Temperature control of Ginjo sake mashing process by automatic fuzzy modeling using fuzzy neural networks

Hiroyuki Honda, Taizo Hanai, Akemi Katayama, Hisao Tohyama, Takeshi Kobayashi

Research output: Contribution to journalArticle

30 Citations (Scopus)

Abstract

Automatic fuzzy modeling using fuzzy neural network (FNN) was attempted for use for temperature control of Ginjo sake mashing process. Data for 25 Ginjo sake mashings obtained from a commercial fermentor were used for the modeling. Models were constructed in four control regions. The acquired models could precisely output a set temperature, and the acquired rules coincided well with those experiences of Toji. The models were applied to temperature control of commercial scale mashing. Time course data were similar to those from a conventional control based on the decision of Toji. The Ginjo sake obtained was analyzed and quality assessed by expert sensory evaluation. The concentrations of chemical components and evaluation scores were confirmed to be similar to those obtained from the conventional control.

Original languageEnglish
Pages (from-to)107-112
Number of pages6
JournalJournal of Fermentation and Bioengineering
Volume85
Issue number1
DOIs
Publication statusPublished - Jan 1 1998
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Biotechnology
  • Applied Microbiology and Biotechnology

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