Electronic Noses and Tongues: Applications for the Food and Pharmaceutical Industries
The electronic nose (e-nose) is designed to crudely mimic the mammalian nose in that most contain sensors that non-selectively interact with odor molecules to produce some sort of signal that is then sent to a computer that uses multivariate statistics to determine patterns in the data. This pattern...
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Online Access: | http://www.mdpi.com/1424-8220/11/5/4744/ |
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doaj-8ac4d4fe7a144c7094d56a066e2cb91f2020-11-25T00:39:45ZengMDPI AGSensors1424-82202011-05-011154744476610.3390/s110504744Electronic Noses and Tongues: Applications for the Food and Pharmaceutical IndustriesSharon DeaAnne PlottoElizabeth A. BaldwinJinhe BaiThe electronic nose (e-nose) is designed to crudely mimic the mammalian nose in that most contain sensors that non-selectively interact with odor molecules to produce some sort of signal that is then sent to a computer that uses multivariate statistics to determine patterns in the data. This pattern recognition is used to determine that one sample is similar or different from another based on headspace volatiles. There are different types of e-nose sensors including organic polymers, metal oxides, quartz crystal microbalance and even gas-chromatography (GC) or combined with mass spectroscopy (MS) can be used in a non-selective manner using chemical mass or patterns from a short GC column as an e-nose or “Z” nose. The electronic tongue reacts similarly to non-volatile compounds in a liquid. This review will concentrate on applications of e-nose and e-tongue technology for edible products and pharmaceutical uses.http://www.mdpi.com/1424-8220/11/5/4744/biosensorschemical sensorsmultivariate statisticsneural networkspattern recognitiongas chromatographymass spectroscopyliquid chromatographysensoryflavorshelf life |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Sharon Dea Anne Plotto Elizabeth A. Baldwin Jinhe Bai |
spellingShingle |
Sharon Dea Anne Plotto Elizabeth A. Baldwin Jinhe Bai Electronic Noses and Tongues: Applications for the Food and Pharmaceutical Industries Sensors biosensors chemical sensors multivariate statistics neural networks pattern recognition gas chromatography mass spectroscopy liquid chromatography sensory flavor shelf life |
author_facet |
Sharon Dea Anne Plotto Elizabeth A. Baldwin Jinhe Bai |
author_sort |
Sharon Dea |
title |
Electronic Noses and Tongues: Applications for the Food and Pharmaceutical Industries |
title_short |
Electronic Noses and Tongues: Applications for the Food and Pharmaceutical Industries |
title_full |
Electronic Noses and Tongues: Applications for the Food and Pharmaceutical Industries |
title_fullStr |
Electronic Noses and Tongues: Applications for the Food and Pharmaceutical Industries |
title_full_unstemmed |
Electronic Noses and Tongues: Applications for the Food and Pharmaceutical Industries |
title_sort |
electronic noses and tongues: applications for the food and pharmaceutical industries |
publisher |
MDPI AG |
series |
Sensors |
issn |
1424-8220 |
publishDate |
2011-05-01 |
description |
The electronic nose (e-nose) is designed to crudely mimic the mammalian nose in that most contain sensors that non-selectively interact with odor molecules to produce some sort of signal that is then sent to a computer that uses multivariate statistics to determine patterns in the data. This pattern recognition is used to determine that one sample is similar or different from another based on headspace volatiles. There are different types of e-nose sensors including organic polymers, metal oxides, quartz crystal microbalance and even gas-chromatography (GC) or combined with mass spectroscopy (MS) can be used in a non-selective manner using chemical mass or patterns from a short GC column as an e-nose or “Z” nose. The electronic tongue reacts similarly to non-volatile compounds in a liquid. This review will concentrate on applications of e-nose and e-tongue technology for edible products and pharmaceutical uses. |
topic |
biosensors chemical sensors multivariate statistics neural networks pattern recognition gas chromatography mass spectroscopy liquid chromatography sensory flavor shelf life |
url |
http://www.mdpi.com/1424-8220/11/5/4744/ |
work_keys_str_mv |
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