1398results 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 invention relates generally to devices, methods and systems for acquiring plant data. Disclosed is a field-deployable sensor attachable to plants for acquisition of plant-related data comprising: a probe including; a probe body with at least one aperture therethrough which locates the placement and spacing of one or more thermally conductive pins within the tissue of a plant; the one or more thermally conductive pins having distal and proximal ends, said distal end traversing through said aperture in the probe body and insertable into the tissue of the plant, and said proximal end located within the deployable sensor; such that when inserted into the tissue the pin approaches thermal equilibrium with the temperature of the region of the tissue in which the pin is located; and, a temperature sensor (T-sensor) enclosed within the deployable sensor located adjacent the proximal end of the pin to acquire the temperature of the proximal end of the pin; such that the T-sensor through the thermal equilibration of the pin with the plant tissue acquires plant tissue temperature data.

Described herein are systems and methods for monitoring plant health by communicating with plant-associated persona(s) via artificial intelligence. These systems and methods can communicate information about the health of plants in a natural-language format through the use of plant-based sensors for collecting data on plant health, analytical models and processors for processing the data on plant health, large language models for converting the data on plant health into a persona-guided, natural-language format, and user devices for receiving the data on plant health in the natural-language format.

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.

The invention discloses an identifying and grading method for saline-alkaline resistance of crops in a germination period, and relates to the technical field of crop planting. In order to solve the problems that in the prior art, due to different saline-alkali soil conditions in different regions, different crops or different varieties of the same crop have different saline-alkali tolerance capacities, and a unified and standard identification process and a grading standard are lacked. Through the steps of standardized seed treatment, seedbed construction and seed sowing, the uniformity and controllability of experimental conditions are ensured, errors caused by experimental operation differences are reduced, the accuracy and repeatability of experimental results are improved, saline-alkali soil environments of different degrees can be accurately simulated by preparing saline-alkali mixed solutions of different concentrations, and the saline-alkali soil quality is improved. The method provides a reliable basis for evaluating the saline-alkaline tolerance of the crop seeds, compares saline-alkaline stress of different concentrations under the same experimental condition, evaluates the saline-alkaline tolerance grade of the crop seeds, and is suitable for saline-alkaline tolerance evaluation of most crop seeds.

The invention relates to the technical field of agricultural production, in particular to a field corn and wheat drought tolerance data analysis and monitoring method which comprises the following steps: S1, data acquisition: acquiring environment and physiological data of field corn and wheat based on a multi-source sensor; s2, data preprocessing: preprocessing the collected environment and physiological data, and integrating the environment and physiological data into comprehensive data; s3, a leaf angle regulation and control transpiration mechanism: analyzing the influence of the leaf angle change of the corn and wheat on illumination absorption and transpiration rate, optimizing the leaf angle in real time to adapt to the change of illumination intensity, and predicting the water consumption conditions of the corn and wheat under different illumination conditions; s4, drought tolerance analysis: evaluating the drought tolerance of corn and wheat. According to the system, the utilization efficiency of water resources is improved, healthy growth of crops in a drought environment is ensured, and the practicability of farmland management and the scientificity of decision making are improved.

A screening method for a drought-resistant germplasm of Ophiopogon japonicus related to the field of Ophiopogon japonicus planting is provided. The method uses Ophiopogon japonicus of the main production areas, which requires a large amount of water and rainfall during the growth period, the drought-resistant germplasm that is suitable for growing well is conducted with drought stress under the drought condition. The growth indicators and the physiological indicators of different Ophiopogon japonicus germplasm under drought stress conditions are comprehensively evaluated and ranked to evaluate the drought-resistant ability of the different germplasm. The screening method is scientific and effective, and can comprehensively evaluate the drought resistance ability of Ophiopogon japonicus under the drought stress conditions, laying a technical foundation for the screening and promotion of in the Ophiopogon japonicus with drought resistance ability.

