Semi-automatic multi-connected soil column system for micro-plastic migration research and analysis method

Abstract

The invention provides a semi-automatic multi-connected soil column system for micro-plastic migration research and an analysis method. Firstly, the invention discloses a semi-automatic multi-connected soil column system for micro-plastic migration research. The semi-automatic multi-connected soil column system comprises a multi-connected soil column automatic liquid receiving system, an automatic liquid transferring system and a detection system. The invention further discloses an analysis method for micro-plastic migration research based on the semi-automatic multi-connected soil column system. According to the semi-automatic multi-connected soil column system disclosed by the invention, by integrating the multi-connected soil column automatic liquid receiving system, the automatic liquid transferring system and the detection system, a traditional dispersive, manual and low-flux soil column experiment is converted into a continuous, semi-automatic and high-flux standardized process, so that the reliability and repeatability of an experiment result are ensured, and the detection efficiency is improved.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of microplastic detection, and particularly relates to a semi-automatic multi-connection soil column system and analysis method for microplastic migration research. BACKGROUND

[0002] As a new type of environmental pollutant, the migration and diffusion of microplastics in soil and groundwater systems has become a research hotspot in the field of global environmental science. Microplastics in soil can enter the food chain through crops absorption, groundwater infiltration and other pathways, posing a potential threat to the ecosystem and human health. Soil column is a cylindrical reactor filled with porous media such as soil or quartz sand, and the material is made of quartz, stainless steel, organic glass, etc., which is commonly used in laboratory to carry out experiments on the migration of pollutants in porous media. Laboratory soil column experiment, as a key means to simulate the migration behavior of microplastics in porous media, is a key technical support for revealing the migration mechanism and evaluating environmental risks.

[0003] However, the existing soil column experiment technology and related devices have the following significant defects: first, the degree of automation is low, and the experimental flux is limited: traditional soil column experiments rely on manual operation to complete the whole process of leaching control, effluent collection, sample removal, etc.; a single experiment can usually only handle 1-2 soil columns, and the sample collection interval of each soil column needs to be manually timed, resulting in extremely low experimental efficiency and seriously restricting the experimental flux and data repeatability; second, the risk of cross contamination is high, and the data reliability is poor: microplastic detection requires high sample purity, but the traditional experimental process has multiple pollution risks, such as direct contact between containers and air during liquid connection, which easily introduces environmental microplastics, and manual operation during soil sample pretreatment and detection further amplifies the pollution risk; third, the detection efficiency is low, and the parameters obtained are not comprehensive: the existing microplastic detection method mainly uses "microscopic counting + infrared spectrum verification": microscopic counting of a single sample requires manual observation for more than 30 minutes, and only the number of particles can be obtained; infrared spectrum verification needs to be compared with the spectrum library one by one, and the time for a single analysis is more than 1 hour, which cannot simultaneously obtain key parameters such as particle size distribution, roundness, and agglomeration rate; fourth, multi-factor coupled experiments are difficult to implement: microplastic migration is affected by multiple factors such as pH, ionic strength, and organic matter content, and coupled experiments need to be carried out by controlling variables. The existing devices are mainly designed for single soil column, which cannot simultaneously set different factor gradients, and the manual adjustment of parameters such as leaching liquid flow rate and liquid connection time has low precision, resulting in insufficient accuracy of variable control in multi-factor experiments.

[0004] Therefore, it is urgent to develop a semi-automatic experimental system for studying the migration behavior of microplastics in soil and groundwater systems, which can integrate automatic liquid connection, liquid transfer and detection to solve the above problems. SUMMARY

[0005] The present disclosure provides a semi-automatic multi-column soil column system and analysis method for microplastic migration research to at least solve the above technical problems existing in the prior art.

[0006] According to a first aspect of the present disclosure, a semi-automatic multi-column soil column system for microplastic migration research is provided, comprising a multi-column soil column automatic liquid receiving system, an automatic pipetting system and a detection system;

[0007] wherein,

[0008] The multi-column soil column automatic liquid receiving system comprises three soil columns, an automatic liquid receiving turntable and a spraying device; the lower end of the soil column is provided with a drainage port; the automatic liquid receiving turntable is located directly below the soil column and is provided with three concentric sample sites, i.e. inner, middle and outer sample sites, which correspond to the drainage ports of the three soil columns respectively, and is used for automatically receiving the seepage liquid discharged from the drainage ports; the spraying device is located directly above the soil column and is used for spraying leaching liquid to the soil column;

[0009] The automatic pipetting system comprises a three-axis mechanical arm, a full-automatic pipetting gun, a pipetting gun head box, a sampling point and a counting plate; the three-axis mechanical arm moves in X, Y and Z axes and is used for controlling the movement of the full-automatic pipetting gun to the sampling point, the pipetting gun head box and the counting plate to complete pipetting; the full-automatic pipetting gun is installed at the end of the three-axis mechanical arm;

[0010] The detection system comprises a microplastic image processing counter; the microplastic image processing counter is provided with a CMOS optical imaging system, and the control program thereof is set to realize automatic focusing function, automatic planning of detection path function and shooting by using the CMOS optical imaging system, and integrate algorithm to identify microplastic particles and output concentration, roundness and particle size distribution parameters.

