3333 results about "Leaf blade" patented technology

The invention provides a farmland disease and pest monitoring method and device and a storage medium, and relates to the technical field of agriculture, the method comprises the steps: dividing a farmland into a plurality of sub-regions, obtaining an infrared spectrum image, and segmenting the infrared spectrum image into corresponding sub-images; and calculating a vegetation stress index based on the reflectivity of the insect pest related characteristic wave band, and screening high-risk sub-regions. Risk plants are randomly extracted in a high-risk area, physiological parameters of leaves are collected, physiological health indexes of the leaves are constructed, and dynamic correction is carried out through an environment regulation coefficient according to environment data. Using the trained network model to identify the risk sample leaf scab, and calculating the scab area index. And finally, fusing the corrected leaf physiological health index and the scab area index, calculating a normalized risk value through a risk assessment function, and dividing the normalized risk value into four risk levels. Through multi-stage fusion of spectral analysis, physiological parameter correction and deep learning scab detection, accurate early warning of diseases and insect pests is realized, and the monitoring efficiency is improved.

An embodiment of an improved fishing lure comprises a fishing lure body having an approximately flat surface on the top side or bottom side of the body and a blade statically affixed to the approximately flat surface. The lure body may include a recess having a wall and a base, wherein the approximately flat surface is at the base of the recess, and wherein around a portion of the perimeter of the recess at least one lip extends inward from the wall of the recess. The blade is preferably disposed in the recess and below the at least one lip. In some embodiments, the approximately flat surface has a float angle between about 30 degrees and about 90 degrees relative to horizontal, and more preferably between about 35 degrees and about 45 degrees relative to horizontal.

The invention relates to the technical field of agricultural intelligent monitoring, in particular to a crop growth detection system and method based on machine vision, and the system comprises an image collection module, a morphological feature capture module, a growth trend judgment module, an abnormal region marking module and a state information output module. According to the method, crop images are collected through a multi-angle camera, leaf contours, stem bending and plant spacing are extracted, multi-dimensional modeling of morphology is realized, structural change identification is enhanced, time sequence comparison of key morphological characteristics is realized, identification precision and time efficiency are improved, leaf and stem change trends are continuously analyzed, offset is quantified, and growth abnormity is early warned in advance; health degradation identification is combined with fluctuation area marking, dynamic monitoring is achieved, high-risk positioning is carried out on a time overlapping area, time-space locking is enhanced, precise management is assisted, the process is from image analysis to abnormal focusing, an information reasoning chain is established, and the monitoring precision and response efficiency are remarkably improved.

The invention belongs to the technical field of image processing, and discloses a grape leaf AI grading processing method and system based on computer vision. Comprising the following steps: acquiring image data of grape leaves, and performing variety label marking and image optimization to obtain a clear leaf image data set; sequentially performing feature extraction and feature fusion on the clear leaf image data set to obtain fused disease condition features and fused growth condition features; constructing a leaf evaluation framework capable of being adjusted in real time based on the fused disease condition features and the fused growth condition features; performing image evaluation on the clear leaf image data set by using a leaf evaluation framework to obtain a disease degree evaluation index and a growth condition evaluation index, and performing disease degree grading and growth condition grading on the clear leaf image data set based on the disease degree evaluation index and the growth condition evaluation index; obtaining a grape leaf grading result; accurate grading of the grape leaves is achieved, and the industrial production efficiency is improved.

The invention relates to the technical field of ecological environment monitoring and forest remote sensing, in particular to a forest plant stoichiometric characteristic spatial-temporal change intelligent analysis method, which comprises the following steps: S1, acquiring spectral reflectivity and element concentration values of plant leaves in a target area; s2, performing space-time registration processing; s3, constructing a three-dimensional space-time matrix, and generating a space-time cube with a dynamic weight identifier; s4, calculating the space-time gradient variation of the carbon-nitrogen-phosphorus ratio in each space unit; s5, performing feature decoupling on the space-time gradient variation; and S6, generating a stoichiometric characteristic three-dimensional atlas with altitude-time double coordinate axes. According to the method, by constructing the multi-factor driven three-dimensional space-time analysis model, decoupling analysis of long-term trend and short-term fluctuation of forest plant stoichiometric characteristics is achieved, the element flux mutation threshold value at the terrain turning position is accurately recognized, and the dynamic monitoring capacity of the ecological process is effectively improved.

