Please use this identifier to cite or link to this item: doi:10.22028/D291-48367
Title: Assessment of Cooked Meatballs’ Edibility Using Calibrated MOS Sensors and Microbiological Validation
Author(s): Masi, Luigi
Gurusamy, Revathy
Garcia-Romeo, Daniel
Schütze, Andreas
Pagán, Rafael
Bur, Christian
Language: English
Title: Chemosensors
Volume: 14
Issue: 7
Publisher/Platform: MDPI
Year of Publication: 2026
Free key words: gas sensors
MOS sensors
cooked food
edibility
temperature-cycled operation
food freshness monitoring
microbiological validation
sensor calibration
DDC notations: 500 Science
Publikation type: Journal Article
Abstract: Food waste is often driven by consumer uncertainty about the spoilage of stored food, especially for cooked meal leftovers where microbial growth is the main concern. We analyzed whether metal oxide semiconductor (MOS) gas sensors placed inside ordinary food containers can monitor the edibility of leftovers, specifically cooked meatballs. Sensors were operated using temperature cycling to enhance selectivity, and cycle-aligned features were extracted. A prior calibration campaign produced information used to map cycle-aligned features into estimated gas concentrations for relevant VOCs. Total viable counts, which represent the growth of total number of spoilage microorganisms, were analyzed on days 0, 5 and 7 to determine the food’s freshness. Both the raw sensor features and the calibration-derived gas concentration estimates were analyzed with principal component analysis (PCA) and evaluated with a leave-one-sensor-out (LOSO) binary classifier for multiple food containers. PCA on the calibrated gas estimates revealed a dominant axis that consistently tracks food degradation over time across various containers. LOSO classification accuracy improved from 81.7% using raw sensor features to 87.8% using calibrated gas concentration estimates. These findings represent a proof of principle that calibrated MOS sensor systems can robustly support in situ edibility assessment for cooked food.
DOI of the first publication: 10.3390/chemosensors14070148
URL of the first publication: https://doi.org/10.3390/chemosensors14070148
Link to this record: urn:nbn:de:bsz:291--ds-483675
hdl:20.500.11880/42293
http://dx.doi.org/10.22028/D291-48367
ISSN: 2227-9040
Date of registration: 28-Jul-2026
Faculty: NT - Naturwissenschaftlich- Technische Fakultät
Department: NT - Systems Engineering
Professorship: NT - Prof. Dr. Andreas Schütze
Collections:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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