A rapid method for identifying soybean shade tolerance and its application

Abstract

This invention discloses a rapid identification method for soybean shade tolerance and its application, belonging to the field of plant breeding technology. The method includes: planting soybean materials under continuous shading at a shading rate of 30% ± 2%; measuring plant height, average internode length, stem diameter at the fifth internode, and petiole length of the largest leaf on the main stem in both the shaded and control groups at 50 ± 3 days after emergence; calculating PHS, ILS, STS, and PLS; calculating a comprehensive evaluation value using the D-value calculation formula; and classifying the materials into three shade tolerance levels—strong, medium, and weak—based on D values ​​≥ 0.65, 0.45 ≤ D value < 0.65, and D value < 0.45. This invention, by optimizing the measurement period and shading rate, combined with a multi-index comprehensive evaluation model, shortens the identification cycle to within 50 days, achieving a consistency rate of over 90% with actual field performance. It can be widely applied to soybean shade tolerance breeding, germplasm resource screening, and variety evaluation.

Description

Technical Field

[0001] This invention belongs to the field of plant breeding technology, and specifically relates to a rapid identification method for soybean shade tolerance and its application. Background Technology

[0002] Soybeans are an important dual-purpose crop for grain and oil in my country. With the adjustment of the planting structure, intercropping soybeans with crops such as corn, sugarcane, cassava, and young fruit trees has become an important way to alleviate competition for land between grains and soybeans and improve land productivity. However, in intercropping environments, light intensity is significantly reduced (weak light stress), and common soybean varieties often suffer from problems such as excessive vegetative growth, lodging, sparse pod formation, and severe yield reduction. Therefore, cultivating shade-tolerant, stable, and high-yielding soybean varieties is the key to the success of intercropping models.

[0003] Traditional soybean shade tolerance breeding mainly relies on field visual inspection for phenotypic selection, which has the following technical defects: (1) low selection efficiency, strong subjectivity of visual inspection, and poor repeatability; (2) long identification cycle, usually requiring the plants to grow to maturity (about 4-5 months) before evaluation can be carried out based on lodging degree, yield, etc.; (3) single identification indicators with low heritability, such as stem and leaf dry weight, root dry weight, etc., although biomass indicators can reflect the stress degree, they are easily affected by environmental year, with large errors, and are not suitable for efficient screening of individual plants of segregating generations; (4) lack of standardized shading treatment parameters, different studies use different shading rates and measurement periods, resulting in incomparable results.

[0004] Existing technologies have reported some findings on crop shade tolerance identification, such as using shade nets to set different shading gradients and measuring indicators like plant height and stem diameter. However, these methods mostly remain at the "testing" level, used only for variety evaluation, and do not incorporate shading stress throughout the entire breeding process (especially early-generation selection), thus failing to achieve the targeted accumulation of shade tolerance traits. Furthermore, the selection of measurement periods (e.g., seedling stage, flowering stage, maturity stage) and shading rates (e.g., 15%, 60%) in existing identification methods lacks data support, failing to screen for the key parameter combinations with the highest heritability and best discriminative power.

[0005] Therefore, establishing a complete breeding technology system that combines "stress environment breeding" with "standardized rapid identification" is of great significance for promoting the breeding of shade-tolerant soybean varieties. Summary of the Invention

[0006] In view of the problems existing in the above-mentioned prior art, such as long identification cycle, inconsistent parameters, and low accuracy, this invention provides a rapid identification method for soybean shade tolerance and its application. This method achieves rapid and accurate identification of soybean shade tolerance through standardized shading treatment, phenotypic determination at key stages, and comprehensive evaluation of multiple indicators.

[0007] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0008] A rapid method for identifying the shade tolerance of soybeans includes the following steps:

[0009] S1. Standardized shading treatment: The soybean materials to be tested were sown in an artificially controlled environment. A shading stress group and a normal light control group were set up. The shading stress group was continuously shaded using a shading net with a shading rate of 30%±2% from before sowing or before emergence.

