CN114190132A - Method for evaluating cold resistance of rice in bud stage - Google Patents
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Abstract
The invention discloses a method for evaluating cold resistance of rice in a germination period. The invention provides a method for identifying cold resistance of rice in a germination period, which comprises the following steps: taking the germination rate, the germination vigor, the germination index, the seed germination index, the average germination time, the germination coefficient and the seedling rate as evaluation indexes of cold resistance in the germination period, respectively carrying out low-temperature treatment on a plurality of test rice varieties, and detecting the 7 indexes; performing principal component analysis; calculating membership function values and weights; and then calculating the comprehensive cold tolerance index D value of each variety of rice, wherein the larger the D value is, the stronger the cold tolerance at the bud stage is. The method adopts multivariate statistical analysis to comprehensively evaluate the cold resistance of the rice germplasm resources in the bud stage, further screens out reasonable phenotype evaluation indexes, and has important significance for evaluation of the rice germplasm resources and breeding of new rice varieties with excellent cold resistance.
Description
Technical Field
The invention relates to the technical field of agriculture, in particular to a method for evaluating cold resistance of rice in a germination period.
Background
Rice is a main food crop, and over half of the world population takes rice as staple food. Cold damage is a major factor that causes a decrease in rice yield. Around 1500 million hectares of land around the world is vulnerable to cold damage, especially in japan, korea, northeast and southwest regions of china. The direct seeding of rice is favorable to mechanized operation, has advantages such as save labour, laborsaving, high efficiency, and along with the labour pours into the city in a large number, the direct seeding is more and more favored by peasant. The germination period is the weakest period in the growth and development process of rice, and the germination rate of directly-sown rice seeds is greatly reduced due to cold damage, so that abnormal seedlings are formed, even the seeds die, and finally the yield is seriously reduced. Therefore, improving the cold resistance of the rice in the bud stage is an important target of rice breeding, and the rice variety with strong cold resistance in the bud stage is beneficial to grain production and promotes grain safety and sustainable development.
And (3) evaluating the low-temperature flooding resistance of 36 parts of rice materials by using a membership function method, and screening 5 parts of rice germplasms with outstanding low-temperature flooding resistance. Zhangxiaoli et al, screened 8 excellent rice varieties resistant to low temperature and low oxygen, such as Guiyu No. 9, by analyzing the direct seeding character indexes of rice by a principal component analysis method. Although scholars at home and abroad carry out a certain amount of work on the identification of cold resistance of rice in the bud stage, the method mostly adopts a single statistical method such as principal component analysis or membership function analysis to carry out identification and evaluation, the cold resistance grade identification result obtained only according to one statistical method lacks accuracy and comprehensiveness, and the results of various methods are possibly inconsistent or have certain correlation. At present, no report of comprehensively evaluating the cold resistance of the rice in the bud stage by using a multivariate statistical method is available.
Disclosure of Invention
The invention aims to comprehensively evaluate the cold resistance of the rice germplasm resources in the bud stage by adopting multivariate statistical analysis, further screens out reasonable phenotype evaluation indexes and provides reference for evaluation of the rice germplasm resources and breeding of new rice varieties with excellent cold resistance.
In a first aspect, the invention claims a method for identifying cold tolerance in rice at the germination stage.
The method for identifying the cold resistance of the rice in the bud stage, which is claimed by the invention, can comprise the following steps:
(A1) taking 7 indexes of Germination Rate (GR), Germination Potential (GP), Germination Index (GI), seed germination index (PI), Mean Germination Time (MGT), Germination Coefficient (GC) and Seedling Rate (SR) as evaluation indexes of cold tolerance in the bud stage, and respectively carrying out (such as 5-15 ℃) low-temperature treatment on a plurality of rice varieties to be tested to detect the 7 indexes.
In the specific embodiment of the invention, the seedling rate is counted under the condition of 5 ℃, and other 6 indexes such as the germination rate is counted under the condition of 15 ℃.
(A2) And (c) performing principal component analysis on the 7 indexes of each variety of rice measured in (A1).
(A3) For each principal component value obtained in (a2), a membership function value u (X) is calculated as followsj,i) And a weight Wj。
u(Xj,i)＝(Xj,i-Xj,min)/(Xj,max-Xj,min) (ii) a j is 1, 2, …, n; n is a positive integer of 2 or more.
