63 results about "Phenotypic trait" patented technology

The invention discloses a rice drought resistance phenotype detection and genetic analysis method based on a phenotypic robot, which is characterized in that rice hyperspectral phenotypic character data is acquired based on the phenotypic robot, and the relative water content RWC of rice is predicted. Through high-frequency data acquisition, RWC (t) based on a time sequence is obtained, RWC (t) curve change characteristic indexes are calculated, the dynamic change process of a rice experiment material in the whole drought experiment period is quantified, the drought resistance index DTI of the rice experiment material is obtained, and the drought resistance of the rice variety is comprehensively evaluated. DTI as a user-defined phenotypic character can be used for whole genome association analysis (GWAS), and a key gene for controlling the drought resistance of rice is excavated. According to the invention, the problems of low efficiency and low flux of traditional rice phenotype detection are solved, phenotype-gene mining based on the mobile robot is realized, and a new way is expanded for improvement of rice genetic breeding.

The invention discloses a corn genetic performance prediction method fusing multiple environmental factors. The corn genetic performance prediction method comprises the following steps: acquiring a parent genotype data matrix, a hybrid phenotype data vector and a multi-environmental time sequence climate data tensor; a climate hysteresis effect matrix is constructed, and hysteresis influence degrees of different climate factors on corn growth and development are quantified; constructing an environment time-space relation matrix and an enhanced genome relation matrix considering non-equal contributions of sections; constructing a linear hybrid prediction model fusing the space-time environment information; estimating a variance component through a constraint maximum likelihood method, and solving model parameters based on a Henderson hybrid model equation; and predicting the phenotypic character of the to-be-predicted corn hybrid in the target environment by using the solving parameters. According to the method, the genotype data and the multi-environment time sequence climate data are fully utilized, the genotype effect, the environment space-time effect and the interaction effect of the genotype effect and the environment space-time effect are effectively integrated, and the accuracy of corn hybrid phenotype prediction is remarkably improved.

The invention relates to haplotypes of cobia fatness degree related SNP sites, a primer group and application of the haplotypes and the primer group, and belongs to the technical field of molecular markers, seven SNP sites related to cobia fatness degree are screened, primers for amplifying the SNP sites are provided, breeding of new varieties with fatness degree characters can be assisted by utilizing the SNP sites or the primers, and breeding of cobia fatness degree characters is facilitated. The method can greatly shorten the breeding period, reduce the dependence on phenotypic characters, improve the selective breeding efficiency, and have good application prospects.

The present application is directed to a method for identifying at least one candidate (Loc), namely a gene location and / or a sequence variant, indicative for at least one selected (phenotypic) trait of an organism, in particular of a plant, comprising the steps of:a. receiving a plurality of candidate lists (Can1, Can2, Can3) of candidates (Loc), the candidate lists being ordered;b. receiving a reference set (RefDB) with gene locations and / or sequence variants;c. matching at least a subset of candidates (Loc) from the candidate lists (Can1, Can2, Can3) with the reference list (RefDB) to determine an evaluation value (EV) for at least the subset;d. assigning each evaluation value (EV) to the respective candidate (Loc) in the respective candidate lists (Can1, Can2, Can3);e. calculating for each candidate list a performance value based on the evaluation value (EV), in particular by using the evaluation values (EV);f. selecting at least one candidate (Loc) as (preferred) candidate (Loc) from one of the candidate lists (Can1, Can2, Can3) using the performance values.

The invention discloses a fig germplasm resource diversity evaluation system and a fig germplasm resource diversity evaluation method, and relates to the field of comprehensive evaluation.The fig germplasm resource diversity evaluation method comprises the steps that after multi-climate zone fig germplasm resources are collected and samples are processed in a standardized mode, 32 phenotypic characters are obtained in combination with hyperspectral imaging, 3D morphological scanning and a physiological sensor; a UPLC-QTOF-MS technology is utilized to construct metabolite fingerprints of leaves and fruits, and an SNP / InDel molecular marker is developed through whole genome re-sequencing for genotyping. Integrating stress resistance physiological data in a stress environment, and calculating a comprehensive score by adopting an analytic hierarchy process. And screening core evaluation indexes through weighted principal component analysis, constructing a similarity matrix in combination with an improved Shannon-Wiener index and a Neii's genetic distance algorithm, and finally forming a germplasm clustering map and a genetic diversity thermodynamic diagram. The method has the advantages that germplasm representativeness is guaranteed through multi-climate-zone sampling, multi-dimensional data are integrated, core indexes are accurately analyzed and screened, a visual atlas is finally generated, and scientific support is provided for germplasm research and breeding.

