2393 results about "Leaf blade" patented technology

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 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 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 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 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 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 application discloses a kind of imitated plant leaf hydrogel composite material and preparation method thereof, belong to bionic composite material field.The application first by colorant compounding preparation printing paste, and fabric is printed, obtain the green fabric that can realize to plant leaf " green peak " and " red edge " spectral characteristic simulation, and with green fabric simulation leaf structure in fence organization and skeleton;Then with biomaterial polyvinyl alcohol (PVA) as base material, join with strong hygroscopic monomer and crosslinking agent, initiator blend preparation hydrogel prepolymer solution;Finally, hydrogel prepolymer solution is poured into the mold containing green fabric and copolymerization, it directly forms hydrogel in fabric surface and pore interior, obtains imitated plant leaf hydrogel composite material.The material gets rid of the dependence on hygroscopic salt, has water absorption and simulation effect stable, durability is good and the like advantages.

The invention discloses a method for dynamically monitoring, regulating and controlling crop growth environment data based on nano sensing, and relates to the technical field of crop environment monitoring and management. Crop growth environment data and leaf dip angle data are synchronously acquired through a deployed nano sensing network; constructing an environment variation vector reflecting environment mutation intensity based on the environment data, and calculating to obtain a comprehensive risk value in combination with the blade attitude anomaly characteristic value processed by the trigonometric function; and generating a spatial risk distribution matrix reflecting continuous distribution of a risk space by using an inverse distance weighted interpolation method. By analyzing the characteristics of the matrix, transient interference caused by gust and the like and continuous stress caused by sudden change of the environment are intelligently distinguished, and two differentiated response management strategies of inhibitory regulation and control and hierarchical regulation and control are respectively triggered. The early, accurate and spatially distinguished perception and preventive intervention of the risk of the flash seedlings in the facility are realized, and the problems of high false alarm rate, response lag and extensive regulation and control of a traditional method are effectively solved.

The invention relates to the technical field of intelligent management of landscaping, in particular to an intelligent management method and system for irrigating landscaping plants, and the method comprises the following steps: 1, carrying out multi-dimensional data collection and dynamic modeling: collecting plant physiological data through a stem flow sensor, a leaf water potential sensor and a high-definition camera, the method comprises the following steps: acquiring environment and soil data through a meteorological station array and a soil sensor, and constructing a digital twinborn model containing a plant growth stage-water demand curve based on historical data; 2, water demand prediction and intelligent decision making: inputting real-time data into an LSTM neural network model to predict the water demand of the plant in the future 1-3 days, generating a dynamic irrigation scheme in combination with weather forecast data, and optimizing the irrigation amount and the time period according to the plant type, the growth stage and the soil partition; the water demand state is directly sensed through plant physiological signals, dynamic regulation and control are combined with a prediction model, water is saved by 50% or above compared with traditional regular irrigation, and the soil water accumulation rate is reduced to 5% or below.

The invention particularly relates to a water-saving irrigation system for intelligent agricultural vegetable seedling raising, and relates to the technical field of intelligent agriculture. And a decision and processing module. According to the method, multi-dimensional data perception and intelligent decision are adopted, so that the core contradiction that disease prevention needs drying and seedling strengthening needs stress in traditional seedling culture is solved; through a non-contact infrared leaf temperature sensor, a miniature resistance-type leaf surface humidity-sensitive sensor and the like, key data such as leaf temperature and leaf surface humidity state are accurately collected, a leaf surface humidity prediction model is constructed, a disease risk window is divided in advance, and propagation of diseases such as downy mildew and gray mold is blocked from the source; the stress intensity is controlled through the wilting coefficient, so that the seedlings are prevented from withering due to excessive stress, and moderate drought is ensured to stimulate root growth.

The invention discloses a breathable plant leaf biomimetic material with antifouling, self-cleaning and spectrum simulation properties and a preparation method of the breathable plant leaf biomimetic material. The breathable plant leaf biomimetic material can be applied to a base material through a two-step coating method. The first layer is a mesophyll-like porous dual-network hydrogel structure, hyperspectral pigment and moisture absorption salt are dispersed in the first layer, spectral characteristics of plant leaves in visible light and near infrared bands are simulated, and a water transpiration function controlled by plant pores is reproduced through a pore structure and a salt medium, so that stable spectral response and dynamic water exchange are realized; and the second layer is a leaf-skin-imitated coating, and has long-term stable antifouling and self-cleaning characteristics through a liquid-like super-smooth hydrophobic surface structure. The plant leaf spectrum simulation coating has anti-mud and hydrophobic properties, can still keep an excellent plant leaf spectrum simulation effect after being washed by rainwater, and can realize high-weather-resistance spectrum simulation.

