1157 results about "Phenotype" patented technology

The invention relates to the technical field of Chinese trumpet creeper breeding, and discloses a Chinese trumpet creeper-based efficient breeding decision support system and method. The method comprises the following steps: acquiring multi-dimensional phenotypic data in a Chinese trumpet creeper breeding test, wherein the multi-dimensional phenotypic data comprises plant height, leaf area, flowering period and yield indexes; performing normalization processing on the multi-dimensional phenotypic data, eliminating influences of different dimensions, and calculating a variable coefficient of each phenotypic index; then screening out phenotypic indexes of which the stability is higher than a preset threshold value based on the variable coefficient, and constructing a Chinese trumpet creeper phenotypic feature matrix; carrying out dimensionality reduction on the Chinese trumpet creeper phenotypic feature matrix by adopting an adaptive weighting algorithm, and extracting key phenotypic features; inputting the key phenotypic features into a genetic algorithm optimization module, and calculating the contribution degree of each genetic locus in combination with the Chinese trumpet creeper genotype data; and constructing a Chinese trumpet creeper breeding decision model according to the contribution degree of the gene locus, and outputting an optimal breeding combination scheme. The system can optimize the Chinese trumpet creeper breeding process and provide effective support for Chinese trumpet creeper breeding work.

The invention belongs to the technical field of pepper planting, and discloses a pepper multi-branch gene CaBr1 linked KASP molecular marker as well as a primer, a kit and application thereof, the KASP molecular marker takes pepper S8 (zhangshuang) as a reference genome, and the single nucleotide polymorphism at the 103175415th basic group on the No.8 chromosome is subjected to basic group G-to-A replacement. A chromosome region closely linked with multiple branches of the pepper is obtained by using a BSA (Bovine Serum Albumin) population positioning method, a molecular marker is developed in a candidate region to determine a candidate gene CaBr1, a KASP molecular marker is screened according to base mutation of the candidate gene, and the marker is used for carrying out genotype identification on 90 randomly sampled single plants of an F2 population, and the coincidence rate reaches 100%. The result not only contributes to pepper branch phenotype identification and assistant breeding, but also lays a foundation for map-based cloning of the branch gene and analysis of a molecular mechanism of pepper plant type regulation.

The invention discloses an application of an OsPES gene and an encoding protein thereof in regulating and controlling the tiller number of rice, and belongs to the technical field of biology. According to the application disclosed by the invention, two OsPES BRCT structural domain homozygous knockout strains Ospesc-cas9-1 and Ospesc-cas9-5, two OsPES overexpression strains OE-OsPES-3 and OE-OsPES-7 and two RNAi (Ribonucleic Acid Interference) interference strains RNAi-OsPES-1 and RNAi-OsPES-6 are respectively obtained by taking japonica rice'cloud guide 'as a background material and utilizing related technologies. Phenotypic observation and statistical analysis find that compared with a wild type, the tiller number of an overexpressed OsPES strain is increased, and the tiller number of an OsPES interference strain and the tiller number of a BRCT structural domain knockout strain are reduced. It is found for the first time that OsPES can positively regulate the tiller number of rice and has application significance in regulation of the tiller number of rice and new strain breeding.

The invention relates to the technical field of molecular markers, in particular to an Indel molecular marker related to yellow leaves of a melon seedling growing point and application of the Indel molecular marker. The invention explores a key candidate gene MELO3C016136 for controlling the leaf color of the growth point of the muskmelon seedling, and develops an Indel molecular marker ygp2 for identifying the leaf color change of the growth point of the muskmelon seedling based on the key candidate gene MELO3C016136. The molecular marker ygp2 can be used for identifying the leaf color change character of the growth point of the muskmelon seedling, only one-time PCR amplification and polyacrylamide gel electrophoresis need to be carried out on the DNA of the plant to be detected, the identification result is reliable, the genotype of the target plant can be simply and conveniently identified, and the genotype identification result is completely consistent with the leaf color phenotype of the growth point of the seedling; important technical support is provided for creating new muskmelon germplasm with yellow seedling growing point leaves.

