Method for identifying high-temperature resistance of soybeans in whole growth period and application of method

Abstract

The invention provides a method for identifying the high temperature resistance of soybeans in the whole growth period and application of the method. The method comprises the following steps: detecting physiological and biochemical indexes, agronomic characters and yield character characteristics in each growth and development period of soybean seeds sown under control treatment and high-temperature treatment, and counting correlation among the indexes; the method comprises the following steps: calculating a high-temperature-resistant coefficient responding to a high-temperature stress character, analyzing correlation among different indexes by using a significant difference high-temperature-resistant coefficient, and rating the high-temperature-resistant grade of the sown soybean according to a high-temperature-resistant membership function value and a clustering analysis result through standardization analysis of a principal component and a membership function. The method is applied to the cultivation of new high-temperature-resistant soybean varieties, and three high-temperature-resistant soybean varieties, namely Jiangxi bean No.1, Jiangxi bean No.1 and Tibetan bean No.1, are cultivated.

Description

Technical Field

[0001] This invention relates to the field of soybean germplasm resource evaluation and breeding. Specifically, it relates to the evaluation of heat-resistant soybean germplasm resources and variety selection. More specifically, it relates to the evaluation, discovery, and breeding of heat-resistant soybean germplasm throughout its entire growth cycle. Background Technology

[0002] Soybean (Glycine max (L.) Merr) originated in China and is an important grain and oil crop, as well as a major source of edible vegetable oil and plant protein. High temperature is a significant factor affecting the yield and stability of soybeans. It not only directly affects growth and development and yield but also indirectly influences various growth and development processes by altering physiological metabolism and water stress, thereby affecting yield and quality. For every 1°C increase in the global average temperature, soybean yield decreases by 3.1%. Particularly in soybean-producing areas of southern my country, influenced by the greenhouse effect and El Niño, extreme high temperatures occur frequently, with high temperatures and long durations of high-temperature stress. Summer soybeans are subjected to high-temperature stress throughout their entire growth period, severely impacting photosynthesis, emergence, branching, fertility, and pod formation, leading to significant yield reductions, underdeveloped grains, and decreased quality. This has become one of the major stress factors restricting the high-quality development of the soybean industry in southern China and even nationwide. To cope with the effects of prolonged high temperatures, breeding heat-resistant soybean varieties and promoting their production and application are the most effective measures to overcome the adverse effects of high temperatures on soybean production. Establishing a precise and efficient technical system for evaluating the heat resistance of soybeans throughout their entire growth cycle is key to discovering superior heat-resistant germplasm resources and then breeding heat-resistant soybean varieties. Summary of the Invention

[0003] The purpose of this invention is to provide a method for identifying the high-temperature resistance of soybeans throughout their entire growth period.

[0004] The method provided by this invention mainly includes two steps. Step (1) involves subjecting sown soybean seeds to high-temperature stress during their growth period, detecting physiological and biochemical indicators, agronomic traits, and yield characteristics of the control and high-temperature treatment at different growth and development stages, and analyzing the correlation between the indicators. Step (2) involves calculating the high-temperature tolerance coefficient of the high-temperature stress response traits, using the significant difference in the high-temperature tolerance coefficient to analyze the correlation between different indicators, performing principal component and membership function standardization analysis, and rating the high-temperature tolerance level of sown soybeans based on the high-temperature tolerance membership function value and cluster analysis results.

[0005] The soybean seeds in step (1) include one or more of the following: germplasm resources, local germplasm, local varieties, strains or varieties from various ecological zones;

[0006] The growth and development stages in step (1) include the seedling stage, flowering stage, pod-setting stage, grain-filling stage, and maturity and harvest stage. Specifically, the seedling stage corresponds to stage V2, the flowering stage corresponds to stage R2, the pod-setting stage corresponds to stage R4, and the maturity and harvest stage corresponds to stage R8.

[0007] The physiological and biochemical indicators in step (1) include chlorophyll content, pollen viability, and peroxidase POD activity;

[0008] The agronomic traits in step (1) include plant height, bottom pod height, number of effective branches, and number of nodes;

[0009] The yield traits in step (1) include the percentage of shriveled pods and the weight of 100 pods.

