1180 results about "Pest control" patented technology

A pest control system is disclosed comprising an optical, computational, and monitoring subsystem, optionally mounted on a mobile platform. The optical system may include a neutralizing laser or multi-wavelength light source, discovery and detail cameras (optionally stereo), a beam-steering mechanism, tunable focus, and optional thermal or depth sensors. The processor, such as a GPU or FPGA, identifies insect or biological targets, adjusts laser focus by depth, and controls beam activation. A monitoring system verifies safety by detecting humans or other non-target entities using environmental and thermal cameras; if detected, laser firing is inhibited. The mobile platform may use wheels, propellers, tracks, or cables, with GPS and data links for remote control. A visible light pre-flash may induce a blink reflex before firing. In some embodiments, a scouting drone transmits target coordinates to the neutralization unit, enabling coordinated, efficient, and safe laser-based pest control.

The invention relates to an intelligent monitoring system for prevention and control of diseases and insect pests for bean planting, in particular to the field of intelligent monitoring of prevention and control of agricultural diseases and insect pests, and can realize extremely early precise recognition and early warning of diseases and insect pests of bean crops. The weak lesion spectral features and the continuous deterioration trend of the plant can be sensitively captured in a stage which is difficult to perceive by naked eyes, real diseases and environmental interference are effectively distinguished, the system can automatically locate a suspicious lesion area by using a weak supervised learning mechanism and only needing image-level labeling, the dependence on expensive pixel-level labeling data is greatly reduced, and the accuracy of the system is improved. Finally, a high-confidence early warning signal is output through multi-source information collaborative decision, a scientific basis is provided for accurate and green prevention and control, blind pesticide application is effectively avoided, and crop health and yield are guaranteed.

The invention relates to the technical field of agricultural informatization and intelligent decision making, and discloses a vegetable growth cycle pest control decision making system and method based on a knowledge graph. According to the method, an unstructured agricultural data stream including vegetable varieties, growth stages, environmental parameters, pest and disease records and geographic information is collected from an original database. A data tuple set with a time stamp is generated by performing scanning identification and content extraction on a data stream. Then, clustering is carried out according to the growth stages to which the tuples belong, and stage feature clusters sorted according to the growth cycle are formed; and performing multi-dimensional feature correlation analysis on the stage feature cluster, and establishing a dynamic coupling relationship among the environmental parameters, the disease and pest history and the geographic space features under the growth cycle dimension. And based on the dynamic coupling relationship, generating disease and pest control decision parameters of the vegetables in the specific planting area in each growth cycle stage. According to the invention, accurate matching between the control decision and the crop physiological time sequence and regional characteristics is realized.

The invention relates to the technical field of forestry intelligent management and control, and discloses a forestry optimization management and control method and system based on artificial intelligence. The method comprises the following steps: collecting multi-source environment monitoring data such as soil humidity, illumination intensity and vegetation growth indexes in a forestry area, aligning a time sequence through a dynamic time warping algorithm, and separating steady-state and transient components; detecting anomalies through an isolated forest algorithm and generating a thermodynamic diagram, and obtaining a potential disease and pest outbreak area through causal reasoning in combination with historical records; constructing a dynamic growth reference curve, and identifying a disturbance sensitive area by using a generative adversarial network and a convolutional neural network; and integrating and generating a management and control priority partition map, optimizing resource allocation through deep reinforcement learning, outputting a task sequence, and driving equipment to execute irrigation, fertilization or pest control operation. According to the method, multiple artificial intelligence algorithms are fused, accurate control over the whole forestry process is achieved, and the method adapts to the dynamically-changing forestry environment.

The invention discloses an early-stage intelligent monitoring system for citrus reiculata Blanco canopy diseases and insect pests based on multispectral imaging, and belongs to the technical field of agricultural information. The system comprises a multispectral imaging module, a three-dimensional point cloud acquisition module, a data fusion module, a time sequence data analysis module, an intelligent identification module and a monitoring result output module. The method comprises the following steps: synchronously acquiring a multispectral image and laser radar point cloud data of a citrus reiculata tree canopy, and generating a point cloud model through spatial registration fusion; continuously recording model data of a plurality of time points, and extracting a time sequence feature vector; identifying disease and pest types and severity by using a deep learning model; and outputting a result to the user terminal. According to the invention, the problem that large-range and high-precision early monitoring of diseases and insect pests of citrus reiculata canopies is difficult to realize in the prior art is solved, early discovery, precise positioning and trend early warning of the diseases and insect pests are realized through air-space-ground integrated data fusion and intelligent analysis, and the intelligent level of orchard management and the disease and insect pest control efficiency are effectively improved.

