51 results about "Invasive species" patented technology

The invention provides a multi-mode underwater biological intrusion detection method and device, and the method comprises the steps: carrying out the sampling of each sampling grid of a target water area through acoustic equipment and image equipment, and obtaining the acoustic data and image data of each sampling grid; extracting and fusing the acoustic data and the image data of each sampling grid to obtain multi-modal features of each sampling grid, taking the multi-modal features as input of a discriminator in the generative adversarial network, and obtaining a discrimination result output by the discriminator as existence of invasive organisms or absence of the invasive organisms in the sampling grids; under the condition that the invasive organism exists in the sampling grid, sampling and detecting the eDNA environment sample on the sampling grid, and determining whether the invasive organism exists in the sampling grid or not based on a detection result. According to the method, rapid identification is carried out by utilizing multi-modal information and acousto-optic characteristics, the identification accuracy is improved by utilizing eDNA, the defects of a single method are overcome, and the efficiency of monitoring invasive species is improved.

The invention discloses a farmland weed and external invasion species detection method and device based on an unmanned aerial vehicle and deep learning, and the method comprises the steps: collecting and marking images containing weeds and external invasion species in a farmland, and forming a data set; the method comprises the following steps: constructing a weed and external invasion species target detection framework AriNanoDet model based on NanoDet, adopting ShuffleNetV2 as a backbone network, utilizing ShuffleNetV2Block in a second stage to a fourth stage of feature extraction, and then weighting channel information of an output feature map by applying an SE module; in the multi-scale feature fusion part, a self-adaptive feature selection mechanism is introduced on the basis of a feature pyramid network, a fused feature map is processed through a detection head, a detection result is optimized, and a model is formed and trained; the trained model is installed on an unmanned aerial vehicle for real-time detection, and positioning is carried out according to the detected coordinates of weeds and external invasion species. According to the invention, automatic monitoring of farmland weeds and external invasion species is realized, the labor cost is saved, the detection precision is high, and the detection process is simple and convenient.

The invention relates to the technical field of nuclear power facility safety protection, and discloses a nuclear power water intake invasion species risk early warning management system. The system comprises a monitoring data acquisition unit for integrating water quality, water flow velocity and biological image data to form a comprehensive monitoring data set; the species feature recognition unit is used for extracting biological image features and comparing the biological image features with the reference library to obtain a recognition verification result; the risk assessment unit is used for determining a species risk index according to an identification result so as to obtain a risk level and risk information; and the early warning response unit combines the risk level and historical data, and uses a model to adjust prevention and control measures to determine an optimal scheme. According to the system, multi-dimensional monitoring, accurate identification, scientific evaluation and effective prevention and control of nuclear power water intake invasion species are realized, the problems of low efficiency, poor accuracy and the like of a traditional management mode are solved, and operation safety and ecological environment stability of the nuclear power water intake are guaranteed.

The invention provides an invasive species identification method and device based on deep learning and DNA storage and electronic equipment, and relates to the technical field of invasive organism prevention and control, and the method comprises the steps: obtaining a to-be-identified invasive species image, and generating a first DNA sequence of a to-be-identified invasive species in the invasive species image through a deoxyribonucleic acid DNA encoder; obtaining a plurality of second DNA sequences to be hybridized from the invasive species database, and obtaining the hybridization yield of the first DNA sequence and each second DNA sequence by using a hybridization yield predictor; and determining the species category corresponding to the DNA sequence with the highest hybridization yield as the species category of the invasive species to be identified. According to the method provided by the invention, the strong feature extraction capability of deep learning is combined with the advantages of ultrahigh density and ultra-long stability of DNA as a data storage medium, so that end-to-end mapping and recognition from a species image to an exclusive DNA sequence thereof are realized.