[0010] The temperature conditions for high temperature stress in step (2) are as follows: (1) Record the real-time field temperature every hour, and statistically analyze the highest temperature and effective accumulated temperature of the sampling / measurement index on the day, the previous five days and the previous ten days. The effective accumulated temperature is ∑(daily average temperature - baseline temperature), and the baseline temperature is 10℃; (2) The high temperature treatment conditions for seedling, flowering and pod-setting stages are: daily temperature ≥ 40℃, effective accumulated temperature ≥ 113℃·d 5 days before sampling, and effective accumulated temperature ≥ 230℃·d 10 days before sampling; (3) The high temperature conditions corresponding to the maturity and harvest period are: effective accumulated temperature ≥ 2367.9℃·d throughout the entire growth period.

[0011] In step (2), the high temperature resistance coefficient is the ratio of the phenotypic value under high temperature treatment conditions to the phenotypic value under control treatment conditions.

[0012] In step (2), the significance analysis is performed by using one-way ANOVA to screen for indicators that show significant differences under the control / high temperature treatment conditions.

[0013] In step (3), the correlation analysis is performed using Spearman correlation analysis to analyze the correlation between different indicators and screen out indicators with significant correlation.

[0014] In step (2), principal component analysis is performed by using the correlation matrix to extract principal components based on the criterion that the eigenvalue is greater than 1.

[0015] The membership function standardization analysis formula in step (2) is F(x) i )=(X i -X min ) / (X max -X min ); i=1, 2, 3,..., n;

[0016] Where X min and X max Let X represent the minimum and maximum scores on each principal component, respectively. iThis represents the principal component score.

[0017] The evaluation method for the high-temperature resistance of soybeans throughout its entire growth period in step (2) is (1) wp=λp / ∑ p p＝1 λp; wp represents the weight of the p-th principal component extracted; λp represents the eigenvalue corresponding to the extracted principal component; (2) C=∑ p p＝1 (wp×(Fx i (3) Perform Euclidean distance cluster analysis based on the C value, select an appropriate Euclidean distance to classify, and adjust the classification according to the size of the C value to classify the high temperature resistance level.

[0018] The heat resistance rating of soybean throughout its entire growth period is as follows: Grade V: ≥0.70; Grade IV: ≥0.60 and <0.70; Grade III: ≥0.51 and <0.60; Grade II: ≥0.45 and <0.51; Grade I: <0.45.

[0019] This invention also provides an application of a method for identifying the high-temperature tolerance of soybeans throughout their entire growth period in the breeding of high-temperature tolerant soybean varieties. Experiments conducted according to this invention demonstrate that, using the method provided by this invention, high-temperature tolerant soybean varieties such as Zhonggan 601 (Gan Shen Dou 20240002), Ganxia Dou 1 (Gan Shen Ding 20240004), and Jingyou Dou 1 (Gan Shen Dou 20240003) were screened and bred. Under conditions of effective accumulated temperature >2241.17℃·d and a maximum temperature of over 45℃ for 45 days in 2024, "Zhonggan 601" achieved a yield of 262.7 kg / mu, demonstrating a high yield level under extreme high-temperature conditions. Attached Figure Description

[0020] Figure 1 The results indicate that there are significant differences in various indicators among different soybean varieties in the control / high-temperature group. The significant differences in different indicators between the control / high-temperature group are represented by the following: A: SPAD (V2 stage); B: SPAD (R2 stage); C: SPAD (R4 stage); D: POD (V2 stage); E: POD (R2 stage); F: POD (R4 stage); G: Pollen viability; H: Pod shriveling rate / %; I: Plant height; J: Bottom pod height; K: Number of effective branches; L: Number of nodes; M: 100-seed weight.

[0021] Figure 2The study used Spearman correlation analysis to analyze the correlations between different indicators in the control / high-temperature group of different soybean varieties. Among them, SPAD (V2 stage) and effective branch number, SPAD (V2 stage) and node number, SPAD (R2 stage) and shriveled pod rate, POD enzyme (R2 stage) and pollen activity, and 100-grain weight were correlated with multiple indicators: SPAD (V2 stage), SPAD (R2 stage), effective branch number, and node number.

[0022] Figure 3 This indicates the results of cluster analysis using the Euclidean distance average linkage method. When the Euclidean distance is 10.0, the heat resistance of 32 soybean varieties can be roughly divided into 4 categories based on the C value. The darker the color, the more heat resistant the soybean, and vice versa.