The invention belongs to the field of agricultural information perception, and relates to a plant leaf scab segmentation method and system based on RGB-D cross-modal fusion, and the method comprises the steps: collecting a color image and a depth image of a crop through a synchronous collection device; registering the color image and the depth image to obtain a registered color image and a corresponding registered depth image; constructing an initial segmentation network, and performing model training on the initial segmentation network; the initial segmentation network comprises a cross attention-based feature aggregation module and an attention-guided adaptive feature fusion module; inputting the registered color image and the registered depth image into a trained segmentation network for segmentation to obtain a segmentation result; through heterogeneous data fusion of a depth sensor and a visible light camera, a multi-dimensional feature system covering two-dimensional textures and three-dimensional deformation is constructed; in combination with a cross-modal feature complementation mechanism, the recognition robustness of weakly dominant diseases and insect pests is enhanced, and the segmentation precision in a complex illumination and branch and leaf shielding scene is significantly improved.

The invention relates to the technical field of intelligent agricultural equipment, in particular to a tomato disease diagnosis method based on multi-modal data analysis, which comprises the following steps of: 1, synchronously acquiring and preprocessing multi-modal data, synchronously triggering a hyperspectral imaging device and a microscopic camera, respectively acquiring a plant canopy hyperspectral image and a stem microscopic image, and acquiring a plant canopy hyperspectral image and a stem microscopic image; meanwhile, temperature, conductivity and dissolved oxygen environment parameters are continuously collected in the root zone; 2, self-adaptive feature extraction and fusion in the growth stage are carried out, reflectivity correction and leaf segmentation are carried out on the hyperspectral image, and leaf surface spectrum curve features are extracted; step 3, hybrid model construction and space-time analysis: constructing a hybrid model comprising spectrum, microscopy and environment analysis networks, and dynamically adjusting each network weight through a gating network; and 4, generating a disease decision. The method can realize accurate, efficient and real-time tomato disease diagnosis, has high practical value, and can effectively improve the disease prevention and control capability in agricultural production.

The invention relates to the technical field of garden monitoring, in particular to a landscaping monitoring system and method, and the system comprises a collection module which is used for obtaining multi-angle images of a garden in stages, and selectively collecting the images according to a correlation judgment result; the analysis module is used for extracting vegetation indexes, disease targets, leaf health features and falling object state features; the identification selection module is used for generating a dynamic acquisition strategy according to the relevance abnormal index and triggering the acquisition module to directionally acquire the second-level image; the weighted fusion module is used for performing adaptive weighted fusion on the multi-source features and calculating a comprehensive wilt risk level; the early-warning module is used for generating early-warning signals and early-warning grades, the view limitation of traditional single-view-angle monitoring is broken through, large-range vegetation vitality abnormal areas can be rapidly screened, detail features of trunk diseases, low leaf withering and microscopic disease spots can be accurately captured, and the comprehensiveness and reliability of early withering recognition are remarkably improved.

The invention relates to the technical field of artificial intelligence, in particular to a pest and disease identification method and system based on image processing and a medium, and the method comprises the steps: obtaining an original image of a plant leaf, and carrying out the preprocessing of the original image, and obtaining a preprocessed image; performing scab region segmentation on the preprocessed image by using an improved U-Net model to obtain a contour and a position of a scab; carrying out feature extraction on the segmented scab region, extracting deep semantic features through a pre-trained ResNet-50 network, and carrying out splicing fusion on the deep semantic features and color features and shape features of the scab to form a comprehensive feature vector; inputting the comprehensive feature vector into an integrated classifier based on XGBoost to carry out disease and insect pest type identification, and outputting disease and insect pest types and corresponding probabilities; the accuracy of pest and disease prediction can be improved.

