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Key Indicators for the Discrimination of Wines by Electronic Noses
In the food industry, and especially in wines as products thereof, ethanol and sulfur dioxide play an equally important role. Both substances are important wine quality characteristics as they influence the taste and odor. As both substances comprise volatile matter, electronic noses should be appli...
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creator | Wotner, Julius Dorksen, Helene Pein-Hackelbusch, Miriam |
description | In the food industry, and especially in wines as products thereof, ethanol and sulfur dioxide play an equally important role. Both substances are important wine quality characteristics as they influence the taste and odor. As both substances comprise volatile matter, electronic noses should be applicable to discriminate the different qualities of wines. Our study investigates the influence of alcohol and sulfur dioxide on the discrimination ability of wines (especially those of the same grape variety) using two different electronic nose systems. One system is equipped with metal oxide sensors and the other with quartz crystal microbalance sensors. Contrary to indications in literature, where the alcohol content is discussed to have a large influence on e-nose results, it was shown that a difference of 1 % ethanol was not sufficient to allow accurate discrimination using Linear Discriminant Analysis by any system. On the positive side, the analyzed concentrations of ethanol (about 12 %) did not superimpose other volatile information. So difference in sulfur dioxide content gave an accuracy for sample discrimination of up to 90.6 % with MOS nose. Thus, we are so far partially able to discriminate wines with electronic noses based on their volatile imprint. |
doi_str_mv | 10.1109/INDIN51400.2023.10217912 |
format | conference_proceeding |
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Both substances are important wine quality characteristics as they influence the taste and odor. As both substances comprise volatile matter, electronic noses should be applicable to discriminate the different qualities of wines. Our study investigates the influence of alcohol and sulfur dioxide on the discrimination ability of wines (especially those of the same grape variety) using two different electronic nose systems. One system is equipped with metal oxide sensors and the other with quartz crystal microbalance sensors. Contrary to indications in literature, where the alcohol content is discussed to have a large influence on e-nose results, it was shown that a difference of 1 % ethanol was not sufficient to allow accurate discrimination using Linear Discriminant Analysis by any system. On the positive side, the analyzed concentrations of ethanol (about 12 %) did not superimpose other volatile information. So difference in sulfur dioxide content gave an accuracy for sample discrimination of up to 90.6 % with MOS nose. Thus, we are so far partially able to discriminate wines with electronic noses based on their volatile imprint.</description><identifier>EISSN: 2378-363X</identifier><identifier>EISBN: 9781665493130</identifier><identifier>EISBN: 1665493135</identifier><identifier>DOI: 10.1109/INDIN51400.2023.10217912</identifier><language>eng</language><publisher>IEEE</publisher><subject>Electronic noses ; Ethanol ; machine learning ; Metals ; Nose ; Pipelines ; Sensor systems ; Sensors ; Souvignier-Gris ; sulfur dioxide</subject><ispartof>2023 IEEE 21st International Conference on Industrial Informatics (INDIN), 2023, p.1-7</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/10217912$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,777,781,786,787,27906,54536,54913</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/10217912$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Wotner, Julius</creatorcontrib><creatorcontrib>Dorksen, Helene</creatorcontrib><creatorcontrib>Pein-Hackelbusch, Miriam</creatorcontrib><title>Key Indicators for the Discrimination of Wines by Electronic Noses</title><title>2023 IEEE 21st International Conference on Industrial Informatics (INDIN)</title><addtitle>INDIN</addtitle><description>In the food industry, and especially in wines as products thereof, ethanol and sulfur dioxide play an equally important role. Both substances are important wine quality characteristics as they influence the taste and odor. As both substances comprise volatile matter, electronic noses should be applicable to discriminate the different qualities of wines. Our study investigates the influence of alcohol and sulfur dioxide on the discrimination ability of wines (especially those of the same grape variety) using two different electronic nose systems. One system is equipped with metal oxide sensors and the other with quartz crystal microbalance sensors. Contrary to indications in literature, where the alcohol content is discussed to have a large influence on e-nose results, it was shown that a difference of 1 % ethanol was not sufficient to allow accurate discrimination using Linear Discriminant Analysis by any system. On the positive side, the analyzed concentrations of ethanol (about 12 %) did not superimpose other volatile information. So difference in sulfur dioxide content gave an accuracy for sample discrimination of up to 90.6 % with MOS nose. Thus, we are so far partially able to discriminate wines with electronic noses based on their volatile imprint.