Article adulteration detection method, system and electronic equipment based on stable isotopes

Abstract

The present application provides a method, system and electronic device for detecting adulteration of articles based on stable isotopes, which relates to the technical field of food analysis and detection, including obtaining a target sample and a control sample of an article to be detected, performing article quality pretreatment on the target sample and the control sample; merging the target sample and the control sample after the article quality pretreatment to obtain an adulterated sample to be detected; wherein the types of merging of adulterated samples include merging of the same total amount with different proportions and merging of the same proportion with different total amounts; performing identification pretreatment on the adulterated sample to be detected, and performing isotope determination on the adulterated sample to be detected after the identification pretreatment to obtain multiple isotope values ​​of a specified type corresponding to different adulterated samples to be detected; performing principal component analysis and / or cluster analysis on the multiple isotope values ​​of a specified type based on the type of merging of the adulterated samples to obtain the article adulteration result. The present application improves the accuracy of article adulteration detection.

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 uses algorithms to automatically learn data structures and extract 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, helps distinguish authentic from adulterated samples, and provides visualization tools. However, PCA may not be applicable to complex adulteration patterns, making it difficult to directly calculate the adulteration rate. Cluster analysis, on the other hand, distinguishes authentic from adulterated samples by dividing samples into different clusters, but research directly estimating the adulteration rate based on clustering results is limited. 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 article adulteration based on stable isotopes, the method comprising:

[0005] Obtain target samples and control samples of the items to be tested, and perform item quality preprocessing on the target samples and the control samples;

[0006] 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;

[0007] Performing pre-identification treatment on the adulterated sample to be detected, and performing isotope determination 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;

[0008] Based on the type of adulterated sample merging, principal component analysis and / or cluster analysis are performed on multiple isotope values ​​of a specified type to obtain the result of article adulteration.

[0009] In an optional embodiment, the item to be detected is rice; wherein the target sample of the item to be detected is a first variety of rice, and the control sample of the item to be detected is a second variety of rice.

[0010] In an optional embodiment, the target sample and the control sample are subjected to article quality preprocessing, including:

[0011] The collected rice samples are processed independently according to their respective numbers; the processing includes drying, removing impurities, sorting, husking, milling, and keeping the moisture content of the samples within the preset content;

[0012] The processed rice is screened for quality to obtain complete and plump single-grain rice samples;

[0013] The screened single-grain rice samples are classified and labeled with corresponding rice sample labels;

[0014] The sorted single-grain rice samples were vacuum-packed, sealed, and stored in a cool, dry place.

[0015] In an optional embodiment, the target sample and the control sample after the article quality pretreatment are combined to obtain the adulterated sample to be detected, including:

[0016] Adding a second variety of rice to a first variety of rice at a plurality of preset proportions 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 in the plurality of first adulterated samples to be detected determined for the second variety of rice at the plurality of preset proportions is the same as the total number of rice grains in the plurality of first adulterated samples to be detected determined for the first variety of rice;

[0017] 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.

[0018] In an optional embodiment, the sample to be detected for adulteration is subjected to pre-identification processing, including:

[0019] 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;

[0020] Each single-grain rice sample was placed in a centrifuge tube of preset volume and placed in a constant temperature drying oven for drying until constant weight was achieved;

[0021] 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.

[0022] In an optional embodiment, isotope determination is performed on the adulterated sample to be detected after pre-identification treatment to obtain multiple isotope values ​​of specified types corresponding to different adulterated samples to be detected, including:

[0023] The dried single-grain rice sample was weighed and wrapped in a tin cup. The single-grain rice sample was then placed into the elemental analysis and stable isotope ratio mass spectrometry through an automatic sampler for δ 13 C and δ 15N isotope ratio analysis; wherein the pyrolysis tube temperature of the elemental analyzer of the elemental analysis and stable isotope ratio mass spectrometry 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;

[0024] 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 spectrometry 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 elemental analysis and stable isotope ratio mass spectrometry 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.

[0025] 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 an adulteration result of the article, including:

[0026] When the type of merging of adulterated samples with the same total amount but different proportions is used:

[0027] The distribution of the first principal component and the second principal component of multiple isotope values ​​of a specified type is determined by principal component analysis;

[0028] 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;

[0029] When the type of adulterated sample merging is used, where the sample is combined in the same proportion but different amounts:

[0030] The distribution of the first principal component of multiple isotope values ​​of a specified type is determined through principal component analysis. Samples that are distributed in the positive direction of the first principal component, with a smaller and more compact distribution range, are identified 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 identified as authentic samples.