The invention belongs to the technical field of biology, and particularly discloses a primer combination, a kit and a method for detecting invasive species pistia stratiotes in water by utilizing multiple PCR (Polymerase Chain Reaction). A primer design method is innovated, a pistia stratiotes multiplex PCR primer combination is screened out, the pistia stratiotes DNA can be detected in a natural water body in combination with an optimized PCR reaction system and conditions, the problem existing in environment eDNA detection is solved, multiplex PCR primers can be combined with environment DNA detection, and the diffusion condition of the pistia stratiotes can be monitored more accurately. The detection method can effectively save time and cost, is high in sensitivity, specificity and efficiency and low in professional requirement, has a better detection rate when the concentration of a target species is low, and can be judged through a gel chart.

The invention discloses a method and a device for dynamically patrolling a farmland by an unmanned aerial vehicle, and relates to the technical field of dynamic patrolling methods. A plurality of patrolling images are collected, and a plurality of pest and disease damage characteristics of rice are determined according to the plurality of patrolling images and the form of the rice; and the rice damage grade of the key inspection area is determined based on the feature position of each pest and disease damage feature, the corresponding feature form and the distribution position of the alien invasive species, so that the accuracy of the rice damage grade of the key inspection area is improved. Therefore, a plurality of abnormal rice areas are determined based on the identification of the dynamic distribution map, and the abnormal patrol event of the unmanned aerial vehicle is determined based on the area positions of the plurality of abnormal rice areas, the water flow areas associated with the abnormal rice areas and the current position of the unmanned aerial vehicle. And the dynamic patrol event of the unmanned aerial vehicle is determined according to the abnormal patrol event of the unmanned aerial vehicle and the weather conditions corresponding to the abnormal rice areas and the farmland, so that the accuracy of the dynamic patrol event of the unmanned aerial vehicle is improved.

The application discloses an automatic generation method of an invasive species prevention and control grade map, comprising the following steps: acquiring suitable habitat data of a target species in a target area and spatial data of at least two human interference factors; respectively performing spatial analysis on the suitable habitat data and the data of each human interference factor, dividing a risk grade, and obtaining a plurality of single-factor risk grade maps; weighting and superimposing the plurality of single-factor risk grade maps, calculating a comprehensive risk distribution according to a comprehensive evaluation rule, and generating a prevention and control grade map through reclassification; the method can be encapsulated as a geographic processing model to realize one-key automatic generation. Through systematic integration of natural suitable habitats and human interference factor systems, the application solves the problems of the existing prevention and control division methods, such as disconnection with actual conditions, difficulty in quickly responding to multi-scenario analysis, strong subjectivity and low repeatability, and realizes high-precision fitting of the division results with actual conditions, as well as an objective, stable and repeatable division process.

The application provides a digital PCR kit for detecting highland invasive species red-eared slider and bullfrog, a set of red-eared slider specific primer probes, which are composed of a primer pair for a specific segment of a red-eared slider mitochondrial CYTB gene and a red-eared slider specific TaqMan probe matched therewith; a set of bullfrog specific primer probes, which are composed of a primer pair for a specific segment of a bullfrog mitochondrial 12S rRNA gene and a bullfrog specific TaqMan probe matched therewith, and a set of internal standard (IPC) primer pairs and internal standard TaqMan probes for monitoring the nucleic acid extraction and amplification reaction process monitoring. The application is provided with the primer pair for the specific segment of the red-eared slider mitochondrial CYTB gene and the red-eared slider specific TaqMan probe, the primer pair for the specific segment of the bullfrog mitochondrial 12S rRNA gene and the bullfrog specific TaqMan probe, and a common internal standard to construct a triple detection reaction system, thereby avoiding the quantitative uncertainty caused by the single species detection in the prior art which needs to be carried out in multiple reactions or relies on a standard curve for relative quantification.

