132 results about "Diseased plant" patented technology

The invention belongs to the technical field of agricultural disease monitoring, prevention and control, and particularly relates to a rice blast monitoring and diagnosing method based on a mooring hot-air balloon and an unmanned aerial vehicle system. By constructing a dynamic observation platform of a tethered hot-air balloon and an unmanned aerial vehicle group, multi-variety, multi-temporal and multi-dimensional rice blast diseased plant multi-spectral / hyperspectral data and multi-information such as geography, soil, climate and field management are synchronously obtained, and a spectral database is constructed. An early diagnosis inversion model is constructed based on spectral characteristics of diseased rice plants and data characteristics of an unmanned aerial vehicle and a captive hot-air balloon by using self-supervised learning and deep learning technologies. According to the method, the cooperative advantages of the tethered hot-air balloon and the unmanned aerial vehicle are fully played, comprehensive acquisition and deep fusion of data are realized, the accuracy and timeliness of rice blast monitoring and diagnosis are improved, powerful technical support is provided for healthy development of the rice industry, and agricultural intelligence and sustainable development are assisted.

A system for detecting diseases among plants includes a mobile device such as a smartphone, table, or personal computer, and a mobile robot which sends photographs of diseased plants to the mobile device including a plant name, disease type and location of the plant. The mobile robot includes a power supply, housing unit, camera, navigation unit, GPS unit, wireless transmitter, and traction unit for mobility of the robot. A geared motor drives the traction unit, and is connected to a low-level controller for motion control. A high-level controller is connected to the camera, navigation unit, GPS unit, and programmed with a convolutional neural network (CNN) configured to process images taken by the camera and associate with each image a plant type, disease type, and location of where the image was taken. The CNN may be a you only look once (YOLO) model trained with images from a dataset.

The invention belongs to the technical field of crop disease and pest control, and discloses a greenhouse tomato disease and pest diffusion distribution diagram prediction method, which comprises the following steps: S1, collecting current growth data of tomatoes in a greenhouse in real time; s2, according to the current growth data, constructing a diffusion velocity model of diseases and insect pests, and predicting a disease radius # imgabs1 # after the time # imgabs0 # of the diseases and insect pests through the diffusion velocity model; and S3, predicting according to the current growth data acquired in the step S1 and the disease radius # imgabs2 # predicted in the step S2 to obtain a disease and pest diffusion distribution diagram. The current pest and disease damage data of the tomatoes in the greenhouse are collected in real time, environmental factors (temperature, humidity and carbon dioxide concentration) and interaction among different pest and disease damage are comprehensively considered, then the pest and disease damage diffusion distribution diagram is predicted and generated, and the generated result is higher in credibility and more accurate. A user can treat diseased plants according to the diffusion distribution diagram and prevent and treat infected plants, so that accurate prevention and treatment of plant diseases and insect pests by the user are facilitated.

The invention provides a preparation method of a root knot nematode disease plant source nematicide, and belongs to the technical field of computational chemistry. The preparation method comprises the following steps: firstly, collecting tobacco plant materials in a root knot nematode disease high-incidence area, drying and crushing; determining optimal extraction parameters through a plant extraction parameter optimization function, and carrying out reflux extraction by taking ethanol as a solvent; filtering and concentrating an extracting solution, and adding an organic silicon surfactant and xanthan gum to enhance the stability; adjusting the pH value and adding a preservative; a high-pressure homogenizer is used for treatment, so that the dispersion uniformity is improved; component analysis and activity evaluation are carried out through a plant nematicidal activity prediction model, and the model is based on a convolutional neural network and a Transform architecture, and accurate prediction is realized through an adaptive attention mechanism; and filling the preparation and storing in a dark place. The whole preparation process realizes standardized control of components, and solves the technical problem of large difference between batches of traditional plant source nematocides.

