58 results about "Phytoplankton" patented technology

The invention discloses a marine phytoplankton abundance monitoring method based on data driving and an underwater acoustic network, and the method comprises the steps: building and training a multi-level spatial-temporal feature integration model based on the historical marine phytoplankton abundance and the corresponding marine environment data, and solving the optimal spatial position and monitoring time window of an underwater acoustic network node; constructing a teacher model which comprises a multi-layer cascade structure and a residual module and is used for channel prediction, and compressing the teacher model into a student model by adopting spatio-temporal knowledge distillation; the student model is trained, and channel state real-time prediction is realized at the underwater acoustic network node; on the basis of the optimal spatial position of an underwater acoustic network node and a real-time predicted channel state, adaptive underwater acoustic communication models and seasonal optimal routing strategies are matched, adaptive modulation and coding are executed at a link level, and monitoring of abundance of phytoplankton is completed based on an underwater acoustic network. According to the invention, the data throughput and prediction precision can be improved under strict energy consumption constraints.

The invention provides a phytoplankton chromatography sequence identification method and a phytoplankton chromatography sequence model building method, and belongs to the technical field of image enhancement identification. The method comprises the following steps: firstly, acquiring microscopic chromatography sequence data of phytoplankton, performing view field extraction and serialization recombination, and constructing a three-dimensional data set; then, constructing a three-dimensional recognition model containing physical perception and a sequence aggregation mechanism, extracting single-frame semantic features by the model by adopting a parameter-shared twin network, and introducing a physical definition prior module to calculate a space-frequency domain quality score of a slice; secondly, designing a deep perception sequence aggregation module, and adaptively aggregating key features of a high signal-to-noise ratio by taking definition scores as gating signals and combining spatial context information between slices; and finally, training and optimizing the model based on the image-level weak supervision label to obtain an optimal model. According to the method, the problems of information truncation and out-of-focus noise interference caused by extremely shallow depth of field of high-power microscopic imaging are solved, and full-depth-of-field stereoscopic perception can be realized under the condition that frame-by-frame fine labeling is not needed.

The invention discloses a method for determining a toughness and catastrophe threshold value of a functional group of a water ecosystem, and relates to the technical field of water environment ecological engineering.The method comprises the steps that the state of a target water ecosystem is determined according to the total nitrogen content, the total phosphorus content and the chlorophyll content of a water body in the target water ecosystem, the state of the target water ecosystem is eutrophication or non-eutrophication; determining the biomass of phytoplankton based on the target water ecosystem state; utilizing an Ecopath model to construct a static food network relation model of the target water ecosystem; based on the target water ecosystem state, the biomass of the phytoplankton and the static food network relation model, determining a toughness threshold value and a catastrophe threshold value of the biomass of each functional group; each functional group is a plurality of groups for dividing species in the target water ecosystem. According to the method, the water ecosystem functional group toughness threshold value and the catastrophe threshold value which are simple to operate and high in accuracy can be provided.

The invention provides a novel mudflat efficient photovoltaic breeding system. The novel mudflat efficient photovoltaic breeding system comprises an arc-shaped ditch bottom, a side ditch, a pool wall, floating objects, a duckweed growth layer, a photovoltaic panel frame, a photovoltaic panel, a pipeline, a control box, a photovoltaic panel support, a first-layer annular pillar lamp, a second-layer annular pillar lamp, a third-layer annular pillar lamp, a fourth-layer annular pillar lamp, a bottom table top and a sponge sleeve. The floating objects comprise phytoplankton and zooplankton, a storage battery, a control panel and a photoelectric detection device are arranged in the control box, the arc-shaped ditch bottom, the side ditch, the pond bottom, the pond wall and the bottom table top form a pond body mechanism facilitating fish gathering and fish lifting, and the photovoltaic panel support, the photovoltaic panel frame, the photovoltaic panel, the control box, the storage battery in the box and the control panel form a photovoltaic mechanism of the fishpond. The first-layer annular pillar lamp, the second-layer annular pillar lamp, the third-layer annular pillar lamp and the fourth-layer annular pillar lamp form a light supplementing mechanism beneficial to photosynthesis, namely growth of phytoplankton, growth of the phytoplankton is beneficial to growth of zooplankton, and growth of fishes is beneficial to growth of the zooplankton.