Wherein u (X)j,i) The membership function value of the jth main component of the ith variety is expressed; xj,iShowing the principal component value, X, of the jth principal component of the ith varietyj,maxAnd Xj,minThe maximum and minimum values of the major component values of the jth major component in all the rice varieties tested are indicated.
Wherein, WjRepresents the importance degree, namely the weight, of the jth principal component in all principal components; pjRepresenting the contribution rate of the jth principal component obtained by principal component analysis.
Principal component value Xj,i、Xj,maxAnd Xj,minAnd anContribution ratio P of principal componentjObtained by performing the principal component analysis.
(A4) The membership function value u (X) obtained in (A3)j,i) And a weight WjAnd respectively calculating the comprehensive cold resistance index D value of each variety of rice according to the following formula, wherein the larger the D value is, the stronger the cold resistance in the bud stage is.
Further, in the step (a1), the detection of the 7 indexes may be calculated according to the following formula:
germination rate (%) (number of seeds to be germinated/total number of seeds) × 100;
germination vigor (%) × 100 (number of seeds germinated in the first 4 days/total number of seeds);
germination index ═ Σ (Gt/Dt); wherein Gt is the germination number of the t day; dt is the t-th day of the germination experiment;
seed germination index is 1.00 xnd2+0.75×nd4+0.50×nd6+0.25×nd8(ii) a Therein, nd2、nd4、nd6、nd8Germination rates of 2d, 4d, 6d and 8d, respectively;
average germination time ═ G1T1+G2T2+……+GnTn)/(G1+G2+……+Gn) (ii) a Wherein Tn is the number of germination days, and Gn is the number of germination seeds per day corresponding to Tn;
germination coefficient is germination rate/average germination time;
the seedling formation rate (%) × 100 (number of surviving seedlings/total number of germinated seeds).
Further, in the step (a2), when principal component analysis is performed on the 7 indexes of each variety of rice, the principal component analysis may be performed according to a principal component extraction standard in which the characteristic value is greater than 1 and the cumulative contribution rate is not less than 80%. Correspondingly, 2 principal components are obtained, and the corresponding feature vectors are respectively:
CI1＝0.429PI+0.426GC+0.418GR-0.418MGT+0.415GI+0.336GP-0.008SR；
CI2＝0.001PI-0.033GC+0.043GR+0.055MGT+0.076GI-0.014GP+0.994SR；
wherein, CI1Representing a first principal component value; CI2Representing a second principal component value; PI represents a seed germination index; GC represents the germination coefficient; GR represents the germination rate; MGT means mean time to germination; GI means germination index; GP represents germination vigour; SR represents the seedling rate.
In a second aspect, the invention claims the use of the method of the first aspect in any one of:
p1, screening varieties with relatively strong cold resistance in the bud stage from a plurality of rice varieties;
p2, comparing the cold resistance of different rice varieties in the bud stage.
In a third aspect, the invention claims a method for identifying cold tolerance in rice at the germination stage.
The method for identifying the cold resistance of the rice in the bud stage, which is claimed by the invention, can comprise the following steps:
(B1) and (3) carrying out low-temperature (such as 5-15 ℃) treatment on the rice to be detected, and counting the germination index, the seedling rate, the average germination time, the seed germination index, the germination rate and the germination potential.
In the specific embodiment of the invention, the seedling rate is counted under the condition of 5 ℃, and other 5 indexes such as the germination rate is counted under the condition of 15 ℃.
(B2) And calculating the comprehensive cold resistance index D 'value of the rice to be detected according to the following formula, wherein the larger the D' value is, the stronger the cold resistance in the bud stage is.
D' value 0.592+0.090GI +0.123SR-0.075MGT +0.086PI +0.099GR +0.054 GP;
wherein GI represents germination index; SR represents the seedling rate; MGT means mean time to germination; PI represents a seed germination index; GR represents the germination rate; GP represents the germination vigour.
Further, the calculation formula of each index is as follows:
germination index ═ Σ (Gt/Dt); wherein Gt is the germination number of the t day; dt is the t-th day of the germination experiment;
the seedling rate (%) (number of surviving seedlings/total number of germinated seeds) × 100;
average germination time ═ G1T1+G2T2+……+GnTn)/(G1+G2+……+Gn) (ii) a Wherein Tn is the number of germination days, and Gn is the number of germination seeds per day corresponding to Tn;
seed germination index is 1.00 xnd2+0.75×nd4+0.50×nd6+0.25×nd8(ii) a Therein, nd2、nd4、nd6、nd8Germination rates of 2d, 4d, 6d and 8d, respectively;
germination rate (%) (number of seeds to be germinated/total number of seeds) × 100;
germination vigor (%) × (number of seeds germinated on the first 4 days/total number of seeds) × 100.
