A method and device for automatically counting algae

Abstract

The present invention discloses a method and device for automatically counting algae, which obtains multiple sub-videos, wherein the sub-videos are obtained by photographing the algae in the water sample flowing through the microfluidic chip through a microscope and a camera; the algae concentration displayed in each sub-video is calculated, and the real concentration of the algae in the water sample is calculated based on the algae concentration displayed in each sub-video. The present invention does not need to observe all algae samples, but only needs to observe samples of some algae, and the concentration of algae in surface water can be calculated according to statistical laws, which overcomes the disadvantage that a zoom camera cannot be used when collecting video.

Description

Technical Field

[0001] The invention relates to the technical field of algae counting, and in particular to a method and a device for automatic algae counting. Background Art

[0002] The phenomenon of algae blooms that occur from time to time in surface water seriously affects the drinking water safety of the surrounding people. Therefore, timely and accurate counting of the number of algae in the water body can accurately determine the safety of the water body. The conventional method is to use reagents to fix the surface water samples containing algae and then concentrate them, and then manually count the concentrated samples under a microscope. This method is very time-consuming, so there is a certain lag in judging the actual safety status of the water body.

[0003] Since the manual counting of algae in water bodies lags behind the actual production needs, the use of artificial intelligence to assist in the intelligent counting of algae has become an objective need. Currently, the related methods based on artificial intelligence are:

[0004] Solution 1: Place the concentrated water sample after artificial pretreatment on a glass slide. The position of the glass slide in space can be controlled by a computer. The third eye can only use the objective lens and an external digital device (which can have a certain digital magnification capability) to obtain the morphology of algae in the water sample. The digital device is used to automatically and continuously take pictures of the water sample. Artificial intelligence technology is used to automatically count the algae in the photos taken. The defect of this solution is that it still requires cumbersome manual means to concentrate the water sample. Since the concentration of algae cells in surface water is unknown, the concentration of algae cells in the concentrated water sample may be extremely high, causing different algae to overlap with each other; at the same time, due to the depth of field problem of the objective lens, all algae under the objective lens cannot be photographed, so this method cannot truly reflect the concentration of algae cells in surface water samples. Since the water sample needs to be pretreated manually, this solution cannot be used for online algae counting in the field.

[0005] Solution 2: Pump the water sample after pretreatment to remove impurities such as particles into several channels. The sizes of these channels are different, suitable for algae of different sizes. The algae counting results in the water sample can be obtained by taking pictures of the algae in different channels with different microscopes and then counting the pictures with artificial intelligence. This solution is not suitable for water samples with high sediment content or algae agglomeration, otherwise the channel may be blocked. This solution cannot be used for field online algae counting of inland surface water. It is mainly used for online counting of algae in seawater.

[0006] Solution 3: Pump the water sample after pretreatment to remove impurities such as particles into several channels. The diameters of these channels are the same. After the water sample is synchronously pumped into these channels by a peristaltic pump, the peristaltic pump stops working. Use a trinocular microscope with a movable stage and variable focus to take pictures of the algae in any channel, and then use artificial intelligence to count the obtained photos. The counting results of all channels are compared with each other. The average of two close results is used as the counting result of the algae in the water sample. The disadvantage of this solution is that the number of water samples used is small, the uncertainty of the results is large, and it is time-consuming.

[0007] Solution 4: No need to pre-treat the water sample. Pump the surface water directly into a flow cytometer tube with a size of millimeters. There is a large amount of sheath fluid in the flow cytometer tube to keep the water sample stable in the middle of the tube. At the same time, the algae cells in the water sample flow through the flow cytometer tube one by one. The algae cells are irradiated with laser, and the algae are counted by analyzing the properties of the forward light and scattered light. At the same time, after laser irradiation, the algae represented by the ultra-high sensitivity photosensitive element can be photographed to obtain the morphology of a certain type of algae cell. The disadvantage of this solution is that the photos taken can only be black and white, and it is difficult to obtain a high accuracy even with machine learning. Different algae may be confused with each other when using laser for qualitative analysis of algae. Summary of the invention

[0008] In view of the above-mentioned shortcomings of the prior art, an object of the present invention is to provide a method and device for automatically counting algae.

