2009
DOI: 10.1016/j.jfoodeng.2008.11.002
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Preliminary study of ion mobility based electronic nose MGD-1 for discrimination of hard cheeses

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Cited by 40 publications
(20 citation statements)
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“…An ion-mobility based e-nose (MGD-1) was used to determine separation of hard and extra-hard cheese samples as well as discrimination of cheeses based on age (ripening time) or origin [53]. Ion mobility spectrometry (IMS) allows rapid on-site determination of volatiles by hand-held devices by ionization of gas molecules.…”
Section: E-nosesmentioning
confidence: 99%
“…An ion-mobility based e-nose (MGD-1) was used to determine separation of hard and extra-hard cheese samples as well as discrimination of cheeses based on age (ripening time) or origin [53]. Ion mobility spectrometry (IMS) allows rapid on-site determination of volatiles by hand-held devices by ionization of gas molecules.…”
Section: E-nosesmentioning
confidence: 99%
“…The most common application of IMS is the detection of explosives and chemical warfare agents . In addition, there is a wide variety of analytical purposes including pharmaceutical applications (quality control, cleaning verification, resolution of isomers), environmental applications (air quality, water and liquid samples, solids and aerosols), applications in the food and feed sector, biomedical and clinical analyses (biomarkers in breath, urine, blood and serum, lymph extracts). Since 1990, IMS is frequently applied in forensic analysis.…”
Section: Introductionmentioning
confidence: 99%
“…A group of samples within the blue cluster were more scattered, probably accounting for variation between the aroma compounds, ripening time, and geographical origin of the cheese samples [23,37]. Few samples were outside the cluster which could be minimized by improving the sensitivity of the sensors [38]. In general, the clusters related to the quality of cheese samples are well separated, so that it is possible to detect the headspace volatile components based on the classes of cheese with the application of S3.…”
Section: Discussionmentioning
confidence: 99%