Method for evaluating resistance of rape to stress based on osmotic adjustment substances

Abstract

The application discloses a rapeseed stress resistance evaluation method based on osmotic adjustment substances, and relates to the technical field of plant stress resistance evaluation. The method comprises the following steps: obtaining soluble protein content data and soluble sugar content data of rapeseed at different growth stages; calculating the synergistic increment between the soluble protein content data and the soluble sugar content data at each growth stage to obtain an osmotic adjustment substance synergistic index of each growth stage; constructing a time series vector according to the osmotic adjustment substance synergistic indexes of all growth stages and calculating the fluctuation amplitude of the time series vector between adjacent growth stages; and generating a rapeseed stress resistance comprehensive evaluation index based on the cumulative effect of all fluctuation amplitudes. The technical scheme realizes quantitative evaluation of the stress resistance of rapeseed by analyzing the synergistic change relationship between the two osmotic adjustment substances and the cumulative effect of the dynamic fluctuation in the whole growth period.

Description

Technical Field

[0001] This invention relates to the field of plant stress resistance evaluation technology, specifically a method for evaluating rapeseed stress resistance based on osmotic regulators. Background Technology

[0002] Rapeseed often suffers from various abiotic stresses such as drought, salinity, and low temperature during its growth and development. Accurately assessing its stress resistance is crucial for variety selection and cultivation management. Osmoregulation is one of the core physiological mechanisms by which plants respond to abiotic stress. Plants actively accumulate osmotic regulators such as soluble proteins and soluble sugars to reduce cell osmotic potential and maintain cell turgor pressure and normal metabolic function. Existing rapeseed stress resistance evaluation techniques typically measure the content of soluble protein or soluble sugar in leaves or roots at a specific growth stage, using the absolute value of static concentration as the basis for judging the strength of stress resistance. Some methods simply sum or average the content of a single osmotic regulator at multiple growth stages to reflect the overall stress resistance level of the variety. However, these existing technical solutions have significant drawbacks. On the one hand, the isolated detection of single substance content ignores the synergistic relationship between soluble proteins and soluble sugars in the osmotic regulation process. When plants actually experience stress, these two types of osmotic regulators do not change independently, but rather exhibit a close complementary and synergistic relationship. Simply relying on the absolute content of a single substance or a simple weighted sum of the contents of the two substances cannot accurately reflect the synergistic efficiency of the osmotic regulation system. Furthermore, static measurements or simple summations ignore the dynamic fluctuations of osmotic regulators across different growth stages. Crops experience multiple environmental changes throughout their growth cycle, and their osmotic regulation system is constantly in a state of dynamic adjustment. Drastic fluctuations in osmotic regulation capacity between adjacent growth stages often indicate a critical stress response during that period, while stable changes reflect a stable regulatory capacity. Ignoring this temporal fluctuation information leads to a discrepancy between stress resistance assessments and the actual tolerance of the crop.

[0003] The technical problems to be solved by this invention are reflected on two levels. First, how to transform soluble proteins and soluble sugars from isolated detection indicators into a comprehensive measure that reflects their synergistic changes, thereby capturing the true synergistic efficiency of the osmotic regulation system. Second, how to extract dynamic fluctuation information from the sequence of changes in osmotic regulatory substances throughout the entire growth period, incorporating the cumulative effect of temporal fluctuation characteristics into the stress resistance quantification process, to compensate for the shortcomings of existing methods that only focus on static concentration levels and ignore dynamic regulatory characteristics. Summary of the Invention

[0004] This invention provides a method for evaluating the stress resistance of rapeseed based on osmotic regulators, which solves the problems of existing technologies that measure the content of a single osmotic regulator alone and ignore the synergistic relationship between the two substances, and that static accumulation methods ignore the dynamic fluctuation information of osmotic regulators between different growth stages.

[0005] To achieve the above objectives, this invention provides the following technical solution: This invention provides a method for evaluating the stress resistance of rapeseed based on osmotic regulators. By comprehensively quantifying the synergistic changes and dynamic fluctuations of soluble protein and soluble sugar at different growth stages, it achieves an accurate assessment of the stress resistance performance of rapeseed. The method includes: acquiring soluble protein and soluble sugar content data of rapeseed at multiple key growth stages; calculating the synergistic increment between soluble protein and soluble sugar content for each growth stage to obtain an osmotic regulator synergistic index; constructing the osmotic regulator synergistic index of all growth stages into a time series vector and calculating the fluctuation amplitude between adjacent growth stages; and generating a comprehensive evaluation index of rapeseed stress resistance based on the cumulative effect of all fluctuation amplitudes. The above process incorporates the synergistic changes in the content of two core osmotic regulators and the regulatory stability throughout the entire growth period into a unified index, which can overcome the one-sidedness of a single physiological indicator in stress resistance evaluation and improve the consistency between the evaluation results and the actual tolerance capacity of the plant.

[0006] As a preferred technical solution, to obtain data on soluble protein and soluble sugar content, root samples and functional leaf samples are collected at the seedling, bolting, flowering, pod-forming, and maturity stages of rapeseed. The samples are homogenized and centrifuged to extract the supernatant. The soluble protein content is obtained from the supernatant using Coomassie brilliant blue staining, and the soluble sugar content is obtained using anthrone colorimetric method. By simultaneously collecting and separately measuring root and functional leaf samples, the source-sink relationship of osmotic regulatory substances in the entire plant can be considered, making the basic data more representative.

[0007] When calculating the osmotic regulation substance synergy index, the soluble protein content data and soluble sugar content data of the same sample source at the same growth stage are numerically aligned to obtain protein and sugar values. The product of the protein and sugar values ​​is calculated to obtain the first intermediate product. The sum of the protein and sugar values ​​is calculated to obtain the first sum. The first intermediate product is divided by the first sum, and then multiplied by a preset weighting coefficient corresponding to the growth stage and sample source to obtain the osmotic regulation substance synergy index. This calculation method uses the ratio of the product to the sum to characterize the degree of synergistic increase of the two osmotic regulation substances, which can highlight the contribution of their simultaneous increase to osmotic regulation. By introducing the weighting coefficient, it reflects the difference in the physiological importance of osmotic regulation at different growth stages. The preset weighting coefficient is determined by the analytic hierarchy process based on the dependence of rapeseed on osmotic regulation at different growth stages, making the synergy index more consistent with the developmental characteristics and stress resistance requirements of rapeseed.

[0008] Following the chronological order of seedling stage, flowering stage, pod-setting stage, and maturity stage, the osmotic regulatory synergy indices corresponding to each growth stage are arranged sequentially to form a time series vector. Starting from the second element of the time series vector, the absolute value of the difference between the current element and the previous element is calculated sequentially to obtain multiple fluctuation amplitudes. The starting and ending growth stages corresponding to each fluctuation amplitude are recorded. The fluctuation amplitude characterizes the degree of fluctuation in the osmotic regulatory synergy between adjacent growth stages, revealing the stability of the plant's regulatory system at developmental transition points.