[0009] In order to solve the above technical problems, the present invention adopts the following technical solutions:

[0010] According to a first technical solution of the present invention, a method for automatic algae counting is provided, the method comprising:

[0011] Acquire multiple sub-videos, wherein the sub-videos are obtained by photographing the algae in the water sample flowing through the microfluidic chip using a microscope and a camera;

[0012] The algae concentration shown in each sub-video is calculated using the following formula (1):

[0013] X i =Y i / (K·t·P) Formula (1)

[0014] Where t is the duration of the sub-video, K is the flow rate of the water sample entering the microfluidic chip, P is the probability of algae being captured by the camera in the microfluidic chip, and Y i is the number of algae captured by the camera, where X i Y is measured within t time iWhen there are algae, the concentration of algae in the water sample is calculated;

[0015] According to the algae concentration shown in each molecular video, the actual concentration of algae in the water sample is calculated by the following formula (2):

[0016]

[0017] Among them, x is the actual concentration of algae in the water sample, E(X i ) is X i The mathematical expectation of .

[0018] Furthermore, the multi-molecule videos are obtained by the following method: a water sample is pumped into a microfluidic chip, the algae flowing in the microfluidic chip are photographed by a microscope and a camera to obtain a video, and the video is divided into N molecular videos at the same time interval.

[0019] Furthermore, the multi-molecule video is obtained by the following method: a water sample is pumped into the microfluidic chip, and the algae flowing in the microfluidic chip are photographed repeatedly within a time t using a microscope and a camera to obtain the multi-molecule video.

[0020] Furthermore, the water sample is processed by the following method: inorganic particles in the surface water are separated from algae by sedimentation, and algae aggregated together are broken up by ultrasound or stirring.

[0021] Furthermore, the water sample is processed by the following method: inorganic particles in the surface water are separated from algae by sedimentation, and algae aggregated together are broken up by ultrasound or stirring and then diluted.

[0022] According to a second technical solution of the present invention, there is provided a device for automatic algae counting, the device comprising a water sample storage unit, a sample injection tube, a syringe pump, a microfluidic chip, a camera acquisition unit and a control unit;

[0023] The water sample storage unit is used to store water samples. The water sample storage unit is connected to the inlet end of the microfluidic chip through a sample injection tube. The injection tube is provided with the injection pump. The video acquisition unit is provided on one side of the microfluidic chip to capture algae in the water sample flowing through the microfluidic chip to obtain multiple molecular videos. The video acquisition unit at least includes a camera and a microscope. The video acquisition unit is connected to the control unit by signal.

[0024] The control unit is configured to receive multiple sub-videos collected by the video collection unit, and calculate the algae concentration displayed in each sub-video by the following formula (1):

[0025] X i =Yi / (K·t·P) Formula (1)

[0026] Where t is the duration of the sub-video, K is the flow rate of the water sample entering the microfluidic chip, P is the probability of algae being captured by the camera in the microfluidic chip, and Y i is the number of algae captured by the camera, where X i Y is measured within t time i When there are algae, the concentration of algae in the water sample is calculated;

[0027] According to the algae concentration shown in each molecular video, the actual concentration of algae in the water sample is calculated by the following formula (2):

[0028]

[0029] Among them, x is the actual concentration of algae in the water sample, E(X i ) is X i The mathematical expectation of .

[0030] Furthermore, the video acquisition unit acquires the plurality of sub-videos by the following method: pumping a water sample into a microfluidic chip, photographing the algae flowing in the microfluidic chip through a microscope and a camera to obtain a video, and dividing the video into N sub-videos at the same time interval;

[0031] Furthermore, the video acquisition unit acquires the multiple molecular videos by the following method: pumping the water sample into the microfluidic chip, repeatedly photographing the algae flowing in the microfluidic chip within time t through a microscope and a camera to obtain the multiple molecular videos.

