22 results about "Blast disease" patented technology

The invention belongs to the technical field of prevention and treatment of rice blast, and particularly relates to a polypeptide MP1 for inhibiting rice blast bacteria and application thereof. The invention discloses a polypeptide MP1 for inhibiting magnaporthe oryzae. The amino acid sequence of the polypeptide MP1 is as shown in SEQ ID NO. 1. The polypeptide MP1 has an obvious inhibition effect on the magnaporthe oryzae appressorium, and the EC50 formed by the MP1 polypeptide on the appressorium is 134.60 mu M. Experiments show that the polypeptide can effectively interfere the normal differentiation and development of the appressorium in the key pathogenic stage of magnaporthe oryzae, so that the polypeptide has a strong prevention and control potential in the early stage of pathogenic bacterium infection. The polypeptide MP1 provided by the invention can significantly reduce the pathogenicity of magnaporthe oryzae to barley and rice, and provides an experimental basis for developing a novel biopesticide for preventing and treating the magnaporthe oryzae.

The present application relates to the field of rice blast prevention, and particularly relates to an application of perphenazine in prevention and treatment of rice blast. At present, perphenazine has not been reported in literatures to be used for prevention and treatment of rice blast. The technical problem to be solved by the present application is to provide an application of perphenazine in prevention and treatment of rice blast. The present application proves the effect of perphenazine in inhibiting rice blast fungus through tests. With the increase of concentration, the vegetative growth of rice blast fungus is obviously inhibited. Under the interference of perphenazine at a certain concentration, the pathogenicity of rice blast fungus is almost completely lost. Therefore, perphenazine can be used as a new antifungal agent for prevention and treatment of rice blast.

The invention relates to the field of crop breeding, in particular to a rice blast detection and counting method, which adopts the technical scheme that by improving a YOLOv8 detection algorithm and introducing a C2f-Aster module, a BFPN module, a WAdapt-IoU loss function and an LSCSAD detection head, the model performance is optimized, the parameter quantity and the calculation complexity are reduced, the characteristic expression ability to rice blast scabs and diseased leaves is enhanced, and the rice blast detection accuracy is improved. The method is suitable for resource-limited rice blast detection scenes, the detection capability of the model on rice blast disease spots and diseased leaves is improved, the generalization capability of the rice blast detection model is enhanced, the rice blast disease spot boundary detection precision is enhanced, the positioning precision of the disease spots and the diseased leaves is improved, and efficient and accurate rice blast detection and counting are achieved. And the accuracy and efficiency of rice blast disease detection and counting are improved.

The embodiment of the present application provides a method, system and equipment for intelligent assessment of rice blast disease grade and initial screening of disease resistance, the method comprising: S1: collecting image data of wild rice leaves infected with rice blast, performing instance segmentation on the image data by improving the YOLOv8‑Seg segmentation model, and obtaining segmentation results, wherein the improvement measures include: GhostHierarchicalNet backbone network, CAHSFPN neck network and LSDECS Head segmentation head; S2: based on the segmentation results, counting the number of pixels and their proportion of diseased leaves and diseased areas, and combining the disease resistance identification technical regulations to obtain disease grade assessment results; S3: based on the disease grade assessment results repeated multiple times, screening wild rice materials with strong disease resistance. This method can effectively improve the accuracy and efficiency of crop disease assessment, provide support for large-scale wild rice disease resistance screening, and thus promote the development of rice blast resistance breeding.