In a fourth aspect, the invention claims the use of the method of the third aspect in any one of:
p1, screening varieties with relatively strong cold resistance in the bud stage from a plurality of rice varieties;
p2, comparing the cold resistance of different rice varieties in the bud stage.
In a fifth aspect, the invention claims the application of the germination rate, the germination vigor, the germination index, the seed germination index, the average germination time, the germination coefficient and the seedling rate as evaluation indexes in the identification of the cold tolerance of the rice in the germination period.
In a sixth aspect, the invention claims the application of the germination index, the seedling rate, the average germination time, the seed germination index, the germination rate and the germination potential as evaluation indexes in the identification of the cold tolerance of the rice in the germination period.
In a seventh aspect, the invention claims a method for grouping rice germplasm resources according to cold tolerance at the bud stage.
The method for classifying the rice germplasm resources according to the cold resistance at the bud stage comprises the following steps:
(C1) performing cold tolerance identification on all rice varieties to be subjected to cluster division by adopting the method of the first aspect, thereby obtaining the comprehensive cold tolerance index D values of all the rice varieties; or
Performing cold tolerance identification on all rice varieties to be subjected to cluster division by adopting the method of the second aspect, thereby obtaining the comprehensive cold tolerance index D' values of all the rice varieties;
(C2) and (4) performing cluster analysis according to the obtained comprehensive cold-resistance index D value or the comprehensive cold-resistance index D' value of (C1), thereby dividing all rice varieties into different groups.
Further, in step (C2), clustering analysis may be performed by using euclidean distance and interclass linkage.
In a specific embodiment of the present invention, the dormancy-breaking seeds are treated at a low temperature of 15 ℃ for 10 days while measuring the germination rate, germination vigor, germination index, seed germination index, average germination time and germination coefficient. When the seedling rate is measured, the germinated seeds are treated at the low temperature of 5 ℃ for 10 days.
In a specific embodiment of the present invention, the rice cultivars are shown in table 1.
The invention takes 18 rice varieties as experimental materials, and counts the germination rate, the germination vigor, the germination index, the seed germination index, the average germination time, the germination coefficient and the seedling rate after low-temperature treatment at 15 ℃ and 5 ℃. And performing comprehensive evaluation on the cold resistance of the rice germplasm resources in the bud stage and screening identification indexes by using methods such as principal component analysis, cluster analysis, stepwise regression analysis and the like. The results show that: the germination rate is in extremely obvious positive correlation with the germination vigor, the seed germination index, the germination index and the germination coefficient, the average germination time is in extremely obvious negative correlation with the germination rate, the germination vigor, the seed germination index, the germination index and the germination coefficient, and the correlation among all indexes except the seedling rate reaches an extremely obvious level. Converting 7 single indexes identified by cold resistance in the bud stage into 2 independent indexes by a principal component analysis method; a comprehensive evaluation value D of the cold resistance of the rice in the bud stage is obtained through membership function and weight calculation, and the D is utilized for carrying out cluster analysis, so that the cold resistance of 18 rice varieties in the bud stage is divided into 5 grades, wherein 2 varieties with strong cold resistance are provided, 5 varieties with strong cold resistance are provided, 7 varieties with medium cold resistance are provided, 1 variety with weak cold resistance is provided, and 3 varieties with weak cold resistance are provided. Obtaining an optimal regression equation of the cold resistance of the rice in the bud stage by adopting a stepwise regression analysis method: and D is 0.592+0.090GI +0.123SR-0.075MGT +0.086PI +0.099GR +0.054GP, and 6 indexes which have obvious influence on the cold tolerance of the rice in the germination period are screened out. The test result of the invention shows that under the condition of low temperature stress, the cold resistance of the rice variety can be quickly and accurately identified and evaluated by measuring 6 indexes of germination rate, germination vigor, germination index, seed germination coefficient, average germination time and seedling rate. The method has important significance for the evaluation of rice germplasm resources and the breeding of new rice varieties with excellent cold resistance.
