4065 results about "Aquaculture" patented technology

The invention, which belongs to the technical field of intelligent breeding equipment, discloses an underwater bionic robotic fish school cooperative breeding environment dynamic monitoring and regulation system comprising a bionic robotic fish body core module, a group cooperative control core module and an intelligent regulation core module. The bionic robotic fish module simulates a real fish swimming mode and carries various water quality sensors to autonomously cruise, so that interference to cultured fishes is reduced; the group cooperation module utilizes a cluster intelligent algorithm and an underwater acoustic communication technology to realize coordinated movement of multiple robotic fishes and full coverage of a monitoring area; the intelligent adjusting module is based on an abnormal detection algorithm, and integrates a miniature oxygenation device, a pH adjusting device and the like to achieve precise regulation and control of the local environment. By the adoption of the system, dynamic sensing and active regulation and control of the culture environment are achieved, a bionic monitoring regulation and control solution is provided for modern aquaculture through intelligent cooperation of the robot fish school and the management system, and the system has the important value of improving the culture efficiency and improving the growth environment.

The invention relates to the technical field of automatic control, in particular to an intelligent aquaculture automatic control system which comprises a feeding feedback control module, a feeding rhythm allocation module, a water body disturbance partition module, a control unit recognition module and a control path construction module. According to the method, the bait residue density is quantified through image recognition, a feeding state dynamic judgment mechanism is constructed, the accuracy and timeliness of feeding response are improved, the feeding speed is calculated through linkage of time difference and density change, a rhythm allocation strategy based on behavior feedback is formulated, the matching degree of the feeding rhythm to the actual feeding ability is enhanced, and the feeding speed is increased. A main flow path continuous block is constructed by combining flow velocity and flow direction, disturbance levels are marked in a grading manner, a key equipment action area is judged according to cross of fish school active density and dissolved oxygen trend, and an equipment linkage path is constructed by connectivity of a physical channel and an inhabitation area. And an intelligent control scheme of cooperative linkage of ingestion behavior driving, disturbance partition recognition and space layout optimization is realized.

The invention provides a river crab feed feeding mixed monitoring method, system and device and a medium, and belongs to the field of aquaculture intelligent monitoring. Data is collected and normalized, and a chain type data collection system is constructed; the edge computing and block chain technology is adopted to realize data distributed storage and transmission; a fuzzy neural network hybrid model is constructed, fuzzification processing, feature mining and defuzzification output are integrated, and a feeding amount prediction value is generated; associating the feed proportioning library with the knowledge graph, and iteratively training the model and generating a multi-target feeding decision parameter; feeding equipment is controlled to execute actions according to the decision parameters, and the real-time monitoring model outputs and triggers an early warning signal; and updating the knowledge graph and the feed matching library based on the feedback data to form closed-loop self-adaptive regulation and control. According to the method, various factors can be comprehensively considered, scientific and intelligent feed feeding decision is realized, feed waste and insufficient feeding are effectively avoided, and the growth quality of the river crabs is improved.

The invention provides an ecological circulation barrel-in-barrel culture data acquisition method and system, and relates to the technical field of intelligent control, and the method comprises the steps: carrying out the feature extraction of a historical data flow through a multivariable coupling analysis model, carrying out the mode matching through a preset environment threshold interval and a culture environment state matrix, and obtaining a culture environment state matrix; generating a water quality health degree evaluation index and an ecological imbalance early warning signal; and analyzing the water quality health degree evaluation index and the ecological imbalance early warning signal based on a fuzzy control algorithm, dynamically calculating a final feeding amount curve and a water change intensity function, and generating a regulation and control instruction set containing the feeding frequency, the bait particle size and the water pump rotating speed. According to the invention, real-time evaluation and accurate intervention of the water quality health state can be realized.

