Method for identifying accumulated temperature sensitivity of peas

Abstract

The invention discloses a method for identifying accumulated temperature sensitivity of peas. The method comprises the following steps: acquiring accumulated temperature resistance coefficients of a plurality of single characters of a to-be-detected variety of peas; converting the accumulated temperature resistance coefficients of the plurality of single characters into a unified membership degree; carrying out dimensionality reduction on the membership degrees of the plurality of single characters through principal component analysis to obtain a plurality of mutually independent comprehensive indexes, and calculating the variance contribution rate of each comprehensive index; taking the variance contribution rate as a weight, and calculating the sum of weighted membership degrees of the plurality of comprehensive indexes as a comprehensive evaluation score; and based on the comprehensive evaluation score of the to-be-detected variety of peas, determining the accumulated temperature sensitivity grade of the to-be-detected variety of peas. The method solves the problem that an advanced identification method for the accumulated temperature sensitivity of the peas is lacked.

Description

Methods for identifying the sensitivity of pea accumulated temperature Technical Field

[0001] This invention relates to the field of pea characteristic identification technology, specifically to a method for identifying the accumulated temperature sensitivity of peas. Background Technology

[0002] Against the backdrop of global warming and regional anomalies, the accumulated temperature patterns in various regions are undergoing significant changes. Different pea genotypes respond differently to accumulated temperature: temperature-sensitive peas are those varieties that, when grown in high-light-transmittance greenhouses, show significantly positive growth in plant and pod morphology compared to the open-field control, with a marked increase in pod yield; while temperature-insensitive peas are those varieties that, under the same greenhouse conditions, show no significant difference in plant and pod morphology or pod yield compared to the open-field control.

[0003] Re-planning open-field sowing times based on updated accumulated temperature data to match crop growth periods with high-temperature seasons, or regional layout based on the accumulated temperature tolerance characteristics of varieties and selecting suitable high / low latitude planting areas, will help to efficiently utilize light and temperature resources and improve crop yield and quality.

[0004] However, current research on crop accumulated temperature mainly focuses on its impact on phenotypic traits and grain quality. Although some studies have focused on the response mechanisms of peas to high and low temperature stress, there is still a lack of exploration into methods for identifying peas' sensitivity to accumulated temperature. Summary of the Invention

[0005] To overcome the shortcomings of existing technologies, a method for identifying the temperature sensitivity of peas is provided to address the lack of advanced methods for identifying the temperature sensitivity of peas.

[0006] To achieve the above objectives, a method for identifying the accumulated temperature sensitivity of peas is provided, comprising the following steps: obtaining the accumulated temperature tolerance coefficients of multiple individual traits of the pea variety to be tested; converting the accumulated temperature tolerance coefficients of the multiple individual traits into a unified membership degree; reducing the membership degrees of the multiple individual traits into multiple independent comprehensive indicators through principal component analysis, and calculating the variance contribution rate of each comprehensive indicator; using the variance contribution rate as a weight, calculating the weighted sum of the membership degrees of the multiple comprehensive indicators as a comprehensive evaluation score; and determining the accumulated temperature sensitivity level of the pea variety to be tested based on the comprehensive evaluation score.

[0007] Furthermore, principal component analysis was performed using SPSS 26.0 software.

[0008] Furthermore, the individual traits include plant height, bottom pod height, number of nodes, pod length, pod width, number of pods per plant, number of grains per plant, grain weight per plant, and weight of 100 fresh seeds.

[0009] Furthermore, the accumulated temperature sensitivity level includes accumulated temperature sensitive type, accumulated temperature intermediate type, and accumulated temperature insensitive type.

[0010] Furthermore, when the comprehensive evaluation score of the pea variety to be tested is greater than 4.0, the variety to be tested is determined to be of the temperature-sensitive type; when the comprehensive evaluation score of the pea variety to be tested is between 1.3 and 4.0, the variety to be tested is determined to be of the intermediate temperature-sensitive type; when the comprehensive evaluation score of the pea variety to be tested is less than 1.3, the variety to be tested is determined to be of the temperature-insensitive type.

