Comprehensive evaluation method, system and equipment for drought resistance of camellia oleifera rootstock and storage medium

Abstract

The invention relates to the technical field of drought resistance evaluation, and particularly discloses a comprehensive evaluation method, system and equipment for the drought resistance of an oil tea rootstock and a storage medium, and the method comprises the steps: obtaining a plurality of initial drought resistance index parameters of the oil tea rootstock, and calculating the drought resistance of the oil tea rootstock based on the initial drought resistance index parameters; determining a plurality of pieces of initial comprehensive index data and characteristic value data and contribution rate data corresponding to each piece of initial comprehensive index data; determining target comprehensive index data according to the characteristic value data and the contribution rate data; according to the target comprehensive index data and the contribution rate data, determining a drought resistance comprehensive evaluation value for representing the drought resistance of the camellia oleifera rootstock; a multivariate regression model combined by different indexes is established according to a drought resistance comprehensive evaluation value, strong correlation index parameters with higher drought resistance correlation are determined based on the multivariate regression model, quantitative evaluation of the drought resistance is achieved, the change trend of the plant drought resistance in the early stage and the later stage of drought stress can be clearly observed, and the drought resistance evaluation accuracy is improved. And the evaluation accuracy and reliability are improved.

Description

Technical Field

[0001] The present application relates to the technical field of drought resistance evaluation, and in particular to a method, system, device and storage medium for comprehensive evaluation of drought resistance of oil-tea camellia rootstocks. Background Art

[0002] Camellia oleifera Abel. is a key oilseed tree species cultivated in the hilly and mountainous regions of southern my country. It exhibits strong drought tolerance. However, persistent drought and extreme high temperatures in the Yangtze River Basin in recent years have severely negatively impacted intensive cultivation and production of Camellia oleifera. Therefore, identifying and cultivating drought-resistant Camellia oleifera varieties has important scientific and practical applications in agricultural production, ecological restoration, and plant breeding.

[0003] Currently, research on evaluating the drought resistance of Camellia oleifera has focused primarily on seedlings and clonal cuttings, with little attention paid to evaluating the drought resistance of Camellia oleifera rootstocks. Furthermore, existing methods for evaluating the drought resistance of Camellia oleifera primarily include single-index and comprehensive-index methods.

[0004] However, the single-index evaluation method can only reflect the drought resistance of Camellia oleifera from a specific aspect. For example, chlorophyll content can only reflect the degree of damage to photosynthetic pigments of Camellia oleifera under drought stress, and cannot cover the overall physiological response of the plant in a drought environment. Drought resistance of Camellia oleifera is a complex and comprehensive trait, involving multiple aspects such as physiology, morphology, and growth. Therefore, a single indicator is difficult to fully evaluate. Although the comprehensive index evaluation method takes multiple indicators into consideration, it relies more on subjective judgment in the weight allocation and lacks an objective quantitative basis. This may lead to inaccuracy and poor repeatability of the evaluation results, making it difficult to make effective comparisons between different studies, and thus it is impossible to accurately screen out the Camellia oleifera rootstock variety with the strongest drought resistance from multiple different varieties of Camellia oleifera rootstocks. At the same time, it is impossible to determine a strong correlation indicator with a significant impact on drought resistance from multiple indicators. Summary of the Invention

[0005] The present application aims to propose a comprehensive evaluation method, system, equipment and storage medium for drought resistance of tea oil rootstocks, so as to at least solve the problems in the existing technology of low reliability and poor repeatability of drought resistance evaluation results of tea oil rootstocks, inability to accurately screen out the tea oil rootstock varieties with the strongest drought resistance and determine strong correlation indicators with significant impact on drought resistance from multiple indicators.

[0006] In a first aspect, the present application provides a method for comprehensively evaluating drought resistance of oil-tea camellia rootstocks, the method comprising: Acquiring a plurality of initial drought resistance index parameters of a plurality of different varieties of Camellia oleifera rootstocks under drought stress, wherein the initial drought resistance index parameters at least include morphological, growth, and physiological and biochemical index parameters; Based on the initial drought resistance index parameter, determining a plurality of initial comprehensive index data and characteristic value data and contribution rate data corresponding to each of the initial comprehensive index data; Determining at least one target comprehensive indicator data based on the characteristic value data and the contribution rate data; Determining a comprehensive drought resistance evaluation value for characterizing the drought resistance of multiple different varieties of camellia rootstocks based on the target comprehensive indicator data and the contribution rate data; A multiple regression model composed of different indicators is established according to the comprehensive drought resistance evaluation value, and a strongly correlated indicator parameter with higher drought resistance correlation is determined based on the multiple regression model.