[0031] In a second aspect, the present invention provides a system for detecting adulteration of articles based on stable isotopes, the system comprising:

[0032] The sample acquisition and preprocessing module is used to obtain the target sample and the control sample of the object to be tested, and perform item quality preprocessing on the target sample and the control sample;

[0033] The sample doping module is used to perform doped sample merging on the target sample and the control sample after the article quality pretreatment 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;

[0034] 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 pre-identification processing, to obtain multiple isotope values ​​of specified types corresponding to different adulterated samples to be detected;

[0035] 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.

[0036] 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.

[0037] 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.

[0038] The stable isotope-based article adulteration detection method, system, and electronic device provided in this application have the following beneficial effects:

[0039] The target and control samples corresponding to the items to be tested are pre-processed to ensure that they meet the requirements of subsequent testing, thereby improving the accuracy of adulteration detection. By merging the two types of adulterated samples from the pre-processed target and control samples, subsequent adulteration detection coverage can be carried out for each different adulteration method, further improving the coverage and accuracy of adulteration detection. The accuracy of item adulteration detection is further improved by combining isotope determination with corresponding analytical methods. Among them, principal component analysis is used for adulteration identification. By extracting the main features in the data, it is observed whether adulterated samples can be effectively distinguished from authentic products, thereby helping to identify adulteration. Cluster analysis is used to divide samples into different clusters based on their characteristics. By analyzing the clustering results, it is observed whether the adulterated samples can be individually classified into a cluster by the clustering algorithm. The proportion of adulterated samples is calculated by the ratio of the number of samples in the cluster to the total number of samples. By combining these two methods, the identification effect of adulterated samples in the data and the estimation of their proportion can be evaluated, greatly improving the accuracy of adulteration detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the specific implementation methods of the present application or the technical solutions in the prior art, the following is a brief introduction to the drawings required for use in the specific implementation methods or the description of the prior art. 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 any creative work.

[0041] Figure 1 A flowchart of a method for detecting article adulteration based on stable isotopes provided in an embodiment of the present application;

[0042] 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;

[0043] 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;

[0044] 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;

[0045] Figure 5 A principal component analysis diagram of a 140-grain rice sample provided in an embodiment of the present application;

[0046] Figure 6 A principal component analysis diagram of a 100-grain rice sample provided in an embodiment of the present application;

[0047] Figure 7 A principal component analysis diagram of a 70-grain rice sample provided in an embodiment of the present application;

[0048] Figure 8 A principal component analysis diagram of a 40-grain rice sample provided in an embodiment of the present application;

[0049] Figure 9 A principal component analysis diagram of a rice sample of 20 single grains of rice provided in an embodiment of the present application;

[0050] Figure 10 A principal component analysis diagram of a 10-grain rice sample provided in an embodiment of the present application;

[0051] Figure 11 A structural diagram of a stable isotope-based article adulteration detection system provided in an embodiment of the present application;

[0052] Figure 12 A structural diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0053] To make the objectives, technical solutions, and advantages of the embodiments of the present application more clear, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Generally, the components of the embodiments of the present application described and shown in the drawings herein can be arranged and designed in various different configurations.

[0054] 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 protection, but merely represents selected embodiments of the present application. All other embodiments obtained by persons of ordinary skill in the art based on the embodiments in the present application without creative work are within the scope of protection of the present application.

[0055] 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, it does not need to be further defined or explained in subsequent drawings.

[0056] The present invention provides a method for detecting adulteration of articles based on stable isotopes. Figure 1 As shown, the method mainly includes the following steps:

[0057] Step S110 , obtaining a target sample and a control sample of the item to be tested, and performing item quality preprocessing on the target sample and the control sample.

[0058] The target sample of the item to be tested is a normal item, and the control sample of the item to be tested is a counterfeit item. The present embodiment primarily uses adulterated items for adulteration detection. Therefore, a target sample of a normal item and a control sample of a counterfeit item are pre-obtained. The two are then adulterated to obtain an adulterated sample, which is then subjected to a series of treatments for adulteration detection.

[0059] 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 samples that do not meet the quality standards, thereby obtaining high-quality samples that can be used for subsequent adulteration detection.

