A method for evaluating the germination performance of polygonatum sibiricum seeds

Abstract

The present invention relates to the field of agricultural technology, and in particular to a method for evaluating the germination performance of polygonatum cyrtonema seeds. The method provided by the present invention uses the individual index values ​​of polygonatum cyrtonema seeds as germination performance evaluation indexes, combines principal component analysis and membership function methods to grade different polygonatum cyrtonema seeds germination performances, sets the simulated germination performance comprehensive value as a dependent variable, and each individual index as an independent variable, constructs a mathematical model for evaluating the germination performance of polygonatum cyrtonema seeds, and can quickly and accurately screen and identify the germination performance of polygonatum cyrtonema seeds according to the germination performance grade classification standard and the mathematical model for evaluating the germination performance of polygonatum cyrtonema seeds, providing a theoretical and technical basis for the breeding of excellent varieties of polygonatum cyrtonema germination performance.

Description

Technical Field

[0001] The invention relates to the technical field of agriculture, and in particular to a method for evaluating the germination performance of polygonatum cyrtonema seeds. Background Art

[0002] Polygonatum sibiricum Red is a perennial herbaceous plant of the genus Polygonatum in the Liliaceae family. It has important medicinal value. The study of its seed germination performance is of key significance for the cultivation and resource utilization of Polygonatum sibiricum. However, the long dormancy characteristics and low germination rate of Polygonatum sibiricum seeds are one of the key factors limiting its efficient breeding and large-scale planting. A deep understanding of the germination performance of Polygonatum sibiricum seeds is crucial for breeding excellent varieties, optimizing cultivation techniques, and improving the overall benefits of the Polygonatum sibiricum industry.

[0003] In addition, Polygonatum sibiricum seeds have a comprehensive dormancy phenomenon, and their germination is a complex physiological and biochemical change process, involving multiple factors such as mechanical obstacles, regulation of hormone balance, energy substance conversion, and physiological after-ripening of embryos. The traditional evaluation method uses a single indicator, such as germination rate, germination time, etc. This method ignores the complexity and diversity of seed germination and growth, lacks in-depth research and comprehensive consideration of the relationship between different indicators, and thus it is difficult to accurately and comprehensively evaluate the germination performance of Polygonatum sibiricum seeds.

[0004] Therefore, it is crucial to construct a comprehensive and accurate method for evaluating the germination performance of Polygonatum cyrtonema seeds. Summary of the invention

[0005] In order to gain a deeper understanding of the germination performance of polygonatum sibiricum seeds, the present invention provides a method for evaluating the germination performance of polygonatum sibiricum seeds. The germination performance evaluation method provided by the present invention is scientific, accurate, comprehensive and objective, and not only provides germplasm resources and theoretical and technical support for the breeding of new varieties with excellent germination performance of polygonatum sibiricum and related high-yield cultivation, but also provides a solid theoretical basis and practical guidance for the sustainable development of the polygonatum sibiricum industry.

[0006] A method for evaluating the germination performance of polygonatum sibiricum seeds, comprising the following steps:

[0007] Determine each single index of Polygonatum cyrtonema seeds to obtain each single index value; each single index includes three categories, namely, phenotypic characteristic index, germination characteristic index and physiological and biochemical index;

[0008] Performing principal component analysis on the individual index values ​​to obtain the characteristic value, contribution rate and cumulative contribution rate of the principal component factors, extracting the key principal component factors according to the characteristic value or cumulative contribution rate, and obtaining the comprehensive index coefficient of each key principal component factor;

[0009] The DPS data processing software was used to standardize the values ​​of each single index to obtain the standardized raw data, and then the standardized raw data and the coefficients of the comprehensive indexes of each principal component were multiplied to calculate the comprehensive index value of each key principal component factor, and then the theoretical germination performance comprehensive value was obtained based on the membership function and the comprehensive index value of each key principal component factor;

[0010] The theoretical germination performance comprehensive values ​​were clustered and statistically analyzed to obtain the germination performance grade classification standard;

[0011] The significance value of each single index was obtained by multivariate regression analysis, key indexes were screened out according to the significance value, and a mathematical model for evaluating the germination performance of Polygonatum cyrtonema seeds was constructed using the key indexes.

[0012] The germination performance of Polygonatum cyrtonema seeds was evaluated according to the germination performance grade classification standard and the mathematical model for evaluating the germination performance of Polygonatum cyrtonema seeds.