The utility model discloses a high-efficiency rotary type suspension ball filler with a good aeration effect, which comprises an upper hemisphere and a lower hemisphere, a first fixed chuck is arranged on the outer side surface of the upper hemisphere, and a second fixed chuck is arranged on the outer side surface of the lower hemisphere. The first fixing chuck and the second fixing chuck are fixedly connected through a hexagonal screw, the upper end surface of the first fixing chuck is fixedly connected with a blade structure through a screw, the upper end surface of the blade structure is coated with a first smooth coating structure, and the lower end surface of the blade structure is coated with a second smooth coating structure. And a streamline curved surface structure is arranged on the surface of the blade structure. According to the utility model, a plurality of blade structures are arranged outside the suspended ball filler structure, and the blades are subjected to multifunctional design protection, so that the rotating effect of the suspended ball filler is better during aeration, a biological layer on an internal sponge block can be conveniently and quickly dropped, and the suspended ball filler has the advantages of good degradation effect and high sewage purification efficiency.

The invention provides a double-layer multi-leaf grating based on embedded rails, and relates to the technical field of multi-leaf gratings, the double-layer multi-leaf grating comprises a fixed frame, mounting side plates are fixedly mounted on the two sides of the interior of the fixed frame respectively, and two layers of embedded rail mechanisms are mounted at the two ends of the mounting side plates on the two sides respectively; a plurality of upper combined type blades are arranged in the upper-layer embedded track mechanism, and a plurality of lower combined type blades are arranged in the lower-layer embedded track mechanism. Through the embedded track mechanism, the track and the driving mechanism are embedded into the space where the blades are arranged, so that the effective shielding height of the blades can be higher under the same external size, and ray leakage is remarkably reduced. And a larger front end arc radius is allowed to be used due to the higher blade height, so that the penumbra of rays can be reduced, and the sharpness of an irradiation boundary is improved.

The invention provides a sea water pump, and relates to the technical field of water pumps, the sea water pump comprises a pump shell, the pump shell is provided with a water inlet, a pumping chamber and a water outlet which are communicated in sequence, and the water inlet is perpendicular to the pump shell and detachably connected with a water inlet elbow; one end of the transmission shaft extends into the pumping chamber, and the other end rotationally penetrates through the bearing body to be connected with a driving motor; the main impeller is mounted on the transmission shaft and close to the water inlet; the auxiliary impeller is installed on the transmission shaft and located between the main impeller and the pump shell. The blades on the main impeller are made of copper, and the blades on the auxiliary impeller are made of rubber. A plurality of main impeller screw holes are distributed in the main impeller; the water inlet is connected with a filter. Due to the arrangement of the main blade screw holes, dynamic balance is conveniently achieved, pressure impact on the main impeller is reduced, and the main blade screw holes are used as auxiliary holes during assembly and disassembly. And the water inlet is connected with a filter, so that the normal work of the main impeller and the auxiliary impeller is prevented from being influenced due to the fact that large-volume soft marine organisms enter the pumping chamber.

This invention discloses a method for breaking peanut seedling membranes and a corresponding membrane-breaking assembly. The assembly is mounted on a membrane-breaking machine support with a walking and cruising function. It includes an image acquisition camera, a YOLOv3 deep learning neural network structure, and a membrane-breaking blade with an adjustable circumferential cutting radius. Based on the characteristic that peanut seedling height and leaf area are proportionally related and relatively fixed during growth, the method preprocesses peanut images acquired by the camera and adds the peanut seedling height as expected data to the training set. The trained model estimates the peanut seedling height by calculating the leaf area. During recognition, the acquired image is input into the model, and then the driving device determines the coordinates based on the camera parameter calibration information, driving the membrane-breaking blade to break the membrane of seedlings that meet the breaking requirements. This invention ensures the scientific cultivation of peanut seedlings, significantly reduces worker time, lowers labor costs, and improves production efficiency.

