111 results about "Phytoplankton" patented technology

The invention relates to the technical field of marine ecological environment monitoring and data analysis, and particularly discloses a sea area phytoplankton biodiversity index prediction method and system based on multi-model integration and feature engineering. After preprocessing, constructing four groups of nonlinear interaction characteristics of a temperature-salt relationship, oxygen-salt balance, chlorophyll chemical oxygen demand coupling and a nitrogen-phosphorus ratio based on environmental factors, combining station characteristics with basic environment and interaction characteristics, carrying out variance threshold screening, inputting a characteristic set into a multi-model integration framework containing models such as linear regression and gradient lifting, and carrying out multi-model integration; training and tuning according to a time sequence segmentation strategy, selecting model output according to a decision coefficient, using a result if the decision coefficient of the support vector regression model is within a preset range, and otherwise, taking a gradient lifting and extreme gradient lifting tree model to predict a mean value. And the prediction accuracy and the model generalization, stability and reliability are improved.

The present invention provides a device for quantitatively collecting surface phytoplankton samples, comprising a sampling tube, wherein a bottom opening is provided at the bottom of the sampling tube, an annular baffle is provided on the inner side of the lower part of the sampling tube, an inlet valve is hinged on the baffle, a baffle is provided above the baffle, the inlet valve is connected to a float through a pull rope, the pull rope is passed through a hanging ring, the float is located above the baffle, a water outlet is provided on the lower side wall of the sampling tube, the water outlet is located above the baffle, a scale is provided on the side wall of the sampling tube, the starting end of the scale is flush with the center line of the water outlet, a side-permeable top cover is provided on the top of the sampling tube, a handle is provided above the side-permeable top cover, a float ring is detachably provided on the upper part of the outer wall of the sampling tube, and a counterweight is detachably provided on the lower part of the outer wall of the sampling tube; the sampling tube can be conveniently used for daily manual sample collection, and can also be applied to a buoy monitoring system, so that surface phytoplankton samples around the buoy body can be collected through auxiliary facilities, thereby improving the accuracy of the buoy monitoring system.

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 discloses a method for determining a chlorophyll concentration value of phytoplankton based on ocean heat waves. The method comprises the following steps: acquiring ocean green ecological remote sensing image data and ocean heat wave data of a target sea area; and inputting the ocean heat wave data and the ocean green ecological remote sensing image data of the target sea area into a chlorophyll concentration determination model, so that the chlorophyll concentration determination model determines the ocean heat wave grade of the target sea area according to the ocean heat wave data, inputting the ocean green ecological remote sensing image data into a chlorophyll concentration determination sub-model according to the ocean heat wave grade, enabling the chlorophyll concentration determination sub-model to extract corresponding multispectral remote sensing image features and ocean microwave remote sensing image features, and outputting a phytoplankton chlorophyll concentration value of the target sea area; and transmitting the phytoplankton chlorophyll concentration value of the target sea area to a marine ecological monitoring system to assist the marine ecological monitoring system in sea area monitoring. The method can improve the accuracy of determining the chlorophyll concentration value of the phytoplankton and the application reliability.

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 phytoplankton density identification method and system based on ocean water temperature. The method comprises the following steps: acquiring a water temperature data set of a preset three-dimensional space of each grid region in a target ocean region within a preset time range; performing feature extraction on each water temperature data set to obtain a time sequence dynamic feature, a vertical layering feature and a space correlation feature of the ocean water temperature of each grid region; inputting the time sequence dynamic features, the vertical layering features and the spatial correlation features into a preset recognition model, so that the recognition model performs feature fusion on the time sequence dynamic features, the vertical layering features and the spatial correlation features based on an attention mechanism and a full-connection network to obtain fusion feature vectors, and generating the phytoplankton density of each grid region according to each fusion feature vector, thereby improving the accuracy and efficiency of phytoplankton density identification.

