1367 results about "Plant disease" patented technology

The invention discloses a plant disease and insect pest early warning method and system based on plant monitoring, and belongs to the field of plant disease and insect pest early warning, and the method comprises the steps: extracting the contour of a lesion region through an edge detection algorithm, carrying out the smoothing of the contour through the combination of morphological operation, and obtaining a more precise lesion region boundary; according to an image segmentation result and a disease type identification result, a plant health condition evaluation model is established, and the plant damage degree is quantified; environmental data and image data are acquired from a plurality of sensor nodes distributed in a field, and the data are gathered to a regional gateway through wireless transmission; carrying out preprocessing and feature extraction on the converged heterogeneous data in a regional gateway, removing noise data and redundant information, and extracting key features; and carrying out pest detection and counting on the preprocessed image by using a deep learning model, carrying out modeling on a pest number change trend, predicting population density change in a period of time in the future in combination with environmental factors, and generating a detection result.

The invention discloses a grape disease recognition and early warning method based on the Internet of Things, and relates to the technical field of plant disease recognition, image acquisition equipment and environment sensing nodes are arranged in a vineyard, and leaf images and corresponding temperature and humidity, illumination and soil moisture parameters are obtained; inputting the image into a neural network fusing dilated convolution and a residual attention mechanism, realizing extraction of a disease spot region and a disease spot variation feature, and generating a preliminary recognition result; constructing a multi-factor evolution sample set in combination with the recognition result and the environment state of the time node; constructing a space-time correlation graph model based on a graph neural network, estimating a disease propagation risk path and a diffusion probability, and performing early warning judgment at a gateway end through a multi-factor gating discrimination algorithm; the method disclosed by the invention is high in recognition precision and strong in response timeliness, has adaptive prediction and targeted treatment capabilities, and remarkably improves the intelligence and precision level of grape disease management.

The invention provides a Pseudomonas protegens P150 strain and an application of the Pseudomonas protegens P150 strain, and belongs to the technical field of biocontrol bacteria. The defensive pseudomonas P150 is preserved in the China General Microbiological Culture Collection Center (CGMCC), the preservation number is CGMCC No.34520, the preservation time is May 13, 2025, and the preservation address is No.3, Yard 1, Beichen West Road, Chaoyang District, Beijing. The defensive pseudomonas P150 disclosed by the invention has the effects of inhibiting various pathogenic bacteria, producing enzymes, promoting growth and preventing and treating tomato bacterial wilt and soybean pustule. The microbial inoculum prepared by adopting the biocontrol bacterium can reduce the dosage of chemical pesticides and the prevention and control cost of plant diseases, is green and pollution-free, can be used for preventing and controlling tomato bacterial wilt and soybean pustule, and has a relatively good popularization value.

The invention relates to the technical field of disease and insect pest early warning, and discloses a big data-based seed industry disease and insect pest early warning method and system, and the method comprises the steps: obtaining environment sound data and leaf image data; performing scab extraction according to the leaf image data to obtain scab morphological characteristics; performing feature extraction according to the environment sound data to obtain pest sound features; matching according to the scab morphological characteristics and the pest sound characteristics in combination with a pre-stored pest disease database to obtain a pest type and a disease type; performing matching degree calculation according to the pest type and the disease type to obtain a pest and disease matching degree; and carrying out damage assessment according to the pest disease matching degree and a preset matching degree threshold value to obtain a disease assessment result. The method has the following effect that the accuracy of early warning of plant diseases and insect pests in the seed industry can be improved.

A data-centric system for analyzing agricultural crops, consisting of: a data acquisition module configured to capture images of agricultural fields using cameras, unmanned aerial vehicles (UAVs) or sensors, with the sensors collecting data on soil moisture, temperature, light, humidity and pH; a data preprocessing module configured to: resize the acquired images to a standardized dimension suitable for input to a deep learning model; apply noise reduction using a Gaussian filter; improve image contrast through histogram equalization; and perform image magnification through rotation, reflection, and scaling transformations; a feature engineering module configured to extract the following features: color features, which include color histograms, mean, and standard deviation of color channels; texture features using Gray-Level Co-occurrence Matrix (GLCM) properties, which include contrast, dissimilarity, homogeneity, energy, angular moment (ASM), and correlation; shape features, which include contour area, perimeter, aspect ratio, and roundness; and other features, which include the green pixel ratio and edge density; a classification module configured to: implement deep learning-based classification models selected from the group consisting of Support Vector Machine (SVM), Artificial Neural Network (ANN), Convolutional Neural Network (CNN), ResNet18, Random Forest (RF), SegNet, VGGNet, Naive Bayes (NBG), Decision Tree (DT), K-Nearest Neighbors (KNN), and DeepLab; detecting and classifying weed species in the images of agricultural fields; and diagnosing plant diseases based on the features extracted from the images of agricultural fields; an output module comprises a user interface configured to display the classification and recognition results; and a recommendation module configured to suggest treatment solutions for diagnosed plant diseases through the output module's user interface.

