ArticleFoods (Basel, Switzerland)2020
An Artificial Intelligence Approach for Italian EVOO Origin Traceability through an Open Source IoT Spectrometer.
Article in Foods (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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Who cites it
5 citing papers in PubMed.
- Traceability and Anti-Counterfeiting in Agri-Food Supply Chains: A Review of RFID, IoT, Blockchain, and AI Technologies.Sensors (Basel, Switzerland) · 2026Review
- Olive Fruit Selection through AI Algorithms and RGB Imaging.Foods (Basel, Switzerland) · 2022Article
- Integration of Innovative Technologies in the Agri-Food Sector: The Fundamentals and Practical Case of DNA-Based Traceability of Olives from Fruit to Oil.Plants (Basel, Switzerland) · 2022Review
- Extra Virgin Olive Oil (EVOO): Quality, Safety, Authenticity, and Adulteration.Foods (Basel, Switzerland) · 2021Article
- An Automated Pipeline for Image Processing and Data Treatment to Track Activity Rhythms ofSensors (Basel, Switzerland) · 2020Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Extra virgin olive oil (EVOO) represents a crucial ingredient of the Mediterranean diet. Being a first-choice product, consumers should be guaranteed its quality and geographical origin, justifying the high purchasing cost. For this reason, it is important to have new reliable tools able to classify products according to their geographical origin. The aim of this work was to demonstrate the efficiency of an open source visible and near infra-red (VIS-NIR) spectrophotometer, relying on a specific app, in assessing olive oil geographical origin. Thus, 67 Italian and 25 foreign EVOO samples were analyzed and their spectral data were processed through an artificial intelligence algorithm. The multivariate analysis of variance (MANOVA) results reported significant differences (
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Registered trials
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