[0023] Figure 4 Using heat-resistant germplasm as parents, we created a new high-quality, high-yield, and heat-resistant strain. Detailed Implementation

[0024] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0025] It should be noted that the embodiments described below are illustrative, and the methods used, unless otherwise specified, are conventional methods intended to provide further explanation of this application. The materials, reagents, etc., used are commercially available unless otherwise specified. Unless otherwise indicated, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.

[0026] It should be noted that the terminology used herein is for the purpose of describing particular implementations only and is not intended to limit the exemplary implementations according to this application; as used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise; furthermore, it should be understood that when the terms “comprising” and / or “including” are used in this specification, they indicate the presence of features, steps, operations, devices, components and / or combinations thereof.

[0027] Soybean Variety Resources: Gan Dou 10 (Gan Shen Dou 20170001), Gan Dou 11 (Gan Shen Dou 20190001), Gan Dou 12 (Gan Shen Dou 20190002), Gan Dou 15 (Gan Shen Dou 20210002), Gan Dou 16 (Gan Shen Dou 20220001), Zhong Dou 63 (Guo Shen Dou 20233006), Zhong Dou 41 (Guo Shen Dou 2013014), Zhong Dou 57 (Guo Shen Dou 20210082), Wan Dou 28 (Guo Shen Dou 2008004), Xu Dou 16 (Guo Shen Dou 2008004). The following soybean varieties have been approved: 2009020, Jidou 12 (National Approved Soybean 2001001), Heihe 45 (Heilongjiang Approved Soybean 2007013), Keshan 1 (National Approved Soybean 2009002), Zhonghuang 39 (National Approved Soybean 2013016), Youchun 1204 (National Approved Soybean 20170018), Xiangchun Soybean 26 (National Approved Soybean 2008024), and Tianlong 1 (National Approved Soybean 2008023). Information on these varieties can be found on the China Seed Industry Big Data Platform. The public can obtain seeds from the breeding units corresponding to the approved varieties.

[0028] Ganxia 2020-1, Jinggan 01-1, and Ganxia 2021-1 were the test materials for the 2022 Jiangxi Province Summer Soybean Variety Regional Trial. Relevant information can be found in the 2022 Jiangxi Province Major Crop Variety Trial Implementation Plan. Ganxia 2206, Ganxia 2215, and Ganxia 2216 were the test materials for the 2024 Jiangxi Province Summer Soybean Variety Regional Trial. Relevant information can be found in the 2024 Jiangxi Province Major Crop Variety Trial Implementation Plan. Ganxia 2204, Ganxia 2221, and Ganxia 2213 are new soybean lines created by the Jiangxi Academy of Agricultural Sciences. Seeds of these materials can be obtained from the Crop Research Institute of the Jiangxi Academy of Agricultural Sciences.

[0029] Brazil 11 is a superior soybean germplasm from abroad, recorded in the following literature: "Zhao Xianwei, Sun Liping, Li Suning, et al. Analysis of phosphorus absorption and utilization efficiency of spring soybean varieties and their backbone parents in Jiangxi Province, Journal of Plant Genetic Resources, 2022, 23(02): 541-552". Seeds can be obtained from the Crop Research Institute of Jiangxi Academy of Agricultural Sciences. Zheng 59 (ZDD24052), Youxian Brown Soybean (ZDD14586), Xuzhuang Black Soybean (ZDD08257), and Baoshan Soybean (ZDD17593) are soybean resources collected and preserved by the National Germplasm Resource Bank. Relevant information can be found on the China Crop Germplasm Information Network, and seeds can be obtained from the Institute of Crop Science of Chinese Academy of Agricultural Sciences.

[0030] Example 1: Method for Identifying the High Temperature Tolerance of Soybeans Throughout Their Growth Cycle

[0031] 1. Identification of high-temperature resistant staggered sowing and collection of phenotypic data

[0032] Utilizing the region's naturally high summer temperatures, the experimental site was located in an area with naturally high summer temperatures. Sowing was carried out every 10 days from mid-May to early August, with a row length of 2 meters, a row spacing of 0.4 meters, and a plant spacing of 10 centimeters. Based on the actual field temperature, the highest temperature and effective accumulated temperature of the sampling / measurement index were monitored on the day of sampling / measurement, the five days prior, and the ten days prior. Different agronomic traits and biochemical indicators of the control / high temperature at different growth stages were recorded. The control / high temperature data of each material at the same growth stage (V2, R2, R4, and R8 stages) were statistically analyzed.