This invention discloses a data-driven method for monitoring marine phytoplankton abundance using underwater acoustic networks. The method includes: constructing and training a multi-level spatiotemporal feature ensemble model based on historical marine phytoplankton abundance and corresponding marine environmental data to determine the optimal spatial location and monitoring time window of the underwater acoustic network nodes; constructing a teacher model for channel prediction, including a multi-layer cascaded structure and residual modules, and compressing the teacher model into a student model using spatiotemporal knowledge distillation; training the student model to achieve real-time channel state prediction at the underwater acoustic network nodes; matching suitable underwater acoustic communication devices and seasonal optimal routing strategies to each underwater acoustic network node based on the optimal spatial location and real-time predicted channel state, and performing adaptive modulation and coding at the link level, while simultaneously monitoring phytoplankton abundance using the underwater acoustic network. This invention can improve data throughput and prediction accuracy under strict energy consumption constraints.

The application relates to the technical field of water ecological environment monitoring, and discloses an automatic monitoring device for planktonic algae in water and a monitoring method for planktonic algae in water. The automatic monitoring device for planktonic algae in water comprises a water sample preparation module, a water sample slice preparation module and a water sample detection module. The water sample preparation module is used for collecting a water sample and obtaining an algae concentrate of the water sample. The water sample slice preparation module is used for preparing a slice from the algae concentrate and transferring the slice to the water sample detection module. The water sample detection module is used for taking a picture of the planktonic algae in the slice and identifying and counting the algae in the picture by using a preset image visual algorithm. The device realizes automatic sampling, automatic precipitation collection, automatic slice preparation, automatic picture taking, automatic identification and counting of the planktonic algae, does not require manual attendance, saves labor cost, effectively avoids differences in identification results caused by differences in identification abilities of different laboratories and detection personnel, improves the standardization degree of algae detection, and facilitates popularization and application.

This invention provides a geochemical method and system for identifying phytoplankton community succession, relating to the fields of aquatic environmental geochemistry and ecological environment monitoring. The method involves simultaneous sampling of a target water body to determine water chemical parameters, dissolved inorganic carbon, particulate organic carbon, and stable carbon isotopes, while simultaneously acquiring data on the species composition and relative abundance of phytoplankton. Based on the water chemical parameters, the forms and concentrations of dissolved inorganic carbon in the water body are determined to ascertain the carbon source utilization pattern. The stable carbon isotope shift in the water body is determined based on the dissolved inorganic carbon, particulate organic carbon, and stable carbon isotopes. Furthermore, the stage of phytoplankton community succession in the target water body is identified by comparing the carbon source utilization pattern and the stable carbon isotope shift with the indicators. This invention enables early identification of the community succession process based on changes in carbon source utilization patterns, even before changes in phytoplankton community morphology become apparent.

The application discloses a kind of multicomponent plankton algae concentration measurement method based on fluorescence spectrum stratification partitioning.The application belongs to the field of marine aquatic ecological environment monitoring technology.The algorithm will unknown to be analyzed mixed three-dimensional fluorescence spectrum according to the following stratification partitioning analysis idea to be analyzed.First layer: full spectrum is involved in analysis, and the purpose is to analyze cyanophyta concentration and cryptophyta concentration, and obtain the difference spectrum in full spectrum region.Second layer: partitioning analysis, take the region containing effective spectral feature to participate in analysis, and the purpose is to analyze chlorophyll a concentration of green algae, diatom, dinoflagellate and yellow algae.The algorithm is significantly superior to common analysis algorithm in reducing misidentification, especially in processing such as diatom, dinoflagellate and yellow algae with high similarity living body fluorescence spectrum.

The utility model discloses a sampling device for phytoplankton detection. The sampling device comprises a fixed frame, a containing frame arranged on the fixed frame and a fixed square frame fixedly mounted on the inner wall of the containing frame. According to the sampling device for phytoplankton detection, the jacking assembly capable of jacking the bearing frame and the translation assembly for driving the jacking assembly to move left and right are arranged on the containing frame, and when the sampling device is used, the translation assembly can be started to drive the jacking assembly to move to the position below the bearing frame to be jacked up and a plankton sample storage bottle; according to the plankton sampling device, the bearing frame can be jacked up by the jacking assembly, so that the plankton sample storage bottle jacked up on the inner side of the bearing frame is lifted, different planktons can be conveniently and quickly selected for sampling, and meanwhile, the phenomenon that the sample storage bottle possibly inclines in the falling process and cannot accurately fall into the limiting sleeve can be prevented; the influence on subsequent detection or sampling operation is avoided.