[0011] In an implementable manner, the soil column is a split column body which is composed of a plurality of shell segments which can be independently detached, and the soil column can be segmented and detached for sampling, thereby facilitating longitudinal distribution analysis and migration monitoring of residual microplastics in soil at different depths.

[0012] In an implementable manner, the end of each shell segment of the split column body is provided with a flange interface, and the flange interface is connected and sealed by a clamp and a silica gel gasket, so as to avoid liquid leakage.

[0013] In a preferred embodiment, the drainage port of the soil column is conical, facilitating collection of the seepage liquid.

[0014] In a preferred embodiment, the split column body is composed of seven shell segments, each of which is 5 cm long and has an inner diameter of 5 cm.

[0015] In an implementable manner, the automatic liquid receiving turntable is a circular automatic liquid receiving turntable, each circle of which contains 50 sample sites, and the total number of sample sites is 150; the control program thereof is pre-set with time intervals and is driven to rotate by a stepping motor.

[0016] In an implementable manner, the semi-automatic multi-column soil column system further comprises three peristaltic pumps connected to the spraying device through reinforced silica gel pump tubes, respectively controlling the flow rate of the leaching liquid sprayed to the three soil columns.

[0017] In an implementable manner, the spraying device is a multi-hole spraying port for uniformly spraying the leaching liquid to the top end of the soil column, simulating the natural rainfall or irrigation process.

[0018] In an implementable manner, the pipetting process is: moving to the pipette tip box to grab a new tip, moving to the sampling point to suck the percolate, moving to the counting plate to inject the percolate, and retracting the tip, the whole process follows the principle of "one sample one tip", that is, a new tip is automatically replaced for each transfer of percolate from a sampling point.

[0019] In an implementable manner, the microplastic image processing counter is improved based on the Venus cell counter, and the pixel of the built-in CMOS optical imaging system is not less than 6.3 million pixels; the automatic focusing function of the microplastic image processing counter is driven by the Z-axis moving assembly; the automatic planning of the detection path function is to automatically move and focus at least 5 different field positions of the same sample.

[0020] In an implementable manner, the algorithm of the microplastic image processing counter can automatically identify, segment and count microplastic particles in the image.

[0021] In a preferred embodiment, the algorithm is: after adaptive binaryzation processing of the image using an improved neural network algorithm, the connected region marking is performed, and all potential target objects are preliminarily identified; by calculating the roundness and contour area of each region, it is judged whether there is a sticking situation: the region with too low roundness or area significantly larger than the average level is judged as a sticking region, and for the identified independent objects which are not sticking, the subsequent analysis step is directly entered; and for the identified sticking region, distance transformation combined with watershed algorithm is further applied for segmentation, and the sticking objects are separated into multiple independent objects; after completing all segmentation operations, the connected region marking is re-executed to ensure that each object is uniquely identified; the number of target objects is counted, and the concentration is calculated; for each independent object, its morphological parameters including equivalent diameter and roundness are extracted, so as to realize the multi-feature quantitative description of the target object; the algorithm output includes the concentration and particle size distribution parameters of the target object, providing comprehensive and accurate quantitative data support for subsequent analysis.

[0022] The improved neural network algorithm is based on a traditional neural network algorithm structure, introduces a self-adaptive link strength mechanism and a dynamic threshold decay coefficient, can adjust the connection weight between neurons according to local features of an image, effectively enhances the response to low-contrast and uneven light areas, and thus improves the overall segmentation quality and robustness; the distance transformation can effectively highlight the center skeleton of the foreground object, and the watershed algorithm accurately determines the segmentation boundary by using gradient information, so that the adhered objects are separated into multiple independent objects.

[0023] In an implementable manner, the semi-automatic multi-connected soil column system further comprises a waste liquid treatment device, which comprises a waste liquid flow channel and a waste liquid barrel, the waste liquid flow channel is arranged in a guide groove at the edge of the automatic liquid receiving turntable and is in communication with the waste liquid barrel, and the effluent liquid in the non-liquid receiving period or the cleaning stage is introduced into the waste liquid barrel through the flow channel.

[0024] It should be noted that only a semi-automatic multi-connected soil column system comprising three soil columns is listed in the present disclosure. In actual application, if more experiments need to be carried out, the number of soil columns can be appropriately increased, and the number of circles of the circular automatic liquid receiving turntable and the sample positions per circle can also be increased to increase the number of sample points.

