19 results about "Leaf curl" patented technology

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.

The invention relates to a method and a system for measuring a curl index of a corn leaf and evaluating a drought stress degree. According to the method, a foundation laser radar is used for collecting point cloud data of a corn plant in the morning and the afternoon under different drought stress degrees in a large bell mouth period; threshold segmentation and stem leaf segmentation are carried out; performing optimization preprocessing operation on the blade point cloud; cutting the point cloud of the blade by using a gradually expanded cylinder, and calculating the vein point of the blade; carrying out equidistant plane segmentation on the corn leaf from the tip to the base of the leaf; calculating the Euclidean distance between two points which are farthest from each other in each section of blade section curve point cloud of the two sample sets; fitting the blade section curve point cloud by using a greedy sorting algorithm based on the shortest distance and a cubic spline curve, and calculating a spline curve fitting length; calculating a blade curl index and an average actual blade curl index of the blade; and finally performing drought stress degree grading evaluation.

The application 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 comprises the following steps: S1, acquiring an infrared image of a corn plant; S2, performing two-dimensional discrete wavelet transform to generate a boundary response graph; S3, generating a binary mask according to the characteristics of the leaf edge of the boundary response graph; S4, performing connected domain analysis to obtain candidate leaves and generate independent single-leaf masks; S5, removing small holes to obtain a mask and quantifying leaf curvature; S6, constructing a multi-dimensional feature vector containing the curling characteristics of the leaves; and S7, outputting the corresponding drought grade of the corn leaves through a multilayer perception machine model. The above method realizes automatic identification and early warning of the early water shortage state of corn.

This invention relates to the field of plant genetic engineering technology, specifically providing the application of the HA7 protein and its encoding gene in regulating rice plant height and grain traits. This invention obtains a dominant leaf-curling mutant through EMS mutagenesis. ha7, Research has found that, ha7 mutants and HA7 Overexpression plants all exhibited significantly reduced plant height, extreme leaf curling, and smaller grains, while knockout plants showed no significant changes in these phenotypes except for plant height. This invention can be used for targeted improvement of rice plant architecture, breeding new varieties with ideal canopy structure and optimized grain traits, which is of great significance for improving rice photosynthetic efficiency, lodging resistance, and yield potential.

The invention discloses a seedling culture device for forestry, belongs to the technical field of seedling culture, and aims to solve the problems that part of seedlings with weak growth vigor easily have physiological injury symptoms such as leaf curl, yellowing and scorched edges due to excessive illumination, timely dynamic shading regulation and control are not easy to carry out, and the seedling culture effect is poor due to the fact that illumination resistance characteristics of the seedlings of different forest tree varieties are different. The seedling raising device comprises a seedling raising box, a plurality of plant growth lamps are evenly arranged in the seedling raising box, a detection assembly is arranged in the seedling raising box, a plurality of seedling raising assemblies are rotationally connected in the seedling raising box, and a plurality of supporting rotating assemblies are arranged in the seedling raising box; according to the device, the dislocation degree of the through holes of the conical light shielding plate is adjusted, the light shielding area above damaged seedlings is accurately regulated and controlled, then the light shielding plate is pushed to achieve all-directional coverage, and a suitable weak light environment is created for leaf damage recovery.

The invention discloses an application of a GmCDC48c gene and an encoded protein thereof in regulation and control of soybean Cd resistance and accumulation. The soybean GmCDC48c gene is knocked out through gene editing to obtain a knockout mutant, under the stress of Cd, compared with WT, a mutant plant is short and small, the leaf base is red, the whole leaf curls, but the Cd concentration of grains is reduced, and Cd accumulation of soybeans is reduced. Therefore, the GmCDC48c gene is a regulatory factor for coding Cd resistance and accumulation, and can provide a new gene target for soybean genetic breeding.

This invention discloses an effective method for controlling leaf curling in macadamia nuts, comprising the following steps: selecting mineral oil with an effective ingredient content ≥99%, mixing it with water at a volume ratio of 1:100-400, then adding an emulsifier accounting for 0.05%-0.2% of the total weight of the mixture, stirring evenly to prepare a mineral oil emulsion; applying the emulsion using a misting device based on the growth characteristics of macadamia nuts during the shoot emergence period, pre-flowering period, young fruit stage, and mid-fruit development stage, combined with the differences in insect resistance among different varieties; integrating four measures: pruning and shaping control, orchard sanitation, soil regulation, and nutrient enhancement; and regularly monitoring key indicators such as thrips population density, leaf curling rate, and deformed fruit rate using a five-point sampling method, adjusting the control plan based on quantitative data. This invention achieves highly efficient control of thrips, prevents leaf curling, improves macadamia nut yield and quality, and protects the orchard ecological environment by optimizing the mineral oil emulsion formulation, precise application strategies, synergistic agricultural management measures, and dynamic monitoring and adjustment.