[0033] Based on the actual field temperature at the experimental site, the highest temperature and effective accumulated temperature of the sampling / measurement index on the day of sampling / measurement, the five days prior, and the ten days prior were monitored. After confirming the significance of the control / high-temperature temperature, the main methods and evaluation criteria for the control / high-temperature treatment are as follows:

[0034] ① Record the real-time field temperature value every hour, and statistically analyze the highest temperature and effective accumulated temperature of the sampling / measurement index on the day, the previous five days and the previous ten days. The effective accumulated temperature is ∑(daily average temperature - baseline temperature), and the baseline temperature is 10℃; ② Select a specific temperature range as the control / high temperature treatment condition according to the measurement index.

[0035] ③ The pollen viability test control / high temperature treatment temperature ranges are as follows: Control treatment conditions: real-time sampling temperature range ≤32.2℃, effective accumulated temperature in the 5 days before sampling ≤118.5℃·d, effective accumulated temperature in the 10 days before sampling ≤226.8℃·d; High temperature treatment conditions: real-time sampling temperature range ≥46.8℃, effective accumulated temperature in the 5 days before sampling ≥119.3℃·d, effective accumulated temperature in the 10 days before sampling ≥230.4℃·d;

[0036] ④ The temperature ranges for chlorophyll content detection control / high-temperature treatment are as follows: Control treatment conditions: real-time sampling temperature range ≤29.1℃, effective accumulated temperature in the 5 days before sampling ≤81.6℃·d, effective accumulated temperature in the 10 days before sampling ≤161.7℃·d; High-temperature treatment conditions: real-time sampling temperature range ≥40.9℃, effective accumulated temperature in the 5 days before sampling ≥113.1℃·d, effective accumulated temperature in the 10 days before sampling ≥537.4℃·d;

[0037] ⑤ The temperature ranges for the peroxidase (POD) activity detection control / high-temperature treatment are as follows: Control treatment conditions: real-time sampling temperature range ≤38.6℃, effective accumulated temperature in the 5 days before sampling ≤110.6℃·d, effective accumulated temperature in the 10 days before sampling ≤230.0℃·d; High-temperature treatment conditions: real-time sampling temperature range ≥46.0℃, effective accumulated temperature in the 5 days before sampling ≥119.8℃·d, effective accumulated temperature in the 10 days before sampling ≥232.3℃·d.

[0038] ⑥ The temperature ranges for measuring agronomic and yield traits (control / high temperature treatment) are as follows: Control treatment conditions: effective accumulated temperature ≤ 2176.2℃·d throughout the growth period; High temperature treatment conditions: effective accumulated temperature ≥ 2367.9℃·d throughout the growth period.

[0039] Test method:

[0040] (1) Comparative analysis of the physiological and biochemical traits of materials at different stages after control / high-temperature treatment, including pollen viability detection, chlorophyll content and peroxidase (POD) activity, and comparative analysis of the differences in agronomic traits between control / high-temperature treated materials at harvest. The sampling / measurement methods for different indicators are as follows:

[0041] ① Pollen viability (R2 phase)

[0042] Eight flowers of different varieties that are about to open (showing white petals but not yet open) were collected with tweezers. The anthers of the freshly collected flowers were carefully removed with tweezers and placed in TTC staining solution. The flowers were stained in the dark for 2.5 hours. The anthers in the TTC staining solution were crushed with a pipette tip and mixed well. 10 μL of the supernatant was taken and dropped onto the center of a glass slide. The flowers were observed using an optical microscope. The same magnification and field of view were used for five replicates to distinguish between viable and non-viable pollen grains. The number of pollen grains in four different viability states (strong viability, moderate viability, weak viability, and no viability) was statistically analyzed, and the percentage of each viability pollen grain in the total number of pollen grains in the field of view was calculated.

