{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T22:24:50Z","timestamp":1780352690691,"version":"3.54.1"},"reference-count":42,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2019,6,11]],"date-time":"2019-06-11T00:00:00Z","timestamp":1560211200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Due to the emergence of new microbreweries in the Brazilian market, there is a need to construct equipment to quickly and accurately identify the alcohol content in beverages, together with a reduced marketing cost. Towards this purpose, the electronic noses prove to be the most suitable equipment for this situation. In this work, a prototype was developed to detect the concentration of ethanol in a high spectrum of beers presents in the market. It was used cheap and easy-to-acquire 13 gas sensors made with a metal oxide semiconductor (MOS). Samples with 15 predetermined alcohol contents were used for the training and construction of the models. For validation, seven different commercial beverages were used. The correlation (R2) of 0.888 for the MLR (RMSE = 0.45) and the error of 5.47% for the ELM (RMSE = 0.33) demonstrate that the equipment can be an effective tool for detecting the levels of alcohol contained in beverages.<\/jats:p>","DOI":"10.3390\/s19112646","type":"journal-article","created":{"date-parts":[[2019,6,11]],"date-time":"2019-06-11T10:55:44Z","timestamp":1560250544000},"page":"2646","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":48,"title":["A Prototype to Detect the Alcohol Content of Beers Based on an Electronic Nose"],"prefix":"10.3390","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7534-3268","authenticated-orcid":false,"given":"Henike Guilherme Jordan","family":"Voss","sequence":"first","affiliation":[{"name":"Graduate Program in Applied Computing (PPGCA), State University of Ponta Grossa (UEPG), Ponta Grossa (PR) 84030-900, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jos\u00e9 Jair Alves","family":"Mendes J\u00fanior","sequence":"additional","affiliation":[{"name":"Graduate Program in Electrical Engineering and Industrial Informatics (CPGEI), Federal University of Technology of Parana (UTFPR), Curitiba (PR) 80230-901, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Murilo Eduardo","family":"Farinelli","sequence":"additional","affiliation":[{"name":"Graduate Program in Chemical Engineering, Federal University of Technology of Parana (UTFPR), Ponta Grossa (PR) 84016-210, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4783-5350","authenticated-orcid":false,"suffix":"Jr.","given":"Sergio Luiz","family":"Stevan","sequence":"additional","affiliation":[{"name":"Graduate Program in Applied Computing (PPGCA), State University of Ponta Grossa (UEPG), Ponta Grossa (PR) 84030-900, Brazil"},{"name":"Graduate Program in Electrical Engineering (PPGEE), Federal University of Technology of Parana (UTFPR), Ponta Grossa (PR) 84016-210, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2019,6,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Dorji, U., Pobkrut, T., and Kerdcharoen, T. 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