Drawings
FIG. 1 shows the result of resource clustering analysis of 18 rice germplasm based on 7 bud stage cold tolerance indexes.
Detailed Description
The present invention is described in further detail below with reference to specific embodiments, which are given for the purpose of illustration only and are not intended to limit the scope of the invention. The examples provided below serve as a guide for further modifications by a person skilled in the art and do not constitute a limitation of the invention in any way.
The experimental procedures in the following examples, unless otherwise indicated, are conventional and are carried out according to the techniques or conditions described in the literature in the field or according to the instructions of the products. Materials, reagents and the like used in the following examples are commercially available unless otherwise specified.
Example 1 comprehensive evaluation of Cold tolerance of Rice at sprout stage by multivariate statistical method
Materials and methods
1. Experimental Material
In the embodiment, 18 parts of rice germplasm resources are selected in total and are derived from 9 different provinces in Japan and China, and detailed germplasm information is shown in Table 1.
TABLE 118 Rice germplasm resource names and sources
2. Experimental methods
After the seeds were put in an oven at 50 ℃ for 72 hours to break dormancy, surface sterilization was performed with 70% ethanol, and the seeds were washed three times with sterile water.
40 seeds of each variety are placed in a 9cm culture dish paved with double-layer filter paper, and after a proper amount of distilled water is added, the seeds are treated for 10 days in a climatic incubator at 15 ℃ (16h light/8 h dark). And (4) recording the exposure of the seeds as germination, and counting the number of the seeds to be germinated every day for calculating the germination cold-resistant index. Each variety was repeated 3 times.
The seedling rate experiment includes that rice seeds are soaked for 48 hours in a dark condition at 28 ℃, and then are put into an incubator at 30 ℃ for germination acceleration for 24 hours in the dark condition. 40 rice seeds with shoots of about 5mm in length were selected and transferred to a petri dish. After being treated in a 5 ℃ climatic incubator (16h light/8 h dark) for 10 days, the culture medium is placed in a culture room (28 ℃, 16h light/8 h dark) and recovered for 7 days. After 7 days, the number of seedlings was counted. Each variety was repeated 3 times.
3. Measurement index
The cold tolerance of different varieties of rice at the germination stage is evaluated by using the Germination Rate (GR), the Germination Potential (GP), the Germination Index (GI), the germination index (PI), the average germination time (MGT), the Germination Coefficient (GC) and the Seedling Rate (SR) as evaluation indexes of the cold tolerance at the germination stage. The calculation formula of each index is as follows:
germination rate (%) ((number of germinated seeds/total number of seeds) × 100 (1))
Germination vigor (%) - (number of seeds germinated in the first 4 days/total number of seeds) × 100(2)
The germination index ═ Σ (Gt/Dt) (3), where Gt is the number of sprouts on day t; dt is day t of germination experiment.
Seed germination index is 1.00 xnd2+0.75×nd4+0.50×nd6+0.25×nd8 (4)
In the formula, nd2、nd4、nd6、nd8The germination rates were 2d, 4d, 6d and 8d, respectively.
Average germination time ═ G1T1+G2T2+……+GnTn)/(G1+G2+……+Gn) And (5) in the formula, Tn is the number of germination days, and Gn is the number of germination seeds corresponding to Tn per day.
Germination coefficient ═ germination percentage/average germination time (6)
Percent seedling growth (number of surviving seedlings/total number of germinated seeds) × 100 (7)
4. Data processing and statistical analysis
(1) Evaluation index
Membership function value of each comprehensive index
u(Xj,i)＝(Xj,i-Xj,min)/(Xj,max-Xj,min) (8) j ═ 1, 2, …, n; n is a positive integer of 2 or more.
In the formula, n is a positive integer greater than or equal to 2; xj,iThe main component value of the jth main component of the ith variety is represented; xj,maxAnd Xj,minThe maximum and minimum values of the major component values of the jth major component in all the rice varieties tested are indicated.
② weight of each comprehensive index
In the formula, WjRepresents the importance degree, namely the weight, of the jth principal component in all principal components; pjRepresenting the contribution rate of the jth principal component obtained by principal component analysis.
Third, the comprehensive cold resistance of the rice germplasm resources
In the formula, the value D is the comprehensive cold resistance evaluation of the ith rice variety under the low-temperature condition through comprehensive index evaluation.