[0060] Step S120 , merging the target sample and the control sample after the 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.

[0061] In one embodiment, two ways of doping the sample can be set:

[0062] 1) Merging samples with the same total amount but different proportions: For example, you can set multiple adulteration ratios: 10%, 30%, and 50% (this example uses three). The total amount of samples for each adulteration ratio is the same, for example, 100 (units).

[0063] 2) Merge samples with the same proportion but different total amounts: For example, set the adulteration proportion to 30%. Set the sample total amount in multiple gradients: 100, 50, 40, 20, and 10 (units). This example uses five gradients.

[0064] In step S130 , the adulterated sample to be detected is subjected to identification pre-processing, and isotope determination is performed on the adulterated sample to be detected after identification pre-processing to obtain multiple isotope values ​​of designated types corresponding to different adulterated samples to be detected.

[0065] In one embodiment, the adulterated sample to be detected is subjected to pre-identification treatment, mainly to facilitate subsequent isotope determination. The pre-identification treatment makes the adulterated sample to be detected meet the standards of isotope determination, thereby improving the accuracy of isotope determination.

[0066] 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.

[0067] Step S140 , performing principal component analysis and / or cluster analysis on multiple isotope values ​​of a specified type based on the type of combined adulterated samples to obtain an adulteration result of the article.

[0068] In practice, extensive experimental results have verified that different types of adulterated sample combinations require significantly different analytical methods to achieve accurate adulteration detection results. Therefore, based on the type of adulterated sample combination, appropriate analysis methods are selected, such as principal component analysis, cluster analysis, and principal component analysis combined with cluster analysis, to achieve more accurate adulteration detection results for the corresponding type of sample combination.

[0069] For ease of understanding, the stable isotope-based method for detecting adulteration of articles provided in the embodiments of the present application is described in detail below.

[0070] In one embodiment of the present application, the above-mentioned item to be detected is rice; wherein, the target sample of the item to be detected is a first variety of rice, and the control sample of the item to be detected is a second variety of rice.

[0071] For the specific implementation method in which the object to be detected is rice, performing object quality pretreatment on the target sample and the control sample may include the following steps 1-1 to 1-4:

[0072] Step 1-1: Process the collected rice samples individually according to their respective numbers; the processing includes drying, removing impurities, sorting, husking, milling, and maintaining the moisture content of the samples at a preset content;

[0073] Step 1-2, quality screening of the processed rice to obtain complete and plump single-grain rice samples;

[0074] Steps 1-3: classify the screened single-grain rice samples and label them with corresponding rice sample labels;

[0075] Steps 1-4: Vacuum and seal the sorted single-grain rice samples and store them in a cool and dry place.

[0076] In one specific example, the rice samples used in the experiment were collected during the 2024 rice harvest. First, the collected rice samples were individually processed according to their respective numbers. Processing steps included airing, cleaning, sorting, husking, and milling to ensure that the moisture content was controlled between 14.0% and 15.5%. The rice was then screened, retaining only intact, plump grains (single-grain rice). The screened rice was placed in a food-grade vacuum bag labeled with the corresponding rice sample, evacuated, and sealed, and finally stored in a cool, dry place for subsequent use.

[0077] Wuchang rice (variety: Wuyoudao No. 4) was collected in Wuchang City, Harbin, Heilongjiang Province, weighing 2 kg. Rice (variety: Zhongkefa No. 5) was collected in Tailai County, Qiqihar City, Heilongjiang Province, hereafter referred to as Tailai rice, weighing 2 kg. Specific information on the rice samples collected is shown in Table 1.

[0078] Table 1 Rice sample collection information

[0079]

[0080] Furthermore, the target sample and the control sample after the quality pretreatment are combined to obtain the adulterated sample to be tested, including the following two situations:

[0081] 1. Adding a second variety of rice to a first variety of rice at a plurality of preset proportions 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 in the plurality of first adulterated samples to be detected determined from the second variety of rice at the plurality of preset proportions is the same as the total number of rice grains in the plurality of first adulterated samples to be detected determined from the first variety of rice;

[0082] 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:

[0083] Wuchang rice (authentic) was adulterated with Tailai rice (adulterated sample) at three adulteration ratios: 10%, 30%, and 50%. The total number of rice grains at each adulteration ratio was 100. The corresponding number of Wuchang and Tailai rice grains at each adulteration ratio is shown in Table 2.