[0007] In some embodiments, the initial drought resistance index parameters include plant height increase, crown biomass, ground diameter increase, total biomass, root-crown ratio, primary root length, secondary root length, tertiary root length, primary root volume, secondary root volume, tertiary root volume, plant relative water content, chlorophyll a content, chlorophyll b content, total chlorophyll content, net photosynthetic rate, stomatal conductance, intercellular carbon dioxide concentration and transpiration rate.

[0008] In some embodiments, the determining of a plurality of initial comprehensive index data and characteristic value data and contribution rate data corresponding to each of the initial comprehensive index data based on the initial drought resistance index parameter includes: Performing data standardization on the initial drought resistance index parameters and calculating the covariance matrix of the standardized data; Performing feature decomposition on the data to obtain a plurality of initial comprehensive indicator data and feature value data corresponding to each of the initial comprehensive indicator data; Contribution rate data corresponding to each of the initial comprehensive indicator data is determined based on the characteristic value data.

[0009] In some embodiments, determining, based on the target comprehensive index data and the contribution rate data, a comprehensive drought resistance evaluation value for characterizing the drought resistance of the oil-tea camellia rootstocks of a plurality of different varieties includes: Determine the corresponding comprehensive index value, minimum comprehensive index value, and maximum comprehensive index value according to the target comprehensive index data; Determining a plurality of grafting combination membership function values ​​corresponding to different varieties of tea oil rootstocks according to the comprehensive index value, the minimum comprehensive index value, and the maximum comprehensive index value; Determining the comprehensive indicator weight corresponding to each of the initial comprehensive indicator data based on the contribution rate data; The comprehensive drought resistance evaluation value of the drought resistance of each variety of Camellia oleifera rootstock is determined according to the grafting combination membership function value and the comprehensive index weight.

[0010] In some embodiments, determining the membership function values ​​of multiple grafting combinations corresponding to different varieties of tea oil rootstocks based on the comprehensive index value, the minimum comprehensive index value, and the maximum comprehensive index value includes: The calculation expression of the grafting combination membership function value is: , Where, Indicates the The membership function value of a comprehensive indicator, Indicates the Comprehensive index value; Indicates the The maximum value of the comprehensive index, Indicates the The minimum value of a comprehensive indicator.

[0011] In some embodiments, determining the comprehensive drought resistance evaluation value of each variety of Camellia oleifera rootstock drought resistance based on the grafting combination membership function value and the comprehensive index weight includes: The calculation expression of the comprehensive index weight is: Where, Indicates the The importance and weight of each comprehensive indicator among all comprehensive indicators; For each variety The contribution rate of the comprehensive indicators; The calculation expression of the comprehensive evaluation value of drought resistance is: Where, It represents the comprehensive evaluation value of the drought resistance of Camellia oleifera rootstock under drought stress conditions.

[0012] In some embodiments, establishing a multiple regression model composed of different indicators based on the comprehensive drought resistance evaluation value, and determining a strongly correlated indicator parameter with a higher correlation with drought resistance based on the multiple regression model, includes: The calculation expression of the regression model is: Where, It represents the measured value of drought resistance index of Camellia oleifera rootstock under drought stress conditions. It represents the coefficient corresponding to the measured value of drought resistance index of Camellia oleifera rootstock under drought stress conditions, represents the error term.

[0013] Compared with the prior art, the technical solution provided in the first aspect of this application includes at least the following beneficial effects or advantages: The present application provides a technical solution that analyzes and reduces the dimensionality of multiple initial drought resistance index parameters of multiple different varieties of tea oil rootstocks under drought stress, thereby screening out relatively fewer drought resistance identification indicators with stronger correlation, and obtaining corresponding component characteristic values ​​and contribution rates, and then determining a comprehensive drought resistance evaluation value for characterizing the drought resistance of multiple different varieties of tea oil rootstocks based on the target comprehensive index data and the contribution rate data. By analyzing the obtained comprehensive drought resistance evaluation value, tea oil rootstock varieties with better drought resistance are screened out. At the same time, the method avoids the influence of subjective judgment on the evaluation results, improves the accuracy and reliability of the evaluation, and can dynamically reflect the changes in the drought resistance of plants during drought stress. By measuring the indicators of plants under different drought degrees, the changing trends of plant drought resistance in the early and late stages of drought stress can be clearly observed.

[0014] In addition, the created multivariate regression model can quantify the relationship between indicators, and intuitively present the contribution of different indicators to drought resistance through mathematical models, thereby accurately screening out key indicators. In addition, it can also process multiple variables and comprehensively consider the impact of multiple factors on drought resistance, avoiding the one-sidedness of single indicator screening.

