Evaluation method for validity period of pear botryosphaeria fruit rot pathogen nucleic acid qualitative standard sample

Abstract

The invention discloses a method for evaluating the validity period of a pear botryosphaeria fruit rot pathogen nucleic acid qualitative standard sample. The method comprises the following steps: acquiring ct value data obtained by carrying out real-time fluorescent PCR (Polymerase Chain Reaction) experiments on the standard sample at different time points; constructing a fitting curve based on the ct value data and the corresponding time points; calculating a slope standard error of the fitting curve, and combining the slope of the fitting curvature to obtain a t value of the fitting curve; judging whether the t value of the fitting curve is smaller than the t inspection critical value or not; if yes, calculating the confirmation probability of the preset validity period of the standard sample; and if the confirmation probability is greater than the threshold, taking the preset validity period as the validity period of the standard sample. According to the method, by analyzing the ct value data and the preset validity period, whether the stability of the standard sample in the preset validity period meets the requirement or not can be judged, and the validity period data is output when the requirement is not met, so that the experiment detection frequency of experimenters is reduced, the occupation of experiment resources and labor cost is reduced, and the stability of the standard sample is ensured.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of computer software, and particularly relates to a method for evaluating the effective period of a Potebniamyces pyri nucleic acid qualitative standard sample. BACKGROUND

[0002] Potebniamyces pyri is a pathogenic fungus that harms plants such as apples and pears. In addition to causing ulceration or necrosis of the bark of fruit trees, it can also cause rot disease in stored pears. The disease is currently distributed in Germany, the United Kingdom, Russia, Cyprus, Canada, Oregon and Washington states in the United States, and China. Considering the high harmfulness of Potebniamyces pyri, it is necessary to develop detection and identification technology research work standardization operation procedures for the disease, and therefore, the development of standard samples for the disease is indispensable.

[0003] The stability of the standard sample of Potebniamyces pyri is of great significance to ensure sensitive, specific and rapid detection of quarantine fungal pathogens. The long-term stability of the standard sample of the disease in the prior art cannot be accurately evaluated, and only periodic detection methods can be used to analyze the real-time stability of the standard sample. The stability of the sample cannot be guaranteed, and a large amount of experimental resources and manpower are consumed. SUMMARY

[0004] The purpose of the present application is to provide a method and device for evaluating the effective period of a Potebniamyces pyri nucleic acid qualitative standard sample, in order to solve the technical problems in the prior art that the long-term stability of the standard sample of Potebniamyces pyri cannot be accurately evaluated, only periodic detection methods can be used to analyze the real-time stability of the standard sample, the stability of the sample cannot be guaranteed, and a large amount of experimental resources and manpower are consumed.

[0005] To achieve the above-mentioned purpose, the first aspect of the present application provides a method for evaluating the effective period of a Potebniamyces pyri nucleic acid qualitative standard sample, comprising:

[0006] Obtaining ct value data obtained by performing real-time fluorescent PCR experiments on the standard sample at different time points;

[0007] Based on the ct value data and the corresponding time points, a fitting curve is constructed;

[0008] The slope standard error of the fitting curve is calculated, and the t value of the fitting curve is obtained in combination with the slope of the fitting curve;

[0009] It is judged whether the t value of the fitting curve is less than a t test critical value;

[0010] If yes, the confidence probability of the preset effective period of the standard sample is calculated.

[0011] If the confidence probability is greater than a threshold value, the preset validity period is taken as the validity period of the standard sample.

[0012] In one or more embodiments, the step of constructing a fitting curve based on the ct value data and corresponding time points comprises:

[0013] constructing a curve model based on the following formula: ;

[0014] calculating the slope and the intercept of the curve model based on the ct value data and corresponding time points, and substituting them into the curve model to obtain a fitting curve.

[0015] In one or more embodiments, the step of calculating the slope and the intercept of the curve model based on the ct value data and corresponding time points comprises:

[0016] calculating the slope of the curve model based on the following formula:

[0017] wherein and are the ct value data and corresponding time points of the i th time point, and n is the total number of time points, and are the average of all ct value data and the average of all time points, respectively;

[0018] calculating the intercept of the curve model based on the following formula: .

[0019] In one or more embodiments, the step of calculating the slope standard error of the fitting curve and obtaining the t value of the fitting curve in combination with the slope of the fitting curve comprises:

[0020] calculating the slope standard error of the fitting curve based on the following formula: .

[0021] wherein is the slope of the fitting curve, is the intercept of the fitting curve, and are the ct value data and corresponding time points of the i th time point, and n is the total number of time points, This is the average value across all time points;

[0022] The t-value of the fitted curve is calculated based on the following formula:

[0023] In the formula, The standard error of the slope, is the slope of the fitted curve.

[0024] In one or more embodiments, in the step of determining whether the t-value of the fitted curve is less than the t-test critical value, the t-test critical value is the t-test critical value with n-2 degrees of freedom at a 95% confidence level.

[0025] In one or more embodiments, the step of calculating the confidence probability of a preset shelf life of the standard sample includes:

[0026] Based on the slope standard error and the preset validity period, the long-term stability standard uncertainty of the standard sample is obtained;

[0027] Substituting the long-term stability standard uncertainty and the intercept of the fitted curve into the normal distribution cumulative function, the confidence probability of the preset validity period of the standard sample is obtained.

[0028] In one or more embodiments, it further includes:

[0029] If the probability of certainty regarding the preset validity period of a standard sample is less than a threshold, the preset validity period is reduced by a preset value, and the probability of certainty is recalculated until the probability of certainty is greater than or equal to the threshold.

[0030] To achieve the above objectives, a second aspect of this application provides a device for assessing the validity period of nucleic acid qualitative standard samples of *Pleurotus ostreatus*, a pathogen causing fruit rot in pears, comprising:

[0031] The data acquisition module is used to acquire ct value data obtained from real-time fluorescence PCR experiments of standard samples at different time points;

[0032] The fitting module is used to construct a fitting curve based on the ct value data and the corresponding time points;

[0033] The first calculation module is used to calculate the standard error of the slope of the fitted curve, and combine it with the slope of the fitted curvature to obtain the t-value of the fitted curve.

[0034] The judgment module is used to determine whether the t-value of the fitted curve is less than the t-test critical value;

[0035] The second calculation module is used to calculate the confidence probability of the preset validity period of the standard sample when the t-value of the fitted curve is less than the t-test critical value.

[0036] The output module is used to use the preset validity period as the validity period of the standard sample when the confidence probability is greater than the threshold.

[0037] To achieve the above objectives, a third aspect of this application provides an electronic device, comprising:

[0038] At least one processor; and

[0039] The memory stores instructions that, when executed by the at least one processor, cause the at least one processor to perform the method for assessing the validity period of nucleic acid qualitative standard samples of *Pleurotus erythrorhizon* fruit rot pathogen as described in any of the above embodiments.

[0040] To achieve the above objectives, a fourth aspect of this application provides a machine-readable storage medium storing executable instructions that, when executed, cause the machine to perform the method for assessing the validity period of nucleic acid qualitative standard samples of *Pleurotus ostreatus* fruit rot pathogen as described in any of the above embodiments.

[0041] The advantages of this application, which differ from existing technologies, are:

[0042] The method of this application analyzes the CT value data at each time point input by the user and the preset validity period to determine whether the stability of the standard sample within the preset validity period meets the requirements. If the requirements are not met, the method outputs the validity period data that can guarantee the stability of the standard sample. After obtaining the validity period data, the experimenters can effectively reduce the number of experimental tests on the standard sample, reduce the occupation of experimental resources and manpower costs, and ensure the stability of the standard sample. Attached Figure Description

[0043] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0044] Figure 1 This is a flowchart illustrating one implementation method of the method for assessing the validity period of the nucleic acid qualitative standard sample of *Pleurotus ostreatus*, the pathogen of fruit rot in pear, as described in this application.

[0045] Figure 2 This is a schematic diagram of an embodiment of the fitting curve of this application;

[0046] Figure 3 yes Figure 1 A flowchart of one embodiment corresponding to S500;

[0047] Figure 4 This is a flowchart illustrating one implementation method of the device for evaluating the validity period of nucleic acid qualitative standard samples of Pyrus pyriformis fruit rot pathogens as described in this application;

[0048] Figure 5 This is a schematic diagram of one embodiment of the electronic device of this application. Detailed Implementation

[0049] To enable those skilled in the art to better understand the technical solutions in this application, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of this application.

[0050] The stability of standard samples for pathogens is of great significance for ensuring sensitive, specific, and rapid detection of quarantine pathogenic fungi. For the nucleic acid qualitative standard sample of *Pleurotus ostreatus*, the pathogen causing fruit rot in pears, existing technologies use intermittent repeated experiments to test the stability of the standard sample. This method can only detect the real-time stability of the standard sample during the experiment and cannot predict the shelf life of the standard, while also consuming a large amount of experimental resources and manpower.

[0051] To address the problems existing in the prior art, the applicant has developed a method for evaluating the validity period of nucleic acid qualitative standard samples of *Pleurotus ostreatus*, a pathogen causing fruit rot in pears. This method is specifically used to analyze the input qt-PCR detection data of the pathogen and the preset validity period to determine whether the stability of the standard sample of the pathogen meets the requirements under the preset validity period. This allows researchers to obtain the accurate validity period of the standard sample, which can significantly reduce the number of experiments and help reduce the consumption of experimental resources and manpower.

[0052] Specifically, please refer to Figure 1 , Figure 1 This is a flowchart illustrating one implementation method of the method for assessing the validity period of the nucleic acid qualitative standard sample of *Pleurotus ostreatus*, the pathogen of fruit rot in pear, as described in this application.

[0053] like Figure 1 As shown, the assessment method includes:

[0054] S100. Obtain ct value data from real-time fluorescence PCR experiments of standard samples at different time points.

[0055] First, obtain ct value data from real-time fluorescence PCR experiments on standard samples at different time points. The time points can be at any interval, and the interval between adjacent time points can be the same or different, all of which can achieve the effect of this implementation method.

[0056] Real-time fluorescence PCT experiment is a commonly used experimental method known to those skilled in the art. The primer and probe sequences for Pyrodisiac borscht, the fruit rot pathogen, are existing technologies and will not be described in detail here.

[0057] In one implementation, the ct values ​​of a standard sample obtained by real-time fluorescence PCT experiments at 0, 6, 12, 36, 72, and 108 months can be obtained. Each measurement can be set up with 3 parallel experiments, and the average value of the 3 experiments is taken as the input value.

[0058] For example, ct value data can be shown in Table 1.

[0059] Table 1. CT values ​​at different time points

[0060] S200. Based on the ct value data and the corresponding time points, construct the fitting curve.

[0061] After obtaining the ct value data for each time point, a fitted curve can be constructed to describe the mapping relationship between the time points and the ct value data.

[0062] In one implementation, the fitted curve can be considered as a regression line, and a curve model is first constructed based on the following formula: .

[0063] Of course, in other implementations, the fitted curve can also be constructed in other ways, such as the least squares method.

[0064] After constructing the curve module, the slope of the curve model can be calculated based on the ct value data and the corresponding time points. and intercept Then, substitute the values ​​into the curve model to obtain the fitted curve.

[0065] Specifically, in one implementation, the slope of the curve model can be calculated based on the following formula. :

[0066] In the formula, and These represent the ct value data for the i-th time point and the corresponding time point, respectively, where n is the total number of time points. and These represent the average value of all ct values ​​and the average value of all time points, respectively.

[0067] Furthermore, the intercept of the curve model is calculated based on the following formula. : .

[0068] Taking the data shown in Table 1 as an example, after calculation , The resulting fitted curve is as follows: Figure 2 As shown. Figure 2 This is a schematic diagram of an embodiment of the fitting curve of this application.

[0069] S300. Calculate the standard error of the slope of the fitted curve, and combine it with the slope of the fitted curvature to obtain the t-value of the fitted curve.

[0070] After the fitted curve is constructed, a t-test is used to detect whether there is a significant difference between the slope of the fitted curve and 0.

[0071] First, the standard error of the slope of the fitted curve needs to be calculated. In one implementation, it can be calculated using the following formula:

[0072] In the formula, Let be the slope of the fitted curve. The intercept of the fitted curve is . and These represent the ct value data for the i-th time point and the corresponding time point, respectively, where n is the total number of time points. This is the average value across all time points.

[0073] Taking the data in Table 1 as an example, after calculation .

[0074] After calculating the standard error of the slope, the t-value of the fitted curve can be obtained by calculating the ratio of the absolute value of the slope to the standard error of the slope. Specifically, the calculation formula is as follows:

[0075] In the formula, The standard error of the slope, represents the slope of the fitted curve.

[0076] Taking the data in Table 1 as an example, the calculated t value is .

[0077] S400. Determine whether the t-value of the fitted curve is less than the critical value of the t-test.

[0078] After obtaining the t-value of the fitted curve, we determine whether there is a significant difference between the slope of the fitted curve and 0 by judging whether the t-value is less than the critical value of the t-test.

[0079] In one implementation, the critical value for the t-test is the critical value for the t-test with n-2 degrees of freedom at a 95% confidence level, which can be obtained by looking up a table.

[0080] Taking the data in Table 1 as an example, the t-value The critical value for the t-test is 1.87. It is 2.776. By comparison, we can see that... This indicates that the slope of the fitted curve is not significantly different from 0.

[0081] Understandably, if the t-value of the fitted curve is greater than the critical value of the t-test, then the slope of the fitted curve is significantly different from 0, and the fitted curve is unstable. Therefore, it is necessary to refit the curve or conduct new experiments to obtain new data.

[0082] If the t-value of the fitted curve is less than the critical value of the t-test, then it includes:

[0083] S500, Calculate the confidence probability of the preset validity period of the standard sample.

[0084] The preset validity period is a value preset by the user, which is generally the limited period that the user expects to achieve, such as 9 years.

[0085] In one implementation, please refer to Figure 3 , Figure 3 yes Figure 1 A flowchart of one embodiment corresponding to S500.

[0086] like Figure 3 As shown, the method for calculating the certainty probability of a preset validity period may include:

[0087] S501. Based on the slope standard error and the preset validity period, the long-term stability standard uncertainty of the standard sample is obtained.

[0088] Specifically, the long-term stability standard uncertainty of the standard sample can be calculated based on the following formula:

[0089] In the formula, The standard uncertainty is the long-term stability, and t is the preset validity period.

[0090] For example, taking the data in Table 1 as an example, .

[0091] S502. Substitute the long-term stability standard uncertainty and the intercept of the fitted curve into the normal distribution cumulative function to obtain the confidence probability of the preset validity period of the standard sample.

[0092] Since the Ct value follows a normal distribution, after obtaining the long-term stability standard uncertainty, based on the standard uncertainty and the intercept of the fitted curve, it can be substituted into the normal distribution cumulative function to obtain the confidence probability of the preset validity period of the standard sample.

[0093] Referring to the positive criterion in SN / T 5467-2022, a test result is considered positive when Ct ≤ 35. Therefore, the standard sample can be calculated. The cumulative probability is calculated using the following formula:

[0094] For example, taking the data in Table 1 as an example, According to the table Therefore, the probability of obtaining the preset shelf life of the standard sample is 100%.

[0095] S600. If the probability of certainty is greater than the threshold, the preset validity period shall be used as the validity period of the standard sample.

[0096] The threshold can be preset based on the specific scenario; for example, the threshold can be 95%.

[0097] Taking the data in Table 1 as an example, the confidence probability of the preset validity period of the standard sample is 100%, which is greater than the threshold. Therefore, the preset validity period of 9 years can be used as the validity period of the standard sample.

[0098] It should be noted that if the confidence probability is less than the threshold, the preset validity period can be reduced by the preset value, and the confidence probability can be recalculated until the confidence probability is greater than or equal to the threshold.

[0099] For example, if the probability of certainty is less than the threshold, the preset validity period can be reduced by 6 months and recalculated until the probability of certainty is greater than or equal to the threshold.

[0100] Based on the methods described above, by acquiring the CT value data at each time point input by the user and the preset validity period, it is possible to determine whether the stability of the standard sample within the preset validity period meets the requirements. If the requirements are not met, the method can automatically output validity period data that ensures the stability of the standard sample. After obtaining the validity period data, researchers can effectively reduce the number of experimental tests on the standard sample, reduce the occupation of experimental resources and labor costs, and ensure the stability of the standard sample.

[0101] This application also provides a device for assessing the validity period of nucleic acid qualitative standard samples of *Pleurotus ostreatus*, the pathogen causing fruit rot in pears. Please refer to [link / reference needed].Figure 4 , Figure 4 This is a flowchart illustrating one implementation method of the device for evaluating the validity period of nucleic acid qualitative standard samples of Pyrus pyriformis fruit rot pathogens in this application.

[0102] like Figure 4 As shown, the evaluation device includes a data acquisition module 21, a fitting module 22, a first calculation module 23, a judgment module 24, a second calculation module 25, and an output module 26.

[0103] Among them, the data acquisition module 21 is used to acquire ct value data obtained by real-time fluorescence PCR experiments of standard samples at different time points;

[0104] The fitting module 22 is used to construct a fitting curve based on the ct value data and the corresponding time points;

[0105] The first calculation module 23 is used to calculate the standard error of the slope of the fitted curve, and combined with the slope of the fitted curvature, to obtain the t-value of the fitted curve.

[0106] The judgment module 24 is used to determine whether the t-value of the fitted curve is less than the t-test critical value;

[0107] The second calculation module 25 is used to calculate the confidence probability of the preset validity period of the standard sample when the t-value of the fitted curve is less than the t-test critical value.

[0108] The output module 26 is used to set the preset validity period as the validity period of the standard sample when the confidence probability is greater than the threshold.

[0109] As per the above reference Figures 1 to 3 This specification describes a method for determining the shelf life of nucleic acid qualitative standard samples of *Plasma gondii*, the pathogen of fruit rot, according to embodiments of this specification. The details mentioned in the above description of the method embodiments also apply to the device for determining the shelf life of nucleic acid qualitative standard samples of *Plasma gondii*, the pathogen of fruit rot, according to embodiments of this specification. The above-described device for determining the shelf life of nucleic acid qualitative standard samples of *Plasma gondii*, the pathogen of fruit rot, can be implemented in hardware, software, or a combination of hardware and software.

[0110] This application also provides an electronic device, please refer to... Figure 5 , Figure 5 This is a schematic diagram of one embodiment of the electronic device of this application. For example... Figure 5 As shown, the electronic device 30 may include at least one processor 31, a memory 32 (e.g., non-volatile memory), a RAM 33, and a communication interface 34, and the at least one processor 31, memory 32, RAM 33, and communication interface 34 are connected together via a bus 35. The at least one processor 31 executes at least one computer-readable instruction stored or encoded in the memory 32.

[0111] It should be understood that the computer-executable instructions stored in memory 32, when executed, cause at least one processor 31 to perform the above-described combinations in the various embodiments of this specification. Figures 1 to 3 The description includes various operations and functions.

[0112] In the embodiments of this specification, electronic device 30 may include, but is not limited to: personal computer, server computer, workstation, desktop computer, laptop computer, notebook computer, mobile electronic device, smartphone, tablet computer, cellular phone, personal digital assistant (PDA), handheld device, messaging device, wearable electronic device, consumer electronic device, etc.

[0113] According to one embodiment, a program product, such as a machine-readable medium, is provided. The machine-readable medium may have instructions (i.e., the elements implemented in software as described above), which, when executed by a machine, cause the machine to perform the above-described combinations of the various embodiments of this specification. Figures 1 to 5 The various operations and functions described. Specifically, a system or apparatus equipped with a readable storage medium storing software program code that implements the functions of any of the embodiments described above, and enabling the computer or processor of the system or apparatus to read and execute the instructions stored in the readable storage medium.

[0114] In this case, the program code read from the readable medium itself can perform the functions of any of the above embodiments, and therefore the machine-readable code and the readable storage medium storing the machine-readable code constitute a part of this specification.

[0115] Examples of readable storage media include floppy disks, hard disks, magneto-optical disks, optical disks (such as CD-ROM, CD-R, CD-RW, DVD-ROM, DVD-RAM, DVD-RW, DVD-RW), magnetic tapes, non-volatile memory cards, and ROMs. Alternatively, program code can be downloaded from a server computer or the cloud via a communication network.

[0116] Those skilled in the art will understand that the various embodiments disclosed above can be modified and varied without departing from the spirit of the invention. Therefore, the scope of protection of this specification should be defined by the appended claims.

[0117] It should be noted that not all steps and units in the above process and system structure diagrams are mandatory; some steps or units can be omitted according to actual needs. The execution order of each step is not fixed and can be determined as needed. The device structure described in the above embodiments can be a physical structure or a logical structure. That is, some units may be implemented by the same physical client, or some units may be implemented by multiple physical clients, or they may be jointly implemented by certain components in multiple independent devices.

[0118] In the above embodiments, the hardware units or modules can be implemented mechanically or electrically. For example, a hardware unit, module, or processor may include permanent dedicated circuitry or logic (such as a dedicated processor, FPGA, or ASIC) to perform the corresponding operation. The hardware unit or processor may also include programmable logic or circuitry (such as a general-purpose processor or other programmable processor), which can be temporarily configured by software to perform the corresponding operation. The specific implementation method (mechanical, dedicated permanent circuitry, or temporarily configured circuitry) can be determined based on cost and time considerations.

[0119] The specific embodiments described above with reference to the accompanying drawings are exemplary embodiments, but do not represent all embodiments that can be implemented or fall within the scope of the claims. The term "exemplary" as used throughout this specification means "serving as an example, instance, or illustration" and does not imply that it is "preferred" or "advantageous" compared to other embodiments. Specific details are included to provide an understanding of the described techniques. However, these techniques can be practiced without these specific details. In some instances, well-known structures and apparatuses are shown in block diagram form to avoid obscuring the concepts of the described embodiments.

[0120] The foregoing description of this disclosure is provided to enable any person skilled in the art to implement or use this disclosure. Various modifications to this disclosure will be apparent to those skilled in the art, and the general principles applicable herein can be applied to other variations without departing from the scope of this disclosure. Therefore, this disclosure is not limited to the examples and designs described herein, but is consistent with the widest scope of the principles and novel features disclosed herein.

Claims

1. A method for assessing the validity period of a nucleic acid qualitative standard sample of *Pleurotus borrellis*, a pathogen causing fruit rot in pears, characterized in that... include: Obtain ct value data from real-time fluorescence PCR experiments on standard samples at different time points; Based on the ct value data and the corresponding time points, a fitting curve is constructed; Calculate the standard error of the slope of the fitted curve, and combine it with the slope of the fitted curvature to obtain the t-value of the fitted curve; Determine whether the t-value of the fitted curve is less than the t-test critical value; If so, calculate the confidence probability of the preset shelf life of the standard sample; If the certainty probability is greater than the threshold, the preset validity period shall be used as the validity period of the standard sample.