[0009] When generating the comprehensive evaluation index of rapeseed stress resistance, all fluctuation amplitudes are summed to obtain the cumulative fluctuation value; the arithmetic mean of the synergistic indices of all osmotic regulators is calculated to obtain the mean synergistic index; the cumulative fluctuation value is divided by the mean synergistic index to obtain the fluctuation ratio; the fluctuation ratio is then numerically fused with the total number of growth periods to generate the comprehensive evaluation index of rapeseed stress resistance. Preferably, the total number of growth periods is 5, and the comprehensive evaluation index of rapeseed stress resistance is generated by standardizing the fluctuation ratio by multiplying it by the square root of the total number of growth periods. This method ensures that the final index not only covers the absolute level of the synergistic ability of osmotic regulators throughout the entire growth period but also amplifies the negative impact of drastic fluctuations in regulatory ability on the plant's stress resistance, thus more sensitively distinguishing the differences in stress resistance between different materials or treatments.

[0010] To further practically apply the evaluation results, after generating the comprehensive evaluation index of rapeseed stress resistance, the stress resistance level of rapeseed is also determined based on this comprehensive evaluation index. Multiple stress resistance level threshold intervals are preset, each interval corresponding to a stress resistance level identifier. The boundary values ​​of each interval—strong, medium, and weak stress resistance—are pre-calibrated using percentile statistics from large-sample field trials. The comprehensive evaluation index of rapeseed stress resistance is sequentially compared with each threshold interval to determine the target threshold interval it falls into, and the corresponding stress resistance level identifier is extracted as the stress resistance level output. This transforms continuous index values ​​into intuitive level information, facilitating variety selection and cultivation management decisions.

[0011] Based on the obtained stress resistance level, the critical response growth period is also determined. From all fluctuation ranges, the target fluctuation range with the largest value is selected, and the corresponding start and end growth periods are obtained, both marked as the critical response growth period. This step accurately locates the most unstable developmental stage of the rapeseed osmotic regulation system, where the response to stress is most intense, providing a time window for targeted regulation and stress resistance assessment.

[0012] When generating a stress resistance assessment report, the comprehensive stress resistance evaluation index of rapeseed is used as the primary assessment indicator, and the critical response growth period is used as the secondary assessment indicator. These indicators are filled into a pre-set report template, which also indicates the direction of change in the osmotic regulatory substance synergistic index during the critical response growth period. The output report includes the primary assessment indicator, the secondary assessment indicator, and the direction of their changes. This report combines quantitative evaluation with characteristics of critical periods, facilitating a rapid understanding of the plant's overall stress resistance and sensitive stages.

[0013] To ensure the reliability of the evaluation results, the stress resistance evaluation results were also verified. The aforementioned evaluation method was executed in multiple different treatment plots of the same rapeseed variety to obtain the comprehensive stress resistance evaluation index for each treatment plot. Actual yield data at maturity were obtained for each treatment plot. The correlation deviation between the comprehensive stress resistance evaluation index and the actual yield data for each treatment plot was calculated. When the correlation deviation value was less than a preset verification threshold, the comprehensive stress resistance evaluation index of the rapeseed variety was confirmed as valid. This verification process correlates physiological indicators with the final yield performance, ensuring that the evaluation index can truly reflect the stress resistance effect in a production sense.

[0014] After confirming the validity of the evaluation index, further optimization and screening of treatment combinations can be conducted. A comprehensive evaluation index of rapeseed stress resistance under multiple combinations of different tillage and fertilization methods is obtained. The evaluation index of each treatment combination is sorted from largest to smallest value, and several top-ranked combinations are selected as candidate optimization combinations. A list of treatment parameters for these candidate optimization combinations is output to guide rapeseed cultivation management. This method extends stress resistance evaluation directly to cultivation measure decisions, improving the level of proactive stress resistance regulation in rapeseed production.

[0015] The technical effects and advantages provided by the present invention in the above technical solution are as follows:

[0016] Within the same reproductive period, soluble protein and soluble sugar content data from the same sample source are numerically aligned. The ratio of their product to the sum is then calculated and multiplied by a preset weighting coefficient corresponding to that reproductive period and sample source to obtain the osmotic regulation substance synergy index. This scheme transforms soluble protein and soluble sugar, two osmotic regulators, from isolated concentration indicators into a comprehensive measure reflecting their synergistic relationship. When both substances are at high levels, the product term increases, and the synergy index rises accordingly, reflecting a highly efficient synergistic operation of the osmotic regulation system. Conversely, when only one substance is high while the other is low, the product term is limited, and the synergy index is at a moderate or low level, reflecting insufficient synergy in the osmotic regulation system. This calculation method constrains fluctuations in single concentration data by synergistic relationships, avoiding the one-sidedness of obtaining high evaluation values ​​solely based on high concentrations of a single substance. This allows the resulting osmotic regulation substance synergy index to more accurately depict the synergistic efficiency of the osmotic regulation system. A time-series vector was constructed by arranging the synergistic indices of osmotic regulatory substances across all growth stages. The absolute value of the difference between adjacent growth stages was calculated as the fluctuation amplitude. All fluctuation amplitudes were then accumulated and fused with the mean of the synergistic indices to generate a comprehensive evaluation index for rapeseed stress resistance. This scheme expands the perspective of stress resistance evaluation from a single mean across the entire growth period to the cumulative effect of temporal fluctuations. A large cumulative fluctuation amplitude indicates that the rapeseed material's osmotic regulation capacity underwent multiple drastic adjustments across different growth stages, indicating poor stability of its self-regulation system and a need for continuous energy consumption to re-establish osmotic equilibrium. Conversely, a small cumulative fluctuation amplitude indicates that the osmotic regulation system maintained a relatively stable operation throughout the entire growth period, demonstrating strong and stable regulation capabilities. Numerical fusion of the cumulative fluctuation effect with the growth period span ensures that the final comprehensive evaluation index simultaneously incorporates information on the synergistic operation level of osmotic regulatory substances and the stability of dynamic regulation throughout the entire growth period, resulting in a higher consistency between the evaluation results and the actual ability of rapeseed to resist adverse stress. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0018] Figure 1 This is a flowchart of a method for evaluating the stress resistance of rapeseed based on osmotic adjustment substances;

[0019] Figure 2 This is a flowchart for calculating the comprehensive evaluation index of rapeseed stress resistance;

[0020] Figure 3 This is a flowchart for generating a rapeseed stress resistance assessment report;

[0021] Figure 4 This is a flowchart for verifying the comprehensive evaluation index of rapeseed stress resistance and screening the optimal combination of tillage and fertilization.