[0032] Furthermore, the device also includes a water sample pretreatment unit, which includes a sedimentation mechanism and an ultrasonic or stirring mechanism that are connected in sequence. The sedimentation mechanism is used to separate inorganic particles from algae in surface water and transport them to the ultrasonic or stirring mechanism, and the ultrasonic or stirring mechanism is used to break up algae that are gathered together to form aggregates.

[0033] Furthermore, the water sample pretreatment unit also includes a dilution mechanism connected to the ultrasonic or stirring mechanism, and the dilution mechanism is used to dilute the water sample treated by the ultrasonic or stirring mechanism.

[0034] Compared with the prior art, the present invention has the following beneficial effects:

[0035] 1) It is not necessary to observe all algae samples, but only some algae samples to calculate the concentration of algae in surface water according to statistical laws. This overcomes the disadvantage of not being able to use a zoom camera when collecting video.

[0036] 2) Compared with the solution 1 mentioned in the background technology: the flow of water samples in the detection device is continuous, and surface water can be continuously pumped into the microfluidic chip, without the need for a control system to operate the injection pump; there is no need to concentrate the water sample and construct a sample on a glass slide;

[0037] 3) Compared with Solution 2 mentioned in the background art: there is only one flow channel and related hardware, and the hardware requirements are significantly reduced;

[0038] 4) Compared with Solution 3 mentioned in the background technology: there is no need to use a zoom photography device on the third eye of the microscope, nor is there a need for a software-controlled mechanical stage, which significantly reduces the technical difficulty and cost, and there is no need to interrupt the working state of the sample water pump.

[0039] 5) Compared with solution 4 mentioned in the background art: no complicated photoelectric (laser) technology and high-sensitivity photosensitive elements are used to count and qualitatively analyze algae, which significantly reduces the technical complexity. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In the drawings, which are not necessarily drawn to scale, the same reference numerals may describe similar parts in different views. The same reference numerals with letter suffixes or different letter suffixes may represent different instances of similar parts. The accompanying drawings generally illustrate various embodiments by way of example and not limitation, and together with the specification and claims, are used to illustrate the disclosed embodiments. When appropriate, the same reference numerals are used throughout the drawings to refer to the same or similar parts. Such embodiments are illustrative and are not intended to be exhaustive or exclusive embodiments of the present apparatus or method.

[0041] Figure 1 is a flow chart of a method for automatic algae counting in an embodiment of the present invention;

[0042] Figure 2 It is a structural schematic diagram of an algae automatic counting device in an embodiment of the present invention;

[0043] Figure 3 It is a structural schematic diagram of an algae automatic counting device in an embodiment of the present invention;

[0044] Figure 4 Schematic diagram of the operation of the microfluidic chip in an embodiment of the present invention. DETAILED DESCRIPTION

[0045] The following examples are only for better explanation of the present invention, but the content of the present invention is not limited to the application in the examples. Therefore, those skilled in the art can make non-essential improvements and adjustments to the implementation scheme according to the above content of the invention and apply them to other examples, which are still within the protection scope of the present invention.

[0046] The embodiment of the present invention provides a method for automatically counting algae, such as Figure 1 As shown, the method starts at step S100, where a plurality of sub-videos are obtained, wherein the sub-videos are obtained by photographing the algae in the water sample flowing through the microfluidic chip using a microscope in conjunction with a camera.

[0047] It should be noted that the sub-videos in the embodiment of the present invention can be individual videos equally intercepted from a continuous video at preset time intervals or individual video segments collected in segments by using a microscope and a camera. The sub-videos should at least contain the image information of the algae.

[0048] In some embodiments, the multiple sub-videos are obtained by the following method: a water sample is pumped into a microfluidic chip, algae flowing in the microfluidic chip are photographed using a microscope and a camera to obtain a video, and the video is divided into N sub-videos at the same time intervals.