The invention relates to an SNP (Single Nucleotide Polymorphism) molecular marker associated with the fatness of turbots fed with fermented soybean meal and application of the SNP molecular marker, and belongs to the technical field of molecular markers. The SNP molecular marker obviously associated with the fatness character is obtained by analyzing the fatness character of the turbots through genome-wide association analysis and comprises at least one of six SNP loci; the scophthalmus maximus molecular marker can be applied to scophthalmus maximus molecular assisted breeding, screening is conducted on the genome level through the breeding method, the breeding period can be greatly shortened, dependence on phenotypic characters is reduced, the selective breeding efficiency is improved, and the scophthalmus maximus molecular marker has good application prospects.

The invention discloses a medicinal plant phenotype prediction method based on a gene action mode, which comprises the following steps of: firstly, constructing a medicinal plant phenotype prediction model based on the gene action mode according to an influence mode of a gene on phenotype, and introducing Gaussian noise and sparse regularization loss to extract key gene characteristics aiming at the influence of the key gene on the phenotype; meanwhile, a hidden layer is used for carrying out data dimension reduction to ensure the model efficiency, gene information of different scales is used for enriching gene feature representation, the inhibition effect between genes is extracted through self-attention, the nonlinear synergistic effect of the genes and the genes is extracted through polynomial features, and finally accurate prediction of phenotypic characters is achieved. According to the method disclosed by the invention, phenotype prediction is carried out from interaction between key genes according to an action mode of a genome on phenotypes, and compared with an existing phenotype prediction technology, the method disclosed by the invention has a better effect in phenotype prediction of medicinal plants, realizes rapid and accurate prediction of crop phenotypes, and accelerates breeding and seed production processes.

The application relates to a haplotype of a SNP site related to the fullness degree of Larimichthys crocea, a primer set and application thereof, and belongs to the technical field of molecular markers. Seven SNP sites related to the fullness degree of Larimichthys crocea are screened, and primers for amplifying the SNP sites are provided. The SNP sites or the primers can assist the breeding of new varieties with the fullness degree, can greatly shorten the breeding period, reduce the dependence on phenotypic traits, improve the selection and breeding efficiency, and have a good application prospect.

A phenotyping device, method and system for measuring phenotypic traits of one or more plants in a target canopy, wherein the comprises a canopy spreader for spreading the target canopy, a camera unit, a means for controlling the angle and the distance of the camera unit in relation to the canopy spreader, an electronic control unit for controlling the camera unit. The phenotyping device, method and system enables recording the raw data from the target canopy during a data collection session comprising information of the plants that are not visible to a camera unit without spreading the canopy.

The invention relates to an SNP molecular marker related to the weight of scophthalmus maximus fed with fermented soybean meal and application of the SNP molecular marker, and belongs to the technical field of molecular markers, the weight character of the scophthalmus maximus is analyzed through genome-wide association analysis, the SNP molecular marker remarkably related to the weight character of the scophthalmus maximus fed with the fermented soybean meal is obtained, and the SNP molecular marker comprises at least one of six SNP sites, the scophthalmus maximus molecular marker can be applied to scophthalmus maximus molecular assisted breeding, screening is conducted on the genome level through the breeding method, the breeding period can be greatly shortened, dependence on phenotypic characters is reduced, the selective breeding efficiency is improved, and the scophthalmus maximus molecular marker has good application prospects.