[0022] Figure 5 Box plots showing the distribution of synergistic index of osmotic regulatory substances in rapeseed root and functional leaf samples at different growth stages;

[0023] Figure 6 This is a schematic diagram showing the synergistic index and fluctuation range of osmotic regulatory substances at different growth stages of rapeseed;

[0024] Figure 7 This is the probability density distribution diagram of the comprehensive evaluation index of rapeseed stress resistance;

[0025] Figure 8 This is a distribution chart of the comprehensive evaluation index of rapeseed stress resistance and a classification chart of stress resistance levels;

[0026] Figure 9 This is a scatter plot showing the correlation between the comprehensive evaluation index of rapeseed stress resistance and actual yield. Detailed Implementation

[0027] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0028] See Figure 1This invention provides a method for evaluating the stress resistance of rapeseed based on osmotic regulators. The method obtains soluble protein and soluble sugar content data of rapeseed at different growth stages, calculates the synergistic increment between the soluble protein and soluble sugar content data at each growth stage, and obtains the osmotic regulator synergistic index for each growth stage. A time series vector is constructed based on the osmotic regulator synergistic indexes for all growth stages, and the fluctuation amplitude of this time series vector between adjacent growth stages is calculated. A comprehensive evaluation index of rapeseed stress resistance is generated based on the cumulative effect of all fluctuation amplitudes.

[0029] Example 1:

[0030] In practice, root samples and functional leaf samples of rapeseed were collected at the seedling, bolting, flowering, pod-forming, and maturity stages. Seedling stage sampling was conducted from the unfolding of true leaves to before budding; bolting stage sampling was conducted from budding to before initial flowering; flowering stage sampling was conducted from initial flowering to final flowering; pod-forming stage sampling was conducted from final flowering to before pod maturity; and maturity stage sampling was conducted at pod maturity. For each growth stage, uniformly growing rapeseed plants were selected, and the entire root system was dug up using digging tools. Root segments with a root tip length of 2-3 cm were cut as root samples. Simultaneously, fully unfolded functional leaves from the middle of the main stem, free from disease and pests, were harvested as functional leaf samples. Root and functional leaf samples were rinsed with distilled water to remove adhering impurities, blotted dry with absorbent paper, and then quickly placed in liquid nitrogen for freezing and preservation.

[0031] Root and functional leaf samples were subjected to tissue homogenization and centrifugation, respectively, and the supernatant was extracted. For tissue homogenization, 0.5 g of the frozen sample was removed from liquid nitrogen and placed in a pre-chilled mortar. 5 mL of pre-chilled phosphate buffer (50 mmol / L, pH 7.0) was added, and the sample was homogenized until a homogenate free of particles was formed under ice bath conditions. The homogenate was then transferred to centrifuge tubes and centrifuged at 10,000 rpm for 15 minutes at 4°C. After centrifugation, the supernatant containing soluble proteins and sugars was carefully aspirated.

[0032] The supernatant was analyzed using the Coomassie Brilliant Blue staining method to obtain soluble protein content data. Specifically, 0.1 mL of supernatant was added to 5 mL of Coomassie Brilliant Blue G-250 staining solution. The Coomassie Brilliant Blue G-250 staining solution was prepared by dissolving 100 mg of Coomassie Brilliant Blue G-250 in 50 mL of 95% ethanol, adding 100 mL of 85% phosphoric acid, and then bringing the volume to 1000 mL with distilled water. After mixing, the solution was allowed to stand at room temperature for 5 minutes, and the absorbance was measured at 595 nm using a spectrophotometer. Using bovine serum albumin as a standard, standard solutions with concentrations of 0, 20, 40, 60, 80, and 100 μg / mL were prepared. The absorbance values ​​were measured using the same method, and a standard curve was plotted. The corresponding protein concentration was found on the standard curve based on the sample absorbance value, and then converted to the soluble protein content per gram of fresh weight of the sample. This soluble protein content data was expressed in milligrams per gram of fresh weight.

[0033] The anthrone colorimetric method was used to detect the soluble sugar content in the supernatant. Specifically, 0.2 mL of the supernatant was added to 0.8 mL of distilled water, followed by 5 mL of anthrone reagent (prepared by dissolving 0.2 g of anthrone in 100 mL of 98% concentrated sulfuric acid). The mixture was heated in a boiling water bath for 10 minutes, then rapidly cooled to room temperature. The absorbance was measured at 620 nm using a spectrophotometer. Standard solutions with concentrations of 0, 10, 20, 30, 40, and 50 μg / mL were prepared using glucose as a standard. The absorbance was measured using the same method, and a standard curve was plotted. The corresponding sugar concentration was found on the standard curve based on the sample absorbance value, and then converted to the soluble sugar content per gram of fresh weight of the sample. This soluble sugar content was expressed in milligrams per gram of fresh weight.

[0034] Numerical alignment was performed on soluble protein and soluble sugar content data from the same sample source at the same growth stage to obtain separate protein and sugar values. Numerical alignment established a correspondence between soluble protein and soluble sugar content data for root samples of the same plant according to sample number; similarly, the correspondence between soluble protein and soluble sugar content data for functional leaf samples was also established according to sample number. In seedling root samples, if the soluble protein content data of a particular sample is... The soluble sugar content data is as follows: milligrams per gram of fresh weight. If the protein content is in milligrams per gram of fresh weight, then the protein value is recorded as follows: The sugar value is recorded as For each growth stage, the root sample set and functional leaf sample set yielded multiple pairs of protein and sugar values.

[0035] Calculate the product between protein and glucose values ​​to obtain the first intermediate product; calculate the sum between protein and glucose values ​​to obtain the first sum; then divide the first intermediate product by the first sum, and multiply by a preset weighting coefficient to obtain the osmotic regulation substance synergy index. The osmotic regulation substance synergy index is calculated using the following formula:

[0036]

[0037] in, The protein value is derived from the soluble protein content data and obtained by numerical alignment. The unit is milligrams per gram of fresh weight. The sugar content value is derived from the soluble sugar content data and obtained by numerical alignment. The unit is milligrams per gram of fresh weight. This is the first intermediate product; The first sum; The preset weighting coefficients corresponding to the reproductive period and sample source are dimensionless values. It represents the synergistic index of osmotic regulating substances and is dimensionless.