[0010] S2. Determination of key phenotypic indicators: At 50 days ± 3 days after emergence, the plant height, average internode length, stem diameter of the fifth internode, and petiole length of the largest leaf on the main stem of each soybean plant in the shaded group and the control group were measured respectively.

[0011] S3. Calculation of Shade Tolerance Response Index: Calculate the shade tolerance response index for each index using the following formula:

[0012] (1) Plant height stability index PHS = plant height of control group / plant height of shaded group; (2) Internode length stability index ILS = average internode length of control group / average internode length of shaded group; (3) Stem diameter retention index STS = stem diameter of control group / stem diameter of shaded group; (4) Petiole length stability index PLS = petiole length of control group / petiole length of shaded group;

[0013] S4. Calculation of the overall shade tolerance evaluation value (D value):

[0014] D value = 0.30 × PHS + 0.30 × ILS + 0.25 × STS + 0.15 × PLS;

[0015] S5. Shade tolerance grading: Compare the D value with a preset threshold:

[0016] If the D value is ≥ 0.65, it is determined to be a strong shade-tolerant type; if 0.45 ≤ D value < 0.65, it is determined to be an intermediate type; if the D value < 0.45, it is determined to be a weak shade-tolerant type.

[0017] Furthermore, the shading rate in step S1 is 30%. Under this shading rate, the heritability of soybean plant height and internode length phenotypic indicators is the highest, and the correlation coefficient with the field shade tolerance level reaches a highly significant level r≥0.70.

[0018] Furthermore, the stem diameter measurement location in step S2 is the middle of the fifth internode above the cotyledon node, measured using a digital caliper with an accuracy of 0.01 mm.

[0019] Furthermore, the weighting coefficients 0.30, 0.30, 0.25, and 0.15 mentioned in step S4 are determined by the following method: based on the phenotypic data (including PHS, ILS, STS, and PLS data) of no less than 100 soybean germplasms under a shading rate of 30%, the first principal component loading value is obtained through principal component analysis and then normalized.

[0020] Furthermore, the thresholds 0.65 and 0.45 mentioned in step S5 are determined by the following method: using multiple standard varieties with known shade tolerance levels as controls, the distribution range of their D values ​​is determined through multi-year, multi-location trials, and the midpoint between the lower limit of strongly shade-tolerant varieties and the upper limit of moderately shade-tolerant varieties is taken as the determination.

[0021] Another objective of this invention is to propose an application of the method described above in soybean shade tolerance breeding, germplasm resource screening, or variety evaluation.

[0022] Furthermore, the application includes: identifying the soybean material to be tested using the methods described above, and selecting breeding parents or screening germplasm resources based on the shade tolerance level obtained from the identification.

[0023] Another object of the present invention is to provide a shade tolerance assessment system for implementing the method described above, comprising:

[0024] Shading unit: artificial climate chamber or shade greenhouse, used to provide a continuous shading environment with a shading rate of 30%±2%;

[0025] Data acquisition unit: includes measuring tools for measuring plant height and internode length, and digital calipers for measuring stem diameter;

[0026] Data processing unit: Connected to the data acquisition unit, it is used to calculate the shade resistance response index and comprehensive evaluation value D of each indicator based on the measurement data, and output the shade resistance grading result based on the D value.

[0027] Compared with the prior art, the present invention has at least the following beneficial effects:

[0028] 1. Regarding the selection of the testing period, it is known in the art that phenotypic testing can be performed throughout the entire growth period of soybeans, but there is no consensus on when the testing best reflects genotypic differences. This application, through comparative experiments, found that 50 days ± 3 days after emergence (around the initial flowering stage) is the optimal window for the expression of shade tolerance traits. During this period, the heritability of the plant height stability index (PHS) reached 88.6%, significantly higher than 75.4% at 40 days and 81.9% at 60 days (see Table 3 in Application Example 3). This indicates that selecting 50 days as the testing period achieves efficient capture of genetic information related to shade tolerance traits while minimizing environmental interference, solving the technical problems of arbitrary testing periods and low heritability in existing technologies.