This invention discloses a method for wheat grain quality detection and functional gene analysis based on hyperspectral imaging technology, belonging to the field of agricultural testing technology. The method includes: extracting hyperspectral indices; measuring wheat grain quality indicators as manual measurements; assigning weight coefficients to each quality indicator to digitize the wheat quality phenotype; extracting characteristic wavelengths to establish predictive models for each indicator and wheat quality values; performing GWAS on hyperspectral indices and chemical indicators as phenotypic traits with genotypes to screen SNP loci, conduct co-location analysis, obtain candidate genes, and perform functional verification. This invention, through hyperspectral technology combined with chemometric modeling, is suitable for real-time monitoring during wheat quality breeding and processing; by combining spectral phenotype with GWAS gene mining, it overcomes the limitations of traditional quality detection that only serves phenotypic screening, forming a closed loop of "non-destructive detection - gene localization," providing targeted genes for wheat quality improvement.

The invention relates to a wheat low-phosphorus response transcription factor TaERF112 and application thereof, and belongs to the technical field of plant bioengineering. The low-phosphorus response transcription factor TaERF112 gene is cloned from wheat, the CDS region sequence of the gene is 882bp, 294 amino acids are encoded, the molecular weight is 31 and 572.92 Da, and the gene is hydrophilic protein. By analyzing the TaERF112 gene structure, protein physicochemical properties, subcellular localization and species evolution characteristics, the characteristics and function prediction of the gene are known. Furthermore, a wheat taerf112 mutant is created by using a CRISPR / Cas9 technology, phenotypic characters, biomass and phosphorus utilization characteristics of a transformed strain under different phosphorus conditions are evaluated, and the important effect of the wheat taerf112 mutant in regulation and control of a wheat root system and phosphorus homeostasis is preliminarily revealed. Theoretical basis and gene resources are provided for efficient genetic improvement of wheat phosphorus.

This application provides a method for screening hybrid parent combinations based on genomic functional site information, relating to the field of hybridization breeding technology, including the following steps: obtaining a functional site library and recording the dominant genotypes of each functional site and their contribution to phenotypic traits; obtaining the actual genotypes of the first and second parents at each functional site; for each functional site, simulating the possible candidate genotypes and their probabilities of occurrence in offspring according to Mendelian laws based on the parent genotypes; for each candidate genotype, adding a positive contribution if it is the same as the dominant genotype of a certain trait, and deducting a negative contribution if it is different, and accumulating them to obtain a comprehensive score; determining the contribution value of each site based on the comprehensive score and occurrence probability of each candidate genotype; accumulating the contribution values ​​of all sites to obtain the matching score of the parent combination, which is used to characterize its potential to produce superior offspring; finally, screening recommended combinations based on the matching scores, realizing the assessment of the breeding potential of parent combinations without actual hybridization.

The invention discloses a fish body size measuring method based on computer vision, and belongs to the technical field of computer vision. The method comprises the following steps: establishing and training an image segmentation model; obtaining a fish body image by using a binocular camera and calibrating the fish body image; performing variety identification and key region segmentation on the image by using the trained model to generate a three-dimensional point cloud; denoising and coordinate transformation are carried out on the point cloud, and a fish body feature point set is extracted; and calculating phenotypic characters such as body length, body width, head length and body length. The device has the advantages of being non-contact, efficient, high in precision, high in adaptability and the like, is suitable for the fields of aquaculture, fishery resource investigation and the like, and can achieve rapid and automatic detection of the size and weight of the fish.

The invention belongs to the technical field of molecular biology, and particularly relates to a universal SNP molecular marker for predicting multiple phenotypic characters of corn, and a screening method and a prediction system thereof. According to the method, through vectorization conversion of genotype data, mutual information screening, LD filtering, LASSO and random forest fusion screening three-time dimensionality reduction is carried out on the converted genotype data, invalid and redundant markers are removed layer by layer, a universal marker suitable for predicting multiple phenotypic characters of corn is developed, and compared with feature screening of traditional whole genome selection, the method has the advantages that the method is simple and convenient to operate, and the efficiency is high. While the cost is reduced, the breadth of screening traits is improved. According to the method, an integrated model of the self-attention neural network, the LASSO and the random forest is constructed, the advantages of the three models are fused through advantage complementation and weight optimization of different models, the limitation of a single model is made up, accurate and efficient prediction of multiple corn phenotypic characters is finally achieved, and the breeding period is shortened.

