Nondestructive testing device and method for crop seeds

Abstract

The invention discloses a nondestructive testing device and method for crop seeds, relates to the technical field of crop detection, and discloses a complex nondestructive testing judgment module, a production batch selection module and a complex nondestructive testing procedure execution module. According to the device, whether subsequent complex nondestructive testing items need to be executed on the seed samples of the batch or not is judged firstly, invalid detection caused by the fact that high-cost detection resources are input into poor-quality batches is avoided, the resource utilization rate is increased, high-consistency historical production batches are rapidly selected as references through a basic nondestructive testing similarity algorithm, and the detection efficiency is improved. According to the method, a complex nondestructive testing procedure adaptive to the priority is intelligently generated, a detection item sequence is preferentially matched for complex quality risks (such as molecular structure abnormity and insufficient cell viability) possibly existing in a seed sample, targeting and high efficiency of complex detection are achieved, and the comprehensiveness and accuracy of seed quality evaluation are improved while the detection cost is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of crop detection, and more particularly to a non-destructive detection device and method for crop seeds. Background Art

[0002] In response to the core problems of the existing technology, such as rigid detection process, inefficient data utilization, and one-sided quality assessment, the present invention provides a non-destructive detection device and method for crop seeds. Summary of the Invention

[0003] In view of the shortcomings of the prior art, the object of the present invention is to provide a non-destructive testing device and method for crop seeds.

[0004] To achieve the above object, the present invention provides the following technical solutions: A nondestructive testing device for crop seeds, comprising a complex nondestructive testing determination module, a production batch selection module, and a complex nondestructive testing procedure execution module; The complex non-destructive testing determination module randomly selects multiple seed samples after each production batch of crop seeds is completed, generates a basic non-destructive testing data set for each seed sample, and determines whether to perform complex non-destructive testing steps on the production batch of crop seeds; According to the production batch selection module, after determining to perform the complex non-destructive testing step on the seed sample of the production batch, the non-destructive testing basis production batch is selected from all previous production batches corresponding to the crop seeds; The complex non-destructive testing procedure execution module determines the complex non-destructive testing procedures for seed samples in the current production batch according to the selected non-destructive testing basis production batch, and performs various complex non-destructive tests on the seed samples in the current production batch according to the complex non-destructive testing procedures.

[0005] Furthermore, it is determined whether to perform complex nondestructive testing steps on the seed samples of the production batch: the basic nondestructive testing data set of each seed sample is imported into the basic nondestructive testing model respectively, the basic nondestructive testing model derives the basic nondestructive analysis values ​​of various sub-samples, the basic nondestructive analysis values ​​of all seed samples are summed and averaged, a comprehensive basic nondestructive analysis value is calculated, a comprehensive basic nondestructive analysis threshold is set, and when the comprehensive basic nondestructive analysis value is greater than or equal to the comprehensive basic nondestructive analysis threshold, it is determined to perform complex nondestructive testing steps on the seed samples of the production batch.

[0006] Furthermore, a basic non-destructive testing data set for each seed sample is generated: various basic non-destructive tests are performed on each seed sample to further generate a basic non-destructive testing data set for each seed sample.

[0007] Furthermore, the steps for generating a basic nondestructive testing data set of a seed sample are as follows: selecting a seed sample, obtaining the test data of the seed sample for each basic nondestructive test, and combining the test data of each basic nondestructive test in the form of a data set to form a basic nondestructive testing data set.

[0008] Furthermore, a non-destructive testing basis production batch is selected from all previous production batches corresponding to crop seeds: the non-destructive testing basis values ​​corresponding to each previous production batch of the system are obtained, a non-destructive testing basis threshold is set, and when the non-destructive testing basis value is greater than or equal to the non-destructive testing basis threshold, the production batch is marked as a non-destructive testing basis production batch.

[0009] Furthermore, the steps for obtaining the non-destructive testing basis value corresponding to the production batch are as follows: select a production batch, mark all seed samples in the production batch as control seed samples, determine the basic non-destructive testing control value of each control seed sample, sum and average the basic non-destructive testing control value of each control seed sample, and calculate the non-destructive testing basis value corresponding to the production batch.

