Rice seedling cold resistance analysis system and method

Abstract

The invention discloses a rice seedling cold resistance analysis system, which relates to the technical field of rice planting and comprises an environment control module, a data acquisition module, a data analysis module and a cold resistance evaluation module, the environment control module is used for regulating and controlling temperature environment parameters of rice seedling growth and setting different temperature conditions; the data acquisition module is used for acquiring parameters of rice seedlings before and after treatment, including seedling height, leaf chlorophyll content and withering rate. The invention further discloses a rice seedling cold tolerance analysis method. According to the cold resistance method provided by the invention, the expressions of different rice varieties under various low-temperature treatment durations can be comprehensively covered, and the cold resistance characteristics of the varieties extremely sensitive to low temperature or the varieties relatively resistant to cold can be fully excavated and embodied through scientific analysis means; the cold resistance of the rice in the seedling stage is identified more accurately, and the scientificity and the accuracy of the cold resistance research of the rice are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of rice cultivation, and specifically relates to a rice seedling cold tolerance analysis system and method. Background Art

[0002] As a common staple food on the tables of Asians, rice plays a crucial role in ensuring world food security due to its strong adaptability and wide planting range. China is a major rice-growing country. Approximately 90% of the world's rice is grown in Asia, and China's rice output accounts for as high as 45% of the world's total rice output. However, as a thermophilic crop, due to global climate change and various environmental conditions, its growth environment has been more affected and challenged. All stages of its growth and development have to withstand the test of cold. The loss of rice yield caused by low temperature is a worldwide problem. Rice grown in different regions will be affected by various degrees and types of low temperature. In China, large-scale cold damage occurs on average every 4 to 5 years, resulting in a sharp reduction in rice harvest, or even a complete failure of the crop.

[0003] In the prior art, the main method for identifying the cold tolerance of rice seedlings at the seedling stage is: treating the seedlings at the 2-3 leaf stage at a temperature of 5°C for 7 days, and then recovering at room temperature for 6 days, and evaluating with the seedling death rate. For most rice seedling varieties at the 2-3 leaf stage, they all died after being treated at 5°C for 2 days, 3 days, 4 days, 5 days or 6 days. The mortality rate of variety A reached 100% after being treated at 5°C for 2 days, while the mortality rate of variety B reached 100% after being treated at 5°C for 5 days. Obviously, the cold resistance of variety B is stronger than that of variety A. However, if the existing method is used to evaluate the cold resistance of varieties A and B, the cold resistance of varieties A and B is the same, which is obviously incorrect and there is an error in the analysis. For this reason, we propose a rice seedling cold tolerance analysis system and method. Summary of the Invention

[0004] To solve the above technical problems, a rice seedling cold tolerance analysis system and method are provided, and this technical solution solves the above problems.

[0005] To achieve the above object, the technical solution adopted by the present invention is: a rice seedling cold tolerance analysis system, including: an environment control module, a data acquisition module, a data analysis module, and a cold tolerance evaluation module;

[0006] The environment control module is used to regulate the temperature environment parameters for the growth of rice seedlings and set different temperature conditions;

[0007] The data acquisition module is used to collect the parameters of rice seedlings before and after treatment, including seedling height, leaf chlorophyll content, and death rate;

[0008] The data analysis module conducts statistical analysis on the collected parameter data, determines the indicators using the principal component analysis method, and calculates the comprehensive index eigenvalue and contribution rate.

[0009] The cold tolerance evaluation module calculates the comprehensive evaluation value of the cold tolerance of rice strains at the seedling stage through the comprehensive index membership function, determines the strength of the cold tolerance of rice strains at the seedling stage according to the size of the comprehensive evaluation value, and analyzes and evaluates the cold tolerance of rice seedlings.

