1959 results about "Genetic stock" patented technology

The invention discloses a crop growth analysis system based on machine vision, and relates to the technical field of agricultural intelligent monitoring and analysis, the system comprises a multi-source acquisition module, a disturbance identification module, a growth behavior modeling module, an environmental adaptability correction module and a feedback prediction module; wherein the multi-source acquisition module can synchronously acquire visible light, near-infrared and depth images, and generates a joint index in combination with environmental data; the disturbance identification module identifies abnormal areas such as wind disturbance and shielding based on the residual image and the image structure network; the growth behavior modeling module is used for extracting internode change, leaf surface tension and bifurcation angle characteristics by using a three-dimensional structure time sequence alignment and hidden change rate coding network; the environment adaptability correction module constructs a crop-environment double-domain mapping relation; the feedback prediction module outputs personalized intervention suggestions in combination with deviation analysis and crop variety embedding vectors; the system has the advantages of high modeling precision, strong adaptability, fast feedback response and the like, and is suitable for intelligent planting management of various crops.

The invention discloses an intelligent temperature and humidity regulation and control fungus cultivation method for edible fungus sticks, and relates to the technical field of agricultural Internet of Things. The problems that in the prior art, multi-variety / multi-stage adaptability is poor, sudden environment response lags behind, and equipment cooperation efficiency is low are solved. Cross-variety control strategy migration is realized through a multi-strain dynamic migration matrix and a migration learning algorithm, and a three-dimensional microenvironment map is generated in combination with a multi-source sensor network and Kriging interpolation; identifying a strain growth stage by using a time sequence convolutional network, loading a corresponding parameter set, and dynamically generating an anti-interference instruction and a power distribution sequence based on a double-delay depth deterministic strategy gradient algorithm and model predictive control; scheduling a conflict-free instruction queue by adopting a heterogeneous equipment collaborative framework, and updating model parameters through federated learning and a Shapley value evaluation closed loop; according to the invention, the intelligence, self-adaptability and precision of edible mushroom growth environment regulation and control are greatly improved, and the robustness of the system to environment mutation is enhanced.

The invention discloses an intelligent breeding method for commercial crops based on big data analysis, and relates to the technical field of agricultural breeding, the method comprises the following specific steps: seed multi-modal data acquisition and processing: acquiring physical characteristic data of seeds, acquiring physiological indexes and genome information data through biochemical experiments and gene sequencing, and determining the seed multi-modal data according to the physiological indexes and the genome information data; carrying out pretreatment on the raw materials; according to the method, after multi-modal data are integrated and preprocessed, a seed vigor accurate evaluation model is constructed by using deep learning and data fusion technologies, the seed vigor level can be measured more accurately, and meanwhile, the electric signal change of the early growth stage of crops is monitored in real time by using high-precision plant electric signal acquisition equipment, so that the accuracy of the seed vigor evaluation is improved. And a correlation model of the electric signal characteristics and multiple traits of crops is established, and fusion analysis is performed on seed vigor evaluation data and plant electric signal data, so that the breeding efficiency is greatly improved, and powerful support is provided for cultivation of high-quality varieties.

An intelligent fertilization and water supply method and system. The method comprises the following steps: step a, comprehensive soil monitoring, involving: comprehensively monitoring various soil indexes by means of a plurality of sensors, so as to obtain real-time data of the soil indexes; b, consideration of crop-specific requirements, involving: for the varieties and growth stages of different crops, thoroughly studying the unique moisture and nutrient requirements of the crops, so as to ensure the rationality and accuracy of a fertilization amount; c, comprehensive consideration of environmental factors, involving: collecting data of surrounding environmental factors; d, utilization of an intelligent irrigation mode, involving: by using a cyclic irrigation mode, an intermittent irrigation mode, etc., in combination with the water requirement pattern of each crop and a change in soil moisture, realizing efficient water utilization; e, implementation of a dynamic fertilization plan, involving: on the basis of a change in a crop growth condition and in soil fertility, dynamically adjusting fertilization time, frequency and dosage, so as to ensure that the nutrient supply matches the requirements of each crop; and f, implementation of a precise fertilization technique, involving: precisely delivering fertilizer to an absorption part of each crop, so as to improve the efficiency of nutrient utilization.