[0043] ② Measurement of chlorophyll (SPAD) content (V2 / R2 / R4 phases)

[0044] Using a SPAD instrument (KONICAMINOLTA SPAD-502plus), the middle leaf of the newly fully expanded trifoliate leaf at the top of the main stem of the plant was selected. Five technical replicates were performed and the average value was taken. Five biological replicates were also performed.

[0045] ③ Peroxidase (POD) activity (V2 phase, R2 phase, R4 phase)

[0046] Select the middle leaf of the newly fully expanded trifoliate leaf at the top of the main stem of the plant, take samples, and immediately flash-freeze them in liquid nitrogen and store them at -80°C. Using a kit (Boxboi), peroxidase activity was measured spectrophotometrically according to the kit instructions, with three technical replicates and three biological replicates.

[0047] ④ Agronomic traits and yield traits (R8 period)

[0048] After harvest at maturity, data from a temperature and humidity recorder were used to select control / experimental group materials at different stages based on the effective accumulated temperature. The main indicators for seed selection were: plant height, shriveled pod rate (%), bottom pod height, number of effective branches, number of nodes, and 100-seed weight.

[0049] 2. Data statistical analysis and establishment of a comprehensive evaluation system for the high-temperature tolerance of soybeans throughout their entire growth period.

[0050] SPSS data processing software was used to perform significance and correlation analysis on the control / high temperature physiological and biochemical test indicators and agronomic traits data, and the indicators that were significant and correlated were selected as key indicators.

[0051] Principal component analysis, membership function analysis, and cluster analysis were performed on the data using SPSS and GraphPad Prism statistical software. The high-temperature resistance levels were then classified based on the evaluation scores. SPSS software was used for the cluster analysis.

[0052] The relevant analysis steps are as follows:

[0053] ① Calculate the high temperature resistance coefficient of each indicator = high temperature data / control data;

[0054] ② The high-temperature resistance coefficient is standardized using the range standardization method;

[0055] ③ Principal component analysis: Extract principal components based on the criterion that the eigenvalue is greater than 1;

[0056] ④ Standardize the scores of each indicator trait on the extracted principal components using membership functions: F(X) i )=(X i -X min ) / (X max -X min ); i=1, 2, 3,..., n;

[0057] Where X min and X max Let each represent the minimum and maximum score on each principal component;

[0058] ⑤ wp represents the weight of the p-th principal component extracted; λp represents the eigenvalue corresponding to the extracted principal component;

[0059] ⑥ C represents the comprehensive value of the high-temperature treatment response factor;

[0060] ⑦ Perform Euclidean distance cluster analysis on the C value, select an appropriate Euclidean distance to classify the groups, and adjust the classification according to the size of the C value to classify the high temperature resistance levels.

[0061] Experimental Results and Analysis:

[0062] (1) High temperature stress significantly affects different indicators

[0063] High temperature stress treatment at different stages of soybean growth can significantly affect physiological and biochemical indicators and agronomic traits such as chlorophyll content, peroxidase (POD) activity, pollen viability, and pod shriveling rate. Figure 1 The results (Table 2) showed that after high-temperature stress, the SPAD value of soybeans decreased significantly by 29% at stage V2. After experiencing high temperatures at stage R2, peroxidase (POD) activity and pollen viability decreased significantly by 33% and 90%, respectively. Furthermore, after prolonged exposure to high temperatures, the proportion of empty pods increased significantly by 207%. Several other agronomic traits, including bottom pod height, number of effective branches, number of nodes, and 100-seed weight, also decreased significantly, by 82%, 69%, 17%, and 11%, respectively. The data indicate that soybeans are affected by high-temperature stress at different stages, with varying degrees of impact on different trait indicators. Under high-temperature stress, chlorophyll content decreases, affecting photosynthesis; peroxidase activity is inhibited, leading to ROS accumulation, plant cell damage, and even death; pollen viability decreases, increasing the occurrence of empty and sterile pods; and agronomic traits such as bottom pod height, number of effective branches, number of nodes, and 100-seed weight all decrease significantly, affecting yield and leading to reduced soybean production.

[0064] Table 2 Effects of high temperature stress on different indicators of soybean.