[0011] The beneficial effects of this invention are that the method for identifying pea accumulated temperature sensitivity establishes and applies a set of pea accumulated temperature sensitivity evaluation systems based on different genotypes, determining the pea accumulated temperature type based on the D-value calculation results. This method provides a reference for future classification of pea accumulated temperature sensitivity levels, not only facilitating the systematic screening and evaluation of the accumulated temperature characteristics of different pea varieties, but also laying the foundation for further revealing the physiological and molecular mechanisms of pea response to temperature changes, thereby promoting the breeding and practical application of temperature-sensitive / insensitive pea varieties. Detailed Implementation

[0012] The present application will now be described in further detail with reference to the embodiments. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and not intended to limit the invention.

[0013] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. The present application will now be described in detail with reference to the embodiments.

[0014] This invention provides a method for identifying the accumulated temperature sensitivity of peas, comprising the following steps: S1, obtaining the accumulated temperature tolerance coefficients of multiple individual traits of the pea variety to be tested.

[0015] First, several individual traits of peas were screened and determined. In this embodiment, the individual traits include plant height, bottom pod height, number of nodes, pod length, pod width, number of pods per plant, number of seeds per plant, seed weight per plant, and 100-seed weight of fresh seeds.

[0016] Compared to open-field conditions, greenhouse-grown crops typically exhibit superior plant phenotypic characteristics and higher yields. However, current research on pea's tolerance to accumulated temperature is still relatively scarce. Therefore, in this embodiment, conventional testing was conducted on the tested pea varieties to compare the mean phenotypic values ​​among different treatments. Several key positive phenotypic traits and yield traits with significant variability were then selected for systematic analysis.

[0017] Specifically, the temperature accumulation tolerance coefficient (TATC) for each individual trait is used as an evaluation index and is calculated using the following formula: ;in, This represents the average observed value of a specific trait for a particular pea genotype under accumulated temperature treatment.

[0018] In this embodiment, accumulated temperature treatment refers to planting peas in a greenhouse cultivation environment with high light transmittance (light transmittance greater than 90%).

[0019] and This represents the average observed value of a single trait for a given pea genotype without accumulated temperature treatment.

[0020] The closer the TATC value is to 1, the less the trait of this genotype is affected by accumulated temperature; conversely, the closer it is to 1, the greater the influence.

[0021] S2. Convert the accumulated temperature coefficients of multiple individual traits into a unified membership degree.

[0022] Different individual traits have different numerical ranges and units for their accumulated temperature coefficients (TATC). Converting all individual trait accumulated temperature coefficients (TATC) to a uniform membership degree F eliminates the dimensionlessness. The membership function value (SFV) (scaled to the interval ([0,1])) is used to convert the TATC of each genotype of the individual trait to a membership degree: Where j = 1, 2, 3...; F represents the membership degree of a single trait of a certain genotype, ranging from 0 to 1; TATC min and TATC max These represent the minimum and maximum values ​​of this trait for a certain genotype, respectively; when F=1, it indicates that this trait is most sensitive to accumulated temperature, and when F=0, it indicates that this trait is least sensitive to accumulated temperature.

[0023] S3. Principal component analysis is used to reduce the membership of multiple individual traits into multiple independent comprehensive indicators, and the variance contribution rate of each comprehensive indicator is calculated.

[0024] Principal component analysis reduces the "membership degree F" of multiple individual traits to a few independent composite indices (i.e., principal components, such as PC1, PC2, PC3, etc.), and calculates the "variance contribution rate (W)" of each composite index, which is the explanatory power of the composite index for the total variation, and is also its "weight" in the calculation of D value.

[0025] Calculation of variance contribution rate (W): The variance contribution rate of a certain comprehensive indicator = the eigenvalue of that indicator / the sum of the eigenvalues ​​of all comprehensive indicators. Where W...j P represents the importance or weight of trait j in the comprehensive index. j It represents the contribution rate of trait j to each genotype.

[0026] Typically, comprehensive metrics with "eigenvalues ​​> 1" (according to the Kaiser criterion) are chosen to ensure that these metrics can explain most (e.g., ≥ 85%) of the original data variation, thus avoiding information loss.

