916results about "Testing plants/trees" patented technology

The invention provides a mangrove forest restoration area carbon sink quantity data monitoring system, and relates to the technical field of ecological carbon sink metering, and the system comprises an acquisition module which is used for collecting a carbon exchange original data set of an atmosphere-vegetation-soil interface based on a multi-type sensor network arranged in an intertidal wetland of a mangrove forest restoration area; the data generation module is used for carrying out space-time coordinate matching based on the original data set and generating a multi-dimensional carbon flux fusion data set of geographic position and time joint indexing; and the identification module is used for calculating a local space-time dispersion and a global correlation threshold value based on the fused data set, and identifying and marking abnormal data points. According to the invention, real-time and multi-dimensional monitoring of the carbon sink amount of the mangrove forest restoration area is realized, the monitoring efficiency and the data reliability are improved, and support is provided for assessment of restoration and management strategies.

Systems for plant culture include a chamber featuring one or more walls enclosing a spatial volume internal to the chamber, where the one or more walls include a surface for supporting a plant within the enclosed spatial volume, a gas delivery apparatus with at least one gas source, a nutrient delivery apparatus with a reservoir, a sampling apparatus connected to a port formed in the one or more walls, and a controller configured so that during operation of the system, the controller activates the nutrient delivery apparatus to deliver an aqueous growth medium to the plant, and activates the gas delivery apparatus to deliver into the enclosed spatial volume a mixture of isotopically-substituted gases. Also provided are methods of use of the system for measuring nitrogen in a plant and for identifying microbes capable of providing fixed nitrogen to a plant.

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.

A rapid monitoring and discrimination method for drought conditions in summer maize based on chlorophyll content includes: 1) Obtaining multi-spectral imagery through UAV multi-payload low-altitude remote sensing technology and measuring chlorophyll content on the ground. Additionally, calculating vegetation indices including Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), and Renormalized Difference Vegetation Index (RENDVI). 2) Selecting vegetation indices and constructing regression equations with measured chlorophyll content during different growth stages. The regression equation with the highest correlation for each growth stage is chosen as the optimal model equation for that particular stage. 3) Using the optimal model equations to retrieve chlorophyll content for each period and determining thresholds for chlorophyll content across different drought levels through calibration. 4) Calculating the required vegetation indices from real-time multi-spectral imagery of the field under test, retrieving chlorophyll content, and comparing it with the established thresholds to assess the real-time drought level.

The present disclosure provides a decision-making method and apparatus for water and fertilizer stress of crops, and a mobile phone terminal, and belongs to the technical field of intelligent agriculture. The method includes: determining a current crop coefficient and canopy temperature of a crop to be identified on the basis of a first crop image and a second crop image; determining a water stress state and a nutrient stress state on the basis of the current crop coefficient and canopy temperature of the crop to be identified; and processing the water stress state and the nutrient stress state with a fuzzy control algorithm, and determining a water and fertilizer stress decision result of the crop to be identified.

Methods are provided for assessing the nitrogen status of a plant or multiple plants in a plurality of plants, and optionally comparing the nutrient status to a plant or multiple plants in another plurality of plants (e.g., another plurality of plants in a different field or different region of the same field). The methods find utility, for example, in validating the performance of alternative plant nitrogen treatments such as validating the performance of nitrogen fixing microbes in replacing a defined amount of nitrogen from synthetic nitrogen treatment.

The invention discloses a hyperspectral technology-based inversion method for SPAD values and nitrogen concentrations of leaves in the whole growth period of rice. The hyperspectral data of the leaves of the rice are obtained by means of an ASD Field Spec4 portable ground object spectrometer in the initial differentiation period (PI), the heading period (HD), the middle filling period (MF) and the mature period (MA) of young ears; measuring the SPAD value of the rice as the chlorophyll content by using an SPAD-502 chlorophyll meter; determining the nitrogen concentration of the rice leaves by adopting a Kjeldahl method; performing correlation analysis on the hyperspectral data of the leaves, the nitrogen concentration and SPAD, and screening sensitive wavebands. According to the method, the hyperspectral characteristic wave band of the rice leaf is extracted through a correlation analysis method, so that the redundancy of full-spectrum data modeling is reduced, data are optimized, an inversion model of the nitrogen concentration and SPAD value of the rice leaf is constructed based on linear regression (LR), random forest (RF), support vector regression (SVR) and gradient boosting (GBRT), and the nitrogen concentration and SPAD value of the rice leaf are obtained. The optimal machine learning algorithm with high precision and good stability is obtained, and a scientific basis can be provided for non-destructive real-time leaf color monitoring and precise fertilization control of indica rice in the South China.

