Please use this identifier to cite or link to this item: doi:10.22028/D291-47400
Title: Using Human Assessment and GC-MS to Identify Potential Use Cases for Evaluating Food Condition with Gas Sensor Systems
Author(s): Joppich, Julian
Schütze, Andreas
Bur, Christian
Language: English
Title: Chemosensors
Volume: 14
Issue: 3
Publisher/Platform: MDPI
Year of Publication: 2026
Free key words: gas sensors
food
fruits
spoilage
mold
damage
human assessment
odor
gas chromatography
mass spectrometry
DDC notations: 500 Science
Publikation type: Journal Article
Abstract: Technological solutions might be of great importance for reducing food waste. In the scope of this article, gas sensor systems for assessing the edibility of food have been studied, which can help to avoid food losses by suggesting consumption before spoilage or by separating infected fruits from fresh ones. Several series of measurements with various foodstuffs were conducted to develop methods that enable the identification of possible use cases in which gas sensors could be used to assess food condition as well as methods to calibrate such sensor systems. This paper presents results for oranges as an important target for grocery stores. The fruit headspace was measured by gas sensors, reference data were acquired using human assessment (appearance, odor, edibility) and gas chromatography–massspectrometry(GC-MS)analysis. Dataevaluationshowscorrelations between the performance of individual sensors for a technical assessment of fruit condition with marker substances identified by GC-MS, e.g., limonene for damaged oranges. Models were derived that are, in general, able to quantify the edibility or to classify defects/mold, but limitations in the applicability/transferability, e.g., between orange varieties, were also identified. With the knowledge gained, important steps could be taken towards an application-oriented setup, and recommendations regarding the sensors used, food trained, and calibration methods applied are derived.
DOI of the first publication: 10.3390/chemosensors14030073
URL of the first publication: https://doi.org/10.3390/chemosensors14030073
Link to this record: urn:nbn:de:bsz:291--ds-474001
hdl:20.500.11880/41478
http://dx.doi.org/10.22028/D291-47400
ISSN: 2227-9040
Date of registration: 1-Apr-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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