[0025] According to a second aspect of the present disclosure, an analysis method for microplastic migration research based on the above semi-automatic multi-connected soil column system is provided, which comprises the following steps:

[0026] (1) Soil column filling and saturation: assemble the shell into three soil columns, fill and compact the soil from bottom to top, continuously inject deionized water into the upper end of the soil column, until the effluent velocity is stable (i.e. the soil reaches a saturated state), and finally add a microplastic pollution mixed layer to the uppermost layer;

[0027] (2) Controllable leaching and time sequence liquid receiving: adjust the flow rate of the peristaltic pump, introduce the leaching liquid into the soil column through the spraying device, start the automatic liquid receiving turntable to rotate at a preset time interval, make the effluent of the three soil columns flow into the corresponding storage tubes of the sample points in the inner, middle and outer circles respectively, and obtain the effluent of all sample points and transfer them to the sampling points;

[0028] (3) Automatic pipetting: start the three-axis mechanical arm to control the full-automatic pipetting gun to move the effluent of all sampling points (move to the pipetting gun head box to grab a new gun head, move to the sampling point to suck the effluent, move to the counting plate to inject the effluent, and retract the gun head) to the counting plate, and automatically replace the new gun head every time the effluent of a sampling point is transferred;

[0029] (4) Automatic detection: start the microplastic image processing counter, insert the counting plate after pipetting into the microplastic image processing counter, control automatic focusing and automatically plan the detection path, use the CMOS optical imaging system to take pictures, analyze the pictures taken by the algorithm, and output the concentration, roundness and particle size distribution of the microplastic particles in the time sequence.

[0030] (5) Microplastic residual analysis: disassemble the soil column, extract microplastics in each layer of soil, and detect using the methods of steps (3)-(4) to obtain the concentration of microplastic particles, roundness and particle size distribution in the longitudinal depth;

[0031] (6) Data integration: combine the microplastic particle concentration and particle size distribution data in time series with the microplastic particle concentration and particle size distribution data in longitudinal depth, draw the migration penetration curve, and calculate the migration rate and retention.

[0032] In the present disclosure, the soil can be replaced by sand of different particle sizes or modified materials such as clay minerals, humus, biochar, etc. of different proportions and different types, to further systematically study the influence of porous media with different physical properties (such as particle size, porosity) and chemical properties (such as surface charge, organic matter content) on the migration behavior of microplastics.

[0033] Based on the above semi-automatic multi-connected soil column system and analysis method, the present disclosure can simulate various key influencing conditions and complex processes of microplastic migration in soil and groundwater systems, for example: simulate different rainfall flows by adjusting the flow rate of the peristaltic pump; simulate the aging process of microplastics under light by adding ultraviolet light irradiation or changing the light source irradiation time; add other pollutants such as antibiotics and heavy metals to the microplastic contaminated mixed layer to simulate the migration of co-contaminants; use the peristaltic pump to control the leaching solution with different ionic strengths to simulate the influence of electrostatic effect on migration; add different types of microorganisms to the matrix of the soil column to study the mechanism of microorganisms on microplastic migration and degradation, etc.

[0034] According to an implementable manner of the present disclosure, at least the following beneficial effects are achieved:

[0035] The semi-automatic multi-connected soil column system for microplastic migration research disclosed in the present disclosure integrates the automatic liquid receiving system, the automatic pipetting system and the detection system of the multi-connected soil column, converts the traditional dispersed, manual and low-throughput soil column experiment into a continuous, semi-automatic and high-throughput standardized process, and has the following advantages: automatic operation greatly reduces human error, ensuring the reliability and repeatability of experimental results; 3 soil columns and 150 samples in time series can be processed simultaneously, and the detection and analysis of all samples can be completed within a few hours, with an efficiency improvement of tens of times; high time resolution effluent data and high spatial resolution soil residual data can be obtained simultaneously, providing rich data support for subsequent model construction; the whole process from liquid receiving, liquid moving to detection is designed with cross-contamination prevention as the core, ensuring data accuracy.

[0036] It is to be understood that the description of the contents of this section is not intended to identify key or essential features of embodiments of the disclosure, nor is it used to limit the scope of the disclosure. Other features of the disclosure will become readily apparent from the following description. BRIEF DESCRIPTION OF DRAWINGS

[0037] The above and other objects, features and advantages of the exemplary embodiments of the present disclosure will be more apparent from the following detailed description read in conjunction with the accompanying drawings, in which:

[0038] In the drawings, the same or corresponding parts are denoted by the same or corresponding reference numerals.

[0039] Figure 1 A structural schematic diagram of the automatic liquid receiving system of the multi-column soil column of the present disclosure is shown.

[0040] Figure 2 A structural schematic diagram of the automatic liquid receiving system of the present disclosure is shown.

[0041] Figure 3 A top view of the automatic liquid receiving system of the present disclosure is shown.

[0042] Figure 4 A structural schematic diagram of the detection system of the present disclosure is shown.

[0043] Figure 5 A flowchart of the algorithm of the microplastic image processing counter of the present disclosure is shown.

[0044] In the drawings: 1, soil column; 2, circular automatic liquid receiving turntable; 3, spraying device; 4, waste liquid barrel; 5, peristaltic pump; 6, three-axis mechanical arm; 7, full-automatic pipette; 8, pipette tip box; 9, sampling point; 10, counting plate; 11, microplastic image processing counter. DETAILED DESCRIPTION

[0045] In order to make the purposes, features and advantages of the present disclosure more obvious and easy to understand, the technical solutions in the embodiments of the present disclosure will be described clearly and completely below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only part of the embodiments of the present disclosure, not all the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present disclosure.