The invention discloses a forest point cloud branch and leaf separation method fusing double attention and edge perception, and relates to the field of forestry environment monitoring, the method is based on a forest point cloud branch and leaf separation network CLEANet, a classical encoder-decoder architecture is adopted, an encoder layer is composed of a down-sampling module and a channel-local point attention CLPA module, and the channel-local point attention CLPA module is composed of a down-sampling module and a channel-local point attention CLPA module. The decoder layer realizes feature recovery through combination of up-sampling, an edge perception module EAM and a multi-layer perceptron MLP, the CLPA module adaptively strengthens geometric detail and semantic feature expression through a double-attention mechanism and effectively captures wood and leaf component differences, the EAM module enhances perception of a network to a local geometric structure through a neighborhood feature propagation and fusion mechanism, and the local geometric structure is effectively captured. And characteristic mutation of the wood and the leaf at the boundary is captured. The method integrates a channel-local point attention mechanism and edge perception, has excellent robustness, good generalization ability and wide practical application potential, and provides powerful technical support for forest resource investigation and ecological environment monitoring.

The invention discloses an infrared corn drought identification method based on wavelet boundary enhancement, and belongs to the field of agricultural informatization and plant phenotype identification, and the method comprises the following steps: S1, obtaining an infrared image of a corn plant; s2, executing two-dimensional discrete wavelet transform to generate a boundary response diagram; s3, generating a binary mask according to the characteristics of the boundary response diagram to the blade edge; s4, connected domain analysis is executed, candidate leaves are obtained, and independent single-leaf masks are generated; s5, the small holes are removed, a mask is obtained, and the blade curvature is quantified; s6, constructing a multi-dimensional feature vector reflecting the curling characteristics of the blade; and S7, outputting the drought grade corresponding to the corn leaf through the multi-layer perceptron model. By adopting the method, automatic identification and early warning of the early-stage water shortage state of the corn are realized.

This invention provides a leaf point cloud completion method based on multi-layer attention fusion and edge structure guidance, comprising: acquiring and preprocessing a 3D point cloud dataset of plant leaves; establishing a leaf point cloud completion network; inputting the preprocessed 3D point cloud dataset of plant leaves into the established leaf point cloud completion network, and using a preset total loss function to guide the leaf point cloud completion network for iterative training; finally, inputting the plant leaf point cloud to be completed into the trained leaf point cloud completion network for completion; this invention designs an encoder-decoder with an attention mechanism for the overall leaf structure, and integrates multi-layer attention-weighted features through a fusion module to improve the model's perception of leaf structure, enabling the network to better complete the leaf point cloud completion task; for the leaf sheet structure, an edge loss function is designed to guide the model to learn leaf edge information, thereby improving the accuracy of plant leaf morphology research.

According to the rice cultivation seedbed field surface terrain and cultivation depth integrated measurement method and the rice cultivation seedbed preparation equipment, a rotary cultivator serves as a measurement platform, and a double-antenna GNSS and an IMU are installed on a rack and a dragging plate respectively so as to measure the course angle, the pitch angle and the roll angle of the cultivator and the rotation angle of the dragging plate relative to the rack; establishing a vehicle body coordinate system; establishing a spatial position vector of the deepest soil cutting point of the rotating blade and a carriage profiling point under a vehicle body coordinate system; during rotary tillage operation, a homogeneous coordinate transformation method is adopted to synchronously measure three-dimensional coordinates of the deepest soil cutting point and the profiling point under coordinates of the east, north and sky, and a deepest soil cutting point set and a profiling point set are constructed; combining the two point sets, extracting plane coordinates of the farmland boundary, and arranging plane grid points; estimating the field terrain height of each plane grid point by using the profiling point set; and estimating the tilling bottom layer terrain height of each plane grid point by using the deepest soil point set, and calculating the tilling depth of each grid point. The invention has high efficiency and accuracy, and belongs to the mechanical agricultural equipment manufacturing technology.