The invention relates to the technical field of pest and disease damage prevention and control, in particular to a trichosanthes kirilowii maxim planting whole-process pest and disease damage monitoring-prevention and control collaborative management system, which comprises a data acquisition module, a data analysis module, a decision making module, a prevention and control execution module and a storage module, by means of agricultural prevention, physical prevention, biological prevention and chemical prevention, prevention and control measures are executed according to requirements of prevention and control decisions, and prevention and control conditions after the prevention and control measures are executed are fed back to the decision making module and the data acquisition module; and the decision making module receives the prevention and control condition feedback and then compares the association table with the prevention and control strategy again to judge whether to output the prevention and control decision again. According to the method, a'monitoring-decision-execution 'closed loop is constructed, the problems of opportunity dislocation and mutual interference of a comprehensive prevention and control strategy are solved through a prevention and control measure cooperative scheduling mechanism, and meanwhile precise prevention and control are achieved in combination with a dynamic monitoring system.

The invention provides a sunlight greenhouse winter seedling raising method for angelica sinensis. The Chinese angelica sunlight greenhouse winter seedling raising method comprises the steps that a sunlight greenhouse is built in an area with the altitude being 2000 m or below, the azimuth angle of the sunlight greenhouse is 5-7 degrees from the south to the west, the base angle of a front roof is 60-65 degrees, the elevation angle of a main lighting surface is 22-25 degrees, and the elevation angle of a back slope is 37-38 degrees; the method comprises the following steps: sowing angelica sinensis seeds in a greenhouse from late November to early and middle December, wherein the seeds comprise early bolting seeds, side ear seeds or main ear seeds; the environment in the greenhouse is controlled, the temperature in the coldest month is not lower than 12 DEG C, the ground temperature is not lower than 10 DEG C, and vernalization of the angelica sinensis seedlings is avoided; managing the seedlings, including water management, sunlight management, temperature regulation and control, weeding and thinning, and disease and pest control. The Chinese angelica sunlight greenhouse winter seedling raising method provided by the invention has the advantages that Chinese angelica seedling raising is carried out in a zone with the altitude of 2000m or below, and the problem that the ecological environment is damaged by Chinese angelica early bolting, Chinese angelica seed reserving, Chinese angelica prepared land seedling raising and Chinese angelica high-altitude seedling raising can be solved.

The invention relates to the technical field of pest prevention and control, in particular to a method for treating pine wood nematode infected wood through poria cocos. The method comprises the following steps: cutting down current-year epidemic wood, and treating tree heads, tree trunks and boughs to complete peeling and tendon retaining treatment; uniformly cutting the trunk and the boughs into standard cut-logs; the method comprises the following steps: selecting fresh poria cocos sclerotium skin tissues as strains, and cutting according to an area greater than 50% of a cross section; pit pits are dug in the sunny slope; laying small branches on the bottom layer, placing the cut-logs in the pits, fixing the cut-logs with non-woven fabrics after inoculation, covering the upper layer with thin branches and leaves, and covering with soil; the two-stage biological process of mycelium planting, propagation expanding and pine wood nematode and medium insect killing is sequentially completed through a soil heat and moisture preservation environment; the propagation path of pine wood nematodes is blocked through the natural isolation effect of soil, deadwood obtained after poria cocos is subjected to biological verification and then smashed on site to return to forests or be made into fuel particles, and harmless and resource recycling of epidemic wood is achieved. According to the method, the problems of pine wood nematode propagation and epidemic wood treatment are synchronously solved.

The invention relates to the technical field of chemical fertilizer preparation, and discloses a special synergistic pesticide fertilizer for a ratoon cane seedling stage, a preparation method and application thereof, the pesticide fertilizer adopts a core-shell layered structure, and comprises a core fertilizer layer, a pesticide layer and a resin coating layer from inside to outside in sequence; the medical fertilizer comprises the following components: 20-40% of an organic fertilizer; 20%-40% of inorganic nitrogen fertilizer; 5%-20% of a medium element fertilizer; 0.1%-2.5% of an insecticide; 0.1%-2.5% of a bactericide; 0.5%-5% of a composite slow release agent; 0.4%-2% of a resin coating material; and the balance of filler. By optimizing a formula and a preparation process, synergistic release of fertilizer nutrients and pesticide active ingredients is realized, nutrient requirements and disease and pest control requirements of ratoon sugarcanes in the seedling stage are met, the budding rate is remarkably increased, the withered seedling rate is reduced, and yield and income are finally increased; the stability and effectiveness of each component in the pesticide fertilizer can be effectively ensured; through precise application, multiple effects of the pesticide fertilizer are exerted to the maximum extent, and a standardized technical scheme is provided for seedling management of ratoon sugarcanes.