[0010] Preferably, the temperature regulation range in the environment control module is 0°C - 30°C, and the temperature is automatically adjusted according to the preset program. When conducting the cold tolerance test of rice seedlings, set the low-temperature treatment time from 1d to 7d. Based on the temperature sensor, the ambient temperature is monitored in real time. When the temperature deviates from the set value, the heating or cooling device responds to regulate the temperature within the range and provide the test environment.

[0011] Preferably, when the data acquisition module measures the height of rice seedlings, a measuring ruler is used for measurement. The measuring ruler is vertically placed from the base to the tip of the rice seedlings for measurement, and the data is recorded. For the measurement of the chlorophyll content of rice leaves, a chlorophyll meter is used. Multiple measurement points are selected at the same part of the rice leaves to take the average value, and the number of measurements is more than 3 groups. When measuring the mortality rate of rice seedlings at the seedling stage, multiple repeated samples are set for each rice strain, and the number of repetitions is more than 5 times. When counting the number of dead seedlings, it is checked manually one by one. The staff distinguishes the dead seedlings and calculates the mortality rate. The calculation formula is: A = (B / C) * 100%, where A is the mortality rate, B is the number of whole-plant deaths, and C is the total number of plants.

[0012] Preferably, when the data analysis module conducts principal component analysis, the data is pre-standardized. The standardization formula is:

[0013]

[0014] where Z is the value after standardization, y is the original data, is the mean value, S is the standard deviation. Calculate the correlation coefficient matrix from the pre-standardized data, and then solve the characteristic equation to obtain the eigenvalues and eigenvectors. When determining the principal components, select the principal components with eigenvalues greater than 1, and calculate the contribution rate of each principal component. The calculation formula is:

[0015]

[0016] where V is the contribution rate, E is the eigenvalue, and n' is a positive integer representing the number of summation terms.

[0017] Preferably, when calculating the comprehensive eigenvalue, set the original data matrix as F, pre-standardize the original data matrix F to obtain the standardized data matrix G, and calculate the covariance matrix of G, O = (1 / h - 1)G PG, where O is the covariance matrix that measures the overall error between two variables, h is the number of samples, G is the standardized data matrix, and G P is the transpose of matrix G;

[0018] Solve for the covariance, |O - λI’| = 0, where λ is the eigenvalue and I’ is the q*q identity matrix; several eigenvalues are obtained, which are the eigenvalues of the comprehensive index.

[0019] Preferably, for the calculation of the membership function value of the comprehensive index by the cold tolerance evaluation module, when there are multiple comprehensive indexes, calculate the membership function value of each comprehensive index separately. The calculation formula is:

[0020]

[0021] where X i represents the value of the i-th comprehensive index in each test material, X min represents the minimum value, X max represents the maximum value, and U(X i ) is the membership function value of the comprehensive index.

[0022] Preferably, calculate the weight value of each comprehensive index. The calculation formula is:

[0023]

[0024] where P i is the contribution rate of the i-th comprehensive index of all test materials, and W i is the weight value;

[0025] Finally, perform weighted summation to calculate the comprehensive evaluation value of cold tolerance. The calculation formula is:

[0026]

[0027] where D is the comprehensively calculated evaluation value; the greater the comprehensive evaluation value of a certain strain, the stronger the cold tolerance of the strain.

[0028] Preferably, the environmental control module simulates the day-night temperature change patterns in different regions. During the low-temperature treatment period, set the daytime low-temperature duration to 8 - 12 h and the nighttime low-temperature duration to 12 - 16 h to simulate the temperature fluctuations in the natural environment.

[0029] A method for analyzing the cold tolerance of rice seedlings. The analysis steps are:

[0030] S1. Use the environmental control module to set different temperature conditions to regulate the temperature environment for the growth of rice seedlings;

[0031] S2. Before the experiment, collect parameters of the rice seedlings;

[0032] S3. Conduct tests by treating the rice plants involved in cold tolerance evaluation at 5°C for 1 day, 2 days, 3 days, 4 days, 5 days, 6 days, and 7 days respectively.