[0010] Furthermore, the steps for determining the basic non-destructive testing control value of the control seed sample are as follows: determine all seed samples in the current production batch, select a control seed sample, determine the basic non-destructive testing similarity between the control seed sample and each seed sample, calculate the average of all basic non-destructive testing similarities, and calculate the average basic non-destructive testing similarity, and mark it as , calculate the absolute difference between all basic non-destructive testing similarities, calculate the basic non-destructive difference degree, calculate the sum and mean of all basic non-destructive difference degrees, and calculate the average basic non-destructive difference degree ,pass Calculate the basic non-destructive test control value of the control seed sample .

[0011] Furthermore, the steps for determining the basic non-destructive testing similarity between the control seed sample and a seed sample are as follows: obtaining a basic non-destructive testing data set of the control seed sample, selecting a seed sample, obtaining a basic non-destructive testing data set of the seed sample, vectorizing the test data of each basic non-destructive test in the two basic non-destructive testing data sets, and calculating the basic non-destructive testing similarity using a similarity calculation formula.

[0012] Furthermore, the steps for determining the complex non-destructive testing procedures for seed samples in the current production batch are as follows: obtaining the number of complex testing executions of each complex non-destructive testing corresponding to each production batch, and then determining the complex testing procedure value of each complex non-destructive testing, sorting the complex testing procedure values ​​from large to small, and generating the complex non-destructive testing procedures based on the sorting order; The steps for obtaining the number of complex test executions corresponding to a complex non-destructive test based on a non-destructive test production batch are as follows: select a non-destructive test based on a production batch and a complex non-destructive test. If the complex non-destructive test is performed on the seed sample in the production batch based on the non-destructive test, the number of complex test executions is increased by one. If the complex non-destructive test is not performed on the seed sample in the production batch based on the non-destructive test, the number of complex test executions is 0. The steps for determining the complex testing procedure value of a complex non-destructive test are as follows: select a complex non-destructive test, calculate the sum of the number of complex tests performed for each non-destructive test according to the production batch, and calculate the complex testing procedure value of the complex non-destructive test.

[0013] Furthermore, a non-destructive testing method for crop seeds comprises the following steps: Step 1: After each batch of crop seeds is produced, determine whether to perform a complex non-destructive testing step on the production batch of crop seeds; Step 2: After determining that the complex non-destructive testing steps are to be performed on the seed samples of the production batch, the production batch based on the non-destructive testing is selected; Step 3: Determine complex nondestructive testing procedures for seed samples from current production batches; Step 4: Perform various complex non-destructive tests on seed samples in the current production batch according to the complex non-destructive testing procedures.

[0014] Compared with the prior art, the present invention has the following beneficial effects: The device and method of the present invention, through the cooperation between various modules, first perform various basic non-destructive tests on seed samples in a batch, and based on the detection data of the basic non-destructive tests, determine whether it is necessary to perform subsequent complex non-destructive testing projects on the seed samples in the batch, so as to avoid ineffective testing caused by high-cost testing resources being invested in inferior batches, improve resource utilization, and quickly select historical production batches with high consistency as a reference through the basic non-destructive testing similarity algorithm, intelligently generate complex non-destructive testing procedures with adaptive priorities, and prioritize matching the order of detection items with possible complex quality risks (such as abnormal molecular structure and insufficient cell activity) of seed samples, so as to achieve the targeting and efficiency of complex detection, and improve the comprehensiveness and accuracy of seed quality assessment while reducing detection costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 This is a principle diagram of the device of the present invention; Figure 2 Flowchart of the method of the present invention. DETAILED DESCRIPTION

[0016] Example 1: Figure 1, a non-destructive testing device for crop seeds (non-destructive testing refers to the detection and evaluation of seed quality, vitality, composition, internal structure and other characteristics without destroying the integrity and physiological activity of the seeds), including a complex non-destructive testing judgment module, a production batch selection module, and a complex non-destructive testing procedure execution module.

