CN111312335B - Soybean parent selection method and device, storage medium and electronic equipment - Google Patents
Soybean parent selection method and device, storage medium and electronic equipment Download PDFInfo
- Publication number
- CN111312335B CN111312335B CN202010114122.9A CN202010114122A CN111312335B CN 111312335 B CN111312335 B CN 111312335B CN 202010114122 A CN202010114122 A CN 202010114122A CN 111312335 B CN111312335 B CN 111312335B
- Authority
- CN
- China
- Prior art keywords
- soybean
- tested
- evaluation
- combinations
- combination
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Classifications
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
- G16B25/00—ICT specially adapted for hybridisation; ICT specially adapted for gene or protein expression
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
- G16B40/00—ICT specially adapted for biostatistics; ICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding
Landscapes
- Physics & Mathematics (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Medical Informatics (AREA)
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Biophysics (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Bioinformatics & Computational Biology (AREA)
- Biotechnology (AREA)
- Evolutionary Biology (AREA)
- General Health & Medical Sciences (AREA)
- Spectroscopy & Molecular Physics (AREA)
- Public Health (AREA)
- Molecular Biology (AREA)
- Measuring Or Testing Involving Enzymes Or Micro-Organisms (AREA)
- Bioethics (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Data Mining & Analysis (AREA)
- Databases & Information Systems (AREA)
- Epidemiology (AREA)
- Evolutionary Computation (AREA)
- Genetics & Genomics (AREA)
- Software Systems (AREA)
- Artificial Intelligence (AREA)
Abstract
The application provides a soybean parent selection method, a device, a storage medium and electronic equipment, and relates to the technical field of plant hybridization, wherein the method comprises the following steps: obtaining all combinations of soybean germplasm resources to be tested and each soybean germplasm resource to be tested in each combination; determining an evaluation grade of each combination based on the soybean target trait value under each combination obtained from the intra-group hybridization results of each combination; determining an evaluation result of each soybean germplasm resource to be tested based on the evaluation grade of each combination to which each soybean germplasm resource to be tested belongs; and determining the soybean parent based on the evaluation result. According to the soybean parent selection method, the soybean target property values of the combinations to which the same soybean germplasm resources to be detected belong are comprehensively used as the basis for selecting soybean parents, so that high-quality soybean parents can be screened out from a plurality of soybean germplasm resources, automatic screening of the soybean parents is realized, and the efficiency of screening the soybean parents can be improved so as to improve the soybean target properties.
Description
Technical Field
The application relates to the technical field of plant hybridization, in particular to a soybean parent selection method, a soybean parent selection device, a soybean parent selection storage medium and electronic equipment.
Background
The utilization of heterosis is a technological innovation with great significance in world agriculture technology and production practice. Heterosis is widely applied to crops such as Gramineae, solanaceae, cruciferae and the like, and huge economic and social benefits are generated.
The domestic soybean heterosis genetic research has a larger gap compared with crops such as corn, rice and the like. Although some researches on soybean heterosis are reported, the research is not deep and systematic, and the guidance effect on hybrid seed selection practice is limited. The determination of the hybridization combination preparation mode in the prior soybean heterosis utilization is mainly carried out by: 1. according to breeding practices, excellent combinations are screened through hybridization of a large number of parent materials through actual performances of complexation force and heterosis; 2. based on breeder experience, by analyzing the geographical origin and the kindred relationship of the parent material, the criteria for selecting the parent are established, but the actual hybridization combination F 1 The expression of the substitution target character value still needs to be obtained through experiments.
The current soybean heterosis utilization and hybridization assembly mode mainly screens parents through target character values of the parents and other corresponding characters, geographical sources, affine relations and the like according to the experience of breeders. Selecting parent and female parent for hybridization combination, and hybridizing F 1 The actual field performance of the generation is used for determining the hybrid vigor of the combination, but a large amount of tests and working cost are required to be input, and the problem that the parent selection efficiency is low so as to influence the selection and the breeding of the target according to the target property value of the soybean exists.
Disclosure of Invention
The embodiment of the application provides a soybean parent selection method, a device, a storage medium and electronic equipment, so as to solve the problem that the efficiency is low when parent selection is carried out in the prior art, and thus the target property of soybean breeding is influenced.
Embodiments of the present application provide a soybean parent selection method comprising:
obtaining all combinations of soybean germplasm resources to be tested and each soybean germplasm resource to be tested in each combination; determining an evaluation grade of each of said combinations based on the soybean target trait values under each of said combinations obtained from the intra-group hybridization results of each of said combinations; determining an evaluation result of each soybean germplasm resource to be tested based on the evaluation grade of each combination to which each soybean germplasm resource to be tested belongs; and determining a soybean parent based on the evaluation result.
In the implementation process, the soybean target property values of the combinations to which the same soybean germplasm resources to be tested belong are comprehensively used as the basis for selecting soybean parents, so that high-quality soybean parents can be screened out of a plurality of soybean germplasm resources, automatic screening of the soybean parents is realized, and the efficiency of screening the soybean parents can be improved, so that the goal of selecting the soybean target property is achieved.