The application discloses a kind of plankton detection method, system and electronic equipment, it is related to computer vision technical field.The present application can be based on the image data of different regions, different river reaches of the river to be detected by using river plankton detection model, accurately, quickly get the plankton detection result of each pixel.And, multiple domain self-adaptive feature extraction modules are arranged in the river plankton detection model of the application, the distinguishing ability of target and background difference in image data can be improved, multiple boundary alignment modules can enhance the target feature extraction capability, the accuracy of plankton detection can be significantly improved, and the economic and ecological cost of plankton management can be effectively reduced.

A deep water drawing step of drawing deep water that exists in a deep region of the sea to a surface region of the sea with an upwelling pipe (1); and a phytoplankton culturing step of culturing the phytoplankton in the upwelling pipe (1) are included to produce, as a basic producer of a food chain, a living marine resource, such as fishes and shellfishes, with phytoplankton produced in the phytoplankton culturing step.

The invention discloses an ecological restoration device for promoting assimilation and purification of plankton by direct-drive rotary oxygenation in the field of ecological restoration, which comprises an aeration platform, a purification unit, a floating bed for planting aquatic plants and a carrier filler for microbial adsorption, an energy storage unit, a water supply unit, a water supply unit and a water supply unit, comprising a vertical wind driven generator, a solar power generation panel and an energy storage battery, and the control unit comprises a controller and a dissolved oxygen monitoring probe used for monitoring dissolved oxygen in a water body; the energy storage battery supplies energy to the control unit and the air blower. The invention provides an ecological restoration device for promoting assimilation and purification of plankton through direct-drive rotary oxygenation, the device can be directly driven to rotate by using reaction torque of aeration, the device not only can reduce loss of energy conversion, but also can recover energy of aeration airflow, and a controller intelligently controls oxygenation and aeration and adjusts the growth microenvironment of aquatic organisms, so that the ecological restoration device is suitable for ecological restoration of aquatic organisms. The assimilation purification effect is achieved.

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 discloses a kind of phytoplankton photosynthetic activity turbidity correction device and method, belong to phytoplankton monitoring technical field, the device includes excitation emission optical structure, light source driving module, signal detection module and main control module;The application constructs water turbidity scattering and initial fluorescence relative increment relationship by measuring 750nm water turbidity scattering and combined light-induced fluorescence kinetics curve, by calculating the correlation coefficient of both, the influence of water turbidity scattering on phytoplankton photosynthetic activity detection is corrected into photosynthetic activity correction model.The device structure is simple, and the measurement period is short, and it is non-invasive, and the underwater in-situ detection of phytoplankton photosynthetic activity of turbid water can be carried out, which provides a new way for rapid and accurate measurement of phytoplankton photosynthetic activity.

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 present application relates to a kind of marine Lidar signal noise removal method, device, equipment and medium, method includes: the information sampling of the sea area to be measured generates airborne laser radar signal, through pre-processing eliminates background noise and corrects sea surface fluctuation error, based on fast fourier transform extraction underwater depth profile frequency domain feature, to the amplitude replacement and spectrum reconstruction of electric noise concentrated frequency band, generate noise reduction radar signal, the method provided in the present application overcomes the vertical resolution loss caused by traditional vertical sliding average algorithm and weak signal error filtering problem, by frequency domain filtering replacement technology retains the original data of non-noise frequency band, while removing electric signal clutter, maintain original vertical resolution, effectively capture the microscale marine dynamic information such as thermocline, suspended solids concentration mutation interface and thin layer phytoplankton aggregation, improve marine environment monitoring precision.

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.