[0017] The complex non-destructive testing judgment module randomly selects multiple seed samples from each production batch of crop seeds after the production is completed (the definition of a production batch of crop seeds is: a collection of seeds of the same variety, same source, same breeding generation, same production season, and same processing batch) based on a pre-set sample extraction ratio (the setting of the pre-set sample extraction ratio is the result of a comprehensive balance of multiple factors, and must take into account statistical principles, national standards, seed characteristics, testing requirements, and quality risk control). Basic non-destructive testing is performed on each seed sample to generate a basic non-destructive testing data set for each seed sample to determine whether complex non-destructive testing steps should be performed on the production batch of crop seeds.

[0018] Determine whether to perform complex nondestructive testing steps on the production batch seed samples: import the basic nondestructive testing data set of each seed sample into the basic nondestructive testing model respectively, the basic nondestructive testing model derives the basic nondestructive analysis values ​​of various sub-samples, sums and averages the basic nondestructive analysis values ​​of all seed samples, calculates the comprehensive basic nondestructive analysis value, sets the comprehensive basic nondestructive analysis threshold (pre-set), and when the comprehensive basic nondestructive analysis value is greater than or equal to the comprehensive basic nondestructive analysis threshold, determine to perform complex nondestructive testing steps on the production batch seed samples (otherwise, there is no need to perform complex nondestructive testing steps on the production batch seed samples, because the production batch seed samples cannot meet the basic quality requirements, and there is no need to analyze their complex quality data again).

[0019] The steps for building a basic nondestructive testing model are as follows: build a deep learning model, collect multiple basic nondestructive testing data sets, use the basic nondestructive testing data sets as basic data, and train the built deep learning model. In this process, a basic nondestructive analysis value is assigned to each basic nondestructive testing data set. The value range of the basic nondestructive analysis value is set between 1 and 100. The size of the basic nondestructive analysis value has a clear meaning. The larger the value, the more basic nondestructive analysis value corresponds to the basic quality requirements of the seed sample under various basic nondestructive testing conditions. Then, the multiple basic nondestructive testing data sets are divided into training set, validation set and test set according to a specific ratio. The specific division ratio is determined to be 60%:20%:20%. First, the deep learning model is repeatedly trained using the training set. During the training process, the validation set is used to timely verify the performance of the model in the training stage. According to the verification results, the model parameters are adjusted in time to optimize the model structure to make it develop in a more accurate and stable direction. Finally, the basic nondestructive testing model is built.

[0020] Perform basic nondestructive testing on each seed sample to generate a basic nondestructive testing dataset for each seed sample: Perform various basic nondestructive tests on each seed sample (basic nondestructive testing includes but is not limited to the following: machine vision inspection project, near-infrared spectroscopy moisture detection project, vibration spectroscopy inspection project. The function of the machine vision inspection project is to analyze the appearance characteristics of the seed sample through two-dimensional images. The function of the near-infrared spectroscopy moisture detection project is to quantify the moisture content and moisture uniformity of the seed sample. The function of the vibration spectroscopy inspection project is to analyze the fullness and internal structure integrity of the seed sample through the natural vibration frequency. The common characteristics of all basic nondestructive testing projects are simple detection methods and fast detection speed, which can quickly detect some characteristics of the nondestructive testing of related seed samples). Then, a basic nondestructive testing dataset for each seed sample is generated.

[0021] The steps for generating a basic nondestructive testing dataset for a seed sample are as follows: select a seed sample, obtain the test data of each basic nondestructive test for the seed sample (each basic nondestructive test corresponds to corresponding test data, such as machine vision test items corresponding to roundness, aspect ratio, breakage rate and other test data, near-infrared spectroscopy moisture test items corresponding to moisture content, moisture standard deviation and other test data, vibration spectroscopy test items corresponding to fundamental frequency, vibration attenuation rate and other test data), and combine the test data of each basic nondestructive test in the form of a data set to form a basic nondestructive testing dataset.

[0022] According to the production batch selection module, after determining to perform complex non-destructive testing steps on the seed samples of the production batch, the non-destructive testing basis production batch is selected from all previous production batches corresponding to the crop seeds.