The invention relates to the technical field of intelligent agriculture, in particular to an intelligent disease and pest monitoring and prevention system which comprises an environment self-adaption module, a spectrum collection module, a dynamic threshold value analysis module, a prevention decision module, an execution terminal and a data storage module. A polarization filter is adopted to suppress reflection of light on the blade surface to obtain a spectrum fusion image; the dynamic threshold value analysis module is used for establishing a dynamic proportion threshold value of the insect spot area and the medicinal material biomass by adopting a U-Net network in combination with a growth cycle recognition algorithm so as to obtain graded insect pest evaluation parameters; and the prevention and control decision module is used for combining the graded insect pest evaluation parameters with the environmental parameter set and generating a prevention and control scheme by adopting a pesticide application decision tree model based on northern climate characteristics. According to the invention, through dynamic environment adaptive adjustment and northern climate optimization pesticide application decision, efficient and accurate prevention and control of diseases and insect pests in a complex agricultural environment are realized.

The invention belongs to the technical field of agriculture, particularly relates to a cranberry water demand dynamic sensing system and a method thereof, and aims to solve the problems that an existing traditional irrigation method is often based on a fixed time table or simple soil humidity measurement, the actual water demand condition of cranberries cannot be timely and accurately reflected, and insufficient irrigation or excessive irrigation is easily caused. In order to solve the problems that in the prior art, water resources are wasted, and the growth and yield of cranberries are possibly influenced, the invention provides the following scheme: the system comprises a monitoring module, a control module and a display module, wherein the monitoring module comprises stem flow rate, leaf water potential, soil water content at different depths and positions, air temperature and humidity, illumination intensity and wind speed data; according to the cranberry water demand monitoring system, accurate monitoring, real-time evaluation and scientific prediction of the cranberry water demand condition can be achieved, then a reasonable irrigation decision and environment regulation and control are guided, and the irrigation efficiency and the water resource utilization efficiency are improved.

The invention relates to the technical field of fish protection in water conservancy projects, and in particular to a fish passing system suitable for a low-head overflow dam and an operation method thereof, comprising a lock chamber, an upper lock head and a lower lock head arranged at two ends of the lock chamber, gates being installed on the gate heads, and a diversion port being opened on the gates; a main rotating blade is fixedly arranged near the diversion port in the lock chamber, reciprocating components are symmetrically arranged on both sides of the main rotating blade, the reciprocating components include a rotating rod and a guide rod arranged in parallel, and the main rotating blade is connected to the rotating rods of the reciprocating components on both sides through a transmission component; a reciprocating plate is arranged on the rotating rod, the reciprocating plate is slidably sleeved on the guide rod, a rotatable flipping rod is arranged on the reciprocating plates opposite to each other on both sides, and a disturbance frame is fixed on the flipping rod; the flipping rod drives the disturbance frame to flip together, so that the disturbance frame is switched between a horizontal state and a vertical state; the water flow at the diversion port is subjected to power conversion, the reciprocating plate on the rotating rod is driven to reciprocate linearly, and the migratory fish is driven to move upward to the upstream waters by automatically flipping the disturbance frame.

The invention discloses a method and a system for reflecting a growth state by a spectral curve of a plant leaf under salt mist stress and a storage medium, and relates to the field of plant growth monitoring. Processing the collected leaf image, extracting a leaf main body area, removing an interference part, and matching the filtered original spectral data to obtain target spectral data of the leaf main body area; the method comprises the following steps: combining target spectral data of a leaf main body area with leaf moisture content data, constructing a spectral analysis model by adopting a partial least square method, taking the leaf moisture content as a covariable into the spectral analysis model, peeling off the interference of leaf moisture change on the spectral data, and calculating the leaf moisture content. And finally obtaining a target spectrum curve of the plant leaf under the salt mist stress. A characteristic wave band corresponding to the target spectrum curve is extracted, a plant growth index is constructed according to the characteristic wave band, and the plant growth index is used for reflecting the growth health state of the plant. The problems that traditional monitoring is high in subjectivity, insufficient in precision and low in efficiency are solved.