The invention discloses an integrated water quality monitoring and processing system for aquaculture, and the system comprises a data collection module which is used for obtaining dissolved oxygen, ammonia nitrogen, pH value, temperature and flow data from a plurality of spatial distributed sensing nodes; the data preprocessing module is used for completing noise removal, correction and time sequence synchronization; the water quality state estimation module is used for outputting real-time multi-point water quality states based on a distributed unscented Kalman filtering algorithm; the space-time fluid modeling module is used for constructing a Lagrange model to extract a flow velocity field and a diffusion coefficient; the scheduling optimization module is used for generating an aeration and dosing scheme by adopting an improved multi-target Pareto optimization algorithm based on a space-time sensitive boundary; the execution module is used for controlling an air blower, an aeration pipe and a dosing pump to complete oxygenation and dosing operations; and the self-adaptive updating module is used for collecting feedback data to adjust filtering gain and optimizing parameters so as to realize closed-loop control of the system.

The invention relates to the technical field of environment assessment, in particular to a coastal zone culture area multi-dimensional environment assessment method and a cloud platform. The method comprises the following steps: continuously recording dissolved oxygen concentration, pH value, centigrade temperature, salinity unit, turbidity scattering unit, chlorophyll fluorescence intensity, ammonia nitrogen milligram per liter and nitrite milligram per liter, synchronously calling multi-source remote sensing images covering a culture area and an adjacent water area, extracting remote sensing reflectivity data through image correction and atmospheric correction, and calculating to obtain water color parameters. According to the method, the water quality sensor array is deployed at the key point of the culture area, continuous multi-parameter environmental data acquisition is carried out, multi-source remote sensing images are synchronously integrated, water color information is extracted in real time, and the timeliness and data accuracy of culture water area environmental monitoring are improved; trend decomposition and dynamic baseline construction are carried out based on the data sequence, so that the environmental fluctuation evaluation of the breeding area is more objective and accurate.

The invention belongs to the field of aquaculture, and particularly relates to an underwater fish multi-target identification, tracking and motion analysis method, the method is based on a multi-target attitude tracking framework based on direction perception, and the framework comprises an improved YOLOv11 model (YOT model) and a directional bounding box attitude tracking module (OPBT module). The YOT model integrates directional bounding box detection and attitude estimation, adopts a task-aligned dynamic detection head structure, and combines a multi-task loss function to realize efficient direction perception detection and key point positioning. The OPBT module is based on an unscented Kalman filter, integrates rotation IoU, angle similarity and body length similarity, and improves identity continuity and occlusion recovery capability in multi-target tracking. The framework is suitable for complex scenes such as high-density fish schools, the real-time processing performance can be kept, meanwhile, the detection and tracking precision can be remarkably improved, and stable and reliable technical support is provided for individual behavior analysis.

The invention discloses an aquaculture comprehensive guarantee method and system based on multi-modal data acquisition, and relates to the technical field of intelligent aquaculture, and the method comprises the steps: collecting aquaculture multi-modal data and an aquaculture image of an aquaculture region, carrying out the aquaculture feature capture of the aquaculture image, and outputting a visual feature group; inputting the visual feature group into a MobileNet lightweight model, and outputting a health state label and a confidence score; based on the health state label and the confidence score, outputting disease type data through a residual network structure optimized by transfer learning; constructing a graph neural network according to the disease type data, and generating a dynamic regulation and control scheme; and the control center executes the dynamic regulation and control scheme, carries out regulation and control effect detection and target comparison on the aquaculture area of the dynamic regulation and control scheme, judges whether the regulation and control effect is effective or not, and generates a feedback regulation instruction. According to the invention, through multi-modal data fusion and intelligent decision closed loop, dynamic and accurate guarantee of aquatic product health management is realized.

The invention discloses a fishery pond water temperature control optimization method based on a swarm intelligence algorithm, and belongs to the technical field of control optimization, and the method comprises the following steps: S1, constructing a fishery pond water temperature PID control system introducing an improved single-corner whale optimization algorithm module; s2, introducing an improved single-corner whale optimization algorithm, and constructing an improved single-corner whale optimization algorithm module; s3, setting and optimizing the pond water temperature PID control parameters by using an improved single-corner whale optimization algorithm to obtain optimal control parameters; and S4, setting an optimal control parameter obtained through optimization by using the improved single-corner whale optimization algorithm as a parameter of a pool water temperature PID controller, and optimizing a pool water temperature regulation control effect. According to the method, a swarm intelligent optimization algorithm, namely an improved unicorn whale optimization algorithm, is introduced, high-performance control over the pond water temperature is achieved, and reliable control technical support is provided for efficient, stable and safe operation of aquaculture.