[0033] S4. The data analysis module conducts statistical analysis on the collected parameter data. After recovering at room temperature for 6 days, it statistically analyzes the total values of chlorophyll changes, plant height changes, and mortality rates of each rice plant involved in the evaluation after being treated at 5°C for 1 day, 2 days, 3 days, 4 days, 5 days, 6 days, and 7 days and then recovering.

[0034] S5. Calculate the comprehensive cold tolerance evaluation value of the rice lines at the seedling stage through the comprehensive index membership function for the data, determine the strength of the cold tolerance of the rice lines at the seedling stage according to the size of the comprehensive evaluation value, and analyze and evaluate the cold tolerance of the rice seedlings.

[0035] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0036] The cold tolerance method proposed by the present invention can comprehensively cover the performance of different rice varieties under various low-temperature treatment durations. Whether it is a variety extremely sensitive to low temperature or a relatively cold-tolerant variety, their respective cold tolerance characteristics can be fully explored and reflected through scientific analysis means. The identification of the cold tolerance of rice seedlings at the seedling stage is more accurate, which improves the scientificity and accuracy of rice cold tolerance research and also provides a reference idea for the research on other crops in the agricultural field to cope with low-temperature stress. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 It is a framework diagram of the cold tolerance analysis system of the present invention;

[0038] Figure 2 It is a cluster analysis diagram of the cold tolerance of 20 tested rice lines at the seedling stage based on D of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0039] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments in the following description are only examples, and those skilled in the art can think of other obvious variations.

[0040] A method for analyzing the cold tolerance of rice seedlings, and the analysis steps are as follows:

[0041] S1. Use the environmental control module to set different temperature conditions to regulate the temperature environment for the growth of rice seedlings;

[0042] S2. Before conducting the test, collect parameters of the rice seedlings;

[0043] S3. Conduct tests by treating the rice plants involved in cold tolerance evaluation at 5°C for 1 day, 2 days, 3 days, 4 days, 5 days, 6 days, and 7 days respectively.

[0044] S4. The data analysis module conducts statistical analysis on the collected parameter data. After 6 days of recovery at room temperature, it calculates the total values of changes in chlorophyll content, plant height, and mortality rate of each rice variety participating in the evaluation after being treated at 5°C for 1 day, 2 days, 3 days, 4 days, 5 days, 6 days, and 7 days of recovery.

[0045] S5. Calculate the comprehensive cold tolerance evaluation value of rice varieties at the seedling stage through the comprehensive index membership function for the data, and determine the strength of cold tolerance of rice varieties at the seedling stage according to the size of the comprehensive evaluation value, for the analysis and evaluation of cold tolerance of rice seedlings.

[0046] Specific experiment

[0047] Table 1 below shows the detailed information table of rice varieties used in this experiment

[0048]

[0049]

[0050] Table 1

[0051] Experimental design:

[0052] For the rice varieties treated at the seedling stage, soaking and germination acceleration started on March 9. After disinfecting the rice seeds with 5% H2O2 for 5 minutes, soak them in clean water for 24 hours, and accelerate germination at 30°C for 48 hours. Sow the seeds on March 12. Select seeds with good germination and consistent germination status (root length 1 cm, bud length 0.5 cm). Sow 35 pots for each variety, with 30 seeds evenly sown in each pot, totaling 700 pots. Conduct conventional water and fertilizer management, and keep the soil fertility and management measures of each pot consistent.

[0053] After the seeds are soaked and germinated and sowing is completed, when they grow to the 2 - 3 leaf stage, the rice varieties participating in the evaluation are respectively treated at 5°C for 1 day, 2 days, 3 days, 4 days, 5 days, 6 days, and 7 days. After 6 days of recovery at room temperature, calculate the total values of changes in chlorophyll content, plant height, and mortality rate of each rice variety participating in the evaluation after being treated at 5°C for 1 day, 2 days, 3 days, 4 days, 5 days, 6 days, and 7 days of recovery.