[0029] 2. Regarding the selection of shading gradients, the intensity of stress directly affects the identification results. Insufficient stress makes it difficult to discern genotype differences, while excessive stress leads to widespread damage and difficulty in differentiation. This application compared three shading gradients (15%, 30%, and 60%) and found that under 15% shading, most varieties showed no significant phenotypic differences (correlation coefficient with field shade tolerance level was only 0.48), while under 60% shading, most varieties suffered severe lodging, making it impossible to effectively distinguish different shade-tolerant genotypes. However, under 30% shading, the correlation coefficients between plant height, internode length, shade tolerance coefficients, and field shade tolerance level reached 0.70 (P<0.001). This indicates that 30% shading provides sufficient stress to stimulate shade-tolerant gene expression without exceeding the tolerance threshold of superior genotypes, maximizing the identification differentiation and solving the technical problem of inappropriate selection of identification stress.

[0030] 3. Regarding the construction of the comprehensive evaluation model, correlation analysis between single indicators and field shade tolerance levels showed that the plant height stability index (PHS) was 0.74, the internode length stability index (ILS) was 0.68, the stem diameter retention index (STS) was 0.58, and the petiole length stability index (PLS) was 0.12. Although each indicator is related to shade tolerance, each has significant limitations when used alone—plant height is easily affected by plant type, internode length is easily affected by the number of nodes, and the measurement errors of stem diameter and petiole length are relatively large. This application determined the weights (PHS 0.30, ILS 0.30, STS 0.25, PLS 0.15) through principal component analysis and constructed a D-value comprehensive evaluation model, which increased the correlation coefficient between the D-value and the overall field shade tolerance performance to 0.87, significantly higher than any single indicator. It is particularly noteworthy that the correlation between the petiole length stability index (PLS) and the field shade tolerance level when used alone is only 0.12, which is statistically insignificant. Those skilled in the art would usually discard such weakly correlated indicators. However, this invention, through principal component analysis, discovered that it still contained valid information. By assigning it a weight of 0.15 and incorporating it into the comprehensive model, the D value reached 0.87. This method of mining and fusing "weak signal" indicators achieves a system gain effect that a single indicator cannot reach.

[0031] 4. Regarding the synergistic effect of the three factors, optimizing the determination period alone can improve heritability, optimizing the shading rate alone can enhance discrimination, and using a comprehensive evaluation alone can improve accuracy. However, this application organically combines the "50-day window period," "30% shading rate," and "comprehensive evaluation of four indicators," resulting in a significant synergistic effect: it only takes 50 days from sowing to obtaining results, while traditional maturity identification methods usually take 4-5 months, increasing identification efficiency by more than 2 times; the identification results have a high degree of agreement with actual field performance; and it is applicable to soybean materials of different ecological types and genetic backgrounds. This simultaneous breakthrough in identification efficiency, accuracy, and universality far exceeds the simple summation of optimizing a single parameter. In particular, when optimizing any one parameter (period, shading rate, or comprehensive model) alone, it is impossible to simultaneously achieve the dual goals of rapid identification within 50 days and an agreement rate of over 90%, while the organic integration of the three factors produces a synergistic effect, demonstrating the holistic nature of this invention. Detailed Implementation

[0032] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention are described in detail below. Many specific details are set forth in the following description to provide a thorough understanding of the present invention. However, the present invention can be practiced in many other ways different from those described herein, and those skilled in the art can make similar modifications without departing from the spirit of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0033] Example 1:

[0034] This embodiment proposes a rapid method for identifying the shade tolerance of soybeans, so that those skilled in the art can implement it accurately.

[0035] 1. Preparation of experimental materials

[0036] Select soybean germplasm or lines to be identified, and prepare a sufficient number of plump seeds for each sample. The seeds should be free from pests and diseases and be of uniform size to ensure consistent starting conditions for the experiment.

[0037] 2. Experimental Design

[0038] A randomized block design is used, with two processing groups:

[0039] Shade stress group: planted in an artificial shaded environment;

[0040] Normal light control group: planted under natural light;

[0041] Each material was planted with no fewer than 10 plants in each treatment group, with 3 replicates. Protective rows were set between plots to avoid the marginal effect.

