Prediction of flavor and retention index for compounds in beer depending on molecular structure using a machine learning method-Reference-Cited by-同舟云学术

Prediction of flavor and retention index for compounds in beer depending on molecular structure using a machine learning method

Published:2021 Issue:58 Volume:11 Page:36942-36950
ISSN:2046-2069
Container-title:RSC Advances
language:en
Short-container-title:RSC Adv.

Author:

Wang Yu-Tang¹²,Yang Zhao-Xia³,Piao Zan-Hao¹²,Xu Xiao-Juan¹²,Yu Jun-Hong³,Zhang Ying-Hua¹²^ORCID

Affiliation:

1. Department of Food Science, Northeast Agricultural University, Harbin 150030, PR China

2. Key Laboratory of Dairy Science, Ministry of Education, Northeast Agricultural University, China

3. State Key Laboratory of Biological Fermentation Engineering of Beer, Tsingtao Brewery Co., Ltd, Qingdao, 266061, Shandong, China

Abstract

In order to make a preliminary prediction of flavor and retention index (RI) for compounds in beer, this work applied the machine learning method to modeling depending on molecular structure.

Funder

State Key Lab of Biological Fermentation Engineering of Beer, Tsingtao Brewery Co. Ltd.

Publisher

Royal Society of Chemistry (RSC)

Subject

General Chemical Engineering,General Chemistry

Link

http://pubs.rsc.org/en/content/articlepdf/2021/RA/D1RA06551C

Reference46 articles.

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3. Bitter or not? BitterPredict, a tool for predicting taste from chemical structure

4. Luminescence Properties of Self-Aggregating TbIII-DOTA-Functionalized Calix[4]arenes

5. Gas-chromatographische Charakterisierung organischer Verbindungen. Teil 1: Retentionsindices aliphatischer Halogenide, Alkohole, Aldehyde und Ketone

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