Instant Olive Oil Quality Detection and Rapid Food Evaluation: A User-Friendly and Attractive Artificial Intelligence Solution

10 Pages Posted: 13 Feb 2024

See all articles by Mehmet Ali Sarsıl

Mehmet Ali Sarsıl

Istanbul Technical University

Dila Dede

Istanbul University

Adildabay Seçilmis

Istanbul Technical University

Gizem Catalkaya

Istanbul Technical University

Ata Shaker

Istanbul Technical University

Esra Capanoglu

Istanbul Technical University - Department of Food Engineering

Onur Ergen

University of California, Berkeley

Abstract

The global demand for high-quality olive oil has witnessed unprecedented growth, driven by heightened health consciousness and consumer preferences for healthy dietary choices. However, this surging demand has made olive oil one of the most adulterated foods worldwide. Olive oil food adulteration can be done through chemical and thermal processing which causes reduced nutritional value as well as serious health risks for consumers. This emphasizes the critical importance of building an effective food fraud detection system for olive oil. In this study, we developed a new method that can instantly determine both adulteration and quality from a single smartphone image, offering a swift and user-friendly solution. A single droplet of oil dispersed across the water’s surface provides rapid and exact detection of food adulteration in seconds. Our method employs two specialized machine learning models: an unsupervised K-means clustering model and a supervised Convolutional Neural Network (CNN) for image analysis of olive oil on the water surface, a phenomenon affected by interfacial tension dynamics. These models excel in classifying olive oil quality, with a 99% accuracy rate, marking a tremendous leap in the identification of food fraud using Artificial Intelligence (AI).

Keywords: Artificialintelligence, Machinelearning, ConvolutionalNeuralNetworks, Foodfraud, Adulteration, OliveOil

Suggested Citation

Sarsıl, Mehmet Ali and Dede, Dila and Seçilmis, Adildabay and Catalkaya, Gizem and Shaker, Ata and Capanoglu, Esra and Ergen, Onur, Instant Olive Oil Quality Detection and Rapid Food Evaluation: A User-Friendly and Attractive Artificial Intelligence Solution. Available at SSRN: https://ssrn.com/abstract=4720565 or http://dx.doi.org/10.2139/ssrn.4720565

Mehmet Ali Sarsıl

Istanbul Technical University ( email )

Ayazaga Kampusu
Fen Edebiyat Fakultesi
İstanbul
Turkey

Dila Dede

Istanbul University ( email )

34459 Istanbul
Turkey

Adildabay Seçilmis

Istanbul Technical University ( email )

Ayazaga Kampusu
Fen Edebiyat Fakultesi
İstanbul
Turkey

Gizem Catalkaya

Istanbul Technical University ( email )

Ayazaga Kampusu
Fen Edebiyat Fakultesi
İstanbul
Turkey

Ata Shaker

Istanbul Technical University ( email )

Ayazaga Kampusu
Fen Edebiyat Fakultesi
İstanbul
Turkey

Esra Capanoglu

Istanbul Technical University - Department of Food Engineering ( email )

Onur Ergen (Contact Author)

University of California, Berkeley ( email )

CA
United States

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