[0084] Table 2 Statistics of single rice grains with different adulteration ratios

[0085]

[0086] 2. Add the second variety of rice to the first variety of rice at a fixed ratio to obtain multiple second adulterated samples to be detected, each corresponding to a different total number of rice grains. In specific implementation, the present embodiment provides a specific sample example, that is, the preparation of adulterated samples with the same adulteration ratio but different total number of rice grains:

[0087] Tailai rice was adulterated with Wuchang rice at a 30% adulteration ratio. Six different total grain counts were set: 140, 100, 70, 40, 20, and 10. Table 3 shows the corresponding Wuchang and Tailai rice grain counts for each total grain count when the adulteration ratio was 30%.

[0088] Table 3 Statistics of single rice grains with different total grain counts

[0089]

[0090] Furthermore, after the aforementioned adulterated sample to be detected is determined, the adulterated sample to be detected may be subjected to pre-identification processing. In specific implementation, the following steps 2-1 to 2-3 may be included:

[0091] 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, the desired single-grain rice is randomly selected from the Wuchang rice and Tailai rice samples to be detected for adulteration.

[0092] In step 2-2, each single-grain rice sample is placed individually in a centrifuge tube of a preset volume and placed in a 60°C constant temperature drying oven for drying until constant weight is achieved. In practical applications, the preset volume can be a 2 ml centrifuge tube, or other volumes can be selected based on actual needs. This is only an example and is not a specific limitation. When placed in a 60°C constant temperature drying oven for drying, it can be continued for 36 hours until constant weight is achieved, that is, the weight difference between the two weighings before and after weighing does not exceed 2 mg.

[0093] 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. The preset aperture can be 0.15 mm. Again, this is merely an example and not a specific limitation. In actual applications, other volume options may be selected based on actual needs.

[0094] Furthermore, isotope determination can be performed on the adulterated sample to be detected after pre-identification treatment to obtain multiple isotope values ​​of a specified type corresponding to different adulterated samples to be detected. In specific implementation, the following two determination methods can be included:

[0095] Determination method 1:

[0096] The dried single-grain rice sample was weighed and wrapped in a tin cup. The single-grain rice sample was then placed into the elemental analysis and stable isotope ratio mass spectrometry 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 elemental analysis and stable isotope ratio mass spectrometry 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.

[0097] In practical applications, 200 μg of dried single-grain rice samples were weighed, wrapped in a tin cup, and then placed in an elemental analysis and stable isotope ratio mass spectrometer (EA-IRMS) for C and N isotope ratio analysis. The sample entered the elemental analyzer through an automatic sampler. The pyrolysis 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 pyrolysis furnace. The entire 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 were respectively entered into the EA-IRMS through a ConFlo IV device 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‰, δ 15 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 precision of N is 0.15‰.

[0098] Determination method 2:

[0099] 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 spectrometry 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 elemental analysis and stable isotope ratio mass spectrometry 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.

[0100] In practical application, 200 μg of dried single-grain rice sample was weighed, wrapped in a silver cup, and placed in the EA-IRMS for H and O isotope ratio analysis. The sample entered the elemental analyzer through an automatic sampler. The temperature of the elemental analyzer's pyrolysis tube 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 automatically online. H2 and CO were separated by gas phase. The chromatographic column temperature was 60°C. H2 and CO were respectively entered into the IRMS through the ConFlo IV device for 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‰.

[0101] After obtaining the isotope determination results, the inventors conducted extensive experiments and comparative analyses to develop the subsequent analytical results for this application. This led them to conclude that, based on the type of adulterated sample combination, principal component analysis and / or cluster analysis were performed on multiple isotope values ​​of a specified type to determine the adulteration of the article. In other words, using the appropriate analytical method for each type of adulterated sample combination can yield more accurate adulteration detection results. The following describes the analytical process in detail.

[0102] For the two types of combined adulterated samples provided in this application, the analysis process is described separately:

[0103] 1. Same total number of particles, different adulteration ratios

[0104] 1-1) The total number of pills is 100, and the adulteration ratio is 10%.

