286 results about "Population" patented technology

The invention provides a digital twinborn monitoring, regulating and controlling method for a copepod bait biological domestication process. The method comprises the following steps: establishing a micro-ecology and population dynamics coupled twinborn model, and defining a monitoring parameter and control object unified term system; collecting multi-source sensing data at an edge end, and performing clock synchronization, signal denoising and state estimation to obtain a micro-ecology, group and water body state joint estimation result; executing parameter online identification based on state estimation, and constructing a safety constraint set of ammonia nitrogen, dissolved oxygen, death rate, environment change rate and the like; the breeding efficiency improvement and the system stability balance are realized through a multi-objective optimization function; and generating a micro-ecological pulse and environment gradual change cooperative control action set according to a solving result, and when a set condition is met, outputting a domestication prescription and terminating the process. Intelligent, low-stress and high-stability regulation and control of a copepod domestication process are realized through digital twin modeling, rolling predictive control and a self-evolution updating mechanism.

The invention discloses a remote monitoring system based on bird species identification and population number estimation, which comprises a front-end monitoring subsystem, a data transmission subsystem, a data analysis and processing subsystem and a user interaction subsystem, and is characterized in that the front-end monitoring subsystem is composed of a plurality of monitoring nodes; each monitoring node is provided with a high-definition camera, a sound sensor, a temperature and humidity sensor and an illumination sensor, the devices work cooperatively, and data of birds and the environment where the birds are located are collected in an omnibearing mode. According to the remote monitoring system based on bird type identification and population number estimation, manual intervention is greatly reduced through an automatic monitoring and analysis process, the monitoring efficiency is improved, the accuracy of bird type identification and population number estimation is remarkably improved based on an algorithm of deep learning and multi-modal data fusion, and the accuracy of bird type identification and population number estimation is improved. And real-time transmission and processing of data are realized through a remote monitoring system.

The invention discloses a macrobrachium rosenbergii cherax ratio prediction and breeding method based on phenotypic omics analysis, which comprises the following steps: selecting a plurality of macrobrachium rosenbergii for multi-generation breeding, recording pedigree data of each individual, and constructing a macrobrachium rosenbergii breeding database; the method comprises the following steps: extracting phenotypic characteristics of macrobrachium at different culture stages, analyzing a rule between a growth index and a chelate ratio, carrying out heritability evaluation, and constructing a macrobrachium phenotypic omics network; the growth path of macrobrachium rosenbergii is analyzed, abnormal events in the breeding period are recognized, and a macrobrachium rosenbergii growth situation network is generated; constructing a macrobrachium phenotype knowledge map, and constructing a macrobrachium cherax ratio prediction model; and performing data acquisition on a macrobrachium rosenbergii population to be bred to obtain early phenotypic data, performing breeding decision, and performing breeding path recommendation on bred individuals by using the macrobrachium rosenbergii phenotypic knowledge graph. Meanwhile, whether the breeding path is deviated or not in the breeding process is analyzed, and a correction scheme is formulated for pushing, so that the breeding period of the macrobrachium is shortened, and the breeding accuracy and efficiency are improved.

The invention belongs to the technical field of species identification, and particularly relates to an InDel molecular marker for identifying a Yunnan acer truncatum population and application, three InDel molecular markers MLP, LZ and WS for identifying the Yunnan acer truncatum population are provided for the first time, the molecular marker MLP is used for identifying a Yunnan acer truncatum chestnut slope population, the molecular marker LZ is used for identifying a Yunnan acer truncatum old Zika population, and the WS is used for identifying a Yunnan acer truncatum population. The molecular marker WS is used for identifying Wenshan population of acer truncatum in Yunnan; then, a primer group for amplifying molecular markers MLP, LZ and WS is designed, and a Yunnan acer truncatum population identification method is developed, so that plant materials from the Yunnan acer truncatum can be accurately and effectively distinguished from related species materials of the Yunnan acer truncatum, and geographical population types of to-be-detected Yunnan acer truncatum samples can be simply, conveniently and efficiently identified; and distinguishing the Chinese chestnut slope population, the old Zihai population and the Wenshan population of the Yunnan acer truncatum.

