673 results about "Disease control" patented technology

The invention discloses a forest prevention and control method based on disease and pest monitoring, and belongs to the technical field of forestry prevention and control, and the method comprises the steps: dividing a target forest into regions according to vegetation types, collecting historical multi-source data, filling the missing data, analyzing a time sequence and causal relationship to construct a time sequence causal diagram, and simulating a disease and pest spatio-temporal dynamic state in combination with current data. And determining a prevention and control risk level and a key induction factor of each region, executing a prevention and control strategy according to the level, and updating a causal diagram through reinforcement learning according to forest health response data. According to the method, a closed loop is formed from data processing to model construction, accurate prevention and control are achieved, efficiency and scientificity are improved, forest ecological changes can be dynamically optimized and adapted, and the prevention and control effect is guaranteed.

The invention relates to the technical field of biological control, in particular to bacillus velezensis JNJK-1, a microbial agent and application of the bacillus velezensis JNJK-1 and the microbial agent in edible fungus disease control, the bacillus velezensis JNJK-1 is preserved in China General Microbiological Culture Collection Center (CGMCC), and the preservation number is CMCC No.31075. The novel bacillus velezensis JNJK-1 is screened out for the first time, and the bacillus velezensis can be applied to biological control of edible mushroom diseases and has a broad-spectrum inhibition effect on pathogenic bacteria of edible mushrooms. Meanwhile, the inventor also finds that the bacillus velezensis JNJK-1, curcumin and sodium alginate are compounded into the microbial agent, so that the inhibition effect on the pathogenic bacteria of the edible fungi can be improved, and the microbial activity can be maintained.

The invention belongs to the technical field of crop disease and insect pest control, and particularly relates to an agricultural disease and insect pest control method fusing computer vision and a language model. Based on a vision model and an optimized language model, after the vision model and the optimized language model are integrated, dynamic scene information can be combined; the method can identify various crop diseases in real time and give more professional and detailed suggestions in the field of crop disease control, has good disease identification ability and control suggestion generation ability, further significantly improves the efficiency of disease control in agricultural production, reduces the labor cost, and is beneficial to improving the yield and quality of crops.

The invention discloses a citrullinated SAA polypeptide and application thereof in preparation of a rheumatoid arthritis diagnosis product, the amino acid sequence of the citrullinated SAA polypeptide is DKYFHA-Cit-GNYDAAK-Cit-GPGGA, through the polypeptide, the citrullinated autoantigen B cell epitope of SAA and a corresponding autoantibody, namely an anti-citrullinated SAA polypeptide antibody (anti-CAP), are identified. The expression level of anti-CAP in RA patients is obviously higher than that of other disease control groups and healthy groups, and the anti-CAP has better positive rate in early RA, ESR / CRP normal RA and anti-CCP antibody / RF negative RA, and provides a new strategy for diagnosis of RA.

The invention relates to the technical field of tomato disease control, in particular to a method for detecting tomato root rot based on volatilization group information. The method comprises the four steps of volatile gas collection, data analysis, intelligent diagnosis and result display, and cloud database and model updating is assisted. The method comprises the following steps: firstly, obtaining tomato root volatile compounds through high-sensitivity sampling equipment, and analyzing volatile components by utilizing a GC-IMS technology to obtain lt; component, concentration gt; the method comprises the following steps: extracting data, generating a feature vector, combining generation and verification of an auditing identifier to ensure the compliance and integrity of the extracted data, accurately judging a disease grade based on a classification model, combining a health score and a classification result, providing prevention and treatment suggestions, and presenting a diagnosis result in a visual mode; and the cloud database continuously accumulates historical data, optimizes the classification model, and improves the system adaptability and the detection effect. According to the invention, early-stage accurate diagnosis and intelligent management of tomato root rot are realized, and the agricultural disease detection efficiency is improved.

