A rapid identification of traditional Chinese medicinal materials 60 System of co-gamma irradiation dose and its construction method and use

Abstract

The application provides a kind of rapid identification of traditional Chinese medicinal materials 60 The application provides a system and method for Co-gamma irradiation dose, wherein the system comprises the following modules: a data acquisition module, a database module, a data processing module, a verification module, a data analysis module and a result output module.The application can quickly and accurately identify traditional Chinese medicinal materials, especially cortex moutan, by using the factorization method to establish an identification model after the NIRS spectrum data is pretreated by the second derivative 60 Co-gamma irradiation dose range.Compared with the traditional HPLC method, the sampling process is simple, the sample is not damaged, there is no chemical reagent pollution, the detection efficiency is high, and the method has practical popularization and application value.

Description

Technical Field

[0001] This invention relates to the field of Chinese medicinal material testing, specifically to a rapid identification method for Chinese medicinal materials. 60 Systems for Co-γ irradiation dose, their construction methods, and applications. Background Technology

[0002] 60 Co-γ irradiation sterilization is a relatively new disinfection and sterilization method developed in recent years. It is performed at room temperature and features strong penetration, uniform disinfection, and rapid and simple operation. my country has relevant regulations on irradiation sterilization; the former Ministry of Health of the People's Republic of China issued the "Regulations on Irradiation Sterilization" in 1997. 60 The Co irradiation sterilization dose standard for traditional Chinese medicine (internal trial) (Health Drug Administration Document

[1997] No. 38) stipulates that the maximum absorbed dose of traditional Chinese medicine raw material powder should not exceed 6 kGy; the former State Food and Drug Administration Notice "Technical Guidelines for Irradiation Sterilization of Traditional Chinese Medicine" (

[2015] No. 86) stipulates that the maximum overall average irradiation dose of traditional Chinese medicine should not exceed 10 kGy in principle.

[0003] Market research has revealed that irradiation doses of some Chinese medicinal herbs in certain regions of my country exceed the permitted levels, generally ranging from 10-15 kGy, with some varieties reaching up to 30 kGy. Among these, peony bark is a permitted irradiation herb, and this variety has been exposed to doses exceeding 10 kGy. 60 Co-γ irradiation alters the HPLC (high-performance liquid chromatography) fingerprint, so HPLC is currently the primary method for monitoring the irradiation status of peony bark. However, this method requires highly skilled personnel and is time-consuming and labor-intensive, limiting its application. Therefore, it is necessary to develop a simple and easy-to-operate method for treating traditional Chinese medicinal materials, especially peony bark. 60 Methods for determining Co-γ irradiation dose. Summary of the Invention

[0004] To address the above problems, this invention provides a rapid method for identifying Chinese medicinal materials. 60 The Co-γ irradiation dose system includes the following modules:

[0005] Data acquisition module: Acquires NIRS spectral data of Chinese medicinal materials;

[0006] Database module: with different dosages 60 The NIRS spectral data of Chinese medicinal materials treated with Co-γ irradiation were used to construct a database, which was randomly divided into a reference spectrum set and a test spectrum set.

[0007] Data processing module: Uses factorization to combine the preprocessed reference spectrum with... 60 Correlate Co-γ irradiation doses to construct a near-infrared discrimination model;

[0008] Validation module: Validates the near-infrared discrimination model using a test spectrum set;

[0009] Data Analysis Module: Utilizes a validated near-infrared identification model to analyze the NIRS spectral data of the tested Chinese medicinal materials, obtaining the... 60 Co-γ irradiation dose range;

[0010] Result Output Module: Outputs Chinese medicinal materials 60 Results of the Co-γ irradiation dose range.

[0011] Furthermore, the resolution of the NIRS spectrum is 8 cm⁻¹. -1 Spectral range 12000~4000cm -1 .