[0015] In a second aspect, the present application provides a comprehensive evaluation system for drought resistance of oil-tea camellia rootstocks, comprising: A first acquisition module is configured to acquire a plurality of initial drought resistance index parameters of a plurality of different varieties of Camellia oleifera rootstocks under drought stress, wherein the initial drought resistance index parameters at least include morphological, growth, and physiological and biochemical index parameters; A first determining module is configured to determine a plurality of initial comprehensive index data and characteristic value data and contribution rate data corresponding to each of the initial comprehensive index data based on the initial drought resistance index parameter; A second determination module is configured to determine at least one target comprehensive indicator data based on the characteristic value data and the contribution rate data; A third determination module is configured to determine a comprehensive drought resistance evaluation value for characterizing the drought resistance of multiple different varieties of tea oil rootstocks based on the target comprehensive index data and the contribution rate data; The regression model creation module is configured to establish a multiple regression model composed of different indicators according to the comprehensive drought resistance evaluation value, and determine a strongly associated indicator parameter with higher drought resistance correlation based on the multiple regression model.

[0016] In a third aspect, the present application further provides an electronic device, comprising: at least one processor; and a memory in communication with the at least one processor; wherein, The storage stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the steps of the comprehensive evaluation method for drought resistance of tea oil rootstock provided in the first aspect above.

[0017] In a fourth aspect, the present application further provides a computer-readable storage medium having computer program instructions stored thereon, which, when executed by a processor, implement the steps of the method for comprehensive evaluation of drought resistance of tea oil rootstock provided in the first aspect.

[0018] It can be understood that the beneficial effects of the technical solutions provided in the second, third and fourth aspects can be found in the relevant description of the first aspect, and will not be repeated here.

[0019] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become obvious from the description below, or will be learned through practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0021] Figure 1 Flowchart of a comprehensive evaluation method for drought resistance of tea oil rootstock according to an embodiment of the present application; Figure 2 1 is a block diagram of a comprehensive evaluation system for drought resistance of camellia oleifera rootstocks according to an embodiment of the present application; Figure 3 It is a structural block diagram of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0022] The embodiments of the present application are described in detail below. The embodiments described with reference to the accompanying drawings are exemplary. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0023] It should be noted that, unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application belongs. The terms used herein in the specification of this application are only for the purpose of describing specific embodiments and are not intended to limit this application. The term "and / or" as used herein includes any and all combinations of one or more of the relevant listed items.

[0024] See also Figure 1 , Figure 1 A flow chart of a comprehensive evaluation method for drought resistance of tea oil rootstock provided in this embodiment is shown. The method of this embodiment includes steps S100 to S500.

[0025] In step S100, a plurality of initial drought resistance index parameters of a plurality of different varieties of Camellia oleifera rootstocks under drought stress are obtained, wherein the initial drought resistance index parameters at least include morphological, growth, and physiological and biochemical index parameters; To obtain multiple initial drought resistance parameters for different oil-tea rootstock varieties under drought stress, for example, Jiangxi Province's main oil-tea varieties "Ganwu 1," "Ganwu 2," and "Changlin 3," and the polyploid oil-tea "Gaozhou Oil-tea" were used as rootstocks, with "Changlin 4" as the scion. Grafted seedlings with the same scion but different rootstocks were cultivated. Four treatments were set up: CK (above 52% of maximum field water holding capacity), D1 (33%-48% of maximum field water holding capacity), D2 (25%-33% of maximum field water holding capacity), and D3 (20%-25% of field water holding capacity). Twenty parameters, including morphology, growth, and physiological and biochemical parameters, of the grafted seedlings under drought stress were measured.

[0026] In some embodiments, specifically, the initial drought resistance index parameters include plant height increase, crown biomass, ground diameter increase, total biomass, root-crown ratio, primary root length, secondary root length, tertiary root length, primary root volume, secondary root volume, tertiary root volume, plant relative water content, chlorophyll a content, chlorophyll b content, total chlorophyll content, net photosynthetic rate, stomatal conductance, intercellular carbon dioxide concentration and transpiration rate.

[0027] It should be noted that the process of obtaining these initial drought resistance index parameters can be carried out using relevant equipment or process methods in the existing technology. For example, acetone extraction method can be used to obtain chlorophyll a content, chlorophyll b content and total chlorophyll content.