The invention relates to the technical field of soil improvement and crop disease prevention and control. The invention provides a zinc-silicon synergistic soil conditioner and a preparation method and application thereof.The zinc-silicon synergistic soil conditioner is prepared from, by mass, 5-8 parts of citric acid chelated zinc, 5-8 parts of citric acid chelated zinc, 5-8 parts of citric acid chelated zinc, 5-8 parts of citric acid chelated zinc, 5-8 parts of citric acid chelated zinc, 5- 25 to 40 parts of potassium silicate; 30 to 45 parts of humic acid; 5 to 10 parts of soluble starch; and the balance of deionized water. According to the zinc-silicon synergistic soil conditioner, the pH and the alkalization degree of soda saline-alkali soil are reduced through humic acid, and the rhizosphere microenvironment is improved; the citric acid chelated zinc provides quick-acting zinc, the potassium silicate continuously releases silicon, and the citric acid chelated zinc and the potassium silicate keep high bioavailability under the protection of humic acid; the soluble starch regulates nutrient release and prevents precipitation and inactivation. Field application shows that the morbidity of the rice red blight in the soda saline-alkali soil can be reduced to 5% or below, and synergistic interaction of soil improvement and disease prevention and control is achieved.

This invention discloses a deep learning-based intelligent detection system for rice seedling blast disease, belonging to the field of crop detection technology. It solves the technical problem that early or atypical symptoms of the disease may not be accurately identified in a timely manner, leading to further disease development and greater losses. Based on feature extraction results, the system classifies the disease risk of leaves and panicles, with different control strategies corresponding to different risk levels. The system continuously monitors image data from the growing and harvesting areas, enabling timely detection of subtle changes in leaf and panicle characteristics, effectively reducing yield losses and quality declines caused by the disease. The disease risk classification of leaves and panicles is combined with meteorological data from various management grids and hydrological data from irrigation areas. The system analyzes the risk of external disease conditions and integrates this analysis with the leaf and panicle disease risk classification for comprehensive risk warning.

This invention provides the application of FSD2 in regulating resistance to rice sheath blight and bacterial leaf blight, belonging to the field of gene breeding technology. This invention provides... FSD2 The application of genes and / or encoded proteins in regulating resistance in rice to infectious diseases caused by pathogenic microorganisms, the aforementioned FSD2 Genes are involved in regulating rice resistance to sheath blight and bacterial leaf blight. This invention obtains these genes through genetic transformation. FSD2 Overexpressing plants, compared with wild-type plants, showed that overexpressing plants... FSD2 The gene expression level was significantly higher than that of the wild type; after inoculation with *Rhizoctonia solani* and *Bacterium oxysporum*, the overexpressing plants showed significantly enhanced resistance to *Rhizoctonia solani* and *Bacterium oxysporum*. This invention provides a theoretical basis for elucidating the disease-resistant properties of plants, and can also be applied to the screening and creation of disease-resistant rice materials, laying a germplasm foundation for future variety improvement.

The invention discloses a rice seedling blast disease intelligent detection system based on deep learning, relates to the technical field of crop detection, and solves the technical problems that early-stage diseases or diseases with atypical symptoms may not be accurately identified in time, further development of the diseases is caused, and greater loss is caused. Performing leaf and spike disease risk grading based on a feature extraction result, wherein different risk grades correspond to different prevention and control strategies; the system continuously monitors the image data of the growth area and the harvesting area, can timely find the subtle change of the characteristics of the leaves and the ears, and effectively reduces the yield loss and the quality reduction caused by diseases. Leaf and spike disease risk grading is combined with meteorological data of each management grid and hydrological data of an irrigation area; according to the system, meteorological data of each management grid and hydrological data of an irrigation area are combined, external disease condition risks are analyzed, and the external disease condition risks are combined with leaf and spike disease condition risk grading to carry out comprehensive risk early warning.

The present invention discloses a feneptamidoquin-containing pesticide composition and its use. The pesticide composition comprises an active ingredient A and an active ingredient B, wherein the active ingredient A is feneptamidoquin and the active ingredient B is either blastifungin or blastamide, and the mass ratio of the active ingredient A to the active ingredient B is 1:25 to 30:1. The pesticide composition of the present invention has excellent control effects on rice blast disease. The rational combination of pesticides with different mechanisms of action effectively reduces the number of applications and the dosage of the pesticide, thereby lowering costs.