[0027] S4. Using the variance contribution rate as the weight, calculate the sum of the weighted membership degrees of multiple comprehensive indicators as the comprehensive evaluation score.

[0028] The weighted sum is used to calculate the comprehensive evaluation score (i.e., the final D value).

[0029] The D-value is the sum of the weighted membership degrees of each comprehensive indicator, with the weights being the variance contribution rate (W) of the corresponding comprehensive indicator. j The formula is: μ j This represents the "comprehensive membership degree" of the j-th comprehensive indicator.

[0030] μ j The membership degree (F) of the individual traits included in the principal component is weighted by loading factors, and the formula is as follows: ; where a ij F represents the loading coefficient of the i-th individual trait on the j-th composite index (output of principal component analysis PCA), k represents the number of individual traits included in the j-th composite index, and F i This represents the membership degree of the i-th individual trait.

[0031] S5. Based on the comprehensive evaluation score of the pea variety to be tested, determine the accumulated temperature sensitivity level of the pea variety to be tested.

[0032] In this embodiment, the accumulated temperature sensitivity level includes accumulated temperature sensitive type, accumulated temperature intermediate type, and accumulated temperature insensitive type.

[0033] Specifically, when the comprehensive evaluation score of the pea variety to be tested is greater than 4.0, the variety is determined to be sensitive to accumulated temperature; when the comprehensive evaluation score of the pea variety to be tested is between 1.3 and 4.0, the variety is determined to be of intermediate accumulated temperature; and when the comprehensive evaluation score of the pea variety to be tested is less than 1.3, the variety is determined to be insensitive to accumulated temperature.

[0034] The threshold for the overall evaluation score is based on the sample D value as the clustering variable. The Ward link method of SPSS 26.0 software is used to generate a phylogenetic chart to classify the sample numbers. Referring to the clustering structure of the phylogenetic chart, 4.0 and 1.3 are selected as the thresholds to divide all samples into 3 clusters.

[0035] To further illustrate the method for identifying the pea accumulated temperature sensitivity of the present invention, the following examples are provided for detailed explanation. Examples

[0036] The pea varieties used in this embodiment, i.e., the test materials, were 119 pea germplasm accessions cultivated or collected by the Jiangsu Yangtze River Agricultural Research Institute from 2021 to 2023, as shown in Table 1 below. The experiment was conducted at the Xueyao Experimental Base of the Jiangsu Yangtze River Agricultural Research Institute, with two treatments: high-transmittance greenhouse cultivation and open field cultivation (CK). The high-transmittance greenhouse used anti-fogging film made of ethylene-vinyl acetate copolymer (EVA) with an initial light transmittance of 90%, with a row spacing of 60 cm and a plant spacing of 10 cm. Sowing was carried out simultaneously on November 15, 2024, and fertilization and field management were the same as in conventional production fields. Harvesting began successively from April 10, 2025. When fresh peas mature, select 6 representative plants from the middle of each row and measure the following parameters: plant height (X1), bottom pod height (X2), number of main stem nodes (X3), pod length (X4), pod width (X5), number of pods per plant (X6), number of pods per plant (X7), pod weight per plant (X8), pod weight per plant (X9), and weight of 100 fresh peas (X1). 10 All the above indicators are positive. Microsoft Excel 2003 was used for data processing and analysis; SPSS 26.0 was used for principal component analysis.

[0037] Table 1. Numbers and names of 119 pea samples

[0038] Data preprocessing includes calculations of accumulated temperature tolerance coefficient (TATC), membership degree, variance contribution rate, and comprehensive evaluation score. The specific TATC calculation results are shown in Table 2 below: Table 2: TATC Table of Accumulated Temperature Tolerance Coefficients for Various Pea Varieties

[0039] Continued from Table 2, TATC table of accumulated temperature tolerance for various pea varieties.

[0040] The specific calculation results of the membership degree F are shown in Table 3 below: Table 3, Membership Degree F of Each Pea Variety

[0041] Continued from Table 3, Membership Degrees (F-table) for Various Pea Varieties

[0042] Principal component analysis (PCA) was used to extract comprehensive indicators and weights: ① KMO and Bartlett test, the specific results of which are shown in Table 4 below.