[0042] 3. Shading procedures

[0043] The shading stress group was continuously shaded with shade nets from before sowing or before emergence until the index measurement was completed.

[0044] Shading net selection: Use black shade netting with a shading rate controlled at 30%±2%. The specific shading rate needs to be calibrated before sowing: On a sunny day between 12:00-13:00, use a lux meter (such as LI-250A) to measure the light intensity under the shade netting and under natural light, respectively. Calculate the shading rate = (1 - light intensity under the netting / natural light intensity) × 100%, ensuring the shading rate is within the range of 28%-32%. If it does not meet the requirements, adjust the number of shade netting layers or replace the shade netting.

[0045] Shading facility requirements: The shade greenhouse or artificial climate chamber should be well-ventilated, with a ceiling height of no less than 2.5m to avoid excessively high temperatures inside the greenhouse affecting the normal growth of the plants. The shade net should cover the entire test area, hanging down to the ground on all sides to prevent sidelight from entering.

[0046] The normal light control group consisted of plants from the same batch and plot, without shade netting, and received natural light.

[0047] 4. Sowing and Management

[0048] Sowing time should be determined based on the suitable sowing period for soybeans in the local area. Sowing methods can include spot sowing or row sowing, with a plant spacing of 10-15cm and a row spacing of 40-50cm. Water promptly after sowing to ensure uniform emergence.

[0049] Fertilizer and water management were conducted in accordance with local field production standards, and the shading group was kept consistent with the control group. Timely weeding and pest and disease control were implemented to avoid interference from non-experimental factors. Special attention was paid to preventing diseases prone to occur under shading conditions, such as damping-off and root rot.

[0050] 5. Phenotypic index determination

[0051] Measurements were taken 50 days ± 3 days after emergence. At this time, soybeans are mostly in the initial flowering stage, which is the period when shade tolerance traits are most fully expressed.

[0052] Five representative plants with uniform growth and free from pests and diseases were randomly selected from each plot, and their indicators were measured using the following methods:

[0053] (1) Plant height measurement

[0054] Measuring tool: ruler, accuracy 0.1cm;

[0055] Measurement method: Starting from the cotyledon node (where the cotyledons are attached), measure upwards along the main stem to the growing point at the top of the main stem (the base of the uppermost unfolded leaf).

[0056] Recording method: Each plant was measured independently, accurate to 0.1cm;

[0057] (2) Count of nodes on the main stem

[0058] Counting range: from the first node above the cotyledon node to the last node at the top of the main stem (the node where the leaves unfold).

[0059] Recording method: Each plant is counted independently;

[0060] (3) Calculation of average intersegment length

[0061] Calculation formula: Average internode length = Plant height / Number of nodes on the main stem;

[0062] Calculation accuracy: 0.1 cm;

[0063] (4) Measurement of stem diameter at the fifth internode

[0064] Measurement location: The middle of the fifth internode above the cotyledon (i.e., the middle position of the fifth internode counting upwards from the cotyledon).

[0065] Measuring tool: Digital caliper, accuracy 0.01mm;

[0066] Measurement method: Hold the calipers perpendicular to the main stem and gently clamp them to avoid squeezing and deformation, and measure the diameter of the internodes;

[0067] Recording method: Each plant was measured independently, accurate to 0.01 mm;

[0068] (5) Measurement of the petiole length of the largest leaf on the main stem

[0069] Leaf position determination: The 3rd or 4th fully unfolded compound leaf from the top is usually the plant's largest functional leaf;

[0070] Measurement range: from the base of the petiole (where it connects to the main stem) to the base of the leaf blade (where the first leaflet attaches).

[0071] Measuring tool: ruler, accuracy 0.1cm;

[0072] Recording method: Each plant was measured independently, accurate to 0.1cm;

[0073] For each indicator, the arithmetic mean of the measurements from 5 plants was taken as the representative value of the material in that treatment group.

[0074] 6. Calculation of Shade Tolerance Index

[0075] Based on the measurement data of the shaded group and the control group, the shade tolerance response index of each index was calculated according to the following formula:

[0076] Plant height stability index (PHS) = average plant height of control group / average plant height of shaded group; the higher the PHS value, the smaller the increase in plant height under shading, and the stronger the shade tolerance.