[0013] The method provided by the present invention uses each single index value as a germination performance evaluation index, comprehensively considers the complex influence of different single indexes on the germination performance of polygonatum cyrtonema seeds, and then combines the principal component analysis method and the membership function method and other steps to classify the germination performance of different polygonatum cyrtonema seeds, obtains the germination performance classification standard, sets the simulated germination performance comprehensive value as the dependent variable, and each single index is used as an independent variable to construct a polygonatum cyrtonema seed germination performance evaluation mathematical model, and according to the germination performance classification standard and the polygonatum cyrtonema seed germination performance, realizes a comprehensive and accurate evaluation of the polygonatum cyrtonema seed germination performance, can quickly and accurately screen and identify the germination performance of polygonatum cyrtonema seeds, and provides a theoretical and technical basis for the selection and breeding of excellent varieties of polygonatum cyrtonema germination performance. The germination performance classification standard and the polygonatum cyrtonema seed germination performance evaluation mathematical model constructed by the present invention can be reused many times, have good stability, and when it is necessary to test the germination performance of new polygonatum cyrtonema seeds, the germination performance classification standard and the polygonatum cyrtonema seed germination performance evaluation mathematical model constructed by the present invention can be directly cited, which saves time and effort, and has high accuracy.

[0014] Furthermore, the phenotypic characteristic indicators are thousand-grain weight, grain length, grain width, grain thickness, water absorption rate and embryo rate.

[0015] Furthermore, the germination characteristic indicators are germination potential, germination index, germination rate and mildew rate.

[0016] Furthermore, the physiological and biochemical indicators are mildew rate, abscisic acid, gibberellin, starch, soluble sugar, β-mannanase and β-galactosidase.

[0017] The Polygonatum sibiricum seeds selected in the present invention have a comprehensive dormancy phenomenon, and their germination is a complex physiological and biochemical change process, involving multiple factors such as mechanical obstruction, regulation of hormone balance, energy material conversion, and physiological after-ripening of the embryo. Microscopic structural tissue observation in the prior art shows that the Polygonatum sibiricum embryo is covered by the endosperm and seed coat with small cell gaps and thick cell walls, and has high mechanical strength. The growth of the embryonic axis during its seed germination is difficult to break through the seed coat and endosperm tissue. Therefore, the weakening of the mechanical obstruction of the endosperm and seed coat is a key factor in the speed of Polygonatum sibiricum seed germination. Other studies have shown that changes in the activity of cell wall degrading enzymes such as β-mannanase and β-galactosidase are the main factors that restrict the weakening of the endosperm and the removal of mechanical obstacles. In the process of dormancy release, the material metabolism, enzyme activity, and hormone balance inside the seeds will change significantly. For example, the decomposition and conversion of storage substances such as starch and soluble sugars provide energy and material basis for seed germination; changes in hormones such as gibberellins and abscisic acid play a key role in regulating seed dormancy and germination. In summary, the present invention found that 16 types of physiological and biochemical indicators that are critical in the germination process of Polygonatum cyrtonema seeds can be used to evaluate the germination performance of Polygonatum cyrtonema seeds.

[0018] Furthermore, the principal component factors are divided into a first principal component, a second principal component, a third principal component and a fourth principal component.

[0019] The first main component includes germination rate, starch, soluble sugar, gibberellin, β-mannanase and β-galactosidase.

[0020] The second principal components include grain width, thousand-grain weight, grain thickness, grain length and grain thickness.

[0021] The third principal component includes water absorption rate, embryo rate, grain width, germination potential and thousand-grain weight.

[0022] The fourth principal component includes embryo rate, grain width, water absorption rate, germination potential, germination index and abscisic acid.

[0023] Furthermore, the germination performance grade classification standards are as follows: Class I high germination type, theoretical germination performance comprehensive value ≥ 0.83; Class II medium germination type, 0.54≤theoretical germination performance comprehensive value ≤ 0.83; Class III low germination type, 0.10≤theoretical germination performance comprehensive value ≤ 0.54.

[0024] Furthermore, the method for constructing a mathematical model for evaluating the germination performance of Polygonatum cyrtonema seeds is as follows:

[0025] The comprehensive value of simulated germination performance was used as the dependent variable, and the key indicators were used as the independent variables. The key indicators were 1000-grain weight, grain length, grain width, grain thickness, embryo rate, germination index, germination rate, relative coefficient of abscisic acid, relative coefficient of starch, and relative coefficient of β-galactosidase.

[0026] The equation for constructing the mathematical model for evaluating the germination performance of Polygonatum cyrtonema seeds is:

[0027] B n =-0.484+0.003X 1 +0.041X 2 +0.032X 3 +0.078X 4 +0.467X 5 +0.009X 8 +0.002X 9 -0

[0028] .07X 11 -0.10X 13 +0.0355X 16 Where X 1 : Thousand-grain weight; X 2 : Grain length; X 3 : Grain width; X 4 : Grain thickness; X 5 : Embryo rate; X 8 : Germination index; X 9 : germination rate; X 11 : Abscisic acid relative coefficient; X 13 : starch relative coefficient; X 16 : β-galactosidase relative coefficient, B n is the comprehensive value of simulated germination performance;

[0029] The comprehensive value of simulated germination performance was compared with the germination performance grade classification standard to evaluate the germination performance of Polygonatum cyrtonema seeds.