[0028] In step S200, based on the initial drought resistance index parameter, a plurality of initial comprehensive index data and characteristic value data and contribution rate data corresponding to each of the initial comprehensive index data are determined; For multiple initial comprehensive index data and the eigenvalue data and contribution rate data corresponding to each initial comprehensive index data, SPSS27.0 software can be used to perform principal component analysis on the 20 indicators (average values ​​under drought stress) of the four oil-tea grafted seedlings with the same ear and different rootstocks. Specifically, the initial drought resistance index parameters are standardized, and the covariance matrix of the standardized data is calculated; characteristic decomposition is performed to obtain multiple initial comprehensive index data and the eigenvalue data corresponding to each initial comprehensive index data; based on the eigenvalue data, the contribution rate data corresponding to each initial comprehensive index data is determined.

[0029] For example, for the principal component analysis (PCA) method, the mean of each feature is adjusted to 0 and the standard deviation to 1 to eliminate the dimension effect. The covariance matrix is ​​calculated based on the standardized data. The eigenvector of the covariance matrix represents the direction of the principal component, and the eigenvalue represents the variance of the corresponding direction. The eigenvalues ​​are sorted from large to small, and the first k eigenvectors are selected as the new feature space. The data are projected onto the selected principal component to obtain the reduced-dimensional data. It can be understood that the principal component analysis method is used to reduce the dimensionality of drought resistance indicators, thereby screening out relatively few drought resistance identification indicators and obtaining the corresponding component eigenvalues ​​and contribution rates.

[0030] In step S300, at least one target comprehensive indicator data is determined based on the characteristic value data and the contribution rate data; In some embodiments, principal component analysis was performed on 20 indicators (average values ​​under drought stress) of the four grafted tea seedlings with the same ear and different rootstocks using SPSS27.0 software, among which the contribution rates of the first three comprehensive indicators were 47.99%, 34.64% and 17.37%, respectively, as shown in Table 1.

[0031] Step S400: determining a comprehensive drought resistance evaluation value for characterizing the drought resistance of multiple different varieties of Camellia oleifera rootstocks based on the target comprehensive index data and the contribution rate data; In some embodiments, according to the target comprehensive index data, the corresponding comprehensive index value, the minimum comprehensive index value and the maximum comprehensive index value are determined; according to the comprehensive index value, the minimum comprehensive index value and the maximum comprehensive index value, the multiple grafting combination membership function values ​​corresponding to different varieties of tea oil rootstocks are determined; based on the contribution rate data, the comprehensive index weight corresponding to each of the initial comprehensive index data is determined; according to the grafting combination membership function value and the comprehensive index weight, the comprehensive drought resistance evaluation value of the drought resistance of each variety of tea oil rootstock is determined.

[0032] Optionally, in determining the membership function values ​​of multiple grafting combinations corresponding to different varieties of tea oil rootstocks based on the comprehensive index value, the minimum comprehensive index value, and the maximum comprehensive index value, the calculation expression of the membership function value of the grafting combination is: (1), Where, Indicates the The membership function value of a comprehensive indicator, Indicates the Comprehensive index value; Indicates the The maximum value of the comprehensive index, Indicates the The minimum value of a comprehensive indicator.

[0033] Optionally, in determining the comprehensive indicator weight corresponding to each initial comprehensive indicator data based on the contribution rate data, the calculation expression of the comprehensive indicator weight is: (2) Where, Indicates the The importance and weight of each comprehensive indicator among all comprehensive indicators; For each variety The contribution rate of the comprehensive indicators; Optionally, in determining the comprehensive drought resistance evaluation value of each variety of oil-tea camellia rootstock drought resistance ability based on the grafting combination membership function value and the comprehensive index weight, the calculation expression of the comprehensive drought resistance evaluation value is: (3) Where, It represents the comprehensive evaluation value of the drought resistance of Camellia oleifera rootstock under drought stress conditions.

[0034] For example, taking the data in Table 1 as an example, using the formula Calculate 3 comprehensive indicators CI (j) The membership function value of , as shown in Table 2: Comprehensive indicators CI(j) The membership function value of the grafting combination with the middle rootstock Ganwu1 is the largest ( =1), indicating that CI (1) The drought tolerance is the strongest under the comprehensive index; the grafting combination membership function value of the rootstock Gaozhou oil tea is the smallest ( =0), indicating that CI (1) The drought tolerance is the weakest under the comprehensive index. , combined with the contribution rate of each comprehensive indicator, the weights of the three comprehensive indicators are obtained They are 0.71, 0.21, and 0.08 respectively. Calculation of comprehensive evaluation value of drought resistance of Camellia oleifera rootstock , and according to The drought resistance ability of rootstocks was ranked according to the size of the values, and the order of drought resistance was: Ganwu 1 > Changlin 3 > Gaozhou Camellia oleifera > Ganwu 2.