The present invention relates to microencapsulated preparations comprising biopesticide, bio-fungicide, and plant growth promoting agents and uses thereof, as well as to methods for controlling pests and for producing said preparations for managing insect pests. In particular, the invention relates to microencapsulated preparations comprising at least one insect-pathogenic (entomopathogenic) fungus selected from Metarhizium spp. and Beauveria bassiana, and at least one pathogenic Bacillus spp. bacterial strain, preparations and particles comprising these, their use on plant material, methods for controlling pests therewith, and processes for their production.

The invention relates to the technical field of disease and pest control, in particular to an image recognition-based garbage dump mosquito suppression system for precisely throwing probiotics, which comprises an image acquisition and sensing module for acquiring image data, environmental parameters, mosquito characteristic data and garbage decomposition state data; the mosquito feature analysis center extracts mosquito species, density and gathering area features, and constructs a mosquito breeding risk assessment model in combination with environmental parameters; the breeding risk assessment module fuses landform, garbage distribution and mosquito activity data, assesses a mosquito breeding risk level and a key breeding area, and generates a breeding risk probability cloud picture; the probiotic delivery decision-making unit simulates inhibition effects of different probiotic formulas and delivery strategies, generates a delivery scheme, and drives the ground robot to perform targeted delivery; the self-adaptive regulation and control module monitors mosquito density change and probiotic activity in real time, and dynamically adjusts a putting scheme through a swarm intelligence algorithm. Therefore, the problems of high pollution cost, poor accuracy and the like in the prior art are solved.

The invention relates to the field of knowledge questions and answers, in particular to a disease and insect pest questions and answers system fusing a knowledge graph and a large model. The uniqueness and accuracy of underlying facts are ensured through an automatic extraction and disambiguation mechanism driven by a large model, and the illusion phenomenon of the large model is effectively inhibited in combination with hard constraints of a knowledge graph, so that the accuracy and preciseness of disease and pest control suggestions are superior to those of a traditional data-driven method; the deep semantic understanding capability of the large language model is utilized, oral expressions, wrongly written characters and implicit intentions of peasant households are accurately recognized, compared with syntactic rule matching in the prior art, the misdiagnosis and omission ratio can be greatly reduced, and higher practicability is shown in a complex consultation scene; structured multi-source data representing expert knowledge is seamlessly fused into a large model generation process, an output result has professional constraints and conforms to human language habits, logic is smooth, the sense of speech is natural, and the interactive experience is far better than that of stiff template reply in the prior art.

The invention provides a multi-modal data driven farming decision-making system based on a large model. According to the system, the accuracy of farming decision making is improved through remote sensing images and field meteorological sensor data. Through integration of multi-modal data, real-time monitoring and accurate decision support of farming operation are realized, and the method aims at overcoming deviation of single-modal data decision and ensuring crop growth and yield. The specific construction process comprises the following stages: 1, collecting crop and farming historical data; 2, processing data, and constructing an agricultural database; thirdly, finely adjusting the multi-modal large model, setting cue words and optimizing the model; 4, processing daily data by using the fine-tuned model, and generating irrigation, fertilization and pest control decisions; fifthly, when the system detects early warning information, a user is notified in time; and 6, carrying out data analysis and reporting, and researching the crop growth trend and environment change. According to the method, multi-modal data are fully utilized, and powerful support is provided for accurate farming decision making.

The invention discloses bacillus subtilis S1703 and application thereof, and belongs to the technical field of plant disease and pest control. The name of the bacterial strain is bacillus subtilis S1703, and the preservation number of the bacterial strain is GDMCC No: 66890. The bacterial strain S1703 has a wider antibacterial spectrum, and can effectively inhibit the growth of pathogenic bacteria such as fusarium oxysporum, colletotrichum gloeosporioides, alternaria alternata, aspergillus, phyllosticta, citrus reticulata, fusarium and the like; fermentation liquor of the S1703 has a good antibacterial effect on the psidium guajava wilt pathogen and the psidium guajava branch blight pathogen; the bacteriostasis rate on sigatoka sigatoka and guava leaf spot germs reaches 95% or above, and an excellent bacteriostasis effect is achieved. The strain S1703 can avoid potential adverse effects of chemical pesticides on the environment and crop safety, and has potential commercial development and application values in biological prevention and control practice of diseases.

