Method for accurately identifying high-salt-tolerance oilseed rape based on large phenotype group platform

Abstract

The invention discloses a method for accurately identifying high-salt-tolerance oilseed rape based on a large phenotype group platform, and relates to the technical field of oilseed rape salt tolerance identification. Comprising the following steps: (1) site construction; (2) phenotype detection; (3) GC-MS (gas chromatography-mass spectrometry) analysis; (4) ICP-MS analysis is carried out; and (5) performing LC-MS analysis. The invention provides a crop phenotype group large-scale platform, and provides powerful assistance for accurate identification of various agronomic traits of rape and breeding of a new variety of strong salt-tolerant rape with excellent comprehensive traits through excellent gene polymerization.

Description

Technical Field

[0001] The present invention relates to the technical field of rapeseed salt tolerance identification, and more particularly to a method for accurately identifying highly salt-tolerant rapeseed based on a large-scale phenotypic group platform. Background Art

[0002] Rapeseed, a Brassica plant in the Cruciferae family, is my country's largest oilseed crop, with an annual planting area of ​​approximately 110 million mu (approximately 1.1 million hectares) and an annual production of nearly 14.5 million tons. my country's rapeseed industry produces approximately 4.5 million tons of rapeseed oil annually, accounting for 41% of my country's total domestically produced vegetable oils and 19.7% of its total oil consumption. Rapeseed is my country's fourth-largest crop after rice, wheat, and corn, but my country's vegetable oil self-sufficiency rate is only about 40%, far below the safety level of 60%.

[0003] Jiangsu Province has a large population and limited land, resulting in a particularly prominent population-land imbalance. The per capita arable land is only 0.87 mu (approximately 1.3 acres). Ensuring that summer grain production continues to grow and utilizing existing arable land to achieve rapeseed production expansion is challenging. However, the total area of ​​local saline-alkali tidal flats reaches approximately 10 million mu (approximately 1.3 acres), accounting for nearly a quarter of the country's total coastal tidal flats. Furthermore, approximately 5,000 square kilometers remain unreclaimed. These abundant coastal tidal flats are not only a vital reserve of land for the region but also a crucial cornerstone for ensuring local food and oil security.

[0004] Currently, the local rapeseed industry is limited by arable land, hindering its expansion. The high salinity of saline-alkali tidal flats makes it difficult for staple crops like wheat and corn to grow in these soils. Rapeseed is a relatively salt-tolerant oilseed crop. Therefore, utilizing local coastal saline-alkali land resources and developing salt-tolerant rapeseed is a major avenue for expanding the local rapeseed industry and a key direction for fully utilizing these resources.

[0005] To fully utilize the local saline-alkali land resources along the coastal mudflats, selecting highly salt-tolerant rapeseed varieties is a top priority. While a number of salt-tolerant rapeseed varieties have been bred for saline-alkali land in China, further improvement is needed in yield and other traits such as salt tolerance. Only by utilizing various salt-tolerant resources to further breed highly salt-tolerant rapeseed lines and leveraging the advantageous geographical location can we fully utilize the reclaimed and abandoned heavily saline-alkali land resources along the local coastal mudflats for rapeseed cultivation, develop the local rapeseed industry, and ensure the local supply of edible oil.

[0006] Currently, the large-scale phenotyping platform is an advantageous platform for large-scale and precise identification of crop phenotypes. This platform can effectively obtain trait data that cannot be obtained through traditional manual labor and traditional methods.

[0007] Therefore, it is an urgent problem for those skilled in the art to provide a large-scale crop phenotyping platform to accurately identify various agronomic traits of rapeseed, and to provide strong support for the selection of new salt-tolerant rapeseed varieties with excellent comprehensive traits through the aggregation of excellent genes. Summary of the Invention

[0008] In view of this, the present invention provides a method for accurately identifying highly salt-tolerant rapeseed based on a large phenotypic platform.

[0009] In order to achieve the above object, the present invention adopts the following technical solutions:

[0010] A method for accurately identifying highly salt-tolerant rapeseed based on a large phenotypic platform comprises the following steps:

[0011] (1) Site construction:

[0012] Build artificial rain-proof salt ponds with precise salinity control, arrange large-scale phenotyping platform instruments, and plant rapeseed resources in the salt ponds in multiple replicates according to soil salinity echelons;

[0013] (2) Phenotypic detection:

[0014] Using high-speed mobile scanning equipment, we can obtain multi-scale, multi-time, and full-stage phenotypic images of the growth phenotypes of rapeseed plants. Through high-speed software identification, we can obtain the developmental phenotypes of rapeseed resources at all growth stages, as well as the phenotypic data of stress and disease resistance.

[0015] (3) GC-MS analysis:

[0016] GC-MS was used to comprehensively analyze the metabolites and oil components of the roots, leaves, stems, and seeds of rapeseed resources, obtaining metabolite and oil profile data for each tissue throughout the entire growth period of various rapeseed resources.

[0017] (4) ICP-MS analysis:

[0018] ICP-MS was used to comprehensively analyze the ion spectra of rapeseed roots, leaves, stems, and seeds, obtaining various ion absorption spectrum data of various rapeseed resources throughout their growth period and in various tissues.