Optionally, the determining the evaluation grade of each combination based on the soybean target trait value under each combination obtained by the intra-group hybridization result of each combination comprises:
classifying the combination into a plurality of maturity stage classes according to fertility stage; sequencing the soybean target property values obtained by hybridization of the combinations in the same maturity stage and the same yield measurement point from high to low; and respectively determining the evaluation grades of all combinations in each maturity stage class according to the sequencing result.
In the implementation process, the soybean target property values obtained by hybridization of the combinations in the same maturity stage and the same yield measurement point are sequenced from high to low, so that the target property values of the soybeans after hybridization of the combinations can be distinguished, and the accuracy of obtaining the combined evaluation grade is improved.
Optionally, the determining the evaluation result of each soybean germplasm resource to be tested based on the evaluation grade of each combination to which each soybean germplasm resource to be tested belongs includes:
counting the evaluation grades of all the combinations in which each soybean germplasm resource to be tested participates in each maturity class respectively to obtain the number of the evaluation grades of each soybean germplasm resource to be tested in each maturity class; and sequencing all the soybean germplasm resources to be tested according to the number of the highest evaluation grades of each soybean germplasm resource from high to low to obtain an evaluation result of each maturity stage.
In the implementation process, the evaluation grade of each combination of the soybean germplasm resources to be tested is counted, so that the evaluation accuracy of each soybean germplasm resource to be tested can be improved.
Optionally, the selecting a soybean parent based on the evaluation result comprises:
and selecting the soybean germplasm resources to be tested positioned at the high position of the evaluation result as soybean parents of each maturity stage class based on the target property value requirement according to the evaluation result of each maturity stage class.
In the implementation process, according to the evaluation result, the soybean germplasm resources which are arranged at a high position are selected as soybean parents, so that the soybean germplasm resources with excellent performance can be screened out, and the reliability of screening the soybean parents is improved.
Optionally, the maturity stage class includes an early maturity stage, and counting the evaluation grades of all the combinations involved in each soybean germplasm resource to be tested in each maturity stage class to obtain the number of the evaluation grades of each soybean germplasm resource to be tested in each maturity stage class, including:
backcrossing the combination in the early maturing class with a maintainer line to obtain a first filial generation, and dividing parents in the combination into a restorer line and a sterile line according to a pollen fertility identification result of the first filial generation obtained by backcrossing the combination with the maintainer line, wherein female parents in the combination are sterile lines, and male parents in the combination are restorer lines; and counting the evaluation grades in all the combinations in which each soybean germplasm resource to be tested participates in the restorer line and the sterile line in the early maturing class, and obtaining the number of each grade of each soybean germplasm resource to be tested in the restorer line in the early maturing class and the number of each grade of each soybean germplasm resource to be tested in the sterile line in the early maturing class.
In the implementation process, the combination is divided into a restorer line and a sterile line, so that independent quality analysis can be carried out on the sterile line and the restorer line respectively, and the reliability of parent soybean germplasm resource selection is improved.
Embodiments of the present application provide a soybean parent selection apparatus, the apparatus comprising:
the acquisition module is used for acquiring all combinations of soybean germplasm resources to be tested and each soybean germplasm resource to be tested in each combination of soybean germplasm resources to be tested; an evaluation module for determining an evaluation grade of each of the combinations based on the soybean target trait values under each of the combinations obtained from the intra-group hybridization results of each of the combinations; the generation module is used for determining an evaluation result of each soybean germplasm resource to be tested according to the evaluation grade of each combination to which each soybean germplasm resource to be tested belongs; and a selection module for determining a soybean parent based on the evaluation result.
In the implementation process, the soybean target property values of the combinations to which the same soybean germplasm resources to be tested belong are comprehensively used as the basis for selecting soybean parents, so that high-quality soybean parents can be screened out of a plurality of soybean germplasm resources, automatic screening of the soybean parents is realized, and the efficiency of screening the soybean parents can be improved, so that the target property breeding goal is achieved.
Optionally, the evaluation module is specifically configured to: classifying the combination into a plurality of maturity stage classes according to fertility stage; sequencing the soybean target property values obtained by hybridization of the combinations in the same maturity stage and the same yield measurement point from high to low; and respectively determining the evaluation grades of all combinations in each maturity stage class according to the sequencing result.
In the implementation process, the soybean target property values obtained by hybridization of the combinations in the same maturity stage and the same yield measurement point are sequenced from high to low, so that the target property values of the soybeans after hybridization of the combinations can be distinguished, and the accuracy of obtaining the combined evaluation grade is improved.
Optionally, the generating module is specifically configured to: counting the evaluation grades of all the combinations in which each soybean germplasm resource to be tested participates in each maturity class respectively to obtain the number of the evaluation grades of each soybean germplasm resource to be tested in each maturity class; and sequencing all the soybean germplasm resources to be tested according to the number of the highest evaluation grades of each soybean germplasm resource from high to low to obtain an evaluation result of each maturity stage.