An aerosol dispensing device including an aerosol valve in fluid communication with a reservoir. A nozzle is in fluid communication with the aerosol valve. The nozzle includes a nozzle insert with an exit orifice and a nozzle body to receive the nozzle insert. The nozzle body is in fluid communication with the aerosol valve. A primary swirl chamber is in fluid communication with one or more inlet ports. The exit orifice is disposed generally concentric with the primary swirl chamber and a secondary swirl chamber and is in fluid communication therewith. The inlet port(s) are in fluid communication with the aerosol valve and may enter the primary swirl chamber non-tangentially. The secondary swirl chamber has a first and second diameter. A ratio of the first diameter to the second diameter is greater than about 1 and less than about 1.6. The pest control composition is non-Newtonian.

The invention belongs to the technical field of planting of herbal coffee beans, particularly relates to a planting method of herbal coffee beans, and provides the following scheme aiming at the problems of unstable pest control effect, soil ecology damage and poor crop stress resistance caused by excessive dependence on chemical pesticides in the planting process of existing herbal coffee beans. The method comprises the following steps: S1, deeply treating soil in a planting area, and disinfecting fine soil to obtain medicine soil; s2, spreading the pesticide soil on the soil surface, and spreading a bio-organic fertilizer; s3, raking the pesticide soil and the bio-organic fertilizer into the middle layer of the ridge soil, and covering the planting ridge with a plastic film; s4, selecting seeds, soaking the seeds in warm water, and coating the seeds; s5, sowing the treated seeds to the planting ridges, and performing health management; according to the method, in the planting process of the herbal coffee beans, effective microbial communities are introduced after soil disinfection, diseases can be effectively prevented, and meanwhile the soil is improved.

The invention relates to an insect condition monitoring method and device, which are used for monitoring insect conditions in real time and providing an accurate insect repelling strategy. The method comprises the following steps: acquiring historical data of a plurality of position nodes in a monitoring environment; the historical data comprises time sequence environment data and insect situation image data. Performing space-time alignment and feature fusion on the historical data to generate feature vector sequences of the position nodes at different historical moments; inputting the feature vector sequence into a self-adaptive causal graph learning module of a space-time causal graph network, deducing a relationship between position nodes through a multi-causal attention mechanism, and outputting a dynamic causal adjacency matrix representing a potential causal relationship; and inputting the dynamic causal adjacency matrix and the position node representation into a time sequence deduction and risk assessment module of a space-time causal graph network, simulating space-time evolution of an insect condition state through graph time sequence propagation, performing probability prediction and risk quantification, and outputting insect condition trend prediction data of each position node in a plurality of time steps in the future.

The utility model discloses a trapping device for preventing insects from laying eggs, which comprises a wool felt (1) compressed into a corrugated shape, a group of bristles (2) sewed at two ends of the wool felt (1) respectively, a support rod (3) and a plastic film (4). The egg laying trapping device induces codling moths to lay eggs in the device, concentratedly destroys eggs and trapped adults, has the advantages of being simple in structure and capable of being recycled, can reduce use of chemical pesticides, guarantees food safety and quality, and reduces prevention and control cost while controlling the number of pests.

The invention discloses a natural recovery method and device for a historical remaining mine. The method comprises the following steps: receiving geographical location information and climate information of a to-be-recovered historical remaining mine; fusing and identifying the multi-source remote sensing data for the historical remaining mine, and determining the to-be-recovered region type of the to-be-recovered region; according to the to-be-recovered region type, determining a recovered target region type; superposing terrain, soil, hydrology and pollution data by using a geographic information system (GIS) to generate a recovery potential coefficient; the recovery potential coefficient is used for adjusting a recovery target; making an ecological restoration plan according to the restoration target, the geographic position information, the climate information and the target area type; according to an ecological restoration plan, a ground robot is used for land improvement and sensor laying, an aerial robot is used for sowing, deinsectization, nutrient spraying and microorganism putting, and an intelligent irrigation system is used for irrigation; monitoring information is obtained; and adjusting and refining the ecological restoration plan based on the monitoring information.