Burkholderia, and a composition, use and usage method thereof. Provided are the Burkholderia, and a composition comprising the strain and / or a metabolite, culture, fermentation broth and / or extract thereof. The Burkholderia or the composition thereof can generate a siderophore, induce plants or seeds thereof to generate systemic resistance to plant pathogens, and reduce the chemotaxis of plant pathogens to plants, so that prevention and treatment of plant diseases and insect pests are achieved. In addition, plant root system development can be promoted, a nitrogen fixation effect is provided, a phosphate solubilization effect is provided, indoleacetic acid is generated, and weeds are removed, thereby promoting plant growth.

The invention belongs to the technical field of garden irrigation, and particularly discloses a garden landscape intelligent irrigation management system which comprises a sensing layer, a transmission layer, a platform layer and an execution layer. The sensing layer is used for collecting garden environment and plant related data; the transmission layer is used for transmitting the data acquired by the sensing layer to the platform layer; the platform layer is used for realizing data visualization, intelligent decision generation and equipment control; the execution layer executes irrigation operation according to an instruction of the platform layer; according to the system, through accurate monitoring and intelligent control, water resource waste and irrigation cost are effectively reduced. Manual inspection and operation workloads are reduced through automatic operation, one administrator can manage thousands of mu of gardens, and the management efficiency is improved. The risk of plant diseases and insect pests can be reduced through on-demand irrigation, and the stability and attractiveness of the garden landscape effect are kept. The environment, irrigation and plant growth data accumulated by the system provides a scientific decision basis for garden maintenance, and is convenient for long-term planning and management strategy optimization.

The invention relates to the technical field of microorganisms, and discloses trichoderma yunnanense and application thereof. The Trichoderma yunnanense CCTCC NO: M 2025645 provided by the invention is a dominant strain of a high-yield siderophore, the activity of the siderophore is 69.79%, and the Trichoderma yunnanense can be used for synthesizing and secreting carboxylic acid type siderophore; the strain has a sulfur oxidation function; in addition, the invention also provides an application of the trichoderma sp. In regulation and control of plant diseases, the trichoderma sp. Disclosed by the invention can be used for antagonizing fusarium solani, fusarium graminearum, fusarium moniliforme, Rosellinia necatrix and Alternaria brassicae (Fr.) Kissler, and the trichoderma sp. Can be used for antagonizing fusarium solani, fusarium graminearum, fusarium moniliforme, Rosellinia necatrix and Alternaria brassicae (Fr.) Kissler, and can be used for antagonizing fusarium solani, fusarium graminearum, fusarium moniliforme, Rosellinia necatrix and Alternaria brassicae. The Trichoderma yunnanense provided by the invention is a strain separated from tobacco planting soil, and compared with a strain subjected to mutagenesis screening in an extreme environment and a laboratory, the Trichoderma yunnanense has better adaptability when being applied to a planting environment, and can be stably colonized in plant rhizosphere and soil, so that the Trichoderma yunnanense stably plays a growth promoting role for a long time, is safe and environment-friendly, and has a wide application prospect.