The invention discloses a positioning method of trachinotus ovatus growth trait related QTL (quantitative trait loci) based on 2b-RAD technology and application, the method uses 2b-RAD technology to perform sequencing on 300 trachinotus ovatus full-sib F1 generation and male and female parent individuals and develop SNP (single nucleotide polymorphism) markers, constructs a trachinotus ovatus high-density genetic linkage map, performs linkage positioning analysis in combination with 8 growth phenotype data, and finds that the trachinotus ovatus growth trait related QTL is found. 85 stable QTLs associated with the growth traits are screened out, and the stable QTLs contain 763 SNP sites. The invention also discloses an application of the method in a genetic map of trachinotus ovatus growth character positioning or molecular marker-assisted breeding of trachinotus ovatus, and the SNP molecular markers of trachinotus ovatus can be applied in genetic map construction and growth character positioning. Particularly, the method has a good application prospect in trachinotus ovatus growth trait molecular marker assisted breeding.

The invention relates to the technical field of molecular biology, and discloses 74 core molecular marker sets for identifying cold resistance of pennisetum alopecuroides, a primer group, a detection reagent, a kit, a gene chip and application thereof. According to the method, core germplasm resources of pennisetum alopecuroides are systematically collected, and the GWAS population is constructed by utilizing multi-environment (different altitudes) conditions, so that wide genetic and phenotypic variation is fully covered, and a representative material foundation is laid for cold-resistant genetic analysis. In the aspect of phenotype evaluation, a method for determining the number of reviving and root cutting seedlings after natural overwintering by combining single-root double-stem-node oblique cutting planting is innovatively provided, a set of scientific and stable cold resistance and reproducibility evaluation system capable of being operated in a standardized mode is established, and the reliability and efficiency of phenotype identification are remarkably improved. The detection is not influenced by human and climate environments; the method realizes efficient and accurate early cold resistance identification of pennisetum alopecuroides, greatly improves the breeding screening efficiency and scale, and accelerates the breeding process.

The invention relates to the technical field of crop genetic breeding, in particular to a plateau rape adaptive germplasm breeding method based on multi-character collaborative screening, which comprises the following steps of: constructing a multi-character evaluation system covering more than 20 indexes of four categories of agriculture, physiology, quality and stress resistance, and determining character weights by applying principal component analysis, grey relational analysis and analytic hierarchy process; and acquiring data by combining unmanned aerial vehicle multispectral imaging, a ground phenotype platform and a molecular marker technology, and substituting the data into the comprehensive evaluation model for germplasm screening. According to the method, the limitation of traditional single-character breeding is broken through, multi-dimensional collaborative evaluation is achieved, and the plateau rape germplasm breeding efficiency and accuracy are remarkably improved.

The invention belongs to the technical field of molecular biology and genetic breeding, and discloses a molecular marker of a locus qSGC.A8-3 remarkably associated with glucosinolate in brassica napus seeds and application of the molecular marker. A locus qSGC.A8-3 remarkably related to the glucosinolate content of the rape seeds and a peak SNP marker Bn-A08-p12638473 of the locus qSGC.A8-3 are located at 10th, 557th and 348th basic groups of a reference genome A08 chromosome of the rape DarmorV4.1, the average additive effect is 9.6 mu mol / g, and 7.5% of phenotypic variance can be explained. When the PARMS marker designed by the SNP is used for detecting rape germplasm resources, the PARMS marker is simple and convenient to operate and clear in typing, and the average thioglycoside content of AA genotype material seeds is higher than that of GG genotype material seeds, so that the PARMS marker has a good selection effect on the thioglycoside of the rape seeds.

The invention discloses a molecular marker closely linked with a cowpea salt tolerance major QTL (quantitative trait loci) and a primer sequence of the molecular marker. The name of the cowpea salt tolerance major QTL is SC300126, a KASP type molecular marker 300126 closely linked with the cowpea salt tolerance major QTL is located at the position of 43816166 bp on a chromosome 11, the marker can be used for amplifying a material to be detected, and whether a sample carries key allelic variation for controlling salt tolerance or not is judged according to the genotype of the marker. The molecular marker and the primer provided by the invention can be used for quickly screening the cowpea salt tolerance major QTL, and compared with a traditional phenotype identification method, the molecular marker and the primer have the advantages of high detection flux, accurate and reliable result and the like, and the typing accuracy can reach 99% or above. The technology can significantly improve the breeding efficiency of the salt-tolerant variety of cowpea and shorten the breeding period.