[0077] For example: the plant height of the control group is 60cm, and the plant height of the shaded group is 80cm, then PHS=60 / 80=0.75;

[0078] Internode length stability index (ILS) = average internode length of control group / average internode length of shaded group; the higher the ILS value, the smaller the internode elongation under shading and the stronger the shade tolerance.

[0079] Stem diameter retention index (STS) = average stem diameter of control group / average stem diameter of shaded group; the larger the STS value, the smaller the stem diameter reduction under shading and the stronger the shade tolerance; STS≥1 indicates that the stem diameter has not reduced or has increased slightly, and STS<1 indicates that the stem diameter has reduced;

[0080] Petiole length stability index (PLS) = average petiole length of control group / average petiole length of shaded group; the larger the PLS value, the smaller the petiole elongation under shading and the stronger the shade tolerance.

[0081] The results of each index calculation are rounded to two decimal places.

[0082] 7. Calculation of the shade tolerance comprehensive evaluation value (D-value)

[0083] Calculate the D value using the following formula: D value = 0.30 × PHS + 0.30 × ILS + 0.25 × STS + 0.15 × PLS;

[0084] The weighting coefficients of 0.30, 0.30, 0.25, and 0.15 in the formula were determined by principal component analysis of no less than 100 soybean germplasm accessions (see Application Example 5 for the specific determination method), which can reflect the comprehensive contribution of each index to shade tolerance to the greatest extent. The D value calculation result is rounded to two decimal places.

[0085] 8. Shade tolerance grading determination

[0086] The calculated D value is compared with the following preset threshold:

[0087] If the D value is ≥ 0.65, the material is determined to be strongly shade-resistant; if 0.45 ≤ D value < 0.65, the material is determined to be intermediate; if the D value < 0.45, the material is determined to be weakly shade-resistant.

[0088] The above thresholds were obtained through multi-year, multi-location trials of multiple standard varieties with known shade tolerance levels (see Application Example 6 for the specific calibration method). After verification by a large number of materials from multiple locations over many years, the agreement with actual field performance reached over 90%.

[0089] 9. Results Recording and Application

[0090] The identification results are recorded in a dedicated form, including information such as material name, various shade tolerance response indices, D-value, and shade tolerance level. The identification results can be used for: selection and elimination of breeding offspring, evaluation and classification of the shade tolerance of germplasm resources, providing shade tolerance certification materials in variety approval, and screening and recommending suitable intercropping varieties.

[0091] Application Example 1: Shade Tolerance Identification and Variety Verification of Guixiadou 105

[0092] This application example is used to verify the effectiveness of the identification method of the present invention on a specific variety.

[0093] The soybean variety GX105 (later named Guixiadou 105) was identified using the complete operating procedure described in Example 1. With a shading rate of 30%, measurements were taken 50 days after emergence. The data are shown in Table 1.

[0094] Table 1. Shade tolerance identification data of Guixiadou 105

[0095]

[0096] Calculate the value of D:

[0097] D= 0.30×0.72 + 0.30×0.71 + 0.25×1.11 + 0.15×0.76 = 0.216 + 0.213+ 0.278 + 0.114 = 0.82

[0098] According to the grading standard, a D value of 0.82 ≥ 0.65 indicates that it is classified as a strong shade-tolerant type.

[0099] This variety, named Guixiadou 105, was verified in Guangxi regional trials to have an 8.7% yield increase compared to the control under 30% shading, with a lodging resistance level of Grade 1. Molecular marker detection showed that it carries the shade-tolerant genes Glyma.06g213100 and Glyma.05g231100. This application example verifies that the identification method of this invention can accurately and early screen for highly shade-tolerant soybean varieties.

[0100] Application Example 2: Shade Tolerance Identification and Variety Verification of Guichundou 108

[0101] This application example is used to verify the effectiveness of the identification method of the present invention on soybeans of different ecological types.

