38 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 discloses a tomato yellow leaf curl disease nondestructive testing method and device based on a hyperspectral imaging technology. The method comprises the following steps: acquiring hyperspectral imaging data of a tomato leaf sample; carrying out black and white correction on the hyperspectral imaging data, and extracting a region of interest; preprocessing the hyperspectral data after the region of interest is extracted; performing feature extraction on the preprocessed hyperspectral data to obtain a key wavelength with the maximum contribution to features; establishing an SVM model, a PLS-DA model and a GBM model, and training the three models by using the processed hyperspectral data to obtain a trained classification model; and detecting the tomato yellow leaf curl disease by using the trained classification model. According to the method, the hyperspectral data of the tomato plant sample to be detected are obtained in a lossless manner by using the hyperspectral imaging technology, and the data are subjected to feature extraction and classification by using a modeling method including machine learning, so that the classification result of the tomato yellow leaf curl disease is efficiently and accurately obtained.

The invention relates to a cotton leaflet character regulation gene and an encoded protein and application thereof, and relates to the technical field of plant genetic engineering, the nucleotide sequence of the gene is shown as SEQ ID NO.1, and the amino acid sequence of the encoded protein is shown as SEQ ID NO.2. According to the invention, a gene capable of regulating and controlling the leaf rolling character of cotton is obtained by cloning from the goblet oilless cotton and is named as a Ghcup gene, and silencing research is carried out on the Ghcup gene in upland cotton goblet oilless cotton by constructing a VIGS vector of the Ghcup gene of the cotton, so that the Ghcup gene can be used for regulating and controlling the leaf rolling character of the cotton. A cotton Ghcup gene overexpression vector is constructed, transgenic overexpression is carried out in normal broad-leaf upland cotton Xinluzhong 75, and results show that the curly phenotype of an oilless goblet-leaf cotton leaf of a silent Ghcup gene disappears, the overexpression of the gene causes the upward curly shape of the Xinluzhong 75 cotton leaf to be similar to a cup shape, and the cotton Ghcup gene overexpression vector is used for transgenosis overexpression in the normal broad-leaf upland cotton Xinluzhong 75. Therefore, the Ghcup gene has great application potential in the aspects of improving the leaf shape and the plant canopy structure of the cotton, improving the photosynthetic efficiency of the plant and the like.

The invention discloses a tea leaf fixation method based on deep learning, which comprises the following steps: S1, collecting tea leaf data in a fixation process, and preprocessing; s2, color change features, leaf curl features and temperature and humidity change features are extracted respectively, and feature alignment operation is executed; s3, executing a time sequence resampling operation on the cross-modal fusion feature representation, extracting a key fixation change frame and deleting a redundant frame; s4, extracting local and global features from the compressed state sequence; s5, inputting the state vector and the stage division label into an autoregression controller, and outputting a control parameter adjustment amount; s6, the heating temperature, the hot air moisture removal proportion and the stir-frying rotating speed of the fixation equipment are adjusted; and S7, periodically inputting the incremental training samples into the network model for parameter updating. According to the invention, multi-mode state accurate identification and intelligent closed-loop control in the tea leaf fixation process are realized, and the consistency and control precision of fixation quality are significantly improved.

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.

The invention discloses a dual real-time fluorescent quantitative TaqMan primer probe group, a kit and a detection method for simultaneously detecting sweet potato leaf curl virus and sweet potato arbuscular phytoplasma, aiming at nucleotide sequences of SPLCV and SPWB genome sequencing, corresponding specific TaqMan detection primer groups and probe primers are designed in conservative segments, and are used for specific detection of SPLCV and SPWB; the invention also designs a fluorescent quantitative kit based on the primer probe group. According to the primer and the probe group, the targets of SPLCV and SPWB can be detected at the same time through one-time reaction, rapidness and convenience are achieved, the detection efficiency is high, and meanwhile the high detection sensitivity of 3.3 copies / uL is achieved and is 100 times that of common PCR. The TaqMan QPCR detection technology established aiming at the SPLCV and the SPWB solves the problems that the existing SPLCV and SPWB detection method is time-consuming and labor-consuming, poor in specificity and sensitivity, easy to cause pollution and the like, and provides a technical basis for early diagnosis of the SPLCV and the SPWB.

