Article adulteration detection method and system based on stable isotope and electronic equipment

Abstract

The invention provides an article adulteration detection method and system based on stable isotope and electronic equipment, and relates to the technical field of food analysis and detection.The method comprises the steps that a target sample and a control sample of an article to be detected are obtained, and article quality pretreatment is conducted on the target sample and the control sample; carrying out doped sample merging on the target sample and the contrast sample after article quality pretreatment to obtain a doped sample to be detected; wherein the doping sample combination type comprises combination of the same total amount and different proportions and combination of the same proportion and different total amount; performing identification pretreatment on the to-be-detected doped samples, and performing isotope determination on the to-be-detected doped samples subjected to identification pretreatment to obtain various isotope values of specified types corresponding to different to-be-detected doped samples; and performing principal component analysis and / or clustering analysis on the various isotope values of the specified type based on the doping sample combination type to obtain an article adulteration result. According to the invention, the accuracy of article adulteration detection is improved.

Description

Technical Field

[0001] The present application relates to the technical field of food analysis and detection, and in particular to a method, system and electronic equipment for detecting adulteration of articles based on stable isotopes. Background Art

[0002] Unsupervised pattern recognition is a method that automatically learns data structure through algorithms to obtain classification information in the absence of sample category information. Unsupervised learning includes principal component analysis (PCA) and cluster analysis. PCA extracts features through dimensionality reduction to help distinguish authentic from adulterated samples and provides visualization tools. However, PCA may not be applicable to complex adulteration patterns, and it is difficult to directly calculate the adulteration ratio; while cluster analysis distinguishes authentic from adulterated samples by dividing samples into different clusters, but there is limited research on quantitatively estimating the adulteration ratio directly based on clustering results. Summary of the invention

[0003] The purpose of this application is to provide a method, system and electronic equipment for detecting adulteration of articles based on stable isotopes, so as to alleviate the above-mentioned technical problems existing in the prior art.

[0004] In a first aspect, the present invention provides a method for detecting adulteration of articles based on stable isotopes, the method comprising: Obtaining target samples and control samples of the items to be tested, and performing item quality preprocessing on the target samples and the control samples; The target sample and the control sample after the quality pretreatment of the article are combined with adulterated samples to obtain adulterated samples to be detected; wherein the types of combined adulterated samples include combined with the same total amount but different proportions and combined with the same proportion but different total amounts; Performing pre-identification processing on the adulterated samples to be detected, and performing isotope determination on the adulterated samples to be detected after the pre-identification processing, to obtain multiple isotope values ​​of designated types corresponding to different adulterated samples to be detected; Based on the type of adulterated sample merging, principal component analysis and / or cluster analysis is performed on multiple isotope values ​​of a specified type to obtain the result of item adulteration.

[0005] In an optional embodiment, the object to be detected is rice; wherein the target sample of the object to be detected is a first variety of rice, and the control sample of the object to be detected is a second variety of rice.

[0006] In an optional embodiment, the target sample and the control sample are subjected to article quality preprocessing, including: The collected rice samples are processed independently according to their respective numbers; the processing includes drying, removing impurities, selecting, husking, milling, and keeping the moisture content of the samples within the preset content; The processed rice is screened for quality to obtain complete and full single-grain rice samples; Classify the screened single-grain rice samples and label them with corresponding rice sample labels; The sorted single-grain rice samples were vacuum-packed and sealed and stored in a cool and dry place.

[0007] In an optional embodiment, the target sample and the control sample after the article quality pretreatment are combined with the adulterated sample to obtain the adulterated sample to be detected, including: Adding a plurality of preset proportions of the second variety of rice to the first variety of rice to obtain a plurality of first adulterated samples to be detected corresponding to the plurality of preset proportions; wherein the total number of rice grains of the plurality of first adulterated samples to be detected determined by the plurality of preset proportions of the second variety of rice is the same as that of the first variety of rice; The second variety of rice is mixed into the first variety of rice in a fixed ratio to obtain a plurality of second adulterated samples to be detected corresponding to different total numbers of rice grains.

[0008] In an optional embodiment, the sample to be detected for adulteration is subjected to pre-identification processing, including: Randomly selecting a single-grain rice sample of the first variety and a single-grain rice sample of the second variety from the adulterated samples to be detected; Each single-grain rice sample is placed in a centrifuge tube of preset volume and placed in a constant temperature drying oven for drying until constant weight; After drying, the single-grain rice sample is ground using a grinder and sieved through a sieve plate with a preset aperture for later use.

[0009] In an optional embodiment, isotope determination is performed on the adulterated sample to be detected after the pre-identification treatment to obtain multiple isotope values ​​of specified types corresponding to different adulterated samples to be detected, including: The dried single-grain rice sample was weighed and wrapped in a tin cup, and then the single-grain rice sample was put into the elemental analysis and stable isotope ratio mass spectrometer through an automatic sampler for δ 13 C and δ 15 N isotope ratio analysis; wherein the pyrolysis tube temperature of the element analyzer of the element analysis and stable isotope ratio mass spectrometer is the first pyrolysis tube temperature, the chromatographic column temperature is the first chromatographic column temperature, and the flow rate of the carrier gas helium is the first flow rate; The dried single-grain rice sample was weighed, wrapped in a silver cup, and then placed into the elemental analysis and stable isotope ratio mass spectrometer through an automatic sampler for δ 2 H and δ 18O isotope ratio analysis; wherein, the pyrolysis tube temperature of the element analyzer of the element analysis and stable isotope ratio mass spectrometer is the second pyrolysis tube temperature, the chromatographic column temperature is the second chromatographic column temperature, and the flow rate of the carrier gas helium is the second flow rate.

[0010] In an optional embodiment, principal component analysis and / or cluster analysis is performed on multiple isotope values ​​of a specified type based on the type of adulterated sample merging to obtain the result of article adulteration, including: When the type of adulterated sample merging with the same total amount but different proportions is used: The distribution of the first principal component and the second principal component is determined for multiple isotope values ​​of the specified type by principal component analysis; Based on the distribution measurement results of the first principal component and the second principal component, cluster analysis is performed to extract the adulterated samples and obtain the results of article adulteration; When the type of adulterated sample merging is used, where the same proportions but different total amounts are merged: Through principal component analysis, the distribution of the first principal component of multiple isotope values ​​of a specified type is determined. Samples that are distributed in the positive direction of the first principal component, with a smaller and more dense distribution range, are determined as adulterated samples, and samples that are distributed in the negative direction of the first principal component, with a wider and more dispersed distribution range, are determined as authentic samples.