[0046] Embodiment 1

[0047] This embodiment demonstrates a semi-automatic multi-connection soil column system for studying the migration behavior of microplastics in soil and groundwater, including a multi-soil column automatic liquid receiving system, an automatic pipetting system and a detection system. The three systems work together to form an integrated semi-automatic workflow from leaching, liquid receiving, pipetting to detection, as follows:

[0048] I. Multi-connection soil column automatic liquid receiving system

[0049] The multi-connection soil column automatic liquid receiving system includes a soil column 1, a circular automatic liquid receiving turntable 2, a spraying device 3 and a waste liquid treatment device. The structural diagram is shown in Figure 1 The components work together to achieve automatic control of leaching, liquid receiving and waste liquid treatment in microplastic migration experiments, as follows:

[0050] Soil column 1: split column, composed of 7 independently detachable shells, each 5 cm long and 5 cm in diameter. Each shell has a flange interface at the end. To prevent liquid leakage, the segments are connected and sealed by a clamp and a silicone gasket. The column can be detached and sampled in segments to analyze the vertical distribution and migration of residual microplastics in different depths of soil. The bottom is equipped with a conical drainage port and is installed on a test rack that accommodates three soil columns.

[0051] Circular automatic liquid receiving turntable 2: located directly below the soil column. To increase the number of sample points, three concentric circles of sample sites (corresponding to three soil columns) are provided, with 50 sample sites (such as test tube holes) evenly distributed along the circumference of each circle, for a total of 150 sample points. The conical drainage ports at the bottom of the three soil columns precisely correspond to the inner, middle and outer three circles of the circular automatic liquid receiving turntable 2. The control program of the circular automatic liquid receiving turntable 2 is pre-set with time intervals and driven by a stepper motor to automatically rotate, achieving timed, sequential and non-contact automatic reception of the leachate from the three soil columns at different time points, avoiding time errors and cross contamination in manual liquid receiving.

[0052] Spraying device 3: located directly above the soil column, used to spray the leachate onto the soil column. It is controlled by three independent peristaltic pumps 5, connected by reinforced silicone pump tubes, to spray the leachate at a constant and adjustable flow rate onto the top of the soil column, ensuring stable and controllable experimental conditions. Multiple spray nozzles are used to ensure uniform spraying of the leachate onto the top of the soil column, simulating natural rainfall or irrigation processes.

[0053] Waste liquid treatment device: includes a waste liquid flow channel and a waste liquid barrel 4. The waste liquid flow channel is a guide groove on the edge of the circular automatic liquid receiving turntable 2, which is connected to the waste liquid barrel 4 to facilitate the flow of waste liquid. During non-liquid receiving periods or cleaning stages, the leachate is directed into the waste liquid barrel 4 for centralized treatment, further ensuring the purity of the samples and the cleanliness of the experimental environment.

[0054] II. Automatic pipetting system

[0055] The automatic pipetting system comprises a three-axis mechanical arm 6, an automatic pipetting gun 7, a pipetting gun head box 8, a sampling point 9 and a counting plate 10, as shown in the structural schematic view and top view, which is used to automatically collect the leachate of the multi-column soil column automatic liquid receiving system to the counting plate 10, avoiding the error and low efficiency of manual pipetting, and the specific implementation is as follows: Figure 2 and Figure 3 The automatic pipetting system comprises a three-axis mechanical arm 6, an automatic pipetting gun 7, a pipetting gun head box 8, a sampling point 9 and a counting plate 10, as shown in the structural schematic view and top view, which is used to automatically collect the leachate of the multi-column soil column automatic liquid receiving system to the counting plate 10, avoiding the error and low efficiency of manual pipetting, and the specific implementation is as follows:

[0056] The three-axis mechanical arm 6 is freely movable on the X, Y and Z axes, and the control program thereof pre-stores the coordinates of the sampling point 9, the pipetting gun head box 8 and the hole position of the counting plate 10, controls the movement of the automatic pipetting gun 7 to the sampling point 9, the pipetting gun head box 8 and the counting plate 10, and completes the actions of taking the gun head, sucking the liquid, discharging the liquid and returning the gun head (i.e. moving to the pipetting gun head box 8 to grab a new gun head, moving to the sampling point 9 to suck the leachate, moving to the counting plate 10 to inject the leachate, and returning the gun head), so as to automatically replace a new pipetting gun head for each transfer of the leachate of the sampling point 9, thereby eliminating the cross contamination caused by the residual gun head between samples, and ensuring the independence and accuracy of the data of each sample.

[0057] The automatic pipetting gun 7 is installed at the end of the three-axis mechanical arm 6, and can perform the actions of taking the gun head, sucking the liquid, discharging the liquid and returning the gun head in the control program of the three-axis mechanical arm 6.