The invention provides a comprehensive prevention and control method for a rice kernel smut disease. The method comprises the steps of seed treatment, crop rotation and deep ploughing, scientific fertilization and irrigation, rational close planting and flowering phase management, field disease monitoring and early warning, biological prevention and control, diseased plant treatment and the like. Seeds are selected by saline water and treated by various disinfectants, so that the health of the seeds is ensured; crop rotation for more than two years and deep ploughing and field drying in winter are performed to reduce accumulation of pathogenic bacteria; reasonable fertilization is performed according to a soil fertility detection result, field humidity is controlled, and diseases are reduced; the planting density and flowering period management are optimized, and the seed production success rate is increased; disease risks are monitored in real time through a disease and pest monitoring and early warning system, the disease trend is predicted through big data analysis and an artificial intelligence algorithm, and early warning information is issued in time; a beneficial microbial community is formed in the field by using a biocontrol inoculant, and growth of pathogenic bacteria is inhibited; diseased plants are removed at fixed points through a small agricultural machine, and disease diffusion is prevented.

The invention relates to the crossing field of agricultural disease monitoring and plant pathology, in particular to an alfalfa root rot prediction method based on pathogenic bacteria classification and data fusion. The method comprises the following steps: separating and purifying alfalfa root rot pathogenic bacteria and identifying types to construct a pathogenic bacteria database; carrying out an indoor artificial contamination test, and collecting hyperspectral data and binocular depth camera point cloud structure characteristics at different disease stages; in combination with multispectral / hyperspectral and point cloud data of a field unmanned aerial vehicle, multi-temporal information of healthy and diseased plants is tracked and marked. After vegetation index screening and principal component analysis dimensionality reduction, a multi-classification model is used for training, spectrum-structure feature generality of indoor and outdoor diseased plants is mined, and an early prediction model is constructed. According to the method, pathological diagnosis, spectral remote sensing and machine learning technologies are fused, cross-scale correlation analysis of pathogenic bacteria classification and field phenotypic characteristics is achieved, technical support is provided for accurate early warning of alfalfa root rot in the early stage, and the problems of traditional detection lagging and data isolation are solved.

The invention discloses a cotton GhATG1t gene and application of the cotton GhATG1t gene in regulation and control of verticillium wilt resistance of plants. According to the invention, the GhATG1t gene is separated from cotton, the nucleotide sequence of the GhATG1t gene is shown as SEQ ID No.1, and the amino acid sequence of the encoded protein of the GhATG1t gene is shown as SEQ ID No.2. According to the invention, a virus-induced gene silencing technology and a transgenic overexpression arabidopsis thaliana technology are further utilized to carry out preliminary research on the function of the cotton GhATG1t gene in cotton verticillium wilt resistance, and a result shows that after the GhATG1t gene in cotton is silenced, the verticillium wilt resistance of a cotton seedling plant is obviously reduced; after the GhATG1t gene is over-expressed in arabidopsis thaliana, the verticillium wilt resistance of arabidopsis thaliana is remarkably improved, and the resistance of a GhATG1t gene forward regulation plant to verticillium dahliae is determined; the invention has application prospects in the aspects of improving the verticillium wilt resistance of plants or cultivating verticillium wilt resistant plant varieties and the like.

The invention belongs to the technical field of plant disease ecology, and particularly discloses an intercropping mode for relieving corn southern rust disease. Different corn varieties and different pepper varieties are selected, for spring-planted peppers, positions are reserved when winter wheat is planted in the previous year, pepper seedlings are transplanted in May of the next year, and corn with the sowing time 1 is planted; after the wheat is harvested, summer-planted pepper is transplanted, and corn with the sowing time 2 is planted; performing statistical determination on the diseased plant rate, diseased leaf rate and disease index of the corn southern rust disease in the intercropping mode in a corn filling stage; selecting an optimal intercropping mode through measured data; in a harvesting period, respectively counting the yields of the corns and the peppers; other planting management methods of corn in the intercropping mode are the same as those of single-cropping corn, and other planting management methods of pepper in the intercropping mode are the same as those of single-cropping pepper. According to the intercropping mode, the morbidity of the corn southern rust disease can be effectively relieved, meanwhile, the yield can be increased, and therefore the economic benefits of strip-shaped compound planting can be remarkably increased.