Described herein are techniques for generating contextually rich plant images. A number of data captures of raw plant data are generated via a sensing unit configured to navigate a growing facility. Metadata is generated and assigned to the raw plant data including at least one of: plant location, timestamp, plant identification, plant strain, facility identification, facility location, facility type, health risk factors, plant conditions, and human observations. Images generated by the sensing unit are analyzed and pixel annotations are generated in the images based on their relation to one or more plant well-being features. Data tags are generated and assigned the data captures based on an analysis of the data captures. The data tags are text phrases linking a particular data capture to a specific threat to plant well-being.

For analysis of the state of a plant (2) or of another eukaryote, an evaluation device or an evaluation system (30) has an evaluation circuit (34) which is designed to carry out an evaluation (36) of spectral data. The spectral data or data generated on the basis thereof by preprocessing are divided into multiple parts and analyzed using an analysis logic. The analysis logic comprises at least one attention mechanism.

The invention belongs to the technical field of agricultural production, and discloses an evaluation method for identifying the preliminary salt tolerance of foxtail millet in a germination period, which comprises the following steps: determining five key indexes of relative germination potential, relative germination rate, relative root length, relative bud length and relative germination index in the germination period of foxtail millet; the salt tolerance of the millet germplasm resources in the germination period can be preliminarily evaluated by establishing a regression equation to estimate the D value. The simple, convenient and scientific method for identifying the salt tolerance of the millet germplasm resources in the germination period is established, convenience is provided for screening salt-tolerant germplasm of millet, and the method is a premise for carrying out research on a salt-tolerant mechanism of millet.

A method is provided for determining soil properties for an area of land, from soil spectrum data. In an embodiment, the method includes receiving soil spectrum data records from hyperspectral sensors that represent a mean soil spectrum of a specific geo-location of the area of land and removing interference signals from the spectrum data records to create soil spectral bands. The method also includes predicting a plurality of soil property datasets based on a partial least-square regression and the soil spectral bands and selecting specific soil property datasets from the plurality of soil property datasets to represent soil properties of the specific geo-location, wherein the specific soil property datasets include property data and spectral band data for spectral bands used to determine the property data. The specific soil property datasets may then be used to generate a crop prescription of recommended hybrid seeds or population densities for the specific geo-location.

A soil moisture and fertility sensor system is presented that includes a plurality of probes and a monitoring system. The plurality of probes are configured to make nutrient, moisture, and / or other measurements of the soil at a plurality of depths. The monitoring system is communicatively connected to the plurality of probes and configured to receive data related to the measurements of the soil from the plurality of probes. In one or more arrangements, the monitoring system is configured to track soil status based on the data to facilitate review of and management of soil nutrient and / or moisture levels.

The invention discloses an urban green land plant growth state monitoring and analyzing system and method, relates to the technical field of big data analysis, and can accurately track the health condition of plants in each sub-region and improve the scientificity and effectiveness of urban green land management through detailed region division and coordinate marking. By means of the plant growth simulation model and the ideal environment growth model which are constructed through the neural network, the system can dynamically predict the plant growth state and conduct personalized management on plant growth conditions in different areas. Various collection means such as environmental factors and remote sensing data are integrated, the growth state of urban green land plants is comprehensively monitored, and the limitation of a traditional method is overcome. By setting the state abnormality threshold and combining the growth deviation trend chart, the system can realize a real-time early warning mechanism, quickly identify potential growth abnormality and ensure that problems are found and solved in time, so that the monitoring error of the remote sensing technology is reduced, and the management efficiency is improved.

A transgenic soybean event, Gm_CSM63717, is provided. Transgenic plant cells, plant parts, plants, seeds, progeny plants, and agricultural and commodity products containing event Gm_CSM63717 are also provided. Recombinant DNA molecules unique to the event Gm_CSM63717, and methods of using and detecting Gm_CSM63717 are also provided. Soybean plants containing the event Gm_CSM63717 exhibit tolerance to PPO inhibitors.

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.