[0105] 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 below. Principal component analysis of the data was performed using Origin. The results are as follows Figure 2 As shown in the figure, samples with serial numbers are all adulterated, while samples without serial numbers are authentic. Adulterated samples are primarily distributed in the positive direction of PC1 and PC2, showing a certain deviation trend. However, the boundaries between adulterated and authentic samples on PC1 and PC2 are not clear, and no clear classification is formed. Therefore, principal component analysis alone cannot effectively distinguish adulterated samples from authentic products.

[0106] Table 4 δ in single grain rice with 10% adulteration 13 C, δ 15 N, δ 2 H, δ 18 O value

[0107]

[0108] Note: WC: Wuchang rice; TL: Tailai rice, the same below.

[0109] When the total number of pellets is 100 and the adulteration ratio is 10%, the clustering results are shown in Table 5. Among the 100 samples, 90 belong to category 1 and 10 belong to category 2, resulting in an adulteration ratio of 10%. Samples 91 to 100 are accurately identified as adulterated.

[0110] Table 5 Cluster analysis results of rice samples with 10% adulteration

[0111]

[0112] Note: In the cluster analysis results, 1 and 2 represent two categories.

[0113] 1-2) The adulteration rate is 30%

[0114] The δ values ​​of 70 grains of Wuchang rice and 30 grains of Tailai rice were measured. 13 C, δ15 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, while samples without serial numbers are authentic. Adulterated samples are primarily concentrated in the positive region of PC1, while authentic samples are more dispersed, primarily concentrated in the negative region of PC1. The two types of samples exhibit certain differences in their distribution trends on PC1. Overall, adulterated samples and authentic products are effectively distinguished in principal component space.

[0115] Table 6 δ in single-grain rice with 30% adulteration 13 C, δ 15 N, δ 2 H, δ 18 O value

[0116]

[0117] When the total number of grains is 100 and the adulteration ratio is 30%, the clustering results are shown in Table 7. Of the 100 samples, 70 belong to category 1 and 30 belong to category 2, resulting in an adulteration ratio of 30%. Sequence numbers 71 to 100 are identified as adulterated rice.

[0118] Table 7 Cluster analysis results of rice samples with 30% adulteration

[0119]

[0120] 1-3) The adulteration ratio is 50%

[0121] The δ values ​​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 a position 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 sample distribution on PC2, its impact on classification is small, and PC1 plays a dominant role in sample differentiation. Therefore, it can be considered that adulterated samples and authentic products are effectively distinguished in the principal component space.

[0122] Table 8 δ in single grain rice with 50% adulteration 13 C, δ 15 N, δ 2 H, δ 18 O value

[0123]

[0124] When the total number of grains is 100 and the adulteration ratio is 50%, the clustering results are shown in Table 9. Of the 100 samples, 50 belong to category 1 and 50 belong to category 2, resulting in an adulteration ratio of 50%. Rice numbers 51 to 100 are identified as adulterated rice.

[0125] Table 9 Cluster analysis results of rice samples with 50% adulteration

[0126]

[0127] 2. Same adulteration ratio, different total number of particles

[0128] 2-1) The adulteration ratio is 30%, and the total number of pills is 140

[0129] 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 difference in distribution along PC1 indicates that adulterated samples and authentic products have good distinguishing ability along this principal component direction. Although there is some overlap between samples on PC2, the two types of samples can still be classified using principal component analysis.

[0130] Table 10 δ in 140 single grains of rice 13 C, δ 15 N, δ 2 H, δ 18 O value

[0131]

[0132] When the adulteration rate is 30% and the total number of grains is 140, the clustering results are shown in Table 11. Among the 140 samples, 98 samples belong to Class 1 and 42 samples belong to Class 2, resulting in an adulteration rate of 30%. Sequence numbers 99 to 140 are identified as adulterated rice.

[0133] Table 11 Cluster analysis results of 140 rice samples

[0134]

[0135] 2-2) The adulteration ratio is 30%, and the total number of pills is 100

[0136] 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 6As shown in the figure, samples with serial numbers are all adulterated, while samples without serial numbers are authentic. Adulterated samples are primarily concentrated in the positive direction of PC1, with a narrower and more concentrated distribution range, while authentic samples are primarily distributed in the negative direction of PC1, with a wider and more dispersed distribution range. On PC2, the distribution of adulterated samples is relatively close to the center, while the distribution of authentic samples is more dispersed, showing a trend of upward and downward expansion. Overall, in the principal component space, adulterated samples can be distinguished from authentic products.