The invention relates to the technical field of data processing, and discloses a peanut anti-bacterial wilt breeding strategy analysis method and system based on a growth cycle. The method comprises the following steps: acquiring and analyzing peanut growth period characteristic data to obtain a growth period characteristic library; performing phenotype comparison on healthy plants and diseased plants, and establishing an anti-bacterial wilt early warning model; performing real-time monitoring according to the early warning model to obtain a risk early warning result; performing growth period tracking based on an early warning result, and establishing a resistance scoring system; strain stability parameters are obtained through environmental response analysis; and finally determining excellent strains to form a bacterial wilt resistant breeding scheme. By establishing a data monitoring and analysis system in the whole growth period, dynamic evaluation and early warning of the bacterial wilt resistance of the plant are realized, and the accuracy and efficiency of bacterial wilt resistance variety breeding are improved.

The invention discloses an intelligent agricultural unmanned aerial vehicle inspection and data analysis system, which belongs to the field of unmanned aerial vehicle inspection and data analysis systems, and can simultaneously pop up corresponding drug types and dosage information for farmers according to the identified diseased plant types and pest types in a response measure link after pest and disease damage identification. According to the method and the system, a corresponding pesticide sales merchant platform link is established, so that a farmer can perform prevention and control operation in time, a mode of automatically matching a sales merchant link and popping up the sales merchant link to a hand-held terminal by utilizing a block chain technology is utilized, transaction security and traceability are ensured, an intelligent contract is introduced to realize a purchase automation process, transaction efficiency and coherence in a response measure link are improved, and the method and the system are convenient for farmers to perform prevention and control operation. The requirements of modern agriculture on efficient and accurate pest control are met.

The invention relates to the technical field of image or video recognition or understanding, and discloses an areca yellows early warning method based on regular economic forest multi-dimensional symptom analysis, in the method, the unique morphology of areca and various morphological changes which are invisible under trees but visible in remote sensing during the period that areca suffers from yellows are fully utilized, and the areca yellows early warning effect is achieved. And the multiple symptoms are combined to form a multi-symptom matching degree, so that the misrecognition problem can be eliminated in an auxiliary manner when specific symptoms exist. When the specific symptoms do not exist, whether the disease of the current areca-nut forest belongs to the infectious disease or not is indirectly judged according to the distribution characteristics of the multi-symptom matching degree in time and space by utilizing the distribution characteristics and the disease course development rule when the areca-nut is cultivated as an economic arbor, and if yes, the disease of the current areca-nut forest belongs to the infectious disease; and considering that the areca yellows occupy a large proportion in the areca infectious diseases, the pathogen detection cannot be infeasible due to entrainment of a large number of irrelevant diseased plant samples when the pathogen detection is carried out at the moment. The above points are combined to realize early warning of areca yellows.

The invention discloses a PCR (Polymerase Chain Reaction) detection specific primer for rhizoctonia solani AG4HG-III (Ribonia solani AG4HG-III) and a corresponding detection method of the rhizoctonia solani AG4HG-III (Ribonia solani AG4HG-III). A pair of PCR specific amplification primers is designed according to an ITS (internal transcribed spacer) gene sequence of the millet rhizoctonia solani AG4HG-III: an upstream primer wk-15 '-GGTATTCCTTGGAGCATGCCTG-3', a downstream primer wk-15 '-GGTATTCCTGCCTG-3', a downstream primer wk-15 '- And a downstream primer wk-25 '-TGGCCACCCTCCCAAACTC-3' is shown in the description. Through PCR (polymerase chain reaction) amplification, a specific 232bp band can be amplified in the millet rhizoctonia solani AG4HG-III pathogen and a millet diseased plant infected by the millet rhizoctonia solani AG4HG-III. The detection method provided by the invention can be applied to detection of the millet rhizoctonia solani AG4HG-III in millet plants in millet production, provides early warning for distribution and occurrence of the millet rhizoctonia solani AG4HG-III in a millet field, provides a theoretical basis for prevention and treatment and diagnosis of the millet rhizoctonia solani, and has a very good application prospect.