The invention discloses a cowpea 5K SNP (Single Nucleotide Polymorphism) liquid chip and application thereof in variety identification, and belongs to the technical field of biology. The liquid chip provided by the invention comprises a set of nucleotide probes for detecting 5847 SNP sites of cowpea, and can be widely applied to different scenes of germplasm resource identification, genetic diversity evaluation, variety identification, genetic relationship identification, purification and rejuvenation of local varieties and the like of different cowpea varieties; an effective scientific basis is provided for cowpea variety identification, the variety identification and evaluation efficiency is improved, and the method has a remarkable application value.

The invention discloses a high-yield cold-resistant pennisetum germplasm screening method and application thereof, and the method is based on 10 yield traits, 4 cold-resistant indexes and 4 low-temperature photosynthetic ability indexes of pennisetum, constructs a multi-dimensional dynamic monitoring system across autumn, winter and spring, and performs high-yield cold-resistant comprehensive evaluation on the pennisetum germplasm, thereby screening out a high-yield cold-resistant breeding material. The invention provides a comprehensive, efficient and accurate high-yield cold-resistant Chinese pennisetum germplasm screening method, through a multi-dimensional dynamic monitoring system crossing autumn, winter and spring, yield traits, cold resistance indexes and low-temperature photosynthetic ability indexes are integrated, and the problems that a traditional method is single in evaluation dimension, disjointed with field reality and insufficient in dynamic adaptability are solved. The comprehensive evaluation system based on the principal component quantitative model not only fills the blank of the high-yield and cold-resistant evaluation model of the pennisetum alopecuroides, but also remarkably improves the breeding efficiency, provides powerful support for cultivating cold-resistant and yield-reduction-free breakthrough varieties, and has important application value and popularization prospect.

The invention relates to the technical field of molecular marker development and molecular marker assisted breeding, and particularly discloses a KASP molecular marker closely linked with a wheat drought resistance related gene TaRPL36-8, a primer and application, the nucleotide sequence of the KASP molecular marker is shown as SEQ ID NO.1, and T / C polymorphism exists at the 201bp position of the sequence. By detecting the KASP molecular marker, the drought-resistant variety of wheat is identified, and technical support is provided for wheat breeding.

The invention belongs to the technical field of agricultural information, and discloses a rape variety environmental adaptability evaluation system based on machine learning. The system is composed of a data acquisition standardization unit, a regional environment feature modeling unit, a variety phenotype and pedigree association unit, a feature screening and model training unit, a regional adaptability scoring and decision-making unit, a dynamic learning and evolution updating unit and an evaluation visualization and variety recommendation unit. By performing standardization processing on multi-source data, format and dimension differences are eliminated, and a high-quality data foundation is laid for subsequent analysis. Fusing environment and variety bilateral characteristics, and enabling the model to capture environment influence and variety heredity characteristics at the same time. Advanced methods such as ensemble learning and a time sequence neural network are adopted, and the complex relation is accurately mined. Compared with a traditional field test and the prior art, errors are greatly reduced, the adaptation degree of the variety in different areas is more accurately judged, a scientific basis is provided for planting recommendation, and the yield and quality of the oilseed rape are improved.

The invention relates to a same-variety grafting method for Tibetan pinus bungeana, and belongs to the technical field of forest vegetative propagation. In order to solve the technical problems that in the high-altitude environment, the grafting survival rate of the white bark pine is low, a connector is prone to being infected by microorganisms, and callus is formed slowly, efficient grafting is achieved through collaborative optimization of scion pretreatment and stock incision treatment. The method comprises the steps that a one-year-old branch with the diameter being 4-6 mm is selected and subjected to temperature and humidity control and composite antibacterial liquid dipping treatment; a sterile healing interface is formed in cooperation with rootstock incision slope cutting and four times of composite antibacterial liquid brushing; a one-year-old branch is cut, at least two or more bud points exist on the branch, two plump bud points are reserved, the branch is cut open from the position between the two plump bud points, and the scion is obtained. According to the method, the grafting survival rate and the interface stress resistance of the pinus bungeana in the alpine region are remarkably improved, the method is suitable for rapid breeding and hereditary characteristic retention of excellent germplasm of the pinus bungeana in Tibet plateau ecological restoration engineering, and more scion resources of the pinus bungeana can be utilized and protected.

