Emerging Opportunities for Machine Learning in Food Safety: Potential and Pitfalls

[...]certain pathogen characteristics of food safety significance are mechanistically complicated and not well understood, for example, the association between particular pathogens and their sources. [...]machine learning holds promise to solve difficult problems in the biomedical sciences using gen...

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Bibliographic Details
Published inFood Safety Magazine
Main Authors Deng, Xiangyu, Cao, Shuhao, Horn, Abigail L
Format Trade Publication Article
LanguageEnglish
Published Troy BNP Media 15.04.2021
Subjects
Antimicrobial agents
Artificial intelligence
Biomedical data
Computers
Data transmission
Drug resistance
Food chains
Food safety
Food supply
Garbage
Genomes
Genomics
Illnesses
Learning algorithms
Machine learning
Pathogens
Public health
Restaurants
Safety
Salmonella
Social networks
Supply chains
Surveillance
Training
United States > US
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Summary:[...]certain pathogen characteristics of food safety significance are mechanistically complicated and not well understood, for example, the association between particular pathogens and their sources. [...]machine learning holds promise to solve difficult problems in the biomedical sciences using genomic data. [...]as mentioned above, training sets greatly affect the outcome of the analysis, and “garbage in, garbage out” is a common pitfall. In the case of machine learning with food safety genomic data, inflated source attribution accuracy can be derived from oversampling of closely related Salmonella genomes of the same source in the training set.4,6 Machine Learning Using Novel Data Streams Another major area of application of machine-learning techniques in food safety involves the use of novel data streams (NDS)⁷—emerging sources of data that are created continuously and passively by individuals going about their daily lives, also called “data in the wild”—which include text (social media), trade, and transactional data. Because these data are generated on the consumer level, their value has been found mainly in surveillance of food safety events at the last mile of the food supply chain.
ISSN:2765-8481
1538-1102