The invention relates to the technical field of microorganisms, and particularly discloses a saline-alkaline tolerant bacillus deserticola BW-13 with biocontrol and growth promoting functions and application thereof. The bacillus safensis BW-13 is preserved in the China Center for Type Culture Collection on January 13, 2025, the classification name of the bacillus safensis BW-13 is bacillus safeensis, and the preservation number of the bacillus safensis BW-13 is CCTCC NO: M 2025108. The strain BW-13 has relatively high salt tolerance, and still keeps good resistance under various stress conditions; meanwhile, the plant growth promoting agent has various plant growth promoting characteristics including nitrogen fixation, phosphorus solubilization and cellulase and protease secretion capacity, and pot experiment verifies that the plant growth promoting agent can improve the salt resistance of cucumber seedlings and promote plant growth; the strain has an antagonistic effect on a plurality of phytopathogens, and especially has a remarkable prevention and treatment effect on plant diseases such as apple ring spot, polygonatum kingianum anthracnose, pear tree rot and tomato gray mold caused by ascomycophyta pathogenic fungi.

The invention discloses a traditional Chinese medicinal material standard base pest and disease damage intelligent monitoring and precise control method and control system, and relates to the technical field of agricultural intelligence. The Internet of Things technology, the block chain and the artificial intelligence algorithm are integrated to improve monitoring accuracy and prevention timeliness, environment and plant states are acquired through the sensor and image data, safe storage of data is ensured by using the block chain, early recognition of diseases and pests is performed by using the convolutional neural network, and the accuracy of disease and pest control is improved. A disease risk index is calculated in combination with environmental parameters, a reinforcement learning algorithm dynamically optimizes a control strategy, control measures are automatically executed through Internet of Things equipment, an execution result is recorded on a block chain, in addition, the strategy is continuously adjusted according to a control effect evaluation result, intelligent and precise disease and pest management is realized, resource consumption is effectively reduced, and the economic benefit is improved. The traditional Chinese medicinal material production safety and efficiency are improved.

The invention relates to the field of microorganisms, in particular to Rahnella and Burkholderia with growth promotion and biological control functions and a composition thereof, and the Rahnella comprises a 16S rDNA sequence shown in SEQ ID NO: 1 or a complementary sequence thereof or a sequence which is at least 85% identical with the sequence shown in SEQ ID NO: 1; the burkholderia comprises a 16S rDNA sequence as shown in SEQ ID NO: 2 or a complementary sequence of the 16S rDNA sequence or a sequence which is at least 85% identical with the sequence as shown in SEQ ID NO: 2. The new strains Rahnella victoriana Rahn.R5, Burkholderia ubonensis Burk.R2 and the application of the composition of the Rahnella victoriana Rahn.R5 and the Burkholderia ubonensis Burk.R2, which are provided by the invention, in promoting crop growth and / or preventing and treating plant diseases, have important significance on improving the crop yield and promoting agricultural green production.

The invention provides an unmanned aerial vehicle target identification and positioning method and system based on multispectral fusion. The method comprises the following steps: firstly, acquiring multispectral image data, then analyzing the multispectral image data of multiple time phases into pixel-level data, then identifying an early infection area of the plant diseases and insect pests, then constructing a geometric distortion correction model, and then determining the relative position of the early infection area of the plant diseases and insect pests through multi-view space intersection calculation. And finally, fusing the real-time differential global navigation satellite system positioning data of the unmanned aerial vehicle and the relative position of the disease and insect pest early-stage infection area to output absolute geographic coordinates of the disease and insect pest early-stage infection area. According to the technical scheme provided by the invention, accurate conversion from a local coordinate system to a global geographic coordinate system is realized, an exact spatial position basis is provided for precise agricultural operation, and precise positioning of a pest and disease damage area is realized.

To provide a novel pest control agent composition, particularly a bactericidal composition.SOLUTION: A bactericidal or bacteriostatic composition comprising an active ingredient A selected from pyrazole compounds or salts thereof represented by formula (I): [G represents G-1; G1 represents C1-C6 haloalkyl or the like; T represents an oxygen atom or the like; RX represents C1-C6 alkyl or the like; RY represents a hydrogen atom or the like; R1 represents a hydrogen atom or the like; R2 represents a hydrogen atom or the like; R3 represents a hydrogen atom or the like; Ra represents a hydrogen atom or the like; Z represents Z-1 or the like; Z1 represents C1-C6 alkyl or the like; m5 and n5 each represent an integer of 0, 1, 2, 3, 4, or 5; and p represents an integer of 0 or 1] and an active ingredient B selected from known bactericidal or bacteriostatic compounds.SELECTED DRAWING: None

The invention belongs to the field of biological agents, and particularly relates to bacillus siamensis and application thereof in the aspects of plant disease control, growth promoting and yield increasing. The bacillus siamensis XNC-3 provided by the invention is wide in antibacterial spectrum, can effectively inhibit various plant pathogenic fungi including phytophthora parasitica var nicotianae, has broad-spectrum antibacterial activity, and can be used for preventing and treating plant diseases, especially tobacco diseases. The bacillus siamensis has a promoting effect on tobacco seedling growth and seed germination, has growth-promoting and yield-increasing effects on tobacco, can remarkably increase the tobacco yield and improve the tobacco quality, is safe to the environment and has a very good application prospect.