[0035] In step S500, a multiple regression model composed of different indicators is established according to the comprehensive drought resistance evaluation value, and a strongly correlated indicator parameter with a higher drought resistance correlation is determined based on the multiple regression model.

[0036] In some embodiments, a multivariate regression model composed of different indicators is established based on the comprehensive drought resistance evaluation value, wherein the calculation expression of the regression model is: Where, It represents the measured value of drought resistance index of Camellia oleifera rootstock under drought stress conditions. It represents the coefficient corresponding to the measured value of drought resistance index of Camellia oleifera rootstock under drought stress conditions, represents the error term.

[0037] For example, take the data in Table 2 above as an example to understand the relationship between the various measurement indicators and The correlation between the values ​​was calculated, and the key drought resistance identification indicators of Camellia oleifera rootstocks were screened out. SPSS27.0 software was used for stepwise regression analysis, and the regression model was established as follows: , (Equation determination coefficient R2=1.000, P<0.01), according to the equation results, 20 key indicators were screened out (total biomass) and (root-to-shoot ratio) are two indicators with stronger correlations. A comparison of the accuracy of the regression equations (as shown in Table 3) revealed that the accuracy of Ganwu 1 was 99.03%, Ganwu 2 was 96.35%, Changlin 3 was 98.64%, and Gaozhou Camellia oleifera was 94.72%. In other words, the accuracy of the predictions for the four different rootstock varieties was above 94%, demonstrating that these two indicators have a significant impact on the drought resistance of Camellia oleifera rootstocks.

[0038] The technical solution provided in the above embodiment analyzes and reduces the dimensionality of multiple initial drought resistance index parameters of multiple different varieties of tea oil rootstocks under drought stress, thereby screening out relatively fewer drought resistance identification indicators with stronger correlation, and obtaining corresponding component characteristic values ​​and contribution rates, and then determining the comprehensive drought resistance evaluation value used to characterize the drought resistance of multiple different varieties of tea oil rootstocks based on the target comprehensive index data and contribution rate data. The comprehensive drought resistance evaluation value obtained by analysis is used to screen out tea oil rootstock varieties with better drought resistance. At the same time, the method avoids the influence of subjective judgment on the evaluation results, improves the accuracy and reliability of the evaluation, and can dynamically reflect the changes in the drought resistance of plants during drought stress. By measuring the indicators of plants under different drought degrees, the changing trends of plant drought resistance in the early and late stages of drought stress can be clearly observed.

[0039] In addition, the created multivariate regression model can quantify the relationship between indicators, and the created mathematical model can intuitively present the contribution of different indicators to drought resistance, thereby accurately screening out key indicators. In addition, it can also process multiple variables and comprehensively consider the impact of multiple factors on drought resistance, avoiding the one-sidedness of single indicator screening.

[0040] See also Figure 2 This embodiment provides a comprehensive evaluation system for drought resistance of oil-tea camellia rootstocks. The comprehensive evaluation system 200 for drought resistance of oil-tea camellia rootstocks includes: The first acquisition module 210 is configured to obtain a plurality of initial drought resistance index parameters of a plurality of different varieties of Camellia oleifera rootstocks under drought stress, wherein the initial drought resistance index parameters at least include morphological, growth, and physiological and biochemical index parameters; The first determining module 220 is configured to determine a plurality of initial comprehensive index data and characteristic value data and contribution rate data corresponding to each of the initial comprehensive index data based on the initial drought resistance index parameter; The second determination module 230 is configured to determine at least one target comprehensive indicator data based on the characteristic value data and the contribution rate data; The third determination module 240 is configured to determine a comprehensive drought resistance evaluation value for characterizing the drought resistance of multiple different varieties of Camellia oleifera rootstocks based on the target comprehensive index data and the contribution rate data; The regression model creation module 250 is configured to establish a multiple regression model composed of different indicators according to the comprehensive drought resistance evaluation value, and determine a strongly correlated indicator parameter with a higher drought resistance correlation based on the multiple regression model.

[0041] In some embodiments, the initial drought resistance index parameters obtained by the first acquisition module 210 may include plant height increase, crown biomass, ground diameter increase, total biomass, root-crown ratio, primary root length, secondary root length, tertiary root length, primary root volume, secondary root volume, tertiary root volume, plant relative water content, chlorophyll a content, chlorophyll b content, total chlorophyll content, net photosynthetic rate, stomatal conductance, intercellular carbon dioxide concentration and transpiration rate.