[0054] Determination of the dead seedling rate of rice seedlings

[0055] Determine the number of dead seedlings after the end of low - temperature treatment at the seedling stage and after 7 days of recovery;

[0056] Dead seedling rate = [(total number of dead plants) / (total number of plants)] × 100%

[0057] Determination of rice seedling height

[0058] Use a 50 - cm long scale for measurement;

[0059] Determination of chlorophyll content in rice leaves

[0060] The SPAD value was measured using a SPAD-502 chlorophyll meter;

[0061] For the measured original data, the comprehensive index membership degree formula was used for processing to comprehensively evaluate the cold tolerance of each rice strain at the seedling stage. The calculation of the membership function value referred to the method of Cheng Lu. Finally, the cold tolerance of each rice strain at the seedling stage was determined according to the size of the comprehensive evaluation value. If the comprehensive evaluation value of a certain strain was larger, the cold tolerance of that strain was stronger.

[0062] Result analysis:

[0063] Table 2 shows the results of the cold tolerance identification of 20 tested rice strains at the seedling stage through the withering rate. By observing and analyzing Table 2, it can be seen that for the rice at the seedling stage, such as Black Glutinous, Chujing 27, Red Fruit 8, Changjing 7, Chujing 48, Jinjingnuo 3, ND4-1, Jinjingnuo 4, Jian No. 1, Huijing 19, Yijing 1, Yunjing 37, Hefuhonggu, Liaojing 212, Honglangman, and ILimibyeo, the cold tolerance level is 1, 2, or 3. The materials that are not cold-tolerant are X32 and Yunnan Red Valley, and their cold tolerance levels are both 9. For other materials, such as Y2 and Green Rice, their cold tolerance levels are 4 or 5, and their cold tolerance is between the above two types. From the results of the cold tolerance identification of 20 tested rice strains at the seedling stage, it can be found that the cold tolerance of different rice strains at the seedling stage can be roughly divided into three types, namely cold-tolerant, not cold-tolerant, and moderately cold-tolerant. Thus, the relevant genotypes of the cold-tolerant, not cold-tolerant, and moderately cold-tolerant rice strains at the seedling stage can be identified, and then rice strains with cold tolerance at the seedling stage can be selected to jointly cultivate improved varieties with good cold tolerance at other growth stages to resist the agricultural production reduction or even crop failure caused by the rotten seedling phenomenon due to cold damage at the rice seedling stage.

[0064] The following Table 2 is the cold tolerance identification table of different rice strains at the seedling stage

[0065]

[0066]

[0067] Table 2 The following Table 3 is the table of the change in seedling height of different rice strains before and after low-temperature treatment at the seedling stage

[0068]

[0069]

[0070] Table 3

[0071] Table 3 shows the change in seedling height of 20 tested rice strains before and after low-temperature treatment at the seedling stage. By observing and analyzing Table 3, it can be seen that for the rice at the seedling stage, the degree of change in seedling height of different rice strains is basically consistent with the cold tolerance shown after low-temperature treatment in the artificial climate chamber.

[0072] Table 4 below shows the changes in chlorophyll content before and after low-temperature treatment at the seedling stage of different rice strains.

[0073]

[0074]

[0075] Table 4

[0076] Table 4 shows the changes in chlorophyll content before and after low-temperature treatment at the seedling stage of 20 tested rice strains. By observing and analyzing Table 4, it can be seen that for the rice strains at the seedling stage, low-temperature stress generally has a certain impact on the changes in chlorophyll content in the leaves at the seedling stage of rice. After artificial low-temperature stress, the chlorophyll content in the leaves at the seedling stage of the tested rice strains has all decreased. Moreover, the degree of change in chlorophyll content in the leaves of different rice strains is basically consistent with the cold tolerance shown after low-temperature treatment in the artificial climate chamber.

[0077] Table 5 below shows the correlation coefficient matrix table of each index at the seedling stage of rice under cold stress.

