Evaluation of methods for the detection of hazardous substances in food based on machine learning-Reference-Cited by-同舟云学术

Evaluation of methods for the detection of hazardous substances in food based on machine learning

Published:2024 Issue:3 Volume:48 Page:1399-1406
ISSN:1144-0546
Container-title:New Journal of Chemistry
language:en
Short-container-title:New J. Chem.

Author:

Zhu Long-yu¹,Yan Lijuan²,Zhao Fang³,Guo Xuewen¹,Xu Dunming²,Lv Jingzhang³,Ding Lin²,Niu Na³,Qiao Jun-qin¹,Ma Shumian³,Huang Xindi³,Liu Huiling³,Lian Hong-zhen¹^ORCID

Affiliation:

1. State Key Laboratory of Analytical Chemistry for Life Science, School of Chemistry & Chemical Engineering and Center of Materials Analysis, Nanjing University, Nanjing 210023, China

2. Technology Center, Xiamen Customs, Xiamen 361026, China

3. Shenzhen Academy of Inspection and Quarantine, Food Inspection and Quarantine Technology Center of Shenzhen Customs District, Shenzhen 518045, China

Abstract

To evaluate methods of hazard detection, two index systems were proposed and four machine learning-based evaluation models were built and compared.

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

Publisher

Royal Society of Chemistry (RSC)

Subject

Materials Chemistry,General Chemistry,Catalysis

Link

http://pubs.rsc.org/en/content/articlepdf/2024/NJ/D3NJ04074G

Reference32 articles.

1. Food supply and food safety issues in China

2. Food safety issues in China: a case study of the dairy sector

3. Public health risks related to food safety issues in the food market: a systematic literature review

4. Food safety in the 21st century

5. Determination of clenbuterol in beef liver and muscle tissue using immunoaffinity chromatographic cleanup and liquid chromatography with ultraviolet absorbance detection