The present invention relates to a highly effective, broad-spectrum anti-plant viral disease pharmaceutical composition and its application. The active ingredients of the anti-plant viral disease pharmaceutical composition include chlorin iron and lentinan; wherein the weight ratio of chlorin iron to lentinan is 1:6000 to 4:1. When a certain concentration of the chlorin iron and lentinan pharmaceutical composition is applied to plants, the two active ingredients exert a synergistic effect, alleviating symptoms of diseased plants, reducing disease indexes, and reducing viral accumulation in the plants. The plant anti-viral disease pharmaceutical composition is a biological agent that is environmentally friendly, safe, and environmentally friendly. It has important application prospects in combating plant viral diseases, preventing and controlling plant diseases caused by plant viruses, and improving plant quality.

This invention belongs to the field of biodetection technology, specifically relating to a primer set, kit, and application for detecting *Alternaria solani* brown spot disease. The base sequences of the primer set are shown in SEQ ID NO.1~SEQ ID NO.5. Based on the primer set, this invention utilizes loop-mediated isothermal amplification technology for the rapid detection of *Alternaria solani*, accurately detecting the fungus from the complex pathogenic environment in diseased plant tissues. The rapid detection system described in this invention exhibits high specificity and sensitivity, with a detection limit of 0.246 fg / μL for *Alternaria solani* DNA. Using the rapid detection system provided by this invention, *Alternaria solani* can be detected rapidly, conveniently, accurately, and sensitively from field samples within 45 minutes, which is simpler and more efficient than traditional symptom identification methods and ordinary molecular detection methods.

The invention discloses a method for ultra-low temperature preservation and detoxification of pinellia ternata, comprising material culture, loading treatment, vitrification treatment, ultra-low temperature treatment, thawing and warming treatment, unloading treatment and regeneration plant culture. The pinellia ternata vitrification ultra-low temperature preservation technology system established by the invention can be applied to the preservation of pinellia ternata germplasm resources. Compared with field preservation and delayed growth preservation technology, the technology can greatly save manpower and material resources, is easy to operate, is not easily attacked by natural disasters, does not need to transfer plant materials regularly, occupies a small space, has low preservation cost, long preservation time, is genetically stable, and can preserve pinellia ternata germplasm for a long time; the technology can also be applied to the detoxification of pinellia ternata plants. After detoxification of test tube tubers of second-generation diseased plants of pinellia ternata, it was found through experimental verification that the detoxification rate of soybean mosaic virus (SMV) was 85.7%, and the detoxification rate of cucumber mosaic virus (CWV) was 57.1%, and the detoxification effect was better than that of commonly used heat treatment and stem tip detoxification.

The invention discloses a greenhouse crop disease image segmentation method and system, relates to the technical field of image processing of ground scenes, solves the problems of low segmentation precision and the like in agricultural scenes with complex disease spot forms and the like in the prior art, and improves the segmentation precision, the processing speed and the robustness. Disease images of greenhouse crop disease plants are obtained and preprocessed; performing graying and non-local mean filtering processing on the disease image to obtain a two-dimensional histogram; taking the maximized two-dimensional Kapur entropy function as a target function, and segmenting the two-dimensional histogram by using a Kapur entropy threshold method to obtain an initial threshold set; searching the initial threshold value set by utilizing an improved rime algorithm to obtain an optimal threshold value set; and carrying out multi-threshold segmentation to obtain a disease image in which a lesion area is segmented, and completing greenhouse crop disease image segmentation. The method is suitable for processing strawberry disease images in the field of greenhouse crop disease image processing.

The invention provides a tobacco and sweet potato relay intercropping field planting method and application thereof, and belongs to the technical field of agricultural planting. The planting method provided by the invention comprises the following steps: after tobacco is harvested, intensively burning diseased roots, diseased plants and weeds in a field, deeply ploughing soil in winter, carrying out soil drying and sterilization, applying an organic fertilizer or a special fertilizer for sweet potatoes by adopting a strip application mode, carrying out tobacco and sweet potato intercropping by adopting a single-side opposite planting mode, applying a bacillus siamensis XZ92 bacterial liquid and a bacillus velezensis XZ93 bacterial liquid to rhizosphere of the intercropped tobacco, and carrying out intercropping on the tobacco and the sweet potatoes by adopting a single-side opposite planting mode. And pouring methyl jasmonate liquid into the tobaccos, and supplementing trace elements in stages to finish planting. The comprehensive prevention and control system for the tobacco bacterial wilt is constructed by optimizing the relay intercropping space layout of tobacco and sweet potatoes, cooperatively applying strains with specific functions and methyl jasmonate and designing a staged nutrient supply scheme.