[0078]

[0079] Table 5

[0080] As can be seen from Table 5, among the 20 tested rice materials after artificial cold stress, the change rate of seedling height is significantly correlated with both the change rate of chlorophyll content and the death rate. Among them, the change rate of seedling height is extremely significantly negatively correlated with the death rate, and the correlation coefficient is the largest, reaching -0.827; the change rate of seedling height is significantly positively correlated with the change rate of chlorophyll content, and the correlation coefficient is 0.491. The change rate of chlorophyll content is significantly negatively correlated with the death rate, and the correlation coefficient is -0.542. From this, it can be seen that there is a significant correlation relationship among these three initial indicators, which will cause cross-overlap of information. Therefore, in this experiment, the principal component analysis method was used to comprehensively evaluate the cold tolerance of 20 tested rice materials at the seedling stage.

[0081] Table 6 below shows the eigenvalue and contribution rate table of each comprehensive index.

[0082]

[0083] Table 6

[0084] As can be seen from Table 6, the eigenvalue of the first principal component, that is, CI 1 is 2.253, which is greater than 0.90. At the same time, the contribution rate of the first principal component, that is, CI 1 is 75.11%, which is equivalent to its cumulative contribution rate reaching as high as 75.11%, indicating that it contains the vast majority of the main information. Therefore, in this experiment, the first principal component, that is, CI 1, this independent comprehensive index replaces the previous 3 initial indicators, thereby comprehensively evaluating the cold tolerance of 20 rice test materials at the seedling stage.

[0085] Table 7 is the factor loading matrix table of the comprehensive index values

[0086]

[0087] Table 7

[0088] As can be seen from Table 7, in the first principal component, that is, CI 1 among them, the factor loading of the dead seedling rate is the highest, which is -0.411; the factor loading of the seedling height change rate is medium, which is 0.403; the factor loading of the chlorophyll content change rate is 0.336. The factor loadings of these three indicators are all relatively high, so they are the main influencing factors of CI 1 .

[0089] The following Table 8 is the table of the comprehensive index values (CI), their weights (W), membership function values (U), cold tolerance evaluation values (D), and rankings of 20 rice lines under cold stress

[0090]

[0091]

[0092] Table 8

[0093] As can be seen from Table 8, for the same comprehensive index value CI 1 , in the case of 5°C cold stress, the comprehensive index value of "Heinuo", that is, CI 1 is the largest, up to 1.4368. At the same time, its relative membership function value, that is, U 1 =1, indicating that if the first principal component, that is, CI 1 is used as the evaluation index for the cold tolerance of 20 test rice materials at the seedling stage, the cold tolerance of the "Heinuo" line material at the seedling stage is the strongest; however, in the case of 5°C cold stress, the comprehensive index value of "X32", that is, CI 1 is the smallest, as low as -2.4450. At the same time, its relative membership function value, that is, U 1 =0, indicating that if the first principal component, that is, CI 1 is used as the evaluation index for the cold tolerance of 20 test rice materials at the seedling stage, the cold tolerance of the "X32" line material at the seedling stage is the weakest. By combining with the previous Wi, that is, the weight formula, and the comprehensive index, that is, CI 1 , the weight of the comprehensive index, that is, W 1 =0.7960. From this, it can also be seen that the first principal component, that is, CI 1, which accounts for a large weight. Through the D in the previous text, that is, the comprehensive cold tolerance evaluation value formula, the comprehensive cold tolerance evaluation values of 20 tested rice lines at the seedling stage can be obtained, as shown in Table 8, and there is a significant positive correlation between the comprehensive cold tolerance evaluation value D and cold tolerance.