The invention relates to the technical field of litchi phenotype analysis, in particular to a litchi phenotype recognition and weight estimation method based on multi-modal learning, and adopts the technical scheme that an RGB (Red, Green, Blue) image and a depth image are used as bimodal input and are input into a LitchiPhenoNet model to realize detection and segmentation of fruits; an RD fusion module is adopted to significantly improve the multi-modal feature expression capability and segmentation performance, and the fusion strategy integrates texture details of an RGB image and space structure information of a depth image, so that the accuracy and robustness of detection and segmentation are improved; on the basis of geometric features and abstract intermediate features directly extracted by LitchiPhenoNet, fruit weight estimation is performed by adopting a multi-modal regression method, a regression model combines information from two aspects of vision and physics, and by combining the two types of features, the regression model can effectively improve the utilization efficiency and prediction precision of multi-modal data, so that the prediction accuracy of the fruit weight is improved. The multi-modal regression framework effectively integrates complementary information of geometric features and intermediate visual features, so that the accuracy and robustness of litchi weight estimation are improved.

The invention relates to a quorum sensing intelligent regulation and control method for violaceum violaceum in an antibiotic gradient region, and aims to solve the problems of uncontrollable multi-partition microenvironment and low biological behavior consistency in an existing system, the quorum sensing intelligent regulation and control method for the violaceum violaceum in the antibiotic gradient region comprises the following steps: accurately positioning space partitions, and collecting liquid phase pH, oxygen concentration and nutrient components in each region in real time by an integrated sensor; high-throughput detection and multi-modal data fusion are combined, and an AI model is input to establish association mapping of a liquid / gas phase environment and a biological phenotype. The system automatically generates and optimizes a partition gas component adjustment instruction, realizes spatial synchronous gas phase regulation and control by utilizing a programmable micro-airflow device, and realizes multi-region environment dynamic balance regulation and control in a culture chamber.

The invention discloses an EsSTB1 gene capable of increasing the number of branches of a plant, reducing the plant height and delaying flowering. The EsSTB1 gene has the functions of increasing the number of branches, reducing the plant height and delaying flowering, and a scientific basis and a new material are provided for cooperative regulation and control of tillering formation and reproductive growth of siberian wildrye; besides, the functional verification method of the EsSTB1 gene provided by the invention performs functional verification by applying transgenic arabidopsis thaliana starting from an internal regulation mechanism of tillering regulation of siberian wildrye, has obvious research depth and breadth and technical effects, and can obtain a plant strain with an intentional phenotype. Through verification, the siberian wildrye EsSTB1 gene disclosed by the invention can be used for remarkably increasing the number of branches of a plant, reducing the plant height and delaying flowering. The method is suitable for popularization and application in the biotechnology field.

The invention belongs to the technical field of plant molecular markers, and particularly discloses an Indel molecular marker related to the salt tolerance of brassica napus and application of the Indel molecular marker. The marker is located at the position of an A01 chromosome scafoldA0133077947 of a brassica napus reference genome ZS11.v10, and the genotype of a polymorphic site is CTAA or C. The invention further discloses a method for identifying the marker of the brassica napus. Large-scale group phenotypic association analysis proves that the molecular marker is remarkably associated with the salt tolerance of the brassica napus in the germination period, and when the polymorphic site genotype is CTAA, the salt tolerance in the germination period is high; when the genotype of the polymorphic site is C, low salt tolerance in the germination period is shown. The invention finds that the polymorphic site is obviously associated with the salt tolerance of the brassica napus for the first time, provides a powerful molecular tool for solving the problems of difficulty in phenotype identification, long period and low efficiency in salt tolerance breeding of the brassica napus, can accurately screen salt-tolerant materials in the early stage, and greatly accelerates the breeding process of new varieties of the salt-tolerant brassica napus.

The invention discloses a corn crossbreeding intelligent matching system and method based on artificial intelligence, and the method comprises the steps: collecting molecular marker genotype data and phenotype data of candidate parents, calculating the genetic distance between the parents, and constructing a genetic distance matrix; analyzing the phenotypic complementarity degree of the parent pair, and calculating a phenotypic complementarity index; constructing a heterosis prediction model based on genetic distance and phenotype complementarity, and predicting the yield heterosis value of the candidate hybrid combination; evaluating the environmental adaptability and resistance comprehensive score of the candidate combination; and adopting a Pareto multi-objective optimization strategy to screen an optimal matching scheme. According to the method, molecular marker data and phenotype data are integrated, a heterosis prediction model considering a genetic distance nonlinear effect is constructed, collaborative optimization of multiple breeding targets such as yield, resistance and environmental adaptability is achieved, the prediction accuracy is improved by about 20% compared with that of a traditional method, and the method is suitable for large-scale popularization and application. And an intelligent and precise decision support tool is provided for corn crossbreeding.