In the implementation process, the evaluation grade of each combination of the soybean germplasm resources to be tested is counted, so that the evaluation accuracy of each soybean germplasm resource to be tested can be improved.
Optionally, the selection module is specifically configured to: and selecting the soybean germplasm resources to be tested positioned at the high position of the evaluation result as soybean parents of each maturity stage class based on the target property value requirement according to the evaluation result of each maturity stage class.
In the implementation process, according to the evaluation result, the soybean germplasm resources which are arranged at a high position are selected as soybean parents, so that the soybean germplasm resources with excellent performance can be screened out, and the reliability of screening the soybean parents is improved.
Optionally, the generating module is specifically configured to: backcrossing the combination in the early maturing class with a maintainer line to obtain a first filial generation, and dividing the parent in the combination into a restorer line and a sterile line according to the pollen fertility identification result of the first filial generation obtained by backcrossing the combination with the maintainer line, wherein the female parent in the combination is the sterile line, and the male parent in the combination is the restorer line; and counting the evaluation grades in all the combinations in which each soybean germplasm resource to be tested participates in the restorer line and the sterile line in the early maturing class, and obtaining the number of each grade of each soybean germplasm resource to be tested in the restorer line in the early maturing class and the number of each grade of each soybean germplasm resource to be tested in the sterile line in the early maturing class.
In the implementation process, the combination is divided into a restorer line and a sterile line, so that independent quality analysis can be carried out on the sterile line and the restorer line respectively, and the reliability of parent soybean germplasm resource selection is improved.
Embodiments of the present application provide a storage medium having stored therein computer program instructions which, when executed by a processor, perform the steps of any of the methods described above.
Embodiments of the present application provide an electronic device comprising a memory and a processor, the memory having stored therein program instructions, which when executed by the processor, perform the steps of any of the methods described above.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments of the present application will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and should not be considered as limiting the scope, and other related drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
It should be noted that: like reference numerals and letters denote like items in the following figures, and thus once an item is defined in one figure, no further definition or explanation thereof is necessary in the following figures.
Fig. 1 is a flowchart of steps of a soybean parent selection method according to an embodiment of the present application.
Fig. 2 is a flowchart of steps for determining a combined evaluation level according to an embodiment of the present application.
Fig. 3 is a flowchart of steps for determining an evaluation result of soybean germplasm resources according to an embodiment of the present application.
Fig. 4 is a flowchart of the number of steps for obtaining each evaluation level of each soybean germplasm resource to be tested in each maturity category according to an embodiment of the present application.
Fig. 5 is a schematic diagram of a soybean parent selection apparatus according to an embodiment of the present application.
Icon: 50-soybean parent selection means; 501-an acquisition module; 502-an evaluation module; 503-a generation module; 504-selection module.
Detailed Description
The technical solutions in the embodiments of the present application will be described below with reference to the drawings in the embodiments of the present application.
Additional features and advantages of the application will be set forth in the description which follows, and in part will be apparent from the description, or may be learned by practice of the embodiments of the application. The objects and other advantages of the present application may be realized and attained by the structure particularly pointed out in the written description and drawings.
An embodiment of the present application provides a soybean parent selection method, please refer to fig. 1, and fig. 1 is a flowchart illustrating steps of a soybean parent selection method according to an embodiment of the present application. The method comprises the following steps:
step S1: and obtaining all combinations of soybean germplasm resources to be tested and each soybean germplasm resource to be tested in each combination.
Wherein each combination comprises a female parent and a male parent which are the same or different in soybean germplasm resources.
Optionally, in order to conveniently represent different soybean germplasm resources to be tested and combinations of soybean germplasm resources to be tested, the soybean germplasm resources and combinations of soybean germplasm resources to be tested are numbered, for example, soybean germplasm resources include different germplasm resources such as JLR1, JLR2, … JLR514, JLCMS1A, JLCMS a, … JLCMS334A, and the like. Each of the combination configuration numbers (combination numbers) has the format: hxx-yyyy, where xx-yyy denotes that the yyy number hybrid combination was deployed in the shed for xx years, such as H16-023 for 2017 versus 023 for 2016 (combination number is the year of deployment of the combination, but the actual performance of the labor measurement task is the next year of deployment of the combination). It is understood that the soybean germplasm resources and combinations to be tested are derived from soybean crossbreeding over the years.
Step S2: the evaluation grade of each combination is determined based on the soybean target trait value for each combination obtained from the intra-group hybridization results for each combination.
Referring to fig. 2, fig. 2 is a flowchart illustrating a step of determining a combined evaluation level according to an embodiment of the present application.
Optionally, since different soybean germplasm resources have different maturity stages, classifying the soybean germplasm resources into different maturity stage classes can further improve the accuracy of the assessment. Step S2 may be divided into the following sub-steps:
step S21: the combinations are divided into a plurality of maturity stage classes based on the period of fertility.
As one embodiment, all combinations may be classified into a very early stage group, an early stage group, a medium late stage group, a late stage group, and the like according to the growth period. The hybridization combinations are prepared in the same maturity at all sites.
Step S22: and sequencing the soybean target property values obtained by hybridization of all combinations in the same maturity stage and the same yield measurement point from high to low.
