Brassica napus seedling stage alkali resistance identification and germplasm resource screening method

Abstract

The invention provides a brassica napus seedling stage alkali resistance identification and germplasm resource screening method. The method comprises the following steps: preparing a mixed alkali solution; alkaline soil with different pH values is prepared according to the mixed alkali solution; the method comprises the following steps: sowing rape seeds in alkaline soil, setting a control group and an alkali treatment group, and measuring phenotypic indexes of rape seedlings after culturing for three weeks; comprehensively evaluating the alkali resistance of the rape through variable coefficient analysis, correlation analysis, membership function analysis and principal component analysis on the basis of phenotypic indexes, calculating a comprehensive evaluation value, and clustering and grading the rape seedlings according to the comprehensive evaluation value to obtain a grading result; and screening out an alkali-resistant rape material according to a grading result. According to the method, a stable alkaline soil simulation system is constructed, and a multi-index comprehensive evaluation system is combined, so that the screening efficiency of the alkali-resistant brassica napus seeds is improved.

Description

Technical Field

[0001] The invention relates to the field of agricultural biotechnology, and in particular to a method for identifying alkali resistance of Brassica napus seedlings and screening germplasm resources. Background Art

[0002] Soil salinization is a major factor limiting the expansion and sustainable development of rapeseed production, and is also a key abiotic stressor restricting crop growth and development. Discovering salt- and alkali-tolerant rapeseed germplasm is crucial for breeding salt- and alkali-tolerant varieties, implementing oilseed production capacity enhancement projects, and comprehensively developing and utilizing saline-alkali land. Accurate and efficient methods for screening and identifying salt- and alkali-tolerant germplasm are essential for identifying salt- and alkali-tolerant germplasm resources and for genetically improving salt- and alkali-tolerant rapeseed.

[0003] There are many causes of soil salinization, mainly including irrational wasteland reclamation, the development of irrigated agriculture, rainwater erosion, and the impact of human activities. Soil salinization is a problem that seriously affects the global environment. Improving soil salinity and planting salt-alkali-tolerant crops are the main measures to solve the global soil salinization problem. Among them, planting salt-alkali-tolerant crops is considered to be one of the most feasible and effective methods. However, the current methods for identifying crop alkaline tolerance have the following limitations: 1) Existing studies mostly use a single alkaline salt to simulate stress, which cannot stably control the pH value, resulting in poor experimental reproducibility; 2) Relying only on a single phenotypic indicator such as germination rate or biomass, it is difficult to fully reflect the alkaline tolerance of crops; 3) Existing methods do not combine comprehensive analysis of multiple indicators, resulting in low screening efficiency. Therefore, it is very necessary to design a method for identifying alkaline tolerance and screening germplasm resources at the seedling stage of Brassica napus. Summary of the Invention

[0004] The purpose of the present invention is to provide a method for identifying alkali resistance of Brassica napus seedlings and screening germplasm resources, by constructing a stable alkaline soil simulation system and combining it with a multi-index comprehensive evaluation system to improve the screening efficiency of alkali-resistant Brassica napus seeds.

[0005] To achieve the above object, the present invention provides the following solutions:

[0006] A method for identifying alkali resistance of Brassica napus seedlings and screening germplasm resources comprises the following steps:

[0007] preparing a mixed alkaline solution;

[0008] Prepare alkaline soils of different pH values based on the mixed alkaline solution;

[0009] Rapeseed seeds were sown in alkaline soil, and a control group and an alkali treatment group were set up. The phenotypic indicators of rapeseed seedlings were measured after three weeks of cultivation.

[0010] Based on the phenotypic indicators, comprehensive evaluation values were calculated through coefficient of variation analysis, correlation analysis, principal component analysis, and membership function analysis. The rapeseed seedlings were clustered and graded according to the comprehensive evaluation values to obtain the classification results. The classification results include: extremely alkali-sensitive type, alkali-sensitive type, intermediate-tolerant type, alkali-tolerant type, and high alkali-tolerant type.

[0011] Alkali-resistant rapeseed materials were screened out based on the grading results.

[0012] Alternatively, the specific steps of preparing the mixed alkali solution are: adding 50 mmol L -1 Sodium bicarbonate solution and 25mmolL -1 Sodium carbonate solution was mixed at a molar concentration ratio of 2:1, and 1 / 2 volume of Hoagland nutrient solution was added and stirred thoroughly until uniform to obtain a mixed alkali solution; the concentration of the mixed alkali solution was 75mmol / LL -1 .