</description><subject>Electronic noses</subject><subject>Ethanol</subject><subject>machine learning</subject><subject>Metals</subject><subject>Nose</subject><subject>Pipelines</subject><subject>Sensor systems</subject><subject>Sensors</subject><subject>Souvignier-Gris</subject><subject>sulfur dioxide</subject><issn>2378-363X</issn><isbn>9781665493130</isbn><isbn>1665493135</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2023</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNo1j7FOwzAURQ0SEqX0Dxj8Awnv-cV2PEJbSkQVFhBslePYwqjEKM6Sv6cSMN3pHJ3LGEcoEcHcNu2maSVWAKUAQSWCQG1QnLGV0TUqJStDSHDOFoJ0XZCi90t2lfMngDxxasHun_zMm6GPzk5pzDykkU8fnm9idmP8ioOdYhp4CvwtDj7zbubbo3fTmIboeJuyz9fsIthj9qu_XbLXh-3L-rHYP--a9d2-iAKqqXBWKqcC9dQZGTrsCIOW3sIptfZ1IIcBrAcwDpUzndbWSeiN7oQ2Tgtasptfb_TeH75PdXacD_-f6Qdr-EwA</recordid><startdate>20230718</startdate><enddate>20230718</enddate><creator>Wotner, Julius</creator><creator>Dorksen, Helene</creator><creator>Pein-Hackelbusch, Miriam</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>20230718</creationdate><title>Key Indicators for the Discrimination of Wines by Electronic Noses</title><author>Wotner, Julius ; Dorksen, Helene ; Pein-Hackelbusch, Miriam</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i204t-ca56c6f3d3b95fb1b31f75ea09788e8f3c1f0ae009c16c9b77ac50d97b279c723</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Electronic noses</topic><topic>Ethanol</topic><topic>machine learning</topic><topic>Metals</topic><topic>Nose</topic><topic>Pipelines</topic><topic>Sensor systems</topic><topic>Sensors</topic><topic>Souvignier-Gris</topic><topic>sulfur dioxide</topic><toplevel>online_resources</toplevel><creatorcontrib>Wotner, Julius</creatorcontrib><creatorcontrib>Dorksen, Helene</creatorcontrib><creatorcontrib>Pein-Hackelbusch, Miriam</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Xplore (Online service)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Wotner, Julius</au><au>Dorksen, Helene</au><au>Pein-Hackelbusch, Miriam</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Key Indicators for the Discrimination of Wines by Electronic Noses</atitle><btitle>2023 IEEE 21st International Conference on Industrial Informatics (INDIN)</btitle><stitle>INDIN</stitle><date>2023-07-18</date><risdate>2023</risdate><spage>1</spage><epage>7</epage><pages>1-7</pages><eissn>2378-363X</eissn><eisbn>9781665493130</eisbn><eisbn>1665493135</eisbn><abstract>In the food industry, and especially in wines as products thereof, ethanol and sulfur dioxide play an equally important role. Both substances are important wine quality characteristics as they influence the taste and odor. As both substances comprise volatile matter, electronic noses should be applicable to discriminate the different qualities of wines. Our study investigates the influence of alcohol and sulfur dioxide on the discrimination ability of wines (especially those of the same grape variety) using two different electronic nose systems. One system is equipped with metal oxide sensors and the other with quartz crystal microbalance sensors. Contrary to indications in literature, where the alcohol content is discussed to have a large influence on e-nose results, it was shown that a difference of 1 % ethanol was not sufficient to allow accurate discrimination using Linear Discriminant Analysis by any system. On the positive side, the analyzed concentrations of ethanol (about 12 %) did not superimpose other volatile information. So difference in sulfur dioxide content gave an accuracy for sample discrimination of up to 90.6 % with MOS nose. Thus, we are so far partially able to discriminate wines with electronic noses based on their volatile imprint.</abstract><pub>IEEE</pub><doi>10.1109/INDIN51400.2023.10217912</doi><tpages>7</tpages></addata></record> |
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issn | 2378-363X |
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subjects | Electronic noses Ethanol machine learning Metals Nose Pipelines Sensor systems Sensors Souvignier-Gris sulfur dioxide |
title | Key Indicators for the Discrimination of Wines by Electronic Noses |
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