The present application relates to marine ecological environment monitoring technical field, disclose a kind of phytoplankton hierarchical sampling device, including annular frame and multiple lifting rings connected with it, further include multiple biological nets connected with annular frame, the lower end of biological net is connected with round tube, and the lower end of round tube is fixedly connected with screen, multiple biological nets are coaxially nested arrangement, and the aperture of multiple biological nets is sequentially reduced from inside to outside. Three biological nets of different aperture are coaxially nested and connected on annular frame (aperture is sequentially reduced from inside to outside aperture), so that large, medium and small different size phytoplankton can be simultaneously completed by hierarchical interception in one sampling, without multiple device lowering, greatly improve sampling efficiency, ensure the purity of sampled phytoplankton sample, reduce error, reduce hierarchical steps, improve deck operation efficiency, improve the overall efficiency of scientific research on the ship, reduce ship time and budget.

The invention discloses a remote sensing estimation method and a remote sensing estimation device for the primary productivity of marine phytoplankton in size fraction, and the method comprises the steps: building an estimation function of the photosynthetic quantum yield of the phytoplankton in the corresponding size fraction based on the relation between the light intensity and the photosynthetic quantum yield of the phytoplankton in the single size fraction; calculating the net primary productivity of the phytoplankton of the corresponding size fraction based on the photosynthetic quantum yield and the average light absorption coefficient of the phytoplankton of the single size fraction under the scale of the light intensity duration and the ocean depth measurement range; and adding the net primary productivity of the phytoplankton in the plurality of size fractions, and calculating to obtain the total primary productivity of the phytoplankton. By adopting the technical scheme, in a framework of light absorption and conversion of the phytoplankton, the light absorption coefficient of the phytoplankton with different size fractions and the size fraction difference of the photosynthetic quantum yield are considered at the same time, an effective scheme for quantitative expression estimation of the phytoplankton is established, the estimation error of the primary productivity caused by neglecting the size fraction difference can be effectively reduced, and the estimation accuracy of the primary productivity is improved. And the estimation accuracy is improved.

This invention relates to a hyperspectral inversion method for phytoplankton absorption coefficients based on multispectral satellites. The method includes fitting a Gaussian decomposition model to the measured phytoplankton absorption coefficient spectrum, selecting several predicted center wavelengths from the center wavelengths of multiple Gaussian curves in the model; establishing a fitting model between the remaining center wavelengths and the predicted center wavelengths; acquiring multispectral remote sensing images, using the remote sensing reflectance and spectral index of the sensitive bands of phytoplankton absorption coefficients as input to train a machine learning model, and obtaining a Gaussian parameter inversion model; using the inversion model and the fitting model to obtain Gaussian parameter values ​​from the multispectral remote sensing images of the lake under test, and substituting them into the Gaussian decomposition model to obtain the phytoplankton absorption coefficient spectrum of the lake under test. This method can solve the problem of the limited applicability of remote sensing inversion algorithms for inherent optical quantities of inland water bodies, and realize the monitoring of phytoplankton absorption coefficients in inland water bodies under different optical conditions.

A passive hydrodynamic apparatus and method for harvesting marine biomass from ambient currents. The apparatus includes a non-sieving retention object comprising a porous 3D network of fibres having a fibre volume fraction (solidity) of less than 5% relative to an envelope volume defined by outer boundaries of the network inside the current. The fibres comprise surface functionalisation and have a fibre diameter of between about 1 micron and about 3000 microns, defining effective void spaces significantly larger than the target biomass particles. Retention is mediated by surface interactions rather than mechanical obstruction, allowing for high capture efficiency of microscopic particles (e.g., phytoplankton) with minimal drag (e.g., drag coefficient is less than 300 at 6 cm / s). A mechanical harvester featuring a sacrificial agitating element may be included to continuously recover biomass while preserving the retention fibres.

The utility model relates to the technical field of water area monitoring, and discloses a sampling device for detecting phytoplankton in a lake, which comprises a placing box, a rotating mechanism is arranged on the upper surface of the placing box, and a reinforcing rod is fixedly connected to the surface of the rotating mechanism. The orientation angle of the salvage net can be flexibly adjusted according to the terrain of a lake, the water flow direction and the predicted distribution condition of phytoplankton, and the angle of the salvage net can be adjusted to be along the water flow direction or form a certain angle with the water flow direction in a lake area with complex water flow, so that the phytoplankton can be salvaged more effectively; depth adjustment is achieved through a second motor, a screw rod, a telescopic rod and a second limiting groove, the depth of the fishing net entering water is controlled, the water entering depth of the fishing net can be adjusted according to the water depth of a lake and the distribution depth of phytoplankton, the sampling quality is improved, and the problems that traditional manual fixed sampling is large in labor amount and high in sampling efficiency are solved. And the sampling depth is difficult to accurately control.