[0013] Optionally, the specific steps of preparing alkaline soils with different pH values according to the mixed alkaline solution are: mixing the mixed alkaline solution with nutrient soil with a pH value of 6.5 and vermiculite in a mass ratio, mixing and standing for 15 minutes to obtain alkaline soils with pH values of 8.75, 8.95, 9.18 and 9.42 respectively.

[0014] Optionally, the mass ratios of alkaline soils with different pH values are:

[0015] When the mass ratio of nutrient soil to vermiculite is 3:2, the pH value of alkaline soil is 8.75; when the mass ratio of nutrient soil to vermiculite is 1:1, the pH value of alkaline soil is 8.95; when the mass ratio of nutrient soil to vermiculite is 2:3, the pH value of alkaline soil is 9.18; when the mass ratio of nutrient soil to vermiculite is 1:4, the pH value of alkaline soil is 9.42.

[0016] Optionally, the phenotypic indicators include: germination rate, aboveground fresh weight, dry weight, survival rate and number of true leaves.

[0017] Optionally, the calculation formula for membership function analysis is: Among them, x j is the alkali resistance coefficient of the phenotypic index, X min is the minimum value of the alkali resistance coefficient of the jth phenotypic index, X max is the maximum value of the alkali resistance coefficient of the jth phenotypic indicator.

[0018] Optionally, the calculation formula for the comprehensive evaluation value is: Among them, W j is the weight of the jth phenotypic indicator among all phenotypic indicators.

[0019] Optionally, the standard for clustering and grading rapeseed seeds according to the comprehensive evaluation value is:

[0020] When the comprehensive evaluation value is ≤0.15, the classification result is extremely alkali sensitive;

[0021] When 0.15<comprehensive evaluation value≤0.37, the classification result is alkali sensitive;

[0022] When 0.37<comprehensive evaluation value≤0.55, the classification result is intermediate tolerance type;

[0023] When 0.55<comprehensive evaluation value≤0.8, the classification result is alkali tolerance;

[0024] When the comprehensive evaluation value is >0.8, the classification result is high alkali tolerance type.

[0025] Optionally, it also includes: constructing a stepwise regression equation based on the phenotypic indicators and the comprehensive evaluation value, and determining the influence intensity of the phenotypic indicators on the comprehensive evaluation value through the stepwise regression equation; the expression of the stepwise regression equation is: y=0.009+0.986X1+0.208X2+0.151X3; wherein X1, X2 and X3 are the alkali resistance coefficients of the fresh weight, dry weight and number of true leaves of the aboveground part, respectively.

[0026] According to the specific embodiments provided by the present invention, the present invention discloses the following technical effects: The present invention provides a method for identifying alkali resistance of Brassica napus seedlings and screening germplasm resources, the method comprising: preparing a mixed alkali solution; preparing alkaline soils of different pH values based on the mixed alkali solution; sowing rapeseed in the alkaline soil, setting up a control group and an alkali treatment group, and measuring the phenotypic indicators of the rapeseed seedlings after three weeks of cultivation; based on the phenotypic indicators, comprehensively evaluating the alkali resistance of the rapeseed through coefficient of variation analysis, correlation analysis, membership function analysis, and principal component analysis and calculating a comprehensive evaluation value; clustering and grading the rapeseed seedlings according to the comprehensive evaluation value to obtain a grading result; and screening for alkali-resistant rapeseed materials based on the grading results. This method improves the efficiency of screening for alkali-resistant Brassica napus materials by constructing a stable alkaline soil simulation system and combining it with a multi-indicator comprehensive evaluation system. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0028] Figure 1 This is a flow chart of the method for identifying alkali resistance and screening germplasm resources of Brassica napus seedlings of the present invention;

[0029] Figure 2This is a graph showing the fresh weight of aboveground parts in alkaline soils with different pH values according to an embodiment of the present invention;

[0030] Figure 3 This is a graph showing the aboveground dry weight results of alkaline soils with different pH values according to an embodiment of the present invention;

[0031] Figure 4 This is a graph showing the number of true leaves in alkaline soils with different pH values according to an embodiment of the present invention;

