Scientia Agricultura Sinica ›› 2025, Vol. 58 ›› Issue (23): 5071-5080.doi: 10.3864/j.issn.0578-1752.2025.23.020

• ANIMAL SCIENCE·VETERINARY SCIENCE • Previous Articles     Next Articles

Study on the Origin Traceability of Beijing Black Pig Based on Stable Isotope Technology

LIU Jing2(), ZHAO ShiLin2(), YANG XiaoTing2, WEI YiXuan1, LI JiaPeng1,*(), ZHAO Yan2,*()   

  1. 1 China Meat Food Comprehensive Research Center, Beijing 100068
    2 Institute of Agricultural Quality Standards, Chinese Academy of Agricultural Sciences/Key Laboratory of Agricultural Product Quality and Safety, Ministry of Agriculture and Rural Areas, Beijing 100081
  • Received:2024-09-30 Accepted:2025-11-01 Online:2025-12-01 Published:2025-12-09
  • Contact: LI JiaPeng, ZHAO Yan

Abstract:

【Background】 Under the background of the quality and safety supervision of agricultural products facing severe challenges, the traceability of characteristic pork products has become a key link to ensure food safety. In recent years, there has been frequent chaos in the market, such as shoddy goods and fake places of origin, which have seriously damaged consumers' rights and interests as well as the healthy development of the industry. 【Objective】 In this study, the characteristics of stable isotope ratio of black pig samples from three producing areas (Yanqing, Beijing; Chengde, Hebei province; Laiwu, Shandong province) were analyzed, so as to establish the traceability technology of Beijing black pig based on stable isotope analysis and provide a support for the traceability identification of meat products. 【Method】 A total of 110 pork samples from three regions were collected in the experiment. The ratios of four stable isotopes, namely carbon, nitrogen, hydrogen and oxygen, in pork samples were determined by elemental analysis and isotope ratio mass spectrometry (EA-IRMS), and the origin discrimination model was established by chemometrics. Specifically, it included: one-way analysis of variance (ANOVA) to test the significant difference between groups; Principal component analysis (PCA) was used to visualize the data distribution. Orthogonal partial least squares discriminant analysis (OPLS-DA) was used to screen key discriminant indexes; according to the linear discriminant analysis (LDA), the data were statistically analyzed, and the traceability model of Beijing black pig with stable isotope index was established. 【Result】 Analysis of variance showed that there were significant differences in δ13C, δ15N, δ2H and δ18O stable isotopic ratios among the samples from three producing areas (P<0.05), which were mainly due to the differences in feed composition, fertilization methods and water source characteristics. Through principal component analysis, it was found that the cumulative contribution rate of the first two principal components reached 90.9%, which effectively distinguished pork samples from three producing areas. Orthogonal partial least squares discriminant analysis further verified the differentiation effect (R2X=1, R2Y=0.876, Q2=0.866). In the linear discriminant model based on four stable isotope combinations, the discriminant accuracy of the training set and the test set were both 100%, and the area under the ROC curve (AUC value) was 1.000, which showed that the model had extremely high stability and reliability, and provided the strong technical support for the traceability of Beijing black pig products. 【Conclusion】 In this study, the stable isotope technique was successfully used to accurately identify the origin of Beijing black pig, and the application potential of this method in security traceability was verified. The stable isotope characteristic fingerprints formed by different regional environmental factors provided the scientific and reliable technical support for the origin certification of pork products.

Key words: Beijing black pig, stable isotope, origin traceability, chemometrics, discriminant model

Table 1

Content of four stable isotopes in pork from different areas"

元素 Element 北京延庆 Yanqing, Beijing 河北承德 Chengde, Hebei 山东莱芜 Laiwu, Shandong
δ13C (‰) -17.24±0.36c -14.71±0.38a -15.80±0.43b
δ15N (‰) 3.38±0.22b 3.01±0.20c 4.09±0.40a
δ2H (‰) -107.54±2.16b -113.17±2.31c -102.22±1.92a
δ18O (‰) 13.70±0.64a 10.16±0.92c 12.58±0.57b

Fig. 1

PCA and OPLS-DA diagrams for pork from different producing areas based on stable isotopes of δ13C, δ15N, δ2H, δ18O A: PCA score diagram; B: OPLS-DA score chart; C: OPLS-DA model with training set and test set"

Fig. 2

Verification of the OPLS-DA model for pork from different producing areas based on δ13C, δ15N, δ2H, δ18O"

Table 2

Prediction accuracy of stable isotope OPLS-DA model for pork"

数据集
Data set
产地
Origin
样本量
Sample size
北京延庆
Yanqing, Beijing
河北承德
Chengde, Hebei
山东莱芜
Laiwu, Shandong
准确率
Accuracy rate (%)
训练集
Training set
北京延庆 Yanqing, Beijing 30 30 0 0 100.0
河北承德 Chengde, Hebei 30 0 30 0 100.0
山东莱芜 Laiwu, Shandong 23 0 0 23 100.0
测试集
Testing set
北京延庆 Yanqing, Beijing 10 10 0 0 100.0
河北承德 Chengde, Hebei 10 0 10 0 100.0
山东莱芜 Laiwu, Shandong 7 0 0 7 100.0

Fig. 3

Distribution of VIP values of stable isotope in OPLS-DA model"

Fig. 4

Confusion matrix for stable isotope classification in pork origin discrimination model based on LDA A: δ13C和δ15N training set (left) and test set (right); B: δ2H和δ18O training set (left) and test set (right); C: δ13C、δ15N、δ2H和δ18O training set (left) and test set (right)"

Table 3

Prediction accuracy of the LDA-based pork origin identification model"

稳定同位素组合
Stable isotope combination
训练集预测正确率
Training set prediction accuracy (%)
测试集预测正确率
Testing set prediction accuracy rate (%)
训练集AUC值
Training set
AUC value
测试集AUC值
Testing set
AUC value
δ13C&δ15N 97.6 96.3 0.995 0.975
δ2H&δ18O 98.8 96.3 0.983 0.992
δ13C&δ15N&δ2H&δ18O 100.0 100.0 1.000 1.000
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