[0019] (5) LC-MS analysis:

[0020] LC-MS was used to comprehensively analyze the small molecule organic matter in the roots, leaves, stems and seeds of rapeseed resources to obtain metabolite spectrum data of various rapeseed resources throughout the growth period and in various tissues.

[0021] Furthermore, in step (1), the salt content is artificially adjusted in the artificial rain-shelter salt pond, different concentration gradients are set in each salt pond grid, and all rapeseed resources are planted three times at each salt concentration.

[0022] Furthermore, in step (1), the rapeseed seeds are sprayed for sterilization before planting, and the seeds are soaked before sowing to enhance the emergence rate of seeds in high-salinity soil;

[0023] The salt pond is set with four different concentrations of soil salt, namely 0.0%, 0.3%, 0.6% and 0.9% salt content;

[0024] The soil thickness of the salt pond is 120 cm, the depth of the shallow sowing furrow is 4-5 cm, the row spacing in step (1) is 35 cm, and the plant spacing is 17 cm.

[0025] Furthermore, in step (2), a high-speed mobile scanning device is used to scan the rapeseed plants throughout their growth period to obtain the rapeseed developmental phenotype and stress and disease resistance data.

[0026] Furthermore, step (3) uses GC-MS to comprehensively detect the metabolites and oil components of the roots, leaves, stems and seeds of rapeseed resources throughout the entire growth period, and obtains data, performs variance analysis at each salt concentration, compares whether the difference with the control at high salt concentration is significant, and preliminarily eliminates a batch of materials whose high salt content affects oil and metabolites.

[0027] Furthermore, step (4) uses ICP-MS to analyze the ion spectrum data of various rapeseed resources throughout their growth period, analyze the absorption differences of various rapeseed resources for Na ions, K ions, etc., perform correlation analysis, and obtain specific materials based on the data.

[0028] Furthermore, (5) LC-MS was used to detect the metabolite spectrum data of rapeseed resources throughout their growth period, focusing on analyzing the differences in metabolite data between high-salt soil and non-salt soil. Resources with large differences were eliminated, while those with no significant differences were retained.

[0029] Furthermore, the entire growth period of the rapeseed resources includes the seedling stage, stalk stage, flowering stage, horn stage, and maturity stage.

[0030] Furthermore, the agronomic traits of the rapeseed resources are detected, including growth phenotype (plant type, stress resistance and disease resistance, etc.), root system, leaves, stems and seeds.

[0031] Furthermore, various indicators of the rapeseed resources are analyzed, including metabolites, oil components, ion spectra, and small molecular organic matter of roots, leaves, stems, and seeds.

[0032] It can be seen from the above technical solution that compared with the prior art, the beneficial effects of the present invention are:

[0033] The present invention provides a precise identification method based on a large-scale phenotypic group platform. By utilizing salt pond sowing and a large-scale phenotypic group platform to screen for highly salt-tolerant rapeseed materials, the screening efficiency is greatly improved, thereby greatly accelerating the speed of salt-tolerant rapeseed breeding and significantly shortening the salt-tolerant breeding cycle. It has important industrial value. Through the various data obtained through the above steps, rapeseed germplasm resources with strong salt-tolerant traits are selected. DETAILED DESCRIPTION

[0034] The following is a clear and complete description of the technical solutions in the embodiments of the present invention. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts are within the scope of protection of the present invention.

[0035] Example 1

[0036] A method for accurately identifying highly salt-tolerant rapeseed based on a large phenotypic platform, the process includes:

[0037] (1) Seeds of 25 candidate rapeseed varieties (variety numbers YCD01-YCD25) were selected and planted in artificial rain-shelter salt ponds with salt contents of 0.0% (control), 0.3%, 0.6%, and 0.9% for salt tolerance testing. The soil thickness was 120 cm, the depth of the shallow sowing trench was 4-5 cm, the row spacing was 35 cm, and the plant spacing was 17 cm. Three replicates were planted for each variety. Before planting, the seeds were sprayed for sterilization with a concentration of 2500 ppm of carbendazim and a spray concentration of 0.2% of potassium permanganate, and the seeds were rinsed with distilled water several times.

[0038] (2) A high-speed mobile scanning instrument was used to scan 56 rapeseed resources planted in three replicates in artificial rain shelter salt ponds throughout the growth period (seedling stage, stalk stage, flowering stage, horn stage, and maturity stage) to obtain rapeseed developmental phenotypes and stress resistance data.

[0039] (3) GC-MS was used to comprehensively detect the metabolites and oil components of the roots, leaves, stems, and seeds of rapeseed resources, obtaining metabolite and oil profile data for each tissue throughout the entire growth period of various rapeseed resources;

[0040] (4) ICP-MS was used to comprehensively analyze the ion spectra of the roots, leaves, stems and seeds of rapeseed resources, and various ion absorption spectrum data of various rapeseed resources throughout their entire growth period (seedling stage, stalk stage, flowering stage, horn stage, and maturity stage) and various tissues were obtained.