[0032] Figure 5 This is a graph showing the survival rate of alkaline soils with different pH values according to an embodiment of the present invention;

[0033] Figure 6 This is a graph showing the germination rates of alkaline soils with different pH values according to an embodiment of the present invention;

[0034] Figure 7 This is a correlation analysis result diagram of an embodiment of the present invention;

[0035] Figure 8 This is a graph showing the normality test results of the principal component PC1 score value in an embodiment of the present invention;

[0036] Figure 9 This is a graph showing the normality test results of the principal component PC2 score values according to an embodiment of the present invention;

[0037] Figure 10 This is a normality test result diagram of the comprehensive evaluation value of an embodiment of the present invention. DETAILED DESCRIPTION

[0038] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0039] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0040] like Figure 1 As shown, the present invention uses Double 11 as the test variety of rapeseed, and tests are conducted under conditions of a 16h / 8h photoperiod and a temperature of 22°C, obtaining 224 germplasm materials. This embodiment provides a method for identifying alkali resistance and screening germplasm resources of Brassica napus seedlings, comprising the following steps:

[0041] Step 100: preparing a mixed alkaline solution;

[0042] Specifically, 50 mmol L -1 (4.2gL -1 ) sodium bicarbonate solution (NaHCO3) and 25mmolL -1 (2.65gL -1 ) sodium carbonate solution (Na2CO3) at a molar concentration ratio of 2:1, and the pH value of the mixed solution is about 10. To ensure the growth of rapeseed, add 1 / 2 volume of Hoagland nutrient solution and stir thoroughly until uniform, obtaining a pH value of about 9.7 and a concentration of 75mmol / L -1 of mixed alkaline solution.

[0043] Step 200: preparing alkaline soils of different pH values according to the mixed alkaline solution;

[0044] Particularly, with the nutrition soil that pH is about 6.5 as matrix, mixed alkaline solution is mixed with the nutrition soil of different masses, mixing is left standstill 15 minutes, and measures its pH value with pH meter.The present embodiment has been provided with the alkaline soil gradient of 5 different pH values, as shown in Table 1, is respectively: when the mass ratio of nutrition soil and vermiculite is 3:2, the alkaline soil pH value is 8.75; when the mass ratio of nutrition soil and vermiculite is 1:1, the alkaline soil pH value is 8.95; when the mass ratio of nutrition soil and vermiculite is 2:3, the alkaline soil pH value is 9.18; when the mass ratio of nutrition soil and vermiculite is 1:4, the alkaline soil pH value is 9.42.Control group does not carry out alkali treatment, and the mass ratio of nutrition soil and vermiculite is 1:1.

[0045] Table 1 Alkaline soil ratio table

[0046]

[0047] Step 300: sowing rapeseed seeds in alkaline soil, setting up a control group and an alkali treatment group, and measuring phenotypic indicators of the rapeseed seedlings after three weeks of cultivation;

[0048] Specifically, alkaline soil was placed in pots measuring 15 cm × 15 cm × 17 cm, with 1500 g of mixed soil per pot. The control and alkali treatment groups were sown separately, with two materials sown per pot, and 6 rapeseed seeds evenly sown in each material. Three biological replicates were set up for each treatment. Film was applied after sowing to reduce water evaporation during germination. After 3 days, most of the rapeseed seeds germinated, and the film was removed. The germination rate was counted 7 days after emergence. Phenotypic indicators including germination rate, aboveground fresh weight, dry weight, survival rate, and number of true leaves were collected 3 weeks after sowing.

[0049] Furthermore, the germination rate was calculated on the 7th day after alkali treatment, with the full expansion of the cotyledons after the seedlings broke through the soil as the germination standard. The calculation formula was: germination rate (%) = (number of seeds germinated under alkali treatment conditions / number of seeds germinated under normal planting conditions) × 100%.

[0050] Three weeks after normal planting and treatment, the aboveground fresh and dry weights were calculated. The fresh weight was measured by weighing the plant above its base, while the dry weight was measured by drying the plant at 100°C and then drying at 80°C for 72 hours. All surviving plants were weighed and divided by the number of surviving plants to obtain the average aboveground fresh and dry weight per plant.