[0094] According to the cold tolerance evaluation value, that is, the D value, determine the Euclidean distance as 5 from the cluster analysis dendrogram, and divide the cold tolerance of 20 tested rice lines at the seedling stage into 3 levels: strong cold tolerance, medium cold tolerance, and weak cold tolerance. From Figure 2 It can be seen that 14 lines, namely Heinuo, Changjing 7, Yunjing 37, Jian No. 1, Hongguo 8, Chujing 27, Jinjingnuo 3, Jinjingnuo 4, ND4-1, Huijing 19, Chujing 48, Liaojing 212, Honglangman, Yijing 1, belong to strong cold tolerance; 4 lines, namely Hefuhonggu, Y2, ILimibyeo, Lvmi, belong to medium cold tolerance; 2 lines, namely Yunnan Honggu, X32, belong to weak cold tolerance, which is basically consistent with the cold tolerance levels of each tested rice line at the seedling stage evaluated by the dead seedling rate above.

[0095] In this experiment, through 3 initial cold tolerance identification indicators, namely the morphological index of rice seedling height, dead seedling rate, and combined with the photosynthetic physiological index of chlorophyll content, the cold tolerance of 20 tested rice lines at the seedling stage was comprehensively evaluated. Through correlation factor analysis, it was found that there were correlations of varying degrees among the 3 initial indicators under cold stress; subsequently, through principal component analysis, the 3 initial indicators were equivalently converted into 1 independent comprehensive indicator; then combined with the membership function to calculate the weight of this comprehensive indicator and the comprehensive cold tolerance evaluation values of 20 tested rice lines at the seedling stage; finally, through cluster analysis, the 20 tested rice lines were divided into 3 different cold tolerance levels, and finally the order of cold tolerance strength of 20 tested rice lines at the seedling stage was obtained as: Heinuo > Changjing 7 > Yunjing 37 > Jian No. 1 > Hongguo 8 > Chujing 27 > Jinjingnuo 3 > Jinjingnuo 4 > ND4-1 > Huijing 19 > Chujing 48 > Liaojing 212 > Honglangman > Yijing 1 > Hefuhonggu > Y2 > ILimibyeo > Lvmi > Yunnan Honggu > X32.

[0096] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art of this industry should understand that the present invention is not limited by the above embodiments. What is described in the above embodiments and the specification is only the principle of the present invention. Without departing from the spirit and scope of the present invention, the present invention will have various changes and improvements, and these changes and improvements all fall within the scope of the present invention claimed.

Claims

1. A rice seedling cold tolerance analysis system, characterized in that: include: Environmental control module, data acquisition module, data analysis module and cold resistance evaluation module; The environmental control module is used to regulate the temperature environment parameters for the growth of rice seedlings and set different temperature conditions; The data collection module is used to collect parameters of rice seedlings before and after treatment, including seedling height, leaf chlorophyll content and death rate; The data analysis module performs statistical analysis on the collected parameter data, uses the principal component analysis method to determine the indicators, and calculates the characteristic value and contribution rate of the comprehensive indicators; The cold tolerance evaluation module calculates the comprehensive evaluation value of the cold tolerance of rice varieties at the seedling stage through the comprehensive index membership function, determines the cold tolerance of rice varieties at the seedling stage according to the size of the comprehensive evaluation value, and analyzes and evaluates the cold tolerance of rice seedlings.

2. A rice seedling cold tolerance analysis system according to claim 1, characterized in that: The temperature control range in the environmental control module is 0℃-30℃. The temperature is automatically adjusted according to the preset program. When conducting cold resistance tests on rice seedlings, the low temperature treatment time is set from 1d to 7d. The ambient temperature is monitored in real time based on the temperature sensor. When the temperature deviates from the set value, the heating or cooling device responds and adjusts the temperature within the range to provide a test environment.

3. A rice seedling cold tolerance analysis system according to claim 1, characterized in that: When measuring the height of rice seedlings, the data acquisition module uses a measuring ruler to measure, and the measuring ruler is placed vertically from the base of the rice seedlings to the tip of the leaf, and the measurement is performed and the data is recorded; for the determination of the chlorophyll content of rice leaves, a chlorophyll meter is used, and multiple measurement points are selected at the same part of the rice leaves to take the average value, and the measurement is more than 3 groups; When determining the mortality rate of rice seedlings, multiple repeated samples are set for each rice variety, and the number of repetitions is greater than 5 times. When counting the number of dead seedlings, the dead seedlings are manually inspected one by one, and the staff identifies the dead seedlings and calculates the mortality rate. The calculation formula is: A=(B / C)*100%, where A is the mortality rate, B is the number of dead plants, and C is the total number of plants.