[0038] The preset weighting coefficients are determined using the Analytic Hierarchy Process (AHP) based on the dependence of rapeseed on osmotic regulation at different growth stages. The AHP implementation process is as follows: a hierarchical structure model is established, with the target layer evaluating the synergistic importance of osmotic regulatory substances; the criterion layer includes five growth stages: seedling, bolting, flowering, pod-forming, and maturity; and the scheme layer contains ten elements: root samples and functional leaf samples for each growth stage. Based on physiological research data on osmotic regulation at each growth stage of rapeseed, the importance of different growth stages in the criterion layer is compared pairwise using a 1-9 scale to construct a judgment matrix. Then, the importance of root samples and functional leaf samples within each growth stage is compared pairwise to construct a sub-judgment matrix. The maximum eigenvalue and corresponding eigenvector of each judgment matrix are calculated, and the eigenvectors are normalized to obtain the weight values ​​of each scheme layer element relative to the target layer. These weight values ​​are the preset weighting coefficients. For example, the preset weighting coefficient for root samples at the flowering stage corresponds to the normalized weight of the scheme layer for root samples at the flowering stage. The judgment matrix must pass a consistency test; when the random consistency ratio (CR) is less than 0.1, the preset weighting coefficients are considered valid. The sum of all preset weight coefficients is 1. The value of each preset weight coefficient is greater than 0 and less than 1. Its specific value depends on the judgment matrix constructed in the analytic hierarchy process. Different rapeseed varieties and ecological conditions can be used to adjust the element values ​​of the judgment matrix to update the preset weight coefficients.

[0039] Based on the above calculations, a set of osmotic regulation synergy indices were obtained for root and functional leaf samples from five growth stages: seedling, bolting, flowering, pod formation, and maturity. These osmotic regulation synergy indices characterize the synergistic effect of soluble proteins and soluble sugars in osmotic regulation at the same time point and in the same tissue.

[0040] See Figure 5 The horizontal axis of the figure represents the five stages of rapeseed growth: seedling stage, bolting stage, flowering stage, pod stage, and maturity stage. The vertical axis represents the synergistic index of osmotic regulators, which is dimensionless. The legend distinguishes between root samples and functional leaf samples. Both samples are displayed using box plots to show the distribution of the synergistic index of osmotic regulators among multiple rapeseed samples at each growth stage, and individual sample data points are displayed as scatter plots.

[0041] From seedling stage to maturity, the synergistic index of osmotic regulators in root samples generally showed a trend of first increasing and then decreasing, reaching its peak at flowering stage with a median of approximately 1.21, indicating the strongest synergistic effect between soluble proteins and soluble sugars in the roots during this stage. Subsequently, it remained at a high level during the silique stage, and then declined significantly at maturity. The trend of the synergistic index in functional leaf samples was similar to that of roots, with the lowest index at the seedling stage (median approximately 0.75), reaching its maximum at flowering stage (median approximately 0.95), and then decreasing at maturity. Overall, the synergistic index values ​​of root samples were significantly higher than those of functional leaf samples, indicating that the synergistic effect of osmotic regulators in the roots was more significant throughout the entire growth period.

[0042] The interquartile range and tendril length at each growth stage in the box plots demonstrate the range of variation among samples. Root samples showed the greatest fluctuation range during flowering, reflecting significant individual differences in the synergistic index of osmotic regulators at this stage. The synergistic index showed smaller fluctuations and more concentrated data at the seedling and maturity stages. The fluctuation trend of functional leaf samples was similar to that of roots, but the overall fluctuation amplitude was slightly smaller.

[0043] This figure reveals the dynamic changes in the synergistic regulatory capacity of rapeseed roots and functional leaves at different growth stages by comparing the synergistic index of osmotic regulatory substances at different growth stages and in different tissue parts. It provides a data basis for the subsequent calculation of the time series vector of the synergistic index of osmotic regulatory substances and reflects the specific methods and data characteristics of sample collection, protein sugar content determination and synergistic index calculation in Example 1.

[0044] Example 2:

[0045] In practice, five growth stages—seedling stage, flowering stage, pod-forming stage, and maturity stage—are used as fixed time points. For each growth stage, a representative osmotic regulation substance synergy index is calculated. The method for obtaining the osmotic regulation substance synergy index corresponding to a growth stage is as follows: the osmotic regulation substance synergy indices calculated separately for all root samples and all functional leaf samples during that growth stage according to the method described in Example 1 are summarized, and the arithmetic mean is calculated. The result of the arithmetic mean is used as the osmotic regulation substance synergy index corresponding to that growth stage. The osmotic regulation substance synergy index corresponding to the seedling stage is denoted as... The synergistic index of osmotic regulating substances corresponding to the bolting stage is denoted as The synergistic index of osmotic regulators corresponding to the flowering period is denoted as The synergistic index of osmotic regulators corresponding to the silique stage is denoted as The synergistic index of osmotic regulators corresponding to the maturity stage is denoted as Each All are dimensionless values, among which The values ​​are sequentially numbered according to the growth period, ranging from 1 to 5, corresponding to the seedling stage, flowering stage, pod stage, and maturity stage, respectively.

[0046] Following the sequence of seedling stage, flowering stage, pod stage, and maturity stage, , , , , Arranged sequentially, they form a time series vector, which is represented as follows: ,in It is a time series vector.

[0047] From time series vectors The second element First, calculate the absolute value of the difference between the current element and the previous element, obtaining multiple fluctuation ranges. The fluctuation range is calculated using the following formula:

[0048]

[0049] in, This represents the sequence number of the fluctuation range. The value range is 1, 2, 3, 4; Represents a time series vector The first in One element; Represents a time series vector The first in One element; express and The absolute value of the difference; Indicates the first The fluctuation range is a dimensionless value.

[0050] In specific implementation, when hour, This reflects the fluctuation range from the seedling stage to the bolting stage; when hour, This reflects the fluctuation range from the budding stage to the flowering stage; when hour, This reflects the fluctuation range from flowering to silique stage; when hour, This reflects the fluctuation range from the pod-setting stage to maturity. A total of four fluctuation ranges are thus obtained. , , , .

[0051] Record the start and end dates of childbirth corresponding to each fluctuation range. For the fluctuation range... The initial growth period is the seedling stage, and the final growth period is the bolting stage; regarding the fluctuation range The initial growth period is the flowering stage, and the end of the growth period is the budding stage; regarding the fluctuation range The initial growth period is the flowering period, and the final growth period is the pod-bearing period; regarding the fluctuation range The initial reproductive period is the silique stage, and the final reproductive period is the maturity stage. Each fluctuation amplitude is associated with its corresponding initial and final reproductive periods and stored in a data table containing three columns: fluctuation amplitude value, initial reproductive period name, and final reproductive period name. These four fluctuation amplitudes, along with their corresponding reproductive period information, will be used for subsequent cumulative effect calculations and key response reproductive period identification.

[0052] See Figure 6 The horizontal axis of the graph represents the five growth stages of rapeseed: seedling stage, bolting stage, flowering stage, pod-forming stage, and maturity stage. The vertical axis represents the dimensionless value of the osmotic regulation substance synergistic index. Solid circles indicate the distribution of the osmotic regulation substance synergistic index data for root samples, and hollow squares indicate the distribution for functional leaf samples. The solid curve formed by connecting black diamond-shaped dots represents the arithmetic mean of the osmotic regulation substance synergistic index for root and functional leaf samples at each growth stage. This curve reflects the trend of the mean value of the osmotic regulation substance synergistic index as it changes with the growth stage. Dashed lines and corresponding text labels represent the calculated fluctuation range between adjacent growth stages. The indicator lines show the specific magnitude of each fluctuation.