The invention relates to the technical field of biology, in particular to a rice salt stress regulation gene OsMTA1 and application thereof.The rice salt stress regulation gene OsMTA1 is obtained by conducting CRISPR gene editing on the OsMTA1 gene, and compared with receptor rice Zhonghua 11 (ZH11), after two independent strains with mutants knocked out of the transgenic rice OsMTA1 gene are subjected to 180mM NaCl simulated salt stress treatment, the rice salt stress regulation gene OsMTA1 is obtained. After recovery treatment, phenotype observation and survival rate statistics are carried out, it is confirmed that the osmta1 mutant has a salt-sensitive phenotype compared with wild type ZH11, and it is indicated that the OsMTA1 gene plays an important role in the process of responding to rice salt stress.

The application is suitable for the technical field of germplasm resources, and provides a germplasm resource data management system.The system comprises: an approval and registration sample management system, a resource survey collection management system, a germplasm resource library position management system, a germplasm resource phenotype database and a germplasm resource genotype database, the approval and registration sample management system manages data of crop standard samples; the germplasm resource phenotype database stores phenotype data of crop germplasm resources; the germplasm resource genotype database stores genotype data of crop germplasm resources; the germplasm resource library position management system manages data of crop germplasm resources; the phenotype data of crop germplasm resources, the genotype data of crop germplasm resources and the data of crop germplasm resources are corresponded through library number coding.The application can scientifically manage crop germplasm resource data, and can also realize internet sharing of crop germplasm resource data.

The invention belongs to the technical field of biology, and particularly relates to a synthetic probiotic phenotypic characteristic prediction method and system.The method comprises the steps that a genome is divided into gene units, K-mer sequences containing position weights and codon coding information are extracted from the gene units, and an initial characteristic vector is constructed for each strain; by calculating mutual information between each K-mer feature and a known phenotype, identifying which gene segments are most critical for predicting a target phenotype, and distributing significance weights for the gene segments; after the feature vectors of the known strains are optimized and weighted through the weights, a machine learning prediction model is trained; and when a new synthetic probiotic needs to be predicted, executing the same feature extraction and weighting process on the genome of the new synthetic probiotic, and inputting the obtained vector into the trained model to obtain a prediction result of the phenotypic features of the new synthetic probiotic.

The invention provides a plant phenotype platform three-dimensional imaging method and device based on multi-sensor fusion, and the method comprises the steps: collecting the original three-dimensional point cloud data of a plant through a plurality of heterogeneous imaging sensors carried on a plant phenotype platform, and carrying out the time synchronization processing and space registration processing. And dynamically calculating the confidence coefficient weight of each data point according to the environment illumination condition, the measurement attribute of each data point in the registration point cloud set and the characteristics of the imaging sensor to which the data point belongs, and obtaining a point cloud set with a point-level confidence coefficient weight. Performing adaptive weighted fusion processing according to the spatial distribution of the point cloud set to generate a preliminary fusion point cloud model; and according to a quality index of the model and a real-time environment illumination condition, dynamically adjusting and calculating a weight parameter of a confidence coefficient weight, and finally outputting an optimized three-dimensional point cloud model after iterative optimization. The defect that a fusion result of an existing plant three-dimensional phenotype accurate acquisition scheme is insufficient in stability and precision in a complex and changeable field environment is overcome.

Embodiments of the disclosure include systems and non-transitory computer readable media for analyzing microscopy images for developing machine learning models for disease modeling. Microscopy images are captured from cells of one or more exposure response phenotypes (ERPs) and further used to train machine learning models. Thus, trained machine learning models can distinguish between microscopy images captured from healthy and diseased samples.