[0012] Furthermore, the near-infrared discrimination model includes a total model, a primary sub-library, a secondary sub-library, and a tertiary sub-library;

[0013] The preprocessing method for NIRS spectral data in the overall model is second derivative, with 9 smoothing points; the spectral range is 10992-5316 cm⁻¹. -1 ;

[0014] The preprocessing method for the NIRS spectral data in the primary sub-library is second derivative, with 5 smoothing points, and a spectral range of 7000-5416 cm⁻¹. -1 ;

[0015] The preprocessing method for the NIRS spectral data in the secondary sub-library is second derivative, with 9 smoothing points, and a spectral range of 8020-5332 cm⁻¹. -1 ;

[0016] The preprocessing method for the NIRS spectral data in the third-level sub-library is second derivative, with 9 smoothing points, and a spectral range of 6848-5360 cm⁻¹. -1 .

[0017] Furthermore, the threshold X value of the near-infrared discrimination model is set to 0.75, with a confidence level of 99.99%.

[0018] Furthermore, the aforementioned 60 The Co-γ irradiation dose is 0–30 kGy.

[0019] Furthermore, the aforementioned Chinese medicinal materials 60 The Co-γ irradiation dose ranges are as follows: irradiation dose = 0, 0 < irradiation dose ≤ 5, 5 < irradiation dose ≤ 10, 10 < irradiation dose ≤ 20, 20 < irradiation dose ≤ 30.

[0020] Furthermore, the medicinal material includes peony bark, preferably peony bark powder that has passed through a No. 2 sieve.

[0021] The present invention also provides a method for constructing the aforementioned system, comprising the following steps:

[0022] (1) Construct a data acquisition module for inputting NIRS spectral data of Chinese medicinal materials;

[0023] (2) Collect different doses 60 NIRS spectral data of Chinese medicinal materials treated with Co-γ irradiation were used to construct a database module; the data in the database were randomly split into a reference spectrum set and a test spectrum set.

[0024] (3) The preprocessed reference spectrum set is combined with the factorization method. 60 Correlate Co-γ irradiation doses to construct a near-infrared discrimination model;

[0025] (5) Construct a verification module to validate the near-infrared discrimination model using a test spectrum set;

[0026] (6) Construct a validated near-infrared identification model to analyze the NIRS spectral data of the Chinese medicinal materials to be tested, and obtain the Chinese medicinal materials to be tested. 60 Data analysis module for Co-γ irradiation dose range;

[0027] (7) Construct an output module that outputs the calculation results of the data analysis module.

[0028] Furthermore, the resolution of the NIRS spectrum is 8 cm⁻¹. -1 Spectral range 12000~4000cm -1 ;

[0029] And / or, the near-infrared discrimination model includes a total model, a primary sub-library, a secondary sub-library, and a tertiary sub-library;

[0030] The preprocessing method for NIRS spectral data in the overall model is second derivative, with 9 smoothing points; the spectral range is 10992-5316 cm⁻¹. -1 ;

[0031] The preprocessing method for the NIRS spectral data in the primary sub-library is second derivative, with 5 smoothing points, and a spectral range of 7000-5416 cm⁻¹. -1 ;

[0032] The preprocessing method for the NIRS spectral data in the secondary sub-library is second derivative, with 9 smoothing points, and a spectral range of 8020-5332 cm⁻¹. -1 ;

[0033] The preprocessing method for the NIRS spectral data in the third-level sub-library is second derivative, with 9 smoothing points, and a spectral range of 6848-5360 cm⁻¹.-1 .

[0034] Furthermore, the aforementioned 60 Co-γ irradiation dose is 0–30 kGy;

[0035] And / or, the Chinese medicinal material includes peony bark, preferably peony bark powder that has passed through a No. 2 sieve.

[0036] This invention also provides a rapid identification method for Chinese medicinal materials based on NIRS spectroscopy. 60 The method for Co-γ irradiation dosage includes the following steps:

[0037] Take the Chinese medicinal material to be tested, measure its NIRS spectrum, and import the spectral data into the aforementioned system to obtain... 60 Range of Co-γ irradiation doses.

[0038] Furthermore, the medicinal material to be tested includes peony bark, preferably peony bark powder that has passed through a No. 2 sieve.

[0039] This invention provides a rapid identification method for peony bark based on near-infrared spectroscopy. 60 A systematic approach to Co-γ irradiation dosage was developed, involving preprocessing NIRS spectral data using second derivatives and then establishing a discrimination model using factorization. This approach enables rapid and accurate identification of traditional Chinese medicinal materials, particularly peony bark. 60 Co-γ irradiation dose range. Compared with the current traditional HPLC method, the sampling process is simple, does not damage the sample, has no chemical reagent pollution, and has high detection efficiency, making it valuable for practical application.