The application belongs to the technical field of plant disease prevention and treatment, and provides application of tetrahydro-gamma-carboline derivative. The structural formula of the tetrahydro-gamma-carboline derivative is: The derivative has a good inhibitory effect on fungal diseases of rice and tobacco, and can be used for preparing pesticides for preventing and treating tobacco target spot disease, tobacco brown spot disease, rice sheath blight disease and rice blast disease, and the application provides a new parent structure for development of the pesticides. The two kinds of tetrahydro-gamma-carboline derivatives provided by the application can be compounded with various types of pesticides, have a good synergistic effect on the above plant diseases, and can be used for delaying resistance development of existing commercial pesticides and prolonging the life cycle.

The invention provides a rice blast condition dynamic monitoring method based on a novel vegetation index and an unmanned aerial vehicle time sequence multispectral image. The method comprises the following steps: obtaining canopy spectrum and condition data of health and different condition severity susceptible samples in a plurality of phenological stages; constructing a multispectral rice blast vegetation index based on the canopy spectrum and the disease index, and constructing a disease index estimation model based on the multispectral rice blast vegetation index; and drawing a multi-temporal disease index spatial distribution map based on the time sequence unmanned aerial vehicle multispectral image, and drawing a disease index daily growth rate spatial distribution map based on the multi-temporal disease index spatial distribution map. According to the method, the disease index estimation precision is remarkably improved by constructing the novel vegetation index, and the defect that traditional static investigation is difficult to reflect the disease development trend is overcome through the time sequence dynamic index. The novel rice blast vegetation index of the method can be suitable for most of multispectral images, the illness condition drawing and sequence analysis steps are simple, the calculation cost is low, and the method can be widely applied to illness condition investigation, accurate pesticide application and pesticide effect tracking.

This invention belongs to the field of rice blast disease control technology, specifically relating to a polypeptide MP1 that inhibits rice blast fungus and its application. This invention discloses a polypeptide MP1 that inhibits rice blast fungus, the amino acid sequence of which is shown in SEQ ID NO.1. This polypeptide MP1 has a significant inhibitory effect on rice blast fungus appressoriums; after 24 h, the MP1 polypeptide significantly inhibits the formation of ECs on appressoriums. 50 The concentration was 134.60 μM. Experiments showed that the peptide could effectively interfere with the normal differentiation and development of appressorium, a key stage in the pathogenesis of rice blast fungus, thus exerting strong control potential in the early stages of pathogen infection. The peptide MP1 provided by this invention can significantly reduce the pathogenicity of rice blast fungus to barley and rice, providing experimental evidence for the development of novel biological pesticides for the control of rice blast.

The invention discloses a rice seedling blast disease intelligent analysis system based on remote sensing data analysis, and relates to the technical field of agricultural remote sensing and plant disease monitoring, the system comprises a physiological data acquisition module, a physiological feature extraction module and a disease severity calculation and severity grading module; wherein the physiological data acquisition module realizes in-situ non-invasive acquisition of the spectral reflectivity of rice seedling leaves, the maximum photochemical efficiency of a light system II and the water transport rate of stalks through various sensors such as a hyperspectral sensor and a chlorophyll luminoscope; the physiological feature extraction module fuses multiple parameters to calculate a leaf surface structure health index and a vascular function activity index; the disease grading module obtains an in-vivo disease load index through weighting, and outputs different disease grades in combination with a K-means clustering threshold value; the system solves the problems that traditional rice seedling blast diagnosis is high in subjectivity and hysteresis quality, and early-stage accurate recognition of diseases is achieved.