The invention discloses a multi-nutrition-level ecological breeding system suitable for freshwater fish breeding, the ecological breeding system comprises a breeding variety combination level and an ecological niche complementary variety combination level, the multi-nutrition-level ecological breeding system has the beneficial effects that efficient utilization of resources and self-regulation of an ecological environment are realized by constructing a multi-species coordinated three-dimensional population structure; through the arrangement of the breeding variety combination level and the ecological niche complementary variety combination level, breeding objects of different nutrition levels are mutually supplemented and mutualistic, so that the productivity of the breeding system is improved, and the anti-risk capability of the system is also enhanced; the system integrates a plurality of functional modules, through application of technologies such as digital monitoring and remote control modules, real-time monitoring, abnormity early warning and remote control of the breeding environment are achieved, the water quality dynamic regulation and control module and the feeding planning module can precisely regulate and control water quality parameters and feeding plans according to growth requirements and environment changes of bred organisms, and the breeding efficiency is improved. And feed waste and water quality pollution are effectively reduced.

The invention provides a three-dimensional multi-dimensional oceanic nekton monitoring method based on artificial intelligence, and relates to the technical field of oceanic nekton monitoring, and the method comprises the steps: deploying a temperature-salinity-depth section plotter and an acoustic Doppler flow velocity section plotter, collecting data, configuring an environment parameter data set, obtaining a three-dimensional environment parameter data set, and obtaining a three-dimensional environment parameter data set; and a multi-dimensional environment parameter database is generated. Various ocean fishery resource investigation means are fused, an advanced artificial intelligence method is applied, three-dimensional multi-dimensional dynamic monitoring of the ocean swimming animals is achieved, on one hand, the number composition and space-time distribution of the ocean swimming animals, especially the vertical distribution characteristics can be monitored, the population dynamics of the ocean swimming animals and the relation between the population dynamics and environmental factors can be revealed, and on the other hand, the population dynamics of the ocean swimming animals can be monitored. By monitoring the swimming animals, basic data can be provided for population resource evaluation, and the method serves formulation of fishing quota of ocean economic swimming animals, delimitation of ocean protection areas and the like.

The invention relates to a lamplight purse seine fishing strategy optimization method and device based on multi-source data analysis, and belongs to the technical field of lamplight purse seine. Further acquiring multi-source data information of each sub-region in the target region, and constructing a biological population migration position point in combination with the multi-source data information and a biological population inhabitation prediction model, thereby constructing a migration route according to the biological population migration position point, setting different light fishing strategies, simulating the fishing effect of each light fishing strategy, and obtaining the target area. And finally, formulating a final light fishing strategy based on the fishing effect of each light fishing strategy and the migration route. According to the method, the migration position point of the target fishing organism population is optimized according to the survival habit data of the target organism population, the lamplight fishing strategy can be further optimized, and the fishing efficiency of the lamplight purse seine is improved.

The invention discloses an ecological regulation and control model for oncomelania indoor culture, and relates to the technical field of oncomelania culture regulation and control. Comprising the following steps: establishing a matching relationship between the number of indoor breeding units and the total oncomelania breeding amount for realizing standardized control of the initial oncomelania number of each breeding unit, ensuring the initial ecological balance of an experiment system, and determining the environment regulation priority of the indoor oncomelania breeding units based on the matching relationship. According to the method, the environmental parameter weight is dynamically corrected based on the risk intensity of different propagation stages of the schistosome, and the bottleneck that a static prevention and control strategy is difficult to adapt to the life cycle change of parasites is broken through; the biological rhythm of the oncomelania snail population can be accurately responded by environment regulation and control, the sustainability of indoor culture of the oncomelania snails is guaranteed to a certain extent, and the risk of schistosomiasis transmission is reduced.

The invention relates to a quorum sensing intelligent regulation and control method for violaceum violaceum in an antibiotic gradient region, and aims to solve the problems of uncontrollable multi-partition microenvironment and low biological behavior consistency in an existing system, the quorum sensing intelligent regulation and control method for the violaceum violaceum in the antibiotic gradient region comprises the following steps: accurately positioning space partitions, and collecting liquid phase pH, oxygen concentration and nutrient components in each region in real time by an integrated sensor; high-throughput detection and multi-modal data fusion are combined, and an AI model is input to establish association mapping of a liquid / gas phase environment and a biological phenotype. The system automatically generates and optimizes a partition gas component adjustment instruction, realizes spatial synchronous gas phase regulation and control by utilizing a programmable micro-airflow device, and realizes multi-region environment dynamic balance regulation and control in a culture chamber.