[0040] Obviously, based on the above description of the present invention, and according to common technical knowledge and conventional methods in the field, various other modifications, substitutions or alterations can be made without departing from the basic technical concept of the present invention.

[0041] The following detailed embodiments further illustrate the above-described content of the present invention. However, this should not be construed as limiting the scope of the present invention to the following examples. All technologies implemented based on the above-described content of the present invention fall within the scope of the present invention. Attached Figure Description

[0042] Figure 1 Original spectra of all peony bark samples

[0043] Figure 2 Reference Spectral Classification

[0044] Figure 3 Factor spectral calculation results (distinguishing the fuzhao0 group from the other 4 groups of samples)

[0045] Figure 4Verification results (distinguishing the fuzhao0 group from the other 4 groups of samples)

[0046] Figure 5 Factorial spectral calculation results (distinguishing between fuzhao3 and fuzhao1, fuzhao2, and fuzhao4 samples)

[0047] Figure 6 Verification results (distinguishing between fuzhao3 and fuzhao1, fuzhao2, and fuzhao4 samples)

[0048] Figure 7 Factor spectral calculation results (distinguishing between samples fuzhao1, fuzhao2, and fuzhao4)

[0049] Figure 8 Verification results (distinguishing between samples fuzhao1, fuzhao2, and fuzhao4)

[0050] Figure 9 Factorial spectral calculation results (distinguishing between samples fuzhao2 and fuzhao4)

[0051] Figure 10 Verification results (distinguishing between fuzhao2 and fuzhao4 samples)

[0052] Figure 11 Verification results (fuzhao0, fuzhao1, 2, 3, 4: all five types of samples were distinguished) Detailed Implementation

[0053] The raw materials and equipment used in this invention are all known products, obtained by purchasing commercially available products.

[0054] Example 1: Rapid Identification of Paeoniae Radix Alba by the Invention 60 Establishment of a systematic approach to Co-γ irradiation dose: 1. Collection 60 NIRS spectra of peony bark powder passing through a No. 2 sieve with Co-γ irradiation doses of 0–30 kGy at a resolution of 8 cm⁻¹ -1 Spectral range 12000~4000cm -1 The data is used to build a database (database module).

[0055] 2. Randomly split the data in the database into a reference spectrum set and a test spectrum set. For the NIRS spectral data in the reference spectrum set, first select the spectral range of 10992-5316 cm⁻¹. -1 After second derivative processing and smoothing with 9 points, the preprocessed spectral data was then compared with the data using factorization. 60 The Co-γ irradiation dose was correlated with the threshold X value of 0.75 and the confidence level of 99.99% to construct the overall model;

[0056] Then, the spectral range of 7000-5416cm was selected. -1 After second derivative processing and smoothing with 5 points, the preprocessed spectral data was then compared with the data using factorization. 60 Co-γ irradiation dose was correlated with a threshold value of X of 0.75 and a confidence level of 99.99% to construct a first-level sub-library.

[0057] Next, select the spectral range 8020-5332cm. -1 After second derivative processing and smoothing with 9 points, the preprocessed spectral data was then compared with the data using factorization. 60 Co-γ irradiation dose was correlated with a threshold value of X=0.75 and a confidence level of 99.99% to construct a secondary sub-library.

[0058] Finally, the spectral range of 6848-5360 cm⁻¹ was selected. -1 After second derivative processing and smoothing with 9 points, the preprocessed spectral data was then compared with the data using factorization. 60 Co-γ irradiation dose was correlated with a threshold value of 0.75 and a confidence level of 99.99% to construct a three-level sub-library.

[0059] The near-infrared discrimination model consists of a general model, a primary sub-library, a secondary sub-library, and a tertiary sub-library (data processing module). The near-infrared discrimination model is validated using a test spectrum set (validation module).

