569 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 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 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 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 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 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 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.

The invention discloses application of allose in preparation of a medicine for treating Alzheimer's disease, and relates to the technical field of biological medicine. An experiment is carried out on a fruit fly model with the Alzheimer's disease, and the allose shows that the movement function of the fruit fly with the Alzheimer's disease can be effectively improved, the service life of the fruit fly with the Alzheimer's disease is effectively prolonged, and death of brain neurons of the fruit fly with the Alzheimer's disease is reduced; therefore, the allose is proved to have a positive effect on disease control of patients with neurodegenerative diseases, and has important application potential.

The invention discloses a forestry intelligent pest control system based on multi-sensor cooperation, and relates to the technical field of intelligent pest control. In order to solve the problems of low diagnosis precision and poor cooperation efficiency in the prior art, the invention provides a hypothesis-verification cooperation strategy: a system firstly generates a preliminary diagnosis hypothesis by using macroscopic sensor data, and adaptively regulates and controls a microscopic sensor according to the preliminary diagnosis hypothesis to carry out targeted verification so as to realize high-confidence diagnosis; the system further establishes a disease and insect pest spatio-temporal diffusion risk map for trend prediction, and formulates graded and partitioned precise prevention and control strategies. According to the invention, through prevention and treatment effect evaluation and closed-loop self-optimization learning of the model, intelligent prevention and treatment from passive response to active prediction are realized, and the diagnosis accuracy and the resource utilization efficiency are remarkably improved.

The invention relates to the technical field of agricultural disease prevention and control, and discloses a rice damping-off prevention and control system based on soil ecology regulation and control, comprising the following modules: a soil ecology monitoring module used for acquiring physical properties, chemical properties and microflora related data of paddy field soil in real time; and the data transmission and storage module is connected with the soil ecology monitoring module and is used for transmitting the data acquired by the soil ecology monitoring module to a storage end and storing the data. The rice damping-off prevention and control system based on soil ecology regulation and control can comprehensively and accurately obtain soil ecology data in real time, guarantee stable, safe transmission and proper storage of the data, accurately judge the rice damping-off occurrence risk and perform early warning in time, and effectively prevent and control rice damping-off. The problem that the paddy field soil ecology cannot be accurately monitored, analyzed, regulated and controlled in multiple dimensions is solved.

The invention relates to a ralstonia solanacearum bacteriophage LC10 capable of preventing and controlling tobacco bacterial wilt, the classification name of the ralstonia solanacearum bacteriophage LC10 is Rastonia phage, the preservation number of the ralstonia solanacearum bacteriophage LC10 is GDMCC No: 66716-B1, and the preservation date of the ralstonia solanacearum bacteriophage LC10 is July 21, 2025. The bacteriophage is a brachytail bacteriophage and can specifically split ralstonia solanacearum, inhibit the growth of the ralstonia solanacearum and enhance the disease inhibition capability of soil. Therefore, the bacteriophage LC10 can be used for preparing related preparations for preventing and controlling tobacco bacterial wilt.

The invention discloses an organic ecological planting method for apples, and particularly relates to the field of fruit tree cultivation, and the method comprises the following specific planting steps: S1, soil foundation improvement; s2, annual fertilizer management; s3, flower and fruit management; s4, ecological prevention and control of diseases and pests; and S5, harvesting management. According to the method, through soil foundation improvement, annual fertilizer management, flower and fruit management, ecological pest control and harvesting management, no chemical fertilizer or pesticide is input, five purposes are achieved, and meanwhile it is guaranteed that soil is healthy, tree bodies are robust and fruits are high in quality; according to the method, microbial agents and bio-organic fertilizers are mainly adopted to replace chemical fertilizers, biological prevention and control are adopted to replace chemical pesticides, precise farming operation is combined, apple planting achieves zero pesticide residue, high quality and high yield, the method is suitable for high-end organic ecological apple production, the purposes of high yield, high quality, safety and high efficiency of apple planting are achieved, and the method has wide application and popularization prospects.

The invention relates to a large-scale high-yield and high-efficiency cultivation mode of pumpkins in saline-alkali soil, which adopts a composite modifier to improve the saline-alkali soil, and the composite modifier contains an organic fertilizer, a soil conditioner and a saline-alkali tolerant microbial strain in a specific proportion, so that the soil structure and fertility are effectively improved; a pumpkin variety with a salt-tolerant gene marker is selected, and the salt tolerance and the survival rate of seedlings are remarkably improved by combining a biochar seedling raising technology; through an intelligent drip irrigation system and a precise fertilization technology, the irrigation and fertilization amount is dynamically adjusted according to the growth stage of pumpkins and soil fertility, and the resource utilization efficiency is improved; a disease and pest control method combining physical and biological control is adopted, meanwhile, an S-shaped vine pressing method is combined to promote plant growth, and product quality tracing is achieved through a block chain technology. The problem of pumpkin planting in the saline-alkali soil is effectively solved, the yield and quality of pumpkins are remarkably improved, remarkable economic benefits and ecological benefits are achieved, and a new thought and method are provided for agricultural development of the saline-alkali soil.