The invention relates to the technical field of waterfowl habitat recovery, in particular to a geranium wilfordii pause habitat recovery method. The method comprises the steps of selection of a suitable pause habitat, terrain transformation of the pause habitat, vegetation adjustment of the pause habitat, water body control of the pause habitat and specific food source supplementation: small fishes are regularly put and matched with benthic organisms such as shrimps and snails, so that smooth feeding of the geranium wilfordii is effectively ensured, the method is suitable for pause of the geranium wilfordii, and the health of geranium wilfordii populations is favorably improved; and a reference thought and practical reference significance are provided for geranium wilfordii population recovery.

The invention discloses an environment RNA (Ribonucleic Acid)-based double-saw eye spot fish detection method and a primer combination thereof, and solves the technical problems of lack of molecular markers, insufficient detection specificity and difficulty in reflecting physiological status in application of an existing environment RNA detection technology to benthic fishes. The primer pair aiming at the Ptger4b gene is designed on the basis of an environment RNA (eRNA) technology, and rapid and sensitive detection of the gemphus ocellatus in an independent feeding system is realized in combination with a fluorescent quantitative PCR (qPCR) technology. The method is easy and convenient to operate, high in sensitivity, small in interference to the ecological environment and suitable for detection and quantitative verification of target species in an independent feeding system, and has the potential of being expanded to natural sea areas in the future and used for fish population monitoring, fishery resource evaluation and species protection.

The invention discloses an energy consumption behavior simulation method based on a generative model, and the method comprises the following steps: S1, carrying out data interpolation reconstruction through time-space energy consumption data collected by equipment, and converting the data into a high-dimensional time-space data matrix; s2, decomposing the data matrix into a plurality of scale sub-matrixes, and using dynamic noise to drive a forward diffusion process to obtain spatio-temporal scale coded data; s3, executing a reverse diffusion process by using cross-scale data overlapping fusion and a dynamic noise weight decline mechanism, and reconstructing space-time energy consumption initial data; s4, according to the reconstruction data, constructing a feature space gravitational field and determining the spatial position of the quantum chaos African vulture group; and S5, dynamically adjusting the group position to enable the group position to carry out adaptive optimization along with the gravitational field gradient, and obtaining a dynamic optimization sequence. Through combination of quantum chaos optimization and a space-time diffusion model, the method can accurately simulate complex and dynamically changing energy consumption behaviors, and has a relatively strong optimization effect and a wide application prospect.

In traditional plant breeding approaches, chemical mutagenesis may be utilized to introduce nucleotide substitutions at random in the genome of a plant, i.e. without possibilities to control the sites of nucleotide changes. Because of genome complexities, the statistical probability is extremely little when it comes to finding a predetermined nucleotide substitution. The present invention, however, demonstrates how a novel, alternative use of digital polymerase chain reaction (dPCR), preferably droplet dPCR (ddPCR), is developed to exploit finding of specific nucleotide substitutions in mutated genes. The entire platform comprises a screening method with a library of mutagenized organisms, digital PCR-based systems and a set-up to propagate and analyze identified, mutated organisms.

The invention discloses an inertia damping VSG control method and device based on a chaos self-adaptive whale algorithm, and belongs to the technical field of generator control, the inertia damping VSG control method is realized through cooperation of an optimization controller executing the whale algorithm on the upper layer and a VSG controller on the bottom layer, and the inertia damping VSG control method comprises the steps of system initialization and parameter pre-configuration; generating an initial population matrix based on an initial whale algorithm of Tent chaotic mapping; dynamically adjusting the population of the initialized whale algorithm according to the convergence factor; calculating the fitness of population individuals according to a fitness function; iteratively updating the whale algorithm population to output global optimal parameters; and switching the global optimal parameter to a bottom layer VSG controller through a linear interpolation transition mechanism, and executing a VSG algorithm to output a switch driving signal. According to the method, the whale algorithm based on Tent chaos is adopted, real-time matching of parameter optimization and power grid working conditions is ensured, performance degradation caused by fixed parameters is avoided, and optimization precision and robustness are improved.

The invention discloses a multi-unmanned aerial vehicle flight path planning method based on a multi-mode cooperative dung beetle optimizer. The method comprises the steps that 1, a dung beetle optimization algorithm is initialized; 2, updating the position of the dung beetle; 3, mapping position elements exceeding the upper and lower bounds back to the effective search area to obtain a dung beetle position updating result and calculating a population fitness value; 4, updating the position of the dung beetle and calculating a population fitness value; 5, updating the position of the small dung beetle and calculating a population fitness value; step 6, updating the position of dung beetle theft and calculating a population fitness value; 7, comparing population fitness values, and recording a maximum value, a minimum value and corresponding position results; and step 8, iterating to obtain a final position result. Compared with DBO, QHDBO and route planning, the total cost of the method is respectively reduced by 80.78% and 63.8% in a simple scene, and is respectively reduced by 83.96% and 68.89% in a complex scene, and high efficiency and practicability of the method are proved.

