459results about "Testing plants/trees" patented technology

The invention relates to the technical field of plant phenotype data processing, in particular to a plant phenotype automatic acquisition and feature processing method oriented to a multi-element environment. According to the method, the plant multi-modal phenotypic data are synchronously collected through the Internet of Things nodes, the coupling strength is calculated in combination with the environmental factors, the phenotypic parameters are divided into an environment sensitive type and a steady type, and the data classification accuracy is improved. A growth trend field is constructed by means of phenological phase decoupling analysis and geographic space superposition, abnormal segments are dynamically eliminated by combining physiological synergy degree and a mutation detection algorithm, and trend analysis stability is enhanced. A phenotype-environment response map is generated through standardized processing and an environment equivalent value model, a key environment sensitive window is recognized, a regional and staged cross-environment regulation scheme is output, intelligent and accurate management of the crop growth environment is achieved, and the method is suitable for agricultural yield increase and breeding optimization.

The invention discloses a rapid identification and comprehensive evaluation method for a polygonatum cyrtonema provenance, and belongs to the field of improved variety breeding and quality control of traditional Chinese medicinal materials. The method systematically measures a plurality of specific biological traits covering three dimensions of growth, physiology and medicine. And carrying out standardization processing on the measured multi-dimensional data, carrying out dimensionality reduction by using a principal component analysis model, constructing an evaluation model capable of comprehensively reflecting the comprehensive quality of the provenance, and calculating a quantitative comprehensive evaluation score. The score can objectively and scientifically divide different provenances into four different quality grades including excellent, good, common and to-be-improved quality grades. The method has the beneficial effects that the strong positive correlation between the easily measured growth traits of the overground part and the medicinal component content of the underground rhizome for determining the final quality of the medicinal material is established, so that the rapid, predictive and non-destructive early screening of the provenance quality is realized.

The invention discloses a key gene identification method related to tobacco nitrogen response, which comprises the following steps: S1, setting four nitrogen fertilizer gradient treatments on the basis of same phosphorus and potassium fertilization by adopting a field experiment of a completely random block; s2, randomly taking the 6th to 8th leaves of the five plants in each area, and dividing a sample into two parts: quickly freezing one part with liquid nitrogen, and storing at-80 DEG C for RNA (Ribonucleic Acid) extraction and transcriptome sequencing; one part is used for measuring the nitrogen content, and after baking and drying treatment, a KjeltecTM8100 automatic nitrogen analyzer is used for measuring; s3, nitrogen content determination: determining the nitrogen content in the treated sample by using an automatic nitrogen analyzer KjeltecTM8100; according to the method, high-throughput transcriptome sequencing and weighted gene co-expression network analysis (WGCNA) are combined, so that not only can gene expression maps of flue-cured tobacco leaves treated by different nitrogen fertilizers be comprehensively captured, but also gene modules with similar expression modes can be mined from a global perspective.

This disclosure relates generally to system and method for estimating crop water requirement using multi-sensor data fusion. Increasing global population is imparting pressure on both agriculture for food demand and limited freshwater resources for consumption. Estimating crop water requirement reduces water demand for crop production. The method divides soil and crop into multiple vertical and horizontal profiles to estimate water balance thereby reducing the errors in estimation of crop water requirement. Additionally, the method has capability to interlink the multiple data sets such as satellite based earth observations, weather observations from IoT sensors, Weather forecasts from global circulation models, and crop knowledge base for crop water requirement estimation. The method is based on spatio-temporal modeling for multi-layer crop and soil water balance and helps to generate the additional insights on crop water requirement like moisture at different levels in soil profile, crop canopy growth at different locations.

The invention provides a tree species screening method for high-altitude drought afforestation, an afforestation method and application, and belongs to the technical field of forest tree breeding and cultivation. According to the screening method, five physiological and biochemical indexes of soluble protein, malondialdehyde, proline, peroxidase and soluble sugar in the tree species are measured through a gradient drought stress experiment, and comprehensive scoring is performed by adopting a membership function, so that the drought-resistant tree species are scientifically screened. The tree species such as sophora moorcroftiana, rosa serrulata and amorpha fruticosa screened by the method are applied to afforestation in the high-altitude arid region, and the afforestation survival rate and preservation rate can be remarkably increased. The invention provides a reliable technical scheme for solving the long-term problem that the selection of tree species in the difficult site field lacks scientific basis.