The invention discloses an industrial robot image processing method based on image fusion, and relates to the technical field of intelligent aquaculture, and the method comprises the steps: collecting an original image in real time through deploying an image collection device integrating visible light, polarization and multispectral imaging, and extracting suspended matter density, water body light transmittance and illumination intensity change information; generating a first image set; suppressing suspension interference through image filtering and enhancement processing to obtain a first corrected image; extracting an aquatic product individual region, performing multi-source image fusion, identifying color deviation, texture interruption and reflection feature anomaly regions, and constructing a lesion candidate set; gray scale reconstruction, edge gradient and brightness normalization correction of a multispectral channel are executed based on illumination and reflection changes, and a high-quality fusion image is generated; and calculating a health anomaly probability coefficient of the target individual by using the depth recognition model, comparing the health anomaly probability coefficient with a threshold value, and recording a recognition result and collecting information if the threshold value is exceeded. The method can significantly improve the accuracy of aquatic individual lesion recognition.

The invention relates to a fence, in particular to an aquaculture fence. In order to solve the technical problems, the aquaculture fence which can save time and is beneficial for screening is provided. The aquaculture fence comprises an installation plate, supporting columns, a guide plate, first connecting plates, a first baffle, a second baffle and the like, wherein the supporting columns are installed on the left side and the right side of the top of the installation plate respectively, the tops of the two supporting columns are connected with the guide plate, a first strip-shaped opening with a guiding effect is formed in the top of the guide plate, a second strip-shaped opening is formed in the rear side of the guide plate and communicated with the first strip-shaped opening, and thetwo first connecting plates are connected between the two supporting columns. Through the effect of the second baffle and the second baffle, fish fry small in size can be screened and does not need tobe fished up by people or screened by people with naked eyes, and therefore screening can be convenient and time can be saved.

The invention relates to the technical field of intelligent aquaculture and automatic processing, in particular to an appearance characteristic-based hippocampus intelligent grading and pond-dividing culture method and system, and the method comprises the following steps: S1, collecting sparse visual data and multi-source physiological data of hippocampus; s2, generating a three-dimensional digital twinborn model based on the sparse visual data; calculating a growth state grading index based on the three-dimensional digital twinborn model; s3, calculating a physiological stress index based on the multi-source physiological data; s4, comparing the physiological stress index calculated in real time with a preset safety stress threshold value and a critical stress threshold value, and generating a hierarchical adaptive correction strategy; s5, according to a grading self-adaptive correction strategy, controlling a flexible mechanical arm to execute fishing and pond separation operation; according to the method, the appearance and physiological data of the hippocampus are synchronously collected in a non-contact mode, the technical problems that the real condition of the hippocampus cannot be evaluated and damage is possibly caused due to target stress response caused by traditional physical intervention are solved, and the authenticity and effectiveness of original data are guaranteed.

The invention belongs to the technical field of aquaculture, and provides a feed feeding efficiency assessment method and system, and the method specifically comprises the steps: firstly, arranging a monitoring node camera in a farm, reading real-time monitoring data at a monitoring node to calculate a feeding fluctuation value, then calculating a feeding abnormal factor according to the feeding fluctuation value, and recognizing a feeding risk state; and finally, evaluating the feed feeding efficiency through the feeding risk state. The feeding abnormity is that the feeding fluctuation value of each sampling point of each monitoring node in a monitoring period is calculated, the fish feeding enthusiasm microscopic decline performance observed by each monitoring node in a long-period feeding strategy is captured, and the identified feeding risk state can more sensitively prevent the excessive feeding amount of feed; the risks of feed waste and water quality deterioration are avoided, and the feed utilization efficiency and the breeding quality under the long-period feeding strategy are improved.