Step S23: and respectively determining the evaluation grades of all combinations in each maturity stage class according to the sequencing result.
In step S22 and step S23, as an embodiment, the target traits include fat content, protein content, yield traits, and the like, and in the example provided in the present application, taking the soybean yield as an example, soybean yield data obtained by all the measurement combinations at the same maturity stage and the same measurement point are ranked from high to low, the combination in which the combined hybrid soybean yield is 25% (25% inclusive) before ranking is classified as a first rank, and the evaluation code of the first rank is set as a. The combination with soybean yield of 26% -50% (including 50%) after combined hybridization was classified into a second grade, and the evaluation code of the second grade was set as B. The combination with soybean yield of 51-75% (75% included) after combined hybridization was classified into a third grade, and the evaluation code of the third grade was set to C. The combination after the yield of the combined hybridized soybeans was classified into a fourth grade, and the evaluation code of the fourth grade was set to D. The combination in which yield data was not obtained due to various factors was classified into a fifth class, and the evaluation code of the fifth class was set to E.
It should be understood that instead of ranking the combination according to the target trait value of the soybean after the combination hybridization, the target trait may be the survival rate of the offspring obtained by the combination hybridization, and the combination may be divided into one, two, three, etc. based on the survival rate of the offspring obtained by the combination hybridization.
With continued reference to fig. 1, step S3: and determining an evaluation result of each soybean germplasm resource to be tested based on the evaluation grade of each combination to which each soybean germplasm resource to be tested belongs. Fig. 3 is a flowchart of steps for determining an evaluation result of soybean germplasm resources according to an embodiment of the present application. Optionally, step S3 is divided into the following sub-steps:
step S31: and counting the evaluation grades of all combinations in which each soybean germplasm resource to be tested participates in each maturity stage class respectively to obtain the number of the evaluation grades of each soybean germplasm resource to be tested in each maturity stage class.
As shown in tables 1 and 2 below, table 1 shows the evaluation level of the premature class combination at test point 1 in 2001, and table 2 shows the evaluation level of the premature class combination at test point 2 in 2001.
TABLE 1
TABLE 2
| Combination number | Parent strain | Evaluation grade |
| H01-021 | JLCMS117A×JLR1 | C |
| H01-022 | JLCMS42A×JLR65 | D |
| H01-023 | JLCMS133A×JLR321 | E |
| H01-024 | JLCMS106A×JLR28 | C |
| H01-025 | JLCMS112A×JLR291 | B |
| H01-026 | JLCMS99A×JLR95 | C |
| H01-027 | JLCMS95A×JLR22 | B |
| H01-028 | JLCMS115A×JLR163 | D |
| H01-029 | JLCMS21A×JLR289 | A |
| H01-030 | JLCMS61A×JLR28 | E |
| ... | ... | ... |
Summarizing tables 1 and 2, using JLCMS117A as an example, all combinations involved therein were summarized, and all evaluation codes were counted in 2001, to obtain table 3:
TABLE 3 Table 3
Step S32: and sequencing all the soybean germplasm resources to be tested from high to low according to the number of the highest evaluation grades of each soybean germplasm resource to obtain an evaluation result of each maturity stage.
And combining the number of combinations corresponding to the evaluation codes obtained in Table 3 to obtain the evaluation results of the JLCMS117A of 3C and 1D. And counting the evaluation grade of each soybean germplasm resource to be tested to obtain a corresponding evaluation result.
With continued reference to fig. 1, step S4: and determining the soybean parent based on the evaluation result.
Optionally, step S4 includes: and selecting soybean germplasm resources to be tested positioned at the high position of the evaluation result as soybean parents of each maturity stage class based on the target property value requirement according to the evaluation result of each maturity stage class.
For example, after the evaluation results of all the soybean germplasm resources to be tested are obtained, the soybean germplasm resources to be tested, which are evaluated as 41A, 23B, 40C, 21D and 52E, are ranked according to the number of A, B, C, D, E from high to low, and the soybean germplasm resources to be tested, which are evaluated as 30A, 23B, 21C, 21D and 34E, are located before the soybean germplasm resources to be tested. And (5) preferentially selecting the soybean germplasm resources to be tested positioned at the high position in the sorting as soybean parents.
Each of the combinations obtained in this example hybridizes F 1 The actual measurement value of the substitution measurement production data is based on heterogeneous population with wide genetic base, and the soybean germplasm resource is applied by a large number of combined preparation (more than 8300)And (3) carrying out comprehensive analysis on the matching force of the rubber.
Practices of plant breeding have shown that plant parents often do not perform consistently with hybrid offspring, some of which perform well, but the hybrid offspring produced are not ideal. In contrast, some parents do not perform particularly well themselves, but are able to isolate very good individuals or combinations from their hybrid offspring, i.e., good germplasm resources are not necessarily good parents. This difference in progeny, which is exhibited by the different parent combinations, indicates that there is a different combination capacity between the different parents, called the binding force (combining ability). The advantages and disadvantages of the combination and the parents can be primarily identified in the early generation by using the cooperation force analysis, so that breeders can greatly reduce the range of processing materials, save the breeding time and improve the breeding efficiency. Tian Peizhan (1985) passed the soybean breeding test for many years, which considered: good offspring of the first generation are not all good, but poor offspring of the first generation have substantially no good offspring.