[0030] Furthermore, the calculation formula of the theoretical germination performance comprehensive value C is:

[0031] C=∑ p p＝1 (W p ×μ(X i )), where C represents the comprehensive value of theoretical germination performance, W p represents the weight of extracting the pth key principal component factor, μ(X i ) represents the membership function value of each key principal component factor.

[0032] Furthermore, the weight W of the key principal component factor p The calculation formula is:

[0033] W p =λ p / ∑ p p＝1 λ p , where W pRepresents the weight of extracting the pth key principal component factor; λ p Indicates the contribution rate corresponding to the extracted pth principal component factor.

[0034] Furthermore, the calculation formula of the membership function value of each polygonatum seed variety is:

[0035] μ(X i )=(X i -X min ) / (X max -X min ), where X min Indicates the minimum value of the comprehensive index value of the principal component factor, X max Indicates the maximum value of the comprehensive index value of the main component factor; X i Represents the comprehensive index value of the i-th Polygonatum sibiricum seed variety.

[0036] Compared with the prior art, the present invention has the following beneficial effects:

[0037] The present invention determines the three types of indicators of seed phenotypic characteristics, germination characteristics, and related physiological and biochemical parameters, performs operations such as principal component analysis, constructs a grading standard for the germination performance of polygonatum seeds and a mathematical model for evaluating the germination performance of polygonatum seeds, clarifies the correlation with changes in the internal physiological processes of polygonatum seeds, and realizes a comprehensive and accurate evaluation of the germination performance of polygonatum seeds. The evaluation system (germination performance grading standard and mathematical model for evaluating the germination performance of polygonatum seeds) provided by the present invention can quickly and accurately screen and identify the germination performance of polygonatum seeds, which can not only provide germplasm resources and theoretical and technical support for the breeding of new varieties with excellent germination performance of polygonatum and related high-yield cultivation, but also provide a solid theoretical basis and practical guidance for the sustainable development of the polygonatum industry. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. 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 creative work.

[0039] Figure 1 Correlation analysis of germination indicators of different Polygonatum cyrtonema germplasm resources; Note: *, **, *** represent 5%, 1%, 0.1% significance levels, respectively.

[0040] Figure 2 This is a clustering dendrogram of the germination performance of different Polygonatum cyrtonema germplasm resources. DETAILED DESCRIPTION

[0041] The specific embodiments of the present invention are described in detail below, but it should be understood that the protection scope of the present invention is not limited by the specific embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without creative work belong to the scope of protection of the present invention. The experimental methods described in the embodiments of the present invention are conventional methods unless otherwise specified, and the materials, reagents, etc. used in the following embodiments can be obtained from commercial channels unless otherwise specified.

[0042] Example 1

[0043] A method for evaluating the germination performance of polygonatum sibiricum seeds, comprising the following steps:

[0044] 1.1 Experimental Materials:

[0045] The experiment was conducted at the Institute of Traditional Chinese Medicine of Henan Academy of Agricultural Sciences. 18 samples of Polygonatum cyrtonema collected in Henan, Sichuan, Jiangsu, Yunnan and other places were selected as experimental materials, as shown in Table 1. The collected Polygonatum cyrtonema fruits were fermented, rubbed and rinsed to obtain seeds. After the seeds were dried in the shade, the seeds with uniform size and fullness were selected for germination test.

[0046] Table 1 Numbers of tested Polygonatum cyrtonema germplasm resources

[0047]

[0048]

[0049] 1.2 Experimental treatment

[0050] Prepare dry, plump, mildew-free and uniform-sized Polygonatum sibiricum seeds. 2 O 2 Disinfect for 20 minutes, rinse thoroughly with distilled water 3 times, soak in distilled water for 24 hours, rinse again 3 times, dry the surface moisture, put it in a germination box covered with sterile gauze, and place it in a light incubator. The temperature in the incubator is set to 25°C, the light intensity is 2500LX, the photoperiod is 12 hours of light and 12 hours of darkness, the ambient humidity is 70%, replenish water in time, keep the gauze moist, and repeat three times for each sample.