The invention discloses an aquaculture disease prediction method based on multi-modal data fusion, and relates to the technical field of aquaculture, and the method mainly comprises the steps: collecting aquaculture data containing structured data and unstructured text data; inputting the structured data into a TabTransform model, carrying out column embedding and modeling of a context relationship between features through a multi-layer Transform encoder, and outputting a structured feature vector; inputting the unstructured text data into a pre-trained BERT encoder, and extracting an output vector marked by the CLS as a text semantic feature; and splicing the structured feature vector and the text semantic feature into a fusion feature, inputting the fusion feature into a full connection layer, and predicting the incidence probability of each target disease through a Sigmoid function. The prediction accuracy is improved, and the problems of single prediction dimension and weak generalization ability in the prior art are effectively solved.

The invention discloses a broad-spectrum lytic bacteriophage for preventing and controlling various vibrio infections in an aquaculture environment. The invention relates to V.alginolyticus phage vBValM-R37J, which is preserved in Guangdong Microbial Culture Collection Center (GDMCC) on August 6, 2025, the address is No.100 Courtyard, Xianlie Middle Road, Xianlie District, Guangzhou City, Guangdong Province, the postcode is 510070, and the preservation number is GDMCC NO.66813-B1. The invention further discloses a method for preparing the V.alginolyticus phage vBValM-R37J strain. The bacteriophage R37J is a candidate therapeutic bacteriophage with wide host spectrum, high splitting efficiency, gene safety and environmental stability, and has the potential of being popularized and applied in aquaculture as a novel biological tool for accurately preventing and controlling various vibrio infections. A new biological resource is provided for accurate prevention and control of aquatic pathogenic bacteria, and a theoretical basis and a technical support are provided for popularization and application of a phage therapy in an actual culture system.

The invention belongs to the technical field of aquaculture and food engineering, and relates to a fish anesthesia recovery activity prediction method based on acoustic signal time-frequency domain feature fusion. The method comprises the following steps of: acquiring acoustic respiratory vibration signals in real time in a fish anesthesia recovery process, performing 0.1-50Hz band-pass filtering, denoising and other pretreatment on the acoustic respiratory vibration signals, and extracting ZCR and Gammatone characteristic spectrums; meanwhile, fish swimming data are collected by adopting a YOLOv11 visual tracking algorithm, and activity grading standards are established by calculating activity indexes; zCR and Gammatone maps are used as double-branch input data of a deep learning model, corresponding activity grading data are used as labels, and a multi-category classification prediction model is constructed. According to the method, the anesthesia recovery state of the fish can be accurately predicted, and excessive stress and death loss in the transportation process are avoided; a non-invasive and intelligent detection means is provided for activity monitoring in the aquatic product transportation process, and the market application prospect is wide.

The invention relates to the technical field of water quality monitoring, in particular to an aquaculture water quality monitoring and self-adaptive regulation and control platform and method.The aquaculture water quality monitoring and self-adaptive regulation and control platform comprises a data processing module used for obtaining water quality parameter data of aquaculture at multiple monitoring points and multiple time points and conducting preprocessing and time sequence serialization fitting on the water quality parameter data to obtain a data processing module; obtaining a water quality parameter time sequence; the feature extraction module is used for carrying out space-time semantic recognition and feature extraction on the water quality parameter time sequence and constructing a feature sequence of each water quality parameter; and the risk early warning module is used for carrying out inter-parameter space-time correlation calculation and dynamic risk threshold value adaptation according to the feature sequence to obtain water quality risk early warning features. By combining the water quality parameters and the culture organism state data, the system can accurately evaluate the risk level of the water quality, timely warn potential risk factors, help a culturist to take effective precautionary measures, and avoid the death or health problem of the culture organism.

The invention relates to the technical field of aquaculture equipment, and discloses a rainbow trout fry rearing special constant-temperature hatching device which comprises a heat preservation box, a constant-temperature mechanism, a tray mechanism, a top cover assembly and a control panel. The constant-temperature mechanism comprises an S-shaped heat conduction water pipe, a bidirectional water pump, an upper-end heating module and a lower-end refrigerating module, the heat conduction water pipe preheats or precools buffer water flow, the bidirectional water pump rotates forwards and backwards to control the water flow to flow up and down, and natural convection of water in the box is promoted by combining'heat flow rising and cold flow falling ', so that water temperature fluctuation is greatly reduced, and compared with an existing device, the temperature difference is remarkably reduced; the rainbow trout embryo development stable temperature environment is ensured. The folding push handle is turned over to the upper end, the linkage splash-proof grid automatically blocks the top cover vent hole, and water is prevented from being splashed when the device moves; a temperature and dissolved oxygen amount sensor is arranged on the side wall of the heat preservation box, a bubble generator at the bottom accurately adjusts dissolved oxygen, air holes are opened for ventilation when the splash-proof grids are fixed, and it is ensured that the internal environment is moderate.