The invention provides a non-lineage animal pairing evaluation method based on genome data, and belongs to the technical field of bioinformatics and protection genetics, the method comprises the following steps: firstly, obtaining whole genome sequencing data of all individuals in a population, and carrying out quality control to obtain a high-quality SNP site set; aiming at all possible male and female pairing combinations in the population, calculating an inter-parent genetic coefficient depKin, an inter-parent heterozygous difference ratio HDR and an inter-parent potential risk load index GRLI, and predicting a fixed proportion Proh of ROH of offspring; performing z-score standardization processing on the four genetic indexes: performing principal component analysis on standardized data, extracting the first two principal components PC1 and PC2, determining a weight according to a variance contribution rate, and calculating a pairing comprehensive score; and generating a pairing candidate recommendation list for each individual according to the comprehensive score, and screening a high-quality pairing scheme. The method disclosed by the invention can be completely independent of pedigree records, and genetic evaluation is directly carried out based on genome data.

The invention belongs to the technical field of ecological restoration, and provides a mountainous river-oriented fish diversified habitat natural shaping restoration method, which comprises the following steps of: determining fishes with a relative important index greater than 5% in a river as target fishes; the habitat factors of the river are screened, the habitat factors with colinearity are divided into a factor group, and only one habitat factor is reserved in each factor group to serve as a representative habitat factor; carrying out modeling on the resource distribution and representative habitat factors of the target fishes by adopting a generalized additive model; screening to obtain a generalized additive model with a minimum akaike information criterion, and determining an optimal habitat factor combination; and determining a restoration scheme according to the habitat factor combination, and adjusting the habitat of the target fish. According to the restoration method, the natural process is simulated to remodel the diversity of the mountain river habitat, the key problems of hydrological connectivity fracture, habitat simplification, engineering and ecological contradiction and the like are solved, and fish population restoration and ecological system self-maintenance are achieved.

The invention discloses an X-chromosome specific molecular marker of micropterus salmoides and application of the X-chromosome specific molecular marker. On the basis of a whole genome sequencing technology, the X chromosome specific molecular marker of micropterus salmoides is obtained. Aiming at the molecular marker, the invention also provides a detection primer pair and a detection method of the molecular marker, and by detecting the molecular marker, rapid and accurate screening of YY supermale fish individuals can be realized to obtain a YY supermale fish population. The obtained YY super-male fish group and a proper female fish group are jointly fed and bred, and then the micropterus salmoides all-male fingerling can be obtained. If the YY super-male fish group and the YY pseudo-female fish group are jointly bred and bred, largemouth bass offspring which is all YY super-male fish can be obtained. Compared with a traditional all-male breeding method of the largemouth black bass, the all-male breeding method of the largemouth black bass is beneficial to simplifying all-male breeding steps of the largemouth black bass, shortening breeding time, and beneficial to cultivation of all-male largemouth black bass fingerlings and popularization of single-male breeding of the largemouth black bass.

The invention discloses a minimum population wild plant identification and early warning method and system. The system comprises: an environmental DNA monitoring network unit, which analyzes environmental DNA through automatic sampling, evaluates the state of species and triggers a first early warning; the biological voiceprint monitoring and recognition unit is used for monitoring related acoustic activities and illegal intrusion behaviors of the target species by using intelligent recording nodes deployed in a gridding manner and a voiceprint recognition model, and triggering second early warning; and the multi-source information fusion and causal inference unit is used for integrating the environment DNA, the voiceprint and the meteorological data, analyzing the causal relationship among the ecological factors based on a causal inference model, generating protection measures and outputting comprehensive early warning. According to the invention, all-weather, interference-free and precise monitoring of the extremely small population wild plants is realized, the problems of low efficiency, many blind areas, large interference and the like of a traditional monitoring mode are solved, and effective technical support is provided for protection of rare plants.