The invention relates to the technical field of crop genetic breeding and plant molecular design breeding, in particular to a pakchoi whole genome liquid phase chip and application. The pakchoi breeding gene chip disclosed by the invention comprises a target capture probe which is designed by taking 1000 core SNP (Single Nucleotide Polymorphism) molecular markers positioned on 40KSNP sites on a pakchoi reference genome version V4.0 as templates. The pakchoi whole genome liquid phase chip provided by the invention comprises a 40K site targeted capture probe mixed solution and a hybridization capture reagent. The pakchoi 40KSNP targeted capture probe can rapidly and effectively track genetic materials of pakchoi, and is suitable for different application scenes such as accurate identification of pakchoi germplasm resources, genetic relationship analysis between materials, variety authenticity identification, QTL gene positioning and mining, molecular marker-assisted breeding, variety improvement and whole genome selective breeding application. Therefore, the method has good application prospect and important social value.

The invention discloses a silver carp 20K liquid phase chip and application thereof, the liquid phase chip comprises a probe combination of 20,909 SNP molecular markers covering a whole genome, the physical positions of the 20,909 SNP molecular markers are determined based on sequence alignment of the silver carp genome (GCA041475455.1), and the site information of the 20,909 SNP molecular markers is shown in the specification table 1. The invention provides a silver carp first type whole genome SNP liquid phase breeding chip, which effectively reduces the application cost of silver carp in genetic diversity analysis, QTL positioning, GWAS analysis and the like in scientific research, solves the problem that no applicable product exists in silver carp molecular auxiliary breeding and whole genome selective breeding, accelerates the progress of silver carp basic research and breeding, and has a wide application prospect. The method is of great significance in improving the utilization efficiency of silver carp germplasm resources, accelerating the breeding process of excellent characters and improving the economic value and environmental adaptability of bred varieties.

The invention discloses an acer elegans cross breeding method based on flowering phase difference regulation and control, and belongs to the technical field of garden plant breeding. The method comprises the following steps: selecting an acer elegans variety of which the natural early flowering phase difference is greater than or equal to 10 days and the genetic distance is greater than or equal to 0.5 as a cross parent, carrying out low-temperature refrigeration and shading blue light supplementing treatment on a female parent to delay the flowering phase, and carrying out prolonged illumination, red light supplementing and hormone and nutrient solution spraying on a male parent to advance the flowering phase; male parent pollen is collected through a vacuum negative pressure adsorption device and stored in a closed container, a sucrose solution is sprayed to female parent stigmas before pollination, and repeated pollination is conducted through a directional nozzle at 9-11 o'clock every day; carrying out stratification treatment and temperature-difference temperature-control germination on the hybrid seeds, and carrying out light-temperature regulation and control seedling culture after sowing; the molecular marker is used for verifying the hybridization authenticity and target traits, phenotype determination is carried out on three-year-old seedlings to complete breeding, the hybridization obstacle caused by asynchronous flowering phases of the caenorhabditis elegans varieties is solved through the flowering phase regulation and control technology, and the hybridization success rate is increased.

The invention belongs to the technical field of crop genetic breeding, and relates to a linked molecular marker of a peanut hypocotyl elongation related gene locus, an identification method and application of the linked molecular marker. The primer pair is C2-15-F / R, and the sequence of the primer pair is as shown in SEQ ID NO. 1 and SEQ ID NO. 2; by designing an InDel marker C2-15, the peanut hypocotyl length character can be quickly distinguished by using a primer to amplify a target band and using polyacrylamide gel electrophoresis detection. The identification method is more accurate and convenient, has good repeatability, can efficiently distinguish the phenotype and genotype of an individual, shortens the experiment process, has the advantages of simple and feasible operation steps and the like, and saves expenditure. The method disclosed by the invention has important application value in the breeding work aspects such as peanut hypocotyl elongation character related gene positioning, genotype typing and later cultivation of excellent peanut varieties.

The invention relates to the technical field of intelligent agricultural information processing, and provides a crop variety suitable planting area recommendation method and device based on deep reinforcement learning, and the method comprises the steps: obtaining crop variety features, environment data of candidate planting areas, and a pre-trained crop variety suitable planting area recommendation model; the recommendation model is trained through the following mode: training a pre-constructed intelligent agent based on variety planting data in different environments and environment data of planting sites and non-planting sites, and obtaining a trained deep reinforcement learning model. And adjusting the trained deep reinforcement learning model based on the variety promotion condition data to obtain a crop variety suitable planting area recommendation model. The recommendation model can accurately match the crop variety and the planting environment according to the input crop variety characteristics and the environment data of the candidate planting area, and accurate recommendation of the crop variety suitable planting area is realized.