[0137] Table 12 δ in 100 single grains of rice 13 C, δ 15 N, δ 2 H, δ 18 O value

[0138]

[0139] When the adulteration rate is 30% and the total number of grains is 100, the clustering results are shown in Table 13. Of the 100 samples, 70 belong to category 1 and 30 belong to category 2, indicating an adulteration rate of 30%. Rice numbers 71 to 100 are identified as adulterated rice.

[0140] Table 13 Cluster analysis results of 100 rice grain samples

[0141]

[0142] 2-3) The adulteration ratio is 30%, and the total number of pills is 70

[0143] 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 with serial numbers are all adulterated, while samples without serial numbers are authentic. Along PC1, adulterated samples and authentic products show a clear trend of separation, with adulterated samples concentrated in the positive direction and authentic samples concentrated in the negative direction. On PC2, adulterated samples are primarily concentrated near the center, while authentic samples have a greater spread in the vertical direction. Overall, adulterated samples and authentic products can be distinguished in principal component space.

[0144] Table 14 δ in 70 single grains of rice13 C, δ 15 N, δ 2 H, δ 18 O value

[0145]

[0146] When the adulteration rate is 30% and the total number of grains is 70, the clustering results are shown in Table 15. Of the 70 samples, 49 belong to Class 1 and 21 belong to Class 2, indicating an adulteration rate of 30%. Rice numbers 50 to 70 are identified as adulterated rice.

[0147] Table 15 Cluster analysis results of 70 rice samples

[0148]

[0149] 2-4) The adulteration ratio is 30%, and the total number of pills is 40

[0150] 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 with serial numbers are all adulterated, while samples without serial numbers are authentic. Adulterated samples are concentrated in the positive direction of PC1 and are densely distributed, showing strong clustering. Authentic samples are concentrated in the negative direction of PC1 and have a more dispersed distribution. Adulterated and authentic samples are completely separated on PC1, with no significant overlap. Overall, principal component analysis is able to distinguish adulterated samples from authentic products.

[0151] Table 16 δ in 40 single grains of rice 13 C, δ 15 N, δ 2 H, δ 18 O value

[0152]

[0153] When the adulteration rate is 30% and the total number of grains is 40, the clustering results are shown in Table 17. Of the 40 samples, 28 belong to Class 1 and 12 belong to Class 2, indicating an adulteration rate of 30%. Sequence numbers 29 to 40 are identified as adulterated rice.

[0154] Table 17 Cluster analysis results of 40 rice samples

[0155]

[0156] 2-5) The adulteration ratio is 30%, and the total number of pills is 20

[0157] The δ values ​​of 14 grains of Wuchang rice and 6 grains of Tailai rice were measured. 13 C, δ 15 N, δ 2 H, 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 Figure 9 As shown in the figure, samples with serial numbers are all adulterated, while samples without serial numbers are authentic. Adulterated samples are distributed in the positive direction of PC1, while authentic products are located in the negative direction of PC1. However, due to the small number of samples, the spatial distribution density of samples is insufficient, resulting in unclear classification boundaries. Therefore, it is impossible to distinguish adulterated samples from authentic products using principal component analysis.

[0158] Table 18 δ in 20 single grains of rice 13 C, δ 15 N, δ 2 H, δ 18 O value

[0159]

[0160] When the adulteration rate is 30% and the total number of grains is 20, the clustering results are shown in Table 19. Among the 20 samples, 14 samples belong to Class 1 and 6 samples belong to Class 2, indicating an adulteration rate of 30%. Sequence numbers 15 to 20 are identified as adulterated rice.

[0161] Table 19 Cluster analysis results of 20 single-grain rice samples

[0162]

[0163] 2-6) The adulteration ratio is 30%, and the total number of pellets is 10

[0164] 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 Figure 10As shown in the figure, samples with serial numbers are all adulterated, while samples without serial numbers are authentic. The adulterated samples are all located in the positive direction of PC1, but they are relatively dispersed and not concentrated. The authentic samples are distributed in the negative direction of PC1, also showing a certain degree of dispersion. Due to the small number of samples and their dispersed distribution, the classification boundaries are blurred. Therefore, it is impossible to distinguish adulterated samples from authentic products using principal component analysis.