The invention provides a tomato leaf health status assessment system and method, and relates to the technical field of tomato leaf health assessment, and the method specifically comprises the steps: firstly, carrying out the preprocessing of a tomato leaf image, converting the image into a Lab color space, and carrying out the segmentation and extraction of a leaf region based on a chromaticity threshold value; and then leaf area chromaticity channel statistical magnitude is counted, pixel-level anomaly detection is carried out through an adaptive threshold value, and an abnormal area mask and a normal area mask are generated. Performing connected domain analysis on the abnormal region, extracting local color and texture features, and extracting corresponding features of the normal region as a reference; the health deviation degree is obtained by calculating the feature distance between each abnormal region and the normal region, and the comprehensive health assessment index is generated by combining the area proportion of the abnormal regions after normalization. And finally, judging a health state according to a preset threshold rule and outputting an evaluation result. According to the invention, a comprehensive and accurate decision basis is provided for agricultural producers, and the automation level and evaluation accuracy of tomato disease monitoring are improved.

The present application belongs to the technical field of seedling raising, and provides a seedling raising and pruning device, which comprises a mounting seat, a first cutter seat and a second cutter seat oppositely arranged on the mounting seat, a first through hole formed in the first cutter seat, a first cutter head arranged on one side of the first cutter seat away from the second cutter seat and used for removing end leaves of seedling branches, a second cutter head and a first elastic member arranged on one side of the first cutter seat close to the second cutter seat, a cutter groove matched with the second cutter head arranged on the second cutter seat, a second through hole formed in the second cutter seat, a centering assembly fixedly connected to one side of the second cutter seat away from the first cutter seat and used for positioning and clamping seedling branches, a clamping assembly arranged on one side of the centering assembly away from the second cutter seat and used for clamping seedling branches, and a shearing assembly used for shearing seedling branches. The present application solves the technical problem that the treatment of seedling branches before cutting in the prior art relies on manual operation, which is time-consuming and laborious and has low production efficiency, saves time and labor cost, and improves production efficiency.

Disclosed is a pair of corn snapping rollers. Each roller has a squared shaft to which intermeshed flutes or blades are bolted. The flutes or blades possess a series of triangular teeth ending in tips that firmly sink into the stalks to lower them and open cracks therein, regardless of their moisture or condition, with the teeth of a roller interspersed with those of their counterpart. Both rollers have the same diameter and tangential velocity. By rotating the rollers, the blades approach each other at a remarkably close distance of a few millimeters. The blades of the same roller may be equidistant from each other or may be paired, such that the distances between consecutive blades are unequal.

The utility model provides a vegetable crop harvester which comprises a frame, a driving mechanism arranged on the frame, a separation conveying mechanism, a root cutting mechanism and a gathering mechanism. The separation conveying mechanism is obliquely arranged on the frame, and a containing cavity is formed by the tail end of the separation conveying mechanism and the top of the rear end of the frame and used for receiving cut vegetable crops; the root cutting mechanism and the gathering mechanism are arranged at the starting end of the separation conveying mechanism, and the gathering mechanism comprises two stem holding devices which are distributed at intervals and used for gathering leaves of vegetable crops and guiding stems of the vegetable crops to a cutting area of the root cutting mechanism; an output shaft of the driving mechanism drives the root cutting mechanism and the separating and conveying mechanism, the root cutting mechanism is used for cutting stems of vegetable crops guided to the cutting area, the separating and conveying mechanism is used for separating the cut vegetable crops and conveying the vegetable crops to the containing cavity, and damage to vegetable leaves is reduced.

The embodiment of the invention relates to the technical field of fruit picking, and discloses a fruit picking method, a picking device and a picking robotic.The method comprises the steps that hidden fruits hidden in a to-be-picked area and the hidden positions of the hidden fruits are determined, and a picking mechanical arm is driven to drive the hidden fruits to be picked; the air nozzle assembly is driven to directly face the hidden position to blow air so as to expose the hidden position, the picking mechanical arm is driven to move towards the hidden position until the clamping mechanism reaches the hidden position, the clamping mechanism is driven to clamp the hidden fruits, the air supply device is controlled to stop supplying air, and the clamping mechanism is driven to be recycled. And picking the hidden fruits. By means of the mode, the fruit sheltered by the leaves can be effectively exposed, and comprehensiveness and thoroughness of picking operation are guaranteed.