[0053] As shown in the figure, the mean synergistic index of osmotic regulators was lowest during the seedling stage, at approximately 0.83, and then significantly increased to approximately 1.02 during the bolting stage, with fluctuations ranging from [missing value]. The maximum value indicates a significant change in the synergistic level of osmotic regulators from the seedling stage to the bolting stage. The index further increases from the bolting stage to reach a peak of approximately 1.12 during the flowering stage, with fluctuations ranging from [missing value]. This indicates that there is still a relatively significant fluctuation from the flowering stage to the pod-forming stage. The fluctuation range from the flowering stage to the pod-forming stage... The extremely low value indicates that the osmotic regulation substance synergy index tends to stabilize during this stage, and the index curve remains flat. From the pod-forming stage to maturity, the osmotic regulation substance synergy index shows a downward trend, with fluctuations... The value is also relatively large, indicating that the synergy index fluctuated significantly during this period.

[0054] The index distribution of root samples was generally higher than that of functional leaf samples, and showed a more concentrated data distribution across all growth stages, reflecting a relatively stable and significant synergistic response of the root system to osmotic regulators. In contrast, the index data of functional leaf samples were more dispersed, with a wider numerical range. The overall mean curve of the osmotic regulator synergy index showed a trend of first rising, then stabilizing, and then decreasing, reflecting the dynamic changes in the synergistic regulatory capacity of osmotic regulators throughout the entire growth period of rapeseed.

[0055] The data and fluctuation amplitude indicator lines shown in this figure correspond to the time series vectors obtained by calculating the arithmetic mean of the osmotic regulation substance synergy index at each growth stage in Example 2, and the fluctuation amplitudes of adjacent stages. This visually reflects the changes in the synergistic state of osmotic regulation substances at different stages of rapeseed growth and key fluctuation nodes, providing a basis for calculating the cumulative effect of fluctuation amplitude and identifying key response growth stages in Example 3. Significant fluctuation amplitudes are observed. and This indicates that the seedling stage to the flowering stem stage and the pod stage to maturity stage are the critical response growth period transition intervals.

[0056] Example 3:

[0057] In specific implementation, please refer to Figure 2 All four fluctuation amplitudes were obtained from the recorded data table of Example 2 and recorded sequentially as follows: , , , Each fluctuation amplitude is a dimensionless value. , , , The cumulative fluctuation range is obtained by summing the results. The cumulative fluctuation range is calculated as follows: ,in This represents the cumulative value of fluctuation amplitude, and is dimensionless.

[0058] From the time series vector of Example 2 Extracting the synergistic index of osmotic regulatory substances corresponding to five reproductive stages , , , , Calculate the arithmetic mean of the synergistic indices of these five osmotic adjustment substances to obtain the mean synergistic index. The method for calculating the mean synergistic index is as follows: ,in This represents the mean of the synergistic index, which is dimensionless.

[0059] Cumulative value of fluctuation amplitude Divide by the mean of the synergy index The volatility ratio is obtained by using the following formula:

[0060]

[0061] in, This represents the fluctuation ratio and is dimensionless. This represents the cumulative value of fluctuation amplitude, and is dimensionless. This represents the mean of the synergy index, which is dimensionless. In practical implementation, when the mean of the synergy index... When the value is not zero, the volatility ratio is calculated directly. .

[0062] volatility ratio The total number of growth stages is numerically fused with the total number of growth stages to generate a comprehensive evaluation index of rapeseed stress resistance. The total number of growth stages is set to 5, based on the fact that this invention divides the entire growth period of rapeseed into five standard growth stages: seedling stage, bolting stage, flowering stage, pod-setting stage, and maturity stage. Therefore, the total number of growth stages is fixed at 5. The specific method of numerical fusion is as follows: the fluctuation ratio is... Multiply by the square root of the total number of reproductive periods, that is, multiply by The comprehensive evaluation index of rapeseed stress resistance was obtained. The comprehensive evaluation index of rapeseed stress resistance was calculated using... The calculation formula is as follows:

[0063]

[0064] in, This represents the comprehensive evaluation index of rapeseed's stress resistance, and is dimensionless. 5 represents the fluctuation ratio, which is dimensionless; 5 represents the total number of reproductive periods, which is a dimensionless positive integer. The index is standardized by multiplying by the square root of the total number of reproductive periods, ensuring comparability of evaluation results across different reproductive period quantitative frameworks. It also reasonably amplifies the cumulative fluctuation effect reflected by the fluctuation ratio, enhancing the index's ability to characterize the stability of the synergistic state of osmotic regulatory substances throughout the entire reproductive period.

[0065] See Figure 7 In the figure, the horizontal axis represents the dimensionless value of the comprehensive evaluation index of rapeseed stress resistance, ranging from approximately 0.5 to 4.5, and the vertical axis represents the probability density value of the corresponding index interval. The figure shows the frequency distribution of the comprehensive evaluation index of stress resistance of multiple rapeseed samples calculated based on the method described in Example 3 in the form of a histogram with diagonal lines, and the probability density curve is superimposed to reflect the continuous distribution trend of the data.

[0066] The histogram shows that the comprehensive evaluation index of rapeseed stress resistance is mainly concentrated between 2.0 and 3.2, with a frequency peak in the range of approximately 2.6 to 2.9. This indicates that the comprehensive evaluation index of the vast majority of samples clusters within this range, reflecting a concentrated trend in the stress resistance performance of rapeseed. The probability density curve exhibits a unimodal distribution, and the index interval corresponding to the peak value is consistent with the frequency peak value of the histogram, further verifying the concentrated distribution characteristics of the data. The index distribution shows an approximately normal distribution, indicating that the comprehensive evaluation index of rapeseed stress resistance calculated through Example 3 has good statistical stability and representativeness.

[0067] The frequency and probability density of indices below 1.0 and above 3.6 are relatively low, indicating fewer samples showing extreme stress resistance, which aligns with the natural distribution of stress resistance in rapeseed populations. The overall curve exhibits good symmetry between its left and right tails, suggesting uniform coverage of the evaluation index across different stress resistance levels.

[0068] This figure reflects the distribution characteristics of the rapeseed stress resistance comprehensive evaluation index calculated by the method described in Example 3 within the sample population. It reveals the numerical concentration range and frequency distribution trend of the rapeseed stress resistance comprehensive evaluation index, laying a data foundation for subsequent stress resistance level classification and zoning analysis based on this index. This distribution characteristic is consistent with the stress resistance level range determined by percentile statistics based on large-sample field trial data in Example 4, supporting the effectiveness and practicality of the rapeseed stress resistance comprehensive evaluation index.