[0165] Table 20 δ in 10 single grains of rice 13 C, δ 15 N, δ 2 H, δ 18 O value

[0166]

[0167] When the adulteration rate is 30% and the total number of grains is 10, the clustering results are shown in Table 21. Among the 10 samples, 7 samples belong to Class 1 and 3 samples belong to Class 2, indicating an adulteration rate of 30%. Sequence numbers 8 to 10 are identified as adulterated rice.

[0168] Table 21 Cluster analysis results of 10 rice samples

[0169]

[0170] The above-mentioned method uses stable isotope technology, combined with principal component analysis and cluster analysis in an unsupervised mode, to identify and quantitatively detect adulteration of rice samples with different adulteration ratios (10, 30, 50%) and different total grain numbers (140, 100, 70, 40, 20, 10 grains).

[0171] The above analysis results indicate that, in principal component analysis (PCA), adulterated samples and authentic products exhibit certain distribution differences in the principal component space. However, when the adulteration ratio is low (e.g., 10%) and the total number of grains is small (e.g., 10 or 20 grains), these differences are insufficient to form a clear classification boundary, and PCA alone cannot effectively distinguish adulterated samples from authentic products. As the adulteration ratio and total number of grains increase, the distribution of adulterated samples in the PCA space gradually exhibits a clustering trend, and the distribution differences between adulterated samples and authentic products in the PCA space become more pronounced, revealing some characteristic differences between the samples. This difference can reveal some characteristic variations between samples, thus aiding in the identification of adulterated samples, but it still cannot accurately calculate the adulteration ratio using PCA.

[0172] In contrast, cluster analysis demonstrated superior results in adulteration identification. In experiments with varying adulteration ratios and total grain counts, cluster analysis accurately separated adulterated samples from authentic products into distinct clusters. 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 set of experiments, the adulteration ratio calculated using cluster analysis was consistent with the experimentally determined adulteration ratio, demonstrating the effectiveness of cluster analysis in quantitatively detecting rice adulteration and its ability to accurately calculate the adulteration ratio.

[0173] 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 combination to obtain an adulteration result of the article, which may include the following two situations:

[0174] 1. When the type of merging of adulterated samples with the same total amount but different proportions is adopted:

[0175] The distribution of the first principal component and the second principal component of multiple isotope values ​​of a specified type is determined by principal component analysis;

[0176] 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;

[0177] 2. When the type of merging of adulterated samples with the same proportion but different total amounts is adopted:

[0178] The distribution of the first principal component of multiple isotope values ​​of a specified type is determined through principal component analysis. Samples that are distributed in the positive direction of the first principal component, with a smaller and more compact distribution range, are identified 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 identified as authentic samples.

[0179] 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.

[0180] Based on the above method embodiment, the present application embodiment also provides an article adulteration detection system based on stable isotopes, see Figure 11 As shown, the system includes the following parts:

[0181] The sample acquisition and preprocessing module 210 is used to acquire target samples and control samples of the items to be tested, and perform item quality preprocessing on the target samples and control samples;

[0182] The sample doping module 220 is used to perform doping sample merging on the target sample and the control sample after the article quality pretreatment 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;

[0183] The isotope determination module 230 is used to perform pre-identification processing on the adulterated sample to be detected, and perform isotope determination on the adulterated sample to be detected after the pre-identification processing, to obtain multiple isotope values ​​of specified types corresponding to different adulterated samples to be detected;

[0184] 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 samples combined to obtain an adulteration result of the article.

[0185] In a feasible 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.

[0186] In a feasible implementation manner, the sample acquisition and preprocessing module 210 is further configured to:

[0187] The collected rice samples are processed independently according to their respective numbers; the processing includes drying, removing impurities, sorting, husking, milling, and keeping the moisture content of the samples within the preset content;

[0188] The processed rice is screened for quality to obtain complete and plump single-grain rice samples;

[0189] The screened single-grain rice samples are classified and labeled with corresponding rice sample labels;

[0190] The sorted single-grain rice samples were vacuum-packed, sealed, and stored in a cool, dry place.

[0191] In a feasible embodiment, the sample doping module 220 is further configured to:

[0192] Adding a second variety of rice to a first variety of rice at a plurality of preset proportions 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 in the plurality of first adulterated samples to be detected determined for the second variety of rice at the plurality of preset proportions is the same as the total number of rice grains in the plurality of first adulterated samples to be detected determined for the first variety of rice;

[0193] 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.