The invention discloses a forest tree genotype-environment interaction modeling method based on multi-modal deep learning, and relates to the technical field of forest tree breeding, the method comprises the following specific steps: multi-modal data acquisition: adopting a high-throughput phenotype platform, a whole genome sequencing technology and soil nutrient detection equipment to acquire multi-modal data; sNP locus genotype data, soil key physicochemical index environmental data and growth-related morphology and biomass parameter phenotype data of forest trees are collected respectively; forest genotype, environment and phenotype multi-modal data are collected through the system, the genotype-environment interaction algorithm and the phenotype prediction model are constructed after preprocessing and fusion, the model can accurately predict forest phenotypes, the breeding screening period is remarkably shortened, the breeding selection precision and efficiency are greatly improved, and the method is suitable for large-scale popularization and application. The method effectively solves the problem that a traditional breeding mode is short in time and efficiency, enables breeding work to respond to market demands and environmental changes more quickly and accurately, and provides powerful support for sustainable development of the forestry industry.

A computer-implemented method of determining one or more sets of features to predict the presence of a particular phenotypic characteristic comprises: (a) receiving patient data comprising, for each of a plurality of patients: a feature profile comprising a respective feature status for each of a plurality of features for that patient; and an indication of whether that patient expresses the particular phenotypic characteristic; (b) using a genetic algorithm to generate a plurality of generations of individuals, wherein each individual comprises a subset of the predetermined plurality of features, each generation of individuals generated based, at least in part, on a plurality of fitness scores, each fitness score corresponding to a respective individual in the previous generation, and parameterizing a predictive accuracy of the set of features, each fitness score being calculated based at least in part on the patient data; (c) repeating step (b) until it has been performed N times; (d) from the plurality of individuals generated in steps (b) and (c), selecting a subset of the individuals based on their fitness scores; (e) clustering the selected subset of individuals to generate a plurality of clusters of individuals, based on the similarity of their respective subsets of features; (f) from each cluster, identifying a respective characteristic feature set based on the frequency with which features appear in individuals in that cluster.

The invention discloses a camellia chekiangoleosa improved variety breeding method and a camellia chekiangoleosa improved variety breeding system based on function superposition, and the method comprises the following steps: cloning excellent single plants through a high-stem grafting technology, and establishing a specific germplasm resource library; determining three types of phenotypic data of a floral leaf character set, an oil yield character set and an oil quality character set; the method comprises the following steps: presetting six types of application scenes such as an edible oil production raw material forest and a specific natural compound production raw material forest, and constructing a comprehensive evaluation model by adopting a hierarchical weight distribution method: distributing first-level weights for three types of character sets, and then distributing second-level weights for characters in subsets; standardizing the character of the floral leaf by adopting a binary comparison method, and standardizing the character of the oil yield and the character of the oil quality by adopting a centesimal system; and screening a target improved variety according to a comparison result of the comprehensive score of the to-be-evaluated variety and the average score of the existing improved variety. By means of the method, superposition breeding of ornamental, oil production and oil quality functions is achieved, and the adaptability of improved varieties and industrial scenes is improved.

A crop phenotype data fusion method and apparatus, an electronic device and a storage medium are provided. The method includes: inputting target data corresponding to the three-dimensional first to-be-fused crop phenotype data among the to-be-fused crop phenotype data into a weight adjustment model; acquiring a weight value corresponding to each first to-be-fused crop phenotype datum output by the weight adjustment model; and performing data fusion on the plurality of to-be-fused crop phenotype data based on the weight value corresponding to each first to-be-fused crop phenotype data and intrinsic and extrinsic parameter data of the crop phenotype sensors that collect the plurality of to-be-fused crop phenotype data. The target data includes environmental data when collecting crop phenotype data, relative position information between the crop phenotype sensors and the crop, and the target parameter values of the crop phenotype data. The target parameter values include signal-to-noise ratios and / or feature entropies.

The invention relates to the technical field of digital twinborn and agricultural information, and discloses a digital twinborn growth simulation and optimization method for safflower seedling breeding, and the method comprises the following steps: constructing individual digital twinborn bodies fusing genotypes, phenotypes and multi-dimensional environmental perception data; performing hybrid modeling in combination with the mechanism model and a depth time sequence neural network, and correcting growth prediction deviation in real time; and based on multi-objective optimization of biomass, medicinal component content and water efficiency, generating a precise cultivation regulation and control instruction. The system comprises a data acquisition unit, a twin construction unit, an environment fusion unit, a hybrid modeling unit, a visualization unit, an optimization decision unit and an instruction execution unit. According to the method, through closed-loop intelligent regulation and control, the yield, quality and resource utilization efficiency of safflower seedling breeding are remarkably improved.