[0049] In some embodiments, the multiple sub-videos are obtained by the following method: a water sample is pumped into a microfluidic chip, and the algae flowing in the microfluidic chip are photographed repeatedly within a time t using a microscope and a camera to obtain the multiple sub-videos.

[0050] In step S200, the algae concentration displayed in each sub-video is calculated by the following formula (1):

[0051] X i =Y i / (K·t·P) Formula (1)

[0052] Where t is the duration of the sub-video, K is the flow rate of the water sample entering the microfluidic chip, P is the probability of algae being captured by the camera in the microfluidic chip, and Y i is the number of algae captured by the camera, where X i Y is measured within t time i When there are algae, the concentration of algae in the water sample is calculated;

[0053] Finally, in step S300, the actual concentration of algae in the water sample is calculated according to the algae concentration displayed in each molecular video by the following formula (2):

[0054]

[0055] Among them, x is the actual concentration of algae in the water sample, E(X i ) is X i The mathematical expectation of .

[0056] In the embodiment of the present invention, the real concentration of algae specifically refers to the real concentration of a certain type of algae. Because the method proposed in the embodiment of the present invention can obtain high-definition video images, it can be combined with image recognition technology to calculate the real concentration of each algae in a water sample containing multiple algae. Specifically, assuming that there are multiple algae in the water sample, namely four types of algae A, B, C, and D, the number of each algae A, B, C, and D captured by the camera can be calculated based on the different sizes and shapes of different algae through image recognition and comparison technology. The corresponding real concentration of each algae can be calculated according to formula (1) and formula (2).

[0057] In order to reduce costs, the microscope lens and stage in the embodiment of the present invention are preferably fixed.

[0058] To prevent particles from clogging the microfluidic channel, the size of the microfluidic chip should be larger than the largest algae in surface water, but of moderate size. For example, the microfluidic chip is 0.4 mm high and 0.5 mm wide.

[0059] In order to clearly photograph the algae and meet the requirements of artificial intelligence technology for sample clarity, the embodiment of the present invention intends to use a high-magnification objective lens, such as a 40X objective lens with a camera mounted on a third eye to record the algae. The defect of a high-magnification objective lens is that its field of view is small. Due to the small field of view, it is difficult to record all algae within a range of 0.5mm. Therefore, there is a certain probability that the algae flowing through the microfluidic chip will not be detected by the camera. In order to accurately measure the amount of algae in the water sample under this defect, the embodiment of the present invention conducts the following theoretical demonstration:

[0060] After pretreatment and dilution, and with the lower water sample flow rate provided by the injection pump, the algae in the water sample can flow through the microfluidic chip one by one. Without loss of generality, assume that there is only one type of algae in the water sample, and its concentration is x / L. The flow rate of the water sample entering the microfluidic chip is KL / min, the operation time is t min (i.e., the duration of the sub-video, which records a water sample flow image with a preset operation time t), and the probability of algae being captured by the camera in the microfluidic chip is P. During the operation time, the number of algae captured by the camera is Y i Then, based on the measurement results, the concentration of the algae in the water sample can be calculated using the formula shown in formula (1).

[0061] If the water sample is tested N times continuously, then X i The mathematical expectation of is equal to the actual concentration x of the algae in the water sample, that is,

[0062]

[0063] It can be seen that the water sample is continuously tested within a long time T min, and the long time is divided into N testing stages. As long as T and N are large enough and the probability P can be determined in advance, it is possible to accurately determine the exact concentration x of the algae even if the camera cannot fully cover the width of the microfluidic chip. Due to the use of a high-magnification objective lens, this solution can obtain a clear image of the algae.

[0064] Therefore, both the concentration and the taxonomy of the algae can be accurately determined.

[0065] Since the water sample can be diluted, the flow rate of the water sample can be maintained at a low level. Even if there are many different algae in the water sample, as long as they are allowed to enter the field of view of the microscope one by one and are captured by the high-definition microscope camera, the number of algae species in the water sample will not affect the accuracy of this scheme.

[0066] The P corresponding to different algae in the above formula is different. A suspension of pure cultured algae with a known cell concentration can be used as a water sample for determination. Therefore, the above formula is operational.