(2) Statistical analysis of data
Data statistics and arrangement are carried out by using Excel 2016 software, and correlation analysis, principal component analysis, cluster analysis and regression analysis are carried out by using SPSS26.0 data analysis software.
Second, result in
1. Correlation analysis between indices
And (4) carrying out correlation analysis on each single index of the bud stage. As can be seen from Table 2, there are different degrees of correlation between the 7 traits. The germination rate is in extremely obvious positive correlation with the germination vigor, the seed germination index, the germination index and the germination coefficient, wherein the correlation coefficient of the germination rate and the germination coefficient is the largest and is 0.985; the average germination time is extremely obviously and negatively related to the germination rate, the germination vigor, the seed germination index, the germination index and the germination coefficient, wherein the correlation coefficient of the average germination time and the germination coefficient is maximum and is-0.953; the relativity between the seedling rate and other indexes does not reach a significant level. The correlation analysis result shows that most of single indexes have extremely significant correlation.
TABLE 2 correlation coefficient matrix of individual indexes of rice in germination stage
Note: indicates a very significant correlation (P ≦ 0.01).
2. Principal component analysis
The SPSS26.0 software is used for carrying out principal component analysis on 7 indexes of 18 rice varieties, and default values are set for parameters. According to the principal component extraction standard that the characteristic value is greater than 1 and the cumulative contribution rate is greater than or equal to 80%, as shown in table 3, two principal components are co-extracted, and the characteristic values of the two principal components are 5.303 and 1.010 respectively, which are both greater than 1. The two principal component contribution rates are 75.752% and 14.428% respectively, the accumulated contribution rate is 90.179%, most indexes can be sufficiently summarized, and therefore, the original 7 indexes are converted into 2 new independent comprehensive indexes which are respectively defined as the 1 st principal component and the 2 nd principal component and are used for the phenotypic index evaluation of rice germplasm resources. The 1 st principal component explains 75.752% change of 7 characters, and the largest absolute value of the feature vector is a seed germination coefficient (0.429); the 2 nd principal component explains the 14.428% change of 7 personality, and the largest absolute value of the eigenvector is the seedling rate (0.994). From table 3, the corresponding feature vectors of the respective comprehensive indexes are:
CI1＝0.429PI+0.426GC+0.418GR-0.418MGT+0.415GI+0.336GP-0.008SR。
CI2＝0.001PI-0.033GC+0.043GR+0.055MGT+0.076GI-0.014GP+0.994SR。
wherein, CI1Is the 1 st principal component value; CI2Is the 2 nd principal component value.
TABLE 3 principal component contribution ratio and eigenvectors
3. Comprehensive evaluation of varieties
(1) Membership function
And (4) calculating the membership function value of each comprehensive index of each variety of rice according to a formula (8) (table 4). For the same comprehensive index such as the main component 1, the highest membership value of the indica type gene accounts for 13 under the low-temperature stress treatment is 1.00, which shows that the germplasm is the strongest in cold resistance in the aspect of the main component 1, while the lowest membership value of the pearl is 0.00, which shows that the germplasm is the worst in cold resistance in the comprehensive index.
(2) Weight determination
The weights of 2 general indicators at the bud stage (table 3) were determined by equation (9) based on the contribution rates of the general indicators at the bud stage, and were 0.84 and 0.16, respectively.
(3) Comprehensive evaluation
And (4) obtaining a comprehensive evaluation value D (shown in table 4) of the cold resistance of the 18 kinds of rice under the low-temperature condition according to the membership value and the weight of each comprehensive index, and ranking the cold resistance in the bud stage according to the comprehensive evaluation value D. The magnitude of the comprehensive evaluation value D reflects the magnitude of the cold resistance of each rice variety in the bud stage, and the larger the numerical value is, the stronger the cold resistance is. As can be seen from table 4, the total evaluation values (D values) of indica type 13 and patrinia are high (0.88, 0.83), and the cold resistance is evaluated to be extremely strong. The comprehensive evaluation values (D values) of Yangdao No. 3 and pearl dwarf are low (0.05, 0.04), and the comprehensive cold resistance is evaluated to be extremely weak.