[0060] 3. Construct and analyze the NIRS spectrum of peony bark powder that has passed through a No. 2 sieve using a validated near-infrared identification model at a resolution of 8 cm⁻¹. -1 Spectral range 12000~4000cm -1 Data to obtain the peony bark to be tested 60 Data analysis module for Co-γ irradiation dose within the following range; and output data analysis module. 60 Output module for Co-γ irradiation dose range results;

[0061] 60 The Co-γ irradiation dose ranges are as follows: irradiation dose = 0, 0 < irradiation dose ≤ 5, 5 < irradiation dose ≤ 10, 10 < irradiation dose ≤ 20, 20 < irradiation dose ≤ 30.

[0062] The following experimental examples further illustrate the beneficial effects of the present invention.

[0063] Experimental Example 1: Study on a rapid method for identifying the 60Co-γ irradiation dose of peony bark based on near-infrared spectroscopy

[0064] 1. Method Establishment Process

[0065] 1.1 Sample

[0066] 122 batches of peony bark samples were sourced from the Chengdu Hehuachi Traditional Chinese Medicine Market and retail pharmacies. The origins were Dianjiang (42 batches), Guanxian (25 batches), and Luding (30 batches) in Sichuan Province, and Tongling (15 batches) and Nanling (10 batches) in Anhui Province. The samples were identified as peony bark by the Key Laboratory of Traditional Chinese Medicine Quality Monitoring of Chengdu Institute for Drug Control.

[0067] 1.2 Experimental Apparatus

[0068] Near-infrared spectrometer (Brimrose MATRIX-F, USA); high-speed Chinese medicine pulverizer; OPUS analysis software.

[0069] 2. Experimental methods and results

[0070] 2.1 Sample irradiation treatment

[0071] Samples of peony bark from different origins, approximately 100g per batch, were taken. Irradiation treatment was carried out according to Table 1 at the Sichuan Provincial Institute of Atomic Energy.

[0072] Table 1. Irradiation treatment of peony bark samples (unit: batch)

[0073]

[0074] Note: fuzhao0-fuzhao4 represent different groups of different irradiation doses during the model establishment process.

[0075] 2.2 Atlas Acquisition

[0076] The irradiated samples were pulverized using a high-speed traditional Chinese medicine pulverizer and passed through a No. 2 sieve. Spectral data were then acquired using a fiber optic diffuse reflection probe under the following conditions: resolution 8cm². -1 Spectral scanning range 12000~4000cm -1 The average spectrum was obtained using OPUS software. The overlay of the original NIRS spectra of 122 batches of samples is shown below. Figure 1 The figure shows different doses 60 The original NIRS spectra of peony bark irradiated with Co-γ show very little difference, making them difficult to distinguish.

[0077] 2.3 Qualitative Identification Model Establishment Process

[0078] 2.3.1 Differentiate between fuzhao0 and fuzhao1, 2, 3, and 4 samples

[0079] In OPUS software, select "Establish Qualitative Test Method". From the "Reference Spectrum" sub-window, select "Selected Spectra as New Group" from the drop-down menu, and click "Add Spectrum" to import it. 60Spectra of samples treated with Co-γ irradiation (spectral data of samples irradiated with different doses are categorized by folder: fuzhao0, fuzhao1, fuzhao2, fuzhao3, fuzhao4, see Table 1 for details), such as Figure 2 As shown.

[0080] 2.2.2 Parameter Settings

[0081] In the "Parameters" sub-window, click the preprocessing drop-down menu and select "Second Derivative". Set the smoothing points to 9, the method to "Factorization", and the interactive selection range to "10992-5316cm". -1 Click "Start Calculation" to obtain the factor spectrum. Figure 3 As can be seen, fuzhao0 can be distinguished from the other groups. In the threshold window, the X value is set to 0.75, with a confidence level of 99.99%.

[0082] 2.2.3 Model Validation

[0083] In the "Model" sub-window, click the "Validate" button, then click "Validate this library" to perform validation. The results will be displayed in the Validate sub-window. Figure 4 The results show that the model can distinguish between fuzhao0 and fuzhao1, fuzhao2, fuzhao3, and fuzhao4. However, samples of fuzhao1-fuzhao4 are confused with each other and cannot be uniquely identified. In other words, it can distinguish between irradiated and unirradiated samples, but it cannot differentiate between samples irradiated with different doses. The model requires further exploration.

[0084] 2.2.2 Differentiation between fuzhao3 and fuzhao1, 2, and 4 samples

[0085] Establish sub-library 1 (ziku1) to distinguish between fuzhao3 and fuzhao1, fuzhao2, and fuzhao4 samples.