[0069] Example 4:

[0070] In specific implementation, please refer to Figure 3 Multiple preset stress resistance level threshold intervals are obtained, each interval corresponding to a stress resistance level identifier. These intervals include strong stress resistance, moderate stress resistance, and weak stress resistance. The stress resistance level identifier for the strong stress resistance interval is "strong stress resistance," for the moderate stress resistance interval it is "moderate stress resistance," and for the weak stress resistance interval it is "weak stress resistance." The boundary values ​​of each interval are pre-calibrated using percentile statistics from large-sample field trial data.

[0071] The specific process for pre-calibrating the percentile statistical method for large-sample field trial data is as follows: At least 200 sets of field trial data from multiple rapeseed varieties in multiple ecological regions are collected. For each set of field trial data, a corresponding rapeseed stress resistance comprehensive evaluation index is generated according to the method described in Example 3. All rapeseed stress resistance comprehensive evaluation indices are sorted from smallest to largest, and the 33.3 percentile and 66.7 percentile are calculated. The 33.3 percentile serves as the boundary between the weak stress resistance interval and the moderate stress resistance interval, and the 66.7 percentile serves as the boundary between the moderate stress resistance interval and the strong stress resistance interval. The range of the weak stress resistance interval is where the rapeseed stress resistance comprehensive evaluation index is less than the 33.3 percentile; the range of the moderate stress resistance interval is where the rapeseed stress resistance comprehensive evaluation index is greater than or equal to the 33.3 percentile and less than the 66.7 percentile; and the range of the strong stress resistance interval is where the rapeseed stress resistance comprehensive evaluation index is greater than or equal to the 66.7 percentile.

[0072] The rapeseed stress resistance comprehensive evaluation index generated in Example 3 was compared sequentially with the strong stress resistance interval, the medium stress resistance interval, and the weak stress resistance interval to determine the target threshold interval into which the rapeseed stress resistance comprehensive evaluation index fell. The comparison process was as follows: the rapeseed stress resistance comprehensive evaluation index was first compared with the upper limit of the weak stress resistance interval, i.e., the 33.3 percentile. If the rapeseed stress resistance comprehensive evaluation index was less than the 33.3 percentile, the target threshold interval was determined to be the weak stress resistance interval; if the rapeseed stress resistance comprehensive evaluation index was greater than or equal to the 33.3 percentile, it was then compared with the 66.7 percentile. If the rapeseed stress resistance comprehensive evaluation index was less than the 66.7 percentile, the target threshold interval was determined to be the medium stress resistance interval; if the rapeseed stress resistance comprehensive evaluation index was greater than or equal to the 66.7 percentile, the target threshold interval was determined to be the strong stress resistance interval.

[0073] Extract the stress resistance level identifier corresponding to the target threshold interval and output it as the current stress resistance level of rapeseed. If the target threshold interval is a strong stress resistance interval, output "strong stress resistance"; if the target threshold interval is a medium stress resistance interval, output "medium stress resistance"; if the target threshold interval is a weak stress resistance interval, output "weak stress resistance".

[0074] Four fluctuation amplitudes recorded from Example 2 , , , The target fluctuation range with the largest value is selected from the data. The selection method is as follows: , , , The values ​​are compared pairwise, and the largest value is retained as the target fluctuation range. If two or more fluctuation ranges have the same maximum value, the fluctuation range that appears first in the time series is selected as the target fluctuation range.

[0075] Obtain the starting and ending growth periods corresponding to the target fluctuation range. From the data table recorded in Example 2, find the associated stored names of the starting and ending growth periods based on the sequence number of the target fluctuation range. Mark both the starting and ending growth periods as the critical response growth period. The critical response growth period represents the growth stage transition interval in rapeseed where the synergistic level of osmotic regulators changes most significantly, indicating the key time window for rapeseed to make a strong osmotic regulation response to stress.

[0076] The comprehensive evaluation index of rapeseed stress resistance generated in Example 3 was used as the primary evaluation indicator, and the critical response reproductive period was used as the secondary evaluation indicator. The primary and secondary evaluation indicators were filled in according to a preset report template. The preset report template contains three content areas: the first area is the "Comprehensive Evaluation Index of Stress Resistance" field and its corresponding numerical display position; the second area is the "Stress Resistance Level" field and its corresponding level identifier display position; and the third area is the "Critical Response Reproductive Period" field and its corresponding reproductive period name display position. The numerical value of the primary evaluation indicator was filled in the first area, the stress resistance level identifier was filled in the second area, and the names of the start and end reproductive periods in the critical response reproductive period were connected by hyphens and filled in the third area.

[0077] In the report template, indicate the direction of change in the osmotic regulatory substance synergy index during the critical response reproductive period. The direction of change in the osmotic regulatory substance synergy index is determined based on the two osmotic regulatory substance synergy indices corresponding to the target fluctuation range: Obtain the two osmotic regulatory substance synergy indices corresponding to the target fluctuation range. and ,in This is the sequence number corresponding to the target fluctuation range. If... If the numerical change is upward; if If the numerical value changes in the direction of decrease; if If the value changes in a certain direction, then the direction of change is the same. The direction of change should be indicated in text format after the content entered in the third area of ​​the report template.

[0078] The output includes a resilience assessment report containing the main assessment indicators, secondary assessment indicators, and the direction of numerical change. The complete content format of the resilience assessment report is as follows: "Comprehensive Resilience Evaluation Index: [Value]; Resilience Level: [Level Indicator]; Key Response Fertility Period: [Name of Initial Fertility Period] - [Name of End Fertility Period], Direction of Change: [Increasing / Decreasing / Stabilizing]".

[0079] See Figure 8In the figure, the horizontal axis represents the sample number, and the vertical axis represents the value of the comprehensive evaluation index of rapeseed stress resistance (dimensionless). The legend indicates the sample distribution of the three stress resistance levels and the two key percentile threshold lines, where the dashed line represents the 33.3 percentile (the boundary between weak and moderate stress resistance), and the dotted line represents the 66.7 percentile (the boundary between moderate and strong stress resistance).

[0080] In the figure, samples marked with circles represent the weak stress resistance level, with their comprehensive stress resistance evaluation index mainly distributed between 0.4 and 1.6. Within this range, the sample points are relatively concentrated and show no significant dispersion, indicating that the overall comprehensive evaluation index of the weak stress resistance samples is low and stable. Samples marked with squares represent the medium stress resistance level, with their comprehensive evaluation index distributed between approximately 1.6 and 2.4. The sample points are evenly distributed within this range, showing that the index value of the medium stress resistance samples is significantly higher than that of the weak stress resistance samples and is at an intermediate level. Samples marked with triangles represent the strong stress resistance level, with their comprehensive evaluation index ranging from 2.4 to 4.2 and exhibiting high dispersion overall. This indicates that the comprehensive index value of the strong stress resistance samples has a wider range, and some samples show significant stress resistance performance.