The invention discloses a tomato yellow leaf curl disease condition grading method and system based on a hyperspectral imaging technology and DB-ResNet, and the method comprises the steps: firstly obtaining the hyperspectral imaging data of tomato leaves at different infection stages, and converting the hyperspectral imaging data into normalized reflectivity through black and white correction; then marking an area-of-interest of an upper leaf of the plant, cutting the image according to coordinates and spatially standardizing the image to a fixed pixel size, and then removing a noise wave band to construct a training data set; then establishing a DB-ResNet model and training, finally inputting the preprocessed to-be-detected sample data into the model, and outputting a tomato yellow leaf curl disease grade classification result. According to the method, hyperspectral data of a tomato plant sample to be detected is obtained in a lossless manner by applying a hyperspectral imaging technology, and the data is evaluated and graded by applying a modeling method including deep learning, so that a disease degree evaluation result of the tomato yellow leaf curl disease is efficiently and accurately obtained.

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 present invention provides the use of the AC4 gene, etc., for increasing GFP expression and / or inhibiting the degradation of mRNA decay substrates using GFP as a reporter gene. The present invention has discovered that AC4 has mRNA decay inhibition function, inhibiting the degradation of nonsense-mediated mRNA decay substrates using GFP as a reporter gene, as well as the degradation of endogenous nonsense-mediated mRNA decay substrates in Arabidopsis thaliana, without affecting ARE-dependent turnover. It can increase the mRNA expression of AtUPF1, AtXRN4, AT1G0106020, RPS6, and others, while reducing the expression of AT1G72450 and AT2G400. It can cause dwarfing and / or leaf curling in Arabidopsis seedlings, enhance the pathogenicity of PVX, interact with MeUpf1 or AtUpf1, and improve yeast growth ability in nutrient-deficient culture media. The research results will lay the foundation for clarifying the function of AC4.

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.

Task of the present disclosure is to provide a solanaceous plant and cells thereof and a method for producing the solanaceous plant where the plant has inhibitory properties against infection by a virus of genus Begomovirus causing tomato yellow leaf curl symptoms, propagation of the infected virus, and / or expression of infection symptoms, and the plant is resistant to the virus. The task is solved by providing a solanaceous plant having a mutation in at least one gene selected from a group consisting of DCL3 gene which is silencing associated dicer gene, 4CL06 gene which is 4-coumarate-CoA ligase gene, RLK2 gene which is receptor-like kinase gene, and genes homologous thereto. The mutation either inhibits the expression of the mutated gene or makes a protein encoded by the mutated gene to be non-functional for the virus, and the plant has virus resistance against the above-mentioned virus.

The present invention discloses a rice outermost cell specific gene 6 ( OsROC6 ) in rice breeding, belonging to the technical field of crop breeding. The present invention constructs a OsRoc6 Activated plants and CRISPR / Cas9 technology OsRoc6 The knockout transgenic plants showed the opposite phenotype, with significant changes in flowering time, plant height and leaf curling compared to wild-type plants; GUS staining showed OsRoc6 The discovery of these results will provide OsRoc6 It provides a strong theoretical basis for its role in rice breeding.

The invention discloses a control strategy for tomato yellow leaf curl virus, and belongs to the technical field of plant protection. A fragment with the length of 300bp between 201bp and 500bp in a TYLCV CP gene, a reverse complementary sequence and a sequence for forming a neck ring structure are selected and sequentially connected with an expression vector pBV220 to construct a recombinant plasmid pBV-TYLCV-CP, then the recombinant plasmid pBV-TYLCV-CP is transformed into an M-JM109-lacY strain, and a prokaryotic expression system obtained through construction can induce production of an extract containing dsRNA. Furthermore, the antiviral composition is prepared by mixing an extract containing dsRNA induced by a prokaryotic expression system and ZNC according to a concentration ratio, and the extract containing dsRNA and ZNC are mixed and sprayed to achieve a synergistic effect on the resistance of the yellow leaf curl virus.