[0011] In a second aspect, the present invention provides an article adulteration detection system based on stable isotopes, the system comprising: The sample acquisition and preprocessing module is used to acquire the target sample and the control sample of the object to be tested, and perform object quality preprocessing on the target sample and the control sample; The sample doping module is used to perform doped sample merging on the target sample and the control sample after the quality preprocessing of the article to obtain the doped sample to be detected; wherein the types of doped sample merging include merging of the same total amount but different proportions and merging of the same proportion but different total amounts; An isotope determination module is used to perform pre-identification processing on the adulterated samples to be detected, and to perform isotope determination on the adulterated samples to be detected after the pre-identification processing, so as to obtain multiple isotope values ​​of specified types corresponding to different adulterated samples to be detected; The adulteration detection module is used to perform principal component analysis and / or cluster analysis on multiple isotope values ​​of a specified type based on the type of adulterated sample merging to obtain the result of article adulteration.

[0012] In a third aspect, the present invention provides an electronic device comprising a processor and a memory, wherein the memory stores computer executable instructions that can be executed by the processor, and the processor executes the computer executable instructions to implement the stable isotope-based method for detecting adulteration of an article according to any one of the aforementioned embodiments.

[0013] In a fourth aspect, the present invention provides a computer-readable storage medium storing computer-executable instructions. When the computer-executable instructions are called and executed by a processor, the computer-executable instructions prompt the processor to implement the method for detecting adulteration of an article based on stable isotopes according to any one of the aforementioned embodiments.

[0014] The beneficial effects of the stable isotope-based article adulteration detection method, system and electronic device provided in this application are as follows: The target samples and control samples corresponding to the items to be tested are pre-processed to ensure that the samples meet the requirements of subsequent testing, thereby improving the accuracy of adulteration detection; by merging the two types of adulterated samples of the target samples and control samples after the quality pre-processing, the subsequent adulteration detection can be covered for each different method of adulteration, further improving the coverage and accuracy of adulteration detection; the accuracy of item adulteration detection is further improved by combining isotope determination with corresponding analysis methods, among which principal component analysis is used for adulteration identification, and by extracting the main features in the data, it is observed whether the adulterated samples can be effectively distinguished from the genuine products, thereby helping to identify the adulteration; cluster analysis can be used to divide the samples into different clusters according to their characteristics, and by analyzing the clustering results, it is observed whether the adulterated samples can be divided into a cluster separately by the clustering algorithm, and the proportion of adulterated samples is calculated by the ratio of the number of samples in the cluster to the total number of samples. Through the combination of these two methods, the recognition effect of adulterated samples in the data and the estimation of their proportion can be evaluated, thereby greatly improving the accuracy of adulteration detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the specific implementation methods of the present application or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0016] Figure 1 A flowchart of a method for detecting adulteration of articles based on stable isotopes provided in an embodiment of the present application; Figure 2 A principal component analysis diagram of a rice sample with an adulteration ratio of 10% provided in an embodiment of the present application; Figure 3 A principal component analysis diagram of a rice sample with an adulteration ratio of 30% provided in an embodiment of the present application; Figure 4 A principal component analysis diagram of a rice sample with an adulteration ratio of 50% provided in an embodiment of the present application; Figure 5A principal component analysis diagram of a 140-grain rice sample provided in an embodiment of the present application; Figure 6 A principal component analysis diagram of a 100-grain rice sample provided in an embodiment of the present application; Figure 7 A principal component analysis diagram of a 70-grain rice sample provided in an embodiment of the present application; Figure 8 A principal component analysis diagram of a 40-grain rice sample provided in an embodiment of the present application; Fig. 9 A principal component analysis diagram of a rice sample of 20 single-grain rice provided in an embodiment of the present application; Fig.10 A principal component analysis diagram of a 10-grain rice sample provided in an embodiment of the present application; Fig.11 A structural diagram of an article adulteration detection system based on stable isotopes provided in an embodiment of the present application; Fig.12 A structural diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. The components of the embodiments of the present application described and shown in the drawings here can be arranged and designed in various different configurations.

[0018] Therefore, the following detailed description of the embodiments of the present application provided in the accompanying drawings is not intended to limit the scope of the present application for which protection is sought, but merely represents selected embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present application.

[0019] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, further definition and explanation thereof is not required in subsequent drawings.

[0020] The present application provides a method for detecting adulteration of articles based on stable isotopes, see Figure 1 As shown, the method mainly includes the following steps: Step S110, obtaining a target sample and a control sample of the object to be detected, and performing object quality preprocessing on the target sample and the control sample.

[0021] The target sample of the item to be detected is a normal item, and the control sample of the item to be detected is a counterfeit item. The embodiment of the present application mainly performs adulteration detection through adulterated items, so the target sample of normal items and the control sample of counterfeit items are obtained in advance, and then the two are mixed to obtain the adulterated sample, and then the adulteration detection is performed after a series of treatments.

[0022] The above-mentioned article quality pretreatment is used to select the quality of the target samples and control samples of the articles to be tested, and to eliminate the samples that do not meet the quality standards, so as to obtain high-quality samples that can be used for subsequent adulteration detection.

[0023] Step S120, merging the target sample and the control sample after the item quality preprocessing to obtain the adulterated sample to be detected; wherein the types of merging of adulterated samples include merging of the same total amount but different proportions and merging of the same proportion but different total amounts.

[0024] In one embodiment, two ways of doping the sample can be set: 1) Merge samples with the same total amount but different proportions: For example, the adulteration ratio is set to multiple gradients: 10, 30, 50% (this example uses 3 as an example). The total amount of samples for each adulteration ratio is the same, for example, 100 (units).

[0025] 2) Merge different total amounts with the same proportion: For example, set the adulteration proportion to 30%. Set multiple gradients for the total amount of the sample: 100, 50, 40, 20, 10 (units) (this example uses 5 gradients).

[0026] Step S130 , performing identification pre-processing on the adulterated samples to be detected, and performing isotope determination on the adulterated samples to be detected after the identification pre-processing, to obtain a plurality of isotope values ​​of designated types corresponding to different adulterated samples to be detected.