TABLE 4 values of principal component, membership function, comprehensive evaluation value (D value), and predicted value for each variety
(4) Regression analysis
In order to analyze the relationship between the index and the variety cold resistance, screening reliable cold resistance identification indexes, establishing a linear relationship which can be used for evaluating the cold resistance of the rice in the bud stage, taking a comprehensive evaluation value (D value) of the cold resistance as a dependent variable, taking each single index as an independent variable to carry out stepwise regression analysis, and establishing an optimal regression equation: d value is 0.592+0.090GI +0.123SR-0.075MGT +0.086PI +0.099GR +0.054 GP. Equation determining coefficient R21.0000 and P0.0000, indicating that 6 independent variables can determine almost all the variations of D values. As can be seen from the equation, 6 indexes of the 7 single indexes have obvious influence on the cold resistance of the rice, namely the germination index, the seedling rate, the average germination time, the seed germination index, the germination rate and the germination vigor. The regression equation is used for predicting the cold resistance of 18 varieties of rice, and the predicted values (table 4) are completely consistent with the sequencing of the comprehensive evaluation value D values. The regression equation can well quantify the relationship between the comprehensive cold resistance of each variety and each index value, and can be used for scientifically and accurately predicting the cold resistance of rice.
(5) Cluster analysis
And (3) performing clustering analysis by using the D value and adopting an Euclidean distance and interclass connection method, and dividing 18 varieties into 5 groups (shown in figure 1) corresponding to 5 grades of strong, medium, weak and weak rice cold resistance.
The I group comprises 7 varieties of Zhendao No. 1, Ji Jing No. 1, Square short, Chu Jing No. 5, Yujing No. 9, Hanfeng No. 8, lotus pool early and the like, and has moderate cold resistance; the second group comprises 2 varieties of indica 13, patrinia and the like, and has extremely strong cold resistance; the group III comprises 5 varieties of red 410, extra green, Ningjing No. 6, Kaijing No. 2, Liaojing No. five and the like, and has strong cold resistance; the IV group comprises 3 varieties of Simi No. 2, Yanggao No. 3, short pearl and the like, and has extremely weak cold resistance; group V included Pioneer 1 variety, with weak cold tolerance (Table 5).
Cold-resistant grading results for 518 rice germplasm resources in Table
Third, discuss
1. Selection of cold tolerance identification index of rice germplasm resource in bud stage
The screening and identification of cold-resistant germplasm resources in the bud stage are one of the core tasks of cold-resistant breeding in the bud stage of rice. According to the invention, through stepwise regression analysis, 6 single indexes which can obviously influence the D value, namely the germination rate, the germination vigor, the germination index, the seed germination coefficient, the average germination time and the seedling rate, are obtained, the requirements of a large number of germplasm resources in the bud stage cold tolerance identification on the evaluation indexes are met, the evaluation indexes are simple, easy, accurate and effective, and the relatively comprehensive evaluation can be carried out on the rice in the bud stage cold tolerance. The evaluation model is used for evaluating the cold tolerance of the rice germplasm in the bud stage, so that the cold tolerance of the rice germplasm resources in the bud stage can be effectively and quickly identified, and the identification work is simple, quick and effective.
2. Multivariate statistical analysis of cold resistance of rice germplasm resources in bud stage
The cold tolerance of the rice in the bud stage is a complex character influenced by a plurality of factors, and the cold tolerance of the rice in the bud stage is difficult to accurately and comprehensively reflect by singly using certain single indexes. The multiple cold-resistant related indexes in the bud stage can be quantified by utilizing a multivariate statistical analysis method, a quantitative relation is established between the cold-resistant indexes and the cold-resistant strength in the bud stage, and the cold-resistant performance of the rice in the bud stage is efficiently identified. The method selects 7 simple, visual and convenient indexes, and comprehensively evaluates the cold resistance of the rice in the bud stage by using a multivariate analysis method.
The principal component analysis is a common dimension reduction method in multivariate statistical analysis, and can convert a plurality of associated complex indexes into a plurality of mutually independent comprehensive indexes. According to the method, through principal component analysis, 7 single indexes in the rice germination period are converted into 2 mutually independent comprehensive indexes, and most of information carried by the original indexes is explained. The membership function analysis is a multi-factor decision method for comprehensively evaluating things under the influence of various factors by using a fuzzy set theory. The invention uses a membership function method to normalize the eigenvectors of 2 comprehensive indexes, and combines the weight obtained by principal component analysis to obtain the comprehensive evaluation value D of the cold resistance of the rice germplasm in the bud stage. And (4) carrying out sequencing grade grading on the cold resistance of 18 rice germplasms according to the D value. The results show that the cold resistance of the indica type rice accounts for 13 and the patrinia is the strongest of the rice germplasm selected by the invention, and the indica type rice can be utilized in the breeding and improvement of cold-resistant varieties in the rice bud stage in the future.