The invention belongs to the technical field of agricultural planting, and particularly relates to a composition for treating grape leafroll disease and application thereof. The composition provided by the invention comprises curdlan. Experiments show that after the curdlan is sprayed on the surfaces of diseased grape leaves for 7 days, the curling level of the leaves can be reduced from level 3 to level 1; the decrease rate of the virus concentration can reach 22% to 37%. The invention further provides application of the composition in treatment of the grape leafroll disease, the composition and water only need to be evenly stirred according to a certain proportion and then sprayed to the surfaces of diseased grape leaves, and the operation method is simple. And the curdlan, as a natural extract, is healthy and non-toxic, and has no pesticide residue and no hidden danger of health risk when being applied to the treatment of the grapevine leafroll disease.

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.

The invention relates to the technical field of moisture detection, in particular to a moisture analysis and detection method and system based on tea processing, and the method specifically comprises the following steps: collecting multi-source heterogeneous data in the processing process of a tea frying machine in real time, and calculating a dynamic moisture distribution value; geometric deformation parameters of the blades in the constant-speed stir-frying stage are obtained, and a water permeation resistance coefficient based on the leaf crimpness is constructed; obtaining blade surface stress spectrum data at a non-uniform speed stage, and calculating a damage accumulation factor based on a microcrack growth rate; a comprehensive vulnerability index is generated in combination with a thermal-mechanical coupling effect, and the tea processing quality state is identified; and dynamically optimizing the stir-frying track according to the tea processing quality state, and outputting a staged time-varying regulation and control strategy. The problems that in an existing tea leaf processing moisture detection system, processing parameter adjustment lags behind, and the risk of leaf breaking is aggravated are solved.

The invention discloses a leaf apoplast solution extraction method, and relates to the technical field of plant leaves. The method for effectively extracting the AWF of the corn leaves is established by taking seedlings cultured by a nutrient solution as a test material, researching the extraction efficiency of the exosome with different centrifugal forces and different leaf curling angles in a centrifugal tube and optimizing the extraction centrifugal forces and the leaf curling angles, and can be applied to plant exosome research, so that the method for effectively extracting the AWF of the corn leaves is established. A foundation is laid for accuracy and reliability of research results such as proteomics and metabonomics, and reference is provided for optimization of AWF separation methods of other crops.

The invention provides a crop curl degree-based drought grade discrimination method, which comprises the following steps: acquiring images of different drought grades of crops in different growth stages, preprocessing the images, and training a Mask R-CNN model as input to obtain a leaf curl degree-based drought grade discrimination model of the crops in different growth stages. The crop image can be collected in real time and preprocessed, the drought grade of the crop can be discriminated by using the drought grade discrimination model of the crop in different growth stages based on the leaf curl degree to obtain the drought grade of the crop, the change of the drought grade of the crop can be timely and accurately discriminated in a large range, the rescue opportunity is prevented from being missed, and the survival rate of the crop is improved. And the situation that the crop growth is severely influenced is avoided.

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 present invention discloses a tomato leaf disease and insect pest detection method based on improved YOLOv5s, which relates to the field of target detection technology. The method comprises the following steps: S1: using tomato leaf disease and insect pest images in the Plant-Village plant disease public dataset to form a tomato leaf disease and insect pest dataset, which specifically includes three categories: tomato late blight, tomato leaf mold, and tomato yellow leaf curl disease, and using open source software LabelImg to perform anchor frame annotation and category classification on different types of diseases and insect pests; S2: dividing the tomato leaf disease and insect pest dataset into a training set, a validation set, and a test set, which are respectively used for model training and testing; S3: adopting YOLOv5s as a basic model, adding a DCAM attention mechanism module to the fourth layer of the original network, using a C3STR module integrated with a Swin Transformer Block to replace the C3 module in the sixth layer of the original network, and simultaneously using a BiFPN network to replace the Neck part of the original YOLOv5s; the present invention improves detection accuracy and detection effect while increasing a small amount of parameters and model size.