The invention discloses protease for improving the resistance of potatoes to late blight as well as a coding gene and application thereof, and belongs to the technical field of genetic engineering and plant disease resistance breeding. The amino acid sequence of the protease StRD21 is as shown in SEQ ID NO.2, or the protease StRD21 has a derivative sequence with the same disease-resistant function. The nucleotide sequence of the coding gene is as shown in SEQ ID NO. 1. The invention also provides a specific primer pair for cloning the gene, a potato recombinant overexpression vector containing the gene and a transgenic host cell. The StRD21 gene is introduced into potatoes and overexpressed, so that the resistance of the potatoes to late blight can be remarkably enhanced. The invention provides an effective gene resource and a biotechnological means for cultivating a new variety of disease-resistant potatoes.

The invention belongs to the field of computer vision, and discloses a plant disease identification method and system based on a three-branch deep neural network, and the method comprises the steps: firstly extracting global, local and middle-layer multi-scale positioning features through employing Vision Transformer, ResNet50 and YOLO in parallel; secondly, aligning and fusing the three paths of features, carrying out interactive enhancement through Transform block, and then respectively predicting crop types and disease types through a double-end stacking classifier; and finally, by setting a proper loss function combination and a joint training strategy, performing end-to-end optimization on the whole network, so as to improve the recognition capability of difficult-to-judge samples and small-scale lesions. According to the invention, accurate identification of plant diseases in a natural scene can be realized. Experimental results show that the method provided by the invention obtains classification performance equivalent to or even better than that of the most advanced plant disease identification method in the prior art.

The invention belongs to the technical field of agricultural microorganisms, and particularly relates to Lecanicillium lecanii as well as a fungicide and application thereof, Lecanicillium lecanii GC-2 is obtained by screening and separating phyllospheric microorganisms, and the strain is proved to have relatively strong inhibitory activity on wheat stripe rust, fusarium graminearum and pseudocereal fusarium; a pot experiment verifies that the strain has a very strong inhibition effect on uredospores of wheat stripe rust, has a relatively strong antagonism effect on pathogenic bacteria of wheat scab and wheat stem rot, has a remarkable prevention and treatment effect on the wheat stripe rust, the wheat stem rot and the wheat scab, has a better prevention effect than a treatment effect, and can be widely applied to prevention and treatment of wheat stripe rust, wheat stem rot and wheat scab. Meanwhile, the strain has no adverse effect on growth and development of wheat and can be applied to prevention and treatment of wheat stripe rust, basal stem rot and gibberellic disease. The invention provides a new strain resource for a biocontrol resource library of plant diseases.

The invention provides an improved YOLOv11 model-based tea plant disease and insect pest detection method in a complex environment, which comprises the following steps of: acquiring an original image through field shooting, performing data amplification by using a data enhancement technology, and realizing bounding box labeling by using a labeling tool label Img to form a training data set; the method comprises the following steps: constructing a network model of tea plant diseases and insect pests, improving an original model structure of YOLOv11n, and improving a Head module by using an MSDAF module; improving a loss function; performing end-to-end training on the network architecture by using the training set and the test set, and adjusting hyper-parameters; and performing field detection on the tea leaf scab area by using the trained network model. The invention provides a novel tea disease and insect pest detection algorithm based on a YOLOv11 target detection algorithm, and the average precision of tea disease and insect pest detection in a complex environment can be effectively improved.

The invention relates to the technical field of digital agriculture, in particular to a farmer portrait generation method and system based on GIS pattern spots. According to the farmer portrait generation method based on the GIS pattern spots, a farmland plot is locked in real time through a satellite map with the precision of 0.5 m, and farmer production behaviors are collected and analyzed in real time so as to generate a digital farmer portrait. According to the farmer portrait generation method and system based on the GIS pattern spots, decision-making precision can be accurate to a window period of 3 days, meanwhile, early warning of plant diseases and insect pests can be achieved 14 days in advance, the fuel cost of agricultural machinery is reduced, meanwhile, environmental pollution is reduced, supervision efficiency is improved, and great convenience is provided for modern agricultural development.