The cluster analysis can classify different germplasm and can intuitively analyze the cluster relation among different germplasm. In the invention, the D value is used for carrying out cluster analysis, 18 rice germplasms are divided into 5 categories, which correspond to 5 rice cold-resistant grades of strong, medium, weak and weak. The result verifies that the result of evaluating the cold resistance of the rice in the bud stage by using the D value is reliable, and provides a powerful reference for the rapid identification of the cold resistance of the rice germplasm in the bud stage. The invention constructs 1 reliable rice bud cold tolerance evaluation model by stepwise regression, can predict the cold tolerance of the target germplasm in the bud stage under the same stress condition, and provides a certain basis for cold tolerance breeding and resource identification of the rice bud stage.
Fourth, conclusion
The method identifies and evaluates the cold resistance of 18 parts of rice germplasm resources in the bud stage. And (3) screening 6 key indexes of germination rate, germination vigor, germination index, seed germination coefficient, average germination time and seedling rate from the 7 measured single indexes by using statistical methods such as stepwise regression, principal component analysis and the like, establishing an optimal regression equation, and being used for rapid identification and prediction of cold tolerance of rice germplasm resources in the germination period. 2 parts of extremely cold-resistant germplasm in the bud stage are obtained by utilizing the comprehensive evaluation value D, and materials and bases are provided for screening and identifying rice germplasm resources and breeding and popularization of cold-resistant varieties.
The present invention has been described in detail above. It will be apparent to those skilled in the art that the invention can be practiced in a wide range of equivalent parameters, concentrations, and conditions without departing from the spirit and scope of the invention and without undue experimentation. While the invention has been described with reference to specific embodiments, it will be appreciated that the invention can be further modified. In general, this application is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the invention and including such departures from the present disclosure as come within known or customary practice within the art to which the invention pertains. The use of some of the essential features is possible within the scope of the claims attached below.
Claims (10)
1. A method for identifying cold resistance of rice in a germination stage comprises the following steps:
(A1) taking 7 indexes of germination rate, germination vigor, germination index, seed germination index, average germination time, germination coefficient and seedling rate as evaluation indexes of cold resistance in a germination period, respectively carrying out low-temperature treatment on a plurality of test rice varieties, and detecting the 7 indexes;
(A2) performing principal component analysis on the 7 indexes of each variety of rice measured in (a 1);
(A3) for each of the principal components obtained in (a2), a membership function value u (X) was calculated as followsj,i) And a weight Wj；
u(Xj,i)＝(Xj,i-Xj,min)/(Xj,max-Xj,min) (ii) a j is 1, 2, …, n; n is a positive integer greater than or equal to 2;
wherein u (X)j,i) The membership function value of the jth main component of the ith variety is expressed; xj,iShowing the principal component value, X, of the jth principal component of the ith varietyj,maxAnd Xj,minRespectively represents the jth main component in all the test waterMaximum and minimum values of principal component values in rice varieties;
wherein, WjRepresents the importance degree, namely the weight, of the jth principal component in all principal components; pjRepresenting the contribution rate of the jth principal component obtained by principal component analysis;
(A4) the membership function value u (X) obtained in (A3)j,i) And a weight WjRespectively calculating the comprehensive cold resistance index D value of each variety of rice according to the following formula, wherein the larger the D value is, the stronger the cold resistance in the bud stage is;
2. The method of claim 1, wherein: in the step (a1), the 7 indexes are detected according to the following formula:
germination rate (%) (number of seeds to be germinated/total number of seeds) × 100;
germination vigor (%) × 100 (number of seeds germinated in the first 4 days/total number of seeds);
germination index ═ Σ (Gt/Dt); wherein Gt is the germination number of the t day; dt is the t-th day of the germination experiment;
seed germination index is 1.00 xnd2+0.75×nd4+0.50×nd6+0.25×nd8(ii) a Therein, nd2、nd4、nd6、nd8Germination rates of 2d, 4d, 6d and 8d, respectively;
average germination time ═ G1T1+G2T2+……+GnTn)/(G1+G2+……+Gn) (ii) a Wherein Tn is the number of germination days, and Gn is the number of germination seeds per day corresponding to Tn;
germination coefficient is germination rate/average germination time;
the seedling formation rate (%) × 100 (number of surviving seedlings/total number of germinated seeds).