A monitoring and evaluation method for comprehensive evaluation index of machine-harvested cotton defoliation effect and system thereof relates to the field of monitoring and evaluation of cotton-harvested indexes. The RGB images of the machine-harvested cotton canopy are firstly acquired to extract visible-light vegetation index features, color component features and texture features of machine-harvested cotton canopy RGB images; the visible-light vegetation index features, color component features and texture features are input to the trained comprehensive evaluation model of machine-harvested cotton defoliation effect, to output the defoliation effect evaluation value; finally, the harvesting timing of machine-harvested cotton is determined according to the defoliation effect evaluation value. The invention can improve the accuracy and efficiency of monitoring and evaluating the comprehensive evaluation index of the machine-harvested cotton defoliation effect and provide a reference for the machine-harvested cotton defoliation effect research and the machine-harvested cotton best harvesting time determination.

The present disclosure describes, in part, compositions and methods for safeguarding plant immunity to pathogens in response to environmental changes.

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 an intelligent monitoring and evaluation system and method for urban green land carbon sequestration, and relates to the technical field of carbon sequestration evaluation, and the monitoring and evaluation method comprises the following steps: constructing a carbon sequestration evaluation system to evaluate each carbon sequestration monitoring record; capturing green land planting types in the area monitored by each carbon sequestration monitoring record to obtain the carbon sequestration capacity of each planting type; extracting influence factors influencing the comprehensive carbon sequestration capability of the region; analyzing the carbon sequestration capability difference in different time periods to obtain the influence degree of each influence factor; obtaining a theoretical carbon sink condition of each region, and generating a plurality of abnormal regions; based on the influence degree of each influence factor, carrying out green land adjustment reminding on any abnormal region, and giving an adjustment suggestion; by effectively analyzing the carbon sequestration capacity of each planting type, the carbon sequestration condition of each region of the city is accurately analyzed, and workers are helped to reasonably plan the green land of the city.

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.

A sensing device and a method for sensing an electrical property of a test sample is provided. The sensing device includes a substrate, and a closed loop resonator and an open loop resonator arranged on the substrate, and are arranged in a cascade configuration, the open loop resonator including a first loop end and a second loop end arranged at an edge of the substrate and are configured to be in contact with the test sample. In this regard, the closed loop resonator is configured to couple in an input excitation and to transfer the input excitation towards the open loop resonator. Furthermore, the open loop resonator is configured to generate localized electric fields between the first loop end and the second loop end propagating through the test sample.

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 provides soybean saline-alkaline tolerance simulation experiment equipment and method.The soybean saline-alkaline tolerance simulation experiment equipment comprises a sowing test bed, a closed box is connected to the top face of the sowing test bed, a sowing soil layer is arranged on the inner side of the closed box, a driving gear ring is arranged on the outer side of the sowing soil layer, and the driving gear ring is rotationally connected to the inner side of the top face of the sowing test bed in a limited mode; a saline-alkali water spraying tank is arranged on one side of the driving gear ring, the driving gear ring is in transmission connection with the saline-alkali water spraying tank, a sunlight simulation lamp set is arranged over the sowing soil layer and is in transmission connection with the driving gear ring, and a soil water conveying tank is arranged on the side, adjacent to the side connected with the saline-alkali water spraying tank, of the driving gear ring; according to the device, the saline-alkali water spraying tank automatically and intermittently sprays atomized saline-alkali water to the upper part of the sowing soil layer, meanwhile, the sowing soil layer can automatically feed saline-alkali water into the interior and the upper part of the sowing soil layer in the day or at night, and the precision of a soybean saline-alkali tolerant sowing experiment result is improved.

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.

An autonomous ground vehicle for agricultural plant and soil management operations. According to some embodiments, autonomous ground vehicle includes: a camera unit configured to generate images of agricultural ground soil and plant organisms, a first mechanical arm having an end effector comprising a hoe portion and an electrode portion, a second mechanical arm having an end effector comprising an electrode portion, a high voltage booster electrically connected to the electrode portions, an electronic memory storage medium comprising computer-executable instructions; one or more processors in electronic communication with the electronic memory storage medium, configured to execute the computer-executable instructions stored in an electronic memory storage medium for implementing a plant species control management operation comprising electrical control and mechanical control options.