The invention provides a method and a system for predicting a potential suitable growth area of alien invasive species in the technical field of risk management of invasive species. The method comprises the following steps: S1, acquiring a large amount of environment variable data and species distribution sample data; s2, downscaling the environment variable data through a spatial regression model to construct a high-resolution environment data set, performing spatial refinement on the species distribution sample data through a Moran index to construct a sample data subset, and constructing a data set based on the high-resolution environment data set and the sample data subset; s3, creating a species distribution model based on a maximum entropy model, a random forest, a support vector machine, a generalized linear model, an XGBOOST or a deep learning model, and training the species distribution model through the data set; and S4, predicting the suitable growth area of the alien invasive species through the trained species distribution model. The method has the advantages that the prediction precision and generalization ability of the potential suitable growth area of the alien invasive species are greatly improved.

In one or more illustrative arrangements, a robotic modular system is presented that is configured to remove vegetation, which may be an invasive plant species and / or target plant. In one or more illustrative arrangements, the robotic modular system includes a cutting module, a spraying module, and an optical module. In one or more illustrative arrangements, the system identifies an invasive species and / or target plant, the system is then moved near the invasive species and / or target plant, and the cutting module is positioned to perform a cutting operation. In one or more illustrative arrangements, the cutting module then performs a cutting operation on the invasive species and / or target plants, and the spraying module sprays the remaining portion thereof.

The application provides a screening method for effectors of foreign invasive species Hyphantria cunea larvae saliva and female insect oviposition secretions. The application collects saliva of invasive species Hyphantria cunea larvae and concentrates female insect oviposition secretions, then performs mass spectrometry analysis, performs KEGG and GO cluster analysis on the obtained protein information, and screens possible key proteins. Further, CRISPR / Cas9 and RNAi means are used to explore the functions and roles of these effectors in key damage-causing processes such as Hyphantria cunea larvae feeding and female insect oviposition, effectively realizing the screening of effectors of the foreign invasive pest, and providing effective means for preventing the maintenance and outbreak of Hyphantria cunea population and the damage of the population to agricultural and forestry crops.

The invention belongs to the field of invasion species prevention and control, and relates to a solenopsis invicta living area prediction technology, in particular to a solenopsis invicta living area prediction method and system based on artificial intelligence, and the method specifically comprises the steps: marking a solenopsis invicta adjacent area as a prediction area, and determining a survival factor 1 through environment data; determining a survival factor 2 through the soil type, the vegetation coverage rate and the landform, and integrating the determined survival factor 1 and the determined survival factor 2 into a total survival factor; and determining a prediction area with the solenopsis invicta according to a flood diffusion factor obtained by combining the total survival factor with the flood flow and the start time and a marriage flight diffusion factor obtained based on the start time of marriage flight diffusion of the solenopsis invicta. According to the method, passive marking of the solenopsis invicta living area is changed into active prediction, the problems that existing marking of the solenopsis invicta living area is delayed, and the diffusion condition of the solenopsis invicta living area under the natural condition is difficult to predict and recognize are solved, and the capability of human beings for preventing and controlling the solenopsis invicta is improved.

The invention discloses an external invasion species identification method based on an unmanned aerial vehicle and hyperspectral multimodal data, relates to the technical field of remote sensing and computer vision, and is deployed on the unmanned aerial vehicle or edge equipment. Constructing a grass decision head and a verification decision head for parallel reasoning through a lightweight convolution trunk of transfer learning in combination with channel attention and improved h-swsh; and performing time window re-judgment on the gray region sample by matching the comprehensive acceptability with a dual-threshold decision, and when the judgment is still uncertain, performing uploading re-checking and backflow for incremental learning and threshold updating. And the end side adopts INT8 / FP8 quantization, operator fusion and asynchronous two-stage pipeline to reduce time delay and energy consumption. And outputting the species category, the confidence coefficient, the timestamp and the rechecking mark. The method is suitable for field rapid identification.