The present application relates to the field of agricultural chemistry and environmental protection, in particular to a kind of with homogentisic acid solanonyl transferase (HST) as molecular target inhibitory compound and its application.A kind of with homogentisic acid solanonyl transferase as molecular target inhibitory compound, it is characterized in that: compound is the compound shown in the following structure, in the formula, R1, R2, R3 And R4 Respectively Br.The compound has significant inhibitory effect on phytoplankton growth at low concentration, and shows strong herbicidal effect on weeds such as eustreptosin and portulaca oleracea.The AlphaFold prediction analysis further confirms that these compounds inhibit the synthesis of plastoquinone by binding with HST, thereby effectively interfering with photosynthesis.The present application can be applied to algae and weed control in agriculture and aquaculture, and has wide application prospect.

To provide a treatment method that enables prevention of color tone change of chlorophyll in an industrially advantageous manner.SOLUTION: A treatment method, comprising a step of bringing a chlorophyll-containing material including a plant, phytoplankton, algae, or a processed product thereof into contact with proline and / or glutamine.SELECTED DRAWING: Figure 1

The application provides a phytoplankton density identification method and system based on ocean water temperature, the method comprising: obtaining water temperature data sets of a preset three-dimensional space of each grid region in a target ocean region within a preset time range; extracting features of each water temperature data set to obtain time sequence dynamic features, vertical stratification features, and spatial correlation features of the ocean water temperature of each grid region; inputting each time sequence dynamic feature, vertical stratification feature, and spatial correlation feature into a preset identification model to enable the identification model to perform feature fusion on each time sequence dynamic feature, vertical stratification feature, and spatial correlation feature based on an attention mechanism and a full connection network, obtain each fusion feature vector, and generate the phytoplankton density of each grid region according to each fusion feature vector, thereby improving the accuracy and efficiency of phytoplankton density identification.

The present invention discloses a comprehensive treatment method for eutrophic water bodies, comprising the following steps: S1, after salvaging phytoplankton in the eutrophic water body, injecting the water to be treated into a permeable hardened soil pit, collecting the remaining silt and distributing it to the permeable hardened soil pit to obtain a pond to be treated; S2, adding a degrading bacterial agent to the pond to be treated to obtain a target water body; S3, after the transparency of the target water body is restored, planting submerged plants in the target water body; S4, after the submerged plants grow stably, releasing fish and benthic aquatic animals into the target water body; S5, maintaining the number of submerged plants, fish and benthic aquatic animals in the target water body stable, and maintaining normal detection indicators in the target water body, thereby completing the treatment of the eutrophic water body. The method of the present invention can reduce the impact of excessive silt nutrients, limit the development of excessive eutrophication in the pond, and intercept suspended matter in the water, thereby shortening the treatment time.

An illumination device (10) illuminates, with light, a region to be illuminated, which is identified on the basis of the amount of phytoplankton in a water area in which a marine product (P) is cultured.

The application discloses a water body ecological restoration device, which comprises a main hull, an oxygenation aeration system, a bacterial agent releasing device, a phytoplankton system and a solar energy system. The device integrates the technologies of microporous aeration oxygenation, microbial agent releasing and aquatic plant purification, and achieves the purpose of water body ecological restoration, so that the water purification efficiency is improved. The device is powered by all-weather solar energy, and is green, environment-friendly and energy-saving. The device changes the previous artificial bacterial releasing mode, and can realize uniform and full-speed bacterial releasing through the slow bacterial agent releasing device, so that the effect is better. The device focuses on the overall visual effect, has ornamental value, and can be fully integrated into the ecological landscape of the use environment.

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.

The invention discloses intelligent plankton analysis equipment which is characterized in that automatic loading of plankton samples is automatically completed through an automatic sampling system, then image scanning is carried out on the plankton samples through an automatic scanning system, and finally intelligent identification analysis is carried out based on scanned images through an intelligent analysis system. The whole process is automatically carried out, the phytoplankton and the zooplankton can be analyzed at the same time only through one sample, the detection time is greatly shortened, the efficiency of plankton population analysis is improved, human intervention is not needed, the recognition and analysis process is not affected by subjective factors, and the method is suitable for popularization and application. And the consistency and the accuracy of analysis results are ensured.

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.