Sprague and Tatum in 1942 have proposed concepts of general and specific mating forces based on genetic studies of quantitative traits in maize and experience in cross breeding. Griffing in 1956 conducted a comprehensive arrangement and study of the double row design to make it more systematic and complete. And the method is applied to hybrid soybean parent combination preparation, and a large number of NC-II tests and triple test designs of two parents are required to obtain the corresponding coordination force effect value (the general coordination force effect value of the parents and the special coordination force effect value of the hybrid combination) of each germplasm resource. For 334 sterile lines, 514 restorer lines, this would involve a very large amount of work.
In the steps, the parent selection is carried out by only carrying out systematic analysis on the soybean target character values obtained after the soybean combination hybridization of the same maturity period and the same yield measurement point, so that the efficiency of screening soybean parents is improved, the blindness of soybean combination is reduced, and the process of guiding the target character selection is accelerated.
Further, since the combination of different maturity stages may be further divided, for example, the combination in the early maturity stage and the maintainer line are backcrossed to obtain the first filial generation, and the parent in the combination is divided into the restorer line and the sterile line according to the pollen fertility identification result of the first filial generation obtained by backcrossing the combination and the maintainer line, wherein the female parent in the combination is the sterile line and the male parent in the combination is the restorer line, the embodiment may further refine the evaluation level according to the same.
Referring to fig. 4, fig. 4 is a flowchart of a step of obtaining the number of evaluation levels of each soybean germplasm resource to be tested in each maturity category according to an embodiment of the present application. Optionally, step S31 is divided into the following sub-steps:
step S31.1: backcrossing a combination in the early maturing class with a maintainer line to obtain a first filial generation, and dividing a parent in the combination into a restorer line and a sterile line according to a pollen fertility identification result of the first filial generation obtained by backcrossing the combination with the maintainer line, wherein a female parent in the combination is the sterile line, and a male parent in the combination is the restorer line.
Step S31.2: and counting the evaluation grades in all combinations in which each soybean germplasm resource to be tested participates in the restorer line and the sterile line in the early maturing class to obtain the number of each grade of each soybean germplasm resource to be tested in the restorer line in the early maturing class and the number of each grade of each soybean germplasm resource to be tested in the sterile line in the early maturing class.
It is understood that soybean germplasm resources to be tested in each mature class can be classified into restorer lines and sterile lines. In the code of the soybean germplasm resource to be tested in step S1, JLR2, … JLR514 are restorer lines, JLCMS1A, JLCMS a, … JLCMS334A are sterile lines.
It is understood that sterile refers to a line which is produced by crossing selected male sterile individual soybean germplasm resources with fertile soybean germplasm resources and then cultivating by continuous backcrossing and has male sterile characteristics and is tidy and consistent. The sterile line is soybean germplasm resource which can not be bred, is generally pistil or stamen abortive, can not reproduce offspring by itself, and is generally applied to production, namely stamen abortive, and is called male sterility. For example, cotton has stamens and pistils in each bud, and if both are well developed, it can self-mature and reproduce offspring. However, sterile stamen are aborted, pollen cannot be produced, and if pollinating is not performed by people from other buds, the sterile stamen cannot survive.
The restorer line is the material for restoring fertility of the sterile line, and the restorer line is hybridized with the sterile line, and the filial generation can be self-matured, so that the restorer line can be applied to commodity production.
In practical production practice, the maintainer line is also included in addition to the sterile line and the restorer line, and can maintain the sterile characteristic of the sterile line, that is to say, the current generation of the sterile line and the maintainer line after hybridization can be hybridized to produce offspring through hybridization, but the offspring is still the sterile line, so that the sterile line can be propagated, and the sterile line material is maintained.
The soybean germplasm resources to be detected in each mature class are classified into sterile lines and maintainer lines according to fertility characteristics, targeted breeding can be carried out according to the fertility characteristics of the soybean germplasm resources, so that the soybean germplasm resources meeting actual requirements are obtained, and the breeding efficiency and accuracy are improved.
Referring to fig. 5, fig. 5 is a schematic diagram of a soybean parent selection apparatus according to the present embodiment.
The soybean parent selection device 50 includes:
an obtaining module 501, configured to obtain a combination of all soybean germplasm resources to be tested, and each soybean germplasm resource to be tested in each combination of soybean germplasm resources to be tested; an evaluation module 502, configured to determine an evaluation grade of each combination based on the soybean target trait value under each combination obtained from the intra-group hybridization result of each combination; a generating module 503, configured to determine an evaluation result of each soybean germplasm resource to be tested according to the evaluation level of each combination to which each soybean germplasm resource to be tested belongs; a selection module 504 for determining a selection of soybean parents based on the evaluation.
