camera 31) that captures an image of an area to be analyzed of the sample W in one go and outputs the image data.

[0031] The computer main body 33 has a CPU, internal memory, and an input / output interface, and performs at least the function of a microplastic identification unit 33a, as shown in Figure 4, by the CPU and peripheral devices working together in accordance with a program pre-stored in the internal memory.

[0032] The microplastics identification unit 33a receives image data of the sample W from the camera 31, processes the image data to identify microplastics from the sample W, and calculates the number and occupancy area of ​​microplastics in the image. This occupancy area may be the total area of ​​multiple microplastics, the individual area of ​​each microplastic, or the average area per microplastic.

[0033] Specifically, the microplastics identifying unit 33a identifies microplastics from the captured image by performing a color extraction process based on HSV (H: hue, S: saturation, V: brightness) on the captured image (color image) indicated by the image data. More specifically, the microplastics identifying unit 33a identifies microplastics from the captured image by performing a color extraction process based on hue on the captured image and extracting from the captured image a color area of ​​a specific range of hue (for example, about 0° to about 23°) designated in advance by the user. Then, the microplastics identifying unit 33a calculates the number and area (total area or individual area) of microplastics in the captured image based on the number and area of ​​each extracted area. Then, the microplastics identifying unit 33a outputs the calculated number and area to the display 32. The microplastics identifying unit 33a may perform a color extraction process taking into account saturation or brightness in addition to hue. For example, a process may be performed to extract from the captured image an area having a specific range of hue and a specific range of brightness, or to extract from the captured image an area having a specific range of hue and a specific range of saturation. The microplastics identification unit 33a may also appropriately accept the range of hues to be extracted as input from a user. The microplastics identification unit 33a may also be configured to identify, as microplastics, only areas among the extracted areas that have a pixel count equal to or greater than a predetermined threshold value.

[0034] Next, a procedure for detecting microplastics in a sample W using the microplastic detection device 100 configured as described above will be described.

[0035] <Dyeing process> As shown in Figure 5, first, Nile Red (C 20 H 18N2O2) is dissolved in toluene, which is a solvent, to produce a Nile red solution (step S11). Then, the sample W is immersed in this Nile red solution (step S12). At this time, the toluene melts the surface of the microplastics slightly, allowing the Nile red to penetrate into the solution, while other particles (glass, stones, wood chips, etc.) are hardly affected by the toluene, and are thought to simply have the Nile red attached to their surfaces.

[0036] Next, the sample W is dried and washed with a washing solution containing hydrogen peroxide (step S13). Specifically, the sample W is washed with a washing solution containing 2.5 w / v% or more and 3.5 w / v% or less of hydrogen peroxide (more specifically, hydrogen peroxide). In this washing step, for example, (a) the sample W is immersed in a room temperature washing solution containing hydrogen peroxide for 24 hours or more, or (b) the sample W is boiled in a washing solution containing hydrogen peroxide for 0.5 hours or more and 2 hours or less. As a result, the other particles in the sample W are decomposed and removed by Nile Red attached to the surface, and only the microplastics are stained with Nile Red. In particular, the wood chips contained in the sample W can be decomposed and fined by hydrogen peroxide, and the Nile Red attached to the complicated surface of the wood chips can be efficiently decomposed and removed. The washing solution is not limited to one containing hydrogen peroxide, and may be any solution that hardly dissolves microplastics and is easy to remove the phosphor attached to the surface of the wood chips.

[0037] <Identification process> As shown in FIG. 6, the sample W in which microplastics have been stained by the above-mentioned staining process is set on the sample placement section 11 of the microplastic detection device 100 (step S21).

[0038] Then, the fluorescence light source 2 is turned on, and the entire surface of the sample W is irradiated with the fluorescence excitation light (step S22). Nile Red is excited to a maximum by light of 553 nm, but can also emit fluorescence of sufficient intensity with light of 400 nm to 600 nm. Therefore, as in this embodiment, it also emits fluorescence by the fluorescence excitation light that has passed through the short-pass filter 22 that transmits light of wavelengths of 550 nm or less. The fluorescence wavelength spectrum in relation to the excitation light of Nile Red is as shown in FIG. 7, and its maximum fluorescence wavelength is generally said to be about 637 nm.