The invention discloses a rape grain weight regulation gene NGAL3 based on whole genome screening and a breeding application thereof, based on the seed size and grain weight phenotypic value of a cabbage type rape germplasm resource, a candidate gene interval is positioned by using GWAS; the method comprises the following steps: selecting large-grain-weight and small-grain-weight extreme phenotypic materials, performing transcriptome sequencing in a critical period of seed development, and screening differential expression genes; and performing cross comparison on the GWAS candidate gene and the differential expression gene to obtain a key gene for jointly regulating and controlling the size and the grain weight of the seed, and performing functional verification on the key gene. The thousand seed weights of the created homozygous three mutant strains L1-sg1-1-4-5 and L2-sg1-4-8-16 are obviously increased by 46% and 29% compared with those of the wild type strains. The invention provides a new target for high-yield rape breeding, and non-transgenic high-grain-weight germplasm can be created through gene editing or beneficial allelic variation of NGAL3 is selected and enriched under the assistance of molecular markers.

The present disclosure provides a systems and methods for processing genetic variations and phenotypic data. The systems and methods may be used to generate one or more databases comprising genetic variations and associations with phenotypes. The system and methods may be used to determine a pathogenicity of a genetic variation. The systems and methods may comprise human interpretation using pre-determined criteria.

Embodiments of the disclosure include systems and non-transitory computer readable media for analyzing microscopy images for developing machine learning models for disease modeling. Microscopy images are captured from cells of one or more exposure response phenotypes (ERPs) and further used to train machine learning models. Thus, trained machine learning models can distinguish between microscopy images captured from healthy and diseased samples.

The invention relates to the technical field of grassland ecological monitoring, and discloses a grassland biomass estimation method based on multi-modal phenotype fusion and moisture content correction. The method comprises the following steps: setting a 0.5 m * 0.5 m quadrat in a grassland research area, synchronously acquiring a multi-spectral image of an unmanned aerial vehicle, multi-view structural data of a ZED 2i depth camera and ground actual measurement data, extracting structural features such as a multi-view vegetation projection volume index and 10 vegetation indexes after preprocessing, and constructing an XGBoost moisture content inversion model; and constructing a biomass initial model by using a pure structure, a pure spectrum and fusion characteristics, introducing a moisture content correction formula to correct deviation, and screening an optimal model through Monte Carlo cross validation. According to the method, multi-source data are effectively fused, moisture interference is stripped, the grassland biomass estimation precision is improved, and reliable technical support is provided for grassland ecological monitoring, carbon cycle evaluation and resource management.

The invention discloses a lutjanus erythropterus breeding auxiliary method and system based on multi-character collaborative selection, and the method comprises the steps: carrying out phenotype data collection and gene detection, and constructing a standardized phenotype matrix and a genotype matrix; performing genetic parameter estimation and breeding value prediction based on the standardized phenotype matrix and the genotype matrix to obtain breeding value prediction information; the method comprises the following steps: analyzing an association relationship between characters of lutjanus rubripes to be bred, constructing a character association network, and carrying out multi-character dynamic weight configuration to obtain a dynamic weight set; performing genome selection index calculation and parent priority analysis according to the breeding value prediction information and the dynamic weight set to generate a parent selection priority list; and generating a candidate parent pool through the parent selection priority list, performing hybridization combination analysis, performing genetic gain prediction on the generated hybridization combination, and generating a hybridization auxiliary scheme. The genetic gain accuracy and balance of breeding of the lutjanus erythropterus are improved, the limitation of traditional experience selection and matching is broken through, and the breeding efficiency is improved.

The invention belongs to the technical field of genetic engineering application and plant breeding, and particularly relates to application of a rice OsHGO gene to improvement of high-temperature tolerance of rice. The OsHGO gene in japonica rice Zhonghua 11 is knocked out through a CRISPR / Cas9 system, and a homozygous mutant plant with the OsHGO gene knocked out is obtained. The phenotypes of the wild type and mutant plants after high-temperature treatment are observed, and it is found that the wild type has more serious leaf wilt than the mutant plants. It is shown that after the OsHGO is knocked out, the influence of the high temperature on plant growth is relieved, and the OsHGO gene regulates and controls the tolerance of the rice to the high temperature. Through mutation of the gene, high-temperature-resistant rice can be cultivated.