The application discloses a heavy metal pollution treatment device for lake purification and belongs to the technical field of heavy metal pollution treatment, which comprises a ship body, a floating plate slidably connected to the ship body, a buoyancy block connected to the floating plate, a feeding component arranged on the floating plate and used for collecting and cutting phytoplankton, a conveying component arranged on the floating plate and used for conveying the phytoplankton, a group of adjusting components arranged on the two sides of the ship body respectively and used for adjusting the conveying component and detecting whether the ship body is fully loaded or not. No matter how many plants are collected by the ship, the change of the water line of the ship will not affect the position of the cutting device, and the accuracy of rhizome separation is improved. Meanwhile, the leaves are shaken during the leaf collecting process, and most of the water carried by the cup-shaped leaves is screened out. When the weight of the collected plants reaches the rated load of the ship, in order to ensure the safety of the personnel, the collecting plate I and the collecting plate II will automatically close the collecting opening, and the rhizome leaves will not be collected any more.

The present application relates to a kind of phytoplankton imaging flow trait analysis method and system, wherein the method comprises: the single particle image exported by imaging flow cytometry equipment is defined as a phenotype object to be analyzed;From the JPEG annotation section of single particle image, corresponding optical signal field of phenotype object is obtained by byte analysis;Phytoplankton target region segmentation is carried out on single particle image, and phytoplankton target mask is obtained;The two-dimensional morphological characteristics of phenotype object are calculated based on phytoplankton target mask;Two-dimensional morphological characteristics and optical signal field are bound in corresponding phenotype object, and event-level morphological-optical fusion trait vector of phenotype object is generated, and event-level morphological-optical fusion trait vector is output.Using the present application, image morphological information and optical property information are synchronously acquired and fused from the same data source, and the acquisition efficiency of phytoplankton single particle comprehensive characteristics is improved.

To provide a freshness retaining agent excellent in retaining the freshness of chlorophyll.SOLUTION: The freshness of a chlorophyll-containing material is retained by using a freshness retaining agent containing rosmarinic acid, its glycoside, its derivative or its pharmacologically acceptable salt as an active ingredient. Preferably, the freshness of the chlorophyll-containing material is retained by bringing a freshness retaining agent containing rosmarinic acid derived from a perilla seeds extract, its glycoside, its derivative or its pharmacologically acceptable salts as an active ingredient into contact with plants, phytoplankton, algae or their processed products.SELECTED DRAWING: Figure 1

The present invention provides a system and method for enhancing adhesion between microplastics and air bubbles. More specifically, the present invention relates to a system and method for enhancing adhesion between microplastics and air bubbles so that the maximum number of microplastics can be collected from aquatic environments. The pressure difference between the stern section (from the buttock stern to the bottom baseline) and the outflow and inflow of air bubbles maximizes collection efficiency. The collected phytoplankton are reintroduced to the ocean surface to enhance the conversion of carbon dioxide to oxygen as a means of mitigating global warming.

This invention proposes a comprehensive calculation method and system for marine biodiversity based on multiple indices, belonging to the field of marine biodiversity assessment technology. The method acquires species abundance data and environmental parameter data for phytoplankton, zooplankton, and fish in a target sea area; it correlates species occurrence frequency with the numerical range of environmental factors to generate the niche width of each species for each environmental factor, then multiplies this value by relative abundance, sums the results, and compares the sum with the theoretical maximum niche width to generate the overall niche occupancy intensity of the community; based on this intensity, it assigns weights to multiple diversity indices using preset baseline weights to generate dynamic weights; and based on these dynamic weights, it performs a weighted summation of the diversity indices to generate a comprehensive biodiversity index. This invention achieves adaptive weight allocation, improving the accuracy and ecological relevance of the assessment.