[0067] The present invention also provides a device for automatically counting algae. Figure 2 As shown, the device includes a water sample storage unit 1, a sample injection tube 2, a syringe pump 3, a microfluidic chip 4, a camera acquisition unit 5 and a control unit 6.

[0068] The water sample storage unit 1 is used to store water samples. The water sample storage unit 1 is connected to the inlet end of the microfluidic chip 4 through the sample injection tube 2. The injection tube 2 is provided with the injection pump 3. The video acquisition unit 5 is arranged on one side of the microfluidic chip 4 to capture the algae in the water sample flowing through the microfluidic chip 4 to obtain multiple molecular videos. The video acquisition unit 5 at least includes a camera and a microscope. The video acquisition unit 5 is connected to the control unit 6 by signal.

[0069] The control unit is configured to receive multiple sub-videos collected by the video collection unit, and calculate the algae concentration displayed in each sub-video by the following formula (1):

[0070] X i =Y i / (K·t·P) Formula (1)

[0071] Where t is the duration of the sub-video, K is the flow rate of the water sample entering the microfluidic chip, P is the probability of algae being captured by the camera in the microfluidic chip, and Y i is the number of algae captured by the camera, where X iY is measured within t time i When there are algae, the concentration of algae in the water sample is calculated;

[0072] According to the algae concentration shown in each molecular video, the actual concentration of algae in the water sample is calculated by the following formula (2):

[0073]

[0074] Among them, x is the actual concentration of algae in the water sample, E(X i ) is X i The mathematical expectation of .

[0075] It should be noted that the "water sample storage unit" described herein can be specifically implemented as a device having a space for accommodating water samples, such as a water tank. The signal connection between the video acquisition unit 5 and the control unit 6 includes at least one of connection through a wire, connection through a WiFi module, connection through a Bluetooth module, and connection through a 2G / 3G / 4G / 5G module, and a combination thereof.

[0076] The control unit 6 can be a processor or a device equipped with a data processing chip. Among them, the processor can be a processing device including one or more general-purpose processing devices, such as a microprocessor, a central processing unit (CPU), a graphics processing unit (GPU), etc. More specifically, the processor can be a complex instruction set computing (CISC) microprocessor, a reduced instruction set computing (RISC) microprocessor, a very long instruction word (VLIW) microprocessor, a processor running other instruction sets, or a processor running a combination of instruction sets. The processor can also be one or more special-purpose processing devices, such as an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA), a digital signal processor (DSP), a system on a chip (SoC), etc. The device equipped with a data processing chip can be an office computer or a smart phone, etc.

[0077] In some embodiments, the video acquisition unit acquires the plurality of sub-videos by the following method: pumping a water sample into a microfluidic chip, photographing the algae flowing in the microfluidic chip through a microscope and a camera to obtain a video, and dividing the video into N sub-videos at the same time interval;

[0078] In some embodiments, the video acquisition unit acquires the multiple molecular videos by the following method: pumping a water sample into a microfluidic chip, and repeatedly photographing the algae flowing in the microfluidic chip within a time t using a microscope and a camera to obtain the multiple molecular videos.

[0079] In some embodiments, Figure 3As shown, the device also includes a water sample pretreatment unit, which includes a sedimentation mechanism 7 and an ultrasonic or stirring mechanism 8 connected in sequence. The sedimentation mechanism 7 is used to separate the inorganic particles from the algae in the surface water and transport them to the ultrasonic or stirring mechanism 8. The ultrasonic or stirring mechanism 8 is used to break up the algae that are gathered together to form aggregates.