[0039] In this state, the entire surface of the sample W is imaged by the camera 31 of the information processing terminal 3 (step S23). As described above, the long-pass filter 4 that transmits light with a wavelength of 625 nm or more is provided in front of the camera 31. Since the fluorescence generated from the phosphor has sufficient intensity even at wavelengths of 625 nm or more, it passes through the long-pass filter 4, whereas the fluorescence excitation light has a wavelength of less than 550 nm, and the light that hits the sample W and is scattered and reflected (Rayleigh scattered) is blocked to some extent by the long-pass filter 4. Therefore, the camera 31 captures and images this fluorescence and the scattered light that is slightly transmitted through the long-pass filter 4, and the image of the sample W is slightly greenish overall due to the slightly transmitted scattered light, with only the fluorescent parts shining red, as shown in FIG. 8.

[0040] Next, the microplastics identification unit 33a performs a color extraction process using HSV (specifically, hue) on the captured image, etc., to identify areas in the sample W from which fluorescence is being emitted (hereinafter also referred to as fluorescent areas), as shown in Fig. 9, calculates the number and size of the areas, and outputs the results to the display 32 (step S24). Here, areas in the captured image having a pixel count equal to or greater than a predetermined threshold (for example, six areas circled in Fig. 9) may be identified as fluorescent areas. Then, the fluorescence light source 2 is turned off (step S25).

[0041] According to the thus configured microplastic detection device 100 of this embodiment and the detection method using the same, in the staining step, the sample W stained with a fluorescent material is washed with a cleaning solution containing hydrogen peroxide, so that the fluorescent material adhering to wood chips and the like can be efficiently removed while preventing excessive removal of the fluorescent material adhering to the microplastics. In the identification step, the captured image is subjected to a color extraction process based on the hue to identify the microplastics, so that the microplastics can be identified more accurately than methods based on the brightness of the image such as the conventional binarization process.

[0042] In other words, even if cleaning with hydrogen peroxide or other cleaning solutions is used, it is not possible to completely remove the staining substances attached to the wood chips, etc. while leaving the staining of microplastics, and the captured image will contain fluorescent emission from fluorescent substances attached to the wood chips, etc. in addition to the emission from the fluorescent substances attached to the microplastics. However, the ratio of scattered light intensity to fluorescent intensity is different between microplastics and wood chips, etc. Specifically, the fluorescent emission intensity is high relative to the scattered light intensity in microplastics, whereas the scattered light intensity is high relative to the fluorescent emission intensity in wood chips, etc. For this reason, it was difficult to clearly distinguish between microplastics and wood chips using binarization processing with brightness (i.e., the sum of scattered light intensity and fluorescent intensity) as a parameter, but if one focuses on the hue, the light from microplastics is closer to red and the emission from wood chips is closer to green, making it possible to distinguish more accurately.

[0043] In addition, by identifying microplastics by performing color extraction processing based on hue on the captured image, the contours of microplastics can be recognized more accurately than with conventional image processing that only binarizes images based on brightness. This makes it possible to calculate the area of ​​microplastics with greater accuracy. Specifically, in binarization processing, the contours of microplastics are recognized when they exceed a threshold value, and so tend to be recognized as small, but by recognizing the area of ​​microplastics based on hue, it is possible to calculate the area of ​​microplastics more accurately.

[0044] The present invention is not limited to the above-described embodiment. For example, the microplastics identification unit 33a identifies microplastics from a captured image by performing a color extraction process using HSV on the captured image, but this is not limited to the above. In other embodiments, microplastics may be identified by performing an equivalent process using other color expressions, such as RGB processing or CMY processing, on the captured image. For example, in RGB processing, an area where the ratio of each value falls within a specific range may be extracted as microplastics.

[0045] In the above embodiment, the optical filter 4 transmits both the fluorescent light and the scattered light, but this is not limiting. In other embodiments, the optical filter 4 may have the property of almost completely blocking the scattered light and transmitting only the fluorescent light.

[0046] A broad wavelength light source such as a mercury lamp may be used as the light source for the fluorescence excitation light. Conversely, a monochromatic LED that emits light of a narrow wavelength may be used. In this case, the short-pass filter 22 may be omitted by selecting the monochromatic LED.

[0047] In the above embodiment, Nile Red is used as the phosphor, but this is not limiting. For example, any phosphor may be used as the phosphor as long as it is soluble in an organic solvent such as toluene, and for example, commercially available phosphors such as fluorescent chalk may be used.

[0048] In other embodiments, the fluorescence light source 2 may be equipped with a white LED instead of the green LED 21, or may be equipped with both the green LED 21 and a white LED so that the irradiated light can be switched between green and white. Instead of or in addition to providing a white LED, an openable opening for inserting and removing the sample W may be provided in the wall of the housing 1, and light for observing the sample W may be taken into the housing 1 by opening the opening. The inner surface of the housing 1 may be coated with a light absorbing material to prevent diffuse reflection within the housing 1 of the fluorescence excitation light irradiated from the fluorescence light source 2.