The invention relates to the technical field of agricultural management, in particular to a smart farm environment regulation and control method and system based on big data analysis, and the method comprises the following steps: obtaining an instantaneous temperature value of the upper surface of a leaf and an instantaneous temperature value of the lower surface of the leaf through an infrared temperature sensor, obtaining an instantaneous value of stomatal conductance through a stomatal conductance sensor; and acquiring a water vapor pressure difference value of the air cavity through a water vapor pressure sensor, aligning a time sequence by adopting a multi-source data fusion algorithm, eliminating noise, and generating a dynamic physiological data set. According to the method, the leaf temperature difference, the air hole conductance and the air cavity water vapor pressure difference are collected, a real-time dynamic data set is constructed, a temperature difference amplification signal is extracted, transpiration enhancement triggering, wind speed increasing, water mist particle size decreasing and wind speed and particle size linkage regulation and control are analyzed in combination with the trend, a regulation and control weight is constructed by introducing multiple regression analysis, and the wind speed and the particle size are dynamically regulated according to the weight. A leaf temperature difference regression base line is guaranteed, the regulation and control accuracy and physiological adaptability are improved, and the environment self-adaptive regulation capability is enhanced.

Seed treatment systems with a mixing reservoir including a tank, a circulation mechanism positioned within the tank, and a controller coupled to the circulation mechanism, where the circulation mechanism includes a plurality of vanes configured to rotate about an axis within the tank, and where the controller is configured to mix seed treatment components within the tank in one or more mixing cycles by rotating the plurality of vanes within the tank, each mixing cycle including a first mixing operation in which the plurality of vanes rotate in a first direction about an axis for a first time period, and a second mixing operation in which the plurality of vanes rotate in a second direction about the axis opposite to the first direction for a second time period. Methods of use of the disclosed systems, e.g., for treating plant seeds, and agricultural compositions produced thereby are also provided.

The invention relates to the field of the centrifugal fan industry, in particular to an impeller with multi-element coupling bionic blades and a centrifugal fan, the impeller comprises a front disc and a rear disc, an exhaust inlet is formed in the middle of the front disc, a plurality of blades are arranged on the rear disc in a surrounding array mode, and the blades comprise long blades and short blades which are evenly distributed at intervals; the long blades and the short blades are all metal plate type single-arc multi-element coupling bionic blades. According to the impeller with the multi-element coupling bionic blades and the centrifugal fan, according to the principle of a bionic flow control technology, the front edge of the long blade adopts a streamline structure characteristic of simulating the outer side edge of a shark tail fin, and the tail edge of the blade adopts a typical arc tooth structure characteristic of simulating the feather front edge of a tenon wing; the common problems of small flow, low pressure, low efficiency and large noise of a centrifugal fan in the prior art are solved.

The invention discloses a method for predicting plant photosynthetic ability by using plant leaf traits, and relates to the technical field of agricultural science, and the method comprises the following steps: obtaining image data of a target plant leaf in a natural state through a high-resolution imaging device, and synchronously recording environment parameter information during collection; extracting multi-dimensional feature parameters of the leaf based on the image data, wherein the multi-dimensional feature parameters comprise a color index, a texture feature, an area, a thickness estimation value and an edge contour form; and carrying out stress feature identification on the character data by utilizing an association rule of the environmental parameters and the leaf characters. According to the invention, by introducing a stress identification and data correction mechanism, the accuracy of photosynthetic capability prediction is improved; the method has good environmental adaptability and crop universality, and is suitable for various agricultural scenes; and a prediction feedback closed-loop system is constructed, continuous optimization and intelligent adjustment of the model are realized, and the stability, reliability and practical application value of the system are remarkably enhanced.