[0051] The survival rate was calculated 3 weeks after normal planting and treatment, and the calculation formula was: survival rate (%) = (number of surviving seedlings under alkali treatment conditions / number of surviving seedlings under normal planting conditions) × 100%.

[0052] The number of fully expanded true leaves was counted 3 weeks after planting under normal and treated conditions.

[0053] It should be noted that the phenotypic indicators of this embodiment in alkaline soils with different pH values are as follows Figures 2 to 6 As shown. The results showed that with the increase of soil pH, the growth and development of the test varieties were inhibited to varying degrees. Under the treatment conditions of pH values of 8.75 and 8.95, true leaves could grow, but compared with the control group, the size of the seedlings and the number of leaves showed a very significant downward trend. When the pH value was 8.95, the inhibitory effect of alkali was more significant than that of pH value 8.75, and the fresh weight and dry weight of the seedlings decreased by 90.67% and 91.05% respectively. When the pH value was 9.18, the seeds were able to germinate, but the seedling growth only stayed at the cotyledon stage, the true leaves could not grow, the growth and development were seriously delayed, and seedling formation was difficult. When the pH value reached 9.42, the seeds could not germinate at all. The above results show that the high pH alkaline treatment environment is the key limiting factor affecting the growth and development of rapeseed. When the pH value reaches 9.18, it causes difficulty in the growth and development of true leaves, making it difficult to complete the subsequent life cycle. By comprehensively comparing the phenotypic data under different pH alkaline treatment conditions, this embodiment determined that the screening of rapeseed alkali-resistant germplasm was carried out when the pH value was 8.95.

[0054] Step 400: Based on the phenotypic indicators, a comprehensive evaluation value is calculated through coefficient of variation analysis, correlation analysis, principal component analysis, and membership function analysis, and the rapeseed seedlings are clustered and graded according to the comprehensive evaluation value to obtain a grading result; the grading results include: extremely alkali-sensitive type, alkali-sensitive type, intermediate-tolerant type (intermediate type), alkali-tolerant type, and high alkali-tolerant type;

[0055] Specifically, we first calculated the alkali tolerance index (ATI) of each phenotypic indicator for 224 rapeseed germplasm resources. The ATI is the ratio of the average value of the phenotypic indicator measured in the alkali treatment to the average value of the phenotypic indicator measured in the control group. Then, based on the alkali tolerance index, we calculated the individual membership function values of the four phenotypic indicators: germination rate, average fresh dry weight per plant, survival rate, and number of true leaves. The calculation formula is:

[0056]

[0057] Among them, x j is the alkali resistance coefficient of the phenotypic index, X min is the minimum value of the alkali resistance coefficient of the jth phenotypic index, X max is the maximum value of the alkali resistance coefficient of the jth phenotypic index. Then, principal component analysis is performed on the membership function value to obtain the variance contribution rate of the four phenotypic indicators to the alkali resistance of rapeseed, and then the weight W of the four phenotypic indicators in all phenotypic indicators is calculated. j , the calculation formula is:

[0058]

[0059] Among them, P j is the variance contribution rate of the jth phenotypic indicator obtained through principal component analysis. Finally, the comprehensive evaluation value D is calculated based on the weight, and the calculation formula is:

[0060] Specifically, the criteria for clustering and grading rapeseed seeds according to the comprehensive evaluation value are as follows:

[0061] When the comprehensive evaluation value is ≤0.15, the classification result is extremely alkali sensitive;

[0062] When 0.15<comprehensive evaluation value≤0.37, the classification result is alkali sensitive;

[0063] When 0.37<comprehensive evaluation value≤0.55, the classification result is intermediate tolerance type (intermediate type);

[0064] When 0.55<comprehensive evaluation value≤0.8, the classification result is alkali tolerance;

[0065] When the comprehensive evaluation value is >0.8, the classification result is high alkali tolerance type.