Various apparatus and procedures for agricultural operations are provided. In particular, in one embodiment, methods for determining the precise location of each seed planted and using the seed planting location data to improve post-planting operations are provided. In another embodiment, apparatus and methods for determining the location of wet zones in an agricultural field and using the wet zone location data to plan an optimal path through the field to avoid wet areas are provided. In another embodiment, methods for tendering seed and chemical inputs for an agricultural operation are provided. In another embodiment, dynamic path planning methods of an autonomous agricultural vehicle are provided. In another embodiment, methods of planting end rows in an agricultural field are provided. In another embodiment, methods for planting multiple seed varieties in an agricultural field are provided.

The invention relates to the technical field of plant breeding, and particularly discloses a metabonomics-based alfalfa stress resistance gene analysis function and a breeding method. The core of the method is that screening is carried out by combining a tissue culture technology with metabolic intervention; an alfalfa explant is inoculated into an induction culture medium containing a specific metabolic pathway regulator for metabolic intervention culture; then transferring the obtained callus to a verification culture medium containing the metabolism regulator and an abiotic adversity stress factor at the same time, and carrying out metabolism mark verification and screening; and finally regenerating the screened cell line into a complete plant. According to the method, metabolic pressure is actively applied to the cellular level, and dual verification screening is implemented, so that early-stage, efficient and accurate breeding of the stress-resistant alfalfa material is realized, and the technical problems of long period, low efficiency and insufficient utilization of metabolic information in traditional breeding are solved.

The present invention discloses a wild soybean whole growth period saline-alkaline tolerance gradient simulation identification device, and relates to the technical field of crop breeding, the wild soybean whole growth period saline-alkaline tolerance gradient simulation identification device comprises: a planting simulation assembly, which is used for adaptively adjusting the saline-alkaline degree according to the growth characteristic of the wild soybean; the housing is arranged on the planting simulation assembly in a covering mode so that a sealed space can be formed by the housing and the planting simulation assembly together, and an exhaust pipe is further arranged on the housing; the first gas tank is communicated with the sealed space, the first gas tank is filled with carbon dioxide gas in advance, the device can monitor the organic acid secretion amount of the root system in real time, the saline-alkaline tolerance of wild soybeans in the current growth period can be dynamically matched, and the data fineness is high.

This invention discloses a method and system for predicting the moisture content of combustibles based on a Long Short-Term Memory (LSTM) model. First, data is collected and processed, combining data sources for both combustible moisture content and meteorological data, and processing the data according to the measurement time and location. An LSTM model is then constructed and trained, and finally, the trained LSTM model is used for result prediction. This method can effectively predict the moisture content of combustibles. By training and validating the dataset using the LSTM model, the accuracy is improved compared to traditional machine learning algorithms. Furthermore, combustible moisture content has a high correlation with meteorological factors; this method integrates meteorological factors such as temperature, vapor pressure, and wind speed, further improving the prediction accuracy compared to using only combustible moisture content for prediction.

The invention discloses an ancient tree health state monitoring method based on digital twinning, and relates to the field of ancient tree health monitoring, and the method comprises the steps: collecting point cloud data and texture data of an ancient tree, and constructing an initial three-dimensional model of the ancient tree; a micro ion selective electrode array is deployed in an ancient tree root distribution area, Ca2 and K + ion flow velocity changes are detected through a constant potential rectifier, and the mycorrhizal symbiosis index is calculated in combination with soil temperature and humidity data; uploading the mycorrhizal symbiosis index to a digital twinborn body, and displaying the active state of a root system area in an initial three-dimensional model of the ancient tree in a three-dimensional thermodynamic diagram form; a 16-channel MOX gas sensor electronic nose array is installed on the surface of a trunk of an ancient tree, and volatile organic compound (VOC) concentration data of the ancient tree are collected. According to the invention, a micro electrode array with a 45-degree inclination angle is adopted to non-destructively monitor the ion flow velocity of a root system through the mycorrhizal symbiosis index detection unit, and a three-dimensional thermodynamic diagram is generated in combination with an inverse distance weighted interpolation algorithm, so that dynamic visualization of underground mycorrhizal activity is realized.

Disclosed are methods of producing nutrient solutions having unique isotopic fingerprints; methods of producing traceable plants; and methods of identifying the source of a traceable plant that does not rely on expensive artificially separated isotopes. Plants grown with these nutrient solutions will have unique isotopic fingerprints that will be difficult or impossible to counterfeit.

