1819 results about "Tea tree" patented technology

The invention provides a clamping force correction method and system based on an oil-tea tree branch clamping manipulator and a storage medium, and relates to the technical field of mechanization and automation, and the method comprises the steps of monitoring and analyzing oil-tea tree branches, an operation environment and a manipulator motion state, collecting key parameters, generating a clamping adaptability index and a clamping stability index, and correcting the clamping force of the oil-tea tree branches; the clamping adaptability index and the clamping stability index are combined, and a clamping control index is calculated; constructing a deep learning model, taking the historical key parameters as a training set, taking the corresponding historical manipulator clamping force as a label, training the model to obtain a clamping force prediction model, inputting the key parameters collected in real time into the model, outputting the predicted clamping force, combining the predicted clamping force with a clamping control index, and calculating the final clamping force. On the basis of obtaining key parameters in real time, the clamping adaptability index and the clamping stability index are generated, then the clamping control index is calculated, and the purpose of dynamically adjusting the clamping force is achieved.

The invention discloses bacillus velezensis P15 and application thereof. The strain is preserved in the China General Microbiological Culture Collection Center (CGMCC), and the preservation number is CGMCC NO.31995. The invention further discloses a preparation method of the bacillus velezensis P15. The bacterial strain has broad-spectrum and efficient antagonistic action on 21 different phytopathogens belonging to 12 genus, can effectively prevent and treat anthracnose of tea trees, powdery mildew of various vegetables and postharvest diseases of mangoes and peaches in vivo, has the prevention and treatment effect higher than 85% or above, has the prevention and treatment effect equivalent to or even more excellent than that of chemical pesticides, and has a broad application prospect in construction of a biocontrol bacterium resource library. The development of safe and efficient biopesticide has important significance.

The invention discloses a tea garden soil improvement method based on microbial communities. The tea garden soil improvement method aims at improving soil fertility and tea tree yield by means of precisely screening beneficial microorganisms, optimizing culture conditions and the like. Firstly, soil samples are collected from a tea garden area, gene high-throughput sequencing is carried out, soil microbial community composition information is obtained, and beneficial microorganisms are screened out. Then, the breeding speed and biomass of the beneficial microorganisms are optimized by adjusting a culture medium formula. When the bio-fertilizer is prepared, besides concentrated bacterial liquid, an organic carrier, inorganic nutrient elements and humic acid serving as a stabilizer are also added, and a proper amount of trace elements and a plant growth regulator are added. In spring or autumn, according to the physicochemical property of the soil, the bio-fertilizer is uniformly spread and ploughed into the soil layer. After fertilization, soil physicochemical properties and tea tree growth conditions are regularly detected to evaluate the soil improvement effect and adjust the fertilization strategy according to the soil improvement effect. The method is beneficial for improving the tea garden soil health condition and improving the tea yield and quality.

The invention relates to the technical field of tea garden disease and insect pest monitoring, in particular to a tea garden disease and insect pest monitoring method and system based on photovoltaic light supplement. The method comprises the following steps that photovoltaic light supplementing equipment is arranged, and tea garden environment data are obtained; carrying out photovoltaic light supplement operation according to the tea garden environment data, and carrying out tea tree image acquisition through camera equipment to obtain tea tree image data; tea tree trunk feature extraction and tea tree tea feature extraction are carried out according to the tea tree image data, and tea tree trunk feature data and tea tree tea feature data are obtained; performing pest assessment according to the tea tree trunk feature data and the tea tree tea feature data to obtain pest assessment data; and performing pest distribution generation according to the pest evaluation data, the tea tree trunk feature data and the tea tree tea feature data to obtain pest distribution data. According to the invention, an intelligent and automatic tea garden disease and insect pest monitoring and prevention and control system is formed by combining photovoltaic light supplement and disease and insect pest simulation.

The invention provides a core SNP (Single Nucleotide Polymorphism) marker for tea tree variety identification. Based on a simplified genome sequencing technology, a KASP system is adopted to carry out genetic typing on 48 tea tree varieties, the SNP fingerprint spectrum of each tea tree variety is constructed, and finally it is determined that the 48 tea tree varieties can be efficiently and accurately distinguished and identified only through 9 specific SNP markers. The 9 SNP markers provided by the invention not only enrich molecular markers of tea tree varieties, but also can be applied to genetic typing, identification, auxiliary identification and similarity detection of the tea tree varieties.