The invention discloses a multi-modal open-field vegetable management decision method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining modal perception data corresponding to a target open-field vegetable field; determining a modal feature corresponding to each modal sensing data, determining a feature fusion weight corresponding to the modal feature of each time anchor point, and determining a global multi-modal fusion feature based on the feature fusion weight and the modal feature; and determining knowledge representation features from the agronomic knowledge spectrogram based on the modal perception data, and determining a target decision scheme according to the knowledge representation features and the global multi-modal fusion features. Various data sources such as weather, soil, crop states and agricultural machinery operation parameters are fused, space-time alignment and a self-adaptive weighting mechanism are adopted, a reinforcement learning technology is combined, an agricultural machinery operation strategy is dynamically adjusted according to real-time data, agricultural management measures such as fertilization, irrigation and pest control are optimized, the production efficiency is improved, and the economic benefit is increased. And the real-time performance and the accuracy of decision making are ensured.

The invention discloses an intelligent crop growth cycle management method and system, and the method comprises the steps: dividing dynamic monitoring grids based on the farmland terrain, laying monitoring points at the vertexes of each grid, and collecting the soil fertility and environment data; and generating a full farmland soil fertility index matrix through a spatial interpolation algorithm. Inputting the matrix, the environment data and the crop growth period parameters into a pre-training model, and outputting growth abnormality risk areas and types; driving the unmanned aerial vehicle to get close to the abnormal area to obtain a high-definition image, analyzing the disease and pest or nutrition deficiency symptom through an image recognition model, and generating an illness state verification result; and calling a farming operation knowledge base according to a verification result, and generating and executing a targeted operation instruction containing a fertilization / pesticide application scheme. According to the method, the spatial representation precision of the soil fertility is improved through dynamic gridding monitoring and interpolation, the crop risk is predicted in combination with multi-source data fusion, accurate pathology recognition is realized by utilizing targeted verification of the unmanned aerial vehicle, and the utilization efficiency of agricultural resources and the pest control precision are remarkably improved.

The invention provides a multi-agent collaborative decision-making method and system for agricultural insect pest evaluation and prevention, and relates to the technical field of AI.The method comprises the steps that multi-modal data are collected through edge sensing agents, insect pest target recognition and physiological stress quantification are conducted, and a standardized triple data structure is formed; the cloud analysis agent performs space-time correlation analysis based on the pest diffusion model, predicts a diffusion trend and calculates a risk level; and the decision-making agent generates a prevention and treatment strategy including region division, time sequence arrangement and resource allocation under the resource constraint. Accurate prediction and scientific decision making of pest control are realized, and the crop protection efficiency is improved.

The invention relates to the technical field of LED displays, in particular to an intelligent LED display based on the Internet of Things, which comprises a shell, a display screen is detachably mounted on the front side of the shell, an air inlet is formed in one side, facing the road surface, of the shell, a dust removal mechanism is mounted in the air inlet, a photocatalysis mechanism is arranged above the dust removal mechanism, and the photocatalysis mechanism is arranged above the dust removal mechanism. And a condensation mechanism connected with the photocatalysis mechanism is arranged on one side of the photocatalysis mechanism, a heat dissipation mechanism is connected to the lower portion of one side of the condensation mechanism, and the heat dissipation mechanism comprises a cavity formed in the middle of the interior of the shell. According to the intelligent LED display screen, protection, purification, heat dissipation, fire prevention and insect pest control are integrated, and multi-dimensional optimization of the intelligent LED display screen of the bus station is achieved; through air purification and cyclic utilization, an automatic fireproof system and mosquito control, the service life of equipment is effectively prolonged, the operation stability is effectively improved, meanwhile, the comfort of passengers and the environment quality of a waiting area are improved, and the requirements for safety, environmental protection and humanization are met.

To provide compounds having ant behavior inhibitory activity, and repellents and pest control agents containing the same. [Solution] An ant behavior inhibitor characterized by containing at least one compound selected from the group consisting of indole, methylheptenone, and methyl dihydrojasmonate.