[0043] Table 4. Results of KMO and Bartlett's Tests

[0044] Conclusion: KMO > 0.5 and significance is 0, making it suitable for principal component analysis.

[0045] ② Explanation of total variance, the specific results are shown in Table 5 below.

[0046] Table 5. Explanation of Total Variance

[0047] Extraction method: Principal component analysis.

[0048] Conclusion: The first four principal components have a cumulative explanatory power of 86.492%, making them suitable as principal components.

[0049] ③ The rotated component matrix a is shown in Table 6 below.

[0050] Table 6. Rotated Component Matrix

[0051] Extraction method: Principal component analysis.

[0052] Rotation method: Caesar normalization maximum variance method.

[0053] The rotation 'a' converged after 5 iterations.

[0054] Conclusion: The weights of the components corresponding to each trait are obtained and used to calculate the value of each material and each trait in each component.

[0055] ④ The calculation of each index of principal component 1 is shown in Table 7 below.

[0056] Table 7. Calculation results of each index of principal component 1

[0057] Continued from Table 7(1), Calculation results of each index of principal component 1

[0058] Continued from Table 7(2), Calculation results of each index of principal component 1

[0059] ⑤ The calculation of each index of principal component 2 is shown in Table 8 below.

[0060] Table 8. Calculation results of each index of principal component 2.

[0061] Continued from Table 8(1), Calculation results of each index of principal component 2

[0062] Continued from Table 8(2), Calculation results of each index of principal component 2

[0063] ⑥ The calculation of each index of principal component 3 is shown in Table 9 below.

[0064] Table 9. Calculation results of each index of principal component 3.

[0065] Continued from Table 9(1), Calculation results of each index of principal component 3

[0066] Continued from Table 9(2), Calculation results of each index of principal component 3

[0067] ⑦ The calculation of each index of principal component 4 is shown in Table 10 below.

[0068] Table 10. Calculation results of each index of principal component 4.

[0069] Table 10(1), Calculation results of each index of principal component 4

[0070] Table 10(2), Calculation results of each index of principal component 4

[0071] ⑧ The calculation of principal component weights W is shown in Tables 11 and 12 below.

[0072] Table 11. Explanation of Total Variance of Principal Component Weights W

[0073] Extraction method: Principal component analysis.

[0074] Table 12. Calculation results of principal component weights W

[0075] (4) The calculation of D value is shown in Table 13 below.

[0076] Table 13, Comprehensive Evaluation Sub-Table

[0077] Continued from Table 13 (1), Comprehensive Evaluation Sub-Table

[0078] Continued from Table 13(2), Comprehensive Evaluation Sub-Table

[0079] As shown in Table 13, pea genotypes 108, 51, 48, 107, 43, 50, 8, and 109 are identified as temperature-sensitive; pea genotypes 99, 83, 63, 79, and 105 are identified as temperature-insensitive; and the rest are identified as intermediate temperature types.

[0080] The method for identifying pea accumulated temperature sensitivity in this invention establishes and applies a set of evaluation systems based on different pea genotypes. Based on the D-value calculation results, the accumulated temperature response of peas is classified into three categories: D-value > 4.0 indicates temperature-sensitive peas, D-value < 1.3 indicates temperature-insensitive peas, and values ​​in between are considered intermediate-temperature-sensitive peas. This method provides a reference for future classification of pea accumulated temperature sensitivity levels. It not only helps in the systematic screening and evaluation of the accumulated temperature sensitivity characteristics of different pea varieties but also lays the foundation for further revealing the physiological and molecular mechanisms of pea response to temperature changes, thereby promoting the breeding and practical application of temperature-sensitive / temperature-insensitive pea varieties.

[0081] The method for identifying the pea accumulated temperature sensitivity of the present invention integrates multiple key traits such as plant height, pod length, and number of pods per plant to construct a multi-dimensional evaluation system, which avoids the one-sidedness of single-trait evaluation and significantly improves the comprehensiveness and accuracy of identification.