[0065]

[0066] (2) High temperature resistance coefficient and correlation of different evaluation indicators

[0067] After high-temperature stress, various indicators of soybean were affected to varying degrees. To determine whether there was a correlation between these indicators, the high-temperature tolerance coefficients before and after high-temperature stress were compared and analyzed. The results (Table 3) showed that traits such as the proportion of empty pods, POD (R4 stage), and pollen viability had relatively large coefficients of variation, ranging from 27% to 33%; while traits such as POD (V2 stage) and the number of effective branches had relatively small coefficients of variation, ranging from 14% to 21%. This indicates that the variation range of high-temperature tolerance coefficients differed among different trait indicators. Therefore, it is unreliable to directly evaluate the high-temperature tolerance of soybean germplasm resources based solely on the high-temperature tolerance coefficient of a single physiological indicator.

[0068] Table 3. Statistical analysis of the variation range of high temperature resistance coefficients for different soybean varieties.

[0069]

[0070] To more accurately determine whether there is a correlation between different trait indicators, Spearman correlation analysis was performed using SPSS software. The results showed that ( Figure 2 (Table 4) shows that there are certain correlations among the various traits. For example, SPAD (V2 stage) and the number of effective branches, SPAD (V2 stage) and the number of nodes, SPAD (R2 stage) and the rate of empty pods, POD enzyme (R2 stage) and pollen activity, and 100-grain weight are all correlated with multiple indicators: SPAD (V2 stage), SPAD (R2 stage), the number of effective branches, and the number of nodes. This indicates that the above single trait indicators cannot effectively evaluate the heat resistance of soybean varieties. It is necessary to use multiple indicators for comprehensive analysis in order to accurately evaluate the heat resistance of soybeans.

[0071] Table 4. Correlation analysis of high-temperature resistance coefficients for different soybean varieties.

[0072]

[0073] *At the 0.05 level (two-tailed), the correlation is significant;**At the 0.01 level (two-tailed), the correlation is significant.

[0074] X1: SPAD (V2 stage); X2: SPAD (R2 stage); X3: SPAD (R4 stage); X4: POD (V2 stage); X5: POD (R2 stage); X6: POD (R4 stage); X7: Pollen viability; X8: Pod shriveling rate / %; X9:

[0075] Plant height; X10: Bottom pod height; X11: Number of effective branches; X12: Number of nodes; X13: Weight of 100 seeds.

[0076] (3) Principal component analysis and clustering of different evaluation indicators

[0077] Based on the above significance and correlation analyses, principal component analysis was performed on several traits that showed significant differences and correlations after high-temperature stress treatment, including SPAD (V2 stage), SPAD (R2 stage), POD (R2 stage), pollen viability, pod shriveling rate / %, number of effective branches, number of nodes, and 100-grain weight. The results (Table 5) show that, according to the eigenvalue greater than 1 criterion, three principal component factors were extracted, with a cumulative contribution rate of 68.192%, indicating significant information representativeness. Furthermore, the component matrix analysis results for each trait showed that SPAD (V2 stage), SPAD (R2 stage), number of effective branches, and 100-grain weight were highly correlated with the first principal component, indicating that the first principal component basically reflected the information of these four indicators; POD (R2 stage), pollen viability, and pod shriveling rate were highly correlated with the second principal component, indicating that the second principal component basically reflected the information of these two indicators; and the number of nodes was highly correlated with the third principal component, indicating that the third principal component basically reflected the information of this indicator. Extracting these three principal components can comprehensively reflect the basic information of these eight significant variation indicators. Therefore, these eight indicators can be transformed into three new comprehensive indicators to further evaluate the high-temperature resistance of soybeans.

[0078] Table 5 Principal component analysis of different traits after high temperature stress

[0079]

[0080] Based on the three comprehensive evaluation indicators extracted from the principal component analysis above, standardized data analysis was performed. The membership function values ​​of each comprehensive indicator were calculated using formulas, and their corresponding weights were also calculated. Based on these new indicator weights, the comprehensive evaluation value (C-value) of soybean's resistance to high temperature stress throughout its entire growth period was calculated using the formulas. The resistance of different soybean varieties to high temperature stress was then classified according to the magnitude of the C-value; a higher C-value indicates stronger resistance to high temperatures, and vice versa.