[0051] 1.3 18 accessions of Polygonatum cyrtonema collected from different regions were used as the Polygonatum cyrtonema seeds to be evaluated, and the individual indicators of the Polygonatum cyrtonema seeds to be evaluated were measured to obtain the values ​​of the individual indicators; the individual indicators include three categories, namely, phenotypic characteristic indicators, germination characteristic indicators and physiological and biochemical indicators. Among them, the phenotypic characteristic indicators include 1000-grain weight, grain length, grain width, grain thickness, water absorption rate and embryo rate, the germination characteristic indicators include germination potential, germination index, germination rate and mildew rate, and the physiological and biochemical indicators include mildew rate, abscisic acid, gibberellin, starch, soluble sugar, β-mannanase and β-galactosidase.

[0052] In order to improve the accuracy, three parallel experiments were conducted on the treated Polygonatum cyrtonema seeds to be evaluated. The test methods for the 16 indicators are as follows:

[0053] a. Use electronic digital display vernier calipers to measure the grain length, width and thickness of Polygonatum cyrtonema germplasm. Measure the embryo length and endosperm length under a stereo microscope, and calculate the embryo rate = (embryo length / seed length) × 100%. Select 500 grains and weigh the fresh weight of 1,000 grains using a 1 / 1000 scale and record. Set up 3 biological replicates.

[0054] b. Observe the number of Polygonatum cyrtonema germplasm germination and the number of seeds moldy every 10 days. The germination period is set at 60 days, and the germination characteristics germination rate, germination potential, germination index and moldy rate are statistically calculated.

[0055] Germination rate (%) = normal germination number within 60 days / total number of test seeds × 100%.

[0056] Germination potential (%) = normal germination number within 30 days / total number of test seeds × 100%.

[0057] Germination index = ∑Gt / Dt (Gt is the number of germinations after t days of germination, and Dt is the corresponding number of germination days).

[0058] Mildew rate (%) = number of mildewed seeds within 60 days / total number of test seeds × 100%.

[0059] c. After soaking for 24 hours and germination for 20 days, randomly select 20 full seeds, absorb the surface moisture of the seeds with absorbent paper and weigh them. Calculate the water absorption rate of seeds, as follows: Water absorption rate (%) = [(W t -W 0 ) / W 0 ]×100, where W t W is the mass of seeds after 20 days of germination; 0 It refers to the quality of seeds after soaking for 24 hours.

[0060] d. After 24 h of soaking and 20 days of germination, 20 full seeds were randomly selected and ground thoroughly in liquid nitrogen. The starch and soluble sugar contents were determined by anthrone colorimetry. β-mannanase was determined by referring to the 3,5-dinitrosalicylic acid method (DNS). β-galactosidase activity was determined by referring to the method of Hruba and Itail. The abscisic acid content and gibberellin content were determined using a kit (Suzhou Keming Biotechnology Co., Ltd., Suzhou) according to the instructions.

[0061] 1.4 Perform principal component analysis on the individual index values ​​to obtain the characteristic value, contribution rate and cumulative contribution rate of the principal component factors, extract key principal component factors according to the criterion that the characteristic value is greater than 1 or the cumulative contribution rate is greater than 90%, and obtain the comprehensive index coefficient of each key principal component factor; use DPS data processing software to standardize the individual index values ​​to obtain the standardized original data, and then multiply the standardized original data and the comprehensive index coefficient of each key principal component factor to calculate the comprehensive index value of each key principal component factor, and then obtain the germination performance comprehensive value based on the membership function and the comprehensive index value of each key principal component factor; cluster the first germination performance comprehensive value to obtain the germination performance grade classification standard; obtain the P value of each individual index according to the multivariate regression analysis, take each individual index with a P value less than 0.05 as the key index, and use the key index to construct a mathematical model for evaluating the germination performance of polygonatum seeds; evaluate the germination performance of polygonatum seeds according to the germination performance grade classification standard and the mathematical model for evaluating the germination performance of polygonatum seeds. The data statistical method includes the following steps:

[0062] (1) Calculate the relative coefficient (γ) of each individual physiological index of each variety = measured value after 20 days of germination / measured value after 24 hours of seed soaking;

[0063] (2) Principal component analysis: extract the principal components based on the criterion that the extracted feature value is greater than 1 or the cumulative contribution rate is greater than 90%;

[0064] (3) Use the membership function to standardize the comprehensive index values ​​of each variety on the extracted principal components: μ(X i )=(X i -X min ) / (X max -X min ); i = 1, 2, 3, ..., n; where X min Indicates the minimum value of the comprehensive index value of the principal component factor, X max Indicates the maximum value of the comprehensive index value of the principal component factor, X i represents the comprehensive index value of the principal component factor of the i-th Polygonatum cyrtonema seed variety;

[0065] (4)W p =λ p / ∑ p p＝1 λ p ; W p Represents the weight of extracting the pth key principal component factor; λ p Indicates the contribution rate corresponding to the extracted main component;

[0066] (5) C = ∑ p p＝1 (W p ×μ(X i )); C represents the comprehensive value of theoretical seed germination performance;

[0067] (6) Cluster statistics were performed using the C value to divide the germination performance levels.