The application discloses a transplanted seedling survival state monitoring method and system based on image analysis, and belongs to the technical field of computer vision and intelligent forestry monitoring, and the method comprises the following steps: collecting a transplanted seedling canopy image and obtaining a canopy region image through illumination correction and background separation; performing leaf instance segmentation through a leaf segmentation network; calculating a leaf greenness index, a yellowing proportion and a browning area proportion in a multi-color space to obtain a color stress score; extracting a leaf curling degree, a wilting drooping angle and a leaf area change rate to obtain a morphological stress comprehensive degree; fusing color and morphological features based on a Bayesian inference framework to output a survival probability score and a health grade classification, and combining a time sequence recovery trend to dynamically correct.

The invention relates to the technical field of plant genetic engineering, and particularly provides an application of HA7 protein and a coding gene thereof in regulation and control of rice plant height and grain traits. The dominant curl leaf mutant ha7 is obtained through EMS mutagenesis, and research finds that both the ha7 mutant and an HA7 overexpression plant show phenotypes that the plant height is remarkably reduced, extreme leaves curl and grains become small, and the phenotypes of the knockout plant have no remarkable change except for the plant height. The method can be used for directionally improving the rice plant type and cultivating a new variety with an ideal canopy structure and optimized grain traits, and has important significance in improving the photosynthetic efficiency, lodging resistance and yield potential of rice.

The present invention relates to a Sonorum lycopersicum plant containing a QTL in its genome that confers an improved phenotype corresponding to leaf and / or fruit resistance and / or resistance to Tomato Brown Leaf Fruit Virus relative to a corresponding plant lacking the QTL, wherein the QTL is selected from the QTL present in the genome of the seed HAZTBRFVRES1 plant with NCIMB accession number 42758. The QTL is preferably characterized by defined alleles of different SNPs on chromosomes 6, 9, and 11. The present invention also relates to parts and progeny of these plants with improved phenotypes, the use of these plants for introgressing the improved phenotype in another genetic background, and different methods for obtaining tomato plants or seeds with increased leaf and / or fruit resistance or resistance to Tomato Brown Leaf Fruit Virus.

The present application relates to a method and system for quantitatively grading the severity of tobacco pepper vein banding virus disease. The present application is aimed at a specific subtype of tobacco pepper vein banding virus in Pu'er tobacco growing areas, excavates key differential symptom combinations, establishes a six-level quantitative grading standard for disease severity, takes the proportion range of leaf curling and deformity as the core grading threshold, realizes the transition from qualitative to quantitative evaluation, in addition, establishes a symptom combination evolution model, integrates scattered characteristics as a differential path, and improves the reliability of early identification; a grading model based on multi-parameter fusion calculation is constructed, which converts experience judgment into a mathematical process, improves the objectivity, consistency and scientificity of grading, and provides a key technical basis for standard development, breeding, drug efficacy test and monitoring.

The invention provides an application of an S1MLP1 gene in promoting broad-spectrum disease resistance of tomatoes. According to the invention, through overexpression of the S1MLP1 gene, the capability of the tomato in resisting gray mold, late blight and tomato yellow leaf curl virus disease is greatly improved, the production cost is saved, the environment is protected, the postharvest quality of the tomato can be effectively improved, and the method is especially suitable for cultivation under facility environment conditions.

This invention relates to a preparation process for jujube leaf green tea, comprising the following steps: Step 1, material selection and cleaning; Step 2, spreading and fixing: after spreading the leaves to dry at room temperature, stir-frying at 110-130℃ for 1-2 minutes, then removing from the pan and setting aside; Step 3, plasma treatment: spraying deionized water onto the leaves to adjust the moisture content, then performing cold plasma treatment, followed by drying at below 60℃; Step 4, rolling: rolling the leaves for 5-30 minutes until they curl into strips; Step 5, drying, shaping, and aroma enhancement: stir-frying at 60-100℃ for 18-22 minutes, continuing to roll and shape during the stir-frying process, then cooling to 40℃ and stir-frying for 13-17 minutes for aroma enhancement treatment, thus obtaining the final product. The jujube leaf green tea prepared by this invention has a clear and mellow aroma, a sweet aftertaste, and a clear and bright tea soup. It also exhibits high content and high dissolution rate of nutrients and active substances in the green tea.