[0080] It should be noted that the sedimentation mechanism 7 is specifically a mechanism that can separate inorganic particles from algae in surface water and transport them to the ultrasonic or stirring mechanism 8. For example, the sedimentation mechanism 7 can be a sedimentation tank. The sedimentation mechanism 7 can transport the water sample after sedimentation treatment to the ultrasonic or stirring mechanism 8 by pipeline transportation. The ultrasonic or stirring mechanism 8 means that it can be a mechanism that can realize the ultrasonic function alone or the stirring function alone or realize the ultrasonic and stirring functions at the same time. The ultrasonic mechanism that realizes the ultrasonic function alone, for example, an ultrasonic generator is set at the lower end of a box body, and the water sample in the box body is ultrasonically subjected to the ultrasonic function to break up the algae that gather together to form agglomerates. The stirring function that realizes the stirring function alone is a stirring mechanism, for example, a stirring tank or a stirring blade is set inside a container, and the water sample inside the container is stirred to break up the algae that gather together to form agglomerates. The mechanism that realizes ultrasonic and stirring at the same time, for example, in a container, an ultrasonic generator is set at the bottom, and a stirring blade is set from the top to break up the algae that gather together to form agglomerates by ultrasonic and mechanical stirring at the same time.

[0081] In some embodiments, the water sample pretreatment unit further includes a dilution mechanism 9 connected to the ultrasonic or stirring mechanism, and the dilution mechanism 9 is used to dilute the water sample treated by the ultrasonic or stirring mechanism. The dilution mechanism 9 can be any device that can dilute the water sample treated by the ultrasonic or stirring mechanism, such as an ordinary water tank with a water injection port, etc.

[0082] The technical effects of the automatic algae counting device in each embodiment of the present invention are basically consistent with the previous automatic algae counting method, which will not be described in detail here.

[0083] The following embodiments of the present invention will further illustrate the feasibility and innovation of the present invention in combination with specific experimental methods.

[0084] use Figure 3 The device shown. The microchannel is 0.5 mm wide, 0.4 mm high, and has an area of ​​2×10 -7 The flow rate of the injection pump is 0.002 ml / min, and the flow rate of the liquid in the microfluidic chip is 166 μm / s. The time it takes for the algae to flow through the field of view of the objective lens (i.e. the field of view of the camera) is about 2 seconds.

[0085] A camera with a frame rate of 20fps is sufficient to clearly capture the algae in the field of view within 2 seconds.

[0086] Limited by the eyepiece field of view, the camera captures images in the following areas: 300 μm along the length direction and 220 μm perpendicular to the length direction. Therefore, the camera's imaging range is less than half of the width of the microchannel. Therefore, the camera cannot cover the entire channel width, so there is a blind spot in the camera's imaging range ( Figure 4 ).

[0087] In order to count accurately, the camera takes 30 samples, each for 5 minutes, and the total sampling time is 150 minutes. The flow rate is 0.002mL / min. If the average number of algae detected within 5 minutes is 1, the probability of the algae being detected when it flows through the camera's field of view is 0.25. Then according to the above formula, calculate Figure 1 The concentration of the algae in the treated surface water is shown to be 4×105 cells / L.

[0088] The concentration of algae in the water sample is obtained by adding up the concentrations of all algae.

[0089] The above description is intended to be illustrative rather than restrictive. For example, the above examples (or one or more of them) can be used in combination with each other. For example, a person of ordinary skill in the art can use other embodiments when reading the above description. In addition, in the above-mentioned specific embodiments, various features can be grouped together to simplify the present disclosure. This should not be interpreted as an intention that a disclosed feature that is not required to be protected is necessary for any claim. On the contrary, the subject matter of the present invention may be less than all the features of a specific disclosed embodiment. Thus, the following claims are incorporated into the specific embodiments as examples or embodiments, wherein each claim is independently used as a separate embodiment, and it is considered that these embodiments can be combined with each other in various combinations or arrangements. The scope of the present invention should be determined with reference to the attached claims and the full scope of equivalent forms granted by these claims.