Optionally, the evaluation module 502 is specifically configured to: dividing the combination into a plurality of maturity stage classes according to the growth stage; sequencing soybean target property values obtained by hybridization of all combinations in the same maturity stage and the same yield measurement point from high to low; and respectively determining the evaluation grades of all combinations in each maturity stage class according to the sequencing result.
Optionally, the generating module 503 is specifically configured to: counting the evaluation grades of all combinations in which each soybean germplasm resource to be tested participates in each maturity stage class respectively to obtain the number of the evaluation grades of each soybean germplasm resource to be tested in each maturity stage class; and sequencing all the soybean germplasm resources to be tested from high to low according to the number of the highest evaluation grades of each soybean germplasm resource to obtain an evaluation result of each maturity stage.
Optionally, the selection module 504 is specifically configured to: and selecting soybean germplasm resources to be tested positioned at the high position of the evaluation result as a preferable soybean parent of each maturity stage class based on the target property value requirement according to the evaluation result of each maturity stage class.
Optionally, the generating module 503 is specifically configured to: backcrossing the combination in the early maturing class with a maintainer line to obtain a first filial generation, and dividing a parent in the combination into a restorer line and a sterile line according to a pollen fertility identification result of the first filial generation obtained by backcrossing the combination with the maintainer line, wherein a female parent in the combination is the sterile line, and a male parent in the combination is the restorer line; and counting the evaluation grades in all combinations in which each soybean germplasm resource to be tested participates in the restorer line and the sterile line in the early maturing class to obtain the number of each grade of each soybean germplasm resource to be tested in the restorer line in the early maturing class and the number of each grade of each soybean germplasm resource to be tested in the sterile line in the early maturing class.
The present embodiment also provides a storage medium having stored therein computer program instructions which, when executed by a processor, perform the steps of any of the methods described above.
The present embodiment also provides a storage medium having stored therein computer program instructions which, when executed by a processor, perform the steps of any of the methods described above.
The embodiment also provides an electronic device, which includes a memory and a processor, where the memory stores program instructions, and the processor executes steps in any of the methods when executing the program instructions.
Alternatively, the electronic device may be a personal computer (personal computer, PC), tablet, smart phone, personal digital assistant (personal digital assistant, PDA), or the like.
In summary, the present application provides a soybean parent selection method, a device, a storage medium and an electronic apparatus, where the method includes: determining an evaluation grade of each of said combinations based on the soybean target trait values under each of said combinations obtained from the intra-group hybridization results of each of said combinations; determining an evaluation result of each soybean germplasm resource to be tested based on the evaluation grade of each combination to which each soybean germplasm resource to be tested belongs; a soybean parent is selected based on the evaluation result.
In the implementation process, the soybean target property values of the combinations to which the same soybean germplasm resources to be tested belong are comprehensively used as the basis for selecting soybean parents, so that high-quality soybean parents can be screened out of a plurality of soybean germplasm resources, automatic screening of the soybean parents is realized, and the efficiency of screening the soybean parents can be improved, so that the goal of soybean target property value breeding is achieved.
In the several embodiments provided in this application, it should be understood that the disclosed apparatus may be implemented in other ways. The apparatus embodiments described above are merely illustrative, for example, block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of devices according to various embodiments of the present application. In this regard, each block in the block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams, and combinations of blocks in the block diagrams, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, the functional modules in the embodiments of the present application may be integrated together to form a single part, or each module may exist alone, or two or more modules may be integrated to form a single part.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. The present embodiment therefore also provides a readable storage medium having stored therein computer program instructions which, when read and executed by a processor, perform the steps of any one of the methods of block data storage. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The foregoing description is only of the preferred embodiments of the present application and is not intended to limit the same, but rather, various modifications and variations may be made by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application.
Claims (6)
1. A method of soybean parent selection, the method comprising:
obtaining all combinations of soybean germplasm resources to be tested and each soybean germplasm resource to be tested in each combination;
determining an evaluation grade of each of said combinations based on the soybean target trait values under each of said combinations obtained from the intra-group hybridization results of each of said combinations;
determining an evaluation result of each soybean germplasm resource to be tested based on the evaluation grade of each combination to which each soybean germplasm resource to be tested belongs;
determining a soybean parent based on the evaluation result;
said determining an evaluation grade for each of said combinations based on soybean target trait values for each of said combinations resulting from intra-group hybridization of each of said combinations, comprising:
classifying the combination into a plurality of maturity stage classes according to fertility stage;
sequencing the soybean target property values obtained by hybridization of the combinations in the same maturity stage and the same yield measurement point from high to low;
according to the sorting result, determining the evaluation grades of all combinations in each maturity stage class respectively;
the determining an evaluation result of each soybean germplasm resource to be tested based on the evaluation grade of each combination to which each soybean germplasm resource to be tested belongs comprises:
counting the evaluation grades of all the combinations in which each soybean germplasm resource to be tested participates in each maturity class respectively to obtain the number of the evaluation grades of each soybean germplasm resource to be tested in each maturity class;
and sequencing all the soybean germplasm resources to be tested according to the number of the highest evaluation grades of each soybean germplasm resource from high to low to obtain an evaluation result of each maturity stage.