[0027] In one embodiment, the adulterated sample to be detected is subjected to identification pre-treatment, mainly to facilitate subsequent isotope determination. The identification pre-treatment makes the adulterated sample to be detected meet the standard of isotope determination, thereby improving the accuracy of isotope determination.

[0028] In practical applications, when performing isotope determination on the adulterated sample to be detected, the stable isotope corresponding to the item to be detected can be selected for determination.

[0029] Step S140, performing principal component analysis and / or cluster analysis on multiple isotope values ​​of a specified type based on the type of adulterated sample merging to obtain an adulteration result of the article.

[0030] In the specific implementation, it is verified through a large number of experimental results that different types of adulterated sample merging need to have relatively accurate adulteration detection results, and the corresponding analysis methods are quite different. Therefore, the corresponding analysis type is selected based on the type of adulterated sample merging, such as principal component analysis, cluster analysis, and principal component analysis combined with cluster analysis, so as to achieve relatively accurate article adulteration detection results under the corresponding type.

[0031] For ease of understanding, the article adulteration detection method based on stable isotopes provided in the embodiments of the present application is described in detail below.

[0032] In one embodiment of the present application, the above-mentioned object to be detected is rice; wherein, the target sample of the object to be detected is a first variety of rice, and the control sample of the object to be detected is a second variety of rice.

[0033] For the specific implementation method in which the object to be detected is rice, the object quality pretreatment of the target sample and the control sample may include the following steps 1-1 to 1-4: Step 1-1, the collected rice samples are processed independently according to their respective numbers; wherein the processing includes drying, removing impurities, selecting, husking, milling, and keeping the moisture content of the samples controlled at a preset content; Step 1-2, screening the quality of the processed rice to obtain complete and full single-grain rice samples; Step 1-3, classifying and processing the screened single-grain rice samples, and marking them with corresponding rice sample labels; Steps 1-4: vacuum and seal the classified single-grain rice samples and store them in a cool and dry place.

[0034] In a specific example, the rice samples used in the experiment were collected during the rice harvest period in 2024. First, the collected rice samples were processed independently according to their respective numbers. The processing steps include drying, removing impurities, selecting, husking, and milling to ensure that the moisture content is controlled between 14.0% and 15.5%. Subsequently, the rice is screened to retain only complete and plump rice grains (single-grain rice). The screened rice is placed in a food-grade vacuum packaging bag with the corresponding rice sample label, vacuumed and sealed, and finally stored in a cool and dry place for subsequent use.

[0035] Wuchang rice (variety: Wuyoudao No. 4) was collected in Wuchang City, Harbin, Heilongjiang Province, with a weight of 2 kg. Rice (variety: Zhongkefa No. 5) was collected in Tailai County, Qiqihar City, Heilongjiang Province, hereinafter referred to as Tailai rice, with a weight of 2 kg. The specific rice sample collection information is shown in Table 1.

[0036] Table 1 Rice sample collection information

[0037] Furthermore, the target sample and the control sample after the quality pretreatment of the article are combined with the adulterated sample to obtain the adulterated sample to be detected, including the following two cases: 1. Adding a plurality of preset proportions of the second variety of rice to the first variety of rice to obtain a plurality of first adulterated samples to be detected corresponding to the plurality of preset proportions; wherein the total number of rice grains of the plurality of first adulterated samples to be detected determined by the plurality of preset proportions of the second variety of rice is the same as that of the first variety of rice; In specific implementation, the embodiment of the present application provides a specific sample example, that is, the preparation of adulterated samples with the same total number of particles and different adulteration ratios: Tailai rice (adulterated sample) was added to Wuchang rice (authentic), and the adulteration ratio was set at three gradients: 10%, 30%, and 50%. The total number of rice grains at each adulteration ratio was 100. The number of Wuchang rice and Tailai rice grains corresponding to each adulteration ratio is shown in Table 2.

[0038] Table 2 Statistics of single rice grains with different adulteration ratios

[0039] 2. Add the second variety of rice to the first variety of rice at a fixed ratio to obtain a plurality of second adulterated samples to be detected corresponding to different total rice grain numbers. In specific implementation, the embodiment of the present application provides a specific sample example, that is, the preparation of adulterated samples with the same adulteration ratio and different total rice grain numbers: Tailai rice was added to Wuchang rice, and the adulteration ratio was set to 30%. The total number of grains was set to 6 levels: 140, 100, 70, 40, 20, and 10 grains. When the adulteration ratio was 30%, the number of Wuchang rice and Tailai rice corresponding to each total number of grains was shown in Table 3.

[0040] Table 3 Statistics of single rice grains with different total grain numbers

[0041] Further, after the aforementioned adulterated sample to be detected is determined, the adulterated sample to be detected may be subjected to pre-identification processing, which may include the following steps 2-1 to 2-3 during specific implementation: Step 2-1, randomly select a single grain rice sample of the first variety and a single grain rice sample of the second variety from the adulterated samples to be detected. That is, in actual application, randomly take out the required single grain rice from the Wuchang rice and Tailai rice of the adulterated samples to be detected.

[0042] Step 2-2, place each single-grain rice sample separately in a centrifuge tube of preset volume, and place it in a 60°C constant temperature drying oven for drying until constant weight. In practical applications, the preset volume can be a 2 ml centrifuge tube, or other volumes can be selected according to actual needs. This is only an example and is not specifically limited. When placed in a 60°C constant temperature drying oven for drying, it can last for 36 hours until constant weight, that is, the weight difference between the two weighings before and after does not exceed 2 mg.

[0043] Step 2-3, after drying, use a grinder to grind the single grain rice sample, and sieve it through a sieve plate with a preset aperture for later use. The preset aperture may be a 0.15 mm aperture, which is also used as an example and is not specifically limited. In practical applications, other volume selections may also be made according to actual needs.

[0044] Furthermore, isotope determination can be performed on the adulterated samples to be detected after the identification pre-treatment to obtain multiple isotope values ​​of specified types corresponding to different adulterated samples to be detected. In specific implementation, the following two determination methods can be included: Determination method 1: The dried single-grain rice sample was weighed and wrapped in a tin cup, and then the single-grain rice sample was put into the elemental analysis and stable isotope ratio mass spectrometer through an automatic sampler for δ 13 C and δ 15 N isotope ratio analysis; wherein the pyrolysis tube temperature of the element analyzer of the element analysis and stable isotope ratio mass spectrometer is the first pyrolysis tube temperature, the chromatographic column temperature is the first chromatographic column temperature, and the flow rate of the carrier gas helium is the first flow rate.