The invention discloses a tea tree CsU3 gene promoter and application thereof, and belongs to the technical field of plant biotechnology and gene engineering. Tea tree RNA polymerase III type promoters-tea tree endogenous U3 gene promoters CsU3a, CsU3b, CsU3c and CsU3d are successfully cloned for the first time, a tea tree U3 gene promoter activity detection carrier is successfully constructed, the transcriptional activities of the four CsU3 promoters are compared through instantaneous tobacco leaf conversion, GUS dyeing and GUS enzyme activity determination, and the CsU3 gene promoter activity detection carrier can be used for detecting the activity of the tea tree U3 gene promoter. CsU3a and CsU6b promoters with strong transcriptional activity are selected to be used for constructing a tea tree gene editing carrier, the feasibility of the promoter applied to a tea tree CRISPR / Cas9 gene editing system is verified in a tea tree protoplast, and CRISPR / Cas9 mediated tea tree genome targeted editing is realized.

The invention provides application of a transcription factor CsPIF7 gene in regulation and control of theanine synthesis and improvement of tea quality, and belongs to the technical field of agricultural molecular biology. The invention finds that high expression of CsPIF7 can activate expression of TS1 and GS1, so that more theanine can be accumulated in tea leaves; after the expression of CsPIF7 is reduced by a tea tree VIGS technology, the activation and expression of TS1 and GS1 can be reduced, so that the content of theanine in tea leaves is reduced. Furthermore, the tea tree transcription factor CsPIF7 is found to be capable of positively regulating and controlling expression of TS1 and GS1 by utilizing LUC verification, and can be used for regulating and controlling the content of theanine in tea trees and improving the quality of tea leaves.

The invention provides a tea tree fresh leaf identification method and system based on YOLOv8 in the technical field of tea leaf detection, and the method comprises the following steps: S1, obtaining a large number of historical images of tea tree fresh leaves, carrying out the preprocessing of data annotation and data expansion of each historical image, and constructing a data set; s2, creating a tea tree fresh leaf recognition model based on a YOLOv8 network, and setting a loss function of the tea tree fresh leaf recognition model as an I nner-S I oU function; s3, dividing the data set into a training set, a verification set and a test set based on a preset proportion, and training, verifying and testing the tea tree fresh leaf recognition model through the training set, the verification set and the test set; and S4, deploying the tea tree fresh leaf recognition model passing the test, and performing tea tree fresh leaf recognition by using the deployed tea tree fresh leaf recognition model. The method has the advantage that the identification accuracy of the fresh tea leaves is greatly improved.

The invention discloses an SSR (Simple Sequence Repeat) core primer combination and a kit for identifying a tea tree variety 'swan gooses 12' and application of the SSR core primer combination and the kit. According to the invention, three pairs of SSR core primers are screened by using an SSR fluorescence labeling detection technology, and the three pairs of SSR core primers can rapidly identify and detect the 'Yangou 12' from other tea tree varieties. The SSR core primer combination disclosed by the invention can be used for identifying the variety of the swan goose 12, the uncertainty of identification based on external morphological characteristics is overcome, the result is reliable and visual, the detection efficiency is high, the operation is simple and convenient, and meanwhile, the popularization, utilization and protection of the variety of the swan goose 12 are also facilitated.

Present invention teaches the method of using a keratin hydrolysis peptide (“KHP”) solution to enhance the yield and quality of tea leaves. By selectively choosing specific weights of feathers and water, and treating the mixture to a high-temperature high-pressure hydrolysis process, the resulting solution is confirmed to contain at least 253 peptides and then apply to the tea trees either by infusing to the soil or by leaf spray at certain growth stages. Optionally, the KHP solution can be diluted by water, as disclosed in the specification, for soil infusing or leaf spraying.

The invention relates to the technical field of film material preparation, and discloses a polylactic acid antibacterial packaging film and a preparation method thereof, the polylactic acid antibacterial packaging film comprises the following raw material components by weight: 60-80 parts of polylactic acid, 10-20 parts of polyvinyl alcohol, 10-20 parts of nano zinc oxide, 0.5-1.5 parts of nano cellulose, 1-3 parts of an antibacterial agent, and 10-15 parts of corn starch; the antibacterial agent is prepared from the following components in parts by weight: 5-10 parts of carboxymethylated chitosan and 0.5-2 parts of a dynamic disulfide bond cross-linking agent, the substitution degree of the carboxymethylated chitosan is greater than or equal to 80%, the antibacterial agent is prepared from tea tree essential oil and eugenol, and the dynamic disulfide bond cross-linking agent is bis (3-aminopropyl) disulfide. By adopting a composite system of carboxymethylated chitosan and a dynamic disulfide bond cross-linking agent, the technical effects of humidity-triggered self-repairing and mechanical property synergistic improvement are achieved, and compared with a packaging film with a single polymer base material in the prior art, the problem of antibacterial failure caused by mechanical damage is solved.