The invention discloses a pest control management system and method for forest tree breeding, and relates to the technical field of forest tree breeding and seedling raising, and the method comprises the following steps: collecting environment data and soil rhizosphere data by collecting multi-mode images of leaves and trunks of a pinus massoniana young forest and videos that pinus massoniana caterpillars gnaw leaves and cluster diffusion; constructing a disease and insect pest recognition model by using a convolutional neural network, performing definite diagnosis on pine wood nematode disease, pine caterpillars and monochamus alternatus hope, and quantifying the disease and insect pest occurrence area and population density of each sub-region; calculating a pine wood nematode disease control demand index, comparing the pine wood nematode disease control demand index with a threshold value, and triggering a corresponding control strategy; the diffusion coefficient of the pine caterpillars is calculated and compared with a risk threshold value, and a prevention and control scheme is formulated; calculating the propagation coefficient of the monochamus alternatus hope, judging the propagation risk and giving a prevention and control strategy; according to the invention, intelligent pest identification, risk quantification and control strategy closed-loop control are realized, treatment and scientific prevention and control are facilitated, and the pest control efficiency of the pinus massoniana young forest and the forest stand health level are improved.

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 relates to a tartary buckwheat pest and disease damage dynamic monitoring method, system and device and a medium, and belongs to the technical field of agricultural intelligent monitoring, the dynamic monitoring method comprises the following steps: periodically collecting environmental parameter data through fixed sensor nodes deployed in a farmland, and obtaining leaf vibration signals and multispectral image data at the same time; performing space-time alignment on the blade vibration signal and the multispectral image data, correcting radiation distortion in the multispectral image data, and outputting a registration data set; according to the registration data set, fusing to generate a multi-modal feature vector, inputting the multi-modal feature vector into a pre-trained space-time analysis model, and outputting a risk level distribution diagram with a geographic coordinate mark; generating a control instruction set according to the risk level distribution map, and triggering execution equipment to execute pest control operation; and optimizing weight parameters of the space-time analysis model through the generative adversarial network based on the execution log of the control instruction set and the historical multi-modal feature vector. The scientificity and timeliness of pest control can be improved.

The invention relates to the technical field of pest control, in particular to a pest outbreak process mining risk prediction method and system based on multi-source factors. The method comprises the following steps: measuring regional meteorological data, regional crop soil fertility degree and regional disease and pest occurrence data corresponding to crop disease and pest monitoring points in real time; the corresponding pesticide spraying usage amount is obtained through the crop disease and insect pest monitoring points, and regional occurrence density accounting and disease and insect pest outbreak mining analysis are carried out on regional disease and insect pest occurrence data based on the pesticide spraying usage amount. Obtaining a corresponding regional pest and disease outbreak characteristic mode under the meteorological condition and a correlation characteristic relation between regional soil fertility and pest and disease outbreak; and performing multi-source factor risk prediction and control decision support analysis on the crop disease and pest monitoring points to generate a disease and pest outbreak area control suggestion scheme. According to the invention, scientific and accurate disease and pest risk early warning can be provided for agricultural production.

The present invention relates to the field of computer vision, specifically a method and system for real-time identification and control of crop pests and diseases based on multimodal edge computing. The system comprises: acquiring drone multispectral imagery, infrared thermal imaging, and the NDVI index, preprocessing them in combination with field IoT sensor data to generate a multimodal feature input sequence; constructing a spectral-environmental fusion feature matrix based on the Transformer attention mechanism, and utilizing the YOLOv7-Spectral model for pest and disease detection to generate a pest and disease distribution heat map; calculating the pest risk index (BRI) and pesticide application priority map based on historical data; employing an ant colony optimization algorithm to plan drone application paths and optimizing the application plan based on wind speed and humidity parameters; accurately applying pesticides along the optimized paths by the drones and monitoring disease trends; adjusting the model based on application feedback data, and optimizing pest and disease control strategies using federated learning. The present invention improves recognition accuracy, reduces pesticide use, and achieves precise, efficient, and intelligent control.