[0068] 2 Results and analysis

[0069] 2.1 Analysis of genetic variation of related indicators of Polygonatum cyrtonema seed germination

[0070] Table 2 Variation of germination-related indicators of different Polygonatum cyrtonema germplasm resources

[0071]

[0072]

[0073] Note: X 1 : Thousand-grain weight; X 2 : Grain length; X 3 : Grain width; X 4 : Grain thickness; X 5 : Embryo rate; X 6 : Water absorption rate; X 7 : Germination potential; X 8 : Germination index; X 9 : germination rate; X 10 : Mildew rate; X 11 : Abscisic acid relative coefficient; X 12 : Gibberellin relative coefficient; X 13 : starch relative coefficient; X 14 : Relative coefficient of soluble sugar; X 15 : β-mannanase relative coefficient; X 16 : Relative coefficient of β-galactosidase.

[0074] As shown in Table 2, 16 indicators were selected for determination in this test, including 6 morphological characteristics related indicators (1000-grain weight, grain length, grain width, grain thickness, water absorption rate and embryo rate), 4 germination related indicators (germination potential, germination index, germination rate and mildew rate) and 6 physiological and biochemical related indicators (abscisic acid relative coefficient, gibberellin relative coefficient, starch relative coefficient, soluble sugar relative coefficient, β-mannanase relative coefficient and β-galactosidase relative coefficient). The results showed that the same indicator had differences among varieties, and the coefficient of variation of each indicator was significantly different. Among them, the coefficient of variation of germination potential was the largest, followed by germination index, germination rate and soluble sugar, and the coefficient of variation of grain width was the smallest, with a range of 9.54%-206.95%, and a large range of variation. It is too one-sided and unreliable to directly evaluate the germination performance of Polygonatum cyrtonema based on a single indicator. Therefore, it is necessary to further analyze and evaluate the relationship (correlation) between the indicators.

[0075] 2.2 Correlation analysis between related indicators of Polygonatum cyrtonema seed germination

[0076] like Figure 1 As shown in the results, there are different degrees of positive or negative correlations between the indicators. The germination rate of Polygonatum cyrtonema seeds is highly positively correlated with germination potential, germination index, gibberellin, soluble sugar, β-mannanase and β-galactosidase (R>0.8, P<0.001), with correlation coefficients (R) of 0.84, 0.89, 0.95, 0.96, 0.93 and 0.88, respectively; it is highly negatively correlated with mildew rate, abscisic acid and starch (R>0.8, P<0.001), with correlation coefficients of -0.83, -0.90 and -0.95, respectively. In addition, there are different degrees of positive or negative correlations between other indicators. It can be seen that there are complex correlations between the indicators, and the data information is cross-over and overlapped. It is still necessary to use multivariate analysis methods to conduct a comprehensive evaluation of germination characteristics.

[0077] 2.3 Principal component analysis of related indicators of Polygonatum cyrtonema seed germination

[0078] As shown in Table 3, four key principal component factors were extracted according to the criterion that the cumulative contribution rate of the principal component factors was greater than 90%, and the 16 individual germination characteristic related indicators were converted into four new independent key principal component factors, represented by principal component 1 [C(1)], principal component 2 [C(2)], principal component 3 [C(3)] and principal component 4 [C(4)], respectively. Their eigenvalues ​​were 9.52, 2.99, 1.17 and 1.02, respectively, and their contribution rates were 59.47%, 18.70%, 7.33% and 6.40%, respectively. The total cumulative contribution rate reached 91.9%, which fully contained most of the information on the germination characteristics of Polygonatum cyrtonema seeds, indicating that the four key principal component factors had relatively comprehensive information representativeness. In addition, from the absolute value of the comprehensive index factor coefficient of each key principal component factor, it can be seen that the first principal component mainly includes germination characteristic indicators such as germination rate, energy synthesis indicators such as starch and soluble sugar, hormone-related indicators such as gibberellin, and cell wall lysis-related indicators such as β-mannanase and β-galactosidase; the second, third and third principal components are mainly morphological characteristics related indicators. The results show that the comprehensive indicators of the above four independent key principal component factors can fully reflect the information contained in the original 16 germination performance related indicators, and can be used for comprehensive evaluation and analysis.