The invention discloses an application method for realizing rice nitrogen fertilizer substitution by utilizing a photocatalytic nitrogen fixation material in the technical field of agricultural production. The application method comprises the following steps: S1, pretreating and proportioning a catalyst; s2, reaction container deployment and illumination optimization; s3, carrying out photocatalytic reaction and ammonium nitrogen generation; s4, synergistically applying base fertilizer and additional fertilizer; s5, monitoring and feeding back nitrogen utilization efficiency; the performance of the photocatalyst is improved by adopting a surface doping and composite modification technology, atmospheric nitrogen can be stably and efficiently converted into ammonium nitrogen which can be directly absorbed by rice under a complex environmental condition, and the nitrogen conversion rate and the nitrogen supply efficiency are improved; the AI algorithm is combined with the chlorophyll meter, the soil nitrogen sensor and the water ammonia nitrogen concentration data to predict and dynamically adjust the nitrogen demand of the rice in real time; a closed loop of nitrogen fixation-conversion-absorption-recovery is formed through a segmented application strategy of base fertilizer and topdressing in combination with physical and chemical synergism and a biochar improvement technology.

This disclosure relates generally to system and method for estimating crop water requirement using multi-sensor data fusion. Increasing global population is imparting pressure on both agriculture for food demand and limited freshwater resources for consumption. Estimating crop water requirement reduces water demand for crop production. The method divides soil and crop into multiple vertical and horizontal profiles to estimate water balance thereby reducing the errors in estimation of crop water requirement. Additionally, the method has capability to interlink the multiple data sets such as satellite based earth observations, weather observations from IoT sensors, Weather forecasts from global circulation models, and crop knowledge base for crop water requirement estimation. The method is based on spatio-temporal modeling for multi-layer crop and soil water balance and helps to generate the additional insights on crop water requirement like moisture at different levels in soil profile, crop canopy growth at different locations.

A computing platform configured to: (i) receive spectrometry data for a leaf sample of a cocoa tree; (ii) utilize a first set of one or more artificial intelligence (AI) models to predict one or more nutrient levels for the leaf sample based on the spectrometry data; (iii) utilize a second set of one or more AI models to generate one or more recommendations for treating the cocoa tree based on the one or more nutrient levels; and (iv) cause the one or more recommendations to be presented to an individual involved in managing the cocoa tree.

The invention discloses a ciliate desert-grass repair efficiency evaluation method and application thereof, and aims to solve the problem that arsenic-rich biomass recycling lacks scientific quality standards. According to the method, the total arsenic concentration and the total flavone concentration of the overground part of the ciliate desert-grass are innovatively combined, a comprehensive evaluation index is constructed, and the harvested biomass is scientifically graded according to the comprehensive evaluation index. Based on the evaluation result, qualified biomass is directionally prepared into an efficient iron-modified biochar adsorbent through the steps of pyrolysis, iron modification and the like, the efficient iron-modified biochar adsorbent is used for treating arsenic-containing wastewater, safe solidification and high-value utilization of pollutants and recycling of water resources are achieved, and remarkable environmental benefits and economic values are achieved.

A method is provided for determining the fracture safety of a tree. The method includes: determining a trunk cross-section of the tree to be assessed; detecting at least a largest and a smallest diameter in the trunk cross-section as well as a shape with possibly existing damages of the trunk cross-section; calculating a percentage relative direction-dependent load-bearing capacity in a plurality of definable directions via moments of resistance respectively associated with the trunk cross-section and specifically determined in accordance with anisotropy of the material, wherein, in order to calculate a respective percentage relative direction-dependent load-bearing capacity for each of the plurality of definable directions, a section modulus determined in each case in the trunk cross-section to be assessed and possibly damaged is divided by a determined section modulus of the same trunk cross-section in an assumed undamaged state; and merging the calculated relative directional load-carrying capacities.

A method for measuring at least one of a mass-specific or size-specific variable of grain crops, the method comprising the following steps: recording a spectrum of the grain crops with a sensor operating in the near-infrared range; and deriving the at least one of mass-specific or size-specific variable from the spectrum.

Provided are a plant water content sensor and a plant water content measuring method configured to measure a water content of a plant in a non-destructive manner. A plant water content sensor 1 includes a water content probe 20, which includes a readout electrode pair 21 made of a pair of electrodes 22, 22 disposed at a predetermined interval thereof, a water sensitive film 23, which is bridged across the pair of electrodes 22, 22, and a supporting portion 10, which supports the water content probe 20. A water content of the plant is measurable by sticking the water content probe 20 into the plant and reading out impedance or an electrostatic capacity from the readout electrode pair 21.