2. The method of claim 1, wherein the selecting a soybean parent based on the evaluation result comprises:
and selecting the soybean germplasm resources to be tested positioned at the high position of the evaluation result as soybean parents of each maturity stage class based on the target property value requirement according to the evaluation result of each maturity stage class.
3. The method of claim 1, wherein the maturity stage classes include early maturity stages, and wherein the counting of the evaluation levels of all of the combinations in which each of the soybean germplasm resources under test participates in each of the maturity stage classes, respectively, results in a number of individual evaluation levels of each of the soybean germplasm resources under test in each of the maturity stage classes, comprises:
backcrossing the combination in the early maturing class with a maintainer line to obtain a first filial generation, and dividing the parent in the combination into a restorer line and a sterile line according to the pollen fertility identification result of the first filial generation obtained by backcrossing the combination with the maintainer line, wherein the female parent in the combination is the sterile line, and the male parent in the combination is the restorer line;
and counting the evaluation grades in all the combinations in which each soybean germplasm resource to be tested participates in the restorer line and the sterile line in the early maturing class, and obtaining the number of each grade of each soybean germplasm resource to be tested in the restorer line in the early maturing class and the number of each grade of each soybean germplasm resource to be tested in the sterile line in the early maturing class.
4. A soybean parent selection apparatus, said apparatus comprising:
the acquisition module is used for acquiring all combinations of soybean germplasm resources to be tested and each soybean germplasm resource to be tested in each combination of soybean germplasm resources to be tested;
an evaluation module for determining an evaluation grade of each of the combinations based on the soybean target trait values under each of the combinations obtained from the intra-group hybridization results of each of the combinations;
the generation module is used for determining an evaluation result of each soybean germplasm resource to be tested according to the evaluation grade of each combination to which each soybean germplasm resource to be tested belongs;
a selection module for determining a soybean parent based on the evaluation result;
the evaluation module is specifically used for:
classifying the combination into a plurality of maturity stage classes according to fertility stage;
sequencing the soybean target property values obtained by hybridization of the combinations in the same maturity stage and the same yield measurement point from high to low;
according to the sorting result, determining the evaluation grades of all combinations in each maturity stage class respectively;
the generating module is specifically configured to:
counting the evaluation grades of all the combinations in which each soybean germplasm resource to be tested participates in each maturity class respectively to obtain the number of the evaluation grades of each soybean germplasm resource to be tested in each maturity class;
and sequencing all the soybean germplasm resources to be tested according to the number of the highest evaluation grades of each soybean germplasm resource from high to low to obtain an evaluation result of each maturity stage.
5. A storage medium having stored therein computer program instructions which, when executed by a processor, perform the steps of the method of any of claims 1-3.
6. An electronic device comprising a memory and a processor, the memory having stored therein program instructions which, when executed by the processor, perform the steps of the method of any of claims 1-3.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010114122.9A CN111312335B (en) | 2020-02-24 | 2020-02-24 | Soybean parent selection method and device, storage medium and electronic equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010114122.9A CN111312335B (en) | 2020-02-24 | 2020-02-24 | Soybean parent selection method and device, storage medium and electronic equipment |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111312335A CN111312335A (en) | 2020-06-19 |
| CN111312335B true CN111312335B (en) | 2023-07-21 |
Family
ID=71148440
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010114122.9A Active CN111312335B (en) | 2020-02-24 | 2020-02-24 | Soybean parent selection method and device, storage medium and electronic equipment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111312335B (en) |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CL2008001682A1 (en) * | 2007-06-08 | 2008-12-12 | Monsanto Technology Llc | Methods for plant improvement through the use of direct nucleic acid sequence information. |
| WO2013156958A1 (en) * | 2012-04-19 | 2013-10-24 | Vilmorin & Cie | High yield tomato plants |
| CN103942466A (en) * | 2014-05-12 | 2014-07-23 | 中国水产科学研究院黑龙江水产研究所 | System and method for selecting fish parents based on genetic backgrounds |
| US9024131B1 (en) * | 2013-02-20 | 2015-05-05 | Pioneer Hi-Bred International, Inc. | Soybean variety XB47H13 |
| CN104885926A (en) * | 2015-05-28 | 2015-09-09 | 浙江大学 | Breeding method for special three-line hybrid rice sterile line of starch substrate |