Within the framework of health policies for monitoring human and animal epidemiological diseases in environments where different mosquito species proliferate as endemic species or appear as non-native invasive species, the smart mosquito sex-sorting device, which uses the sexual dimorphism of pupa size of certain mosquito species, automatically separates mosquito pupae by sex using artificial intelligence (AI) by analysing images with algorithms to identify the sex, thus optimising the volume of males recovered. For this purpose, successive steps are performed, using a tank of pupae and larvae to be sexed, a batch dosing device, a pupae dispenser with a flow divider shaft (12), a pupae calibrating device containing an optical camera for acquiring a digital image, and a distributor arm for depositing the sorted insects into containers.

The invention discloses a LAMP (loop-mediated isothermal amplification)-based rapid detection primer group, method and kit for Solenopsis invicta. According to the invention, by innovatively combining a commercial isothermal amplification kit, a self-designed specific primer, a sample releasing agent and a portable constant-temperature heater, rapid, portable and low-cost detection in a field environment is realized; detection can be completed within 45 min, the sensitivity reaches 2.31 * 10 <-3 > ng / L, and the specificity is larger than or equal to 99%. The method can be widely applied to the scenes of agricultural quarantine, import and export detection, ecological monitoring, prevention and control of invasive species and the like, provides a better solution for quickly identifying the small imported fire ants on site, and has remarkable practical value and popularization and application prospects.

This invention provides a system and method for controlling invasive species in port facilities, as well as cargo handling equipment for port facilities, that more easily prevents the establishment and spread of invasive species attached to cargo in port facilities. [Solution] The pest control system 1 for controlling invasive species A attached to cargo C handled by cargo handling equipment 10 at port facilities P comprises camera devices 2a to 2c that acquire image data D1 to D3 of cargo C during cargo handling by cargo handling equipment 10, and a computing device 3. A section capable of storing cargo C is designated as a pest control section 6. The computing device 3 performs data processing to identify invasive species A in the image data D1 to D3 based on the image data D1 to D3 acquired by the camera devices 2a to 2c, and data processing to interrupt the handling of the target cargo CA and have the cargo handling equipment 10 store the target cargo CA in the pest control section 6. In the pest control section 6, invasive species A attached to the stored target cargo CA is controlled.

A system is provided.SOLUTION: A system comprising: means for detecting dangerous animals, harmful insects, and foreign organisms; means for generating a countermeasure using a generation AI based on a type and an invasion place of the detected organisms; and means for notifying a user of the generated countermeasure and notifying a public institution of the countermeasure as necessary.SELECTED DRAWING: Figure 1

The invention discloses a YOLOV8-based alien invasive species detection method. The method comprises the following steps: S1, obtaining an alien invasive species picture; s2, preprocessing the external invasive species data set; s3, the original data set is expanded through a python code; s4, performing object labeling on the alien invasive species picture, dividing the alien invasive species picture into a training set, a verification set and a test set, and constructing to obtain alien invasive species data sets which are respectively used for model training, verification and test; s5, putting the training set into an improved YOLOv8 model for iterative training to obtain an optimal model file; and S6, verifying the model by using the verification set, and outputting a detection result. And S7, testing the alien invasive species detection model obtained in the step S6 by using the alien invasive species data set obtained after preprocessing in the step S4. The invention provides an alien invasive species detection method based on YOLOV8. The species information of alien invasive species is detected and identified through a target detection algorithm.

The invention belongs to the technical field of biology, and particularly discloses a primer and probe combination for detecting an invasive species, namely Salvelinus pelitovii, in water by utilizing multiple PCR (Polymerase Chain Reaction). According to the invention, the RPA specific primer of the saw fat carp is innovatively designed, an eDNA technology and an RPA flow measurement chromatography detection technology are combined, and a technology for visually and timely detecting the saw fat carp is established. The method is simple to operate, does not need a precise instrument, can obtain a detection result within 50 minutes at 38 DEG C, and is suitable for field real-time monitoring research. The detection method can effectively save time and cost, is high in sensitivity, strong in specificity, high in efficiency and low in professional requirement, has a better detection rate when the concentration of a target species is low, and can obtain a detection result without the help of a special instrument.