The invention discloses a multi-layer liftable three-dimensional planting shed frame which comprises a planting shed frame body, the planting shed frame body comprises a mounting shell, one side of the mounting shell is fixedly connected with a supporting top plate with a built-in light supplementing lamp, and the top of the supporting top plate is fixedly connected with a water storage tank; the invention belongs to the technical field of agricultural planting, and aims at solving the problems that in the prior art, when vegetables on the upper layer grow flourishing, illumination of the vegetables on the lower layer is prone to being shielded, and consequently leaves of the vegetables on the lower layer become yellow and grow slowly due to insufficient illumination. The technical effects are that through the arrangement of the layer height circulation adjusting mechanism, the upper layer vegetable planting rack can be automatically and regularly adjusted to the lower layer and the lower layer vegetable planting rack can be automatically and regularly adjusted to the upper layer in the vegetable growth process, so that the normal growth of the lower layer vegetables is prevented from being influenced by the fact that the vegetables always located on the upper layer shield light; and the illumination uniformity of each layer of vegetable planting frame is improved.

The invention discloses an apple anthracnose leaf blight recognition five-dimensional data fusion method based on a patrol robot, relates to the technical field of anthracnose leaf blight recognition, and solves the problems of limited sensing dimension, large illumination interference and inaccurate spatial positioning in the prior art. Comprising the following steps: S1, acquiring surface curvature characteristics of apple leaves, collecting RGB-D images of the leaves, constructing a three-dimensional topological structure of the leaves, and positioning scab space distribution; s2, acquiring spectral reflection information of apple leaves, quantifying biochemical components of chlorophyll a and carotenoid, and constructing a vegetation index feature set sensitive to diseases; s3, apple tree canopy temperature information is collected, a transpiration anomaly detection model is constructed, and multi-modal fusion of thermal infrared and point cloud data is realized; and S4, integrating spatial distribution, spectral reflection and thermal radiation information, constructing a five-dimensional phenotypic characteristic matrix model, and comprehensively analyzing apple phenotypic characteristics. According to the method, the recognition accuracy under the conditions of blade shielding, uneven illumination, blade posture change and environment interference can be remarkably improved.

The invention relates to the technical field of agricultural irrigation, and discloses an intelligent agricultural water-saving irrigation and fertilization device which comprises an irrigation box, sliding rails, an irrigation assembly, a self-walking stirring assembly, a scraping and blowing assembly and a cylindrical filter part, the irrigation box is arranged on the two sliding rails, the cylindrical filter part is arranged in the irrigation box, the irrigation assembly is installed on one side of the irrigation box, and the self-walking stirring assembly is installed on the other side of the irrigation box. The spraying device is used for spraying water and fertilizer to crops; the self-walking stirring assembly comprises a rolling wheel, a rod type stirring piece and a driving piece. Water-soluble fertilizer water beads on the surfaces of seedlings are scraped and blown through the scraping and blowing assembly, water-soluble fertilizer attached to the surfaces of leaves and stalks of the seedlings can be effectively removed and shaken off to the bottoms of the seedlings, and therefore waste of the water-soluble fertilizer is reduced, meanwhile, the water-soluble fertilizer can directly act on root systems of the seedlings and is fully absorbed by crops, and the water-soluble fertilizer can be applied to the roots of the seedlings. The utilization rate of the water-soluble fertilizer is increased, and the problem of volatilization of nutritional ingredients caused by strong quick-acting property and short lasting period of the water-soluble fertilizer is reduced.

The invention discloses a noise reduction method of a bionic fish scale blade centrifugal pump, which comprises the following steps that a long and short blade centrifugal pump is selected for research, and the main design parameters of the long and short blade centrifugal pump are as follows: the specific speed ns is equal to 40.79, the rated flow Qd is equal to 10.6 m < 3 > / h, the lift H is equal to 34m, and the rotating speed n is equal to 2900r / min; a computational domain three-dimensional model of the long and short vane centrifugal pump is established through Creo8.0; in order to prevent backflow of inlet and outlet sections, ensure that fluid stably flows into an impeller and ensure the accuracy of a simulation result, extension pipelines are additionally arranged at an impeller inlet and a volute outlet of the centrifugal pump, the pipe diameter of the inlet extension section is 4 times that of the outlet extension section, and the pipe diameter of the outlet extension section is 8 times that of the inlet extension section; in order to verify the accuracy of a calculation result, a centrifugal pump experiment platform is built for external characteristic experiments; the bionic fish scale pit has the advantages that the dynamic and static interference between the impeller and the volute is reduced, the pressure fluctuation in the pump is stabilized, the amplitude fluctuation of a wave number-frequency spectrum and the energy region of a low wave number region are reduced, the migration of a wave number-frequency spectrum peak ridge is reduced, the curve change is gentle, and then the noise reduction effect is achieved.