Family Cites Families (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20020138882A1 (en) * | 1999-07-30 | 2002-09-26 | Cahoon Rebecca E | Polynucleotides encoding proteins involved in plant metabolism |
| AR030360A1 (en) * | 2001-01-05 | 2003-08-20 | Monsanto Technology Llc | METHODS FOR BREEDING AND SELECTING SOYBEAN PLANTS WITH IMPROVED PERFORMANCES |
| CA2525956A1 (en) * | 2003-05-28 | 2005-01-06 | Pioneer Hi-Bred International, Inc. | Plant breeding method |
| US7339093B1 (en) * | 2006-02-23 | 2008-03-04 | Syngenta Participations Ag | Soybean cultivar S06-WW013107 |
| JP2009022217A (en) * | 2007-07-20 | 2009-02-05 | Plant Genome Center Co Ltd | Method for producing rice of early maturing heading date |
| EP3219199A1 (en) * | 2007-09-11 | 2017-09-20 | Monsanto Technology LLC | Increased alpha-prime beta-conglycinin soybeans |
| US10031116B2 (en) * | 2012-05-30 | 2018-07-24 | Agrigenetics, Inc. | Multivariate genetic evaluation of maize for grain yield and moisture content |
| EP3135103B1 (en) * | 2013-06-14 | 2019-09-04 | Keygene N.V. | Directed strategies for improving phenotypic traits |
| CN104969855B (en) * | 2015-07-30 | 2017-05-17 | 江苏里下河地区农业科学研究所 | Method for cultivating rice breeding material with broad spectrum and lasting spike blast resistance |
| CN109328016A (en) * | 2016-06-08 | 2019-02-12 | 孟山都技术有限公司 | Method for the hybrid species of plant breeding for identification |
| CN107047282B (en) * | 2017-01-18 | 2019-05-28 | 浙江省农业科学院 | A kind of selection of Indica-Japonica hybrid rice new varieties |
-
2020
- 2020-02-24 CN CN202010114122.9A patent/CN111312335B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CL2008001682A1 (en) * | 2007-06-08 | 2008-12-12 | Monsanto Technology Llc | Methods for plant improvement through the use of direct nucleic acid sequence information. |
| WO2013156958A1 (en) * | 2012-04-19 | 2013-10-24 | Vilmorin & Cie | High yield tomato plants |
| US9024131B1 (en) * | 2013-02-20 | 2015-05-05 | Pioneer Hi-Bred International, Inc. | Soybean variety XB47H13 |
| CN103942466A (en) * | 2014-05-12 | 2014-07-23 | 中国水产科学研究院黑龙江水产研究所 | System and method for selecting fish parents based on genetic backgrounds |
| CN104885926A (en) * | 2015-05-28 | 2015-09-09 | 浙江大学 | Breeding method for special three-line hybrid rice sterile line of starch substrate |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111312335A (en) | 2020-06-19 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Ocampo Pérez et al. | Morphological characterization in the genus Passiflora L.: an approach to understanding its complex variability | |
| Fatokun et al. | Genetic diversity and population structure of a mini-core subset from the world cowpea (Vigna unguiculata (L.) Walp.) germplasm collection | |
| Geber et al. | Gender and sexual dimorphism in flowering plants | |
| Jungmann et al. | Genetic diversity and population structure analysis of the tropical pasture grass Brachiaria humidicola based on microsatellites, cytogenetics, morphological traits, and geographical origin | |
| Esmail et al. | Genetic diversity in elite cotton germplasm lines using field performance and RAPD markers | |
| Hu et al. | Genetic diversity of Brassica napus L. Germplasm from China and Europe assessed by some agronomically important characters | |
| Williams | Trifolium interspecific hybridisation: widening the white clover gene pool | |
| CRISTINA GONÇALVES CEOLIN et al. | Genetic divergence of the common bean (Phaseolus vulgaris L.) group Carioca using morpho‐agronomic traits by multivariate analysis | |
| Hardy et al. | Seed and pollen dispersal distances in two African legume timber trees and their reproductive potential under selective logging | |
| Narro et al. | Using line× tester interaction for the formation of yellow maize synthetics tolerant to acid soils | |
| Egwu | Factors affecting farmer’s adoption of agricultural innovation in Delta State | |
| Mendonça et al. | Importance and correlations of characters for cowpea diversity in traditional varieties | |
| Yehia et al. | Correlation and multivariate analysis across non-segregation and segregation generations in two cotton crosses | |
| CN111312335B (en) | Soybean parent selection method and device, storage medium and electronic equipment | |
| Egan et al. | Identification of founding accessions and patterns of relatedness and inbreeding derived from historical pedigree data in a white clover germplasm collection in New Zealand | |
| Yusop et al. | Genetic improvement of oil palm through recurrent selection | |
| Giuliani et al. | Floral morphology, micromorphology and palinology of selected Sedum sl species (Crassulaceae) | |
| de Oliveira et al. | Multitrait selection of pumpkin genotypes aimed at reducing the growth habit and improving seed production | |
| Johnson et al. | Genetic variability for seed size of two‐and three‐parent soybean populations | |
| Pereira de Castro et al. | Population improvement via recurrent selection drives genetic gain in upland rice breeding | |
| Orellana et al. | Evaluation and selection in half-sib progenies of Physalis ixocarpa Brot. aiming to increase productivity | |
| St. Martin et al. | Genetic gain in early stages of a soybean breeding program | |
| Ilić et al. | Productivity assessment of common bean (Phaseolus vulgaris) germplasm from Serbia | |
| Sá et al. | Kohonen’s self-organizing maps for the study of genetic dissimilarity among soybean cultivars and genotypes | |
| Raduski et al. | Biosystematic studies on the status of Solanum chilense (Dunal) Reiche |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |