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Titel: Using Human Assessment and GC-MS to Identify Potential Use Cases for Evaluating Food Condition with Gas Sensor Systems
VerfasserIn: Joppich, Julian
Schütze, Andreas
Bur, Christian
Sprache: Englisch
Titel: Chemosensors
Bandnummer: 14
Heft: 3
Verlag/Plattform: MDPI
Erscheinungsjahr: 2026
Freie Schlagwörter: gas sensors
food
fruits
spoilage
mold
damage
human assessment
odor
gas chromatography
mass spectrometry
DDC-Sachgruppe: 500 Naturwissenschaften
Dokumenttyp: Journalartikel / Zeitschriftenartikel
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 der Erstveröffentlichung: 10.3390/chemosensors14030073
URL der Erstveröffentlichung: https://doi.org/10.3390/chemosensors14030073
Link zu diesem Datensatz: urn:nbn:de:bsz:291--ds-474001
hdl:20.500.11880/41478
http://dx.doi.org/10.22028/D291-47400
ISSN: 2227-9040
Datum des Eintrags: 1-Apr-2026
Fakultät: NT - Naturwissenschaftlich- Technische Fakultät
Fachrichtung: NT - Systems Engineering
Professur: NT - Prof. Dr. Andreas Schütze
Sammlung:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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