ArticleBiosensors2020
An Array of MOX Sensors and ANNs to Assess Grated Parmigiano Reggiano Cheese Packs' Compliance with CFPR Guidelines.
Article in Biosensors, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed.
- Nano-Tailored Triple Gas Sensor for Real-Time Monitoring of Dough Preparation in Kitchen Machines.Sensors (Basel, Switzerland) · 2025Article
- Unraveling the Chicken Meat Volatilome with Nanostructured Sensors: Impact of Live and Dehydrated Insect Larvae Feeding.Sensors (Basel, Switzerland) · 2024Article
- Applications of Gas Sensing in Food Quality Detection: A Review.Foods (Basel, Switzerland) · 2023Review
- Characterization of the Response of Magnetron Sputtered InSensors (Basel, Switzerland) · 2023Article
- Electrically Transduced Gas Sensors Based on Semiconducting Metal Oxide Nanowires.Sensors (Basel, Switzerland) · 2020Review
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Parmigiano Reggiano cheese is one of the most appreciated Italian foods on account of its high nutrient content and taste. Due to its high cost, these characteristics make this product subject to counterfeiting in different forms. In this study, an approach based on an array of gas sensors has been employed to assess if it was possible to distinguish different samples based on their aroma. Samples were characterized in terms of rind percentage, seasoning, and rind working process. From the responses of the sensors, five features were extracted and the capability of these parameters to recognize target classes was tested with statistical analysis. Hence, the performance of the sensors' array was quantified using artificial neural networks. To simplify the problem, a hierarchical approach has been used: three steps of classification were performed, and in each step one parameter of the grated cheese was identified (firstly, seasoning; secondly, rind working process; finally, rind percentage). The accuracies ranged from 88.24% to 100%.
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Registered trials
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