[0086] In the "Reference Spectrum" sub-window, click the "Set Sublibrary" button. In the pop-up window, name the sublibrary "ziku1", hold down the Ctrl key to select fuzhao1, fuzhao2, fuzhao3, and fuzhao4, and click the "Define" button. In the "Import Method" sub-window, select "ziku1" on the right. In the "Parameters" window, set the parameters: preprocessing to "Second Derivative", method to "Factorization", and interactively select the range from 7000 to 5416 cm⁻¹. -1 With a smoothing point count of 5, click "Start Calculation" to obtain the factor spectrum. Figure 5In the threshold window, set the X value to 0.75 and the confidence level to 99.99%. In the "Model" sub-window, click the "Validate" button, then click "Validate this library" to perform validation. The model can distinguish between fuzhao3 and fuzhao1, fuzhao2, and fuzhao4. However, the three types of samples (fuzhao1, fuzhao2, and fuzhao4) are mutually confused and cannot be uniquely identified. Further exploration of the model is needed. Figure 6 ).

[0087] 2.2.3 Differentiation between fuzhao1 and fuzhao2, 4 samples

[0088] Establish sub-library 2 (ziku2) to distinguish between fuzhao1 and fuzhao2, fuzhao4 samples.

[0089] Continue in the "Reference Spectrum" sub-window and click the "Set Sublibrary" button. In the pop-up window, name the sublibrary "ziku2", hold down the Ctrl key to select fuzhao1, fuzhao2, and fuzhao4, and click the "Define" button. In the "Import Method" sub-window, select "ziku2" on the right. In the "Parameters" window, set the preprocessing to "Second Derivative", the smoothing points to 9, the method to "Factorization", and the interactive selection range to 8020-5332 cm⁻¹. -1 Click "Start Calculation" to obtain the factor spectrum. Figure 7 In the threshold window, set the X value to 0.75 and the confidence level to 99.99%. In the "Model" sub-window, click the "Validate" button, then click "Validate this library" to perform validation. The model can distinguish between fuzhao31 and fuzhao2 / fuzhao4. However, fuzhao2 and fuzhao4 samples are mutually confused and cannot be uniquely identified. Further exploration of the model is needed. Figure 8 ).

[0090] 2.2.3 Identification of samples fuzhao2 and fuzhao4

[0091] Sub-library 3 (ziku3) was established to distinguish between samples fuzhao2 and fuzhao4.

[0092] Continue in the "Reference Spectrum" sub-window and click the "Set Sublibrary" button. In the pop-up window, name the sublibrary "ziku3", hold down the Ctrl key to select fuzhao2 and fuzhao4, and click the "Define" button. In the "Import Method" sub-window, select "ziku3" on the right. In the "Parameters" window, set the preprocessing to "Second Derivative", the smoothing point count to 9, the method to "Factorization", and the interactive selection range to 6848-5360 cm⁻¹. -1Click "Start Calculation" to obtain the factor spectrum. Figure 9 In the threshold window, set the X value to 0.75 and the confidence level to 99.99%. In the "Model" sub-window, click the "Validate" button, then click "Validate this library" to validate the model. The model can distinguish between fuzhao2 and fuzhao4. Figure 10 Finally, the established qualitative identification method is saved as "Qualitative Method a".

[0093] 2.4 The model was validated using a test spectrum set.

[0094] Select "Establish Qualitative Test Method", and choose "Qualitative Method a" as the method name. Click "Validate Library" to validate the model. The established model can distinguish all five types of samples: fuzhao0, fuzhao1, 2, 3, and 4. Figure 11 ).

[0095] 3. Summary of Model Methods

[0096] The model uses a near-infrared spectrometer, with reference spectra at several different doses. 60 Near-infrared spectra of peony bark after Co-γ irradiation. The overall model parameters were: preprocessing method "second derivative", smoothing points of 9, method "factorization", and interactive selection range of "10992-5316 cm⁻¹". -1 In the threshold window, the X value is set to 0.75, and the confidence level is 99.99%. At this point, samples fuzhao0 and fuzhao1, 2, 3, and 4 can be distinguished.