[0066] In this example, the coefficient of variation analysis was performed on the aboveground fresh weight, aboveground dry weight, leaf number, and surviving seedling number of 224 Brassica napus samples under normal and alkaline treatment (pH 8.95) conditions. The results are shown in Table 2:

[0067] Table 2 Coefficient of variation analysis results

[0068]

[0069]

[0070] CK represents materials grown under normal planting conditions, and AT represents materials grown under alkaline soil with a pH of 8.95. Compared with normal conditions, the coefficients of variation of phenotypic parameters increased significantly under alkaline treatment. The coefficient of variation of aboveground fresh weight increased from 41.49% in the control group to 70.41%, with a relative coefficient of variation of 63.08% for aboveground fresh weight. The coefficient of variation of aboveground dry weight increased from 36.26% in the control group to 68.22%, with a relative coefficient of variation of 70.40% for aboveground dry weight. The coefficient of variation of survival number increased from 0.00% in the control group to 44.78%, and the coefficient of variation of survival rate was 44.78%. The increases in the coefficients of variation for fresh weight, dry weight, and survival number all exceeded 25%. The coefficient of variation of leaf number was relatively small, increasing from 18.65% in the control group to 30.62%, while the coefficient of variation of leaf ratio was 30.2%, both reaching a significant level. The coefficient of variation of each phenotypic index under alkaline stress ranged from 30.62% to 70.41%, indicating that under alkaline treatment conditions, different Brassica napus germplasm resources had a wide range of variations in alkali tolerance and rich genetic variation within the population; alkaline stress had different effects on each index, so it was difficult to determine whether any single index could be used to evaluate the alkali tolerance of rapeseed. In-depth analysis of each trait index was needed to clarify the relationship between each trait index and alkali tolerance.

[0071] Then, the correlation analysis of the alkali tolerance coefficients of the four phenotypic indicators of the aboveground fresh weight and dry weight of the control treatment and the aboveground fresh weight and dry weight of the alkali treatment of 224 Brassica napus seedlings was conducted. Figure 7As shown in the table. CSFW represents the aboveground fresh weight of the control group; CSDW represents the aboveground dry weight of the control group; ASFW represents the aboveground fresh weight of the alkali treatment group; ASDW represents the aboveground dry weight of the alkali treatment group; RSFW represents the alkali resistance coefficient of aboveground fresh weight; RSDW represents the alkali resistance coefficient of aboveground dry weight; LR represents the alkali resistance coefficient of leaf number; SVR represents the alkali resistance coefficient of survival rate; and D-value represents the comprehensive evaluation value (D). The numerical value represents the magnitude of the correlation coefficient, and the color represents the degree of correlation between different indicators, with darker colors indicating higher correlations. In the control group, there was a highly significant negative correlation between the aboveground fresh weight and the alkali resistance index of the aboveground fresh weight, and between the dry weight and the alkali resistance index of the dry weight, with correlation coefficients of -0.21 and -0.27, respectively. The correlation coefficient between the aboveground dry and fresh weights under the alkali treatment was the highest, at 0.91, indicating a highly significant positive correlation. The correlation coefficients between the aboveground fresh weight and aboveground dry weight of the control group and the aboveground fresh and dry weight, leaf number, and survival rate alkali tolerance coefficient were all less than 0.01, indicating no significant correlation between them. The correlations between the remaining indicators were extremely significant, indicating that there was overlap in alkali tolerance information between the various phenotypic indicators. Therefore, no single phenotypic indicator can be used as a criterion for determining the alkali tolerance of Brassica napus. Further dimensionality reduction analysis is needed to extract the main components of Brassica napus alkali tolerance from the four phenotypic indicators.

[0072] Then, in order to compare the contribution of different indicators to alkali resistance, the four phenotypic indicators were first converted into membership function values, and then principal component analysis was performed on each membership function value. The results are shown in Table 3. PC1, PC2, PC3 and PC4 are the four principal components in the principal component analysis process.

[0073] Table 3 Principal component analysis results

[0074]

[0075] Principal component analysis was used to obtain the variance contributions of the four phenotypic indicators, which in this example were 61.26%, 20.56%, 10.78%, and 7.41%, respectively. Two principal components with cumulative contributions greater than 80% were extracted. The first principal component had an eigenvalue of 2.450 and a variance contribution of 61.26%, while the second principal component had an eigenvalue of 0.822 and a variance contribution of 20.56%. These two principal components represent the vast majority of the alkali resistance information of the four phenotypic indicators and are suitable for subsequent comprehensive evaluation. The load factor represents the contribution of each phenotypic indicator to the principal component. For the first principal component, the load factors for aboveground fresh weight and leaf number were 0.849 and 0.812, respectively, indicating that aboveground fresh weight and leaf number have a significant influence on the first principal component. The load factor for survival rate in the second principal component was 0.651, indicating that survival rate plays a major role in the second principal component. Then, Jarque-Bera was used to conduct a normality test on the scores of the two principal components PC1 and PC2 and the comprehensive evaluation value D of the material. The test results are as follows: Figures 8 to 10 The values are 0.6549, 0.2520, and 0.1562, respectively, all greater than 0.05, indicating that PC1, PC2, and the comprehensive evaluation value D all follow a normal distribution. This indicates that the four phenotypic indicators of aboveground fresh weight, dry weight, leaf number, and survival rate also conform to a normal distribution and have no obvious discrete values.