[0081] Two percentile threshold lines clearly delineate three stress resistance level intervals, corresponding to the distribution intervals of different labeled samples in the figure, verifying the rationality and effectiveness of the stress resistance level classification determined by the percentile statistical method based on large-sample field trial data in Example 4. Overall, the sample numbers in the figure, from left to right, cover the three intervals of weak stress resistance, moderate stress resistance, and strong stress resistance, reflecting the distribution characteristics of the rapeseed stress resistance comprehensive evaluation index in the sample population and the scientific nature of the level classification. This figure, together with the threshold lines, can intuitively display the stress resistance levels of different rapeseed varieties or treatment samples and their corresponding comprehensive evaluation index ranges, providing an effective numerical reference for rapeseed stress resistance evaluation and screening.

[0082] Example 5:

[0083] In specific implementation, please refer to Figure 4In multiple different treatment plots of the same rapeseed variety, the steps of obtaining soluble protein content data and soluble sugar content data and calculating the osmotic regulation substance synergistic index in Example 1 were performed; the steps of constructing time series vectors and calculating fluctuation amplitude in Example 2 were performed; and the steps of generating rapeseed stress resistance comprehensive evaluation index in Example 3 were performed to obtain the rapeseed stress resistance comprehensive evaluation index corresponding to each treatment plot. The number of treatment plots was set to at least five, and each treatment plot used the same rapeseed variety but applied different tillage or fertilization methods. The area of ​​each treatment plot was 20 square meters, and protective rows with a width of 1 meter were set between plots. At the seedling stage, bolting stage, flowering stage, pod stage and maturity stage of rapeseed, five rapeseed plants were randomly selected from each treatment plot, and root samples and functional leaf samples were collected according to the method described in Example 1. The supernatant was extracted and the soluble protein content data and soluble sugar content data were measured. For each treatment plot, the osmotic regulation substance synergistic index of the treatment plot in each of the five growth stages is calculated according to the method described in Example 1. Then, the time series vector is constructed and four fluctuation amplitudes are calculated according to the method described in Example 2. Finally, the comprehensive evaluation index of rapeseed stress resistance corresponding to the treatment plot is generated according to the method described in Example 3.

[0084] The actual yield data for each treatment plot at maturity was obtained. The actual yield data was obtained as follows: At rapeseed maturity, a central harvesting area of ​​10 square meters was demarcated from each treatment plot, excluding the sampled plants. All rapeseed plants within the central harvesting area were harvested at ground level, threshed, and the seed weight was measured. The actual yield data was obtained by converting the weight to a standard moisture content of 9%. The actual yield data was expressed in kilograms per hectare.

[0085] Calculate the correlation deviation between the comprehensive evaluation index of rapeseed stress resistance and the actual yield data in each treatment plot. The correlation deviation is calculated using the following formula:

[0086]

[0087] in, This represents the correlation deviation value, which is dimensionless. This represents the comprehensive evaluation index of rapeseed stress resistance corresponding to a certain treatment plot, and is dimensionless; This represents the arithmetic mean of the comprehensive evaluation index of rapeseed stress resistance corresponding to all treated plots, and is dimensionless. This represents the actual yield data corresponding to a specific processing area, expressed in kilograms per hectare. This represents the arithmetic mean of the actual yield data for all processed plots, expressed in kilograms per hectare. It represents the absolute value of the difference between the comprehensive evaluation index of rapeseed stress resistance in a certain treatment plot and the mean of the comprehensive evaluation index of rapeseed stress resistance in all treatment plots; It represents the absolute value of the difference between the actual output data of a certain processing cell and the mean of the actual output data of all processing cells.

[0088] The calculated correlation deviation value The result is compared with a preset verification threshold. The preset verification threshold is set to 0.20, which is determined based on statistical data on the coefficient of variation of rapeseed yield: under normal cultivation conditions, the coefficient of variation of rapeseed yield usually does not exceed 20%, and 0.20 is used as the correlation deviation value. The maximum allowable upper limit, when the correlation deviation value of a certain processing cell is... When the index is less than 0.20, the deviation between the rapeseed stress resistance comprehensive evaluation index and the actual yield data is within the normal fluctuation range, confirming the validity of the rapeseed variety's comprehensive stress resistance evaluation index. When the correlation deviation value exceeds 80% of all treatment plots... When all values ​​are less than 0.20, the overall comprehensive evaluation index of the rapeseed resistance of this rapeseed variety is confirmed to be effective.

[0089] A comprehensive evaluation index of rapeseed stress resistance was obtained under multiple combinations of different tillage and fertilization methods. Tillage methods included no-till, shallow rotary tillage, and deep tillage; fertilization methods included conventional fertilization, application of supplemental organic fertilizer, and controlled-release fertilizer. The three tillage methods and three fertilization methods were completely combined to form nine treatment combinations. In the plots corresponding to each treatment combination, the comprehensive evaluation index of rapeseed stress resistance was generated according to the methods described in Examples 1, 2, and 3.

[0090] The comprehensive evaluation index of rapeseed stress resistance for the nine treatment combinations was sorted from largest to smallest. After sorting, the treatment combinations corresponding to the top three comprehensive evaluation indices of rapeseed stress resistance were selected as candidate optimization combinations. The selection of the top three was based on the following criteria: the top one-third of the nine treatment combinations represent the candidate combinations with the best overall performance, which can effectively screen out the most favorable combination of cultivation and fertilization methods to improve rapeseed stress resistance.

[0091] Output a list of treatment parameters for candidate optimization combinations. The list includes the tillage method name, fertilization method name, and corresponding rapeseed stress resistance comprehensive evaluation index for each candidate optimization combination. The list is presented in tabular form, with the first column being the candidate optimization combination number, the second column being the tillage method, the third column being the fertilization method, and the fourth column being the rapeseed stress resistance comprehensive evaluation index. Output the treatment parameter list to a display device or printer to guide the optimal selection of tillage and fertilization methods in rapeseed cultivation management.

[0092] See Figure 9In the figure, the horizontal axis represents the comprehensive evaluation index of rapeseed's stress resistance (dimensionless), with values ​​ranging from approximately 0.8 to 5, and the vertical axis represents the actual yield data (kilograms per hectare), with values ​​ranging from approximately 2400 to 3500. Two different marking symbols are used in the figure to distinguish correlation deviation values. The size, the empty circle symbol represents the correlation deviation value The cross indicates the correlation deviation value. According to the definition in Example 5, the associated deviation value This is used to measure the deviation between the comprehensive evaluation index of rapeseed stress resistance and the actual yield data. 0.20 is the preset verification threshold.