Provided are a method for controlling a soilborne disease in which a load on an environment and a human body is reduced, and a novel predatory bacterium therefor.　Provided are: a predatory bacterium or a variant thereof selected from the group consisting of bacteria of the genus Bacteriovorax and bacteria of the genus Bdellovibrio which selectively prey on a pathogenic bacterium belonging to the family Burkholderiaceae, the family Pectobacteriaceae, or the family Lysobacteraceae; a method for controlling a soilborne plant disease caused by the pathogenic bacterium, the method characterized in that the predatory bacterium or variant thereof is applied to a seed, root, or underground stem of a plant, rhizosphere soil, or soil; and a composition.

The invention discloses a plant immune induced resistance protein PpAE4 and application thereof, and the protein can induce plant resistance and can be used as a plant immune activating factor to be applied to the field of prevention and treatment of plant diseases. The amino acid sequence of the protein is as shown in SEQ ID NO: 2. High-concentration protein can be obtained through expression of the engineering strain, the disease resistance of plants to soybean rust germs can be improved when the protein is used for treating the plants, and the protein is low in needed concentration, quick in effect taking and long in acting time. The PpAE4 provides a new way for improving plant disease resistance and preventing and treating plant diseases.

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 the technical field of microorganisms, and particularly discloses bacillus velezensis DSSR-2, a biocontrol microbial agent and application of the bacillus velezensis DSSR-2, the bacillus velezensis DSSR-2 is preserved in the China General Microbiological Culture Collection Center on July 8, 2024, the preservation number is CGMCC No.31207, and the bacillus velezensis DSSR-2 is classified and named as bacillus velezensis. The bacillus velezensis DSSR-2 provided by the invention has broad-spectrum antibacterial activity and can be used for inhibiting pathogenic bacteria of plant diseases, so that the plant diseases are prevented and treated, and meanwhile, the growth and development of plants are promoted.

The invention belongs to the technical field of agricultural irrigation, and discloses a crop irrigation system and method, and the method comprises the steps: a sensor arrangement module reasonably arranges various sensors; the environment data acquisition module acquires environment data; the meteorological data acquisition module is used for actually collecting meteorological data; the route planning module plans a flight irrigation route of the unmanned aerial vehicle; the cruise irrigation mechanism is used for spraying water to irrigate crops; the image acquisition module acquires high-definition images of crops; the image preprocessing module preprocesses the image; the feature extraction module performs feature extraction on the image; the abnormity recognition module recognizes abnormal growth conditions of crops; the growth period identification module accurately identifies the growth period of the crops; and the comprehensive evaluation module predicts the growth trend of the crops. By means of the automatic and intelligent irrigation system, the workload of manual inspection and manual irrigation is reduced; abnormal conditions such as plant diseases and insect pests, water shortage and seedling shortage in the growth process of crops can be found in time.

The invention relates to the technical field of plant disease and insect pest detection, and discloses a plant disease and insect pest identification method based on a multispectral image acquisition system. Specifically, multispectral image data of a plant sample is obtained through a multispectral image acquisition system, geometric calibration is performed on the multispectral image data, noise and atmospheric influence in the multispectral image data are eliminated, and target multispectral image data are obtained. An improved competitive self-adaptive reweighted sampling method is used for extracting key characteristic wave bands related to diseases from target multispectral data, and the characteristic selection efficiency is remarkably improved. And finally, feature extraction and classification decision are performed on the key feature wavebands by using a multi-modal classification model, so that the model interpretability and classification precision can be enhanced, and the method has significant advantages in early disease detection and can effectively identify early disease symptoms.

