Home Journals Articles Updates About
CN
image
收藏切换
Risk warning of veterinary drug residues in beef and mutton in a province based on Bayesian network
收藏切换
Han-Xiang WANG1, 2, Jing-Yan LI1, Wen-Chuan GUO3, Xin-Hua ZHU3, Yu-Jie CHEN1, 2, *, Xin LV1, 2, *
Journal of Food Safety & Quality | 2026, 17(6) : 37 - 47
Less
收藏切换
Journal of Food Safety & Quality | 2026, 17(6): 37-47
• Special Topic: Food Safety Risk Monitoring and Assessment •
Risk warning of veterinary drug residues in beef and mutton in a province based on Bayesian network
Full
Han-Xiang WANG1, 2, Jing-Yan LI1, Wen-Chuan GUO3, Xin-Hua ZHU3, Yu-Jie CHEN1, 2, *, Xin LV1, 2, *
Affiliations
  • 1.College of Food Science and Engineering, Northwest A&F University, Yangling 712100, China
  • 2.Shaanxi Engineering Research Centre of Dairy Products Quality, Safety and Health, Yangling 712100, China
  • 3.College of Mechanical and Electronic Engineering, Northwest A&F University, Yangling 712100, China
doi: 10.19812/j.cnki.jfsq11-5956/ts.20251010008
Outline
收藏切换
Objective

To construct a Bayesian network risk assessment model to systematically quantify the risks of tetracycline, quinolone, β2-receptor agonist and sulfonamide drug residues.

Methods

The risk value was evaluated by expert scoring, and the initial model was established by using the information entropy weight method to obtain the prior probability. The Bayesian network warning model was established by importing the monitoring data through the expectation maximization algorithm (EM) of Bayesian network, and the risk prediction of the risk factors of animal residues was carried out.

Results

The overall risk probability of a province obtained by the Bayesian network model was (within the maximum detection limit): Low risk 74%, medium risk 16% and high risk 10%. The highest sensitivity of tetracycline was 0.37, which was the key risk factor; the risk of quinolones and sulfonamides was in good condition; as a banned drug, the risk probability of β2-receptor agonist did not reach 100% low risk, and supervision needed to be strengthened.

Conclusion

The constructed Bayesian network model has risk assessment and warning, and many kinds of drugs can be classified and supervised, which provides technical support for improving the accuracy and timeliness of veterinary drug residue risk management.

Bayesian network  /  veterinary drug residues  /  warning model  /  risk assessment
王汉祥, 李婧妍, 郭文川, 朱新华, 陈玉洁, 吕欣. 基于贝叶斯网络的某省牛羊肉中兽药残留风险预警研究. 食品安全质量检测学报, 2026 , 17 (6) : 37 -47 . DOI: 10.19812/j.cnki.jfsq11-5956/ts.20251010008
Han-Xiang WANG, Jing-Yan LI, Wen-Chuan GUO, Xin-Hua ZHU, Yu-Jie CHEN, Xin LV. Risk warning of veterinary drug residues in beef and mutton in a province based on Bayesian network[J]. Journal of Food Safety & Quality, 2026 , 17 (6) : 37 -47 . DOI: 10.19812/j.cnki.jfsq11-5956/ts.20251010008
Appendix
Less
Year 2026 volume 17 Issue 6
9
1
Cite this Article
BibTeX
Article Info
doi: 10.19812/j.cnki.jfsq11-5956/ts.20251010008
  • Receive Date：2025-10-10
  • Online Date：2026-11-05
Article Data
Affiliations
History
  • Received：2025-10-10
Funding
Affiliations
    1.College of Food Science and Engineering, Northwest A&F University, Yangling 712100, China
    2.Shaanxi Engineering Research Centre of Dairy Products Quality, Safety and Health, Yangling 712100, China
    3.College of Mechanical and Electronic Engineering, Northwest A&F University, Yangling 712100, China
References
Share
https://castjournals.cast.org.cn/joweb/spaq/EN/10.19812/j.cnki.jfsq11-5956/ts.20251010008
Share to
QR

Scan QR to access full text

Cite this article
BibTeX
Citations
表12种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
关闭全屏
  • BibTeX
  • EndNote
  • RefWorks
  • TxT
Links
Articles
Latest Articles
Most Read
Collections
Updates
Events
News
Multimedia
About
About Us
Contact
No. 86 Xueyuan South Road, Haidian District, Beijing
100081
010-62662699(Operation and Technical Support)
qkjq@cast.org.cn

Copyright © 2025 China Association for Science and Technology. All rights reserved. For all open access content, the relevant licensing terms apply.
Sponsored by the Office of the Leading Group for Cybersecurity and Informatization of CAST, and supported by Science and Technology Review Publishing House