[0093] The data points in the figure are mainly distributed in the range of approximately 1.0 to 4.5 for the comprehensive evaluation index of rapeseed stress resistance and approximately 2500 to 3400 kg / ha for actual yield. Data points with empty circles are concentrated between approximately 1 and 3 for the comprehensive evaluation index, and the actual yield is mostly concentrated in the range of 2700 to 3200 kg / ha, indicating that the deviation between the evaluation index and yield data is within the normal fluctuation range, confirming that the comprehensive evaluation index of this rapeseed variety is effective in most treatment plots. Data points with crosses are more dispersed, including ranges with evaluation indices below 2 and above 3, and the corresponding actual yield data fluctuates significantly, indicating that the correlation deviation value of the relevant treatment plots exceeds the verification threshold, and the deviation between the evaluation index and actual yield is large.

[0094] This figure fully reflects the correlation between the comprehensive stress resistance evaluation index and actual yield data collected from plots treated with different tillage and fertilization methods in Example 5, verifying the effectiveness and applicability of the evaluation index. (Correlation deviation value) The distribution clearly demonstrates that the evaluation index meets the deviation threshold requirement in over 80% of the treatment areas, conforming to the validation criteria. The legend further visually illustrates the deviation level between the evaluation index and the actual yield, providing data support for the practicality of the evaluation method.

[0095] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A method for evaluating the stress resistance of rapeseed based on osmotic regulators, characterized in that, The method includes: To obtain data on the soluble protein content and soluble sugar content of rapeseed at different growth stages; The synergistic increment between the soluble protein content data and the soluble sugar content data in each reproductive stage is calculated to obtain the osmotic regulation substance synergistic index for each reproductive stage. A time series vector is constructed based on the osmotic regulatory substance synergistic index for all reproductive periods, and the fluctuation amplitude of the time series vector between adjacent reproductive periods is calculated. A comprehensive evaluation index of rapeseed stress resistance is generated based on the cumulative effect of all the aforementioned fluctuation amplitudes.

2. The method for evaluating the stress resistance of rapeseed based on osmotic regulating substances according to claim 1, characterized in that, The acquisition of soluble protein content data and soluble sugar content data of rapeseed at different growth stages includes: Root samples and functional leaf samples of rapeseed were collected at the seedling stage, bolting stage, flowering stage, pod stage and maturity stage. The root samples and the functional leaf samples were subjected to tissue homogenization and centrifugation, respectively, and the supernatant was extracted. The soluble protein content data were obtained by analyzing the supernatant using the Coomassie brilliant blue staining method. The soluble sugar content data were obtained by detecting the supernatant using the anthrone colorimetric method.

3. The method for evaluating the stress resistance of rapeseed based on osmotic regulating substances according to claim 2, characterized in that, The calculation of the synergistic increment between the soluble protein content data and the soluble sugar content data in each reproductive stage yields the osmotic regulatory substance synergistic index for each reproductive stage, including: The soluble protein content data and soluble sugar content data from the same sample source during the same reproductive period are numerically aligned to obtain the protein value and sugar value, respectively. Calculate the product between the protein value and the sugar value to obtain the first intermediate product; Calculate the sum between the protein value and the sugar value to obtain a first sum; Divide the first intermediate product by the first sum, and then multiply by the preset weighting coefficient corresponding to the reproductive period and the sample source to obtain the osmotic regulation substance synergistic index.

4. The method for evaluating the stress resistance of rapeseed based on osmotic regulating substances according to claim 3, characterized in that, The preset weighting coefficients are determined using the analytic hierarchy process (AHP) based on the degree of dependence of rapeseed on osmotic regulation at different growth stages.

5. The method for evaluating the stress resistance of rapeseed based on osmotic regulating substances according to claim 3, characterized in that, The step of constructing a time series vector based on the osmotic regulatory substance synergistic index for all reproductive periods, and calculating the fluctuation amplitude of the time series vector between adjacent reproductive periods, includes: The osmotic regulation substance synergistic indices corresponding to each growth stage are arranged sequentially according to the order of seedling stage, flowering stage, pod stage and maturity stage to form the time series vector; Starting from the second element of the time series vector, the absolute value of the difference between the current element and the previous element is calculated sequentially to obtain multiple fluctuation amplitudes; Record the start and end of the reproductive period corresponding to each fluctuation range.

6. The method for evaluating the stress resistance of rapeseed based on osmotic regulating substances according to claim 5, characterized in that, A comprehensive evaluation index for rapeseed stress resistance is generated based on the cumulative effect of all the aforementioned fluctuation amplitudes, including: Sum all the fluctuation amplitudes to obtain the cumulative fluctuation amplitude value; Calculate the arithmetic mean of the synergistic indices of all the aforementioned osmotic conditioning substances to obtain the mean synergistic index; Divide the cumulative value of the volatility by the mean of the synergistic index to obtain the volatility ratio; The fluctuation ratio is numerically fused with the total number of growing seasons to generate the comprehensive evaluation index of rapeseed stress resistance.

7. The method for evaluating the stress resistance of rapeseed based on osmotic regulating substances according to claim 6, characterized in that, The total number of the reproductive periods is 5, and the comprehensive evaluation index of rapeseed stress resistance is generated by standardizing the fluctuation ratio by multiplying it by the square root of the total number of reproductive periods.

8. The method for evaluating the stress resistance of rapeseed based on osmotic regulating substances according to claim 6, characterized in that, After numerically fusing the fluctuation ratio with the total number of growth periods to generate the rapeseed stress resistance comprehensive evaluation index, the process further includes a step of determining the rapeseed stress resistance level based on the rapeseed stress resistance comprehensive evaluation index. This step specifically involves: Obtain multiple preset stress resistance level threshold ranges, each of which corresponds to a stress resistance level identifier; The comprehensive evaluation index of rapeseed stress resistance is compared with each stress resistance level threshold interval in turn to determine the target threshold interval into which the comprehensive evaluation index of rapeseed stress resistance falls. Extract the stress resistance level identifier corresponding to the target threshold range and output it as the current stress resistance level of rapeseed.

9. The method for evaluating the stress resistance of rapeseed based on osmotic regulating substances according to claim 8, characterized in that, The multiple stress resistance level threshold intervals include strong stress resistance interval, medium stress resistance interval and weak stress resistance interval, and the boundary values ​​of each interval are pre-calibrated by percentile statistics of large sample field test data.

10. The method for evaluating the stress resistance of rapeseed based on osmotic regulating substances according to claim 8, characterized in that, After determining the stress resistance level of rapeseed based on the comprehensive evaluation index of rapeseed stress resistance, the next step is to determine the critical response growth period, which specifically involves: Select the target fluctuation amplitude with the largest value from all the fluctuation amplitudes described; Obtain the starting period of childbearing and the ending period of childbearing corresponding to the target fluctuation range; The initiation period and the end period of reproduction are collectively marked as the critical response period of reproduction.

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