The invention relates to a double-arm intelligent collaborative tea picking method and device based on multi-strategy dynamic scheduling, and belongs to the field of robot automation. The method comprises the following steps: obtaining three-dimensional coordinate information of a target picking point; identifying and positioning potential branch and leaf shields, and generating space data of the shields; the method comprises the following steps: simultaneously projecting a shielding object and a clamping jaw geometric contour under an expected grabbing pose on a plane where a target picking point is located, analyzing the overlapping amount, the proximity and / or the density of the projections of the shielding object and the clamping jaw geometric contour, and generating a standardized shielding evaluation index; comparing the shielding evaluation index with a preset decision threshold, and if the shielding evaluation index is greater than the preset decision threshold, executing a master-slave collaborative picking method based on multi-stage positioning; otherwise, executing the parallel picking method based on dynamic collision-free region division. The problems that a traditional single-arm tea picking robot is low in operation efficiency, high in collision risk and insufficient in intelligent degree in a dense and unstructured tea tree environment are solved.

The invention discloses an SSR (Simple Sequence Repeat) core primer combination for identifying a tea tree variety 'Danxia No.1', a kit and application. According to the invention, three pairs of SSR core primers are screened by utilizing an SSR fluorescence labeling detection technology, and the three pairs of SSR core primers can be used for rapidly identifying and detecting 'Danxia No.1' from other tea tree varieties. The SSR core primer combination disclosed by the invention can be used for identifying the variety of Danxia No.1, overcomes the uncertainty of identification based on external morphological characteristics, is reliable and visual in result, high in detection efficiency and simple and convenient to operate, and is also beneficial to popularization, utilization and protection of the variety of Danxia No.1.

The invention discloses a tea tree liquid phase chip and application thereof, and relates to the technical field of molecular detection. The invention discloses a tea tree liquid phase chip and application thereof, according to site screening requirements and probe design principles, the tea tree liquid phase chip comprises 5781 SNP sites, and tea tree resource genetic typing can be realized based on a target interval genome sequence liquid phase capture accurate positioning sequencing typing technology. The tea tree liquid chip can realize low-cost genetic typing, is mainly specific to tea trees, can realize variety identification and genetic relationship analysis of the tea trees, scientifically guides hybridization improvement work of the tea trees and assists protection and development of germplasm resources of the tea trees, and has relatively high application values in multiple fields of tea tree breeding. The tea tree liquid phase chip can be used for tea tree genetic diversity evaluation, germplasm resource and genetic relationship identification, genetic map construction and gene localization, whole genome association analysis and tea tree molecular marker assisted breeding.

The invention relates to the technical field of image data processing, in particular to a multispectral monitoring and optimizing method and system for tea tree growth in a tea garden. The method comprises the following steps: acquiring tea tree growth spectrum data; performing tea tree growth spectral feature extraction according to the tea tree growth spectral data to obtain tea tree growth spectral feature data; performing tea tree growth index calculation according to the tea tree growth spectral feature data to obtain tea tree growth index data; and performing growth state monitoring according to the tea tree growth index data to obtain tea tree growth state monitoring data so as to perform tea tree growth and cultivation optimization operation. By continuously monitoring the growth state of the tea trees and performing dynamic optimization, the tea trees can be ensured to be always in the optimal growth environment, so that the yield and quality of the tea leaves are improved to the maximum extent.

The invention discloses a tea tender shoot recognition method and device, equipment and a medium, and relates to the technical field of image recognition, and the method comprises the steps: obtaining a target image; the target image is an image obtained by shooting a target tea picking area; inputting the target image into a trained tea tree tender shoot recognition model to obtain a tea tree tender shoot recognition result corresponding to the target image; wherein the trained tea tree tender shoot recognition model is an improved RT-DETR model; according to the improved RT-DETR model, a backbone network is a ResNet18 network, an AIFI module is replaced by a CGFA module, a CCFM module is replaced by a GD feature fusion module, a RepC3 module is replaced by a DRBC3 module, and the CGFA module replaces a multi-head attention mechanism layer in the AIFI module with a cascade group attention mechanism layer. The tea tender shoot recognition efficiency and precision are improved.