The present application relates to the field of ecological restoration, and more particularly to a method for restoring the ecology of a coastal wetland, which comprises the following steps: removing invasive species from the area to be restored; laying an ecological restoration substrate; planting the sea grass in a cluster-strip composite pattern; introducing biological communities in batches every two months; setting up a tidal response system and an intelligent monitoring platform to monitor the condition of the area to be restored; and the ecological restoration substrate comprises 40% oyster shells, 40% coral sand and 20% bentonite. The method for restoring the ecology of a coastal wetland provided by the present application forms an "algae-grass barrier" by planting sea grass and eucheuma alternately, effectively improves the water transparency and promotes photosynthesis; the disturbance behavior of benthic animals such as sea cucumbers enhances the oxygen penetration depth and oxidation-reduction potential (Eh) of the sediments, and improves the bottom environment; and the gradient buoyancy planting device realizes tidal self-adaptation, ensuring the stable growth of the sea grass under different water level conditions.

The invention discloses a method for constructing an annual fleabane monitoring model based on remote sensing data, and the method comprises the following steps: 1), carrying out the ground investigation of a target region in the growth period of annual fleabane, and collecting the sample data of annual fleabane; 2) performing remote sensing multispectral image data acquisition on the target area, and preprocessing the acquired remote sensing multispectral image data; 3) obtaining a grassland area; 4) calculating multi-source remote sensing features of the remote sensing multispectral image data of the grassland area preprocessed in the step 2); (5) permutation and combination are carried out on the multi-source remote sensing features obtained in the step (4), the importance of different multi-source remote sensing features in annual fleabane monitoring is evaluated by utilizing an average descending Gini coefficient, and the importance of the multi-source remote sensing features is sequenced; 6) removing multi-source remote sensing features with high correlation by using a Pearson's correlation coefficient, and 7) constructing an erigeron annuus monitoring model.The erigeron annuus monitoring method is suitable for monitoring, management and early prediction and early warning of erigeron annuus.

Wakeboats that include an aquatic invasive species control apparatus are provided. These wakeboats can include: a wakeboat with a hull; at least one throughhull fitting in the hull of the wakeboat; an irradiation chamber in fluid communication with the at least one throughhull fitting, the irradiation chamber having a radiation source; and at least one water destination aboard the wakeboat. Methods for irradiating invasive aquatic species aboard a wakeboat are also provided. The methods can include: receiving water from outside the wakeboat hull; and irradiating water aboard the wakeboat prior to discharging the water.

The invention discloses a spartina alterniflora monitoring method based on NDSPI, and the method comprises the steps: firstly calculating a normalized phenological index of a time sequence through a multi-temporal Sentinel-2L2A image, and reconstructing a smooth phenological curve through time sequence harmonic analysis; the NDSPI is innovatively constructed through the combined calculation of the key phenological period, so that the difference between the spartina alterniflora and other salt marsh vegetation is enhanced. And then median filtering noise reduction is performed on the NDSPI image, and K-means + + unsupervised classification is adopted to efficiently extract spatial and temporal distribution of spartina alterniflora. The method has the advantages of full-process automation, convenient data acquisition and strong adaptability, and provides reliable technical support for coastal wetland invasive species monitoring and ecological protection.

The invention relates to the technical field of prevention and control of alien invasive species ampullaria gigas, in particular to an ampullaria gigas trapping and collecting device which comprises a collecting barrel used for being placed in water, and the top of the collecting barrel is movably connected with a barrel cover; a vertical telescopic rod is fixedly connected into the collecting barrel and comprises a lower rod and an upper rod, the lower rod is provided with a vertical rod cavity, and the upper rod is vertically connected into the rod cavity in a sliding mode; the telescopic rod penetrates through the can cover, and the can cover is provided with a notch for the telescopic rod to penetrate through. By means of the scheme, fixed-point, efficient and clean trapping and collecting of the ampullaria gigas are achieved.