The invention provides a causal analysis method and system for ocean heat wave events and chlorophyll changes, which are applied to the technical field of ocean environment monitoring, and are characterized in that a multi-dimensional causal feature matrix is constructed through multi-source long-time sequence environmental data in combination with time-space identifiers and abnormal change sequences of the heat wave events, and the causal analysis result of the heat wave events and chlorophyll changes is obtained through joint probability distribution expression. And performing decomposition calculation on the causal information of the heat wave accumulated intensity characteristic and the dynamic environment element characteristic relative to the chlorophyll abnormal change to obtain multiple types of causal information components, judging the dominant action type of the chlorophyll change according to the proportion of the multiple types of causal information components, and outputting a corresponding causal attribution result. According to the causal analysis method and system for the ocean heat wave event and the chlorophyll change, the causal relationship of the ocean heat wave event to the chlorophyll concentration change of the phytoplankton is analyzed through construction of a multi-dimensional causal feature matrix, joint probability distribution mapping and causal information decoupling.

The present invention relates to a large-scale CO2 capture and neutralization system and marine phytoplankton production system comprising a plurality of production units grouped in sets of 6, 8, or 10 to form a module, where the modules are arranged in a hexagonal, octagonal, or decagonal shape, respectively. Each production unit consists of two concentric tubes made of transparent PMMA material, with the space between the tubes containing a marine phytoplankton culture. The system includes a central distributor, a pump to generate a recirculation circuit, and lighting and a coil arranged in the free space inside each production unit. The distribution of the conduits ensures homogeneity of the contents within the production units to guarantee the production of marine phytoplankton with a photosynthetic yield greater than 8%.

The application discloses a phytoplankton community change marking method and application thereof. The marking method is designed based on the ecological functional group theory and the state space theory, that is, a continuous time sequence is discretized into time periods of any time scale, a regional phytoplankton community index (APCI) of each time period is calculated to quantitatively determine the phytoplankton community state, and then the phytoplankton community change is marked according to the change of the APCI of each time period on a continuous time axis. The marking method of the phytoplankton community change does not need to determine a reference state in advance, the community state is quantitatively determined by the APCI, and the marking method has the advantages of absoluteness, quantitativeness and high sensitivity compared with a marking method using a PCI, can better mark the relationship between the phytoplankton community change and the environment, and is suitable for marking the phytoplankton community change in any water body.

The invention relates to the technical field of water area ecological monitoring, in particular to a method for quantitatively calculating phytoplankton community stability, which comprises the following steps of: determining an optimal sampling area: starting a region selection module to obtain a plurality of depth data of a water area to be sampled, and analyzing and processing the depth data to select the optimal sampling area; a precise sampling step: putting a data acquisition module in the optimal sampling area, acquiring environmental information in water, performing data evaluation of the environmental information on the optimal sampling area, and presetting illumination and temperature parameters most conforming to the sampling area for the sampling assembly based on a data evaluation result; according to the invention, the environmental factors at the sampling point of the water area to be detected are detected and counted, and the specific sampling assembly is placed at the sampling point for sampling, so that the environment in the sampling process is stabilized, and the influence on the evaluation accuracy of the stability of phytoplankton communities caused by the influence on data statistics of the phytoplankton communities due to the change of the environmental factors is avoided; and the occurrence of data distortion is reduced to a great extent.

The application relates to the field of ecological environment monitoring production, in particular to a high-efficiency separation type ecological plankton and zooplankton collecting net which comprises a frame, a first layer net for intercepting large sundries is arranged at the middle portion of the frame, and a lifting hook is arranged at the top of the first layer net. The application is provided with a rotary layered component, that is, a second layer net at the bottom is used for intercepting phytoplankton, and a third layer net on the same axis in the inner side of the second layer net is used for intercepting zooplankton. A rotating force is generated under the action of water flow through a propeller, so that the Jiaolong push plate in the third layer net is in a conical structure and rotates on the inner side of the third layer net, one end of the corrugated plate on the outer side of the Jiaolong push plate is inclined along the inner side of the third layer net, and when rotating, the Jiaolong push plate can push the plankton to move and disperse to avoid local accumulation and blockage, can intercept the zooplankton accurately by means of the component force, and the staggered stirring effect caused by the fact that the wave trough positions of the three corrugated plates are not on the same horizontal plane makes the filtration more comprehensive and uniform.