[0102] The soybean variety GX108 (later named Guichundou 108) was identified using the complete operating procedure described in Example 1. The shading rate was 30%, and measurements were taken 50 days after emergence. The data are shown in Table 2.

[0103] Table 2. Shade tolerance identification data of Guichundou 108

[0104]

[0105] Calculate the value of D:

[0106] D= 0.30×0.74 + 0.30×0.72 + 0.25×1.09 + 0.15×0.78 = 0.222 + 0.216+ 0.273 + 0.117 = 0.83.

[0107] According to the grading standard, a D value of 0.83 ≥ 0.65 indicates that it is classified as a strong shade-tolerant type.

[0108] This strain, named Guichundou 108, was approved by the state in 2017. It has a protein content of 47.86% and is resistant to the beet armyworm and soybean mosaic virus. This application example verifies the universality of the identification method of this invention in soybeans of different ecotypes.

[0109] Application Example 3: Comparative Experiment for Screening Key Parameters

[0110] This application example is used to verify the superiority of the parameters selected in this invention (30% shading rate, 50-day measurement period).

[0111] One hundred and one soybean germplasm samples with different shade tolerance levels were selected. Different shading gradients (15%, 30%, 60%) and different measurement periods (40 days, 50 days, 60 days) were set up. The correlation coefficients and heritability of plant height + average internode length with shade tolerance level at field maturity were calculated for each treatment. The results are shown in Table 3.

[0112] Table 3 Comparison of identification results under different shading gradients and measurement periods

[0113]

[0114] As shown in Table 3, the combination of 30% shading and 50-day measurement resulted in the highest correlation coefficient and heritability, which were significantly better than other treatments, proving that this parameter combination is the optimal identification condition selected by this invention.

[0115] Meanwhile, to verify the correlation between each individual index and shade tolerance, a correlation analysis was conducted on the shade tolerance response indices and field shade tolerance grades of 101 germplasm accessions under 30% shading and 50-day testing conditions. The results are shown in Table 4.

[0116] Table 4. Correlation between various shade tolerance response indices and field shade tolerance levels.

[0117]

[0118] As shown in Table 4, PHS had the highest correlation among individual indicators (0.74), but the D-value comprehensive evaluation improved the correlation to 0.87, demonstrating the significant gain effect of multi-indicator fusion.

[0119] Application Example 4: The Effect of Different Shading Starting Generations on Breeding Efficiency

[0120] This application example is used to verify the breeding efficiency improvement effect of the identification method of the present invention when applied to early generation screening.

[0121] F2 seeds from the same hybrid combination (Zhongdou 8 × Ba 13) were subjected to different treatments:

[0122] Treatment A (this invention): F2-F4 were screened with 30% shading throughout the process. The method of this invention was used to evaluate the D value of individual plants at 50 days after each generation, and individual plants with D≥0.65 were retained.

[0123] Process B: F2-F3 under normal lighting conditions, standard selection; F4 onwards, 30% shading for screening.

[0124] Treatment C (standard control): F2-F5 were selected under normal lighting conditions, and F6 was evaluated under 30% shading.

[0125] Each treatment yielded 30 stable lines. The D-value and shade tolerance gene carrier rate were uniformly measured, and the results are shown in Table 5.

[0126] Table 5. Comparison of breeding efficiency of different screening strategies

[0127]

[0128] As shown in Table 5, when the method of the present invention was used for early generation stress screening (treatment A), the proportion of strong shade-tolerant lines and the carrying rate of shade-tolerant genes were significantly higher than those of other treatments. This proves that when the identification method of the present invention is applied to early generation screening, the accumulation effect of shade-tolerant traits is the best, and the enrichment efficiency of shade-tolerant genes is increased by more than 5 times.

[0129] Application Example 5: Basis for Determining Weighting Coefficients

[0130] This application example illustrates the method for determining the weighting coefficients (PHS 0.30, ILS 0.30, STS 0.25, PLS 0.15) used in this invention.

