Application of compressed sensing for selecting relevant variables for a model to predict the quality of Japanese fermented soy sauce-Reference-Cited by-同舟云学术

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Application of compressed sensing for selecting relevant variables for a model to predict the quality of Japanese fermented soy sauce

Published:2020-01 Issue: Volume:59 Page:102241
ISSN:1466-8564
Container-title:Innovative Food Science & Emerging Technologies
language:en
Short-container-title:Innovative Food Science & Emerging Technologies

Author:

Wang Shuo,Liu Beiyi,Xu Li,Tamura Takehiro,Kyouno Nobuyuki,Liu Xiaofang,Zhang Han,Akiyama Yoshinobu,Chen Jie Yu

Publisher

Elsevier BV

Subject

Industrial and Manufacturing Engineering,General Chemistry,Food Science

Reference29 articles.

1. Partial least squares regression and projection on latent structure regression (PLS regression);Abdi;Wiley Interdisciplinary Reviews: Computational Statistics,2010

2. Flavour evaluation by multiple regression analysis of gas chromatographic patterns in soy sauce;Aishima;Food Chemistry,1977

3. Statistical inference;Berger,2001

4. Chapter 15 - condiments and sauces;Chavasit,2018

5. Characteristics of fermented seasoning sauces using Tenebrio molitor larvae;Cho;Innovative Food Science & Emerging Technologies,2018

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Effect of Tetragenococcus halophilus, Zygosaccharomyces rouxii, and Torulopsis versatilis addition sequence on soy sauce fermentation;Innovative Food Science & Emerging Technologies;2021-05

2. 令和2年における醤油の研究業績;JOURNAL OF THE BREWING SOCIETY OF JAPAN;2021

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