[0079] Table 3 Coefficients and contribution rates of the principal component comprehensive indicators of each key principal component factor

[0080]

[0081]

[0082] Note: X 1 : Thousand-grain weight; X 2 : Grain length; X 3 : Grain width; X 4 : Grain thickness; X 5 : Embryo rate; X 6 : Water absorption rate; X 7 : Germination potential; X 8 : Germination index; X 9 : germination rate; X 10 : Mildew rate; X 11 : Abscisic acid relative coefficient; X 12 : Gibberellin relative coefficient; X 13 : starch relative coefficient; X 14 : Relative coefficient of soluble sugar; X 15 : β-mannanase relative coefficient; X 16 : Relative coefficient of β-galactosidase.

[0083] 2.4 Comprehensive evaluation of germination performance of different Polygonatum cyrtonema germplasm resources

[0084] The DPSv18.10 data processing software was used to standardize the values ​​of each single index. The comprehensive index coefficient of each key principal component factor was obtained by principal component analysis and the corresponding product of the standardized index value was used to evaluate the comprehensive index value [CI(x)] of the four key principal component factors of each Polygonatum germplasm. The membership function value μ(x) of the comprehensive index of the four key principal component factors of each material was calculated according to formula (3). The weights of the comprehensive index of the four key principal component factors were calculated according to formula (4), which were 0.65, 0.20, 0.08 and 0.07 respectively. The theoretical germination performance comprehensive value (C) of each material was calculated using formula (5), which was the germination performance. The germination performance of each material was ranked according to the C value. The larger the C value, the higher the theoretical germination performance of the material. As shown in Table 4, the comprehensive value (C) of the theoretical germination performance of 18 Polygonatum cyrtonema germplasm resources ranges from 0.1 to 0.83. By sorting the C values ​​of each Polygonatum cyrtonema material, the germination performance of different Polygonatum cyrtonema germplasm resources is in the following order: DJ2>DJ1>HJ4>HJ5>HJ2>HJ3>DH5>DJ3 / JH4>JH3>DH3>JH2>JH5>DH4>HJ1>JH1>DH2>DH1.

[0085] Table 4 Comprehensive index values, membership function values, weights and theoretical germination performance comprehensive values ​​of different Polygonatum cyrtonema seeds

[0086]

[0087] 2.5 Cluster analysis of germination performance of different Polygonatum cyrtonema germplasm resources

[0088] In order to further divide and classify the germination performance of different Polygonatum cyrtonema germplasms, the European longest distance method was used to conduct a systematic germination performance level cluster analysis on the theoretical germination performance comprehensive value C value of 18 Polygonatum cyrtonema germplasms. Figure 2 As shown in the figure, after data standardization, at the threshold of Euclidean distance of 0.07, the 18 Polygonatum cyrtonema germplasms can be clearly divided into three categories and levels, namely, Class I level with one resource (C≥0.83), including DJ2, which has weak dormancy, high germination rate and germination rate; Class II level with three resources (0.54≤C≤0.83), including DJ1, HJ4 and HJ5, which has moderate dormancy, high germination rate and germination rate; Class III level with 14 varieties (0.10≤C≤0.54), including HJ2, HJ3, DH5, DJ3, JH4, JH3, DH3, JH2, JH5, DH4, HJ1, JH1, DH2 and DH1, which has strong dormancy, low germination rate and germination rate.

[0089] 2.6 Grey correlation analysis between germination performance related indicators of different Polygonatum cyrtonema germplasm resources and the theoretical germination performance comprehensive value C value

[0090] In order to deeply explore the germination performance of different Polygonatum cyrtonema germplasm resources, the grey correlation analysis method was used to systematically evaluate each single index and the theoretical germination performance comprehensive value (C), aiming to clarify the relative importance of each index in the evaluation of the germination performance of Polygonatum cyrtonema germplasm resources.

[0091] Table 5 Grey correlation analysis between individual indicators and theoretical germination performance comprehensive value C of different Polygonatum cyrtonema germplasm resources

[0092]

[0093]

[0094] Note: X 1 : Thousand-grain weight; X 2 : Grain length; X 3 : Grain width; X 4 : Grain thickness; X 5 : Embryo rate; X 6 : Water absorption rate; X 7 : Germination potential; X 8 : Germination index; X 9 : germination rate; X 10 : Mildew rate; X 11 : Abscisic acid relative coefficient; X 12 : Gibberellin relative coefficient; X 13 : starch relative coefficient; X 14 : Relative coefficient of soluble sugar; X 15 : β-mannanase relative coefficient; X 16 : Relative coefficient of β-galactosidase.