The invention discloses application of an OsCDPK24 gene in rice disease-resistant breeding, and belongs to the technical field of molecular biology. According to the invention, a calcium-dependent protein kinase induced by magnaporthe oryzae is identified, and the calcium-dependent protein kinase is named as OsCDPK24. Experiments show that the expression quantity of the OsCDPK24 protein and the encoding gene thereof OsCDPK24 is closely related to the development of rice blast. The rice OsCDPK24 gene overexpression and gene knockout plants are constructed, disease resistance analysis is performed on the rice OsCDPK24 gene overexpression and gene knockout plants, results show that the OsCDPK24 gene knockout remarkably improves the resistance level of rice to rice blast, it is indicated that OsCDPK24 negatively regulates the disease resistance of the plants, the encoding gene OsCDPK24 can serve as a target gene to be used for improving the disease resistance of the plants, and the application prospect is wide. The method has a good application prospect in cultivation of disease-resistant rice varieties, and lays an important foundation for rice resistance breeding.

The present application relates to the technical field of agricultural disease detection and crop disease resistance screening, and in particular to a rice bacterial leaf blight disease resistance screening method based on a UAV and deep learning, which has the technical scheme of: an optimized YOLOv11-OBB model is composed of a C3k2FC module, an SPPF_LSKA module, a SlimNeck module and a LiteHead module, is responsible for extracting features in an image and locating bacterial leaf blight spots, and can efficiently and accurately detect bacterial leaf blight spots; a lightweight deep learning model is used, can efficiently run on a resource-limited UAV platform, and reduces device and computing costs; through cooperation of multiple optimization modules, the detection accuracy of bacterial leaf blight spots is significantly improved, and stable detection effects can be maintained; the operation process is simplified, and full automation of bacterial leaf blight disease resistance screening is realized; therefore, by using the lightweight and optimized YOLOv11-OBB model and combining the module design with high computing efficiency, low-cost, efficient, automated and high-precision bacterial leaf blight disease resistance screening is realized, and the method is suitable for large-scale field application.

This invention relates to the field of pesticide technology, specifically to a soluble concentrate containing kasugamycin and its preparation process. By mass percentage, the raw materials for preparation include at least 0.1-8% kasugamycin, 0.1-30% plant growth regulators, 1-8% surfactants, 0.1-2% pH adjusters, 5-40% stabilizers, and deionized water to make up the balance. Specifically, this invention uses a combination of orthosilicic acid and kasugamycin. By controlling the amount of orthosilicic acid added to the soluble concentrate to 1-3 wt%, the mass ratio of kasugamycin to orthosilicic acid is (2-4):(1-3). This ensures product stability while achieving effective control of rice blast disease, exhibiting control effects no less than conventional agents such as tricyclazole and isoprothiolane, and with relatively lower pesticide residues compared to these agents, effectively improving rice quality and ensuring the safety of agricultural products.

The invention provides a molecular identification chip aiming at permanent resistance of rice blast and application thereof, the chip comprises 600-800 specific nucleic acid probes fixed on a solid phase carrier, each probe corresponds to a functional genetic locus subjected to multi-year, multi-point and multi-race inoculation tests and whole genome association analysis verification, and the molecular identification chip is used for identifying the permanent resistance of the rice blast. According to the method, a comprehensive resistance index (CRI) prediction model is constructed by combining high-throughput typing with machine learning. During breeding, the lasting resistance level of the material to multiple rice blast can be rapidly quantified in the seedling stage, and early-stage accurate screening is achieved. Compared with a traditional method depending on a single major R gene, the method has the advantages that the resistance broad spectrum and durability are remarkably improved, the field identification cost is reduced by 70% or above, and pesticide application reduction and green production are supported. The technology provides an efficient, intelligent and sustainable molecular tool for rice disease-resistant breeding.

The application discloses application of a compound BTD-81 in preparation of a medicine for preventing and treating Pyricularia oryzae, and belongs to the field of plant fungal disease prevention and treatment. The compound BTD-81 has a remarkable effect in preventing and treating rice blast or / and other pathogenic fungi, can effectively inhibit spore pathogenicity of the Pyricularia oryzae in a concentration range of 10-50 ppm, and especially, the compound BTD-81 at 50 ppm can completely prevent and treat the rice blast. The compound BTD-81 can be used as a protective agent, has a better effect when used at an initial stage of the rice blast infection, and under the condition of spraying the compound, the growth state of the rice is good, and there is no obvious adverse effect, indicating that the compound is safe to the rice, and has a practical significance for preventing the rice blast disease.