This application discloses a comprehensive assessment method and system for multi-source data management and correction of watershed fish resources. The method includes: extracting multi-dimensional features from a first data matrix to obtain a first feature matrix; classifying species data based on anomaly scores, outputting verification results, and correcting the first feature matrix to obtain a second feature matrix; acquiring environmental DNA sequencing data and corresponding environmental data; obtaining a first eDNA dataset from the environmental DNA sequencing data through ecological screening; correcting the species in the first eDNA dataset to obtain a second eDNA dataset; fusing the second eDNA dataset with the second feature matrix; calculating biodiversity indices and analyzing community structure; analyzing long-term trends in population and community structure; and generating a comprehensive assessment report. This application achieves full-process automation and intelligence from data quality control and fusion to assessment, significantly improving the accuracy and efficiency of watershed fish resource assessment.

This invention discloses a deep learning-based method for predicting the phenological synchronization of specialized butterflies and their host plants, belonging to the interdisciplinary field of biodiversity conservation, ecological prediction, and deep learning technology. The method includes: collecting environmental climate variables, butterfly occurrence data, and phenological time-series data of their host plants; preprocessing the data to create training and validation sets; constructing a dual-label system with the day of year (DOY) of butterfly occurrence peaks (e.g., emergence peak, egg-laying peak) as the primary label and the normalized value of synchronization deviation as the secondary label; building a deep learning model with ecological weights, including an embedding layer, an LSTM layer, and a fusion layer; inputting a vector concatenated from daily or weekly climate time-series features and ecological dynamic features; and outputting the primary and secondary labels through a dual-output layer; designing a hybrid loss function that integrates the main regression loss, ecological synchronization constraint loss, and small-sample regularization loss; training the model using the Adam optimizer and implementing an early stopping mechanism; and validating and evaluating the model using regression accuracy and ecological synchronization accuracy indicators. The method includes modules for data acquisition, preprocessing, label construction, model training, prediction evaluation, and storage. This invention improves the accuracy of phenological synchronous prediction by embedding ecological dynamic feature weights and dual-label constraints, adapts to small sample scenarios, and provides technical support for the monitoring and protection management of rare butterfly species (such as the Golden Birdwing and the Chinese Tiger Swallowtail).

This invention discloses a method, system, equipment, and storage medium for determining ecological flow based on the suitable living area of ​​aquatic organisms. The method includes: dividing the river into high-water, normal, and low-water years; determining ecological protection targets for high-water, normal, and low-water years based on the suitable living conditions of dominant aquatic organism populations in the river channel; calculating the size of the suitable living area of ​​dominant aquatic organism populations in the river section under different water levels or wetted perimeters based on the ecological protection targets and hydraulic formulas; plotting the change curve of the suitable living area of ​​dominant aquatic organism populations in the river section under different water levels; and determining the river ecological flow in combination with the ecological protection targets for high-water, normal, and low-water years. This invention uses the suitable living area of ​​dominant aquatic organism populations in the river section as a label to deduce the river ecological flow target. Compared with previous methods, this method more fully considers the suitable living space of dominant aquatic organism populations in the river channel, and the determined ecological flow target is more suitable for the survival of aquatic organisms in the river channel.

The invention relates to an SNP (Single Nucleotide Polymorphism) marker for identifying silver pheasant species and application thereof, and relates to the technical field of biology. The SNP marker can effectively solve the current identification problem caused by the problem that the silver pheasants are hybridized, nestlings and female pheasants are difficult to distinguish, and provides solid technical support for silver pheasant protection, population monitoring and related scientific research.

The invention relates to the technical field of genetic breeding, and discloses a method for stabilizing the chemical property of a subtropical silkworm mid-line variety, which comprises the following steps: screening an egg circle with the optimal chemical property from a production group to establish an initial group; second-generation frame seed production is obtained through incubation and single moth breeding in combination with comprehensive screening of pupa unified life rate, cocoon quality and offspring hatching rate; single moth breeding screening is repeated twice, and third-generation and fourth-generation frame seed production is obtained; adopting a 4 / 4 moth area mixed breeding method to obtain five-generation frame seed production; then five-generation frame seed production is used as a new starting point, the breeding and screening processes are repeatedly executed, each time 4 / 4 moth area mixed breeding is executed as a breeding cycle, and at least two breeding cycles are continuously executed until a new silkworm strain with the sum of the seed generation rate and the re-egg-out rate stably lower than 0.5% is obtained. The method is used for cultivating new silkworm strains which are stable in chemical property and maintain excellent economic characters and robustness, and provides support for stable development of the silkworm industry.