[0023] Select the non-destructive testing basis production batch from all previous production batches corresponding to crop seeds: obtain the non-destructive testing basis values ​​corresponding to previous production batches in the system, set the non-destructive testing basis threshold (pre-set), and when the non-destructive testing basis value is greater than or equal to the non-destructive testing basis threshold, mark the production batch as the non-destructive testing basis production batch (otherwise, do not mark it).

[0024] The steps for obtaining the non-destructive testing basis value corresponding to the production batch are as follows: select a production batch, mark all seed samples in the production batch as control seed samples, determine the basic non-destructive testing control value of each control seed sample, sum and average the basic non-destructive testing control value of each control seed sample, and calculate the non-destructive testing basis value corresponding to the production batch.

[0025] The steps for determining the basic non-destructive testing control value of the control seed sample are as follows: determine all seed samples in the current production batch, select a control seed sample, determine the basic non-destructive testing similarity between the control seed sample and each seed sample, calculate the average basic non-destructive testing similarity by summing up all the basic non-destructive testing similarities, and calculate the average basic non-destructive testing similarity and mark it as , calculate the absolute difference between all basic non-destructive testing similarities, calculate the basic non-destructive gap, calculate the sum and mean of all basic non-destructive gaps, and calculate the average basic non-destructive gap ,pass Calculate the basic non-destructive test control value of the control seed sample .

[0026] The steps for determining the basic nondestructive testing similarity between a control seed sample and a seed sample are as follows: obtain the basic nondestructive testing data set of the control seed sample, select a seed sample, obtain the basic nondestructive testing data set of the seed sample, vectorize the test data of each basic nondestructive test in the two basic nondestructive testing data sets, and calculate the basic nondestructive testing similarity using the similarity calculation formula.

[0027] The detection data of each basic nondestructive testing in the two basic nondestructive testing data sets are vectorized, and the basic nondestructive testing similarity is calculated using the similarity calculation formula: The detection data of each basic nondestructive testing in the control seed sample are vectorized and converted into a feature vector A=(a1,a2,...,a n ), the test data of each basic non-destructive test in the seed sample are vectorized and converted into a feature vector B=(b1,b2,...,b n ), using the similarity formula Calculate the basic nondestructive testing similarity.

[0028] The complex non-destructive testing procedure execution module determines the complex non-destructive testing procedure for the seed samples in the current production batch according to the selected non-destructive testing production batch (the complex non-destructive testing procedure includes various complex non-destructive tests arranged in a certain order, and the complex non-destructive testing includes but is not limited to the following items: Fourier transform infrared spectroscopy detection item, fluorescence imaging item. The role of the Fourier transform infrared spectroscopy detection item is to provide molecular structure information of chemical components without destroying the integrity of the seeds. The role of the fluorescence imaging item is to specifically mark the physiological state of the living cells of the seeds with fluorescent dyes to achieve cell-level activity evaluation, and the entire detection process does not destroy the integrity of the seeds). According to the complex non-destructive testing procedures, various complex non-destructive tests are performed on the seed samples in the current production batch (for example, if the first item in the complex non-destructive testing procedures is the Fourier transform infrared spectroscopy test item, then the Fourier transform infrared spectroscopy test is performed on all seed samples first. After all the seed samples in the current production batch have completed the Fourier transform infrared spectroscopy test item, if the seed samples do not meet the complex quality standards of the Fourier transform infrared spectroscopy test item, there is no need to perform subsequent complex non-destructive tests on the seed samples in the current production batch. If they meet the complex quality standards of the Fourier transform infrared spectroscopy test item, the next complex non-destructive test in the order is performed on the seed samples in the current production batch).

[0029] The steps for determining the complex non-destructive testing procedures for seed samples in the current production batch are as follows: obtain the number of complex testing executions of each complex non-destructive test corresponding to the production batch, and then determine the complex testing procedure value of each complex non-destructive test, sort the complex testing procedure values ​​from large to small, and generate the complex non-destructive testing procedures based on the sorting order.