[0131] 1. Data Source

[0132] Using shading test data of soybean germplasm resources collected over many years and at multiple locations, all materials were planted under a shading rate of 30%. Plant height, average internode length, stem diameter of the fifth internode, and petiole length were measured 50 days after emergence. The shade tolerance response indices (PHS, ILS, STS, PLS) of each index were calculated.

[0133] 2. Principal Component Analysis

[0134] Principal component analysis was performed on the above data. The results show that the variance contribution rate of the first principal component exceeds 60%, which can well represent the comprehensive information of the four indicators. The loading values ​​of each indicator on the first principal component reflect their contribution to the overall shade resistance.

[0135] 3. Weight Determination

[0136] The loading values ​​of the first principal component were normalized by absolute value to obtain the initial weights of each index. For practical application, the initial weights were adjusted by rounding, and the final weights were determined as follows: Plant height stability index PHS: 0.30, internode length stability index ILS: 0.30, stem diameter retention index STS: 0.25, and petiole length stability index PLS: 0.15.

[0137] 4. Weight Verification

[0138] The D value was calculated using the above weighted combination, and a correlation analysis was performed between it and the actual shade tolerance level in the field. As shown in Table 4 of Application Example 3, the correlation coefficient between the D value and the field shade tolerance level under this weighted combination reached 0.87, which is significantly higher than any single indicator (PHS 0.74, ILS 0.68, STS 0.58, PLS 0.12), and also better than other combinations such as equal weights, proving that the weighted combination determined in this invention has the optimal discriminative ability.

[0139] Application Example 6: Threshold Calibration Test

[0140] This application example illustrates the calibration basis for the grading thresholds (D value ≥ 0.65 for strong shade tolerance, 0.45 ≤ D value < 0.65 for intermediate type, and D value < 0.45 for weak shade tolerance) used in this invention.

[0141] 1. Selection of Standard Varieties

[0142] To calibrate the D-value grading threshold, several standard varieties with known shade tolerance levels were selected as controls, including:

[0143] Strong shade-tolerant control: Guixiadou 105 and Guichundou 108 (confirmed as strong shade-tolerant by review and multiple years of multi-site identification);

[0144] Moderate shade tolerance control: Zhongdou No. 8 and Huaxia No. 3 (widely used in production, with moderate shade tolerance);

[0145] Weak shade tolerance control: Ba 13, local soybean (prone to excessive growth and lodging under shade).

[0146] 2. Multi-year, multi-location measurements

[0147] Using the method of this invention, the above-mentioned standard varieties were identified in multiple pilot areas such as Wuming and Nanning in Guangxi for several consecutive years. Each variety was repeatedly measured, and the distribution range of D values ​​was statistically analyzed. The results are as follows:

[0148] Strong shade-tolerant varieties (Guixiadou 105, Guichundou 108): After multiple tests, the D value fluctuated between 0.78 and 0.85, with most measured values ​​around 0.82;

[0149] Medium shade-tolerant varieties (Zhongdou No. 8, Huaxia No. 3): D value is mainly concentrated in the range of 0.5-0.6, with Zhongdou No. 8 having a measured value of around 0.55;

[0150] Shade-tolerant varieties (Bar 13, local soybeans): D value is generally below 0.4, mostly between 0.3 and 0.35.

[0151] 3. Threshold setting

[0152] Taking into account the statistical distribution of the above measurement results and the needs of breeding practice, the grading thresholds are set as follows:

[0153] Strong shade tolerance: D value ≥ 0.65; take the lower-middle value between the upper limit of medium shade tolerance (about 0.6) and the lower limit of strong shade tolerance (about 0.75) to ensure that truly strong shade tolerance materials are selected, while avoiding the omission of potential excellent materials due to excessively high thresholds.

[0154] Intermediate type: 0.45 ≤ D value < 0.65; the lower limit is the upper limit of the weak shade-tolerant variety (about 0.4) rounded up to 0.45 to ensure effective differentiation from the weak shade-tolerant group and provide selection space for intermediate type materials for breeding.

[0155] Weak shade tolerance: D value < 0.45; materials below this threshold perform poorly in shaded environments and should be eliminated in breeding.

