37 results about "Phenotypic trait" patented technology

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.

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.

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 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 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 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.

Provided area a method and system for assessing a crop germplasm resource based on priori knowledge. The method includes: collecting genomic data of a germplasm resource to be measured and performing variation detection thereon to obtain whole-genome genetic variation information of the germplasm resource to be measured; determining variation scores of phenotypic characters of the germplasm resource to be measured according to the whole-genome genetic variation information and a priori knowledge base of crop character variations; and determining a comprehensive variation score of the germplasm resource to be measured based on the variation scores of the phenotypic characters of the germplasm resource to be measured. The method of the present application can rapidly assess the scores of the phenotypic characters of the germplasm resource to be measured according to the genotype data thereof and calculate the comprehensive score in combination with the scores of the phenotypic characters.

This invention discloses a mobile phenotypic information acquisition platform and method based on the entire plant growth cycle, belonging to the field of intelligent plant phenotypic detection technology. It includes acquiring image sequences and depth point cloud data of multiple key growth stages of a target plant, and constructing a multi-dimensional phenotypic feature tensor representing the joint information of the plant's three-dimensional morphological structure and color texture through spatiotemporal registration and fusion. The tensor is input into a learnable phenotypic parsing network, and a dynamic phenotypic evolution map is generated by iteratively enhancing the plant organ feature response and suppressing the background feature response. Key phenotypic trait parameter sequences from budding to maturity are extracted, and the growth trend degree and developmental stability scores of each sequence are calculated, sorted, and integrated to form a hierarchical full-cycle phenotypic atlas. This method can achieve multi-dimensional phenotypic information fusion representation, weaken background interference, accurately depict the dynamic evolution process of phenotypic changes, and clearly present the correlation between phenotypic states at each growth stage.

The present application relates to the SNP molecular marker of the body length correlation under the fermented soybean meal feeding of Scophthalmus maximus and application thereof, and belongs to the technical field of molecular marker, the body length trait of the present application is analyzed by using whole genome correlation analysis on Scophthalmus maximus, the SNP molecular marker of the significant correlation under the fermented soybean meal feeding of Scophthalmus maximus and body length trait is obtained, including at least one of 6 SNP sites, can be applied to the molecular assisted breeding of Scophthalmus maximus, the screening can be carried out at the genome level through the breeding method disclosed in the present application, the breeding cycle can be greatly shortened, the dependence on phenotypic traits is reduced, the selection breeding efficiency is improved, and good application prospect is obtained.

The present disclosure provides yeasts, which can be recombinant yeast host cells, exhibiting prolonged persistence when submitted to a plurality of fermentation cycles. The yeasts exhibit at least one of the following phenotypic trait: a fast settling phenotype, a rugose phenotype, an improved invertase activity, triploidy, increased signaling in a RAS / cAMP / PKA pathway or combinations thereof.

The invention relates to the field of crop information, and discloses a multispectral-based method and system for identifying a rice drought-resistant gene, and the method comprises the following steps: S1, planting a rice genetic material under a drought stress condition and a normal condition, and obtaining multispectral image data; s2, processing the multispectral image data to obtain multispectral phenotypic characters related to the drought resistance of the rice; s3, based on the multispectral phenotypic characters and the genome data after quality control, performing whole genome association analysis through a mixed linear model, and positioning drought-resistant candidate genes; s4, performing eQTL analysis by combining expression quantity data of the drought-resistant candidate gene under drought stress conditions and normal conditions, and verifying a drought-resistant function. The method provided by the invention not only overcomes the defect of lossy measurement in a method for measuring physiological and biochemical indexes related to drought resistance during traditional rice drought-resistant gene identification, but also provides a new and feasible solution for extracting useful information from massive multispectral data.

The application discloses a kind of phenotypic data visualization analysis method and system of potato germplasm resources, it is related to agricultural information technology and data visualization technical field.The multidimensional dataset containing variety identification, multi-time point phenotypic trait value, environmental factor parameter and genetic distance is obtained;Variety is mapped to the first dimension axis of three-dimensional space based on genetic distance;Multi-phenotypic trait is weighted and projected to the second dimension axis;Time and environmental factor are complexly weighted and mapped to the third dimension axis;The control point of each variety in three-dimensional space is generated, and the phenotypic development trajectory curve is generated using spline interpolation;Three-dimensional space and trajectory curve are rendered to display device and provide interactive interface.Can simultaneously integrate four-dimensional information of genetic background, multi-phenotypic trait performance, time dynamics and environmental response, realize the dynamic visualization of phenotypic development process and the automatic identification of abnormal variety, significantly improve the analysis efficiency and cognitive intuitiveness of potato germplasm resources.