[0081] To better classify and evaluate the soybean's response to high-temperature stress according to the C-value, this study used the Euclidean distance between-group average linkage method to perform cluster analysis on the response capabilities of different soybean varieties to high-temperature stress. The results showed that a Euclidean distance of 10.0 was the most suitable for classification. When the Euclidean distance was 10.0, the 32 tested soybean varieties could be preliminarily divided into four major categories (…). Figure 1) and classified them into 5 categories according to the C value (Table 6). There are 4 types of high temperature sensitive type I (C < 0.4), 4 types of relatively high temperature sensitive type II (0.4 < C < 0.5), 11 types of intermediate high temperature tolerance type III (0.5 < C < 0.6), 9 types of relatively high temperature tolerance type IV (0.6 < C < 0.7) and 4 types of high temperature tolerance type V (0.7 < C).

[0082] Table 6 C values and classification of different soybean varieties

[0083]

[0084] Example 2 Application of a method for identifying the high temperature tolerance ability of soybeans throughout the whole growth period in the breeding of heat-tolerant soybean germplasm: Utilization of heat-tolerant soybean germplasm breeding

[0085] 1. Breeding of new heat-tolerant varieties throughout the whole growth period

[0086] Comprehensively evaluate germplasm resources using the method for identifying the high temperature tolerance ability throughout the whole growth period, and configure hybrid combinations in combination with the comprehensive performance such as the suitable ecological region type, yield per unit area, protein content, and oil content of the identified germplasm. Through shuttle breeding and multi-point identification, screen excellent lines, and further comprehensively evaluate breeding materials using the method for identifying the high temperature tolerance ability throughout the whole growth period.

[0087] 2. High-yield demonstration of excellent heat-tolerant varieties throughout the whole growth period

[0088] Utilize the newly bred heat-tolerant soybean varieties throughout the whole growth period to carry out high-yield demonstrations in areas with effective accumulated temperature > 2241℃·d. Among them, the yield measurement methods are as follows:

[0089] Theoretical yield measurement standard:

[0090] Sampling method. Divide the demonstration field into 3 - 5 yield measurement points according to the planting area, soil fertility, and soybean growth situation. For each yield measurement point, adopt the diagonal 3 - 5 point sampling method, with each sample point more than 5 meters away from the field edge, and randomly select points. For fields sown with equal rows or wide and narrow rows, continuously measure the distance of 11 rows in the sample point to calculate the average row spacing (meters). Select 4 adjacent rows, and select 11 consecutive plants in each row to calculate the average plant spacing (meters). Continuously measure the number of grains per plant of 10 plants to calculate the average number of grains per plant. The 100-seed weight is calculated according to the variety approval announcement.

[0091] Calculation formula. Yield per mu (kg) = number of plants / mu × number of grains per plant × 100-seed weight (g) × 10 -5 × 0.9.

[0092] Actual yield measurement standard:

[0093] Yield Measurement Method. Representative plots (at least 3 mu in area) are selected from the yield measurement area. Mechanical harvesting is used to calculate the actual yield, and moisture content is measured using a moisture meter. The harvester is cleaned and inspected before harvesting; grains lost in the field are not counted in the yield calculation.

[0094] Calculation formula: Actual yield (kg / mu) = [Actual yield (kg) / Actual yield area (m²)] × 666.7 × [1 - Moisture content (%)] ÷ (1 - 13%)

[0095] 3. Experimental Results

[0096] By comprehensively evaluating breeding materials using the whole-growth-cycle high-temperature tolerance identification method, a batch of new Gan Dou series varieties, including Jinggan 01-1 (Jingyoudou No. 1, Gan Shen Dou 20240003), Ganxia 2020-1 (Ganxiadou No. 1, Gan Shen Ding 20240004), and Ganxia 2021-1 (Zhonggan 601, Gan Shen Dou 20240002), have been bred. The overall high-temperature tolerance comprehensive C value is greater than 0.7, and the high-temperature tolerance level is 5 (high-temperature tolerance). Currently, all three varieties have been approved by the Jiangxi Provincial Variety Approval Committee.

[0097] In 2024, the Jinggan 01-1 and Ganxia 2021-1 crops experienced an effective accumulated temperature of >2241.17℃·d and a maximum temperature of over 45℃ for 45 days, with actual yields reaching 260.78 kg / mu and 262.7 kg / mu respectively, achieving high yield levels under extreme high-temperature conditions.