[0097] To further differentiate samples fuzhao3 from fuzhao1, 2, and 4, a primary sub-library was established. The parameters were: preprocessing mode "second derivative", smoothing points of 5, method "factorization", and interactive selection range "7000-5416 cm⁻¹". -1 In the threshold window, the X value is set to 0.75, and the confidence level is 99.99%.

[0098] To further differentiate between samples fuzhao1 and fuzhao2 and 4, a secondary sub-library was established. The parameters were: preprocessing mode "second derivative", smoothing points of 9, method "factorization", and interactive selection range of 8020-5332 cm⁻¹. -1 Within the threshold window, the X value is set to 0.75, with a confidence level of 99.99%.

[0099] To further identify samples fuzhao2 and fuzhao4, a three-level sub-library was established. The parameters were: preprocessing mode "second derivative", smoothing points of 9, method "factorization", and interactive selection range of 6848-5360 cm⁻¹.-1 Within the threshold window, the X value is set to 0.75, with a confidence level of 99.99%.

[0100] 4. Instructions for Model Parameter Selection (Setting)

[0101] Regarding preprocessing methods: There are six preprocessing methods for the model: 1. No preprocessing; 2. Vector normalization; 3. First derivative; 4. First derivative + vector normalization; 5. Second derivative; 6. Second derivative + vector normalization. During the model building process, through repeated experiments, it was found that only by using the "second derivative" could the model accurately identify the target spectrum of different doses of irradiation. Therefore, the "second derivative" preprocessing method was chosen.

[0102] Regarding the methodology: There are six available methods for the model: 1. Standard method (Euclidean distance); 2. Factorization method; 3. Factorization (original spectrum); 4. Correlation factor; 5. First range calibration method; 6. Reproducibility level normalization method. During the model building process, repeated experiments revealed that only the "factorization method" could be successfully established; therefore, the "factorization method" was chosen.

[0103] Other parameters, such as the number of smoothing points, interactive selection range (spectral range), and threshold settings, were summarized through repeated experiments (verifications) and optimization during the model building process.

[0104] 5. Validate the model using medicinal material samples treated with different doses of 60Co-γ irradiation outside the modeling database.

[0105] In the OPUS software, select "Qualitative Testing" from the "Evaluation" drop-down menu. Verification was performed using sample spectra with different irradiation doses that were not in the modeling database; the accuracy rate was 85%.

[0106] Table 2 Model Validation Spectrum

[0107]

[0108]

[0109] Note: fuzhao0: Unirradiated sample;

[0110] fuzhao1:0 < Irradiation dose ≤ 5;

[0111] fuzhao2:5 < Irradiation dose ≤ 10;

[0112] fuzhao3:10 < Irradiation dose ≤ 20;

[0113] fuzhao4:20 < Irradiation dose ≤30

[0114] In summary, this invention preprocesses NIRS spectral data using the second derivative and then employs a factorization method to establish a discrimination model, which can quickly identify peony bark. 60 The Co-γ irradiation dose range has an accuracy of 85%, demonstrating high detection accuracy and efficiency, and possessing practical application value.