[0058] III. Detection system

[0059] The detection system comprises a microplastic image processing counter 11, as shown in the structural schematic view Figure 4 , which can automatically image, identify, count and analyze parameters of the leachate in the counting plate 10, and output key data such as the concentration, roundness and particle size distribution of the microplastics, and the specific implementation is as follows:

[0060] The microplastic image processing counter 11 is improved based on the Venus cell counter, and is internally provided with an industrial-grade CMOS optical imaging system (with a resolution of up to 6.3 million pixels). The control program thereof is set to have an automatic focusing function, which is completed by the Z-axis movement assembly drive, so as to ensure that the morphology and size information of the micron-level microplastics can be clearly captured, and high-quality image data is provided for subsequent accurate identification. The control program thereof is also set to have an automatic planning detection path function, which automatically moves, focuses and takes pictures of at least 5 different field positions of the same sample by the industrial-grade CMOS optical imaging system, effectively avoiding the counting error caused by uneven distribution of the microplastics, and ensuring the representativeness and statistical significance of the data. The integrated algorithm can quickly and automatically identify, segment and count the microplastic particles (irregular shape and non-reflective, particle size range of 2-400 um) in the image, and complete the test of one sample within 51 seconds, further output the concentration, roundness and particle size distribution of the microplastic particles, and realize the automatic conversion of the microplastics from the image to the structured data.

[0061] The flowchart of the algorithm is as follows: Figure 5 As shown, the specific steps are as follows: After adaptive binarization of the image using an improved neural network algorithm, connected component labeling is performed to initially identify all potential target objects. By calculating the roundness and contour area of ​​each region, it is determined whether there is adhesion: regions with low roundness or significantly larger than average area are identified as adhesion regions. For the identified non-adhesive independent objects, they directly proceed to the subsequent analysis steps. For the identified adhesion regions, distance transform combined with the watershed algorithm is further applied for segmentation to separate the adhesion objects into multiple independent objects. After completing all segmentation operations, connected component labeling is re-executed to ensure that each object is uniquely identified. The number of target objects is counted, and their concentration is calculated. For each independent object, its morphological parameters, including equivalent diameter and roundness, are extracted to achieve multi-feature quantitative description of the target object. The algorithm output includes the concentration and particle size distribution parameters of the target objects, providing comprehensive and accurate quantitative data support for subsequent analysis.

[0062] The improved neural network algorithm is based on the traditional neural network algorithm structure and introduces an adaptive link strength mechanism and a dynamic threshold decay coefficient. It can adjust the connection weights between neurons according to the local features of the image, effectively enhance the response to low contrast and uneven lighting areas, thereby improving the overall segmentation quality and robustness. The distance transformation can effectively highlight the central skeleton of the foreground object, while the watershed algorithm uses gradient information to accurately determine the segmentation boundary, thereby separating the adhered objects into multiple independent objects.

[0063] Example 2

[0064] This embodiment demonstrates a rapid analysis method based on a semi-automated multi-soil column system for microplastic migration research, specifically including:

[0065] I. Soil column filling and assembly

[0066] The flange interfaces of the seven-section shell are vertically sealed and assembled into three soil columns using clamps and silicone gaskets. Soil is filled from bottom to top (the cross-sectional area A, height L, and porosity n of the soil column are known). The lower soil column is filled first and gently compacted. The three filled soil columns 1 are then installed on the test frame. The peristaltic pump 5 is turned on, and deionized water is evenly sprayed onto the soil column 1 through the spray device 3 until the soil column 1 reaches saturation (i.e., the exudate flow rate is stable). Finally, a microplastic contamination mixture layer (the concentration and volume of microplastic particles are known, i.e., the initial concentration C0 and volume V0 of microplastic particles) is placed at the top of the soil column 1.

[0067] II. Controlled filtration and sequential liquid collection

[0068] Three conical drainage outlets at the bottom of the three soil columns 1 are precisely aligned with the inner, middle and outer three circles of the circular automatic liquid receiving turntable 2, respectively, and the liquid storage tubes (such as centrifuge tubes) are placed on all 150 sample points 9 of the circular automatic liquid receiving turntable 2. Adjust the peristaltic pump 5 to the set flow rate Q, and start the control program of the circular automatic liquid receiving turntable 2, and pass deionized water into the soil column through the spraying device. The circular automatic liquid receiving turntable 2 is driven by a stepper motor to automatically step rotate a site point at a preset time interval (Δt, for example, every 15 minutes). During each time interval, the leachate of the three soil columns 1 will be introduced into the corresponding 150 sample points of the inner, middle and outer circles of the circular automatic liquid receiving turntable 2, respectively, thereby realizing the automatic sequential collection of the leachate of the three groups of soil columns 1. During the non-liquid receiving period or the cleaning stage, the leachate is collected in the waste liquid tank 4 through the waste liquid flow channel for unified treatment. After the leaching is completed (such as all 150 sample points have collected leachate or the experiment reaches the predetermined time t), the leachate of all 150 sample points is transferred to the sampling point 9.