[0045] In practical applications, 200 μg of dried single-grain rice samples were weighed, wrapped in a tin cup, and then put into the elemental analysis and stable isotope ratio mass spectrometry (EA-IRMS) for C and N isotope ratio analysis. The sample entered the elemental analyzer through an automatic sampler. The cracking tube temperature of the elemental analyzer was 960°C. The C and N in the sample were reduced to CO2 and N2 by the glassy carbon in the cracking furnace. The whole process was carried out online automatically. CO2 and N2 were separated by gas phase, and the chromatographic column temperature was 50°C. CO2 and N2 entered the EA-IRMS through the ConFlo IV device respectively for δ 13 C and δ 15 The flow rate of carrier gas helium was 100 mL / min. USGS44 (δ 13 C=−42.21‰), USGS63 (δ 13 C = −1.17‰, δ 15 N=37.83‰), USGS88 (δ 13 C = −16.06‰, δ15 N = 14.96‰) and USGS91 (δ 13 C = −28.28‰, δ 15 N = 1.78‰) as the correction δ 13 C and δ 15 Standard sample of N.δ 13 C and δ 15 The analytical accuracy of N is 0.15‰.

[0046] Determination method 2: The dried single-grain rice sample was weighed, wrapped in a silver cup, and then placed into the elemental analysis and stable isotope ratio mass spectrometer through an automatic sampler for δ 2 H and δ 18 O isotope ratio analysis; wherein, the pyrolysis tube temperature of the element analyzer of the element analysis and stable isotope ratio mass spectrometer is the second pyrolysis tube temperature, the chromatographic column temperature is the second chromatographic column temperature, and the flow rate of the carrier gas helium is the second flow rate.

[0047] In practical applications, 200 µg of dried single-grain rice samples were weighed, wrapped in a silver cup, and put into EA-IRMS for H and O isotope ratio analysis. The sample entered the element analyzer through an automatic sampler. The pyrolysis tube temperature of the element analyzer was 1380°C. The H and O in the sample were reduced to H2 and CO by the glassy carbon in the pyrolysis furnace. The whole process was carried out online automatically. H2 and CO were separated by gas phase. The chromatographic column temperature was 60°C. H2 and CO entered IRMS through the ConFlo IV device respectively. δ 2 H and δ 18 O determination. The flow rate of carrier gas helium is 100mL / min. USGS90 (δ 2 H=-13.90‰, δ 18 O=35.90‰), USGS91 (δ 2 H=-45.70‰, δ 18 O = 21.13‰) and CBS (δ 2 H=-157‰, δ 18 O = 3.8‰) as the correction δ 2 H and δ 18 Standard sample of O.δ 2 The analytical accuracy of H is 3‰, δ 18 The analytical accuracy of O is 0.4‰.

[0048] After obtaining the isotope determination results, the inventors conducted a large number of experiments for comparative analysis in order to obtain the subsequent analysis results of this application, and thus obtained the results of article adulteration by performing principal component analysis and / or cluster analysis on multiple isotope values ​​of a specified type based on the type of adulterated sample merger. That is, corresponding to different types of adulterated sample mergers, using corresponding analysis methods can obtain more accurate adulteration detection results. The analysis process is described in detail below.

[0049] For the two types of combined doped samples provided in this application, the analysis process is described respectively: 1. Same total number of grains, different adulteration ratios 1-1) The total number of pills is 100 and the adulteration ratio is 10% The δ values ​​of 90 grains of Wuchang rice and 10 grains of Tailai rice were measured. 13 C.δ 15 N, δ 2 H, δ 18 O values ​​are shown in Table 4. Principal component analysis of the data was performed using Origin. Figure 2 As shown in the figure. The samples marked with serial numbers in the figure are all adulterated samples, while the samples without serial numbers are authentic. The adulterated samples are mainly distributed in the positive direction of PC1 and the positive direction of PC2, showing a certain deviation trend. However, the boundaries between adulterated samples and authentic samples on PC1 and PC2 are not clear enough, and no obvious classification is formed. It is impossible to effectively distinguish adulterated samples from authentic products only through the principal component analysis results.

[0050] Table 4 δ in single grain rice with 10% adulteration 13 C.δ 15 N, δ 2 H, δ 18 O value

[0051] Note: WC: Wuchang rice; TL: Tailai rice, the same below.

[0052] When the total number of grains is 100 and the adulteration ratio is 10%, the clustering results are shown in Table 5. Among them, 90 samples belong to category 1 and 10 samples belong to category 2, so the adulteration ratio is 10%, and the serial numbers 91 to 100 are accurately identified as adulterated samples.

[0053] Table 5 Cluster analysis results of rice samples with 10% adulteration ratio

[0054] Note: In the cluster analysis results, 1 and 2 represent two categories.

[0055] 1-2) The adulteration ratio is 30% The δ values ​​of 70 grains of Wuchang rice and 30 grains of Tailai rice were measured. 13 C.δ 15 N, δ 2 H, δ 18 The O values ​​are shown in Table 6. Principal component analysis of the data was performed using Origin, and the results are as follows Figure 3 As shown in the figure, samples with serial numbers are all adulterated samples, while samples without serial numbers are authentic. Adulterated samples are mainly concentrated in the positive direction of PC1, while authentic samples are more dispersed, mainly concentrated in the negative direction of PC1. The two types of samples show certain differences in distribution trends on PC1. Overall, adulterated samples and authentic products are effectively distinguished in the principal component space.

[0056] Table 6 δ in single grain rice with 30% adulteration 13 C.δ 15 N, δ 2 H, δ 18 O value

[0057] When the total number of grains is 100 and the adulteration ratio is 30%, the clustering results are shown in Table 7. Among the 100 samples, 70 samples belong to category 1 and 30 samples belong to category 2, so the adulteration ratio is 30%, and serial numbers 71 to 100 are identified as adulterated rice.

[0058] Table 7 Cluster analysis results of rice samples with 30% adulteration

[0059] 1-3) The adulteration ratio is 50% The δ of 50 grains of Wuchang rice and 50 grains of Tailai rice were measured. 13 C.δ 15 N, δ 2 H, δ 18 The O values ​​are shown in Table 8. Principal component analysis of the data was performed using Origin, and the results are as follows Figure 4As shown. In the figure, samples marked with serial numbers are all adulterated samples, while samples without serial numbers are authentic. Adulterated samples are concentrated in the positive direction of PC1, with a smaller distribution range and closer to the central area, while authentic products are mainly distributed in the negative direction of PC1, with a relatively wide distribution range and more dispersed. PC1 can effectively distinguish the two types of samples, forming a certain separation trend in the principal component space. Although there is still a certain degree of overlap in the distribution of samples on PC2, its impact on classification is small, and PC1 plays a leading role in sample differentiation. Therefore, it can be considered that adulterated samples and authentic products are effectively distinguished in the principal component space.

[0060] Table 8 δ in single grain rice with 50% adulteration 13 C.δ 15 N, δ 2 H, δ 18 O value

[0061] When the total number of grains is 100 and the adulteration ratio is 50%, the clustering results are shown in Table 9. Among the 100 samples, 50 samples belong to category 1 and 50 samples belong to category 2, so the adulteration ratio is 50%, and serial numbers 51 to 100 are identified as adulterated rice.

[0062] Table 9 Cluster analysis results of rice samples with 50% adulteration

[0063] 2. Same adulteration ratio, different total number of grains 2-1) The adulteration ratio is 30% and the total number of grains is 140 The δ values ​​of 98 grains of Wuchang rice and 42 grains of Tailai rice were measured. 13 C.δ 15 N, δ 2 H, δ 18 The O values ​​are shown in Table 10. Principal component analysis of the data was performed using Origin, and the results are as follows Figure 5As shown in the figure, samples marked with serial numbers are all adulterated samples, while samples without serial numbers are authentic. Adulterated samples are distributed in the positive direction of PC1, with a smaller and more compact distribution range, while authentic samples are mainly distributed in the negative direction of PC1, with a wider and more dispersed distribution range. This distribution difference in the PC1 direction indicates that adulterated samples and authentic products have good distinguishing ability in this principal component direction. Although there is a certain overlap in samples on PC2, the two types of samples can still be classified by principal component analysis.

[0064] Table 10 δ in 140 single grains of rice 13 C.δ 15 N, δ 2 H, δ 18 O value

[0065] When the adulteration ratio is 30% and the total number of grains is 140, the clustering results are shown in Table 11. Among them, 98 samples belong to category 1 and 42 samples belong to category 2, so the adulteration ratio is 30%, and serial numbers 99 to 140 are identified as adulterated rice.

[0066] Table 11 Cluster analysis results of 140 rice samples

[0067] 2-2) The adulteration ratio is 30% and the total number of pills is 100 The δ values ​​of 70 grains of Wuchang rice and 30 grains of Tailai rice were measured. 13 C.δ 15 N, δ 2 H, δ 18 The O values ​​are shown in Table 12. Principal component analysis of the data was performed using Origin, and the results are as follows Figure 6 As shown. In the figure, samples marked with serial numbers are all adulterated samples, while samples without serial numbers are authentic. Adulterated samples are mainly concentrated in the positive direction of PC1, with a narrower and more concentrated distribution range, while authentic samples are mainly distributed in the negative direction of PC1, with a wider range and more dispersed. On PC2, the distribution of adulterated samples is relatively close to the central area, while the distribution of authentic samples is more dispersed, showing a trend of expanding up and down. Overall, in the principal component space, adulterated samples and authentic products can be distinguished.

[0068] Table 12 δ in 100 single grains of rice 13 C.δ 15 N, δ 2 H, δ 18 O value

[0069] When the adulteration ratio is 30% and the total number of grains is 100, the clustering results are shown in Table 13. Among them, 70 samples belong to category 1 and 30 samples belong to category 2 among the 100 samples, so the adulteration ratio is 30%, and serial numbers 71 to 100 are identified as adulterated rice.

[0070] Table 13 Cluster analysis results of 100 rice grain samples

[0071] 2-3) The adulteration ratio is 30% and the total number of grains is 70 The δ values ​​of 49 grains of Wuchang rice and 21 grains of Tailai rice were measured. 13 C.δ 15 N, δ 2 H, δ 18 The O values ​​are shown in Table 14. Principal component analysis of the data was performed using Origin, and the results are as follows Figure 7 As shown. In the figure, samples marked with serial numbers are all adulterated samples, while samples without serial numbers are authentic. In the PC1 direction, adulterated samples and authentic products show an obvious separation trend, with adulterated samples concentrated in the positive direction and authentic samples concentrated in the negative direction. On PC2, adulterated samples are mainly concentrated in the area close to the center, while authentic products have a larger expansion in the up and down directions. Overall, in the principal component space, adulterated samples and authentic products can be distinguished.

[0072] Table 14 δ in 70 single grains of rice 13 C.δ 15 N, δ 2 H, δ 18 O value

[0073] When the adulteration ratio is 30% and the total number of grains is 70, the clustering results are shown in Table 15. Among them, 49 samples belong to category 1 and 21 samples belong to category 2 among the 70 samples, so the adulteration ratio is 30%, and serial numbers 50 to 70 are identified as adulterated rice.

[0074] Table 15 Cluster analysis results of 70 rice samples

[0075] 2-4) The adulteration ratio is 30% and the total number of grains is 40 The δ values ​​of 28 grains of Wuchang rice and 12 grains of Tailai rice were measured. 13 C.δ 15 N, δ 2 H, δ 18 The O values ​​are shown in Table 16. Principal component analysis of the data was performed using Origin, and the results are as follows Figure 8 As shown in the figure, samples marked with serial numbers are all adulterated samples, while samples without serial numbers are authentic. Adulterated samples are concentrated in the positive direction of PC1, with a tight distribution, showing strong aggregation. Authentic samples are concentrated in the negative direction of PC1, and the distribution range is more dispersed. Adulterated samples and authentic samples are completely separated on PC1, with no obvious overlap. Overall, principal component analysis can distinguish adulterated samples from authentic products.

[0076] Table 16 δ in 40 single grains of rice 13 C.δ 15 N, δ 2 H, δ 18 O value

[0077] When the adulteration ratio is 30% and the total number of grains is 40, the clustering results are shown in Table 17. Among them, 28 samples belong to category 1 and 12 samples belong to category 2 among the 40 samples, so the adulteration ratio is 30%, and serial numbers 29 to 40 are identified as adulterated rice.