The invention relates to a microbial agent prepared based on a new strain of bacillus velezensis, which has the function of broad-spectrum antagonism of common pathogenic bacteria of aquatic products and can effectively prevent and / or treat bacterial diseases and / or fungal diseases of aquatic organisms including crustaceans and fishes. Meanwhile, the content of nitrite and ammonia nitrogen in aquaculture water can be effectively reduced, and the usage amount and residual quantity of antibiotics and chemical drugs in aquaculture are reduced.

According to the plasma aquaculture water purification method and system, a cold plasma directional screening technology is used as a core to construct a cold plasma water treatment module, a nanosecond pulse plasma generator is used for exciting a gas medium to form cold plasma, active particles are screened in situ through a directional screening assembly, and the cold plasma water treatment module is used for purifying aquaculture water. The method comprises the following steps: introducing ammonia nitrogen into a water body, guiding < 1 > O2 to be quickly injected into the water body, instantaneously completing a primary purification reaction in a gas-liquid intersection chamber, further, in order to fully utilize residual active particles, directionally converting a reaction precursor O3 of < 1 > O2 into < 1 > O2 through a catalytic dissociation module, and completing a secondary purification reaction between the < 1 > O2 and the ammonia nitrogen. Ammonia nitrogen is directionally converted into nitrogen by utilizing a 1O2-dominated non-free radical reaction path, the content of ammonia nitrogen and total inorganic nitrogen in a water body is reduced, and after purification is completed, oxidizing components in the water body and tail gas are respectively removed by adopting a by-product removal assembly, so that the use safety is guaranteed.

The invention discloses a nitrifying bacterium agent suitable for aquarium, fishpond and other aquatic industries, the strain of the nitrifying bacterium agent is Glutamicacter nicotianae TJ-X, the nitrifying bacterium agent is preserved in Guangdong Microbial Culture Collection Center on February 12, 2025, and the preservation number is GDMCC NO.65877. The invention further discloses a preparation method of the nitrifying bacterium agent. The nitrifying bacteria TJ-X strain suitable for the aquarium industry can perform heterotrophic nitrification and aerobic denitrification under the condition that the salt content is 5wt%, under the condition of laboratory pure culture, within 8 hours, the removal rate of ammonia nitrogen, nitrite nitrogen and nitrate nitrogen is 99% or above, the COD degradation rate is 81%, the nitrifying bacteria TJ-X strain is suitable for the environment where organic matter, ammonia nitrogen, nitrite and nitrate coexist, and the nitrifying bacteria TJ-X strain can be applied to the aquarium industry. The microbial agent has the functions of degrading organic matters such as excrement of ornamental fish and fish food, converting organic nitrogen into inorganic nitrogen, and simultaneously degrading inorganic nitrogen such as ammonia nitrogen, nitrite nitrogen and nitrate nitrogen into nitrogen. And the strain is high in biological safety, high in environmental adaptability and high in growth density, can be applied to water industries with high organic matter content and inorganic nitrogen, such as the aquarium industry and aquaculture, and has a wide application prospect.

