基于稳定同位素技术的北京黑猪产地溯源研究

doi:10.3864/j.issn.0578-1752.2025.23.020

摘要/Abstract

摘要：

【背景】在当前农产品质量安全监管面临严峻挑战的背景下，特色猪肉产品的产地溯源已成为保障食品安全的关键环节。近年来，市场上以次充好、产地造假等乱象频发，严重损害消费者权益和产业健康发展。【目的】 通过对3个产地（北京延庆、河北承德、山东莱芜）黑猪样品的稳定同位素比值特征差异分析，建立基于稳定同位素分析的北京黑猪产地溯源技术，为肉类产品产地溯源鉴别提供支持。【方法】 采集3个地区共110份猪肉样品，采用元素分析与同位素比质谱仪（EA-IRMS）测定猪肉样品中碳、氮、氢、氧4种稳定同位素比值，结合化学计量学方法构建产地判别模型。具体包括：单因素方差分析（ANOVA）检验组间差异显著性比较；采用主成分分析（PCA）可视化数据分布；利用正交偏最小二乘判别分析（OPLS-DA）筛选关键判别指标；根据线性判别分析（LDA）对数据进行统计分析，建立稳定同位素指标的北京黑猪产地溯源模型。【结果】 方差分析显示，3个产地样品之间的δ¹³C、δ¹⁵N、δ²H、δ¹⁸O稳定同位素比值均存在显著差异（P<0.05），这些差异主要源于各地饲料组成、施肥方式和水源特征的不同。通过主成分分析发现前两个主成分累计贡献率达90.9%，有效区分了3个产地的猪肉样品，正交偏最小二乘判别分析进一步验证了该区分效果（R²X=1，R²Y=0.876，Q²=0.866）。在基于4种稳定同位素组合建立的线性判别模型中，训练集和测试集判别准确率均达100%，且ROC曲线下面积（AUC值）均为1.000，表明该模型具有极高的稳定性和可靠性，为北京黑猪产品产地溯源提供了强有力的技术支撑。【结论】 通过稳定同位素技术，成功实现了对北京黑猪产地的精准鉴别，验证了该方法在肉类产品防伪溯源领域的应用潜力。不同地域环境因素形成的稳定同位素特征指纹，为猪肉产品的原产地认证提供了科学可靠的技术支撑。

关键词: 北京黑猪, 稳定同位素, 产地溯源, 化学计量学, 判别模型

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

刘静, 赵世琳, 阳晓婷, 韦忆萱, 李家鹏, 赵燕. 基于稳定同位素技术的北京黑猪产地溯源研究[J]. 中国农业科学, 2025, 58(23): 5071-5080.

LIU Jing, ZHAO ShiLin, YANG XiaoTing, WEI YiXuan, LI JiaPeng, ZHAO Yan. Study on the Origin Traceability of Beijing Black Pig Based on Stable Isotope Technology[J]. Scientia Agricultura Sinica, 2025, 58(23): 5071-5080.

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链接本文: https://www.chinaagrisci.com/CN/10.3864/j.issn.0578-1752.2025.23.020

https://www.chinaagrisci.com/CN/Y2025/V58/I23/5071

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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

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

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