The invention relates to the technical field of sea area phytoplankton monitoring, and particularly discloses a sea area phytoplankton monitoring system and method based on artificial intelligence, and the system comprises a data collection module which is used for obtaining multi-source three-dimensional monitoring data of a target sea area, and the multi-source three-dimensional monitoring data comprises a surface layer optical remote sensing image; the vertical profile data of the water body comprises optical parameters and seawater physical and chemical parameters which are acquired by a profile buoy, a towed sensor, an underwater unmanned vehicle or a shipborne profile measurement system, have at least two different depths and are related to phytoplankton; and the data preprocessing and fusion module is in communication connection with the data acquisition module. According to the sea area phytoplankton monitoring system and method based on artificial intelligence, comprehensive technology upgrading of phytoplankton from a two-dimensional plane to a three-dimensional space, from representation to mechanism and from post-event statistics to prospective early warning is achieved, and the dimension limitation of traditional monitoring is broken through.

The present application relates to fluorescence detection methods, in particular to a turbidity compensation method in fluorescence detection and a concentration prediction method of water phytoplankton, to solve the problems of deviation of the characterization of turbidity interference, insufficient reliability and accuracy of the existing turbidity compensation method, or the problem of greater influence of the compensation accuracy of the neural network on the training set, and the problem of serious deviation of the measured value from the true value caused by the turbidity interference in the fluorescence detection of water phytoplankton. The turbidity compensation method in fluorescence detection comprises the following steps: obtaining standardized scattering spectrum S1 and standardized scattering spectrum S2, calculating weakening coefficient K i or weakening coefficient M i , eliminating the scattering enhancement of the fluorescence spectrum of the sample to be measured, calculating the fluorescence intensity of the sample to be measured after turbidity compensation, and completing the turbidity compensation. The concentration prediction method of water phytoplankton uses the above method to obtain the fluorescence intensity of the sample to be measured after turbidity compensation, and then substitutes it into the concentration prediction model to obtain more accurate concentration prediction value.

The invention discloses a phytoplankton in-situ flow imaging device and an imaging method, and belongs to the technical field of marine ecology and water quality monitoring, and the phytoplankton in-situ flow imaging device comprises an optical imaging module, a fluid control module, a data processing module and a communication module which are fixedly arranged in a sealed cavity of an outer shell. According to the in-situ detection device, optical triggering is not needed, the structure is simple, full-fluid microscopic images can be continuously collected, automatic monitoring and high-throughput quantitative analysis of phytoplankton and suspended particles are achieved, the remote interaction operation capacity is achieved, and reliable long-term data support is provided for marine ecological monitoring.

1. Name of the designed product: control boat (blue algae). 2. Use of the designed product: for controlling phytoplankton in water. 3. Design points of the designed product: in the combination of shape and pattern. 4. Picture or photo best showing the design points: perspective view.

This invention provides a method for identifying phytoplankton tomographic sequences and a model building method thereof, belonging to the field of image enhancement and recognition technology. First, microscopic tomographic sequence data of phytoplankton is acquired, and field of view extraction and serialization reconstruction are performed to construct a stereo dataset. Next, a stereo recognition model incorporating physical perception and sequence aggregation mechanisms is constructed. The model uses a parameter-shared Siamese network to extract semantic features of single frames and introduces a physical sharpness prior module to calculate the spatial frequency domain quality score of the slices. Then, a depth-sensing sequence aggregation module is designed, using the sharpness score as a gating signal and combining it with spatial context information between slices to adaptively aggregate key features with high signal-to-noise ratio. Finally, the model is trained and optimized based on image-level weakly supervised labels to obtain the optimal model. This invention overcomes the problems of information truncation and defocus noise interference caused by the extremely shallow depth of field in high-magnification microscopic imaging, enabling full-depth stereo perception without the need for frame-by-frame detailed annotation.

The application discloses an intelligent phytoplankton collecting net system, which comprises a control unit, and is connected with an execution module, a parameter setting module, a real-time environment detection module and an optimization module on the control unit; the execution module is used for collecting phytoplankton; the parameter setting module is used for setting and changing the sampling depth, sampling time, sampling frequency and sampling amount in the early and late stages; the real-time environment detection module is used for monitoring the water environment parameters in real time after starting the system and transmitting the data to the control unit; and the optimization module is integrated in the control unit, is used for processing and analyzing the real-time environment data through its own algorithm, and optimizes the collecting strategy according to the preset condition or real-time data; in the application, the automation, intelligence and sampling efficiency are significantly improved, the environment can be automatically monitored, the phytoplankton samples can be automatically collected and stored, the real-time monitoring of the environment parameters, the intelligent optimization of the sampling strategy and the integration of the automatic and accurate sampling are realized, and the efficiency, accuracy and research value of the phytoplankton sample collection are significantly improved.