The invention relates to a mulberry disease and insect pest monitoring system and method based on Internet of Things image processing, and the method comprises the steps: obtaining mulberry disease and insect pest image data, carrying out the preprocessing and marking, creating a disease and insect pest analysis model, and training; evaluating the performance of the trained pest and disease analysis model; a first image acquisition module performs preliminary image acquisition on a to-be-monitored mulberry planting area and transmits the image to a disease and pest analysis model for preliminary disease and pest condition identification and analysis, and each disease and pest area is positioned; expanding the disease and insect pest areas, and performing infrared image acquisition on the expanded disease and insect pest areas by a second image acquisition module; identifying and analyzing pest and disease damage conditions of the expanded pest and disease damage areas; and the pest and disease drawing module draws a pest and disease region of the mulberry planting region to be monitored based on the output analysis result, renders the severity of pest and disease, and executes pest and disease control measures. Omnibearing pest and disease monitoring of mulberries is realized, and the accuracy of pest and disease recognition and analysis results is improved.

The invention discloses application of fungus fermentation liquor to prevention and treatment of areca leaf spot disease. The invention relates to the technical field of agricultural biology, and provides application of fungus fermentation liquor in prevention and treatment of areca leaf spot disease. The fungus fermentation liquor is filtrate obtained by performing fermentation culture on specific fungi and filtering a culture solution to remove thalli; the specific fungus is phomopsis of RdRp protein from the PaFV1 virus through overexpression. The fungus fermentation liquor provided by the invention is sprayed on areca leaves, so that the occurrence of areca leaf spot disease can be obviously reduced, and good disease control potential is shown. The invention has important significance for preventing and treating areca leaf spot disease.

The invention relates to the technical field of pepper planting, and discloses a pepper planting method for improving pepper quality, which comprises the following steps: soil and matrix treatment, seed treatment and sowing, field management and regulation, fertilization strategy, pest control and ecological balance, and plant pruning and fruit optimization. According to the pepper planting method, through the synergistic effect of all links, the pepper planting effect and quality are comprehensively improved from soil improvement to seed treatment, from field management to pest and disease control and then to plant pruning and fruit optimization. Compared with a traditional planting method, the quality indexes such as vitamin C content and capsaicin content of the chilies planted through the method are remarkably improved, the growth cycle is shortened, the yield is increased, meanwhile, use of chemical pesticides is reduced, and the method is environmentally friendly, has remarkable economic, social and ecological benefits and is worthy of popularization and application. Powerful support and guarantee are provided for sustainable development of the pepper planting industry.

The invention discloses a forestry new technology intelligent disease and pest prevention and control system and method, and relates to the technical field of disease and pest prevention and control, and the system comprises a data collection module which collects the real-time data of diseases and pests in a forest; the pest and disease damage identification and analysis module is used for analyzing the collected real-time data, carrying out pest and disease damage identification by utilizing an artificial intelligence algorithm and calculating the threat level of the pest and disease damage; the pest and disease early warning module sends out pest and disease early warning signals and provides prevention and control suggestions according to recognition and calculation results; the prevention and control measure recommendation module intelligently recommends prevention and control measures according to the early warning result and the specific disease and pest species; and the execution module is used for performing automatic prevention and control operation through intelligent equipment according to the recommended prevention and control measures. Dynamic monitoring of diseases and insect pests is provided, the recognition module based on deep learning automatically analyzes data, the diseases and insect pests are accurately recognized, threat levels are evaluated, personalized prevention and control measures are recommended, the prevention and control efficiency is effectively improved, and the ecological environment is protected.