[0078] Table 17 Cluster analysis results of 40 rice samples

[0079] 2-5) The adulteration ratio is 30% and the total number of grains is 20 The δ values ​​of 14 grains of Wuchang rice and 6 grains of Tailai rice were measured. 13 C.δ 15 N, δ 2H, δ 18 The O values ​​are shown in Table 18. Principal component analysis of the data was performed using Origin, and the results are as follows Fig. 9 As shown in the figure, samples with serial numbers are all adulterated samples, while samples without serial numbers are authentic. Adulterated samples are distributed in the positive direction of PC1, while authentic samples are located in the negative direction of PC1. However, due to the small number of samples, the distribution density of samples in space is insufficient, resulting in unclear classification boundaries. Therefore, it is impossible to distinguish adulterated samples from authentic products through principal component analysis.

[0080] Table 18 δ in 20 single grains of rice 13 C.δ 15 N, δ 2 H, δ 18 O value

[0081] When the adulteration ratio is 30% and the total number of grains is 20, the clustering results are shown in Table 19. Among them, 14 samples belong to category 1 and 6 samples belong to category 2 among the 20 samples, so the adulteration ratio is 30%, and serial numbers 15 to 20 are identified as adulterated rice.

[0082] Table 19 Cluster analysis results of 20 single-grain rice samples

[0083] 2-6) The adulteration ratio is 30%, and the total number of grains is 10 The δ values ​​of 7 grains of Wuchang rice and 3 grains of Tailai rice were measured. 13 C.δ 15 N, δ 2 H, δ 18 The O values ​​are shown in Table 20. Principal component analysis of the data was performed using Origin, and the results are as follows Fig.10 As shown. In the figure, samples marked with serial numbers are all adulterated samples, while samples without serial numbers are authentic. The adulterated samples are all located in the positive direction of PC1, but they are relatively scattered with each other and the distribution is not concentrated. The authentic samples are distributed in the negative direction of PC1 and also show a certain degree of dispersion. Due to the small number of samples and their scattered distribution, the classification boundaries are fuzzy. Therefore, it is impossible to distinguish adulterated samples from authentic products through principal component analysis.

[0084] Table 20 δ in 10 single grains of rice 13 C.δ 15 N, δ 2 H, δ 18 O value

[0085] When the adulteration ratio is 30% and the total number of grains is 10, the clustering results are shown in Table 21. Among them, 7 samples belong to category 1 and 3 samples belong to category 2 among the 10 samples, so the adulteration ratio is 30%, and serial numbers 8 to 10 are identified as adulterated rice.

[0086] Table 21 Cluster analysis results of 10 rice samples

[0087] The above-mentioned method uses stable isotope technology, in an unsupervised mode, combined with principal component analysis and cluster analysis to conduct adulteration identification and quantitative detection of rice samples with different adulteration ratios (10, 30, 50%) and different total grain numbers (140, 100, 70, 40, 20, 10 grains).

[0088] From the above analysis results, it can be concluded that in principal component analysis, there are certain distribution differences between adulterated samples and authentic products in the principal component space. However, when the adulteration ratio is low (such as 10%) and the total number of particles is small (such as 10, 20 particles), this difference is not enough to form a clear classification boundary, and the principal component analysis results alone cannot effectively distinguish adulterated samples from authentic products. With the increase of adulteration ratio and total number of particles, the distribution of adulterated samples in the principal component space gradually shows a clustering trend, and the distribution difference between adulterated samples and authentic products in the principal component space is more obvious, which can reveal the characteristic differences between samples to a certain extent. This difference can reveal the characteristic changes between samples to a certain extent, thereby helping to identify adulterated samples, but the adulteration ratio cannot be accurately calculated through principal component analysis.

[0089] In contrast, cluster analysis showed better results in adulteration identification. In experiments with different adulteration ratios and different total grain numbers, cluster analysis was able to accurately classify adulterated samples and authentic products into different categories. The adulteration ratio was calculated by calculating the ratio of the number of samples in each category to the total number of samples. In each group of experiments, the adulteration ratio calculated by cluster analysis was completely consistent with the adulteration ratio set in the experiment, proving the effectiveness of cluster analysis in quantitative detection of rice adulteration and its ability to accurately calculate the adulteration ratio.

[0090] Therefore, in a specific embodiment, principal component analysis and / or cluster analysis is performed on multiple isotope values ​​of a specified type based on the type of adulterated sample merging to obtain the result of article adulteration, which may include the following two situations: 1. When the type of merging of adulterated samples with the same total amount but different proportions is adopted: The distribution of the first principal component and the second principal component is determined for multiple isotope values ​​of the specified type by principal component analysis; Based on the distribution measurement results of the first principal component and the second principal component, cluster analysis is performed to extract the adulterated samples and obtain the results of article adulteration; 2. When the type of adulterated sample merging with the same proportion but different total amount is adopted: Through principal component analysis, the distribution of the first principal component of multiple isotope values ​​of a specified type is determined. Samples that are distributed in the positive direction of the first principal component, with a smaller and more dense distribution range, are determined as adulterated samples, and samples that are distributed in the negative direction of the first principal component, with a wider and more dispersed distribution range, are determined as authentic samples.

[0091] In summary, the accuracy of rice adulteration detection was improved by combining stable isotope technology with principal component analysis and cluster analysis to monitor rice adulteration.

[0092] Based on the above method embodiment, the present application embodiment also provides an article adulteration detection system based on stable isotopes, see Fig.11 As shown, the system includes the following parts: The sample acquisition and preprocessing module 210 is used to acquire the target sample and the control sample of the object to be detected, and perform object quality preprocessing on the target sample and the control sample; The sample doping module 220 is used to perform doping sample merging on the target sample and the control sample after the article quality preprocessing to obtain the doped sample to be detected; wherein the types of doped sample merging include merging of the same total amount but different proportions and merging of the same proportion but different total amounts; The isotope determination module 230 is used to perform pre-identification processing on the adulterated samples to be detected, and perform isotope determination on the adulterated samples to be detected after the pre-identification processing, so as to obtain multiple isotope values ​​of designated types corresponding to different adulterated samples to be detected; The adulteration detection module 240 is used to perform principal component analysis and / or cluster analysis on multiple isotope values ​​of a specified type based on the type of adulterated sample merging to obtain the result of article adulteration.