The invention discloses a wheat flag picking and heading uniformity monitoring method and system based on deep learning, and further discloses a wheat growth period consistency monitoring method and system based on deep learning. According to the wheat flag picking and heading uniformity monitoring method and system based on deep learning, high-resolution time sequence image analysis and a deep learning algorithm are fused, the wheat flag picking and heading uniformity monitoring method and system based on deep learning are established, and the wheat flag picking and heading uniformity can be dynamically monitored; the invention also provides a wheat growth period consistency monitoring method and system based on deep learning, which can dynamically monitor the flag picking-heading consistency phenotypic character of wheat, accurately quantify the individual development heterogeneity of the population, reveal the association between the population and the yield, and in a word, improve the yield of wheat. The technical scheme provided by the invention provides a theoretical reference and a practical basis for improving the yield stability of wheat populations.

The present application relates to the field of breeding trait analysis, and provides a breeding trait analysis method, device, equipment, medium and computer program product.The method comprises the following steps: constructing a target data set based on genotype data and phenotype trait data of a breeding sample; training a trait prediction model through the target data set; analyzing the effect of a genetic variation site on a phenotype trait through the trait prediction model to obtain an effect matrix; the genetic variation site is determined based on the genotype data; and performing aggregation processing on the effect matrix to obtain a key variation site corresponding to a target trait; the target trait is selected from the phenotype trait data according to requirements.The present application mines the effect of a genetic site on a trait through a trait prediction model, fully utilizes genotype data and phenotype data, and improves the accuracy of breeding trait analysis.

The invention discloses a wheat grain quality detection and functional gene analysis method based on a hyperspectral imaging technology, and belongs to the technical field of agricultural detection. The method comprises the following steps: extracting a hyperspectral index; determining a wheat grain quality index as an artificial measurement value; a weight coefficient is given to each quality index, and the wheat quality phenotype is digitalized; extracting a characteristic wavelength, and establishing a prediction model of each index and a wheat quality value; gWAS, SNP site screening and co-localization analysis are performed on the hyper-spectral index and the chemical index as phenotypic characters and genotypes respectively, and candidate genes are obtained and subjected to functional verification. The method combines a hyperspectral technology with chemometrics modeling, and is suitable for real-time monitoring in wheat quality breeding and processing processes; the spectrum phenotype is combined with GWAS gene mining, the limitation that traditional quality detection only serves phenotype screening is broken through, a'nondestructive testing-gene positioning 'closed loop is formed, and a target gene is provided for wheat quality improvement.

The invention discloses a mesosulfuron-resistant SNP site of a wheat TaASADH-A1 gene, a KASP marker and application, and relates to the technical field of molecular marker-assisted breeding and application of the SNP site, the SNP site takes a common wheat Chinese spring genome Chine Spring RefSeq v1.1 as a reference genome, the SNP is the SNP site of a TraesCS5A02G398300 gene promoter region on a wheat 5A chromosome, and the KASP marker is the KASP marker of the mesosulfuron-resistant SNP site of the wheat TaASADH-A1 gene, the KASP marker is the KASP marker of the mesosulfuron-resistant SNP site of the wheat TaASADH-A1 gene, and the KASP marker is the KASP marker of the wheat TaASADH-A1 gene. Corresponding to the 101st basic group from the 5'tail end of the sequence shown in SEQ ID NO: 1, when the site is GG homozygosis, the corresponding genotype is A; when the site is CC homozygous, the corresponding genotype is B; according to the application, mesosulfuron-resistant wheat is screened or screened in an auxiliary mode, and the mesosulfuron-resistant capacity of wheat is that wheat with the homozygous genotype A is higher than wheat with the homozygous genotype A or wheat with the homozygous genotype B or wheat with the homozygous genotype B in a candidate mode. The developed KASP marker is related to the wheat herbicide-resistant mesosulfuron-methyl, and can be used for screening and identifying the phenotypic character of the wheat herbicide-resistant mesosulfuron-methyl.