3. The method according to claim 1 or 2, characterized in that: in the step (A2), when principal component analysis is performed on the 7 indexes of each variety of rice, the principal component analysis is performed according to a principal component extraction standard that the characteristic value is greater than 1 and the cumulative contribution rate is greater than or equal to 80%.
4. The method of claim 3, wherein: in the step (a2), when principal component analysis is performed on the 7 indexes of each variety of rice, 2 principal components are obtained in total, and the corresponding feature vectors are respectively:
CI1＝0.429PI+0.426GC+0.418GR-0.418MGT+0.415GI+0.336GP-0.008SR；
CI2＝0.001PI-0.033GC+0.043GR+0.055MGT+0.076GI-0.014GP+0.994SR；
wherein, CI1Representing a first principal component value; CI2Representing a second principal component value; PI represents a seed germination index; GC represents the germination coefficient; GR represents the germination rate; MGT means mean time to germination; GI means germination index; GP represents germination vigour; SR represents the seedling rate.
5. Use of the method of any one of claims 1 to 4 in any one of:
p1, screening varieties with relatively strong cold resistance in the bud stage from a plurality of rice varieties;
p2, comparing the cold resistance of different rice varieties in the bud stage.
6. A method for identifying cold resistance of rice in a germination stage comprises the following steps:
(B1) carrying out low-temperature treatment on the rice to be detected, and detecting a germination index, a seedling rate, average germination time, a seed germination index, a germination rate and germination vigor;
(B2) calculating the comprehensive cold resistance index D 'value of the rice to be detected according to the following formula, wherein the larger the D' value is, the stronger the cold resistance in the bud stage is;
d' value 0.592+0.090GI +0.123SR-0.075MGT +0.086PI +0.099GR +0.054 GP;
wherein GI represents germination index; SR represents the seedling rate; MGT means mean time to germination; PI represents a seed germination index; GR represents the germination rate; GP represents the germination vigour.
7. Use of the method of claim 6 in any one of:
p1, screening varieties with relatively strong cold resistance in the bud stage from a plurality of rice varieties;
p2, comparing the cold resistance of different rice varieties in the bud stage.
8. The germination rate, the germination vigor, the germination index, the seed germination index, the average germination time, the germination coefficient and the seedling rate are used as evaluation indexes for identifying the cold resistance of the rice in the germination period.
9. The germination index, the seedling rate, the average germination time, the seed germination index, the germination rate and the germination potential are used as evaluation indexes for identifying the cold resistance of the rice in the germination period.
10. A method for classifying rice germplasm resources into groups according to cold resistance in a bud stage comprises the following steps:
(C1) performing cold tolerance identification on all rice varieties to be subjected to cluster division by adopting the method of any one of claims 1 to 4 so as to obtain comprehensive cold tolerance index D values of all the rice varieties; or
Performing cold tolerance identification on all rice varieties to be subjected to cluster division by adopting the method of claim 6 so as to obtain the comprehensive cold tolerance index D' values of all the rice varieties;
(C2) and (4) performing cluster analysis according to the obtained comprehensive cold-resistance index D value or the comprehensive cold-resistance index D' value of (C1), thereby dividing all rice varieties into different groups.
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| AU2020100624A4 (en) * | 2019-06-04 | 2020-06-04 | Institute Of Cotton Research Of The Chinese Academy Of Agricultural Sciences | Method for screening cold-resistant cotton varieties and application thereof |
| CN111386790A (en) * | 2020-04-24 | 2020-07-10 | 黑龙江省农业科学院耕作栽培研究所 | Method for identifying low-temperature germination capacity of direct-seeded rice in cold region |
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| AU2020100624A4 (en) * | 2019-06-04 | 2020-06-04 | Institute Of Cotton Research Of The Chinese Academy Of Agricultural Sciences | Method for screening cold-resistant cotton varieties and application thereof |
| CN111386790A (en) * | 2020-04-24 | 2020-07-10 | 黑龙江省农业科学院耕作栽培研究所 | Method for identifying low-temperature germination capacity of direct-seeded rice in cold region |
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