[0093] In a feasible implementation manner, the object to be detected is rice; wherein the target sample of the object to be detected is a first variety of rice, and the control sample of the object to be detected is a second variety of rice.

[0094] In a feasible implementation manner, the sample acquisition and preprocessing module 210 is further used for: The collected rice samples are processed independently according to their respective numbers; the processing includes drying, removing impurities, selecting, husking, milling, and keeping the moisture content of the samples within the preset content; The processed rice is screened for quality to obtain complete and full single-grain rice samples; Classify the screened single-grain rice samples and label them with corresponding rice sample labels; The sorted single-grain rice samples were vacuum-packed and sealed and stored in a cool and dry place.

[0095] In a feasible implementation manner, the sample doping module 220 is further used for: Adding a plurality of preset proportions of the second variety of rice to the first variety of rice to obtain a plurality of first adulterated samples to be detected corresponding to the plurality of preset proportions; wherein the total number of rice grains of the plurality of first adulterated samples to be detected determined by the plurality of preset proportions of the second variety of rice is the same as that of the first variety of rice; The second variety of rice is mixed into the first variety of rice in a fixed ratio to obtain a plurality of second adulterated samples to be detected corresponding to different total numbers of rice grains.

[0096] In a feasible implementation manner, the isotope determination module 230 is further used for: Randomly selecting a single-grain rice sample of the first variety and a single-grain rice sample of the second variety from the adulterated samples to be detected; Each single-grain rice sample is placed in a centrifuge tube of preset volume and placed in a constant temperature drying oven for drying until constant weight; After drying, the single-grain rice sample is ground using a grinder and sieved through a sieve plate with a preset aperture for later use.

[0097] In a feasible implementation manner, the isotope determination module 230 is further used for: The dried single-grain rice sample is weighed, wrapped with a tin cup, and then put into an elemental analysis and stable isotope ratio mass spectrometer through an automatic sample injector to perform isotope ratio analysis of δ13C and δ15N; wherein the pyrolysis tube temperature of the element analyzer of the elemental analysis and stable isotope ratio mass spectrometer is a first pyrolysis tube temperature, the chromatographic column temperature is a first chromatographic column temperature, and the flow rate of the carrier gas helium is a first flow rate; The dried single-grain rice sample is weighed, wrapped in a silver cup, and then introduced into an elemental analysis and stable isotope ratio mass spectrometer through an automatic sample injector to perform isotope ratio analysis of δ2H and δ18O; wherein the pyrolysis tube temperature of the element analyzer of the elemental analysis and stable isotope ratio mass spectrometer is the second pyrolysis tube temperature, the chromatographic column temperature is the second chromatographic column temperature, and the flow rate of the carrier gas helium is the second flow rate.

[0098] In a feasible implementation manner, the adulteration detection module 240 is further used to: When the type of adulterated sample merging with the same total amount but different proportions is used: The distribution of the first principal component and the second principal component is determined for multiple isotope values ​​of the specified type by principal component analysis; Based on the distribution measurement results of the first principal component and the second principal component, cluster analysis is performed to extract the adulterated samples and obtain the results of article adulteration; When the type of adulterated sample merging is used, where the same proportions but different total amounts are merged: Through principal component analysis, the distribution of the first principal component of multiple isotope values ​​of a specified type is determined. Samples that are distributed in the positive direction of the first principal component, with a smaller and more dense distribution range, are determined as adulterated samples, and samples that are distributed in the negative direction of the first principal component, with a wider and more dispersed distribution range, are determined as authentic samples.

[0099] The stable isotope-based article adulteration detection system provided in the embodiment of the present application has the same implementation principle and technical effects as those of the aforementioned method embodiment. For the sake of brief description, for matters not mentioned in the embodiment of the stable isotope-based article adulteration detection system, reference may be made to the corresponding contents in the aforementioned stable isotope-based article adulteration detection method embodiment.

[0100] The present application also provides an electronic device, such as Fig.12 As shown, it is a schematic diagram of the structure of the electronic device, wherein the electronic device 100 includes a processor 11 and a memory 10, the memory 10 stores computer executable instructions that can be executed by the processor 11, and the processor 11 executes the computer executable instructions to implement any of the above-mentioned stable isotope-based article adulteration detection methods.

[0101] exist Fig.12 In the illustrated embodiment, the electronic device further includes a bus 12 and a communication interface 13 , wherein the processor 11 , the communication interface 13 and the memory 10 are connected via the bus 12 .

[0102] Among them, the memory 10 may include a high-speed random access memory (RAM), and may also include a non-volatile memory (non-volatile memory), such as at least one disk storage. The communication connection between the system network element and at least one other network element is realized through at least one communication interface 13 (which may be wired or wireless), and the Internet, wide area network, local area network, metropolitan area network, etc. can be used. The bus 12 can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. The bus 12 can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 1 Only one bidirectional arrow is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0103] The processor 11 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the hardware integrated logic circuit or software instructions in the processor 11. The above processor 11 can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor. The steps of the method disclosed in the embodiment of the present application can be directly embodied as a hardware decoding processor to be executed, or the hardware and software modules in the decoding processor are combined and executed. The software module can be located in a mature storage medium in the field such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory, and the processor 11 reads the information in the memory and completes the steps of the article adulteration detection method based on stable isotopes in the aforementioned embodiment in combination with its hardware.

[0104] An embodiment of the present application also provides a computer-readable storage medium, which stores computer-executable instructions. When the computer-executable instructions are called and executed by a processor, the computer-executable instructions prompt the processor to implement the above-mentioned stable isotope-based article adulteration detection method. The specific implementation can be found in the aforementioned method embodiment, which will not be repeated here.

[0105] The computer program product of the stable isotope-based article adulteration detection method, system and electronic device provided in the embodiments of the present application includes a computer-readable storage medium storing program code. The instructions included in the program code can be used to execute the methods in the previous method embodiments. The specific implementation can be found in the method embodiments, which will not be repeated here.

[0106] Unless otherwise specifically stated, the relative steps, numerical expressions and values ​​of the components and steps set forth in these embodiments do not limit the scope of the present application.

[0107] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a non-volatile computer-readable storage medium that is executable by a processor. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, and other media that can store program codes.