The invention belongs to the technical field of aquatic animal molecular markers and aquatic genetic breeding, and particularly relates to an SNP (Single Nucleotide Polymorphism) molecular marker remarkably related to growth traits of grass carp and application of the SNP molecular marker. The SNP molecular marker is located at the position of 23608308bp of the eleventh chromosome (SLG1123608308) of the grass carp, and is Tgt; and A basic group mutation. Experiments show that the SNP molecular marker developed by the invention has significant influence on four growth traits (Plt; 0.05), and the allele A has more excellent growth traits. The invention discloses application of an SNP (Single Nucleotide Polymorphism) molecular marker, an amplification primer or a kit in breeding grass carp with excellent growth traits. The SNP molecular marker provided by the invention is not limited by the age, sex and the like of the grass carp, can be used for breeding grass carp varieties with excellent growth traits, and even can be accurately screened after being hatched, so that the breeding process of the grass carp varieties with excellent growth traits is greatly accelerated.

The invention belongs to the technical field of biology, and particularly relates to a pleurotus citrinopileatus strain and application, the pleurotus citrinopileatus strain is JAUP10L and preserved in the China Center for Type Culture Collection on April 19, 2024, the preservation number is CCTCC NO: M2024720, and the pleurotus citrinopileatus strain is classified and named as Pleurotus citrinopileatus. The Pleurotus citrinopileatus strain JAUP10L has a pileus polymerization state which is obviously different from a variety in production, has the potential of being developed into a new variety, and enriches the variety of Pleurotus citrinopileatus.

The invention discloses a molecular marker closely linked with wheat flag leaf width major QTL and application of the molecular marker in prediction of wheat flag leaf width, and belongs to the technical field of wheat molecular biotechnology and breeding. Wherein the molecular marker is 4BFLW-290, the nucleotide sequences of the molecular marker are as shown in SEQ ID NO: 3 and SEQ ID NO: 4, the specific primer pair of the molecular marker is 4BFLW-290-F / R, and the nucleotide sequences of the specific primer pair are as shown in SEQ ID NO: 1 and SEQ ID NO: 2. The molecular marker 4BFLW-290 provided by the invention fully embodies the flag leaf width major QTL of the wheat variety (line), can quickly and accurately predict whether the wheat variety (line) has the flag leaf width major QTL or not, and provides excellent gene resources and selection tools for wheat yield trait molecular breeding.

The invention relates to the technical field of plant breeding, in particular to a molecular marker related to oil content and protein content of soybean and application of the molecular marker. The molecular marker is constructed on the basis of SNP sites; based on a genome version number Wm82. A2. V1, the SNP site is located at the 8605814th site of the No.8 chromosome of the soybean, and the polymorphism is A / G. The application comprises the following steps: (1) predicting or detecting the oil content or protein content of soybeans; (2) identifying or cultivating soybean varieties with high oil content or protein content; (3) soybean molecular marker assisted breeding; (4) soybean variety improvement related to oil content or protein content; and (5) soybean germplasm resource improvement. The molecular marker related to the soybean oil content and the protein content is obtained through research and screening, and the molecular marker can be applied to cultivation of soybean varieties with high oil content and high protein content and has important value in the field of soybean breeding.

The invention relates to the technical field of agricultural informatization and intelligent decision making, and discloses a vegetable growth cycle pest control decision making system and method based on a knowledge graph. According to the method, an unstructured agricultural data stream including vegetable varieties, growth stages, environmental parameters, pest and disease records and geographic information is collected from an original database. A data tuple set with a time stamp is generated by performing scanning identification and content extraction on a data stream. Then, clustering is carried out according to the growth stages to which the tuples belong, and stage feature clusters sorted according to the growth cycle are formed; and performing multi-dimensional feature correlation analysis on the stage feature cluster, and establishing a dynamic coupling relationship among the environmental parameters, the disease and pest history and the geographic space features under the growth cycle dimension. And based on the dynamic coupling relationship, generating disease and pest control decision parameters of the vegetables in the specific planting area in each growth cycle stage. According to the invention, accurate matching between the control decision and the crop physiological time sequence and regional characteristics is realized.