The invention discloses a hyperspectral oblique photography method based on an unmanned aerial vehicle and a ground agricultural machine, and the method employs the unmanned aerial vehicle to obtain the air data of a farmland, employs the agricultural machine to continuously obtain the ground data in real time, obtains the data in the operation process of the agricultural machine, and does not need to invest extra time and manpower. The advantages of an air platform and a ground platform are fused in an air-ground cooperation mode, high-precision, high-spectral-resolution and multi-angle comprehensive acquisition of remote sensing data of a farm is achieved, the spatial and spectral resolution of the data is improved, the requirement of precision agriculture for the data is met, air oblique photography is used, and the precision agriculture is improved. And multi-view information of the farmland is obtained to establish a high-precision farmland three-dimensional model. The method can solve the problems of insufficient data acquisition precision and timeliness in the prior art, remarkably improves the remote sensing data acquisition precision in agricultural production, and is widely applied to the fields of crop health monitoring, pest control, soil management and the like.

The invention relates to the field of biopesticide and microbial fertilizer, in particular to bacillus subtilis wettable powder and a preparation method thereof. The bacillus subtilis wettable powder is prepared from the following preparation raw materials in parts by mass: 40 to 45 parts of bacillus subtilis fermentation liquor, 25 to 28 parts of a bio-based carrier, 0.5 to 0.7 part of sodium carboxymethyl cellulose, 1 to 1.2 parts of amino-oligosaccharin, 3 to 5 parts of a composite surfactant, 0.8 to 1.2 parts of a spore germination agent, 1.5 to 2 parts of a protective agent, 0.2 to 0.3 part of an anti-freezing agent and 0.2 to 0.3 part of a synergist. After the bacillus subtilis wettable powder is applied to a paddy field, the spore germination speed is high, the germination rate is high, the bacillus subtilis wettable powder is free of toxic effects on people and livestock and convenient to use, the fertilizer efficiency and the rice disease control effect of the bacillus subtilis wettable powder can be obviously improved, the dosage of spores is reduced, and the cost is reduced. The adhesiveness and conductivity of the bacillus subtilis wettable powder on rice can be improved through the composite surfactant, so that the bacillus subtilis wettable powder can be better attached to leaf surfaces and stem surfaces of the rice, and the control effect of the bacillus subtilis wettable powder on the neck blast of the rice is improved.

The invention belongs to the technical field of biological prevention and control of plant diseases, and provides bacillus subtilis and application thereof in prevention and control of corn diseases. The preservation number of the bacillus subtilis SEB-34 is CGMCC (China General Microbiological Culture Collection Center) No. 26419. The invention also provides a microbial agent produced by using the SEB-34 strain, and the microbial agent can be used for preventing and treating plant diseases caused by fusarium graminearum or pelamys maydis. The bacillus subtilis provided by the invention is applied through seed treatment before sowing or root drip irrigation after seedling emergence, has the effects of preventing diseases, promoting growth and increasing yield, and can effectively reduce the occurrence of corn southern leaf blight and basal stem rot. The microbial agent provided by the invention is in a semi-dormant state, has relatively strong stress resistance, is more stable to store, ensures the effect, and effectively reduces the production and transportation cost at the same time. The invention also provides beneficial microbial resources for green prevention and control of corn diseases, and has good application prospect and high application value.

The invention relates to the technical field of disease prevention and control, in particular to a dengue epidemic situation intelligent prediction and early warning system based on multi-source monitoring data, comprising a prediction and early warning system for monitoring, predicting and early warning the dengue epidemic situation, the prediction and early warning system comprising: a data acquisition module for collecting multi-source monitoring data related to the dengue epidemic situation; the data processing module is used for cleaning, integrating and standardizing the collected original data to form a data set which can be used for analysis and prediction; the information early warning module is used for carrying out deep analysis on the processed data by utilizing a big data analysis technology and an intelligent algorithm, establishing a prediction model and predicting the epidemic trend and risk of the dengue epidemic situation; according to the system, through multi-region mosquito-borne monitoring points and integration of data in multiple fields of hospitals, disease control centers, meteorology, telecom operators, social media platforms and the like, a big data analysis technology and an intelligent algorithm are applied, and the dengue epidemic situation prediction accuracy is greatly improved.