[0095] As shown in Table 5, among all the individual indicators, β-galactosidase has the closest correlation with the theoretical germination performance comprehensive value (C), and its correlation coefficient is as high as 0.80. This result shows that β-galactosidase occupies a crucial position in the evaluation of the germination performance of Polygonatum cyrtonema seeds. In addition to β-galactosidase, other indicators with a high correlation with the theoretical germination performance comprehensive value (C) are β-mannanase relative coefficient, soluble sugar, gibberellin, 1000-grain weight, grain length and grain thickness, with correlation coefficients of 0.76, 0.73, 0.69, 0.69, 0.68 and 0.67, respectively, all showing a strong correlation with the germination performance of Polygonatum cyrtonema seeds. In summary, these 7 indicators have a high correlation coefficient in the evaluation of the germination performance of Polygonatum cyrtonema seeds, especially β-galactosidase, which may be the key determinant for evaluating the germination performance of Polygonatum cyrtonema seeds. Therefore, in actual identification and evaluation, grading and variety breeding, these indicators can be used as the main reference to ensure the accuracy and effectiveness of the evaluation.

[0096] 2.7 Construction of mathematical model for evaluating germination performance of Polygonatum cyrtonema seeds

[0097] In order to deeply explore the specific relationship between the 16 individual indicators and the germination performance of Polygonatum cyrtonema seeds, and to improve the accuracy of the evaluation of the germination performance of Polygonatum cyrtonema seeds, the present invention adopts a multivariate stepwise regression analysis method to establish a mathematical model for germination performance evaluation. In this process, the simulated germination performance comprehensive value is set as the dependent variable, and each individual indicator is used as an independent variable to construct an optimal regression equation, aiming to predict and model the germination performance of Polygonatum cyrtonema. The obtained regression equation for the identification of the germination performance of Polygonatum cyrtonema seeds is: n =-0.484+0.003X 1 +0.041X 2 +0.032X 3 +0.078X 4 +0.467X 5 +0.009X 8 +0.002X 9 -0.07X 11 -0.10X 13 +0.0355X 16 ; The coefficient of determination of this equation is R 2 As high as 0.990, reaching the extremely significant level (P<0.0001), at the same time, the Durbin-Watson statistic d=2.22, indicating that no autocorrelation was detected in the sample data set, and the model was well constructed, further verifying the reliable explanatory power of the model. From this equation, it can be seen that among the 16 individual indicators, 10 have significant statistical correlations with the comprehensive value of simulated germination performance (P<0.05), X 1 : Thousand-grain weight; X 2 : Grain length; X 3 : Grain width; X 4 : Grain thickness; X 5 : Embryo rate; X 8 : Germination index; X 9 : germination rate; X 11 : Abscisic acid relative coefficient; X 13 : starch relative coefficient; X 16 : Relative coefficient of β-galactosidase.

[0098] 3 Conclusion

[0099] The present invention systematically analyzed the germination performance of Polygonatum cyrtonema seeds and found that 16 related indicators had significant genetic variation among different varieties, indicating that there was rich genetic diversity among germplasm resources. There was a complex correlation between the indicators, among which the germination rate was positively correlated with germination potential, germination index, gibberellin, soluble sugar, β-mannanase and β-galactosidase, and negatively correlated with mildew rate, abscisic acid and starch, highlighting the multi-factor comprehensive effect of germination performance. Four key principal component factors were extracted by principal component analysis, which included indicators such as germination characteristics, energy synthesis, hormone-related and cell wall lysis, respectively, which fully reflected the original indicator information and provided a basis for the comprehensive evaluation of the germination performance of Polygonatum cyrtonema seeds. Cluster analysis divided the germplasm resources into three levels. Grey correlation analysis showed that β-galactosidase was the key indicator for evaluating germination performance, and other highly correlated indicators included β-mannanase, soluble sugar and gibberellin. In addition, a mathematical model with high determination coefficient and reliable explanatory power was constructed, which can be used to predict and model the germination performance of Polygonatum cyrtonema. In summary, the present invention provides a scientific basis and technical support for the screening, utilization and variety breeding of Polygonatum cyrtonema germplasm resources.

[0100] Although preferred embodiments of the present invention have been described, additional changes and modifications may occur to these embodiments once those skilled in the art are aware of the basic inventive concepts.

[0101] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for evaluating the germination performance of Polygonatum cyrtonema seeds, characterized in that: The following steps are involved: Determine each single index of Polygonatum cyrtonema seeds to obtain each single index value; each single index includes three categories, namely, phenotypic characteristic index, germination characteristic index and physiological and biochemical index; Performing principal component analysis on the individual index values ​​to obtain the characteristic value, contribution rate and cumulative contribution rate of the principal component factors, extracting the key principal component factors according to the characteristic value or cumulative contribution rate, and obtaining the comprehensive index coefficient of each key principal component factor; The DPS data processing software was used to standardize the values ​​of each single index to obtain the standardized raw data, and then the standardized raw data and the coefficients of the comprehensive indexes of each principal component were multiplied to calculate the comprehensive index value of each key principal component factor, and then the theoretical germination performance comprehensive value was obtained based on the membership function and the comprehensive index value of each key principal component factor; The theoretical germination performance comprehensive values ​​were clustered and statistically analyzed to obtain the germination performance grade classification standard; The significance value of each single index was obtained by multivariate regression analysis, key indexes were screened out according to the significance value, and a mathematical model for evaluating the germination performance of Polygonatum cyrtonema seeds was constructed using the key indexes. The germination performance of Polygonatum cyrtonema seeds was evaluated according to the germination performance grade classification standard and the mathematical model for evaluating the germination performance of Polygonatum cyrtonema seeds.