The invention relates to a product of an SNP (Single Nucleotide Polymorphism) molecular marker related to sow litter size character detection and application of the product. The SNP molecular marker comprises Cgt, Cgt, Cgt, Cgt, Cgt, Cgt, Cgt, Cgt, Cgt, Cgt, Cgt, Cgt, Cgt, Cgt, Cgt, Cgt, Cgt, Cgt The nucleotide sequence of the gene is shown as SEQ ID No.1, and the nucleotide sequence of the gene is shown as SEQ ID No.1. The product at least comprises an upstream primer and a downstream primer, the nucleotide sequence of the upstream primer is as shown in SEQ ID No.2, and the nucleotide sequence of the downstream primer is as shown in SEQ ID No.3. The SNP molecular marker provided by the invention can be used for breeding, breeding and evaluating multi-variety sows with high reproductive performance.

The invention relates to a mulberry MaBEH1 / 2 gene for improving plant salt tolerance and application thereof, and belongs to the technical field of plant genetic engineering and biology. Wherein the coding nucleotide sequence of the mulberry MaBEH1 / 2 gene for regulating and controlling the salt tolerance of the woody plant is shown as a sequence 3; and the amino acid sequence of the MaBEH1 / 2 expression protein is shown as a sequence 4. According to the invention, MaBEH1 / 2 is transferred into 84K poplars to obtain MaBEH1 / 2-OE transgenic poplars; compared with a non-transgenic poplar, the salt stress tolerance of the MaBEH1 / 2-OE transgenic poplar can be remarkably enhanced. The invention provides key gene resources and technical support for genetic improvement of salt-tolerant forest varieties.

The invention discloses a fertilization method and system based on a regional land parcel image, and belongs to the technical field of agricultural fertilization, and the method specifically comprises the steps: collecting a target regional land parcel image through an unmanned aerial vehicle, and after radiation correction and geometric correction, extracting fertilization information containing soil color, vegetation coverage, vegetation index and landform characteristics, integrating to form a fertilization feature data set; according to the fertilization feature data set, dividing regions through a decision tree classification algorithm, identifying and visually displaying by means of a geographic information system; collecting crop variety, planting density and regional division result data, making a fertilization scheme of each region in combination with a fertilization model, and applying fertilization by using automatic equipment; images are collected again after fertilization, the crop growth response evaluation effect is monitored, and the fertilization scheme is adjusted as required, so that the agricultural production benefits are effectively improved, the fertilizer waste is reduced, and the scientificity and rationality of fertilization are optimized.

The application provides a wheat flour wet gluten content main effect site and SNP marker and application, and belongs to the wheat breeding technical field, and mainly provides SNP molecular markers Marker45889, Marker45896, Marker45348, Marker45403, Marker45397 and Marker45431, and the SNP site provided by the application has important significance for detecting and breeding wheat flour high FWG varieties, lines and breeding materials, and molecular markers can be developed according to the SNP site, so that the wheat quality breeding efficiency is accelerated.

The invention relates to the technical field of crop molecular genetic markers, and discloses an InDel molecular marker of avena nuda and application thereof.The molecular marker is a group of 314bp deletion variation and 2bp insertion variation in the 610439484-610440026 interval of the 5C chromosome position of a reference genome of an avena nuda variety OT3098, the nucleotide sequence of the deletion variation is shown as SEQ ID NO.1, the nucleotide sequence of the insertion variation is shown as SEQ ID NO.2, and the nucleotide sequence of the insertion variation is shown as SEQ ID NO.3. The nucleotide sequence of the insertion variation is 5 '-AA-3'. The molecular marker provided by the invention can realize stable detection in agarose gel electrophoresis by combining a specific primer pair (SEQ ID NO.2-3) with an optimized touchdown PCR (Polymerase Chain Reaction) program, has the advantage of being not influenced by a tissue part and a growth period, and provides an efficient and reliable technical means for oat germplasm identification, seed purity detection and molecular breeding.