The invention provides a hyperspectrum-based tea tree canopy leaf nitrogen estimation method, which comprises the following steps of: firstly, smoothing original spectral data of a tea tree canopy by using a Savitzky-Golay method so as to reduce random noise and improve a signal-to-noise ratio; then, the original spectrum is converted into 600 wave bands at the interval of 1 nm through spline interpolation, so that the continuity and convenience of calculation are ensured; the method comprises the following steps of: firstly, carrying out first-order derivative processing on a spectrum, then carrying out second-order derivative processing on the processed spectrum, calculating a normalized difference spectrum index (NDSI) by using a derivative spectrum, calculating a Pearson's correlation coefficient (PCC) between the NDSI and a measured nitrogen element, carrying out principal component analysis (PCA) on the highest 20 indexes of the correlation coefficient, and finally constructing a multiple linear regression model by using the principal components with the first 10 PCA scores as parameters. The method is used for predicting the nitrogen content (LNC) of tea tree canopy leaves. Prediction experiments of a plurality of tea gardens show that the model shows a good prediction effect which is close to the actual nitrogen content, and the generalization performance is good.

The invention belongs to the field of biological organic fertilizers, and discloses a special organic selenium-rich fertilizer for grapes as well as a preparation method and application thereof. The fertilizer is prepared from the following raw materials in percentage by mass: 0.05-0.2% of a selenium complex, 2-15% of a stabilizer, 15-25% of a microbial fermentation product, 0.5-2.0% of a natural plant extract and the balance of auxiliary materials, totaling 100%. The microbial fermentation product is microbial fermentation liquid obtained by fermenting bacillus tequilensis and cyanobacteria; the auxiliary material is obtained by mixing sodium alginate and maltodextrin; the natural plant extract is obtained by mixing azadirachtin, sophocarpidine, tea tree essential oil and cnidium lactone. Through the synergistic effect of the microbial fermentation product, the natural plant extract and the auxiliary materials, the industrial problem that in the prior art, a selenium fertilizer can only improve the selenium content of grapes, but cannot effectively improve the disease resistance and insect pest resistance of the grapes and slow down selenium element loss is solved, and the double improvement of the grape quality and the selenium content is achieved.

The invention relates to a tea-picking robot autonomous navigation method based on tea ridge composite boundary identification and driving area adjustment, and belongs to the technical field of robot navigation. The method comprises the steps that tea ridge growth state information is evaluated, and a global path planning strategy is made; a root-ground intersection ground navigation datum line and lateral boundary constraints are established, the ground navigation datum line, the lateral boundary constraints and tea tree growth density and distribution characteristics are integrated, a tea ridge three-dimensional drivable road network model is established, and key geometric characteristics of the model are analyzed to establish an adaptive risk assessment system. Dividing the drivable area into areas with different risk levels; and establishing a multi-objective optimization function in combination with the risk region distribution diagram, fusing the multi-objective optimization function through an exponential weighted fusion mechanism, and generating an optimal navigation path under the risk gradient constraint. Guiding of intelligent navigation of the tea garden is achieved, the tea leaf picking efficiency and quality are improved, and technical support is provided for mechanical and intelligent picking of the tea garden.

The invention relates to the technical field of agricultural management, in particular to a tea garden temperature and humidity regulation and control method based on photovoltaic light supplement. The method comprises the following steps: acquiring temperature and humidity data of a tea garden; obtaining tea tree distribution data, and obtaining a tea tree temperature and humidity environment model according to the tea tree distribution data and the tea garden temperature and humidity data; obtaining photovoltaic parameter data, and performing photovoltaic light supplement simulation according to the photovoltaic parameter data and the tea tree temperature and humidity environment model to obtain tea tree temperature and humidity photovoltaic light supplement data; performing temperature and humidity light supplement coupling relation calculation according to the tea tree temperature and humidity photovoltaic light supplement data to obtain temperature and humidity light supplement coupling relation data; and obtaining tea tree variety data, and performing light supplement effect optimization matching according to the temperature and humidity light supplement coupling relation data and the tea tree variety data to obtain light supplement effect optimization data. The light supplementing intensity and duration can be dynamically adjusted according to environment changes and tea tree growth requirements, and the utilization efficiency and the environment regulation and control effect of a photovoltaic system are improved.