The invention belongs to the technical field of microorganisms, and discloses streptomycete Y309 and application thereof. The preservation number of the streptomyces sp. Y309 is GDMCC No: 64527, and the streptomyces sp. Y309 has relatively strong secondary metabolite synthesis capability and can be used for producing siderophore, IAA (Indoleacetic Acid) and the like. The strain Y309 also has the potential of plant growth promotion and disease control, and the strain Y309 has a relatively strong bacteriostatic effect on 12 pathogenic fungi such as fusarium oxysporum, rhizoctonia cerealis, monilinia fusarium and coracocystis fimbristipula as well as 7 pathogenic bacteria such as pseudomonas syringae lacrimation pathogenic variants and bacillus cereus, and has a relatively strong bacteriostatic effect on 12 pathogenic fungi such as fusarium oxysporum, rhizoctonia cerealis, monilinia fusarium and coracocystis fimbristipula. The strain Y309 has good prevention and treatment effects on wheat sharp eyespot, tomato gray mold and pepper fusarium wilt, fermentation liquor of the strain Y309 can remarkably promote wheat seed germination and seedling growth, agronomic characters such as the plant height, the dry weight and the leaf area in the corn seedling stage can be improved in different saline-alkali soil, and the strain Y309 has good application prospects.

The invention belongs to the technical field of disease control, and discloses a bactericide for controlling radix bupleuri root rot, which is prepared from the following components: 10%-20% of a vesicle-arbuscular mycorrhizal agent, 30%-50% of carbendazim, 15%-25% of JS399-19, 10%-20% of phenazino-1-carboxylic acid, 10%-20% of bacillus subtilis, 3%-7% of a surfactant, 3%-7% of a stabilizer and the balance of a carrier, the dispersing agent is used for diluting and dispersing the active ingredients. By scientifically proportioning various efficient active components such as the vesicle-arbuscular mycorrhizal agent, the carbendazim, the phenamacril, the phenazino-1-carboxylic acid and the bacillus subtilis, a set of multi-target and multi-layer disease prevention and control system is formed, pathogenic bacteria of radix bupleuri root rot are accurately struck, growth and reproduction of radix bupleuri root rot are effectively inhibited, and the disease incidence rate is greatly reduced. Compared with a traditional medicament, the bactericide not only has a remarkable control effect, but also is safe and friendly to human bodies, animals and the environment, the use frequency and the total amount of the medicament are reduced, the requirements of consumers on green agricultural products are met, and occurrence and spreading of radix bupleuri root rot are controlled.

The invention provides a drug target protein MoFrd1 and application of the drug target protein MoFrd1 in agricultural disease control. The amino acid sequence of the MoFrd1 is as shown in SEQ ID No. 1, and the nucleotide sequence of the coding gene of the MoFrd1 is as shown in SEQ ID No. 4. Researches show that the pathogenicity of the magnaporthe oryzae can be remarkably reduced by knocking out the MoFrd1 coding gene. Homologous protein of MoFrd1 widely exists in plant pathogenic fungi and shows high conservative property in pathogenic mechanisms, however, homologous protein is not found in plants and mammals, and it is indicated that the homologous protein of MoFrd1 has the potential of serving as a specific drug target of pathogenic bacteria. Based on a key structural domain and a functional site of the MoFrd1 protein, a specific agent for preventing and treating plant fungal pathogens is expected to be developed through design or screening. The invention provides a new drug target and a control strategy for controlling fungal diseases of crops, and has important application value and market potential.