[0076] In this example, 224 materials were ranked by alkali resistance based on the comprehensive evaluation value D and subjected to systematic clustering. A distance matrix for the 224 materials was calculated using Euclidean distance, and the 224 materials were clustered using the centroid clustering method, resulting in the group materials being divided into five categories. The first category contained 16 materials, representing extremely alkali-sensitive types, accounting for 7.14% of the total number of materials; the second category contained 112 materials, representing alkali-sensitive types, accounting for 50% of the total number of materials; the third category contained 76 materials, representing intermediate tolerance types, accounting for 33.93% of the total number of materials; the fourth category contained 19 materials, representing alkali-tolerant types, accounting for 8.48% of the total number of materials; and the fifth category contained 1 material, representing high alkali tolerance types, accounting for 0.45% of the total number of materials.

[0077] Step 500: Screening out rapeseed materials with alkali resistance according to the classification results.

[0078] In order to determine the phenotypic indicators for identifying the alkali resistance of Brassica napus, this example also uses the alkali resistance coefficients of the four phenotypic indicators and the comprehensive evaluation value D to construct a stepwise regression equation. This equation uses the D value as the dependent variable y and the alkali resistance coefficients of the four phenotypic indicators as the independent variable X, thereby further determining the phenotypic indicators that affect the alkali resistance of rapeseed. The expression of the stepwise regression equation is:

[0079] y=0.009+0.986X1+0.208X2+0.151X3;

[0080] Among them, X1, X2 and X3 are the alkali resistance coefficients of aboveground fresh weight, dry weight and number of true leaves respectively. SPSS26 software was used to perform stepwise regression analysis on the equation to obtain the determination coefficient R 2 =0.99, F=8233.412. A larger F indicates a more significant test result, with p (significance level) <0.01. This indicates that this equation contains 99% of the alkali tolerance information of the phenotypic indicators. The coefficients of X1, X2, and X3 represent the influence of the phenotypic indicator on the comprehensive evaluation value D. Finally, the analysis shows that the aboveground dry and fresh weight and leaf number can be used as phenotypic indicators to identify rapeseed alkali tolerance. Among them, the aboveground fresh weight has the greatest impact on the comprehensive evaluation value D and is more closely associated with alkali tolerance.

[0081] The beneficial effects of the present invention are as follows:

[0082] 1) The pH value can be precisely controlled by adjusting the ratio of mixed carbonates to soil matrix, effectively simulating the saline-alkali land environment and solving the problem of pH instability in traditional single alkaline salt treatment;

[0083] 2) By integrating four phenotypic indicators (aerial fresh weight, dry weight, leaf number, and survival rate) and combining coefficient of variation analysis, correlation analysis, membership function analysis, and principal component analysis, we achieved comprehensive quantification of alkaline tolerance and improved screening accuracy.

[0084] 3) The constructed stepwise regression equation can quickly predict alkali resistance based on key indicators, shortening the experimental cycle and reducing screening costs.

[0085] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0086] The present invention uses specific examples to illustrate the principles and implementation methods of the present invention. The above examples are only intended to help understand the method and core concept of the present invention. At the same time, those skilled in the art will find that the specific implementation methods and application scopes may vary based on the concept of the present invention. In summary, the contents of this specification should not be construed as limiting the present invention.