The application relates to a haplotype of a SNP site related to body weight of Larimichthys crocea, a primer set and application thereof, and belongs to the technical field of molecular markers. Seven SNP sites related to the body weight of the Larimichthys crocea are screened, and primers for amplifying the SNP sites are provided. The SNP sites or the primers can assist the breeding of new varieties with the body weight, can greatly shorten a breeding period, reduce the dependence on phenotypic traits, improve the selection and breeding efficiency, and have a good application prospect.

The invention discloses a mytilus coruscus byssus adhesion protein mutant, application thereof and a method for identifying phenotypic characters of mytilus coruscus byssus, and relates to the technical field of biology. The amino acid sequence of the mytilus coruscus byssus adhesion protein mutant is as shown in SEQ ID NO. 4. In-depth study shows that non-synonymous mutation of a mytilus coruscus Mfp3-6 gene coding region can directly influence functional characteristics of protein, so that a clear causal relationship is established between a genotype and a mytilus coruscus byssus adhesion performance phenotype. The invention further provides a mytilus coruscus byssus adhesion protein mutant. The mytilus coruscus byssus adhesion protein mutant has an excellent adhesion strength characteristic, so that the mytilus coruscus byssus adhesion protein mutant has a wide application prospect in the field of functional adhesion materials. The protein mutant can be widely applied to development of materials such as medical glue, dressing and gel, provides important technical support for research and development of bionic adhesion technology and novel biological materials, and has good industrialization potential and social value.

The invention discloses a salt-tolerant flooding-resistant mangrove plant variety breeding method, belongs to the technical field of mangrove plant breeding, and systematically carries out salt-tolerant flooding-resistant excellent mangrove variety breeding work through three links of germplasm resource collection, character evaluation and variety breeding. The method comprises the following steps: firstly, carrying out resource census on mangrove plants in a natural distribution area, comprehensively evaluating the growth and resistance performance of the mangrove plants, and collecting at least 50-60 parts of excellent germplasm for local planting and storage; secondly, carrying out salt-tolerant and flooding-tolerant experiments on the collected germplasm, analyzing phenotypic characters and physiological changes of the germplasm, deeply excavating stress-resistant key genes by applying multiple omics technologies such as transcriptome and metabolome, and verifying the expression quantity of the key genes in combination with a qPCR technology; finally, gene expression data and phenotypic resistance analysis results are integrated, salt-tolerant and flood-tolerant mangrove plant varieties rich in genetic background diversity are screened out, a complete technical route of resource collection, omics analysis and directional breeding is formed, and high-quality germplasm resources are provided for mangrove forest ecological restoration.

The invention provides a four-level precise breed conservation method and platform for local livestock and poultry, and the method comprises the following steps: collecting newly born or newly introduced samples in a breed conservation population of a target local livestock and poultry variety in each generation, constructing a whole genome genotype database, and constructing a whole genome genotype database of the samples on the premise of maintaining the genetic diversity of the population; genomic breeding values on the concerned phenotypic characters are sequenced, a predetermined proportion of individuals ranked at the last are eliminated or are not reserved for seed use any more, and a four-level seed conservation system and an integrated management platform for dynamically monitoring all data in real time are established. According to the method and the platform, a four-stage breed conservation system and an integrated management platform are constructed, so that real protection, accurate real-time dynamic monitoring, characteristic maintenance and efficient utilization of local livestock and poultry genetic resources are realized.

The invention belongs to the technical field of oat germplasm resource genetic diversity analysis, and discloses an oat germplasm resource genetic diversity analysis and feeding value evaluation method which comprises the following steps: S1, planting oats; s2, recording growth periods, and dividing maturity; s3, recording organ characteristics and hay components, and calculating a feeding value; s4, recording quality character indexes; s5, measuring spike characteristics and seed weight; s6, performing genetic diversity index calculation, correlation, clustering, principal component and multiple correspondence analysis, and analyzing and evaluating genetic diversity and feeding value; according to the method, the genetic diversity index of oat phenotypic characters in each planting area is calculated, correlation analysis, principal component analysis, clustering analysis, structural equation model construction and multiple correspondence analysis among quantitative characters are carried out, the genetic diversity of each resource is explored, the resource suitable for the climate of the planting land is screened out, and the method has the advantages of being high in practicability and the like. And a scientific basis is provided for improvement and innovative breeding of oat germplasm resources.