The invention discloses a low-water-head water turbine with a flow guide wing bionic blade, which is provided with a variable pitch system for adjusting an included angle between a runner blade and an incoming flow direction, and a deflection control system for adjusting an included angle between a guide vane arranged on a bulb body and the incoming flow direction, the water flow impact acting force on the blades can be changed through the water flow impact acting force, the water flow impact acting force on the blades can be changed through the water flow impact acting force, and the water flow impact acting force on the blades can be changed through the water flow impact acting force. In addition, the blade of the runner of the hydraulic turbine set is the blade with the wave-shaped front edge, and a section protruding outwards is arranged in a pipeline for containing the bulb body and the runner, so that the water energy utilization rate of the hydraulic turbine set is further increased. The blade adopts a sine curve-shaped waveform front edge, and the structure simulates a convex shape on a fin-shaped limb of an underwater organism, so that the resistance in water is reduced, and the water energy utilization rate of a water turbine set is increased.

The invention discloses a sapling planting growth evaluation method based on image recognition parameter acquisition, relates to the technical field of sapling planting growth evaluation, and aims to solve the problem that the sapling survival rate is reduced due to inaccurate sapling growth cycle evaluation. According to the method, visual information is converted into quantitative data through single plant marking and feature binding, the objectivity and accuracy of growth state evaluation are greatly improved, a high-quality data foundation is laid for subsequent analysis, the leaf withering and yellowing risk is pre-judged through correlation of temperature fluctuation and soil humidity, a prospective management basis is provided for planters, and the method is suitable for large-scale popularization and application. According to the method, the timeliness and scientificity of growth regulation and control are remarkably improved, the withered and yellow risk of the leaves is pre-judged through correlation of temperature fluctuation and soil humidity, a prospective management basis is provided for planters, and the timeliness and scientificity of growth regulation and control are remarkably improved.

The invention relates to the technical field of image recognition, in particular to a method for recognizing the irrigation state of a plant growth area based on image recognition, which comprises the following steps: acquiring an image of the plant growth area, segmenting the plant area and extracting contour coordinate points of each leaf; and calculating the mean value of the ratios of the centroid spacing to the perimeter of each contour to obtain a leaf contour space distribution factor, and based on the leaf contour space distribution factor and the segmented plant region pixels. According to the method, by extracting the centroid position and the spatial structure feature of the leaf contour, the spatial distribution difference of each leaf in a plant area is quantified, and further through contour coordinate iteration alignment operation, more stable and unified group leaf shape features are obtained, and interference caused by leaf shape difference is reduced; meanwhile, precise quantification and symbiotic relationship analysis of a pixel color channel are adopted, spatial position information and color differences are combined, and a heterogeneity index of fusion of the leaf shape and color distribution is constructed.

The invention relates to the technical field of space life science, in particular to a multi-axis control and acoustic levitation combined microgravity environment simulation closed cultivation device and a control system.The multi-axis control and acoustic levitation combined microgravity environment simulation closed cultivation device comprises two vertical sliding rail mechanisms, a first rotating servo motor is arranged on each vertical sliding rail mechanism in a sliding mode, and an outer rotating frame is driven to rotate in the first direction; the second rotating servo motor is fixed to the outer rotating frame and drives the cultivation chamber connected with the inner rotating frame to rotate in the second direction, and the acoustic levitation device is installed in the cultivation chamber. According to the invention, random gravity disturbance is introduced through random sliding on the sliding rail, and a microgravity environment with coupled random gravity and rotating speed double factors is constructed in combination with random rotation of double shafts; according to the method, the influence of microgravity on plant leaf respiration under the condition of no heat convection and air shear force can be deeply researched, the influence of air heat convection and shear force can be inhibited, the space microgravity cultivation condition can be truly simulated, and a reliable platform is provided for ground plant space cultivation research.