The invention relates to the technical field of new energy, in particular to a natural-leaf-imitated 3D printing liquid drop friction generator which comprises a bionic blade main body structure, a bottom electrode, a friction layer and a top electrode which are sequentially arranged from bottom to top, the bionic blade main body structure serves as a substrate, and a rigid supporting framework is formed through a bionic vein network of the bionic blade main body structure; when liquid drops impact the prismatic surface, the liquid drops axially and directionally flow along a connecting channel of the vein network and are in contact with the friction layer, charge transfer between the bottom electrode and the top electrode is induced through a solid-liquid triboelectrification effect, meanwhile, a rigid skeleton of the vein limits excessive deformation of the FEP film, the spreading area of the liquid drops and the charge output density are synergistically improved, and the charge output density is increased. And the stability of an electrical path and the signal output efficiency are ensured.

Systems and methods for preparing a ligament graft for a ligament reconstruction procedure are provided. In general, the described techniques utilize a graft holder construct having a graft preparation holder and a suture assembly removably coupled thereto. The graft preparation holder includes an elongate support rail having a longitudinal axis, and a plurality of leaf segments positioned along the longitudinal axis in a spaced relationship and extending laterally from the support rail. The leaf segments can bend to a graft holding configuration so as to define a graft receiving channel configured to receive a graft therethrough. The holder also has at least one support structure configured to mate with the leaf segments to provide stability and rigidity to the segments. The suture assembly has at least one suture tail that can be pulled to affix the suture assembly to a graft without penetrating the graft.

The invention discloses a plant leaf physicochemical parameter inversion method based on spectrum two-dimensional characterization and multi-task deep learning, and belongs to the technical field of plant physiological detection. The method comprises the following steps: constructing a hyperspectral plant leaf data set; preprocessing a hyperspectral plant leaf data set; reconstructing the preprocessed one-dimensional spectral vector into a two-dimensional image; taking the generated two-dimensional image as input, constructing a multi-task learning model, and performing training and evaluation; and applying the trained model to a test set to obtain an inversion result of the physical and chemical parameters of the leaf. The method solves the problem of parameter inversion interference caused by the same-spectrum foreign matter phenomenon, achieves the precise modeling of local fine feature extraction and global context relation, solves the inversion precision bottleneck caused by spectral response overlapping among parameters, improves the distinguishing capability of the model for easily confused parameters such as chlorophyll and carotenoid, and improves the accuracy of the model. And finally, high-precision and robust synchronous inversion of the physical and chemical parameters of the plant leaves is realized.

The invention provides a plant chlorophyll index determination method based on multispectral laser, which comprises the following steps: detecting ambient light intensity of an environment where plant leaves are located to obtain an actual ambient light detection value; according to the actual detection value of the ambient light, a pulse generator is regulated and controlled, and a PWM frequency conversion signal is generated; driving a multi-band laser source based on the PWM frequency conversion signal to enable the laser source to emit laser and form uniform light spots on the surface of the plant leaf; receiving and preprocessing the laser signal reflected by the plant leaf to obtain a pure electric signal; the pure electric signal is converted into a digital quantity, calculation processing is carried out based on the digital quantity and a preset digital quantity, and the reflectivity corresponding to each wave band is obtained; and calculating based on the reflectivity corresponding to each wave band to obtain the chlorophyll index. By adopting the method, related data of the chlorophyll content of the plant can be accurately obtained, and technical support is provided for agricultural scientific management, diagnosis decision and high yield.

The invention relates to the technical field of scenic spot plant growth monitoring, and particularly discloses a scenic spot plant growth intelligent monitoring method and system, and the method comprises the steps: carrying out the multi-band image data collection of ornamental vegetation, and obtaining leaf spectrum purification data; extracting wave band response curves of anthocyanin, carotenoid and chlorophyll according to the spectral purification data to obtain pigment wave band characteristic data; performing spectrum aliasing sensitivity analysis on the pigment wave band characteristic data to obtain spectrum aliasing nonlinear characteristic data; carrying out differentiation attribution calculation on a wave band aliasing region between the healthy purple leaves and the iron-deficient yellowing to obtain aliasing difference attribution data; and finally obtaining vegetation pigment unmixing mapping data. Performing physiological status difference identification on the pigment unmixing mapping data to obtain a vegetation health monitoring result; the precision, high efficiency and foresight of scenic spot vegetation monitoring are technically guaranteed, the technical requirements of modern scenic spot vegetation management are met, and losses caused by vegetation health problems are effectively reduced.