[0042] In some embodiments, the third determination module 240 is specifically further used to determine the corresponding comprehensive index value, the minimum comprehensive index value and the maximum comprehensive index value based on the target comprehensive index data; determine the multiple grafting combination membership function values ​​corresponding to different varieties of tea oil rootstocks based on the comprehensive index value, the minimum comprehensive index value and the maximum comprehensive index value; determine the comprehensive index weight corresponding to each of the initial comprehensive index data based on the contribution rate data; determine the comprehensive drought resistance evaluation value of the drought resistance of each variety of tea oil rootstock based on the grafting combination membership function value and the comprehensive index weight.

[0043] Optionally, the calculation expression for the membership function value of the grafted combination is: , Where, Indicates the The membership function value of a comprehensive indicator, Indicates the Comprehensive index value; Indicates the The maximum value of the comprehensive index, Indicates the The minimum value of a comprehensive indicator.

[0044] Optionally, the calculation expression for the comprehensive indicator weight is: Where, Indicates the The importance and weight of each comprehensive indicator among all comprehensive indicators; For each variety The contribution rate of the comprehensive indicators; The calculation expression of the comprehensive evaluation value of drought resistance is: Where, It represents the comprehensive evaluation value of the drought resistance of Camellia oleifera rootstock under drought stress conditions.

[0045] Optionally, the calculation expression of the regression model in the regression model creation module 250 is: Where, It represents the measured value of drought resistance index of Camellia oleifera rootstock under drought stress conditions. It represents the coefficient corresponding to the measured value of drought resistance index of Camellia oleifera rootstock under drought stress conditions, represents the error term.

[0046] It is understandable that, in the embodiment of the comprehensive evaluation system 200 for drought resistance of oil-tea tree rootstock, each module runs the above Figure 1 The steps of a comprehensive evaluation method for drought resistance of oil-tea tree rootstock in the corresponding embodiment, and the technical effects that can be achieved can be referred to the above Figure 1 The relevant descriptions in the corresponding embodiments are not repeated here.

[0047] See also Figure 3 , Figure 3 5 is a block diagram of a structure of an electronic device provided in an embodiment of the present application. The server 500 of the electronic device includes: a processor 501, a memory 502, and a computer program 503 stored in the memory 502 and executable on the processor 501, such as a program for a method for comprehensively evaluating drought resistance of oil-tea rootstocks. When the processor 501 executes the computer program 503, the steps of the method for comprehensively evaluating drought resistance of oil-tea rootstocks in the above-mentioned embodiments are implemented, such as Figure 1 The corresponding embodiment of the step S100 to step S500. Alternatively, the processor 501 executes the computer program 503 to implement the above Figure 2The functions of each module in the corresponding embodiment are, for example, Figure 2 For details on the functions of the modules shown (such as the first acquisition module 210), please refer to the relevant descriptions in the corresponding embodiments of 2, which will not be repeated here.

[0048] For example, computer program 503 may be divided into one or more units, one or more of which are stored in storage 502 and executed by processor 501 to implement the technical solutions provided in the above embodiments. One or more units may be a series of computer program instruction segments capable of performing specific functions, and the instruction segments are used to describe the execution process of computer program 503 in server 500.

[0049] The electronic device may include, but is not limited to, a processor 501 and a storage 502. Those skilled in the art will understand that Figure 3 It is only an example of the server 500 in the electronic device and does not constitute a limitation of the server 500. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the turntable terminal device may also include input and output terminal devices, network access terminal devices, buses, etc.

[0050] The processor 501 may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0051] Storage 502 can be an internal storage unit of server 500, such as the server's hard drive or memory. Storage 502 can also be an external storage terminal device of server 500, such as a plug-in hard drive, a Smart Media Card (SMC), a Secure Digital (SD) card, a flash memory card, etc. Furthermore, storage 502 can include both the server's internal storage unit and an external storage terminal device. Storage 502 is used to store computer programs and other programs and data required by the turntable terminal device. Storage 502 can also be used to temporarily store data that has been output or is about to be output.

[0052] In some embodiments, a computer-readable storage medium is also provided, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of a comprehensive evaluation method for drought resistance of tea oil rootstock as described in the above embodiment are implemented.

[0053] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0054] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. The computer-readable storage medium can be either non-volatile or volatile. Based on this understanding, the present application can implement all or part of the process steps in the above-mentioned method embodiments by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, it can implement the steps of each of the above-mentioned method embodiments. The computer program includes computer program code, which can be in source code form, object code form, executable file, or some intermediate form. Computer-readable storage media can include: any entity or device capable of carrying computer program code, recording medium, USB flash drive, mobile hard drive, magnetic disk, optical disk, computer storage, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal, and software distribution medium.