[0041] (5) LC-MS was used to comprehensively detect the small molecule organic matter in the roots, leaves, stems and seeds of rapeseed resources, and the metabolite spectrum data of various rapeseed resources throughout the entire growth period (seedling stage, stalk stage, flowering stage, horn stage, and maturity stage) and various tissues were obtained.

[0042] A method for accurately identifying highly salt-tolerant rapeseed based on a large-scale phenotyping platform. The public example can partially explain rapeseed salt tolerance index data (plant height at maturity, necrotic spot area on leaves at seedling stage, and Na+ content in leaves at seedling stage. All data are the means of three replicates). The results are shown in Table 1:

[0043] Table 1. Data on salt tolerance of rapeseed at four salt concentrations.

[0044]

[0045]

[0046] The results in Table 1 show that the key results of the salt-tolerant resources selected in the present invention at two salt concentrations, 0.6% and 0.9%, were not significantly different from the control concentration (0.0%). In addition to the three key indicators listed above, various other data were combined to select rapeseed germplasm resources with strong salt tolerance, including materials such as YCD04, YCD05, YCD08, YCD09, YCD17, and YCD24.

[0047] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention is not limited to the embodiments shown herein but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for accurately identifying highly salt-tolerant rapeseed based on a large phenotypic platform, characterized in that: The following steps are involved: (1) Site construction: Build artificial rain-proof salt ponds with precise salinity control, arrange large-scale phenotyping platform instruments, and plant rapeseed resources in the salt ponds in multiple replicates according to soil salinity echelons; (2) Phenotypic detection: Using high-speed mobile scanning equipment, we can obtain multi-scale, multi-time, and full-stage phenotypic images of the growth phenotypes of rapeseed plants. Through high-speed software identification, we can obtain the developmental phenotypes of rapeseed resources at all growth stages, as well as the phenotypic data of stress and disease resistance. (3) GC-MS analysis: GC-MS was used to comprehensively analyze the metabolites and oil components of the roots, leaves, stems, and seeds of rapeseed resources, obtaining metabolite and oil profile data for each tissue throughout the entire growth period of various rapeseed resources. (4) ICP-MS analysis: ICP-MS was used to comprehensively analyze the ion spectra of rapeseed roots, leaves, stems, and seeds, obtaining various ion absorption spectrum data of various rapeseed resources throughout their growth period and in various tissues. (5) LC-MS analysis: LC-MS was used to comprehensively analyze the small molecule organic matter in the roots, leaves, stems and seeds of rapeseed resources to obtain metabolite spectrum data of various rapeseed resources throughout the growth period and in various tissues.

2. The method according to claim 1, characterized in that The step (1) is to artificially adjust the salt content in the artificial rain-shelter salt pond, set different concentration gradients in each salt pond grid, and plant all rapeseed resources in triplicate according to each salt concentration.

3. The method according to claim 2, characterized in that In the step (1), before planting rapeseed seeds, spray sterilize them and soak them before sowing to enhance the emergence rate of seeds in high-salt soil; The salt pond is set with four different concentrations of soil salt, namely 0.0%, 0.3%, 0.6% and 0.9% salt content; The soil thickness of the salt pond is 120 cm, the depth of the shallow sowing furrow is 4-5 cm, the row spacing in step (1) is 35 cm, and the plant spacing is 17 cm.

4. The method according to claim 1, characterized in that Step (2) uses a high-speed mobile scanning device to scan the rapeseed plants throughout their growth period to obtain rapeseed developmental phenotypes and stress and disease resistance data.

5. The method according to claim 1, characterized in that Step (3) GC-MS is used to comprehensively detect the metabolites and oil components of the roots, leaves, stems and seeds of rapeseed resources throughout their growth period, and data are obtained. Variance analysis is performed at each salt concentration to compare whether the difference with the control at high salt concentration is significant, and a batch of materials with high salt content that affects oil and metabolites are preliminarily eliminated.

6. The method according to claim 1, characterized in that Step (4) using ICP-MS to analyze the ion spectrum data of various rapeseed resources throughout their growth period, analyzing the differences in the absorption of Na ions, K ions, etc. by various rapeseed resources, performing correlation analysis, and obtaining specific materials based on the data.

7. The method according to claim 1, characterized in that (5) LC-MS was used to detect the metabolite spectrum data of rapeseed resources throughout their growth period, focusing on analyzing the differences in metabolite data between high-salt soil and salt-free soil. Resources with large differences were eliminated, and those with no significant differences were retained.

8. The method according to claims 4-7, characterized in that The entire growth period of the rapeseed resource includes the seedling stage, stalk stage, flowering stage, horn stage, and maturity stage.

9. The method according to claim 1, characterized in that The agronomic traits of the rapeseed resources are detected, including growth phenotype (plant type, stress resistance and disease resistance, etc.), root system, leaves, stems and seeds.

10. The method according to claim 1, wherein Analyze various indicators of the rapeseed resources, including metabolites, oil components, ion spectra, and small molecular organic matter in roots, leaves, stems, and seeds.

Images