Claims

1. A method for automatically counting algae, characterized in that: The method comprises: Acquire multiple sub-videos, wherein the sub-videos are obtained by photographing algae in a water sample flowing through a microfluidic chip using a microscope and a camera; The algae concentration shown in each sub-video is calculated using the following formula (1): X i = Y i / (K·t·P) formula(1) Where t is the duration of the sub-video, K is the flow rate of the water sample entering the microfluidic chip, P is the probability of algae being captured by the camera in the microfluidic chip, and Y i is the number of algae captured by the camera, where X i Y is measured within t time i When there are algae, the concentration of algae in the water sample is calculated; According to the algae concentration shown in each molecular video, the actual concentration of algae in the water sample is calculated by the following formula (2): Among them, x is the actual concentration of algae in the water sample, E(X i ) is X i The mathematical expectation of .

2. The method according to claim 1, characterized in that The multiple sub-videos are obtained by the following method: The water sample is pumped into the microfluidic chip, and the algae flowing in the microfluidic chip are photographed by a microscope and a camera to obtain a video, and the video is divided into N parts at the same time interval.

3. The method according to claim 1, characterized in that The multiple sub-videos are obtained by the following method: The water sample is pumped into the microfluidic chip, and the algae flowing in the microfluidic chip are photographed repeatedly within a time t using a microscope and a camera to obtain the multi-molecule video.

4. The method according to any one of claims 1 to 3, characterized in that: The water sample is processed by the following method: Inorganic particles in surface water are separated from algae by sedimentation, and algae aggregates that have gathered together are broken up by ultrasound or stirring.

5. The method according to any one of claims 1 to 3, characterized in that: The water sample is processed by the following method: Inorganic particles in surface water are separated from algae by sedimentation, and algae aggregated together are broken up by ultrasound or stirring and diluted.

6. A device for automatically counting algae, characterized in that: The device comprises a water sample storage unit, a sample injection tube, a syringe pump, a microfluidic chip, a camera acquisition unit and a control unit; The water sample storage unit is used to store water samples. The water sample storage unit is connected to the inlet end of the microfluidic chip through a sample injection tube. The injection tube is provided with the injection pump. The video acquisition unit is provided on one side of the microfluidic chip to capture algae in the water sample flowing through the microfluidic chip to obtain multiple molecular videos. The video acquisition unit at least includes a camera and a microscope. The video acquisition unit is connected to the control unit by signal. The control unit is configured to receive multiple sub-videos collected by the video collection unit, and calculate the algae concentration displayed in each sub-video by the following formula (1): X i = Y i / (K·t·P) formula(1) Where t is the duration of the sub-video, K is the flow rate of the water sample entering the microfluidic chip, P is the probability of algae being captured by the camera in the microfluidic chip, and Y i is the number of algae captured by the camera, where X i Y is measured within t time i When there are algae, the concentration of algae in the water sample is calculated; According to the algae concentration shown in each molecular video, the actual concentration of algae in the water sample is calculated by the following formula (2): Among them, x is the actual concentration of algae in the water sample, E(X i ) is X i The mathematical expectation of .

7. The device according to claim 6, characterized in that The video acquisition unit acquires the multiple sub-videos by the following method: The water sample is pumped into the microfluidic chip, and the algae flowing in the microfluidic chip are photographed by a microscope and a camera to obtain a video, and the video is divided into N parts at the same time interval.

8. The device according to claim 6, characterized in that The video acquisition unit acquires the multiple sub-videos by the following method: The water sample is pumped into the microfluidic chip, and the algae flowing in the microfluidic chip are photographed repeatedly within a time t using a microscope and a camera to obtain the multi-molecule video.

9. The device according to any one of claims 6 to 8, characterized in that: The device also includes a water sample pretreatment unit, which includes a sedimentation mechanism and an ultrasonic or stirring mechanism connected in sequence. The sedimentation mechanism is used to separate inorganic particles from algae in surface water and transport them to the ultrasonic or stirring mechanism, and the ultrasonic or stirring mechanism is used to break up algae that are gathered together to form aggregates.

10. The device according to claim 9, characterized in that The water sample pretreatment unit further comprises a dilution mechanism connected to the ultrasonic or stirring mechanism, and the dilution mechanism is used to dilute the water sample treated by the ultrasonic or stirring mechanism.

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