[0108] In the description of the present application, it should be noted that the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0109] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for detecting adulteration of articles based on stable isotopes, characterized in that: The method comprises: Obtaining a target sample and a control sample of an object to be tested, and performing object quality preprocessing on the target sample and the control sample; The target sample and the control sample after the quality pretreatment of the article are subjected to adulterated sample merging to obtain an adulterated sample to be detected; wherein the types of adulterated sample merging include merging of the same total amount but different proportions and merging of the same proportion but different total amounts; The adulterated samples to be detected are subjected to identification pre-treatment, and isotope determination is performed on the adulterated samples to be detected after the identification pre-treatment to obtain multiple isotope values ​​of designated types corresponding to different adulterated samples to be detected; Based on the type of the adulterated sample combination, principal component analysis and / or cluster analysis is performed on the multiple isotope values ​​of the specified type to obtain the result of article adulteration.

2. The method for detecting adulteration of articles based on stable isotopes according to claim 1, characterized in that: The object to be detected is rice; wherein the target sample of the object to be detected is a first variety of rice, and the control sample of the object to be detected is a second variety of rice.

3. The method for detecting adulteration of articles based on stable isotopes according to claim 2, characterized in that: The target sample and the control sample are subjected to article quality preprocessing, including: The collected rice samples are processed independently according to their respective numbers; the processing includes drying, removing impurities, selecting, husking, milling, and keeping the moisture content of the samples within the preset content; The processed rice is screened for quality to obtain complete and full single-grain rice samples; Classify the screened single-grain rice samples and label them with corresponding rice sample labels; The sorted single-grain rice samples were vacuum-packed and sealed and stored in a cool and dry place.

4. The method for detecting adulteration of articles based on stable isotopes according to claim 2, characterized in that: The target sample and the control sample after the quality pretreatment of the article are combined with the adulterated sample to obtain the adulterated sample to be detected, including: Adding a plurality of preset proportions of the second variety of rice to the first variety of rice to obtain a plurality of first adulterated samples to be detected corresponding to the plurality of preset proportions; wherein the total number of rice grains of the plurality of first adulterated samples to be detected determined by the plurality of preset proportions of the second variety of rice and the first variety of rice is the same; The second variety of rice is mixed into the first variety of rice in a fixed ratio to obtain a plurality of second adulterated samples to be detected corresponding to different total numbers of rice grains.

5. The method for detecting adulteration of articles based on stable isotopes according to claim 2, characterized in that: The adulterated sample to be detected is subjected to pre-identification processing, including: Randomly selecting a single-grain rice sample of a first variety and a single-grain rice sample of a second variety from the adulterated samples to be detected; Each single-grain rice sample is placed in a centrifuge tube of preset volume and placed in a constant temperature drying oven for drying until constant weight; After drying, the single-grain rice sample is ground using a grinder and sieved through a sieve plate with a preset aperture for later use.

6. The method for detecting adulteration of articles based on stable isotopes according to claim 2, characterized in that: The isotope determination is performed on the adulterated samples to be detected after pre-identification treatment to obtain multiple isotope values ​​of specified types corresponding to different adulterated samples to be detected, including: The dried single-grain rice sample was weighed and wrapped in a tin cup, and then the single-grain rice sample was put into an elemental analysis and stable isotope ratio mass spectrometer through an automatic sampler for δ 13 C and δ 15 N isotope ratio analysis; wherein the pyrolysis tube temperature of the element analyzer of the element analysis and stable isotope ratio mass spectrometer is the first pyrolysis tube temperature, the chromatographic column temperature is the first chromatographic column temperature, and the flow rate of the carrier gas helium is the first flow rate; The dried single-grain rice sample was weighed, wrapped in a silver cup, and then placed into an elemental analysis and stable isotope ratio mass spectrometer through an automatic sampler for δ 2 H and δ 18 O isotope ratio analysis; wherein, the pyrolysis tube temperature of the element analyzer of the element analysis and stable isotope ratio mass spectrometer is the second pyrolysis tube temperature, the chromatographic column temperature is the second chromatographic column temperature, and the flow rate of the carrier gas helium is the second flow rate.

7. The method for detecting adulteration of articles based on stable isotopes according to claim 2, characterized in that: Based on the type of the adulterated sample combination, principal component analysis and / or cluster analysis is performed on the multiple isotope values ​​of the specified type to obtain the result of article adulteration, including: When the type of adulterated sample merging with the same total amount but different proportions is used: Determine the distribution of the first principal component and the second principal component of the plurality of isotope values ​​of the specified type by principal component analysis; Based on the distribution measurement results of the first principal component and the second principal component, cluster analysis is performed to extract the adulterated samples and obtain the results of article adulteration; When the type of adulterated sample merging is used, where the same proportions but different total amounts are merged: The distribution of the first principal component of the multiple isotope values ​​of the specified type is determined through principal component analysis, and the samples that are distributed in the positive direction of the first principal component, with a smaller and more dense distribution range, are determined as adulterated samples, and the samples that are distributed in the negative direction of the first principal component, with a wider and more dispersed distribution range, are determined as authentic samples.

8. A system for detecting adulteration of articles based on stable isotopes, characterized in that: The system comprises: The sample acquisition and preprocessing module is used to acquire the target sample and the control sample of the object to be detected, and perform object quality preprocessing on the target sample and the control sample; The sample doping module is used to perform doped sample merging on the target sample and the control sample after the quality preprocessing of the article to obtain the doped sample to be detected; wherein the types of doped sample merging include merging of the same total amount but different proportions and merging of the same proportion but different total amounts; An isotope determination module is used to perform pre-identification processing on the adulterated sample to be detected, and to perform isotope determination on the adulterated sample to be detected after the pre-identification processing, so as to obtain multiple isotope values ​​of specified types corresponding to different adulterated samples to be detected; The adulteration detection module is used to perform principal component analysis and / or cluster analysis on the multiple isotope values ​​of the specified type based on the type of the adulterated sample combination to obtain the result of article adulteration.

9. An electronic device, characterized in that: It comprises a processor and a memory, wherein the memory stores computer executable instructions that can be executed by the processor, and the processor executes the computer executable instructions to implement the method for detecting adulteration of articles based on stable isotopes as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions. When the computer-executable instructions are called and executed by the processor, the computer-executable instructions prompt the processor to implement the method for detecting adulteration of articles based on stable isotopes as described in any one of claims 1 to 7.

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