[0069] III. Automatic pipetting

[0070] Start the control program of the three-axis mechanical arm 6 to control the full-automatic pipetting gun 7 to perform pipetting operation: move to the pipetting gun head box 8, grab a new pipetting gun head; move to the sampling point 9, suck a certain amount (such as 5 μL) of leachate; move to the designated hole position of the counting plate 10, and inject the leachate; withdraw the used gun head to the waste box, and repeat the above steps until all the leachate of the sampling points 9 is transferred to the counting plate 10. The whole process follows the principle of "one sample one gun head" to avoid cross contamination.

[0071] IV. Automatic detection

[0072] Insert the counting plate 10, which has completed leachate injection, into the card slot of the microplastic image processing counter 11 one by one. Start the control program of the automatic counting of microplastics, and the microplastic image processing counter 11 starts to work: automatic focusing and automatic planning of detection path: for each sample on the counting plate 10, automatically focus through the control of the Z-axis moving assembly, and automatically move, focus and high-definition shoot using an industrial-grade CMOS optical imaging system for at least 5 different field positions of the same sample; image recognition and counting: the algorithm automatically analyzes the photographed images, identifies the microplastic particles in each field, and counts the number and measures the size; data integration and output: the system automatically integrates the data of multiple fields of the same sample, calculates the microplastic particle concentration, roundness and particle size distribution at different time points (i.e. at different time points), and generates a data report.

[0073] V. Microplastic residual analysis

[0074] After the leaching experiment is completed, the three soil columns 1 can be disassembled respectively, and the soil is taken out in sections (every 5 cm as a section) to extract the residual microplastics. Similarly, the automatic pipetting system and the microplastic image processing counter 11 are used to analyze the extraction liquid to obtain the concentration, roundness and particle size distribution of the microplastic particles in the longitudinal depth.

[0075] Six, data processing

[0076] The microplastic particle concentration and particle size distribution (change of microplastic concentration with time / liquid volume) obtained in the fourth step are combined with the microplastic particle concentration and particle size distribution obtained in the fifth step in the longitudinal depth of the soil column, the migration penetration curve of the microplastic is drawn, and the migration rate, retention amount and other key parameters are calculated to deeply analyze the migration behavior and mechanism of the microplastic in the soil.

[0077] Among them, the migration penetration curve is a curve describing the relative concentration (C t / C0) of the tracer or pollutant in the leachate with time (t) or cumulative pore volume (PV t ), which directly shows when the microplastic starts to penetrate, when it reaches the peak value, and the final outflow situation. The specific drawing method is as follows:

[0078] 1. Time series data: the circular automatic liquid receiving turntable 2 provides the collection time interval (Δt) of each sample point;

[0079] 2. Particle concentration data: the microplastic image processing counter 11 provides the microplastic particle concentration (C t ) of each sample point 9;

[0080] 3. Initial microplastic particle concentration (C0): the microplastic particle concentration of the microplastic pollution mixed layer (tested by the microplastic image processing counter 11);

[0081] 4. Total pore volume (PV) = soil column cross-sectional area (A) x soil column height (L) x soil porosity (n)

[0082] 5. Cumulative pore volume (PV t ): At time t, how many PVs is the cumulative leaching liquid volume?

[0083] PV t = (cumulative leaching liquid volume) / PV = (peristaltic pump flow rate (Q) x time (t)) / PV

[0084] With the cumulative pore volume (PV t ) or time (t) as the abscissa (X axis), and the calculated relative particle concentration (C t / C0) as the ordinate (Y axis), the data (PVt ,C t / C0) in the figure, connecting these points, forming an S-shaped curve that is the migration penetration curve of microplastics.

[0085] The calculation method of migration rate and retention amount is as follows:

[0086] 1. Calculate the migration rate

[0087] Migration rate (%) = (total outflow amount / total dosage amount) x 100%

[0088] Integrate the entire penetration curve to get the total outflow amount, and the total dosage amount = initial dosage microplastic particle concentration x volume, i.e. C0xV0.

[0089] 2. Calculate the retention amount

[0090] Retention amount = total dosage amount - total outflow amount.

[0091] Example 3

[0092] This example carries out an identification and differentiation verification experiment of microplastic particles and sand matrix particles to verify the specific recognition ability of the microplastic image processing counter algorithm in the disclosure to microplastic particles, and the effect of distinguishing microplastics from sand, as follows:

[0093] I. Sample preparation

[0094] Microplastic particle stock solution: 16 μm standard microplastic particles are selected to prepare a microplastic particle stock solution with a known concentration (as a positive control);

[0095] Matrix: quartz sand (particle size 0.55 μm-1 mm, simulating sand) is selected, washed with deionized water and reserved.

[0096] II. Soil column filling and saturation

[0097] Assemble soil column 1, fill quartz sand from bottom to top and compact, then introduce deionized water to saturation; add 16 μm microplastic particle stock solution to the surface layer of quartz sand to simulate a microplastic contaminated environment.

[0098] III. Controllable leaching and time sequence liquid connection

[0099] Adjust the flow rate of peristaltic pump 5, introduce deionized water to the soil column through the spraying device 3, start the circular automatic liquid receiving turntable 2 driven by the stepper motor to rotate at the preset time interval, collect 1 min and 10 min effluent (divided into small and large tubes, two sets of each), and transfer the stock solution, 1 min effluent and 10 min effluent to the sampling points 9.

