Instant Olive Oil Quality Detection and Rapid Food Evaluation: A User-Friendly and Attractive Artificial Intelligence Solution
10 Pages Posted: 13 Feb 2024
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
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