[0156] 4. Threshold Validation

[0157] Using the above grading standard, a large number of soybean materials (covering different ecological types and genetic backgrounds) collected over many years and from multiple locations were back-generation verified. The results showed that the grading standard was more than 90% consistent with the actual performance of the materials in intercropping environments. This is consistent with the result in Application Example 3, where the correlation coefficient between the D value and the field shade tolerance level was 0.87, proving that the grading standard of this invention can effectively distinguish soybean materials with different shade tolerance levels, providing a reliable basis for shade tolerance identification and breeding selection.

[0158] In summary, the rapid identification method for soybean shade tolerance provided by this invention has the advantages of simple operation, clear parameters, short cycle, high accuracy, and wide applicability: it can be completed with only conventional measuring tools, and the reproducibility of the method is ensured by clear technical parameters (shading rate 30%±2%, measurement period 50 days±3 days, four key indicators, specific calculation formula, and clear grading threshold). It only takes 50 days from sowing to obtaining results, improving the identification efficiency by more than 2 times, and the consistency with actual field performance is over 90%. It can be widely used in the identification of shade tolerance of soybean materials with different ecological types and genetic backgrounds, providing reliable technical support for shade-tolerant germplasm innovation and variety selection in soybean breeding units, variety regional trials and approval tests in seed management departments, screening of intercropping special varieties in agricultural technology extension departments, and the mining and functional verification of shade-tolerant genes in scientific research units.

[0159] The above embodiments are merely examples of several implementations of the present invention, and their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of the present invention.

Claims

1. A rapid method for identifying shade tolerance in soybean, characterized by, Includes the following steps: S1. Standardized shading treatment: The soybean materials to be tested were sown in an artificially controlled environment. A shading stress group and a normal light control group were set up. The shading stress group was continuously shaded using a shading net with a shading rate of 30%±2% from before sowing or before emergence. S2. Determination of key phenotypic indicators: At 50 days ± 3 days after emergence, the plant height, average internode length, stem diameter of the fifth internode, and petiole length of the largest leaf on the main stem of each soybean plant in the shaded group and the control group were measured respectively. S3. Calculation of Shade Tolerance Response Index: Calculate the shade tolerance response index for each index using the following formula: (1) Plant height stability index PHS = plant height of control group / plant height of shaded group; (2) Internode length stability index ILS = average internode length of control group / average internode length of shaded group; (3) Stem diameter retention index STS = stem diameter of control group / stem diameter of shaded group; (4) Petiole length stability index PLS = petiole length of control group / petiole length of shaded group; S4. Calculation of the overall shade tolerance evaluation value (D value): D value = 0.30 × PHS + 0.30 × ILS + 0.25 × STS + 0.15 × PLS; S5. Shade tolerance grading: Compare the D value with a preset threshold: If the D value is ≥ 0.65, it is determined to be a strong shade-tolerant type; if 0.45 ≤ D value < 0.65, it is determined to be an intermediate type; if the D value < 0.45, it is determined to be a weak shade-tolerant type.

2. The method of claim 1, wherein, The shading rate mentioned in step S1 is 30%.

3. The method of claim 1, wherein, The stem diameter measurement location in step S2 is the middle of the fifth internode above the cotyledon node, measured using a digital caliper with an accuracy of 0.01 mm.

4. The application of the method as described in any one of claims 1-3 in soybean shade tolerance breeding, germplasm resource screening, or variety evaluation.

5. Use according to claim 4, characterized in that, The application includes: identifying the soybean material to be tested using the method described in any one of claims 1-3, and selecting breeding parents or screening germplasm resources based on the shade tolerance level obtained from the identification.

6. A shade tolerance identification system for implementing the method according to any one of claims 1 to 3, characterized in that include: Shading unit: artificial climate chamber or shade greenhouse, used to provide a continuous shading environment with a shading rate of 30%±2%; Data acquisition unit: includes measuring tools for measuring plant height and internode length, and digital calipers for measuring stem diameter; Data processing unit: Connected to the data acquisition unit, it is used to calculate the shade resistance response index and comprehensive evaluation value D of each indicator based on the measurement data, and output the shade resistance grading result based on the D value.

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