This invention discloses a method for analyzing maize yield under water stress, belonging to the field of agricultural planting technology. It analyzes the effects of soil water stress on key physiological parameters of maize (net photosynthetic rate A) by setting different irrigation treatments and combining field experiments with model analysis. n Pore ​​conductance g s The study investigated the regulatory effects of photosynthetic parameters, growth indices (plant height, stem diameter, leaf area index, LAI), and yield components (number of grains per ear, 100-grain weight) on yield. Photosynthetic parameters, growth indices, and yield components at the jointing and tasseling stages were measured. Structural equation modeling and variance decomposition analysis were used to quantify the multi-factor interaction pathways of "photosynthesis-growth-yield" under water stress, thereby providing support for the screening of drought-resistant maize varieties and the formulation of precision irrigation management strategies.

The invention discloses a tree species screening method for heavy metal lead contaminated soil remediation, and relates to the technical field of heavy metal lead contaminated ecological management. Common greening tree species such as cinnamomum camphora, willow, gingko, koelreuteria paniculata, photinia serrulata and osmanthus fragrans are selected, leaf and rhizosphere soil are collected in a point distribution mode, and the content of heavy metal Pb in a sample is measured; the heavy metal Pb content distribution characteristics of different tree species are quantified, the heavy metal Pb enrichment capacity difference of the greening tree species is explored, the heavy metal Pb enrichment and transfer efficiency of the greening tree species is comprehensively evaluated, and the greening tree species with the best heavy metal Pb purification effect is screened out. The method is a phytoremediation technology which has the advantages of being economical, simple, convenient, high in recognition degree, long in life cycle, free of damage to the soil structure, not prone to causing secondary pollution and the like.

The invention comprises a method and apparatus for managing cropland, comprising the steps of: (1) optically measuring, each of a set of spatially resolved locations, level zero data with an orbiting satellite, the level zero data comprising: first reflected cropland radiation; (2) processing, on-board the orbiting satellite, the level zero data comprising a first data storage size, to yield crop condition information comprising a second data storage size of less than one percent of the first data storage size; (3) receiving from the orbiting satellite to a ground-based communication system the crop condition information; and (4) relaying at least a portion of the crop condition information and an actionable prescription to a farmer within twenty-four hours.

The invention discloses a screening and dosage determining method of a grape heat resistance inducer, and belongs to the technical field of plant stress resistance physiology and cultivation. The method comprises the following steps: soaking grape leaf wafers in inducers with different concentrations, and carrying out heat treatment under a plurality of temperature gradients; determining a chlorophyll OJIP rapid fluorescence parameter and constructing a heat resistance comprehensive index, and further calculating a normalized relative heat resistance improvement value; fitting a quantitative relation with the concentration by using a single-peak dose-effect model containing a high-dose inhibition item; statistical inference is carried out by adopting Bootstrap resampling, and a stable and effective recommended application concentration in a wide temperature range is finally determined by analyzing a common intersection or a statistical median of effective concentration intervals under multiple temperatures. The method realizes indoor rapid and quantitative screening, can realize quantitative comparison of induction intensity and dose sensitivity of different inducers under a unified evaluation system, and can be used for identifying heat resistance of grapes.

This biological information measuring instrument is characterized by comprising: a receptacle for covering at least a section of a plant leaf; and a sensor for measuring the concentration of water vapor and / or carbon dioxide on the inside and the outside of the receptacle. At least a section of the walls that constitute the receptacle is characterized by being formed of a permeable film having permeation resistance with respect to water vapor and carbon dioxide.

Variants of the system can include: an electrode module and a reader module. In variants, the system can function to record electrical signals from one or more plants (e.g., the system can function as a plant sensor), which can be used to evaluate the condition of the plant(s) and / or other elements of the environment.

The present invention relates to improved technology for a device that ascertains and diagnoses the state of environmental stress in plants.　A control circuit 20b controls a measurement light source 12 such that a second measurement light ML2 is higher powered than first measurement light ML1 and such that the first measurement light ML1 and the second measurement light ML2 have opposite phase square waves, and further controls the measurement light source 12 such that the first measurement light ML1 and the second measurement light ML2 are output synchronously, thereby forming the first measurement light ML1 and the second measurement light ML2 into a single pseudo synthesized square wave measurement light ML3 of 5-30 kHz.　A transmitted light detector 18 detects, as synthesized square wave transmitted light TL, the synthesized square wave measurement light ML3 that has passed through a plant sample S.　An analysis circuit 20a uses the synthesized square wave transmitted light TL to calculate a light absorption difference, uses the light absorption difference to calculate, as a ROS marker, Y(ND) which is the oxidation state of P700, and uses the ROS marker to diagnose the state of environmental stress of a plant.