2. The evaluation method according to claim 1, characterized in that, The step of constructing the fitting curve based on the ct value data and the corresponding time points includes: The curve model is constructed based on the following formula: ; Based on the ct value data and the corresponding time points, the slope of the curve model is calculated. and intercept The fitted curve is obtained by substituting the values ​​into the curve model.

3. The evaluation method according to claim 2, characterized in that, The slope of the curve model is calculated based on the ct value data and the corresponding time point. and intercept The specific steps are as follows: The slope of the curve model is calculated based on the following formula. : In the formula, and These represent the ct value data for the i-th time point and the corresponding time point, respectively, where n is the total number of time points. and These are the average values ​​of all ct values ​​and the average values ​​at all time points, respectively. The intercept of the curve model is calculated based on the following formula. : .

4. The evaluation method according to claim 1, characterized in that, The step of calculating the standard error of the slope of the fitted curve and obtaining the t-value of the fitted curve by combining the slope of the fitted curvature includes: The standard error of the slope of the fitted curve is calculated based on the following formula. : In the formula, The slope of the fitted curve is... The intercept of the fitted curve is given. and These represent the ct value data for the i-th time point and the corresponding time point, respectively, where n is the total number of time points. This is the average value across all time points; The t-value of the fitted curve is calculated based on the following formula: In the formula, The standard error of the slope, is the slope of the fitted curve.

5. The evaluation method according to claim 1, characterized in that, In the step of determining whether the t-value of the fitted curve is less than the critical value of the t-test, the critical value of the t-test is the critical value of the t-test with n-2 degrees of freedom at a 95% confidence level.

6. The evaluation method according to claim 1, characterized in that, The steps for calculating the confidence probability of the preset validity period of the standard sample include: Based on the slope standard error and the preset validity period, the long-term stability standard uncertainty of the standard sample is obtained; Substituting the long-term stability standard uncertainty and the intercept of the fitted curve into the normal distribution cumulative function, the confidence probability of the preset validity period of the standard sample is obtained.

7. The evaluation method according to claim 1, characterized in that, Also includes: If the probability of certainty regarding the preset validity period of a standard sample is less than a threshold, the preset validity period is reduced by a preset value, and the probability of certainty is recalculated until the probability of certainty is greater than or equal to the threshold.

8. A device for assessing the validity period of a nucleic acid qualitative standard sample of *Pleurotus borrellis*, a pathogen causing fruit rot in pears, characterized in that... include: The data acquisition module is used to acquire ct value data obtained from real-time fluorescence PCR experiments of standard samples at different time points; The fitting module is used to construct a fitting curve based on the ct value data and the corresponding time points; The first calculation module is used to calculate the standard error of the slope of the fitted curve, and combine it with the slope of the fitted curvature to obtain the t-value of the fitted curve. The judgment module is used to determine whether the t-value of the fitted curve is less than the t-test critical value; The second calculation module is used to calculate the confidence probability of the preset validity period of the standard sample when the t-value of the fitted curve is less than the t-test critical value. The output module is used to use the preset validity period as the validity period of the standard sample when the confidence probability is greater than the threshold.

9. An electronic device, comprising: At least one processor; as well as A memory storing instructions that, when executed by the at least one processor, cause the at least one processor to perform the method for assessing the validity period of nucleic acid qualitative standard samples of *Pleurotus ostreatus* fruit rot pathogen as described in any one of claims 1 to 7.

10. A machine-readable storage medium storing executable instructions, which, when executed, cause the machine to perform the method for assessing the validity period of a nucleic acid qualitative standard sample of *Pleurotus ostreatus* fruit rot pathogen as described in any one of claims 1 to 7.

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