[0055] In the specification, claims, and accompanying drawings of this application, the terms "first," "second," "third," and the like are used to distinguish different objects and are not used to describe a particular order. Furthermore, the terms "including," "comprising," "having," and any variations thereof are intended to cover non-exclusive inclusions. For example, a list of steps or elements may be included, or alternatively, steps or elements not listed may be included, or other steps or elements may be included that are inherent to the process, method, product, or apparatus.

[0056] Only portions relevant to the present application are shown in the accompanying drawings, not all of them. Before discussing the exemplary embodiments in more detail, it should be noted that some exemplary embodiments are described as processes or methods depicted as flow charts. Although the flow charts describe the various operations (or steps) as sequential processes, many of the operations can be performed in parallel, concurrently, or simultaneously. In addition, the order of the various operations can be rearranged. The process can be terminated when its operations are completed, but can also have additional steps not included in the accompanying drawings. The process can correspond to a method, function, procedure, subroutine, subprogram, etc.

[0057] As used in this specification, the terms "component," "module," "system," "unit," and the like are used to refer to computer-related entities, hardware, firmware, a combination of hardware and software, software, or software in execution. For example, a unit can be, but is not limited to, a process running on a processor, a processor, an object, an executable file, an execution thread, a program, and / or distributed between two or more computers. In addition, these units can be executed from various computer-readable media having various data structures stored thereon. Units can communicate, for example, via local and / or remote processes based on signals having one or more data packets (e.g., data from a second unit interacting with another unit in a local system, a distributed system, and / or a network, such as the Internet, which interacts with other systems via signals).

[0058] Throughout this specification, reference to terms such as "one embodiment," "some embodiments," "illustrative embodiments," "example," "specific example," or "some examples" means that a specific feature, structure, material, or characteristic described in conjunction with the embodiment or example is included in at least one embodiment or example of the present application. In this specification, illustrative expressions of the above terms do not necessarily refer to the same embodiment or example.

[0059] Obviously, the described embodiments are only some of the embodiments of the present application, rather than all of the embodiments. Mentioning "embodiment" in this article means that the specific features, structures or characteristics described in conjunction with the embodiment may be included in at least one embodiment of the present embodiment application. The appearance of this phrase in various positions in the specification does not necessarily mean that they are all the same embodiments, nor are they independent or alternative embodiments that are mutually exclusive with other embodiments. It can be understood explicitly and implicitly by those skilled in the art that the embodiments described herein can be combined with other embodiments. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art without making creative work are within the scope of protection of this application.

[0060] Although the embodiments of the present application have been shown and described, those skilled in the art will appreciate that various changes, modifications, substitutions, and variations may be made to the embodiments without departing from the principles and intent of the present application, and that the scope of the present application is defined by the claims and their equivalents.

[0061] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the disclosure disclosed herein. This application is intended to cover any variations, uses, or adaptations of the present application that follow the general principles of the present application and include common knowledge or customary techniques in the art not disclosed herein. The description and examples are to be considered as exemplary only, and the true scope and spirit of the present application are indicated by the following claims.

Claims

1. A comprehensive evaluation method for drought resistance of oil-tea camellia rootstock, characterized in that: The method comprises: Acquiring a plurality of initial drought resistance index parameters of a plurality of different varieties of Camellia oleifera rootstocks under drought stress, wherein the initial drought resistance index parameters at least include morphological, growth, and physiological and biochemical index parameters; Based on the initial drought resistance index parameter, determining a plurality of initial comprehensive index data and characteristic value data and contribution rate data corresponding to each of the initial comprehensive index data; Determining at least one target comprehensive indicator data based on the characteristic value data and the contribution rate data; Determining a comprehensive drought resistance evaluation value for characterizing the drought resistance of multiple different varieties of camellia rootstocks based on the target comprehensive indicator data and the contribution rate data; A multiple regression model composed of different indicators is established according to the comprehensive drought resistance evaluation value, and a strongly correlated indicator parameter with higher drought resistance correlation is determined based on the multiple regression model.

2. The method for comprehensive evaluation of drought resistance of oil-tea camellia rootstock according to claim 1, wherein The initial drought resistance index parameters include plant height increase, crown biomass, ground diameter increase, total biomass, root-crown ratio, primary root length, secondary root length, tertiary root length, primary root volume, secondary root volume, tertiary root volume, plant relative water content, chlorophyll a content, chlorophyll b content, total chlorophyll content, net photosynthetic rate, stomatal conductance, intercellular carbon dioxide concentration and transpiration rate.