A measurement system including: a. a sensor system that includes: i. a Light Detection And Ranging (LiDAR) module with a laser emitter configured to generate measurement data representing raw range measurements to measure heights of a crop, and ii. a computing module, including: at least one wireline / wired communications module configured to communicate with the LiDAR module for the computing module to acquire the measurement data from the LiDAR module; and at least one wireless communications module configured for the computing module to communicate using a wireless connection / link with a remote computing system that is configured receive the acquired measurement data and to determine / calculate / estimate phenotypic quantities of the crop based on the measured heights for the purpose of high-throughput plant phenotyping (HTPP); and b. a mobile / vehicle mount configured to hold / support the sensor system above the crop and to direct the laser emitter towards the crop.

A working electrode is inserted into the plant to monitor the health of the plant components or to detect physical, mechanical damage or environmental change in the soil or atmosphere. A standard electrode is inserted into soil surrounding the plant or in the plant itself. A data logger connects the working electrode and the standard electrode. The data logger measures the potential difference between the working electrode and the electrolyte to provide the ability to compare a measured potential difference with a predetermined critical potential difference for the plant. A second electrochemical cell can inject electrons and ions into the plant. The plant can be used as a sensor to monitor the environmental change in the soil or in the atmosphere.

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.

The invention relates to the technical field of stable isotope tracing, in particular to a simple 13CO2 pulse marking device with adjustable volume and height and a method thereof.The simple 13CO2 pulse marking device comprises an incubator, a preparation structure is arranged on one side of the incubator, a pulse marking structure is arranged above the incubator, and a detection structure is arranged on the side adjacent to the preparation structure; a circulation structure is arranged on the side, away from the preparation structure, of the detection structure, a rising structure is arranged at the bottom of the incubator, a plant culture base is arranged above the rising structure, a volume regulation and control structure is arranged above the plant culture base, and an exhaust structure is arranged on the side, away from the detection structure, of the incubator; through organic integration of all the structures, the whole process from plant culture to pulse marking can be achieved in the same device, all the parts are matched with one another, the convenience and efficiency of experimental operation are greatly improved, errors and inconvenience caused by device conversion are reduced, and the experimental efficiency is improved. And an integrated solution is provided for accurately researching plants in different growth stages and related physiological processes.

The invention relates to the field of compound fertilizer analysis, and discloses an analysis method and device for combining polyglutamic acid and a compound fertilizer, computing equipment and a storage medium, and the method comprises the following steps: determining a growth cycle and a critical period of crops of which a fertilization scheme needs to be analyzed; determining environment conditions and nutrient absorption characteristics of crop growth; determining types of fertilizer raw materials and fertilization modes according to environmental conditions and nutrient absorption characteristics; combined fertilization schemes corresponding to different growth cycles are generated according to fertilizer raw material types and fertilization modes; inputting the plurality of combined fertilization schemes into a first fertilizer effect prediction model to obtain evaluation results of the plurality of combined fertilization schemes; and determining an optimal combined fertilization scheme according to the evaluation results of the plurality of combined fertilization schemes. According to the application, a polyglutamic acid and compound fertilizer combination scheme is designed according to crop requirements, and then a scheme with an optimal crop growth effect is selected according to the evaluation model, so that crops can obtain required nutrients, and the production cost is reduced.

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 discloses a rapid evaluation method for heat resistance phenotypes of non-heading Chinese cabbages. The method comprises the following steps: step 1, performing standardized seedling culture under the conditions of day and night constant temperature of 22 DEG C / 18 DEG C, relative humidity of 60%, illumination for 16h / darkness for 8h and light intensity of 20000Lux; step 2, extreme high temperature stress treatment: the temperature is 49 + / -0.5 DEG C, the humidity is 60%-70%, the illumination intensity is 20000Lux, treatment is performed for 8 hours, and then culture is recovered; step 3, observing phenotypic indexes including survival rate S, leaf damage index D, plant height inhibition rate H and new leaf germination number N; 4, constructing a comprehensive evaluation model, and calculating a heat resistance index HI; 5, plant heat resistance phenotype rapid evaluation. According to the method, variety heat resistance accurate classification is achieved, professional instruments are not needed, the single cycle only needs 20 days, the supply pressure of non-heading Chinese cabbages in the high-temperature season is remarkably relieved, breeding standardization of stress-resistant varieties is promoted, and agricultural sustainable development is promoted.