The invention relates to a landscaping plant disease and insect pest distribution data statistical method, which comprises the following steps: acquiring multi-source parameter data in real time on the basis of an environmental induction factor having a causal relationship with disease and insect pest occurrence, constructing an inducement fluctuation trend judgment relationship, and dynamically judging whether a disease and insect pest distribution data statistical task is triggered or not in a statistical period; after the statistical task is triggered, statistical layering processing is conducted on the same plant species, and the pest exposure rate, the occurrence frequency and the recovery duration of each layered population are calculated respectively; carrying out continuous, stage and wandering behavior recognition on insect pest types in combination with distribution evolution characteristics of insect pests in time and space dimensions in a historical statistical period; identifying a statistical blind area for an area with data missing in the statistical period; and constructing a pest and disease damage accumulated threshold value judgment relation, when a certain pest and disease damage statistical value exceeds a set threshold value, triggering an early warning prompt, and marking a corresponding risk level and a disposal priority in a statistical result.

The invention discloses Delftia tsuhuensis and an application of the Delftia tsuhuensis in prevention and treatment of plant diseases. The Delftia tsuhuensis CDJ2 is preserved in the Guangdong Microbial Culture Collection Center on October 18, 2024, and the preservation number is GDMCC (China General Microbiological Culture Collection Center) NO: 65290. The strain has a good prevention and treatment effect on citrus canker, and the prevention and treatment effect can reach 84%. Meanwhile, the strain can also effectively prevent and treat soft rot of taro, bacterial basal rot of rice, bacterial wilt of crops, kiwifruit canker, angular leaf spot of mango, black rot of brassicaceous vegetables, tomato scab, gummosis of sugarcane, bacterial wilt of walnuts and bacterial leaf spot of plums. Wide application prospects are realized in the aspects of preventing and treating diseases of crops and commercial crops and promoting healthy growth of plants.

The invention discloses a soybean phospholipid disease-preventing and root-promoting microbial agent as well as a preparation method and application thereof, and belongs to the technical field of microorganisms. The microbial agent comprises a microbial composition, modified enzymolysis soybean phospholipid, a carrier and auxiliary components. According to the invention, the modified enzymolysis soybean phospholipid and microorganisms are combined to achieve a synergistic effect. According to the method, soybean phospholipid is modified and subjected to enzymolysis, and the steps of pretreatment, stepped low-temperature treatment, enzymolysis treatment, enzyme inactivation and purification and the like are carried out, so that the quality and performance of the soybean phospholipid are improved, the rhizosphere colonization rate of strains can be increased, the disease prevention and root promotion effects can be improved, the soil micro-ecological environment can be improved, and good growth conditions are created for plant root systems; and the disease-preventing and root-promoting effects of the microbial agent are further enhanced. The microbial agent disclosed by the invention can be used for remarkably reducing the morbidity of wheat sharp eyespot and reducing the use amount of chemical pesticides, can also be applied to planting of other crops, and can play a role in preventing and controlling various plant diseases and promoting root growth.

The invention provides a trichoderma maple fungicide, a microbial granular fertilizer as well as a preparation method and application of the trichoderma maple fungicide and the microbial granular fertilizer, and relates to the field of microorganisms. The acer rubrum fungicide contains acer rubrum RA with the preservation number of CGMCC No.35889. The acer rubrum fungicide has the capability of decomposing inorganic phosphorus, is wide in phosphorus dissolving range, can decompose tricalcium phosphate, ferric phosphate and aluminum phosphate, and particularly still has the very strong capability of decomposing the inorganic phosphorus under the low-temperature condition; the strain has the capability of producing siderophore and IAA at low temperature; the strain has an inhibition effect on various pathogenic bacteria causing field crop diseases. The microbial granular fertilizer provided by the invention contains various biostimulant substances, can promote crop growth, improve plant stress resistance and improve plant resistance to plant diseases and insect pests, and field tests prove that the microbial granular fertilizer can significantly promote crop growth and improve crop yield.

The invention belongs to the technical field of plant disease control, and particularly relates to bacillus agave, fermentation liquor, a biological agent and application. The invention discloses a strain of bacillus tequilensis, which is preserved in the China General Microbiological Culture Collection Center (CGMCC), and the preservation number of the bacillus tequilensis is CGMCC NO.34830. The strain of bacillus tequilensis has the advantages that the preservation number is CGMCC NO.34830; the invention also discloses a fermentation broth and a biological agent prepared according to the bacillus agave, and the bacillus agave, the fermentation broth and the biological agent provided by the invention can effectively reduce the harm of root knot nematode disease to plants and promote seed germination or crop growth, and have the advantages of high efficiency, safety, environmental protection and difficult generation of resistance.