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

The invention discloses a soil microbial fermentation device and a fermentation method, and relates to the field of microbial fermentation. A soil microorganism fermentation device comprises a fermentation tank and further comprises a cover plate detachably connected to the upper end of the fermentation tank; the material conveying barrel is positioned in the fermentation tank and is rotationally connected to the cover plate; the rotating sleeve is connected to the material conveying barrel in a sleeving mode, and a shifting rod is fixedly connected to the rotating sleeve; the motor drives the bevel gear for transmission, the linkage conveying barrel and the rotating shaft to rotate, and the electric telescopic rod is matched to drive the rotating sleeve to reciprocate, so that the three-dimensional stirring of the driving lever and the circulating conveying of the spiral blade are realized, a multi-dimensional stirring mode is formed, the material mixing uniformity is improved, the full contact of microorganisms and nutrient substances is promoted, and the fermentation efficiency and quality are improved; the elastic deflector rod and the counterweight ball can adaptively adjust the stirring range along with the rotating speed, eliminate stirring dead angles, accelerate the fermentation process, shorten the period, reduce the cost, and further optimize the fermentation effect and the product quality.

The invention provides a leaf image mode classification method and system for double cropping rice spike fertilization, and the method comprises the steps: collecting a first leaf image parameter array and a second leaf image parameter array at a preset time window of target double cropping rice and at a plurality of positions of a first leaf and a second leaf; carrying out image parameter discrete analysis on the parameter arrays to obtain a first dispersion and a second dispersion, and calculating to obtain a leaf pollution degree by combining a preset dispersion; and carrying out averaging processing and leaf pattern classification on the parameter array, and respectively obtaining two leaf pattern arrays based on the image parameters and the pollution degree, thereby determining a suitable leaf pattern and carrying out double cropping rice fertilization. The technical problem of insufficient fertilization recommendation accuracy on different fields due to insufficient test data volume in the prior art is solved, and the technical effects of realizing accurate regulation and control of the panicle fertilizer and improving the fertilization recommendation accuracy by analyzing pattern classification of double cropping rice leaf image parameters and pollution degrees are achieved.

The present application provides a kind of active helical pushing type gap straw cleaning wheel for straw returning, including active blade rotating shaft, right helical gap blade group and left helical gap blade group, and gap blade group includes multiple helical gap blades.The intersection of right helical gap blade and left helical gap blade is fixed together, and symmetric to each other.Gap blade group is fixed with active blade rotating shaft, and helical blade contacts soil during operation, and pushes straw on soil to both sides, and the size of helical gap blade outer diameter and the rotating speed of active blade rotating shaft are changed to improve the returning efficiency of straw.The gap depth of helical gap blade is consistent and staggered, to improve the quality of sowing belt straw cleaning, form a more clean sowing belt, and the soil driven by blade can flow out of the gap to reduce the amount of soil.The present application efficiently cleans the straw on sowing belt under the premise of minimizing the amount of soil, improves the quality of no-tillage seeding, and is beneficial to crop yield increase.

The invention relates to the technical field of nursery stock transplanting, in particular to a garden landscape nursery stock transplanting device which comprises a vehicle body, an operation table is arranged at the front end of the vehicle body, a fixing seat is fixedly mounted at the front end of a rotating arm, a soil ball digging mechanism is arranged at the front end of the fixing seat, and an extension frame is fixedly mounted at the upper end of a stand; a tree crown wrapping mechanism is fixedly installed at the front end of the extending frame, a hydraulic pump is fixedly installed at the lower end of the stand, a movable frame is fixedly installed at the upper end of the hydraulic pump, a transverse moving rail is fixedly installed at the front end of the movable frame, a moving table is slidably installed at the upper end of the transverse moving rail, and a tree catching clamp mechanism is fixedly installed at the front end of the moving table. The crown is covered with the protective film, and moisture evaporation of leaves and branches can be remarkably reduced by covering the crown. In the seedling transplanting process, seedling trunks are clamped and fixed through the telescopic tree catching mechanism, and shaking caused by the influence of wind blowing and the like in the moving-out process is avoided.