The utility model discloses a pesticide spreading device for pest control and relates to the technical field of greenhouse equipment. The device structurally comprises a guide channel, a suspension guide pulley seat, a driving carrying table, a movable carrying table and a suspension connecting piece, a plurality of suspension connecting pieces are mounted on the guide channel; the suspension connecting piece is mounted on a circular steel pipe horizontally arranged in the center of the top of the greenhouse; the two ends of one side wall of the guide channel are each fixedly provided with a limiting plate. And two suspension guide pulley seats are mounted in the guide channel in a rolling manner. According to the utility model, the guide channel, the suspended guide pulley seat, the driving carrying platform and the movable carrying platform are matched for use, so that automatic spraying operation on crops in a greenhouse is realized; the problems that in the prior art, an existing device is complex in structure, large in installation and combination difficulty with a greenhouse steel structure, inconvenient to operate, incapable of being flexibly adjusted according to the crop height and uneven in spraying are solved. The automatic operation and sudden stop functions are also realized, the spraying efficiency and the safety are improved, and the labor intensity is reduced.

The invention discloses a crop disease and pest control pesticide spraying method and system based on image recognition, and the method comprises the steps: collecting crop images through carrying multiple cameras by an unmanned aerial vehicle, inputting the crop images into a double-branch deep learning model after preprocessing, and enabling the model to comprise an FCA frequency domain feature extraction network, a DAT-Transform spatial domain feature extraction network and an MSAF fusion module, precise identification of diseases and pests is realized; further integrating real-time environment parameters such as temperature and humidity, wind speed and crop growth stages, constructing a dynamic pesticide amount calculation model, and outputting personalized pesticide spraying amount; the pesticide spraying mechanism is driven by the controller to execute pesticide spraying, effect data is collected after a prevention and treatment period, an optimization recognition model and pesticide amount calculation parameters are fed back, and a recognition-pesticide spraying-feedback-iteration closed-loop prevention and treatment system is formed. The method solves the problems of low recognition precision, rigid pesticide amount regulation and control and lack of a continuous optimization mechanism in a complex environment in the prior art, improves the recognition precision, saves the pesticide amount, and improves the control effect.

The invention discloses a plateau pepper growth environment regulation and control integrated system based on multi-source data fusion, and relates to the field of plateau pepper auxiliary planting, and the integrated system is configured to be a closed cultivation device integrating environment perception, data fusion analysis and multi-factor cooperative regulation and control. The closed cultivation device comprises a cultivation bin body, an environment regulation and control module, a visual inspection module and a directional deinsectization module, the inner side of the cultivation bin body is divided into a plant growth regulation and control chamber and an equipment integration chamber which are adjacently arranged up and down through a transverse partition plate, and multiple rows of pepper planting modules distributed in the longitudinal direction are arranged on the inner side of the plant growth regulation and control chamber; according to the integrated system, environment perception, data fusion analysis and multi-factor cooperative regulation and control functions are integrated into the closed cultivation device, the visual inspection module is used for dynamically obtaining the plant growth state and pest and disease damage information, and the directional deinsectization module achieves precise deinsectization; and full-period stable control and multi-factor dynamic collaborative optimization of the plateau pepper growth environment can be realized.

The utility model relates to the technical field of agricultural planting, and discloses a polygonatum sibiricum planting land disease and pest prevention device which comprises four first telescopic rods, adjusting knobs are arranged in the middles of one sides of the four first telescopic rods, a protection mechanism is arranged above the first telescopic rods, a pest killing mechanism is arranged below the protection mechanism, and the pest killing mechanism is arranged above the first telescopic rods. The protection mechanism comprises a fixing disc, the middle of the lower surface of the fixing disc is fixedly connected to the top of the first telescopic rod, a threaded head is fixedly connected to the middle of the upper surface of the fixing disc, and an insect-proof net is arranged above the threaded head. The top of the first telescopic rod is connected with the fixing disc, the bottom of the threaded head is perpendicularly connected to the middle of the upper surface of the fixing disc, the threaded head can penetrate through the interior of the through hole, the first telescopic rod is covered with the insect-proof net, the nut can be screwed outside the threaded head, the insect-proof net is limited, and pests are blocked; therefore, the effect of preventing the pesticide from damaging the rhizoma polygonati can be achieved.

The invention belongs to the field of pest repellents, and particularly relates to application of n-octadecane in preparation of a pest repellent. According to the invention, n-octadecane (n-octadecane, with the CAS number of 593-45-3) is screened and identified from chemical signal substances on the body surface of the spider brachyta, and the n-octadecane has remarkable behavior regulation and control activity. A behavioral experiment proves that the pest repellent taking n-octadecane as a unique effective repelling component can remarkably induce the repelling behavior of cockroach pests such as cockroaches and periplaneta americana. The invention provides a novel, environment-friendly and efficient prevention and control product and a prevention and control method for pest prevention and control.