Claims

1. A rapid identification method for Chinese medicinal materials 60 A system for Co-γ irradiation dosage, characterized in that: Includes the following modules: Data acquisition module: acquires NIRS spectral data of Chinese medicinal materials; the resolution of the NIRS spectrum is 8 cm⁻¹. -1 Spectral range 12000~4000cm -1 ; Database module: for different dosages 60 The NIRS spectral data of Chinese medicinal materials treated with Co-γ irradiation were used to construct a database, which was randomly divided into a reference spectrum set and a test spectrum set. Data processing module: Uses factorization to combine the preprocessed reference spectrum set with... 60 A near-infrared discrimination model was constructed by correlating Co-γ irradiation dose; the near-infrared discrimination model includes a total model, a primary sub-library, a secondary sub-library, and a tertiary sub-library. The preprocessing method for NIRS spectral data in the overall model is second derivative with 9 smoothing points; the interactive selection range of the factorization method is 10992-5316 cm⁻¹. -1 The threshold χ² value was set to 0.75, with a confidence level of 99.99%. The preprocessing method for the NIRS spectral data in the primary sub-library is second derivative with a smoothing point count of 5; the interactive selection range for factorization is 7000-5416 cm⁻¹. -1 The threshold χ² value was set to 0.75, with a confidence level of 99.99%. The preprocessing method for the NIRS spectral data in the secondary sub-library is second derivative with a smoothing point count of 9; the interactive selection range for factorization is 8020-5332 cm⁻¹. -1 The threshold χ² value was set to 0.75, with a confidence level of 99.99%. The preprocessing method for the NIRS spectral data in the three-level sub-library is second derivative with a smoothing point count of 9; the interactive selection range for factorization is 6848-5360 cm⁻¹. -1 The threshold χ² value was set to 0.75, with a confidence level of 99.99%. The factorization method mentioned is the factorization method in OPUS software; Validation module: Validates the near-infrared discrimination model using a test spectrum set; Data Analysis Module: Utilizes a validated near-infrared identification model to analyze the NIRS spectral data of the tested Chinese medicinal materials, obtaining the... 60 Co-γ irradiation dose range; Result Output Module: Outputs Chinese medicinal materials 60 Results of Co-γ irradiation dose range; The Chinese medicinal materials 60 The Co-γ irradiation dose ranges are as follows: irradiation dose = 0, 0 < irradiation dose ≤ 5, 5 < irradiation dose ≤ 10, 10 < irradiation dose ≤ 20, 20 < irradiation dose ≤ 30; The medicinal material mentioned is peony bark.

2. The system as described in claim 1, characterized in that, The medicinal material mentioned is peony bark powder that has passed through a No. 2 sieve.

3. A method for constructing the system of claim 1 or 2, characterized in that: Includes the following steps: (1) Construct a data acquisition module for inputting NIRS spectral data of Chinese medicinal materials; the resolution of the NIRS spectrum is 8 cm⁻¹. -1 Spectral range 12000~4000cm -1 ; (2) Collect different doses 60 NIRS spectral data of Chinese medicinal materials treated with Co-γ irradiation were used to construct a database module; the data in the database were randomly split into a reference spectrum set and a test spectrum set; 60 The Co-γ irradiation dose is 0~30 kGy; (3) The preprocessed reference spectrum set is combined with the factorization method. 60 A near-infrared discrimination model was constructed by correlating Co-γ irradiation dose; the near-infrared discrimination model includes a total model, a primary sub-library, a secondary sub-library, and a tertiary sub-library. The preprocessing method for NIRS spectral data in the overall model is second derivative with 9 smoothing points; the interactive selection range of the factorization method is 10992-5316 cm⁻¹. -1 ; The preprocessing method for the NIRS spectral data in the primary sub-library is second derivative, with 5 smoothing points, and the interactive selection range of the factorization method is 7000-5416 cm⁻¹. -1 ; The preprocessing method for the NIRS spectral data in the secondary sub-library is second derivative, with 9 smoothing points, and the interactive selection range of the factorization method is 8020-5332 cm⁻¹. -1 ; The preprocessing method for the NIRS spectral data in the three-level sub-library is second derivative, with a smoothing point count of 9, and the interactive selection range of the factorization method is 6848-5360 cm⁻¹. -1 ; The factorization method mentioned is the factorization method in OPUS software; (4) Construct a verification module to validate the near-infrared discrimination model using a test spectrum set; (5) Construct and analyze the NIRS spectral data of the Chinese medicinal materials to be tested using a validated near-infrared identification model to obtain the Chinese medicinal materials to be tested. 60 Data analysis module for Co-γ irradiation dose range; (6) Construct an output module that outputs the calculation results from the data analysis module; The medicinal material mentioned is peony bark.

4. The method as described in claim 3, characterized in that: And / or, the Chinese medicinal material is peony bark powder that has passed through a No. 2 sieve.

5. A rapid identification method for traditional Chinese medicinal materials based on NIRS spectroscopy 60 The method for Co-γ irradiation dosage is characterized by... Includes the following steps: Take the Chinese medicinal material to be tested, measure its NIRS spectrum, and import the spectral data into the system described in claim 1 or 2 to obtain... 60 Range of Co-γ irradiation dose; The medicinal material to be tested was peony bark.

6. The method as described in claim 5, characterized in that, The medicinal material to be tested was peony bark powder that had passed through a No. 2 sieve.

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