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 discloses a plant water potential real-time nondestructive detection system and method, and relates to the technical field of plant water potential detection.The method comprises the steps that firstly, multispectral reflection data and surface deformation data of a target leaf are obtained; then calculating a leaf curl index, and extracting a spectral distortion amount; judging whether the curl index exceeds a preset threshold value or not, if yes, switching the detection wavelength to calculate a compensated water potential value, and if not, calculating a standard water potential value; and finally, adjusting mapping relation parameters according to the water potential value time sequence change. Real-time performance is achieved, and a water potential result can be rapidly obtained; non-destructive testing is adopted, and plants are not damaged; multispectral and deformation data are integrated, and the mapping relation between the two is combined, so that the detection accuracy is high; the wavelength can be adaptively switched according to the curling condition of the blade, and the adaptability is high; parameters can be dynamically adjusted, so that a detection model is continuously optimized, and a reliable means is provided for monitoring the plant moisture state.

Present invention relates to a virus resistant solanaceous plant, a solanaceous plant cell, and a method for producing the solanaceous plant, and the solanaceous plant has inhibitory properties against: infection by a virus of genus Begomovirus causing tomato yellow leaf curl symptoms, proliferation of the infected virus, and / or expression of infection symptoms. The present invention provides a solanaceous plant having a mutation in at least one gene selected from a group consisting of translation initiation factor eIF4E gene, receptor-like kinase RLK gene, coatomer complex deltaCOP gene, nuclear shuttle protein interactor NSI gene, and genes homologous thereto. The mutation in such a solanaceous plant either inhibits the expression of the mutated gene or makes a protein encoded by the mutated gene to be non-functional for the virus, and the solanaceous plant has virus resistance against the above-mentioned virus.

The invention belongs to the technical field of crop drought grade discrimination, and particularly relates to a crop drought grade real-time discrimination system, which is characterized in that images of crops suffering from different drought grades in different growth stages are acquired, preprocessed and used as input to train a Mask R-CNN model, and the drought grade of the crops is determined. The method comprises the following steps: acquiring a crop image in real time to obtain a drought grade discrimination model of different growth stages of crops based on the leaf curl degree, further acquiring the crop image in real time, performing preprocessing, and performing drought grade discrimination by using the drought grade discrimination model of different growth stages of crops based on the leaf curl degree to obtain the drought grade of the crops. The crop drought level change can be timely and accurately judged in a large range, the rescue opportunity is prevented from being missed, and the situation that the crop growth is seriously influenced is avoided.

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 belongs to the technical field of plant genetic engineering, and specifically relates to the BnACO1 gene and protein, and their application in regulating the height of Brassica napus plants. The present invention isolated the plant height-related gene BnACO1 from the leaf curl mutant Bnuc1 of Brassica napus. Subcellular localization results indicate that BnACO1 is localized to the cytoplasm and cell membrane. A BnACO1 overexpression vector was constructed and used to transform the Brassica napus wild-type Zhongshuang 11 (ZS11). Compared with the control ZS11, transgenic positive plants exhibited significantly reduced plant height, shrunken leaves, and a delayed flowering period of 5-7 days. The present invention discloses that BnACO1 can control rapeseed plant height, which is of great value in dwarf rapeseed breeding.

This invention discloses a method, medium, and equipment for grading raw tea. The method includes: acquiring raw tea information containing a first visible light image, first near-infrared spectral information, and first three-dimensional morphological information at a preset sampling frequency; performing illumination compensation, geometric correction, and multi-source registration processing on the raw tea information to obtain standard tea information; extracting static quality parameters such as leaf curl from the registered second visible light image, analyzing and obtaining physicochemical quality parameters from the second near-infrared spectral information, and extracting structural features such as leaf compactness from the second three-dimensional morphological information; finally, determining the grade through a cascaded decision model and controlling the sorting device to perform corresponding sorting actions. This invention achieves the fusion analysis and intelligent grading of multi-dimensional characteristics of raw tea, effectively improving sorting accuracy and efficiency.

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.