Claims

1. A method for identifying alkali resistance of Brassica napus seedlings and screening germplasm resources, characterized in that: The steps include: preparing a mixed alkaline solution; preparing alkaline soils with different pH values according to the mixed alkaline solution; sowing rapeseed seeds in the alkaline soil, setting a control group and an alkali treatment group, and measuring the phenotypic indicators of the rapeseed seedlings after culturing for three weeks; Based on the phenotypic indicators, a comprehensive evaluation of the alkali resistance of rapeseed is performed through coefficient of variation analysis, correlation analysis, membership function analysis, and principal component analysis to calculate a comprehensive evaluation value, and the rapeseed seeds are clustered and graded according to the comprehensive evaluation value to obtain a grading result; the grading result includes: extremely alkali-sensitive type, alkali-sensitive type, intermediate-tolerant type, alkali-tolerant type, and high-alkali-tolerant type; The rapeseed material with alkali resistance is screened out according to the classification results.

2. The method for identifying alkali resistance and screening germplasm resources of Brassica napus seedlings according to claim 1, wherein: The specific steps for preparing the mixed alkali solution are: add 50mmolL -1 Sodium bicarbonate solution and 25mmolL -1 Sodium carbonate solution is mixed at a molar concentration ratio of 2:1, and 1 / 2 volume of Hoagland nutrient solution is added and stirred until uniform to obtain the mixed alkaline solution; The concentration of the mixed alkali solution is 75mmolL -1 .

3. The method for identifying alkali resistance and screening germplasm resources of Brassica napus seedlings according to claim 1, wherein: The specific steps of preparing alkaline soils with different pH values according to the mixed alkaline solution are as follows: mixing the mixed alkaline solution with nutrient soil with a pH value of 6.5 and vermiculite in different mass ratios, mixing well and standing for 15 minutes to obtain the alkaline soils with pH values of 8.75, 8.95, 9.18 and 9.42, respectively.

4. The method for identifying alkali resistance and screening germplasm resources of Brassica napus seedlings according to claim 3, wherein: The mass ratios of the alkaline soils with different pH values are: When the mass ratio of the nutrient soil to the vermiculite is 3:2, the pH value of the alkaline soil is 8.75; when the mass ratio of the nutrient soil to the vermiculite is 1:1, the pH value of the alkaline soil is 8.95; when the mass ratio of the nutrient soil to the vermiculite is 2:3, the pH value of the alkaline soil is 9.18; when the mass ratio of the nutrient soil to the vermiculite is 1:4, the pH value of the alkaline soil is 9.

42.

5. The method for identifying alkali resistance and screening germplasm resources of Brassica napus seedlings according to claim 1, wherein: The phenotypic indicators include: germination rate, aboveground fresh weight, dry weight, survival rate and number of true leaves.

6. The method for identifying alkali resistance and screening germplasm resources of Brassica napus seedlings according to claim 1, wherein: The calculation formula of the membership function analysis is: Among them, x j is the alkali resistance coefficient of the phenotypic index, X min is the minimum value of the alkali resistance coefficient of the jth phenotypic index, X max is the maximum value of the alkali resistance coefficient of the jth phenotypic indicator.

7. The method for identifying alkali resistance and screening germplasm resources of Brassica napus seedlings according to claim 6, characterized in that: The calculation formula of the comprehensive evaluation value is: Among them, W j is the weight of the jth phenotypic indicator among all phenotypic indicators.

8. The method for identifying alkali resistance and screening germplasm resources of Brassica napus seedlings according to claim 1, wherein: The standard for clustering and grading the rapeseed seeds according to the comprehensive evaluation value is: When the comprehensive evaluation value is ≤0.15, the classification result is the extremely alkali-sensitive type; When 0.15<comprehensive evaluation value≤0.37, the classification result is the alkali-sensitive type; When 0.37<comprehensive evaluation value≤0.55, the classification result is the intermediate tolerance type; When 0.55<comprehensive evaluation value≤0.8, the classification result is the alkali-tolerant type; When the comprehensive evaluation value is greater than 0.8, the classification result is the high alkali tolerance type.

9. The method for identifying alkali resistance and screening germplasm resources of Brassica napus seedlings according to claim 1, wherein: Also includes: A stepwise regression equation is constructed based on the phenotypic indicators and the comprehensive evaluation value, and the influence intensity of the phenotypic indicators on the comprehensive evaluation value is determined by the stepwise regression equation; the expression of the stepwise regression equation is: y=0.009+0.986X1+0.208X2+0.151X3; wherein X1, X2 and X3 are the alkali resistance coefficients of the fresh weight, dry weight and number of true leaves of the aboveground part, respectively.

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