The invention relates to the field of ecological restoration, in particular to a coastal wetland ecology restoration method. The invention provides a coastal wetland ecology restoration method. The coastal wetland ecology restoration method comprises the following steps that invasive species of a to-be-restored land are removed; laying an ecological restoration matrix; the sea grass is planted in a cluster-strip composite mode, and field planting is conducted; introducing biocenosis in batches every two months; a tide response system and an intelligent monitoring platform are set up to monitor the condition of the to-be-repaired land; the ecological restoration matrix comprises 40% of oyster shells, 40% of coral sand and 20% of bentonite. According to the remediation method provided by the invention, the seaweed bed and the eucheuma are planted at intervals to form an algae-grass barrier, so that the transparency of a water body is effectively improved, and photosynthesis is promoted; the disturbance behavior of benthonic animals such as sea cucumbers enhances the oxygen penetration depth and oxidation-reduction potential (Eh) of sediments and improves the substrate environment; tidal self-adaption is achieved through the gradient buoyancy planting device, and it is guaranteed that sea grass stably grows under different water level conditions.

The application discloses a kind of prairie ecological restoration grass comprehensive evaluation method, it is related to ecological restoration assessment technical field, the present application includes the following steps: obtaining the flora characteristics and distribution characteristics of grassland plant, selecting ecological restoration grass;Set the basic conditions of ecological restoration grass: first, no public nuisance, no pollution, no security risk species, then avoid selecting invasive species, finally, strong self-reproduction ability and strong soil and water conservation ability species;Set the optimization condition and specific index of ecological restoration grass, the optimization condition includes: environmental adaptability, soil and water conservation capacity, reproductive capacity;Specific index includes: cold resistance, drought resistance, salt tolerance, wide distribution, green period, green period, root biomass, aboveground biomass, crown width, growth rate, branch growth type, tillering / branching number, seed thousand-grain weight, seed germination force;Build comprehensive evaluation model;Calculate the total score of target layer, and comprehensively evaluate ecological restoration grass.

The invention discloses a visualized rapid detection method for solenopsis invicta, and relates to the technical field of biological detection, and the technical key points are as follows: a rapid molecular detection method for invading species solenopsis invicta is developed on the basis of a loop-mediated isothermal amplification technology, mitochondrial DNA (mitochondrial DNA, mtDNA) cytochrome b (Cytochrome b, Cytb) genes of the solenopsis invicta are taken as targets, and the primers are used for detecting the mitochondrial DNA of the solenopsis invicta and the cytochrome b of the solenopsis invicta; the method comprises the following steps: designing and screening specific LAMP primers (F3 / B3, FIP / BIP); the method can accurately distinguish the solenopsis invicta from nine related species of solenopsis invicta, breaks through the dependence of traditional molecular detection on professional equipment and complex operation, and provides a high-sensitivity and high-specificity field detection tool for solenopsis invicta invasion monitoring and port quarantine.

The application discloses a kind of real fly luring and killing agents.The real fly luring and killing agent is composed of the following components by mass percentage: 75-85% of apple snail meat hydrolysate, 3-7% of pest toxic components, 5-15% of auxiliary materials and 2-5% of stabilizers.The apple snail meat hydrolysate is a mixture of apple snail meat after protease hydrolysis and enzyme inactivation, and the pest toxic components are Metarhizium or Beauveria.The luring and killing agent uses the protein hydrolysate of invasive species apple snail meat as the main raw material to prepare food lure, and then adds a small amount of Metarhizium / Beauveria to prepare the luring and killing agent.The synergistic effect of food lure and Metarhizium / Beauveria significantly improves the luring and killing effect on real flies.The new real fly luring and killing agent has the characteristics of high efficiency and green environmental protection.