The invention discloses a rice field crayfish body surface cleanliness improving method based on accurate aquatic plant management and protection and ecological induction, and relates to the technical field of crossing of aquaculture and ecological agriculture. The lifting method comprises the steps that submerged plants are planted in the rice field in February every year, and the submerged plants are trimmed regularly in the cultivation process so that the top ends of the submerged plants can be kept under the water surface; shrimp seeds are put into the rice field, and feed is fed regularly; in the subsequent breeding process, during regular feeding of feed, feeding of crushed pomacea canaliculata is carried out; and after the young crayfishes grow up and shell, catching the crayfishes to obtain the crayfishes with high body surface cleanliness. According to the method, the growth state of the aquatic plants is precisely controlled to construct a natural clean field domain, the functional bait is fed to increase nutrition, meanwhile, friction cleaning is carried out through the feeding behavior, precise fishing is carried out based on the molting period, and therefore the body surface cleanliness of the crayfishes bred in the rice field is improved.

The invention provides an AI-based trachinotus ovatus juvenile fish culture water parasite prediction and prevention method and system, and the method comprises the steps: collecting multi-source data from a culture water body through a sensor array, including a nucleic acid signal, a fish school behavior track and an environment parameter sequence, and obtaining an original data set; unifying the data format and the acquisition frequency according to the original data set by adopting a time sequence alignment method, and obtaining an aligned feature flow; aiming at the aligned feature flow, applying a convolutional neural network to extract a space-time pattern of a nucleic acid signal and an abnormal index of a fish school behavior, and determining an extracted feature set; if the abnormal index in the extracted feature set exceeds a preset threshold value, a causal association between environmental parameters and parasitic risks is classified through a support vector machine, and a preliminary risk level is judged; simulating a water body change scene according to the comprehensive causal model to obtain a predicted trajectory of parasite propagation; and determining a quantitative score of the parasite risk and generating a prevention and control instruction sequence by comparing the predicted trajectory with the real-time monitoring data.

The invention discloses a lytic bacteriophage vBVpaSR40Z and application of the lytic bacteriophage vBVpaSR40Z to prevention and control of vibrio parahaemolyticus in an aquaculture environment. The preservation number of the vibrio parahaemolyticus phage vBVpaSR40Z is as follows: GDMCC No: 67440-B1, and the vibrio parahaemolyticus phage vBVpaSR40Z is The R40Z can be used for cracking multiple strains of vibrio parahaemolyticus and vibrio alginolyticus, has the capability of adapting to an aquaculture environment, and keeps relatively high activity within the range of 4-25 DEG C and pH of 4-10; no virulence gene or drug-resistant gene is detected through genome analysis, and phylogenetic and whole genome comparison shows that the similarity between R40Z and a related phage is lower than a species level threshold value, so that R40Z is a new phage species; the R40Z can obviously inhibit the growth of a host under various infection complex numbers. The R40Z has the advantages of strong splitting capacity, good environmental stability, high genome safety, unique evolutionary characteristics and the like, and is an aquatic vibriosis biological prevention and control bacteriophage with application potential.

The invention provides a ventilation system optimization method and system based on the air quality of an industrial aquaculture workshop, and relates to the technical field of environment regulation and ventilation system.The method includes the steps that aquaculture workshop gas is analyzed through an infrared spectrometer, the spectral intensity of the characteristic absorption wavelength of a target pollutant is obtained, and then the accurate concentration of the pollutant is analyzed according to the spectral intensity; and calculating a ventilation parameter reference value and controlling a fan to adjust the air supply amount. An air treatment device in the ventilation system can determine the optimal working time according to the air supply amount so as to decompose pollutants and continuously monitor the concentration of the pollutants at the inlet and the outlet of the device. Subsequently, the air quality deterioration index is predicted by analyzing the concentration change trend, and the current overall purification efficiency is calculated. When the purification efficiency deviates from the range or the deterioration index exceeds the threshold value, the running state of the device is dynamically adjusted and fed back to the system, self-adaptive optimization of the ventilation system of the industrial aquaculture workshop can be achieved, and it is guaranteed that the workshop air quality is stable and the purification efficiency reaches the standard.