The invention discloses a method for determining a chlorophyll concentration value of phytoplankton based on ocean heat waves. The method comprises the following steps: acquiring ocean green ecological remote sensing image data and ocean heat wave data of a target sea area; and inputting the ocean heat wave data and the ocean green ecological remote sensing image data of the target sea area into a chlorophyll concentration determination model, so that the chlorophyll concentration determination model determines the ocean heat wave grade of the target sea area according to the ocean heat wave data, inputting the ocean green ecological remote sensing image data into a chlorophyll concentration determination sub-model according to the ocean heat wave grade, enabling the chlorophyll concentration determination sub-model to extract corresponding multispectral remote sensing image features and ocean microwave remote sensing image features, and outputting a phytoplankton chlorophyll concentration value of the target sea area; and transmitting the phytoplankton chlorophyll concentration value of the target sea area to a marine ecological monitoring system to assist the marine ecological monitoring system in sea area monitoring. The method can improve the accuracy of determining the chlorophyll concentration value of the phytoplankton and the application reliability.

The invention belongs to the technical field of plant physiology dynamic monitoring and decision optimization, and particularly provides a healthy plant volatile matter component dynamic monitoring method based on big data, and the method mainly comprises the steps: obtaining plant volatile matter concentration time sequence data, an environment parameter set and meteorological time sequence data, performing collaborative preprocessing to obtain a time-space synchronous multi-dimensional data cube; and calculating an environment interference component based on the multi-dimensional data cube to obtain a physiological volatile matter feature set. According to the method, the problem of data distortion caused by difficulty in comprehensively capturing dynamic changes of volatile matters and integrating multi-dimensional associated information in a large-range, long-period and complex environment in the prior art is effectively solved, the actual release rule of the volatile matters is accurately mastered, and a powerful support is provided for evaluation and regulation and control decision of plant health-care efficacy.

The invention discloses a corn drought resistance identification device and method, and belongs to the technical field of agricultural scientific research. According to the method, the problems of inaccurate environment control, long identification period, poor repeatability and the like of an existing method are solved, the drought resistance index of the corn is calculated through the random forest model, the drought resistance grade of the corn is divided, and the drought resistance index threshold value is set; the drought resistance indexes of the corn in different growth periods are analyzed, the drought resistance index threshold value is dynamically adjusted according to the corn growth data monitored in real time, and the drought resistance of the corn in different growth periods can be reflected more accurately; feature importance scores are calculated through a random forest model, feature variables are sorted, and it can be determined that certain features make the greatest contribution to the drought resistance index; based on feature importance analysis, suggestions on corn drought resistance research and breeding are provided, researchers can be helped to optimize breeding strategies, errors caused by subjective judgment are reduced, and the breeding efficiency of drought-resistant varieties is improved.

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.

A round baler includes a bale size sensor operable to detect a radial size of a bale during formation thereof, a bale weight sensor operable to detect a weight of a completed bale, and a location sensor operable to determine a respective field origin location of the crop material gathered for each respective one of a plurality of radial layers of the bale. A controller calculates a density of a completed bale with data from the bale weight sensor and the bale size sensor. The controller determines a volume of a respective one of the radial layers during formation of a current bale, subsequent to the completed bale, with data from the bale size sensor. The controller may then estimate a density of the respective one of the radial layers based on the volume of the respective one of the radial layers, and the density of the previously completed bale.

The invention discloses a saline-alkali soil salt-tolerant crop intelligent breeding evaluation method and system. The method comprises the steps of crop data acquisition, crop data improvement, crop breeding evaluation model establishment and crop intelligent breeding evaluation. The invention belongs to the field of breeding evaluation, and particularly relates to an intelligent breeding evaluation method and system for saline-alkali soil salt-tolerant crops. According to the scheme, environmental suitability grade difference regulation is introduced, and it is avoided that only a single salt-tolerant grade sample is generated; target function optimization is carried out by introducing a stress level difference coefficient, and a function is adjusted through a phenotypic sample generator feature, so that a generated sample is highly matched with an actual salt stress rule of the saline-alkali soil; evaluating contributions of different hierarchical features of the crop breeding data according to a feature importance function through a hierarchical attention mechanism, and eliminating redundant features; by introducing environmental edge loss, the distinction degree of adjacent salt tolerance grades in the extreme saline-alkaline environment is improved; the distance between adjacent salt tolerance grade characteristic centers is increased, so that the crop breeding evaluation effect is improved.