[0100] IV. Automatic pipetting

[0101] Start the three-axis mechanical arm 6 to control the full-automatic pipette 7 to move the stock solution, 1 min leachate, and 10 min leachate (move to the pipette tip box 8, grab a new pipette tip, move to the sampling point 9 to suck the leachate, move to the designated hole of the counting plate 10, inject the leachate, and withdraw the used pipette tip to the waste box, and repeat the above steps) to the counting plate 10. A new pipette tip is automatically replaced for each sampling point 9 of the leachate.

[0102] V. Automatic detection

[0103] Start the microplastic image processing counter 11, insert the counting plate 10 after the pipetting into the microplastic image processing counter 11, control the Z-axis movement assembly to drive automatic focusing and automatically plan the detection path, use the CMOS optical imaging system to automatically take pictures of each sample in 5 different fields of view, analyze the photographed images through algorithms (adaptive binaryzation, connected region labeling, distance transformation + watershed algorithm segmentation, and feature analysis), and output the total number of microplastic particles, average particle size, and average circularity. The results are shown in Table 1. The results show that for the microplastic particle stock solution (containing 16 μm standard microplastic particles), the total number of particles is 1213 and 1269, the average particle size is 15.6 μm and 15.0 μm, and the average circularity is 0.88 and 0.89, respectively. The particle size and regular shape characteristics of the 16 μm target microplastic are highly matched, proving that the algorithm can accurately identify particles in high-purity microplastic samples. The detection results of the leachate show a significant time sequence rule: in the 1 min leachate, the total number of small tube particles is 379 and 304, and the total number of large tube particles is 460 and 514, respectively. The average particle size is concentrated in 14.6-15.9 μm, and the average circularity is 0.89-0.90, which is consistent with the particle size and shape characteristics of the microplastic stock solution, in line with the rule of microplastic preliminary migration during leaching process. In the 10 min leachate, the total number of small tube particles decreases to 28 and 36, and the total number of large tube particles decreases to 46 and 50, respectively. The average diameter is 14.1-15.1 μm, and the average circularity is 0.83-0.88. The particle number decreases with the increase of leaching time, which is consistent with the migration characteristics of microplastic gradually retarding in porous medium, further proving that the identified particles are microplastics. The quartz sand used in the experiment (particle size 0.55 μm-1 mm, simulating gravel) is not recognized and counted by the algorithm due to its irregular shape (circularity is significantly lower than that of microplastic) and chaotic light reflection (differing significantly from the uniform light reflection characteristics of microplastic), indicating that the algorithm can effectively distinguish microplastic from matrix particles such as sand.

[0104] Table 1 Total number of microplastic particles, average particle size, and average circularity parameters

[0105] Sample type Total number of particles Average diameter Average circularity Microplastic stock solution-1 1213 15.6 0.88 Microplastic stock solution-2 1269 15.85 0.89 Small tube-1 min leachate-1 379 15.09 0.89 Small tube-1 min leachate-2 304 14.6 0.9 Small tube-10 min leachate-1 28 14.61 0.89 Small tube-10 min leachate-2 36 14.22 0.88 Large tube-1 min leachate-1 460 16.7 0.89 Large tube-1 min leachate-2 514 15.91 0.89 Large tube-10 min leachate-1 46 14.81 0.88 Large tube-10 min leachate-2 50 15.08 0.83

[0106] Therefore, the present embodiment verifies the specific recognition and accurate counting ability of the microplastic image processing counter algorithm of the present disclosure to 16 μm microplastic particles, and can effectively distinguish microplastic particles from sand, dust and other particles in the matrix. This result directly supports the applicability of the algorithm in microplastic migration research, and further confirms the detection reliability of the semi-automatic multi-connection soil column system of the present disclosure.

[0107] It should be understood that the various forms of flow shown above can be reordered, added, or deleted steps. For example, each step described in the present disclosure can be executed in parallel, sequentially, or in a different order, as long as the desired results of the technical solutions of the present disclosure can be achieved, which is not limited herein.

[0108] In addition, the terms "first", "second" are only for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of indicated technical features. Therefore, the features defined with "first", "second" can explicitly or implicitly include at least one of the features. In the description of the present disclosure, the meaning of "a plurality of" is two or more, unless otherwise specifically limited.

[0109] The above is only a specific embodiment of the present disclosure, but the protection scope of the present disclosure is not limited thereto, and any person skilled in the art can easily think of changes or replacements within the technical scope disclosed by the present disclosure, which should be covered within the protection scope of the present disclosure. Therefore, the protection scope of the present disclosure should be subject to the protection scope of the claims.