The invention discloses bacillus, a fungicide and application of the fungicide in disease control and plant growth promotion, and relates to the technical field of biocontrol bacteria. The preservation number of the bacillus is CGMCC (China General Microbiological Culture Collection Center) No.3265. The bacillus RD22S2 strain of bacillus is separated and screened from rhizosphere soil of eucommia ulmoides, and experiments prove that the bacillus RD22S2 strain can effectively prevent and control gray mold of eucommia ulmoides leaves and has broad-spectrum fungal disease resistance and growth promoting functions. Therefore, the bacillus provided by the invention not only can be used for preventing and treating plant diseases caused by fungi, but also can be used for promoting the growth of various plants and improving the yield and quality of the plants. Good application prospects of preventing and treating plant diseases and promoting plant growth are realized.

The invention relates to the technical field of crop cultivation, and discloses a matched cultivation method for strong gluten wheat seed production and application thereof.The method comprises the steps that soil improvement before sowing is conducted, specifically, deep ploughing, organic fertilizer and compound fertilizer application and medium trace element supplement are conducted; then optimizing fertilization management, and applying a potassium fertilizer by nitrogen and sulfur combined application, adjusting a nitrogen fertilizer application strategy and applying the potassium fertilizer by stages; then an optimized sowing technology is implemented; then, precise irrigation and moisture regulation are conducted, the irrigation opportunity and times are optimized, and moderate deficiency of the soil is kept in a specific period; and finally, carrying out comprehensive pest control in parallel or in corresponding stages in the whole growth cycle. By integrating key measures such as soil improvement, scientific fertilization, fine seed close planting, precise irrigation and comprehensive plant protection, a set of synergetic and efficient strong gluten wheat seed production technology system is established, the seed yield and quality are remarkably improved, and the problems of unstable quality, low nutrient utilization rate, water resource waste, insufficient pest control and the like are solved.

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 relates to the technical field of prevention and treatment of plant diseases, in particular to application of a biocontrol strain hzq1601 to prevention and treatment of rice bacterial blight. The biocontrol strain hzq1601 is a bacterial strain hzq1601 of bacillus amyloliquefaciens, the preservation number of the bacterial strain hzq1601 is GDMCC (China General Microbiological Culture Collection Center) NO: 60355, and the biocontrol strain hzq1601 is a bacterial strain hzq1601 of bacillus amyloliquefaciens with the preservation number of GDMCC NO: 60355. The invention further provides a method for preventing and treating the rice bacterial blight, in the rice seedling stage, the biocontrol strain hzq1601 bacterial liquid is sprayed to leaves, so that the morbidity of the rice bacterial blight is remarkably reduced to 1% or below, and losses caused by the bacterial blight are reduced; the bacterial liquid of the biocontrol strain hzq1601 is sprayed to the surface of soil in the tillering stage or booting stage, and the bacterial leaf blight prevention effect and the disease index prevention effect of the biocontrol strain hzq1601 are obviously higher than those of other treatments under the condition that the dosage of the bacterial liquid for seedling treatment is small. The action path of the bacillus amyloliquefaciens is direct and efficient, especially, the strong control effect can be achieved through low-dose spraying in the seedling stage, cost and operation difficulty are reduced, a stable pesticide application window and strategy are formed, and wide popularization prospects are achieved.

The invention discloses a bacillus thuringiensis CMS-BT17, which is classified and named as bacillus thuringiensis, is preserved in the China General Microbiological Culture Collection Center (CGMCC), has the preservation number of CGMCC 35313, and is preserved on July 21, 2025. The bacillus thuringiensis strain CMS-BT17 directly separated and screened from a zizania aquatica soil sample in Haikou City of Hainan carries four insecticidal protein coding genes of Cry8Ca, Cry8Da, Spp1Aa and Vpb4Ca, not only is high in insecticidal toxicity and good in insecticidal effect, but also has a certain effect of inhibiting tomato fungal diseases, can be widely applied to prevention and control of agricultural diseases and pests, and has a wide application prospect. The sustainable development of green agricultural production is promoted.