A method for breeding a new grape variety with red flesh and seedlessness based on molecular markers is provided. The molecular markers are identified significantly associated with grape red flesh and seedlessness traits through whole-genome analysis. The molecular markers may identify the phenotypic traits of grape red flesh and seedlessness at the initial stage of hybrid seedlings by using the electrophoretic banding patterns of amplified molecular marker gene fragments.

Analysis devices, storage media, and methods relating to prediction of phenotypic traits from proteomic data and correlation of the phenotypic traits to genomic data. The proteomic data includes information regarding protein abundance for a plurality of distinct proteins for a plurality of individuals. The genomic data includes information regarding presence of a plurality of distinct genetic variants for each individual. The methods include applying a predictive model to the proteomic data to predict at least one predicted phenotypic trait that is correlated to the proteomic data for at least one individual. The applying includes correlating the protein abundance of at least two proteins to the predicted phenotypic trait for the at least one individual. The methods also include identifying, from the genomic data for the at least one individual, at least one genetic variant that is correlated to the at least one predicted phenotypic trait.

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.

The invention relates to the technical field of plant phenotypic character intelligent detection, and particularly discloses a crop three-dimensional organ panoramic image acquisition device and a method thereof.The crop three-dimensional organ panoramic image acquisition device comprises an acquisition box body, a servo motor is fixedly connected to the upper surface of the acquisition box body, and a cantilever support is installed on the top surface of a cavity of the acquisition box body; a crop supporting table is fixed to the bottom surface of the cavity of the collecting box body, a limiting stand column is fixed to the upper end of the crop supporting table, and an inserting block is fixed to the upper surface of the limiting stand column. According to the crop three-dimensional organ panoramic image acquisition device and method, the acquisition efficiency and accuracy are improved, the servo motor drives the n-shaped cantilever support to rotate at a constant speed of 360 degrees, and the integrated design of the industrial line scanning camera, the light source and the background plate is matched; the full-surface RGB image automatic splicing and panoramic reconstruction of the three-dimensional organ can be completely acquired and synchronously and automatically completed, and accurate data support is provided for intelligent detection of three-dimensional organ characters.

Pea plants or part(s) thereof, as well as products such as commodity whole or split grains, pea protein concentrates (PPC), dairy analogues or protein-fortified beverages and meat analogues or texturized pea protein prepared therefrom, which have high protein content, low fat content and neutral taste are provided. The pea plans, part(s) and products are characterized by specific sets of genetic markers that correspond to identified quantitative trait loci (QTLs). Phenotypic and genotypic analysis of many pea varieties was performed to derive the markers for these phenotypic traits, and a breeding simulation was used to identify the most common and most stable markers. Following verification of trait stability over several generations, markers and marker cassettes were defined as being uniquely present in the developed pea lines. The resulting pea lines can be used to provide products with pea-based protein and low or no off flavors.

The invention provides a comprehensive evaluation method for drought resistance of cotton seeds in a germination period, and belongs to the technical field of agricultural science. The method comprises the following steps: 1) performing drought stress treatment on cotton seeds; 2) culturing the treated seeds in a germination box; the method comprises the following steps of (1) determining phenotypic character indexes of seeds, (2) determining phenotypic character indexes of the seeds, (3) calculating a drought tolerance comprehensive evaluation value of the cotton seeds by adopting a membership function method according to the phenotypic character indexes, and (5) carrying out grading evaluation on the cotton seeds according to the drought tolerance comprehensive evaluation value.By screening and integrating a plurality of excellent evaluation indexes, drought-resistant cotton germplasm resources can be efficiently and accurately identified.

The application provides a method and device for batch measuring leaf phenotype traits, electronic equipment and a storage medium. The method for batch measuring leaf phenotype traits comprises: acquiring images containing at least two to-be-measured leaves; the images comprise a background area and at least two leaf areas randomly distributed in the background area; the color of the background area is different from that of the leaf areas, and the placement direction of the leaves in the leaf areas is random; the images are preprocessed to make the color of the leaf areas white and the color of the background area black, thereby obtaining binary images; open operation processing and close operation processing are performed to obtain to-be-measured images; contour recognition is performed to obtain coordinate information of pixel points of the contours of the to-be-measured leaves and coordinate information of internal pixel points; and area parameters, perimeter parameters, length parameters and width parameters of the at least two to-be-measured leaves are calculated respectively. The length parameters and width parameters of leaves with random placement directions can be accurately measured in batches, and the efficiency is high.