Artificial intelligence-based identification of butter variations as a model study for detecting food adulteration

The demand for high-quality food products is increasing globally at unprecedented rates in response to growing health concerns and consumer awareness about healthy food options. Yet, the tools for determining food quality remain restricted to well-equipped laboratories, not readily accessible to con...

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Bibliographic Details
Published in:Innovative food science & emerging technologies 2020-12, Vol.66, p.102527, Article 102527
Main Authors: Iymen, Gokce, Tanriver, Gizem, Hayirlioglu, Yusuf Ziya, Ergen, Onur
Format: Article
Language:English
Subjects:
Adulteration
Artificial intelligence
CRNN
Food fraud
Frequency response
Machine learning
MFCCs
Mobile application
Organic food products
Parallel CNN-RNN
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Summary:The demand for high-quality food products is increasing globally at unprecedented rates in response to growing health concerns and consumer awareness about healthy food options. Yet, the tools for determining food quality remain restricted to well-equipped laboratories, not readily accessible to consumers. Unfortunately, the current inspection mechanisms are limited and cannot keep track of all the products continuously, which exposes weakness in the system towards adulteration, falsification, and mislabeling products. Consumers rely on manufacturer labeling alone, with no convenient and user-friendly tool to confirm quality, especially for organic products. The advancement of Artificial Intelligence (AI) provides an opportunity for these tools to be developed. In this study, we demonstrate that simple sound vibrations traversing the food products can be used in conjunction with deep learning models to verify high quality products with no additives, as well as organic food products. Our neural network models, namely Parallel CNN-RNN and CRNN, achieve high accuracy on the defined classification tasks. To our knowledge, this is the first report of an AI-based tool utilizing simple sound vibrations to identify adulteration in food products. •A simple artificial intelligence based food fraud, or economically motivated adulteration, technology is introduced.•An innovative sound vibration based detection mechanism was designed.•Very good performance achieved to verify high quality products with no additives, as well as organic food products.•Proof of concept is developed towards a simple smart phone application to make every consumer an inspector of their own food.
ISSN:1466-8564
1878-5522
DOI:10.1016/j.ifset.2020.102527