The invention discloses a molecular marker related to thousand seed weight of wheat, a detection primer and application of the molecular marker and the detection primer, and belongs to the technical field of molecular marker-assisted breeding. The nucleotide sequence of the molecular marker TaDTX50-STS is as shown in SEQ ID NO. 1; basic groups from the 502 site to the 661 site of the sequence as shown in SEQ ID NO. 1 have insertion / deletion mutation. The InDel molecular marker related to the thousand seed weight character in a wheat genome is identified and named as TaDTX50-STS, and by detecting the polymorphism or genotype of the InDel molecular marker, the InDel molecular marker can be used for identifying or assisting in identifying the thousand seed weight character of wheat, assisting in breeding dominant varieties with high thousand seed weight of wheat and improving the wheat breeding efficiency.

The invention discloses a molecular marker, a primer pair, a kit and a method for identifying the size character of watermelon seeds and application, and belongs to the technical field of molecular marker-assisted breeding. The invention provides a molecular marker (as shown in SEQ ID NO.1-2), a primer pair (as shown in SEQ ID NO.3-4) and a kit containing the primer pair for identifying the size character of watermelon seeds in order to identify the size character of the watermelon seeds more quickly and more accurately in the watermelon seedling stage and realize watermelon germplasm resource screening and molecular assisted selection breeding. According to the identification method provided by the invention, the to-be-detected watermelon genome DNA is extracted in the seedling stage, so that molecular marker-assisted selection can be performed on the watermelon seed size character, the operation is simple and convenient, the breeding accuracy and efficiency are improved, the variety breeding period is shortened, and the variety breeding process is accelerated.

The present invention belongs to the field of biotechnology, and specifically relates to a GmSGT2 gene related to plant height and branch development, and a mutant thereof and the use thereof. A Glycine max mutant having fewer branches and decreased plant height is obtained by means of EMS mutagenesis, and a target gene thereof that is located by means of a map-based cloning technique is a GmSGT2 gene of Hedou 12. It is found through searching that the gene encodes soyasapogenol B glucuronide galactosyltransferase, and can galactosylate soyasapogenol B monoglucuronide, thereby affecting the plant height of Glycine max and reducing the branches of Glycine max. Therefore, the GmSGT2 mutant can be used for cultivating dwarf high-yield Glycine max varieties, and is of great significance in the breeding of ideal plant types of Glycine max and research on important agronomic traits of plants. The mutant has broad application prospects and great research value with regard to understanding the plant height and branch regulation mechanism of Glycine max and improving the process of Glycine max breeding; and can provide an excellent germplasm resource stock for regulating the close planting and high-yield breeding of Glycine max.

The invention discloses an unmanned aerial vehicle LiDAR-based high-canopy-density crop plant height double-end adaptive inversion method and system, and relates to the technical field of agricultural remote sensing. The method comprises the following steps: acquiring a crop canopy point cloud and extracting density, skewness and original ground elevation characteristics; constructing a near-surface pseudo ground layer thickness correction model, introducing a pseudo ground layer thickness parameter to carry out pressing correction of a physical layer on an original ground elevation, and reconstructing a real bare soil layer ground reference; constructing a canopy end density-form adaptive model, and dynamically calculating the optimal upper boundary percentile by using the point cloud density and the elevation distribution skewness; and calculating the final plant height based on a double-end correction result. According to the method, the problems of systematic overestimation caused by near-surface pseudo ground blocking and poor adaptability of a fixed threshold value to the canopy form in LiDAR ground detection under the high-canopy-density canopy are effectively solved, and high-precision and robust plant height automatic extraction under multiple varieties and different flight heights is realized under the condition that external terrain auxiliary data is not needed.

The invention discloses a beef cattle whole industry chain management method and device based on digital twinning and a medium, and the method comprises the steps: collecting physiological data in real time through an intelligent wearable device worn on a beef cattle individual, and collecting environment parameters of a farm, a transport vehicle and a processing line through an environment sensor; the physiological data and the environmental parameters are transmitted to a cloud end to construct a digital twinborn model of the beef cattle individuals, the beef cattle variety, genetic information and real-time physiological data are fused through the digital twinborn model, and the weight gain curve and health risk of the beef cattle individuals are dynamically predicted; dynamically optimizing the industry decision instruction of the beef cattle individual through a reinforcement learning algorithm based on the weight gain curve and the health risk; and adjusting an actual production flow based on the optimized industry decision instruction, recording whole industry chain data of the beef cattle individuals based on a block chain technology, and generating a corresponding traceability chain for querying a whole life cycle file of the beef cattle individuals.

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.