According to the field muskmelon EMS mutation breeding method, field muskmelon seeds are used as test materials, three EMS concentration gradients and two mutagenesis time are set for treatment so as to research the influence of different mutagenesis conditions on the germination rate, the emergence rate and the field agronomic traits of the field muskmelon seeds, the total germination rate of a control group is about 70%, and the total germination rate of the control group is about 70%. The germination rate of the field muskmelon seeds in the treatment group is reduced along with the increase of the EMS concentration, and the germination rate of the field muskmelon seeds treated at the same concentration is reduced along with the increase of time. Wherein the difference of 12 h and 24 h experimental groups with the concentration of 0.8% is most obvious, the germination rate of 12 h treatment is up to 43%, and the germination rate is reduced to 20% on the contrary after the time is doubled; the fatality rate of the field muskmelon treated by 1.5% EMS for 24 hours is high, and the field muskmelon plants subjected to mutagenesis show rich variation in phenotypic characters such as plant types, peel lines and fruits; according to various indexes, 0.8% EMS is screened to soak seeds for 12 h, and the condition is a relatively suitable induction condition for field muskmelon seed mutation.

The application discloses a crop germplasm resource evaluation method and system based on prior knowledge, and relates to the technical field of crop germplasm resource evaluation. The method comprises the following steps: collecting the genomic data of the to-be-tested germplasm resource and performing variation detection to obtain whole-genome genetic variation information of the to-be-tested germplasm resource; determining the variation scores of various phenotypic traits of the to-be-tested germplasm resource according to the whole-genome genetic variation information and a crop trait variation prior knowledge base, so as to determine the comprehensive variation score of the to-be-tested germplasm resource based on the variation scores of various phenotypic traits of the to-be-tested germplasm resource. The method can quickly evaluate the phenotypic trait scores of the to-be-tested germplasm resource according to the genotype data of the to-be-tested germplasm resource, and calculate the comprehensive score in combination with the various phenotypic trait scores, is applied to the field of crop germplasm resource evaluation, can greatly improve the evaluation efficiency of the phenotypic traits of the germplasm resource, save the evaluation cost, and thus better realize the efficient exploration and utilization of the germplasm resource.

The application discloses a multi-head attention mechanism-based super network representation learning method applied to breeding, relates to the technical field of crop breeding, and comprises the following steps: constructing a crop heterogeneous super network, and constructing an initial embedding matrix corresponding to all nodes; obtaining a normalized node representation vector corresponding to each tuple and a similarity score of each tuple; calculating the pairwise similarity between each two nodes; constructing a joint loss function, and optimizing the parameters of a target model; generating a final representation vector of a node in the crop heterogeneous super network by using the target model after parameter optimization; and predicting a crop variety according to the final representation vector. The application avoids complex graph conversion and explicit high-order combination calculation, improves the calculation efficiency and scalability, can more comprehensively and accurately encode semantic and structural information of phenotypic traits, and thus provides reliable and high-quality data basis for crop variety prediction based on the final representation vector.

Chickpea plants with high protein content. low fat and / or modified protein composition are provided. as well as progeny or parts thereof. Phenotypic and genotypic analysis of many chickpea varieties were performed to derive markers for phenotypic traits that contribute to high protein content. low fat and / or modified protein composition. and a breeding simulation was used to identify the most common and most stable markers. Examples of such phenotypic traits include the protein content. the fat content as measured by near infrared spectroscopy. and protein composition and seed color traits. Following verification of trait stability over several generations. markers and marker cassettes comprising at least three specific QTLs were defined as being uniquely present in the developed chickpea lines. The resulting chickpea lines can be used to improve nutritional and organoleptic properties of various chickpea products and chickpea-based food ingredients. e.g., in plant-based protein products.