[0194] In a feasible embodiment, the isotope determination module 230 is further configured to:

[0195] 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;

[0196] Each single-grain rice sample was placed in a centrifuge tube of preset volume and placed in a constant temperature drying oven for drying until constant weight was achieved;

[0197] 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.

[0198] In a feasible embodiment, the isotope determination module 230 is further configured to:

[0199] The dried single-grain rice sample is weighed and wrapped in a tin cup, and then the single-grain rice sample is placed 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 elemental 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;

[0200] A dried single-grain rice sample is weighed, wrapped in a silver cup, and then placed into an elemental analysis and stable isotope ratio mass spectrometer through an automatic sample injector for isotope ratio analysis of δ2H and δ18O. The pyrolysis tube temperature of the elemental 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.

[0201] In a feasible embodiment, the adulteration detection module 240 is further configured to:

[0202] When the type of merging of adulterated samples with the same total amount but different proportions is used:

[0203] The distribution of the first principal component and the second principal component of multiple isotope values ​​of a specified type is determined by principal component analysis;

[0204] 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;

[0205] When the type of adulterated sample merging is used, where the sample is combined in the same proportion but different amounts:

[0206] The distribution of the first principal component of multiple isotope values ​​of a specified type is determined through principal component analysis. Samples that are distributed in the positive direction of the first principal component, with a smaller and more compact distribution range, are identified 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 identified as authentic samples.

[0207] The stable isotope-based article adulteration detection system provided in the embodiments of the present application has the same implementation principle and technical effects as those of the aforementioned method embodiments. For the sake of brief description, for matters not mentioned in the embodiments 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 embodiments.

[0208] The present application also provides an electronic device, such as Figure 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.

[0209] exist Figure 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 .

[0210] Among them, the memory 10 may include high-speed random access memory (RAM), and may also include 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 can 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 one type of bus.

[0211] The processor 11 may be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method can be completed by hardware integrated logic circuits in the processor 11 or by software instructions. The above processor 11 may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it may 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 gate or transistor logic devices, or discrete hardware components. The general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in the embodiments of the present application can be directly implemented as being executed by a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. The software module can be located in a storage medium mature in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, etc. The storage medium is located in the memory, and the processor 11 reads the information in the memory and, in combination with its hardware, completes the steps of the article adulteration detection method based on stable isotopes in the aforementioned embodiment.

[0212] 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 and will not be repeated here.

[0213] The computer program products of the stable isotope-based article adulteration detection method, system, and electronic device provided in the embodiments of the present application include 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. For specific implementation, please refer to the method embodiments and will not be repeated here.

[0214] 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.

[0215] 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 existing technology, 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 and includes a number of instructions for enabling 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 code.

[0216] In the description of this 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.

[0217] 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 them. 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 make equivalent replacements for some or all of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions 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; Performing 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 an article adulteration result; Based on the type of the adulterated sample merging, principal component analysis and / or cluster analysis are performed on the multiple isotope values ​​of the specified type to obtain the result of the adulteration of the article, including: when the type of the adulterated sample merging with the same total amount but different proportions is adopted: the distribution of the first principal component and the second principal component is measured on the 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 the result of the adulteration of the article is obtained; When the type of merging adulterated samples with the same proportion but different total amounts is adopted: the distribution of the first principal component of the multiple isotope values ​​of the specified type is determined by principal component analysis, and the samples distributed in the positive direction of the first principal component, with a smaller distribution range and more compactness are determined as adulterated samples, and the samples distributed in the negative direction of the first principal component, with a wider distribution range and more dispersedness are determined as authentic samples.

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. 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 the article adulteration; the adulteration detection module is also used to: when the type of the adulterated sample combination with the same total amount but different proportions is adopted: perform the distribution measurement of the first principal component and the second principal component on the multiple isotope values ​​of the specified type through principal component analysis; perform cluster analysis based on the distribution measurement results of the first principal component and the second principal component, perform cluster extraction on the adulterated samples, and obtain the result of the article adulteration; When the type of merging adulterated samples with the same proportion but different total amounts is adopted: the distribution of the first principal component of the multiple isotope values ​​of the specified type is determined by principal component analysis, and the samples distributed in the positive direction of the first principal component, with a smaller distribution range and more compactness are determined as adulterated samples, and the samples distributed in the negative direction of the first principal component, with a wider distribution range and more dispersedness are determined as authentic samples.

8. 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 6.

9. 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 6.

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