[0049] Furthermore, in order to reduce uneven illumination of the fluorescence excitation light to the sample W, a light diffusing member such as a diffusion plate or diffusion sheet may be provided in front of the light emission direction of the fluorescence light source 2 and between the sample W and the sample W. Furthermore, the fluorescence light sources 2 may be provided not only on the top surface of the sample W in the housing 1 but also on the side surfaces thereof, and the fluorescence excitation light may be irradiated onto the sample W from above and from the sides, thereby reducing uneven illumination.

[0050] In addition, the microplastic detection device 100 of the above embodiment is equipped with the camera 31 and the computer main body 33 integrated as a smartphone, but this is not limited to this. The microplastic detection device 100 of other embodiments may be equipped with the camera 31 and the computer main body 33 separately. In this case, the computer main body 33 may be a notebook PC or the like.

[0051] In the above embodiment, the function of the microplastics identification unit 33a is performed by the information processing terminal 3 attached to the housing 1, but this is not limited to the above. The function may be performed by a server device connected to the information processing terminal 3 via a communication network.

[0052] The disclosure of this specification also provides: A staining step of staining microplastics in a sample with a fluorescent substance; a fluorescence excitation step of irradiating the sample with fluorescence excitation light; an imaging step of imaging the sample through a filter that transmits both the scattered light scattered by the sample and the fluorescent light generated from the fluorescent material, the filter having a higher transmittance for the fluorescent light than for the scattered light; The present invention also includes a method for detecting microplastics, which includes an image display step of displaying the captured image on a screen. Even with such a detection method, the effects of the present invention described above can be achieved. In other words, by doing so, microplastics whose fluorescence intensity is greater than the scattered light intensity and wood chips whose scattered light intensity is greater than the fluorescence intensity can be displayed in a captured image with the difference in hue highlighted, making it possible to more accurately identify microplastics.

[0053] In addition, various modifications and combinations of the embodiments may be made as long as they do not go against the spirit of the present invention. [Explanation of symbols]

[0054] 100 Microplastic detection device 2. Fluorescent light source 31. Camera 33a Microplastics Identification Unit W: Sample

Claims

1. A staining step of staining microplastics in the sample with a fluorescent substance; a fluorescence excitation step of irradiating the sample with fluorescence excitation light; an imaging step of imaging the sample irradiated with fluorescence excitation light; A method for detecting microplastics, comprising an identification step of identifying the microplastics from the sample based on the hue of the captured image.

2. The method for detecting microplastics according to claim 1, wherein in the identification step, the microplastics are identified by extracting a color area within a specific range of hues.

3. The method for detecting microplastics according to claim 1 or 2, wherein the number or area of ​​the microplastics is calculated in the identification step.

4. The method for detecting microplastics according to claim 1 or 2, wherein the fluorescent substance is Nile Red.

5. The method for detecting microplastics according to claim 1 or 2, further comprising a washing step of washing the sample with a washing solution containing hydrogen peroxide after the staining step.

6. A microplastic detection method as described in claim 5, wherein in the cleaning step, the sample is immersed in a cleaning solution at room temperature containing 2.5 w / v% or more and 3.5 w / v% or less of hydrogen peroxide for 24 hours or more.

7. A microplastic detection method as described in claim 5, wherein in the washing step, the sample is boiled for at least 0.5 hours and not more than 2 hours in a washing solution containing 2.5 w / v% or more and 3.5 w / v% or less hydrogen peroxide.

8. A microplastic detection method as described in claim 1 or 2, wherein in the imaging step, the sample is imaged through a filter that transmits both scattered light scattered by the sample and fluorescence generated from the fluorescent material, and has a higher transmittance for the fluorescence than for the scattered light.

9. a sample placement section on which a sample containing microplastics stained with a fluorescent material is placed; a fluorescence light source that irradiates the sample with fluorescence excitation light; a camera for capturing an image of the sample irradiated with the fluorescence excitation light; A microplastic detection device having an identification unit that identifies the microplastics from the sample based on the hue of the image acquired from the camera.

10. A program for a microplastic detection device that irradiates a sample containing microplastics stained with a fluorescent substance with fluorescence excitation light, captures an image of the sample, and detects microplastics contained in the sample based on the captured image, A program for a microplastic detection device that causes a computer to function as an identification unit that identifies microplastics from the sample based on the hue of the captured image.

Images