The invention discloses a hawthorn disease identification method based on a deep convolutional neural network and a disease image, and is applied to the technical field of hawthorn disease prevention and control. Comprising the following steps: collecting hawthorn disease image data as a training sample, distinguishing healthy plants and disease plants in a manual labeling manner, and refining to disease categories and disease degrees; carrying out data cleaning, data enhancement, data set expansion and normalization processing, constructing and training a deep convolutional neural network model for disease identification, and testing the detection performance by adopting a multi-dimensional evaluation index; and acquiring an image of a to-be-detected hawthorn plant, and inputting the image into the hawthorn disease identification model for real-time identification. According to the method, the pre-trained deep convolutional neural model is combined with the multi-scale data enhancement strategy and the adaptive transfer learning technology, the hawthorn disease intelligent identification system for the complex plant image scene is constructed, high-precision identification and automatic efficient detection of multiple diseases of hawthorns can be realized, and the real-time monitoring requirement of an orchard is met.

The invention belongs to the technical field of biological detection, and particularly relates to a primer group and a kit for detecting new plum brown spot and application of the primer group and the kit, and base sequences of the primer group are shown as SEQ ID NO.1-SEQ ID NO.5. Based on the primer group, the loop-mediated isothermal amplification technology is used for rapid detection of the alternaria nepalensis, and the alternaria nepalensis can be accurately detected from a complex pathogenic bacterium environment in diseased plant tissues. The rapid detection system disclosed by the invention is good in specificity and high in sensitivity, and the detection limit of the DNA of the alternaria nepalensis is 0.246 fg / mu L. By utilizing the rapid detection system provided by the invention, the alternaria nepalensis can be rapidly, simply, accurately and sensitively detected from a field sample within 45 minutes, and compared with a traditional symptom recognition method and a common molecular detection method, the rapid detection system is simpler and more efficient.

The utility model relates to a remote monitoring device for diseased plants in agricultural plants, including a bottom plate and a transparent sleeve, wherein the bottom plate is a convex structure, and the bottom end of the transparent sleeve is rotatably sleeved on the periphery of the bottom plate; an observation hole is provided on one side of the transparent sleeve, and a monitoring camera is slidably arranged in the observation hole. The utility model can perform 360-degree diagnosis and monitoring of diseased plants in all directions through the rotation of the monitoring camera and the transparent sleeve, and the monitoring camera can be remotely controlled to facilitate remote diagnosis of diseased plants, and through the monitoring of the monitoring camera, the image can be magnified and observed during observation, and the diseased plants can be clearly displayed on the remote screen to facilitate diagnosis of the diseased plants and improve diagnostic efficiency.

The invention relates to the field of intelligent recognition and mechanical arm control, in particular to a multi-axis mechanical arm precise insect suction control method based on low-power-consumption intelligent recognition, and aims to solve the problems that in the existing multi-axis mechanical arm insect suction control process based on intelligent recognition, a multi-axis mechanical arm is high in power consumption in the operation process; in order to solve the problems of high-speed action execution and large-amplitude shaking at the execution tail end due to wrong frames, the invention provides a multi-axis mechanical arm precise insect suction control method based on low-power-consumption intelligent recognition, and the method comprises the following steps: a long-distance search stage: carrying out long-distance large-range search on a plant target; in the middle distance approaching stage, after the plant leaf target is searched, a tail end self-adaptive anti-shake suppression method is used for controlling the mechanical arm to move to keep aligning with the plant leaf target; in the short-distance adsorption stage, the ID of a single diseased plant leaf target is locked, a tail end self-adaptive anti-shake suppression method is used for controlling a mechanical arm to move, finely adjust and get close to the diseased plant leaf target, and adsorption is executed.