2. The method for evaluating the germination performance of polygonatum seeds according to claim 1, characterized in that: The phenotypic characteristic indicators are thousand-grain weight, grain length, grain width, grain thickness, water absorption rate and embryo rate.

3. The method for evaluating the germination performance of polygonatum seeds according to claim 1, characterized in that: The germination characteristic indicators are germination potential, germination index, germination rate and mildew rate.

4. The method for evaluating the germination performance of polygonatum seeds according to claim 1, characterized in that: The physiological and biochemical indicators are mildew rate, abscisic acid, gibberellin, starch, soluble sugar, beta-mannanase and beta-galactosidase.

5. The method for evaluating the germination performance of polygonatum seeds according to claim 1, characterized in that: The principal component factors are the first principal component, the second principal component, the third principal component and the fourth principal component; The first main component includes germination rate, starch, soluble sugar, gibberellin, β-mannanase and β-galactosidase; The second principal component includes grain width, thousand-grain weight, grain thickness, grain length and grain thickness; The third principal component includes water absorption rate, embryo rate, grain width, germination potential and thousand-grain weight; The fourth principal component includes embryo rate, grain width, water absorption rate, germination potential, germination index and abscisic acid.

6. The method for evaluating the germination performance of polygonatum seeds according to claim 1, characterized in that: The germination performance grade classification standards are as follows: Class I high germination type, theoretical germination performance comprehensive value ≥ 0.83; Class II medium germination type, 0.54 ≤ theoretical germination performance comprehensive value ≤ 0.83; Class III low germination type, 0.10 ≤ theoretical germination performance comprehensive value ≤ 0.

54.

7. The method for evaluating the germination performance of polygonatum seeds according to claim 1, characterized in that: The method for constructing a mathematical model for evaluating the germination performance of Polygonatum cyrtonema seeds is as follows: The simulated germination performance comprehensive value was used as the dependent variable, and the key indicators were used as the independent variables. The key indicators were thousand-grain weight, grain length, grain width, grain thickness, embryo rate, germination index, germination rate, relative coefficient of abscisic acid, relative coefficient of starch, and relative coefficient of β-galactosidase. The equation for constructing the mathematical model for evaluating the germination performance of Polygonatum cyrtonema seeds is: B n =-0.484+0.003X1+0.041X2+0.032X3+0.078X4+0.467X5+0.009X8+0.002X9-0.07X 11 -0.10X 13 +0.0355X 16 ; In the formula, X1: thousand-grain weight; X2: grain length; X3: grain width; X4: grain thickness; X5: embryo rate; X8: germination index; X9: germination rate; X 11 : Abscisic acid relative coefficient; X 13 : starch relative coefficient; X 16 : β-galactosidase relative coefficient, B n is the comprehensive value of simulated germination performance; The comprehensive value of simulated germination performance was compared with the germination performance grade classification standard to evaluate the germination performance of Polygonatum cyrtonema seeds.

8. The method for evaluating the germination performance of polygonatum seeds according to claim 1, characterized in that: The calculation formula of the comprehensive value of the theoretical germination performance is: C=∑ p p＝1 (W p ×μ(X i )), where C represents the comprehensive value of theoretical germination performance, W p represents the weight of the pth key principal component factor, μ(X i ) represents the membership function value of each key principal component factor.

9. The method for evaluating the germination performance of polygonatum sibiricum seeds according to claim 8, characterized in that: The calculation formula of the weight of the key principal component factor is: W p =λ p / ∑ p p＝1 λ p , where W p Represents the weight of the pth key principal component factor; λ p Represents the contribution rate corresponding to the pth principal component factor.

10. The method for evaluating the germination performance of polygonatum cyrtonema seeds according to claim 8, characterized in that: The calculation formula of the membership function value is: μ(X i )=(X i -X min ) / (X max -X min ), where X min Indicates the minimum value of the comprehensive index value of the principal component factor, X max Indicates the maximum value of the comprehensive index value of the main component factor; X i Represents the comprehensive index value of the principal component factors of the i-th Polygonatum cyrtonema seed variety.

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