The application relates to the technical field of pesticides for rice, and aims to solve the problem of ecological environment damage caused by existing chemical pesticides, and provides application of Chymostatin in prevention and control of rice blast, including: S1, inhibiting rice Magnaporthe oryzae; S2, preventing and controlling rice blast; the CAS No of the Chymostatin is 9076-44-2. Chymostatin has a strong inhibiting effect on rice Magnaporthe oryzae, has low harm degree on animals such as human and livestock, is easy to degrade, is friendly to the environment, is beneficial to ecological balance and stability. Chymostatin can significantly inhibit the formation of Magnaporthe oryzae appressorium, and then inhibit the infection. Chymostatin has good inhibiting activity on various rice Magnaporthe oryzae and has broad spectrum.

The invention discloses an application of stenotrophomonas maltophilia CGMCC (China General Microbiological Culture Collection Center) NO.1. 1788 in inhibiting the growth of rice blast bacteria, and particularly discloses an application of stenotrophomonas maltophilia CGMCC NO.1. 1788 in inhibiting the growth of rice blast bacteria. Experiments prove that the stenotrophomonas maltophilia CGMCC NO.1. 1788 can be used for inhibiting and killing the rice blast bacteria, which is mainly embodied in killing the rice blast bacteria to obtain nutrition, inhibiting the growth of the rice blast bacteria and / or inhibiting the spore germination of the rice blast bacteria, and the stenotrophomonas maltophilia CGMCC NO.1. 1788 has the advantages that the stenotrophomonas maltophilia CGMCC NO.1. 1788 can be used for inhibiting and killing the rice blast bacteria; therefore, the stenotrophomonas maltophilia can be used as a natural microbial antagonistic agent for preventing and treating the rice blast, the use of chemical pesticides is remarkably reduced, and the generation of the drug resistance of phytopathogen caused by abuse of the chemical pesticides is prevented. The method has an important application value.

The present invention belongs to the technical field of agricultural disease monitoring and prevention and control, and specifically relates to a rice blast monitoring and diagnosis method based on a tethered hot air balloon and drone system. By constructing a dynamic observation platform of a tethered hot air balloon + drone group, multi-variety, multi-phase, and multi-dimensional multi- / hyperspectral data of rice blast diseased plants and multivariate information such as geography, soil, climate, and field management are simultaneously acquired to construct a spectral database. Utilizing self-supervised learning and deep learning techniques, an early diagnosis inversion model is constructed based on the spectral characteristics of diseased rice plants and the data characteristics of drones and tethered hot air balloons. This method gives full play to the synergistic advantages of tethered hot air balloons and drones, realizes comprehensive data collection and deep integration, improves the accuracy and timeliness of rice blast monitoring and diagnosis, provides strong technical support for the healthy development of the rice industry, and contributes to the intelligentization and sustainable development of agriculture.

This invention discloses the application of FSIBR, a key enzyme in rice flavanone synthesis, and its encoding gene, in rice disease resistance breeding, relating to the field of genetic engineering technology. The amino acid sequence of the key enzyme FSIBR is shown in SEQ ID NO.2, and the nucleotide sequence of the encoding gene is shown in SEQ ID NO.1. This invention found that the expression levels of FSIBR protein and its encoding gene are closely related to the development of rice blast disease. Knocking out the FSIBR gene significantly improved the resistance level of rice to rice blast disease, indicating that FSIBR negatively regulates plant disease resistance. Its encoding gene, FSIBR, can be used as a target gene to improve plant disease resistance, showing good application prospects in breeding disease-resistant rice varieties and laying an important foundation for rice resistance breeding.