Harnessing artificial intelligence in microbial food safety: global progress and implications in the ASEAN region

被引:0
|
作者
Panaligan, Dominic [1 ,3 ]
Sy, Isaac Cornelius Bensley [2 ]
Sarza, Riann Martin [1 ,3 ]
机构
[1] Univ Philippines Diliman, Coll Home Econ, Dept Food Sci & Nutr, Quezon City, Philippines
[2] Univ Philippines Diliman, Coll Engn, Elect & Elect Engn Inst, Quezon City, Philippines
[3] Natl Univ Singapore, Fac Sci, Dept Chem, Singapore City, Singapore
来源
INTERNATIONAL JOURNAL OF FOOD SCIENCE AND TECHNOLOGY | 2024年 / 59卷 / 10期
关键词
AI; ASEAN; food safety; machine learning; FOODBORNE ILLNESS;
D O I
10.1111/ijfs.17216
中图分类号
TS2 [食品工业];
学科分类号
0832 ;
摘要
Food safety remains one of the major concerns in ASEAN, with many of the recent developmental plans and published policies in the region being focused on the topic. Most recent WHO data indicate that over 90% of the food safety burden in ASEAN is due to microbial foodborne diseases. However, conventional systems for controlling FBDs are resource-intensive and require significant infrastructure which may not yet be present in ASEAN. Prior work on the use of Artificial intelligence (AI) in food safety application has shown its potential to reduce costs and increase efficiency. However, there remains a paucity in such research specific for the ASEAN region. In this review, the state of microbial food safety and the unique challenges in the ASEAN region are presented. The global state-of-the-art of microbial food safety applications of AI are presented and possible steps for its adaptation to the ASEAN context are then discussed. This paper is a global review of the applications AI in microbial food safety. It also contextualises the current status of the ASEAN region when it comes to microbial food safety, and how the region can adapt AI technologies to improve its current state. image
引用
收藏
页码:7754 / 7766
页数:13
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