The utility model provides a diseased plant removing device for konjak planting, and relates to the technical field of diseased plant removing devices, the diseased plant removing device comprises a machine body, a rotating motor is arranged in the machine body, an output shaft is arranged on one side of the rotating motor, a main switch button on the surface of the machine body can be turned on during use, and a CCD camera is started when the main switch button is turned on; when the CCD camera is turned on, a captured object is converted into an image signal, then the image signal is sent to the special image processing system, and the image signal is converted into a digital signal according to information such as pixel distribution, brightness and color; the image system performs various operations on the signals to extract features of a target, then realizes an automatic identification function according to a preset allowable range, and then controls starting of the rotating motor according to a discrimination result, when disqualification is found, the CCD camera controls the rotating motor to start, and when the rotating motor starts, the arc blade rotates through the output shaft, and the target is detected. The rotating arc-shaped blade is used for shoveling diseased plants, so that the problem that manual removal wastes time and labor is solved.

The application discloses long-chain non-coding RNA lncRNA109897 for promoting walnut resistance to anthracnose and application thereof. The application provides an RNA molecule, which is a lncRNA and is named as LncRNA109897, as shown in sequence 1 of a sequence table. The application also provides a DNA molecule, which is a DNA molecule for coding LncRNA109897 and is named as LncRNA109897 gene, as shown in sequence 3 of the sequence table. The application also protects an anti-disease plant breeding method, which comprises the following steps: introducing the LncRNA109897 gene into a starting plant to obtain a transgenic plant with higher disease resistance than the starting plant. The application has great application and popularization value for plant anthracnose resistance breeding, in particular, walnut anthracnose resistance breeding.

The invention discloses alcaligenes faecalis NRM3 and application of the alcaligenes faecalis NRM3 in prevention and treatment of tobacco root rot, and belongs to the technical field of biological prevention and treatment of tobacco diseases. The alcaligenes faecalis NRM3 is separated from tobacco, is a tobacco endophytic bacterium and is preserved in the China Center for Type Culture Collection (CCTCC), and the preservation number is CCTCC NO: M 20251578. The alcaligenes faecalis NRM3 can effectively inhibit the growth of pathogenic bacteria of the tobacco root rot, can effectively prevent and treat the tobacco root rot, can remarkably reduce the morbidity and the disease index of diseased plants, also has a positive promotion effect on the germination and growth of tobacco seeds, and has good application potential in the tobacco industry.

The utility model discloses a konjak diseased plant removing device which comprises a movable base, stand columns are fixedly connected to the four corners of the top of the movable base, a top plate is fixedly connected to the tops of the stand columns, a diseased plant collecting tank is connected to the top of the movable base, a diseased plant shoveling mechanism is arranged at the end of the top plate, and a diseased plant transferring mechanism is arranged at the bottom of the top plate. The diseased plant shoveling mechanism comprises a fixing plate, a U-shaped fixing frame, a lifting plate, an inclined plate, a second electric lifting rod, a supporting plate, a second electric telescopic rod and a shoveling plate, the end of the top plate is fixedly connected with the fixing plate, the bottom of the fixing plate is fixedly connected with the U-shaped fixing frame, and the top of the U-shaped fixing frame is fixedly connected with the second electric lifting rod. According to the diseased konjak plant removing and processing device, diseased plants in planting can be shoveled out through the diseased plant shoveling mechanism, the shoveled diseased konjak plants can be clamped and transferred into the diseased plant collecting tank to be collected through the diseased plant transferring mechanism, the overall structure is compact, and a large amount of manual labor cost is saved.

The utility model relates to the technical field of plant tissue sampling, and discloses a plant diseased leaf sampling tool which comprises a mounting cylinder and a sampling mechanism arranged on the mounting cylinder, the sampling mechanism comprises an inserting rod, two adapter rods and two sampling discs, the inserting rod is movably inserted in the mounting cylinder, the upper end of the inserting rod extends out of an upper cylinder opening of the mounting cylinder, and the two adapter rods are connected with the two sampling discs. Two through holes are formed in the lower part of the insertion rod, the two adapter rods are arranged in the two through holes in a penetrating manner, the middle parts of the two adapter rods are fixedly connected with the inner walls of the through holes, the two sampling discs are rotationally mounted on the two adapter rods respectively, torsional springs are arranged between the sampling discs and the adapter rods, and a plurality of barbs are arranged at the lower ends of the two sampling discs. A pressing block is fixedly mounted at the upper end of the inserting rod, and a containing groove is formed in the upper end of the mounting cylinder. The objective of the utility model is to solve the problem that at present, when sampling work is carried out, diseased plant tissues are removed through tweezers and scissors, and then the diseased plant tissues are cut into required sizes, so that tissue samples are easy to fall off due to misoperation.