The invention discloses an automatic irrigation control system and method for a tea garden based on photovoltaic power generation, and particularly relates to the technical field of agricultural irrigation, photovoltaic power generation capacity, tea tree growth irrigation cycle and meteorological condition information are collected in real time through multiple types of sensors, and formatting processing is carried out to ensure data availability; information lag degree analysis is carried out based on the processed data, and feedback lag early signs in photovoltaic power generation and tea garden irrigation cooperative control are identified; according to the lag signs, extracting power supply fluctuation, tea tree irrigation demand urgency and climate environment change characteristics, and generating corresponding fluctuation indexes, demand indexes and change indexes; dividing a feedback sampling period into a high-quality period or a low-quality period by using fuzzy logic, and dynamically adjusting the sampling frequency based on the current sampling frequency in the low-quality period; the feedback sampling frequency can be dynamically adjusted, and the stability and the response speed in the cooperative control process of photovoltaic power generation and tea garden automatic irrigation are effectively improved.

The invention discloses a tea picking net covering device and a working method thereof. The tea picking net covering device comprises a winding drum, a winding drum frame and a sunshade net wound around the winding drum. A plurality of bags are symmetrically arranged on the two sides of the sunshade net at equal intervals. A guide rail assembly matched with the bag body is arranged on the winding drum frame. A liquid injection pipe for injecting liquid into the bag body is movably arranged on the winding drum frame; an adsorption part is arranged on the liquid injection pipe, and a butt joint plate matched with the adsorption part is arranged on the side, away from the sunshade net, of the bag body, so that precise liquid injection of the liquid injection pipe to the bag body is achieved after the butt joint plate is matched with the adsorption part; the flushing bag body is arranged on the sunshade net, and water is injected into the bag body during net covering, so that the bag body is vertically hung and fixed through the self weight of the bag body, manual operation is not needed, the net covering efficiency is improved, and meanwhile the initial weight of the sunshade net during winding is reduced; meanwhile, capsule liquid is recycled as an irrigation water source during net drawing, the utilization rate of water resources is increased, transpiration stress of the tea trees is relieved synchronously, and the irrigation effect is improved.

The invention discloses a tea tree germplasm resource garden management method, which adopts a tea tree germplasm resource garden management system consisting of a data storage module, a data processing module, a system operation module, a system display module and an external port module. Through overall plane data and block distribution data of a tea tree germplasm resource garden, meteorological station and soil moisture content information data, basic information data of tea tree germplasm resources entering the garden, germplasm resource agronomic characteristic original data and data processing, agronomic character mean values of vigorous tea tree germplasm resource states in the fourth, fifth and sixth years are converted into standard values; and comparing agronomic character data of the seventh year with a standard value, carrying out fixed-period tea tree data acquisition, and combining a scientific management mode of resource nursery soil and climate factors to realize effective management of dynamic growth of resources of the resource nursery.

The invention belongs to the technical field of microorganisms, and discloses a soil microorganism for promoting the growth of tea trees and improving the quality of tea leaves, the strain name is Streptomyces cerevisiae SI-3B1, the preservation unit is Guangdong Microbial Culture Collection Center, the preservation date is September 13, 2024, and the preservation number is GDMCC No.65129. The invention further discloses a preparation method of the soil microorganism for promoting the growth of the tea trees and improving the quality of the tea leaves. The microorganisms effectively improve the content of theanine and water extract of fresh leaves of one bud and two leaves of large-leaf spring tea, summer tea leaves are thicker, and the biomass of the leaves is increased.

The invention belongs to the technical field of biological medicine, and particularly relates to a luliconazole composition containing essential oil, cream and a preparation method and application of the luliconazole composition. The present application provides a composition containing tea tree essential oil that promotes the skin permeability of luliconazole and has an antibacterial function, the tea tree essential oil and luliconazole form a synergistic antifungal effect, the transdermal absorption is enhanced by a natural terpene component, and the irritation to the skin is significantly reduced.