The invention relates to the field of disease control, and discloses a semantic segmentation and grading method for cross-scale identification of rice black dwarf disease and lodging, and the method comprises the following steps: S1, collecting rice field data under different elevation scales, and processing the data through software to obtain image data; s2, based on the altitude information of the DSM, determining a classification threshold by combining elevation error correction and height distribution difference statistical analysis, and constructing a DSM-guided auxiliary supervision mask; s3, constructing a cross-scale semantic fusion network, and inputting the image data set in S1 and the auxiliary supervision mask in S2 into the network for training to obtain a rice black dwarf disease and lodging detection model; and S4, predicting by using the rice black dwarf disease and lodging detection model in the S3. By constructing a digital surface model and a digital orthoimage with aligned pixels and combining elevation error correction, accurate association of rice field data under multiple elevation scales can be realized, and support is provided for rice black dwarf disease and lodging identification.

The invention discloses a rice disease and insect pest monitoring method and system, and relates to the technical field of disease and insect pest monitoring, and the method comprises the steps: firstly testing the resistance of different rice varieties to different disease and insect pests, then selecting an optimal rice planting variety for a planting field, and according to the disease and insect pest conditions of the planting field, determining the disease and insect pest conditions of the planting field; according to the method, a variety with relatively high resistance is selected for planting, damage of diseases and insect pests during later growth is reduced, and meanwhile, the cost of monitoring the diseases and insect pests is reduced, so that the cost of rice planting is reduced, a basis is provided for subsequent high-yield and high-quality planting of rice, and during rice planting, an image of each single rice plant is monitored, and a three-dimensional model is constructed; the defense effect of each part in each single rice plant is obtained, then abnormal parts and abnormal pest and disease damage types in the rice are confirmed, reference is provided for subsequent pest and disease damage treatment, the treatment position is accurately positioned, and the pest and disease damage monitoring and treatment effects are improved.

The invention relates to the technical field of facility agriculture, in particular to a green cultivation method for greenhouse water culture of Chinese chives. Through integration of intelligent greenhouse facilities, staged nutrient solution regulation and control, physical-biological-chemical synergistic disease and insect pest prevention and control and an annual production management technology, the problems of continuous cropping obstacles, high pesticide residues, winter dormancy and the like existing in traditional soil culture of Chinese chives are solved. According to the method, annual production of Chinese chives is achieved, the harvesting period of each crop is shortened to 20-30 days, compared with traditional soil culture, the annual yield is increased by 40% or above, the pesticide use amount is reduced by 95%, the pesticide residue percent of pass is 100%, and the product is free of heavy metal pollution, meets the green food standard and is suitable for green transformation and popularization of facility agriculture.

According to the nano pesticide and the preparation method and application thereof, pH response type nano particles ZIF-90 serve as a carrier, azoxystrobin is loaded to serve as a medicine, and the nano pesticide is used for preventing and treating rice sheath blight disease caused by rhizoctonia solani. When the rhizoctonia solani infects rice, oxalic acid can be generated to reduce the pH around an infected area, so that the ZIF-90 carrier skeleton and the hyaluronic acid coating are decomposed to release azoxystrobin, and the rhizoctonia solani is inhibited in a targeted manner. It is further found that ZIF-90 and azoxystrobin have synergistic bacteriostatic activity, the EC50 value of azoxystrobin to rhizoctonia solani can be greatly reduced, after ZIF-90 carrier encapsulation and hyaluronic acid end capping, the photolysis stability of azoxystrobin can be improved, the adhesive force of azoxystrobin on rice leaves can be enhanced, and the ZIF-90 and azoxystrobin compound has important application in agricultural disease control.