The present invention discloses a mobile robot path planning method, system, robot and storage medium, and relates to the field of path planning technology. The mobile robot path planning method comprises: using a grid method to divide a map into 1×1 grids, using preset color blocks to represent traversable areas or obstacles; establishing a mathematical model; initializing whale optimization algorithm parameters; initializing the population using the Tent chaotic sequence strategy; performing a linear equidistant interpolation strategy on all whale individuals to add new position vectors; calculating fitness; selecting the whale individual with the smallest fitness as the current global optimal individual; updating the whale individual; when the current number of iterations t reaches the maximum number of iterations T, outputting the current global optimal individual; calculating and generating a cubic uniform B-spline curve to complete the path curve construction. The mobile robot path planning method proposed in the present invention has the characteristics of fast running speed, high solution quality, strong optimization ability, etc., and can better solve practical problems.

This invention discloses a method and system for determining the propagation conditions of wood-eating insect populations based on data modeling. Specifically, it relates to the field of computer data modeling and simulation optimization technology. The method addresses the problem that existing data modeling methods for establishing propagation conditions of wood-eating insect populations suffer from drift in model parameter mapping relationships and poor reproducibility of output propagation conditions in subsequent batches due to neglecting latent variables such as cross-interface microbial communities. The method establishes an initial mapping model by acquiring environmental parameters and population response data from multiple historical batches. For the data in the initial stage of the current batch, a residual sequence is calculated, and a non-random structure is determined based on the monotonic change trend of the residual fluctuation amplitude with the substrate fermentation process. When a non-random structure exists, the partial dependence relationship between the residual sequence and each environmental factor is extracted along the drift trajectory of the fermentation process as a characterization of the latent variable effect. After concentration screening, the initial mapping model is corrected, and the corrected mapping model is then used to simulate and optimize the output propagation conditions adapted to the latent variable environment.

This invention relates to a 3D UAV path planning method based on an improved gray wolf optimization algorithm, comprising: acquiring a 3D environment model; setting the start and end positions of the UAV based on the 3D environment model; employing the improved gray wolf optimization algorithm, using the objective function as the fitness function; updating the positions of all gray wolves synchronously during the iterative process; and outputting the optimal path. This invention introduces a circle chaotic mapping to the gray wolf optimization algorithm to increase population diversity; introduces an adaptive exploration factor to increase the balance between global and local search; combines the global and local development formulas of the dung beetle optimization algorithm to compensate for the slow convergence speed of the traditional gray wolf optimization algorithm; subsequently introduces a sine and cosine strategy to help the algorithm search for potential optimal solution regions, thus better exploring the global optimal solution; and finally introduces a pooling mechanism to randomly recombine stored historical poor solutions to generate new solutions, accelerating the convergence speed and improving the robustness of the algorithm.

The invention discloses a density detection and intrusion early warning method for a shallow sea biological model, and the method comprises the following steps: 1, density detection: a system firstly analyzes an input image or video frame through a target detection module based on an improved YOLO algorithm, recognizes a shallow sea biological target in the image or video frame, determines the type of the shallow sea biological target, and carries out the early warning of the intrusion of the shallow sea biological target; the shallow sea biological density detection is realized by combining an image processing method; step 2, acquisition of a shallow sea organism population coefficient: according to the detected shallow sea organism category, acquiring a corresponding population coefficient which reflects contribution of different types of shallow sea organisms to intrusion intensity; the method has the beneficial effects that the shallow sea organism data set is self-made, the content of the data set is enriched through an image enhancement technology and a data enhancement means, the diversity of samples is increased, and the recognition capability and generalization performance of the model on different types of shallow sea organisms are improved, so that the model can adapt to a complex underwater environment and a variable target form.

The application discloses a kind of molecular markers for identifying genetic sex of blue fish and its application, belong to the field of aquatic animal genetics and breeding.The molecular marker includes nucleotide sequence such as the common band of blue fish female and male fish shown in SEQ ID NO:1 and nucleotide sequence such as the unique band of blue fish male shown in SEQ ID NO:2, and the identification method comprises: taking the DNA of the blue fish sample to be identified as template for PCR amplification, after the band of PCR product is determined by agarose electrophoresis, capillary electrophoresis is carried out, if signal appears at 152bp and 168bp simultaneously, then it is male;If only signal appears at 168bp, then it is female.The molecular marker of the application can accurately obtain the genetic sex of different blue fish populations, has the advantages such as simple, fast, efficient, not affected by early undifferentiated gonad of blue fish, etc., is used for blue fish marker assisted breeding, which greatly saves the cost of aquaculture and improves the breeding efficiency.