The invention relates to a tea tree nitrogen nutrition diagnosis method based on unmanned aerial vehicle multi-source remote sensing. The method comprises the following steps: S1, setting a gradient nitrogen application experiment; s2, collecting tea tree shoot samples, and measuring biomass and nitrogen content data of overground parts; collecting and preprocessing tea tree canopy remote sensing data; s3, constructing a critical nitrogen dilution curve, and calculating to obtain a nitrogen nutrition index NNI; s4, constructing a multi-source fusion feature set; s5, performing feature optimization selection on the multi-source remote sensing fusion feature set; s6, taking the optimal subset in S5 as input, taking the NNI in S3 as output, training an NNI estimation model by utilizing a machine learning algorithm, and selecting and determining an optimal estimation model through model precision; s7, performing inversion and spatial mapping on the tea garden NNI, and performing nitrogen nutrition status diagnosis according to the NNI value; and S8, topdressing the nitrogen fertilizer in a flat cabinet for the diagnosed nitrogen-deficient area. The method can realize large-area, lossless and rapid diagnosis of the nitrogen condition of the tea garden, guide variable fertilization, save fertilizer and increase yield, and has remarkable environmental protection benefits.

Systems and methods for determining a concentration of a substance in a sample. In one embodiment, the system uses a device that cooperates with a container containing a sample mixed with a solution. The mixture comes into contact with a sensor that has been activated by the device, thereby allowing data signals to be received by the device through electrodes that are coupled to the sensor. The data signals are then analyzed and, based on the characteristics of the signal, a concentration of the substance can be estimated. After a single use, the container is sealed and can be disposed of properly to avoid further contact with the solution or the sample. In some embodiments, a solid sample is first processed in a second container before being mixed with the solution.

Method and control system are provided for controlling values of process parameters of a pretreatment process of wood particles. A sampler is used to obtain a sample of a product flow of said pretreatment process after said wood particles have undergone steam explosion in a hemihydrolysis reactor. A particle measurement device is used to measure one or more characteristics of particles in said sample and to produce one or more pieces of measurement information indicative of the measured characteristics. Said one or more pieces of measurement information are used to select one or more values of one or more of said process parameters.

This application discloses a method and related equipment for assessing coastal vegetation damage and recovery after extreme storms, relating to the field of data processing technology. The method includes: constructing a synchronous grid stack; mapping four states—storm, moisture, scattering, and damage—to a set of nodes, and constructing a pixel-level community lag causality graph based on each node; solving for the expected value of water film scattering from the pixel-level community lag causality graph, and using the expected value of water film scattering to determine the net damage sequence; dividing the area into ecological zones of different environments, calculating scattering values ​​in each ecological zone to obtain the natural fluctuation envelope; encapsulating the net damage sequence, the natural fluctuation envelope, and the edge weights and confidence factors of pixel-level moisture and scattering in the pixel-level community lag causality graph as game inputs and inputting them to the parameter player, thereby outputting multiple parameters of vegetation damage and recovery, and determining the peak damage rate, half-recovery time, and full recovery time of the vegetation. This application can improve the accuracy of vegetation damage and recovery assessment.

This invention proposes a comprehensive ancient tree health monitoring method and system based on IoT and AI technologies. The method includes: collecting physiological data of ancient trees through sensors and preprocessing it; extracting disturbance indicators from the millimeter-wave radar point cloud frame data through edge computing to represent the intensity of behavioral disturbances at the current time step; initializing the ancient tree health state variable as the current health state and inputting it into a pre-constructed dynamic recursive model to obtain the predicted ancient tree health state variable; sampling the millimeter-wave radar point cloud frame data once per second and performing pre-clustering processing; constructing a graph neural network based on the target point cloud set to encode and extract the disturbance activation degree representing the current behavioral risk; correcting the disturbance indicator according to the disturbance activation degree and outputting the disturbance amount; calculating a comprehensive risk score and dynamically generating corresponding health response actions based on the comprehensive risk score.