[0030] The steps for obtaining the number of complex test executions corresponding to a complex non-destructive test for a non-destructive test basis production batch are as follows: select a non-destructive test basis production batch and select a complex non-destructive test. When the complex non-destructive test is performed on the seed sample in the non-destructive test basis production batch, the number of complex test executions is increased by one. When the complex non-destructive test is not performed on the seed sample in the non-destructive test basis production batch (because the seed sample in the non-destructive test basis production batch does not meet the corresponding complex quality standards in the previous complex non-destructive test project, the complex non-destructive test is not performed), the number of complex test executions is 0.

[0031] The steps for determining the complex testing procedure value of a complex non-destructive test are as follows: select a complex non-destructive test, calculate the sum of the number of complex tests performed for each non-destructive test according to the production batch, and calculate the complex testing procedure value of the complex non-destructive test.

[0032] Through the cooperation between various modules, the above-mentioned device first performs various basic non-destructive tests on the seed samples in the batch, and based on the test data of the basic non-destructive tests, determines whether it is necessary to perform subsequent complex non-destructive testing projects on the seed samples in the batch, so as to avoid ineffective testing caused by high-cost testing resources being invested in inferior batches, improve resource utilization, and quickly select highly consistent historical production batches as a reference through the basic non-destructive testing similarity algorithm, intelligently generate priority-adapted complex non-destructive testing procedures, and prioritize matching the order of test items with possible complex quality risks of seed samples (such as abnormal molecular structure and insufficient cell activity), so as to achieve the targeting and efficiency of complex testing, and improve the comprehensiveness and accuracy of seed quality assessment while reducing testing costs.

[0033] Example 2: Figure 2 , a non-destructive testing method for crop seeds, the steps are as follows: Step 1: After each batch of crop seeds is produced, determine whether to perform a complex non-destructive testing step on the production batch of crop seeds; Step 2: After determining that the complex non-destructive testing steps are to be performed on the seed samples of the production batch, the production batch based on the non-destructive testing is selected; Step 3: Determine complex nondestructive testing procedures for seed samples from current production batches; Step 4: Perform various complex non-destructive tests on seed samples in the current production batch according to the complex non-destructive testing procedures.

[0034] The above formulas are all dimensionless and numerical calculations. The formulas are obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters in the formulas are set by technicians in this field according to actual conditions.

[0035] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0036] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0037] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0038] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0039] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

Claims

1. A non-destructive testing device for crop seeds, characterized in that: include The complex non-destructive testing determination module randomly selects multiple seed samples after each production batch of crop seeds is completed, generates a basic non-destructive testing data set for each seed sample, and determines whether to perform complex non-destructive testing steps on the production batch of crop seeds; According to the production batch selection module, after determining to perform the complex non-destructive testing step on the seed sample of the production batch, the non-destructive testing basis production batch is selected from all previous production batches corresponding to the crop seeds; The complex non-destructive testing procedure execution module determines the complex non-destructive testing procedures for seed samples in the current production batch according to the selected non-destructive testing basis production batch, and performs various complex non-destructive tests on the seed samples in the current production batch according to the complex non-destructive testing procedures.

2. The nondestructive testing device for crop seeds according to claim 1, characterized in that: Determine whether to perform complex nondestructive testing steps on the production batch seed samples: import the basic nondestructive testing data set of each seed sample into the basic nondestructive testing model respectively, the basic nondestructive testing model derives the basic nondestructive analysis values ​​of various sub-samples, sums and averages the basic nondestructive analysis values ​​of all seed samples, calculates the comprehensive basic nondestructive analysis value, sets the comprehensive basic nondestructive analysis threshold, and determines to perform complex nondestructive testing steps on the production batch seed samples when the comprehensive basic nondestructive analysis value is greater than or equal to the comprehensive basic nondestructive analysis threshold.

3. The non-destructive testing device for crop seeds according to claim 1, characterized in that: Generate a basic nondestructive testing dataset for each seed sample: Perform various basic nondestructive tests on each seed sample to further generate a basic nondestructive testing dataset for each seed sample.