The invention belongs to the technical field of molecular plant breeding, and particularly relates to application of a transcription factor RcWRKY36 in regulation and control of plant cold resistance and / or growth and development. The login number of the transcription factor RcWRKY36 in a release RchiOBHm-V2 database is RchiOBHmChr4g0425801, and the login number of the transcription factor RcWRKY36 in the release RchiOBHm-V2 database is RchiOBHmChr4g0425801. The research finds that under the condition of 4 DEG C, the leaves of the rosa chinensis overexpressed with the RcWRKY36 gene are still kept dark green, and new shoots germinate; and the RcWRKY36 gene silenced Chinese rose shows leaf curling and yellowing. The RcWRKY36 gene is a key gene for regulating and controlling the cold resistance and growth and development of the Chinese rose, and the application of the gene can break through the biological limitation of'growth-defense trade-off 'of plants. The research result not only enriches the molecular regulation mechanism of low-temperature stress response of the Chinese rose, but also provides a new theoretical basis and a breeding target for genetic improvement of cold tolerance of the Chinese rose.

The application discloses a double real-time fluorescent quantitative TaqMan primer probe set, a kit and a detection method for simultaneously detecting sweet potato leaf curl virus and sweet potato witches' broom phytoplasma, which is designed according to the nucleotide sequences of SPLCV and SPWB genome sequencing in a conservative segment, and is used for specific detection of SPLCV and SPWB; and the application also designs a fluorescent quantitative kit based on the primer probe set. The primer and probe set can simultaneously detect the target of SPLCV and SPWB in one reaction, is fast and convenient, has high detection efficiency, and has high detection sensitivity of 3.3 copies / uL, which is 100 times of that of ordinary PCR. The TaqMan QPCR detection technology established by the application for SPLCV and SPWB solves the problems of time-consuming and labor-consuming, poor specificity and sensitivity, and easy pollution in the existing detection methods of SPLCV and SPWB, and provides a technical basis for early diagnosis of SPLCV and SPWB.

The invention discloses a crop growth simulation method and system, and relates to the technical field of irrigation, and the method comprises the steps: building a physiological model according to the physiological change of crops, comprising the following steps: simulating a three-dimensional leaf model of a crop according to the leaf length, the leaf width, the leaf area, the leaf curl rate and the leaf distribution condition of the crop, simulating a three-dimensional physiological model of the crop according to the leaf area change degree of the crop, assimilation products of the crop under photosynthesis, respiration consumption of the crop under respiration, growth weight increment of the crop and organ dry weight of the crop; and jointly simulating the growth condition of the crop according to the three-dimensional leaf model of the crop and the three-dimensional physiological model of the crop. The device can truly simulate the crop growth process.

The invention provides a dry season high-standard farmland irrigation method and device and a storage medium, and relates to the technical field of farmland irrigation. Determining the current growth period of the crops; judging whether the current growth period of the crop reaches the target growth period or not, or whether the current drought stress degree of the crop reaches the drought degree which is delimited in advance according to the evapotranspiration amount and the leaf curling degree or not; based on the constructed initial crop dry season root system water demand model, obtaining a unit farmland crop root system water demand calculation value; the current water storage capacity of the buried water storage and irrigation device is obtained, and an irrigation water volume calibration value is obtained; the soil root system layer humidity and the crop drought stress relieving degree after the irrigation is completed for a set time period are obtained; if the corresponding predicted value is not reached, a deviation index is calculated, and an adjusted crop dry season root system water demand model is obtained; and iteration is carried out until a corresponding prediction value is reached. By adopting the irrigation method provided by the invention, the targeted precise irrigation of the root system can be realized, and the water-saving effect is improved.

This invention discloses a method and system for calculating the curl of corn leaves based on image processing. The method utilizes multi-location fixed-point acquisition of corn leaf image data; based on the image data, it extracts multi-view corn leaf features and reconstructs a three-dimensional image of the leaf from a point cloud; based on the minimum directed bounding box algorithm, it overlaps the three-dimensional image of the leaf with the minimum effective bounding box to obtain first geometric data; it extracts the first geometric data, calculates the corn leaf curl and projected area ratio, and determines the leaf health status; based on the corn leaf curl, it constructs a curvature heatmap and generates a dynamic curling process model based on a time series, capturing the deformation rate and generating a dynamic model, providing an effective method for smart agriculture from data acquisition to precise intervention.

The application discloses a cotton disease and pest grade recognition method and system based on spectrum and laser radar images, and belongs to the technical field of agricultural remote sensing. In view of the problems that single spectrum monitoring is greatly disturbed by light and is difficult to capture three-dimensional features such as leaf curling, a multi-modal collaborative perception fusion scheme is provided. The method synchronously collects spectrum images and laser radar data of a cotton canopy by using a UAV. After pretreatment and space-time registration, a multi-branch feature extraction network is constructed to extract fine spectrum features, spectrum image texture features and CHM data of the laser radar respectively. By designing a cross-modal attention module, the complementary weights of different modal features are dynamically calculated and weighted fusion is performed. The fused high-dimensional joint features are input into the constructed RCG-Net model, and an end-to-end cotton disease and pest damage grade is output, so that the disease and pest grade of the multi-scale cotton plant remote sensing data of the UAV is accurately recognized, and technical support is provided for disease and pest monitoring in intelligent agriculture.