The invention relates to the technical field of pest and disease control, in particular to a forestry pest and disease control branch whitewash smearing device which comprises a bottom frame, a driving mechanism, a spraying mechanism used for spraying whitewash to a tree trunk in a reciprocating mode and a smearing mechanism used for evenly smearing the whitewash to the tree trunk. The bottom end of the driving mechanism is fixedly connected with the top face of the bottom frame, the spraying mechanism is fixedly connected to one side of the driving mechanism, and the spraying mechanism comprises an arc-shaped plate. According to the device, the chassis is moved to the trunk, the trunk part enters the spraying mechanism, then the driving mechanism is started to drive the spraying mechanism to rotate in a reciprocating mode, the spraying mechanism rotates around the trunk in a reciprocating mode, and therefore lime water is evenly sprayed to the trunk; and meanwhile, the spraying mechanism drives the two smearing mechanisms to smear the whitewash sprayed to the tree trunk, so that a user can use the whitewash conveniently, and the whitewash on the tree trunk is distributed more uniformly.

The invention discloses a drug screening method based on endotoxin attack, and relates to the technical field of drug screening, in the process of drug screening by using an experimental animal, firstly, an experimental animal model with diseases is established, a certain dose of endotoxin is given to the experimental animal for a period of time after the model is successfully built, and then the experimental animal is subjected to drug screening. And establishing evaluation indexes by utilizing a mathematical formula, and comprehensively evaluating the effectiveness and the safety of the medicine. The evaluation indexes comprise an endotoxin attack survival rate, a survival disease control rate and a survival disease control index. The method can be applied to screening of drugs for treating different diseases, and a more scientific and reliable screening method is provided for research of preclinical drugs or treatment methods.

The invention relates to the technical field of paris polyphylla plant disease and insect pest data processing, and discloses a paris polyphylla planting plant disease and insect pest control scheme data analysis system and method. According to paris polyphylla plant growth image shelter type identification information, an intelligent search algorithm and standard preset paris polyphylla plant growth image shelter removal algorithm type information are combined to carry out shelter feature removal algorithm type accurate analysis in a paris polyphylla plant growth image; scientific matching of image shelter removal algorithm objects based on shelter interference feature types in paris polyphylla disease and insect pest monitoring images is realized, and the quality of paris polyphylla disease and insect pest monitoring image acquisition is improved; the method can autonomously and efficiently remove interference features of plant surface attached shelters in the paris polyphylla plant growth image, realizes efficient and accurate processing of the interference features of the shelters in the paris polyphylla plant growth image, improves the authenticity of paris polyphylla plant disease and insect pest monitoring image acquisition, and improves the paris polyphylla planting disease and insect pest control effect.

The invention discloses an intelligent tea inquiry method, device and system based on a big language model and a storage medium, and the method comprises the steps: taking tea professional domain knowledge as a basis, and constructing a tea domain knowledge corpus in a manner of combining a general big language model and artificial semi-supervision; a corpus is utilized, and a low-rank matrix is adopted for fine tuning training of an intelligent inquiry big language model ChatTea in the tea field; constructing an intelligent tea interrogation platform, quantifying ChatTea through a quantification technology, and deploying the ChatTea on the intelligent tea interrogation platform; and inputting the inquiry information of the tea intelligent inquiry platform user into the ChatTea model to obtain accurate answers of related problems such as tea planting, processing, pest control and the like. By means of the method, the tea garden management problem, the tea plant disease and insect pest problem, the planting problem and the like in the tea planting production process can be accurately judged, scientific and professional solutions are provided for different problems, tea farmers are helped to take effective measures in time, losses are avoided, and the yield and quality of tea are guaranteed.

Bacteriophages that comprise a tail fiber protein sequence comprising a C terminus host recognition site described by SEQ ID NO: 1 and which infect Ralstonia solanacearum which causes bacterial wilt disease are disclosed. Compositions comprising these bacteriophages may be employed as wilt control agents. Methods for preventing or treating diseases caused by Ralstonia solanacearum such as bacterial wilt disease are also disclosed. A bacterial wilt disease control method in a plant may include administering such bacteriophages to a plant or to a plant growth medium and can be effective against a wide variety of Ralstonia solanacearum strains. Nucleic acids encoding the C terminus host recognition site and amino acid sequences comprising the host recognition site are also disclosed.