4. The non-destructive testing device for crop seeds according to claim 3, characterized in that: The steps for generating a basic nondestructive testing dataset of a seed sample are as follows: select a seed sample, obtain the test data of the seed sample for each basic nondestructive test, and combine the test data of each basic nondestructive test in the form of a data set to form a basic nondestructive testing dataset.

5. The non-destructive testing device for crop seeds according to claim 1, characterized in that: Select the non-destructive testing basis production batch from all previous production batches corresponding to crop seeds: obtain the non-destructive testing basis values ​​corresponding to previous production batches in the system, set the non-destructive testing basis threshold, and when the non-destructive testing basis value is greater than or equal to the non-destructive testing basis threshold, mark the production batch as the non-destructive testing basis production batch.

6. The non-destructive testing device for crop seeds according to claim 5, characterized in that: The steps for obtaining the non-destructive testing basis value corresponding to the production batch are as follows: select a production batch, mark all seed samples in the production batch as control seed samples, determine the basic non-destructive testing control value of each control seed sample, sum and average the basic non-destructive testing control value of each control seed sample, and calculate the non-destructive testing basis value corresponding to the production batch.

7. The non-destructive testing device for crop seeds according to claim 6, characterized in that: The steps for determining the basic non-destructive testing control value of the control seed sample are as follows: determine all seed samples in the current production batch, select a control seed sample, determine the basic non-destructive testing similarity between the control seed sample and each seed sample, calculate the average basic non-destructive testing similarity by summing up all the basic non-destructive testing similarities, and calculate the average basic non-destructive testing similarity and mark it as , calculate the absolute difference between all basic non-destructive testing similarities, calculate the basic non-destructive difference degree, calculate the sum and mean of all basic non-destructive difference degrees, and calculate the average basic non-destructive difference degree ,pass Calculate the basic non-destructive test control value of the control seed sample .

8. The non-destructive testing device for crop seeds according to claim 7, characterized in that: The steps for determining the basic nondestructive testing similarity between a control seed sample and a seed sample are as follows: obtain the basic nondestructive testing data set of the control seed sample, select a seed sample, obtain the basic nondestructive testing data set of the seed sample, vectorize the test data of each basic nondestructive test in the two basic nondestructive testing data sets, and calculate the basic nondestructive testing similarity using the similarity calculation formula.

9. The non-destructive testing device for crop seeds according to claim 1, characterized in that: The steps for determining the complex non-destructive testing procedures for seed samples in the current production batch are as follows: obtaining the number of complex testing executions of each complex non-destructive testing corresponding to each production batch, and then determining the complex testing procedure value of each complex non-destructive testing, sorting the complex testing procedure values ​​from large to small, and generating the complex non-destructive testing procedures based on the sorting order; The steps for obtaining the number of complex test executions corresponding to a complex non-destructive test based on a non-destructive test production batch are as follows: select a non-destructive test based on a production batch and a complex non-destructive test. If the complex non-destructive test is performed on the seed sample in the production batch based on the non-destructive test, the number of complex test executions is increased by one. If the complex non-destructive test is not performed on the seed sample in the production batch based on the non-destructive test, the number of complex test executions is 0. The steps for determining the complex testing procedure value of a complex non-destructive test are as follows: select a complex non-destructive test, calculate the sum of the number of complex tests performed for each non-destructive test according to the production batch, and calculate the complex testing procedure value of the complex non-destructive test.

10. A non-destructive testing method for crop seeds, applied to a non-destructive testing device for crop seeds according to any one of claims 1 to 9, characterized in that: Here are the steps: Step 1: After each batch of crop seeds is produced, determine whether to perform a complex non-destructive testing step on the production batch of crop seeds; Step 2: After determining that the complex non-destructive testing steps are to be performed on the seed samples of the production batch, the production batch based on the non-destructive testing is selected; Step 3: Determine complex nondestructive testing procedures for seed samples from current production batches; Step 4: Perform various complex non-destructive tests on seed samples in the current production batch according to the complex non-destructive testing procedures.

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