Assessment of Cooked Meatballs’ Edibility Using Calibrated MOS Sensors and Microbiological Validation

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.

Authors

Institutions

Publication Details

Journal
Chemosensors
Published
2026-06-30
DOI
https://doi.org/10.3390/chemosensors14070148
Primary Topic
Advanced Chemical Sensor Technologies
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Assessment of Cooked Meatballs’ Edibility Using Calibrated MOS Sensors and Microbiological Validation

Rafael Pagán, Andreas Schütze, Christian Bur, D. García-Romeo et al.
Chemosensors
Advanced Chemical Sensor Technologies
article

Assessment of Cooked Meatballs’ Edibility Using Calibrated MOS Sensors and Microbiological Validation

Rafael Pagán, Andreas Schütze, Christian Bur, D. García-Romeo, Revathy Gurusamy, Luigi Masi
article en

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.

ChemosensorsVol. 14(7)
Universidad de Zaragoza (ES), Centro de Investigación y Tecnología Agroalimentaria de Aragón (ES), BSH Electrodomésticos (Spain) (ES), Saarland University (DE)
European Commission
Responsible consumption and production
Openalex Percentile: Top 13%
Advanced Chemical Sensor Technologies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.