The invention discloses paenibacillus polymyxa K17 for preventing and treating diseases, the preservation number of the paenibacillus polymyxa K17 is CGMCC (China General Microbiological Culture Collection Center) No.33366, and the paenibacillus polymyxa K17 is classified and named as Paenibacillus polymyxa K17. The strain has a good anti-antagonism effect on 16 different plant pathogenic fungi from 8 crops; particularly, the antibacterial effect on various leaf spot diseases of tea trees is superior to that of part of common biocontrol strains such as Pristeria aryabhattai 11, Bacillus tequilensis R2 and the like. The control effect on tea tree leaf spot and tea tree anthracnose is higher than 70%, the control effect on black spot of picked tomatoes is 68%, the control effect is equivalent to that of various chemical pesticides, and the method has extremely high application prospects and market value in field biological control and postharvest preservation of plant diseases. Meanwhile, the strain K17 has the plant growth-promoting characteristics of secreting multiple extracellular hydrolases, dissolving inorganic phosphorus and mineral potassium and biologically fixing nitrogen, and has the potential of preparing plant growth-promoting microbial agents or bacterial fertilizers.

The invention discloses an application of a 2-cyano-3-amino acrylate compound in prevention and treatment of fungal diseases caused by pestalotiopsis, and the compound has general ultrahigh bacteriostatic activity on pestalotiopsis fungi in vitro, including pestalotiopsis, pestalotiopsis neospecies and pestalotiopsis pseudospecies. Wherein the effective medium concentration (EC50) range of the phenamacril to 56 pestalotiopsis-like pathogenic bacteria picked from tea trees, peach trees and grapes is 0.1455-0.6025 [mu] g / mL, the average value is 0.2800 [mu] g / mL, and the standard deviation is 0.095 [mu] g / mL. According to the scheme of spraying the JS399-19 suspending agent to treat the tea trees, the tea yield can be remarkably increased, and a basis is provided for preventing and treating diseases caused by pestalotiopsis, new pestalotiopsis and pseudopestalotiopsis in a tea garden and monitoring drug resistance.

The invention discloses a tea leaf trimmer with a telescopic adjusting mechanism and a trimming process thereof, and the tea leaf trimmer comprises a holding part for an operator to hold and control; the driving unit is used for driving the pruning machine to perform pruning operation; the pruning cutter is in transmission connection with the driving unit and is used for pruning branches and leaves of the tea leaves; the holding part comprises a frame body, and a supporting plate for supporting a trimmed tea tree is arranged on the frame body; the supporting plate is provided with a plurality of walking units capable of being transversely adjusted in a telescopic mode. The walking unit is in transmission connection with the driving unit, and the trimmer climbs on the surface of a trimmed tea tree after being driven; according to the tea trimmer with the telescopic adjusting mechanism, the traveling unit is arranged on the trimmer, so that the trimmer can crawl on the surface of a trimmed tea tree when the trimmer needs to trim, and manual labor is saved.

The invention discloses a smart tea garden planting management system and method. The smart tea garden planting management system comprises a multi-source sensor network, an edge computing gateway, an AI decision unit and a control execution unit. The soil fertility and pest and disease damage are monitored in real time through a high-precision sensor, and precise recognition of disease spots and pests is achieved in combination with a YOLOv5 algorithm; the AI decision-making unit dynamically generates variable fertilization and graded prevention and control instructions according to the growth stages of the tea trees, and controls the water and fertilizer integrated device and the biological prevention and control equipment to execute operation. The system supports adaptation of multiple tea types, compatibility of new and old facilities and stable operation in an extreme environment, the fertilizer utilization rate is remarkably increased, the pesticide usage amount is reduced, and the system is suitable for intelligent and standardized management of large-scale tea gardens.

The invention discloses a tea tree pest degree prediction method based on an electronic nose technology, and is applied to the technical field of pest detection. Comprising the following steps: pretreating a plurality of tea trees to enable the tea trees to have different types of insect pests; an electronic nose is used for detecting volatile gas of all tea trees within a certain period of time after the tea trees are subjected to insect damage, a response curve is obtained, and tea tree insect damage feature data are extracted; constructing and training a tea tree pest classifier; constructing a pest degree prediction network for each type of pest and training the pest degree prediction network based on the tea tree pest feature data and the corresponding pest degree; and collecting insect pest feature data of a to-be-detected tea tree through an electronic nose, inputting the to-be-detected insect pest feature data into the tea tree insect pest classifier to obtain a classification result, and inputting the classification result into the corresponding insect pest degree prediction network to obtain an insect pest degree prediction result. The method can quickly identify insect pest types and predict insect pest degrees, and provides reference for insect pest control of tea trees.