3. The method for comprehensive evaluation of drought resistance of oil-tea camellia rootstock according to claim 1, wherein The determining of a plurality of initial comprehensive index data and characteristic value data and contribution rate data corresponding to each of the initial comprehensive index data based on the initial drought resistance index parameter includes: Performing data standardization on the initial drought resistance index parameters and calculating the covariance matrix of the standardized data; Performing feature decomposition on the data to obtain a plurality of initial comprehensive indicator data and feature value data corresponding to each of the initial comprehensive indicator data; Contribution rate data corresponding to each of the initial comprehensive indicator data is determined based on the characteristic value data.

4. The method for comprehensive evaluation of drought resistance of oil-tea camellia rootstock according to claim 1, wherein Determining, based on the target comprehensive index data and the contribution rate data, a comprehensive drought resistance evaluation value for characterizing the drought resistance of the oil-tea camellia rootstocks of a plurality of different varieties, includes: Determine the corresponding comprehensive index value, minimum comprehensive index value, and maximum comprehensive index value according to the target comprehensive index data; Determining a plurality of grafting combination membership function values ​​corresponding to different varieties of tea oil rootstocks according to the comprehensive index value, the minimum comprehensive index value, and the maximum comprehensive index value; Determining the comprehensive indicator weight corresponding to each of the initial comprehensive indicator data based on the contribution rate data; The comprehensive drought resistance evaluation value of the drought resistance of each variety of Camellia oleifera rootstock is determined according to the grafting combination membership function value and the comprehensive index weight.

5. The method for comprehensive evaluation of drought resistance of oil-tea camellia rootstock according to claim 4, wherein The step of determining the membership function values ​​of multiple grafting combinations corresponding to different varieties of tea oil rootstocks according to the comprehensive index value, the minimum comprehensive index value, and the maximum comprehensive index value comprises: The calculation expression of the grafting combination membership function value is: , Where, Indicates the The membership function value of a comprehensive indicator, Indicates the Comprehensive index value; Indicates the The maximum value of the comprehensive index, Indicates the The minimum value of a comprehensive indicator.

6. The method for comprehensive evaluation of drought resistance of oil-tea camellia rootstock according to claim 4, wherein: Determining a comprehensive drought resistance evaluation value of each variety of Camellia oleifera rootstock drought resistance based on the grafting combination membership function value and the comprehensive index weight, including: The calculation expression of the comprehensive index weight is: Where, Indicates the The importance and weight of each comprehensive indicator among all comprehensive indicators; For each variety The contribution rate of the comprehensive indicators; The calculation expression of the comprehensive evaluation value of drought resistance is: Where, It represents the comprehensive evaluation value of the drought resistance of Camellia oleifera rootstock under drought stress conditions.

7. The method for comprehensive evaluation of drought resistance of oil-tea camellia rootstock according to claim 1, wherein The method of establishing a multiple regression model composed of different indicators according to the comprehensive drought resistance evaluation value, and determining a strongly correlated indicator parameter with a higher drought resistance correlation based on the multiple regression model, includes: The calculation expression of the regression model is: Where, It represents the measured value of drought resistance index of Camellia oleifera rootstock under drought stress conditions. It represents the coefficient corresponding to the measured value of drought resistance index of Camellia oleifera rootstock under drought stress conditions, represents the error term.

8. A comprehensive evaluation system for drought resistance of oil-tea camellia rootstocks, characterized in that: include: A first acquisition module is configured to acquire a plurality of initial drought resistance index parameters of a plurality of different varieties of Camellia oleifera rootstocks under drought stress, wherein the initial drought resistance index parameters at least include morphological, growth, and physiological and biochemical index parameters; A first determining module is configured to determine a plurality of initial comprehensive index data and characteristic value data and contribution rate data corresponding to each of the initial comprehensive index data based on the initial drought resistance index parameter; A second determination module is configured to determine at least one target comprehensive indicator data based on the characteristic value data and the contribution rate data; A third determination module is configured to determine a comprehensive drought resistance evaluation value for characterizing the drought resistance of multiple different varieties of tea oil rootstocks based on the target comprehensive index data and the contribution rate data; The regression model creation module is configured to establish a multiple regression model composed of different indicators according to the comprehensive drought resistance evaluation value, and determine a strongly associated indicator parameter with higher drought resistance correlation based on the multiple regression model.

9. An electronic device, characterized in that: include: at least one processor; as well as a memory in communication with the at least one processor; wherein, The storage stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the steps of the comprehensive evaluation method for drought resistance of oil tea rootstocks according to any one of claims 1-7.

10. A computer-readable storage medium having computer program instructions stored thereon, characterized in that: When the computer program instructions are executed by a processor, the steps of the comprehensive evaluation method for drought resistance of oil-tea camellia rootstocks according to any one of claims 1 to 7 are implemented.

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