Claims

1. A method for identifying the high-temperature tolerance of soybeans throughout their entire growth period, characterized in that: Step (1) Sow soybean seeds and subject them to high temperature stress during the growth period. Detect the physiological and biochemical indicators, agronomic traits and yield traits of soybeans under control and high temperature treatment at different growth and development stages, and calculate the correlation between each trait index. Step (2) Calculate the heat tolerance coefficient of the high temperature stress response trait. Utilize the trait with significant differences in heat tolerance coefficient among varieties to calculate the correlation between the trait and the heat tolerance coefficient. Based on the principal component and membership function standardization analysis results, rate the heat tolerance level of the sown soybeans according to the heat tolerance membership function value and cluster analysis results.

2. The method for identifying the high-temperature resistance of soybeans throughout their entire growth period according to claim 1, characterized in that: The soybean seeds sown in step (1) include one or more of the following: germplasm resources from different sources, local germplasm, local varieties, strains or varieties; The growth and development stages mentioned in step (1) include the seedling stage, flowering stage, pod-filling stage, grain-filling stage, and maturity and harvest stage; The physiological and biochemical indicators mentioned in step (1) include chlorophyll content, pollen viability, and peroxidase POD activity; The agronomic traits mentioned in step (1) include plant height, bottom pod height, number of effective branches, and number of nodes; The yield traits mentioned in step (1) include the percentage of shriveled pods and the weight of 100 pods.

3. The method for identifying the high-temperature resistance of soybeans throughout their entire growth period according to claim 1, characterized in that, The temperature conditions for high-temperature stress in step (2) are as follows: (1) Record the real-time field temperature value every hour, and statistically analyze the highest temperature and effective accumulated temperature of the sampling / measurement index on the day, the previous five days and the previous ten days. The effective accumulated temperature is ∑(daily average temperature - reference temperature), and the reference temperature is 10℃. (2) The high temperature treatment conditions for seedling, flowering and pod-setting stages are: daily temperature ≥ 40℃, effective accumulated temperature ≥ 113℃·d 5 days before sampling, and effective accumulated temperature ≥ 230℃·d 10 days before sampling. (3) The high temperature condition during the harvest period is ≥2367.9℃·d of effective accumulated temperature throughout the entire growth period.

4. The method for identifying the high-temperature resistance of soybeans throughout their entire growth period according to claim 1, characterized in that, In step (2), the high temperature resistance coefficient = high temperature phenotype value / control phenotype value.

5. The method for identifying the high-temperature resistance of soybeans throughout their entire growth period according to claim 1, characterized in that, In step (2), the correlation between different indicators is analyzed based on the high-temperature resistance coefficient of the significant response to high-temperature stress traits; principal component analysis uses the correlation matrix to extract principal components with eigenvalues ​​greater than 1; the membership function standardization analysis formula in step (2) is as follows: F(X i )=(X i -X min ) / (X max -X min ); i = 1, 2, 3, ..., n; where X min and X max Let X represent the minimum and maximum scores on each principal component, respectively. i This represents the principal component score.

6. The method for identifying the high-temperature resistance of soybeans throughout their entire growth period according to claim 1, characterized in that, The steps for establishing the soybean high-temperature tolerance evaluation system throughout its entire growth period in step (2) are as follows: (1) wp represents the weight of the p-th principal component extracted; λp represents the eigenvalues ​​corresponding to the extracted principal components; (2) C represents the comprehensive value of the high-temperature treatment response factor; (3) Perform Euclidean distance cluster analysis based on C value, select appropriate Euclidean distance to classify, and classify high temperature resistance levels according to the size of C value.

7. The method for identifying the high-temperature resistance of soybeans throughout their entire growth period according to claim 1, characterized in that, The high-temperature resistance rating method described in step (2) calculates the average value of the membership function corresponding to the high-temperature resistance index of soybeans, and classifies the high-temperature resistance level according to the numerical range of the average value. The numerical range is divided as follows: several consecutive threshold intervals are set in sequence, and the high-temperature resistance level is mapped to each threshold interval.

8. The application of a method for identifying the high-temperature tolerance of soybeans throughout their entire growth period, characterized in that... The method for identifying the heat resistance of soybean throughout its entire growth period, as described in any one of claims 1 to 7, is applied in the discovery of heat resistance genes in soybeans, germplasm evaluation, germplasm innovation, variety breeding, and production promotion.

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