4. A rice seedling cold tolerance analysis system according to claim 1, characterized in that: When the data analysis module performs principal component analysis, the data is standardized in advance. The standardization formula is: Where Z is the standardized value and y is the original data. is the mean, S is the standard deviation, the correlation coefficient matrix is ​​calculated through the standardized data, and then the characteristic equation is solved to obtain the eigenvalue and eigenvector; when determining the principal component, the principal component with an eigenvalue greater than 1 is selected, and the contribution rate of each principal component is calculated. The calculation formula is: Where V is the contribution rate, E is the eigenvalue, and n' is a positive integer representing the number of summation items.

5. A rice seedling cold tolerance analysis system according to claim 4, characterized in that: The original data matrix is ​​set as F, and the original data matrix F is standardized to obtain the standardized data matrix G. The covariance matrix of G is calculated, O = (1 / h-1)G P G, where O is the covariance matrix, measuring the overall error of the two variables, h is the number of samples, G is the standardized data matrix, G P is the transpose of matrix G; Solve the covariance, |O-λI'|=0, λ is the eigenvalue, I' is the q*q unit matrix; several eigenvalues ​​are obtained, which are the eigenvalues ​​of the comprehensive index.

6. A rice seedling cold tolerance analysis system according to claim 1, characterized in that: The cold resistance evaluation module calculates the membership function value of the comprehensive index. When there are multiple comprehensive indexes, the membership function value of each comprehensive index is calculated separately. The calculation formula is: Among them, X i represents the i-th comprehensive index value of each test material, X min Indicates the minimum value, X max Indicates the maximum value, U(X i ) is the membership function value of the comprehensive indicator.

7. A rice seedling cold tolerance analysis system according to claim 6, characterized in that: Calculate the weight value of each comprehensive indicator, the calculation formula is: Where P i is the contribution rate of the ith comprehensive index of all tested materials, W i is the weight value; Finally, the comprehensive evaluation value of cold resistance is calculated by weighted summation, and the calculation formula is: Where D is the evaluation value obtained by comprehensive calculation; the larger the comprehensive evaluation value of a certain variety is, the stronger the cold resistance of the variety is.

8. A rice seedling cold tolerance analysis system according to claim 1, characterized in that: The environmental control module simulates the day and night temperature variation patterns in different regions. During the low temperature treatment period, the daytime low temperature duration is set to 8-12 hours and the nighttime low temperature duration is set to 12-16 hours to simulate the temperature fluctuations of the natural environment.

9. A method for analyzing cold tolerance of rice seedlings, characterized in that: The analysis steps are: S1. Using the environment control module, setting different temperature conditions to regulate the temperature environment for the growth of rice seedlings; S2. Before the experiment, collect parameters of rice seedlings; S3. Conduct an experiment to treat the rice involved in the cold tolerance evaluation at 5°C for 1d, 2d, 3d, 4d, 5d, 6d and 7d respectively; S4, the data analysis module performs statistical analysis on the collected parameter data. After 6 days of recovery at room temperature, the total values ​​of chlorophyll changes, plant height changes and mortality rates of each rice participating in the evaluation after 1 day, 2 days, 3 days, 4 days, 5 days, 6 days and 7 days of recovery at 5°C are counted; S5. Calculate the comprehensive evaluation value of cold resistance of rice strains at the seedling stage through the comprehensive index membership function, determine the strength of cold resistance of rice strains at the seedling stage according to the size of the comprehensive evaluation value, and analyze and evaluate the cold resistance of rice seedlings.

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