The invention discloses an aquaculture oxygenation monitoring method and system based on artificial intelligence, and the method comprises the steps: collecting multi-modal environment data, inputting the multi-modal environment data into an ST-BiGRU space-time bidirectional gating circulation unit, processing historical time sequence data through a time channel, and carrying out the processing of the historical time sequence data through a time channel; introducing a dynamic weight attention mechanism to adaptively adjust contribution degrees of different environment factors to obtain a multi-dimensional feature vector; establishing a dissolved oxygen prediction model based on an LSTM (Long Short-Term Memory) network, optimizing hyper-parameters of the model by using an improved IPOS particle swarm optimization algorithm, inputting the multi-dimensional feature vector into the target dissolved oxygen prediction model for prediction, and outputting a water body dissolved oxygen concentration index in a future preset time period; and performing oxygenation resource management according to the water body dissolved oxygen concentration index in combination with a reinforcement learning algorithm and a preset dissolved oxygen safety threshold range. The power consumption and equipment loss are effectively reduced, the breeding cost is reduced, and the resource utilization efficiency of breeding is improved.

The invention discloses a fish ingestion behavior identification method and system, particularly relates to the technical field of aquaculture intelligent monitoring, and is used for solving the problems of fuzzy feature extraction and low behavior discrimination accuracy caused by underwater environment complexity and ingestion action instantaneity of an existing visual identification method. The method comprises the following steps: acquiring underwater continuous video frames, extracting fish body head motion continuity parameters, and screening candidate key frames; analyzing nonlinear dynamic characteristics of mouth deformation displacement to generate time sequence correlation parameters, and dynamically weighting and fusing the head and mouth motion coupling strength; finally, the ingestion behavior state is counted and judged based on the cumulative effect of the motion coupling strength and the distribution mode. According to the method, through multi-dimensional time sequence feature fusion and a dynamic weight distribution mechanism, accurate capture and reliable judgment of transient feeding actions of fishes in a complex underwater scene are realized, and an effective technical support is provided for optimizing a culture feeding strategy.

The invention discloses a lytic bacteriophage for preventing and controlling vibrio in an aquaculture environment. The bacteriophage vBValMR42H belongs to a muscle tail bacteriophage and is insensitive to chloroform, the capsid of the bacteriophage vBValMR42H is free of lipid substances, and the preservation number is GDMCC No: 67434-B1. The bacteriophage has the characteristics of high adsorption speed, short incubation period and high cracking amount, keeps high activity in a wide range of temperature (4-55 DEG C) and pH (2-11), and has strong environmental adaptability. Genome analysis shows that the bacteriophage does not contain virulence factors, antibiotic resistance genes and lyogen related genes, and is high in biological safety. Physical development analysis shows that the method can be divided into a new genus. The bacteriophage R42H has the advantages of high splitting efficiency, good environmental stability, strong specificity, gene safety and the like, and can be used as an ideal biological prevention and control agent for preventing and controlling vibrio alginolyticus diseases in aquaculture.

The invention discloses a shrimp pond water quality prediction method based on a deep echo state network, and relates to the technical field of shrimp pond water quality prediction, and the method comprises the following steps: deploying an underwater fluorescence sensor in a shrimp pond culture water body to detect a fluorescence response signal of algae, and obtaining algae concentration data in the water body in real time based on the fluorescence signal intensity; dynamic changes of algae in the prawn pond water are monitored in real time; and performing time sequence alignment on the collected algae concentration data, and constructing an algae concentration time sequence data map based on the aligned time sequence data. According to the method, fluorescence sensor data and a short-time feature extraction mechanism are fused, a deep echo state network is combined to model an algae burst trend, and early warning can be realized before red tide outbreak; and the abnormal area monitoring precision is improved by enhancing a sampling mechanism, the problem of slow recognition of emergencies by a traditional model is effectively solved, and the aquaculture water quality risk perception and intelligent management capability is remarkably improved.

The utility model provides a breeding and photovoltaic buoyant raft utilizing retired wind power blades, which comprises a buoyant raft assembly, a positioning rope, a breeding box, a lifting device and a photovoltaic power generation and storage device. The wind power blades are connected in the side face direction through the blade supports, the assembling positions of the blade supports can be conveniently determined on site, the assembling process is simplified, and the wind power blades can still be transferred before and after entering water through the mode that the wind power blades are connected pairwise; and the wind power blade forming the integral buoyancy structure is more convenient to assemble on site in water, so that the utilization efficiency and the refitting efficiency of the wind power blade are greatly improved, and the refitting treatment cost is reduced.