The application discloses a primer composition for detecting Pythium sylvesterianum based on LAMP technology and application thereof, and belongs to the technical field of microorganism detection; the primer composition is a LAMP primer composition designed according to a specific sequence shown in SEQ ID NO. 1. The application adopts a method for rapidly detecting Pythium sylvesterianum, the pathogenic bacterium of stem base rot of raw ginger, based on loop-mediated isothermal amplification technology, and establishes a perfect detection and field real-time detection system for soil samples, water source samples and diseased plant samples, thereby opening up a new train of thought and method for the measurement and prediction of field crop diseases, winning valuable time for the prevention and control of related diseases, and reducing the loss caused by diseases to a certain extent.

The invention relates to the technical field of crop disease prevention and control, and discloses a potato late blight prevention and control device and a prevention and control method.The potato late blight prevention and control device comprises a mounting frame, and the mounting frame is provided with a dynamic cross detection assembly, a re-checking assembly, a telescopic assembly, a spraying assembly and an isolation assembly; the prevention and control method of the potato late blight prevention and control device comprises the following steps: S1, regular inspection; s2, carrying out primary identification and positioning; s3, identifying and positioning again; s4, determining the position of a diseased plant; s5, positioning and re-checking; s6, unfolding and isolating; and S7, covering and spraying. Through cooperative use of the dynamic cross detection assembly, the re-checking assembly, the telescopic assembly, the spraying assembly and the isolation assembly, the whole set of system works cooperatively, potato late blight can be monitored, prevented and controlled efficiently and accurately, the monitoring efficiency and the protection effect are improved, loss caused by diseases is reduced, and the yield and quality of potatoes are guaranteed.

The present application relates to the technical field of fruit tree virus-free rapid propagation, and particularly relates to a method for virus-free propagation of passion fruit. The method comprises the following steps: inoculating stem tips of passion fruit into a callus induction medium to induce callus, obtaining callus; inoculating the obtained callus into a bud differentiation induction medium to induce regenerated buds, obtaining regenerated buds; inoculating the obtained regenerated buds into a strong seedling culture medium to culture strong seedlings, and realizing virus-free propagation of passion fruit. The above steps are referred to as a virus-free propagation cycle, and the virus-free propagation efficiency is 69%. The diseased plants that are still positive after detection after one cycle of virus-free propagation are subjected to a second cycle of virus-free propagation according to the above method, and the virus-free propagation efficiency can reach 95%.

The invention discloses mushroom cultivation equipment and an environment monitoring control system, and relates to the technical field of mushroom cultivation, the mushroom cultivation equipment comprises a fixed frame, a top frame is fixedly connected to the top of the fixed frame, a movable frame is arranged in the top frame, a fixed sleeve is fixedly connected to the interior of the movable frame, a neck bush is movably connected to the interior of the fixed sleeve, and the neck bush is fixedly connected to the top of the fixed frame. A piston sleeve is slidably connected to the interior of the neck bush, a supporting plate is rotatably connected to the outer side of the bottom end of the piston sleeve, a piston plate is slidably connected to the interior of the piston sleeve, a sliding rod is fixedly connected to the bottom of the piston plate, an arc-shaped plate is rotatably connected to the bottom end of the sliding rod, and a transverse plate is fixedly connected to the bottom end of the piston sleeve; according to the mushroom cultivation equipment and the environment monitoring control system, mushroom with germs can be pulled out easily, diseased plants are prevented from spreading germs to infect other healthy mushrooms in a plant, the diseased plants are detected in time, response measures are taken, and loss is reduced.