Claims

1. A semi-automated multi-soil column system for microplastic migration research, characterized in that, The semi-automatic multi-soil column system includes an automatic liquid receiving system, an automatic liquid transfer system, and a detection system for multi-soil columns. in, The multi-soil column automatic liquid collection system includes three soil columns, an automatic liquid collection turntable, and a spraying device. The lower end of each soil column has a drainage outlet. The automatic liquid collection turntable is located directly below the soil column and has three concentric sample positions (inner, middle, and outer) corresponding to the drainage outlets of the three soil columns, used to automatically receive the leachate discharged from the drainage outlets. The spraying device is located directly above the soil column and is used to spray the leachate onto the soil column. The automated pipetting system includes a three-axis robotic arm, a fully automated pipette, a pipette tip box, a sampling point, and a counting plate. The three-axis robotic arm moves along the X, Y, and Z axes to control the movement of the fully automated pipette towards the sampling point, the pipette tip box, and the counting plate to complete the pipetting. The fully automated pipette is mounted at the end of the three-axis robotic arm. The detection system includes a microplastic image processing counter; the microplastic image processing counter has a built-in CMOS optical imaging system, whose control program is set to realize the functions of automatic focusing, automatic detection path planning, and using the CMOS optical imaging system to take pictures, and integrates algorithms to identify microplastic particles and output concentration, roundness and particle size distribution parameters.

2. The semi-automated multi-soil column system according to claim 1, characterized in that, The soil column is a modular column, consisting of several independently detachable shell sections. Each shell section has a flange interface at its end, which is connected and sealed by clamps and silicone gaskets.

3. The semi-automated multi-soil column system according to claim 1, characterized in that, The automatic liquid receiving turntable is a circular automatic liquid receiving turntable with 50 sample positions per revolution, totaling 150 sample points. Its control program is preset with time intervals and is driven to rotate by a stepper motor.

4. The semi-automated multi-soil column system according to claim 1, characterized in that, The semi-automatic multi-soil column system also includes three peristaltic pumps, which are connected to the spraying device through reinforced silicone pump pipes to control the flow rate of the leachate sprayed onto the three soil columns.

5. The semi-automated multi-soil column system according to claim 1, characterized in that, The spraying device is a multi-hole spray nozzle used to evenly spray the leachate onto the top of the soil column, simulating natural precipitation or irrigation.

6. The semi-automated multi-soil column system according to claim 1, characterized in that, The pipetting process is as follows: move the pipette tip to the pipette tip box to grab a new tip, move it to the sampling point to draw up the exudate, move it to the counting plate to inject the exudate, and withdraw the tip. A new tip is automatically replaced for each sampling point of exudate.

7. The semi-automated multi-soil column system according to claim 1, characterized in that, The built-in CMOS optical imaging system of the microplastic image processing counter has a pixel count of no less than 6.3 million pixels. Preferably, the autofocus function is driven by a Z-axis movement component; More preferably, the automatic detection path planning function automatically moves and focuses on at least 5 different field-of-view positions of the same sample.

8. The semi-automated multi-soil column system according to claim 1, characterized in that, The algorithm of the microplastic image processing counter can automatically identify, segment, and count microplastic particles in images.

9. The semi-automated multi-soil column system according to claim 1, characterized in that, The multi-column automatic liquid receiving system also includes a waste liquid treatment device, which includes a waste liquid channel and a waste liquid tank. The waste liquid channel is a guide groove opened at the edge of the automatic liquid receiving turntable and is connected to the waste liquid tank. It is used to guide the outflow liquid during non-liquid receiving periods or cleaning stages into the waste liquid tank.

10. An analytical method for studying microplastic migration in a semi-automated multi-soil column system according to any one of claims 1-9, characterized in that, Includes the following steps: (1) Soil column filling and saturation: The shell is assembled into 3 soil columns, and soil is filled and compacted from bottom to top. After deionized water is introduced and the soil is saturated, a microplastic pollution mixed layer is added to the top layer. (2) Controllable leaching and timed liquid collection: Adjust the flow rate of the peristaltic pump, spray the leaching liquid onto the soil column through the spraying device, start the automatic liquid collection turntable to rotate at a preset time interval, so that the effluent of the 3 soil columns flows into the storage tubes corresponding to the sample points in the inner, middle and outer rings respectively, obtain the effluent of all sample points and transfer it to the sampling point. (3) Automatic pipetting: Start the three-axis robotic arm to control the fully automatic pipette to transfer the exudate from all sampling points to the counting plate. The pipette tip is automatically replaced every time the exudate from a sampling point is transferred. (4) Automated detection: Start the microplastic image processing counter, insert the counting plate after pipetting into the microplastic image processing counter, control the autofocus and automatically plan the detection path, use the CMOS optical imaging system to take pictures, analyze the captured images through the algorithm, and output the concentration, roundness and particle size distribution of microplastic particles in the time series. (5) Microplastic residue analysis: Disassemble the soil column, extract microplastics from each soil layer, and use the method in steps (3)-(4) to detect the concentration, roundness and particle size distribution of microplastic particles in the longitudinal depth; (6) Data integration: Combine the concentration and size distribution data of microplastic particles in the time series with the concentration and size distribution data of microplastic particles in the vertical depth to draw migration and penetration curves and calculate migration rate and retention amount.

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