[0082] The method for identifying the accumulated temperature sensitivity of peas in this invention combines membership transformation and principal component analysis (PCA) to effectively eliminate dimensional differences and information overlap between traits, extract comprehensive indicators with clear biological significance, and achieve an objective and quantitative evaluation of accumulated temperature sensitivity.

[0083] The method for identifying the accumulated temperature sensitivity of peas in this invention achieves rapid and standardized classification of the accumulated temperature sensitivity of pea varieties by setting a clear comprehensive evaluation score (D value) threshold, which facilitates practical application.

[0084] The method for identifying the accumulated temperature sensitivity of peas in this invention is based on modeling and verification using measured data from 119 pea varieties. The method has high reliability and repeatability and is applicable to the identification of accumulated temperature sensitivity of peas under different genetic backgrounds and ecological environments.

[0085] The method for identifying the accumulated temperature sensitivity of peas in this invention can not only be used for evaluating and screening the accumulated temperature sensitivity of existing varieties, but also provide theoretical support and data basis for the breeding of new pea varieties with accumulated temperature sensitivity / insensitivity, and help optimize the regional layout and sowing time of pea production.

[0086] The evaluation system established by the method for identifying pea accumulated temperature sensitivity in this invention provides phenotypic data support for subsequent analysis of the physiological and molecular mechanisms by which peas respond to changes in accumulated temperature, which helps to deepen the understanding of pea temperature adaptability and promotes the development of crop climate adaptability research.

[0087] The trait selection, data processing, and comprehensive evaluation methods used in the identification of pea accumulated temperature sensitivity of the present invention have a certain degree of universality and can be extended to the systematic identification and evaluation of other crops' accumulated temperature sensitivity, stress resistance, and other related traits.

[0088] In summary, this invention provides a scientific, systematic, and operable method for identifying the accumulated temperature sensitivity of peas, which has strong theoretical value and practical significance, and can provide important technical support for pea breeding, production layout, and climate change adaptability research.

[0089] The above description is merely a preferred embodiment of this application and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of the invention involved in this application is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the inventive concept. For example, technical solutions formed by substituting the above features with (but not limited to) technical features with similar functions disclosed in this application.

Claims

1. A method for identifying the temperature sensitivity of peas, characterized in that, Includes the following steps: The accumulated temperature tolerance coefficients of multiple individual traits of the pea variety to be tested are obtained; the accumulated temperature tolerance coefficients of the multiple individual traits are converted into a unified membership degree; the membership degrees of the multiple individual traits are reduced to multiple independent comprehensive indicators through principal component analysis, and the variance contribution rate of each comprehensive indicator is calculated; the weighted sum of the membership degrees of the multiple comprehensive indicators is calculated as the comprehensive evaluation score using the variance contribution rate as the weight. Based on the comprehensive evaluation score of the pea variety to be tested, the accumulated temperature sensitivity level of the pea variety to be tested is determined.

2. The method for identifying the pea's accumulated temperature sensitivity according to claim 1, characterized in that, Principal component analysis was performed using SPSS 26.0 software.

3. The method for identifying the pea's accumulated temperature sensitivity according to claim 1, characterized in that, The individual traits mentioned include plant height, bottom pod height, number of nodes, pod length, pod width, number of pods per plant, number of grains per plant, grain weight per plant, and weight of 100 fresh seeds.

4. The method for identifying the pea's accumulated temperature sensitivity according to claim 1, characterized in that, The accumulated temperature sensitivity levels include accumulated temperature sensitive type, accumulated temperature intermediate type, and accumulated temperature insensitive type.

5. The method for identifying the pea's accumulated temperature sensitivity according to claim 4, characterized in that, When the comprehensive evaluation score of the pea variety to be tested is greater than 4.0, the variety is determined to be temperature-sensitive; when the comprehensive evaluation score of the pea variety to be tested is between 1.3 and 4.0, the variety is determined to be of intermediate temperature; when the comprehensive evaluation score of the pea variety to be tested is less than 1.3, the variety is determined to be temperature-insensitive.

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