Medium optimization for glutathione production by Saccharomyces cerevisiae

Chi Hsien Liu; Chin Fa Hwang; Chii Cherng Liao

doi:10.1016/S0032-9592(98)00055-7

Medium optimization for glutathione production by Saccharomyces cerevisiae

Chi Hsien Liu, Chin Fa Hwang, Chii Cherng Liao^*

^*Corresponding author for this work

Food Indust. Research Devmt. I.

Research output: Contribution to journal › Journal Article › peer-review

54 Scopus citations

Abstract

Glucose, peptone and magnesium sulphate were found to be suitable components for the cell growth and glutathione (GSH) production in the yeast strain. Saccharomyces cerevisiae CCRC 21727. The Box-Behnken design and response surface methodology were employed to derive a statistical model to investigate the effects of glucose, peptone and magnesium sulphate concentrations on GSH production. Neural networks were compared with a second-order-polynomial model in predicting the effects of component concentrations on the production of GSH and dry cell weight (DCW). Neural network models can predict cell growth and GSH production more precisely than second-order-response-surface models.

Original language	English
Pages (from-to)	17-23
Number of pages	7
Journal	Process Biochemistry
Volume	34
Issue number	1
DOIs	https://doi.org/10.1016/S0032-9592(98)00055-7
State	Published - 01 01 1999
Externally published	Yes

Keywords

Glutathione
Medium optimization
Neural network prediction
Response- surface model

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10.1016/S0032-9592(98)00055-7

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title = "Medium optimization for glutathione production by Saccharomyces cerevisiae",

abstract = "Glucose, peptone and magnesium sulphate were found to be suitable components for the cell growth and glutathione (GSH) production in the yeast strain. Saccharomyces cerevisiae CCRC 21727. The Box-Behnken design and response surface methodology were employed to derive a statistical model to investigate the effects of glucose, peptone and magnesium sulphate concentrations on GSH production. Neural networks were compared with a second-order-polynomial model in predicting the effects of component concentrations on the production of GSH and dry cell weight (DCW). Neural network models can predict cell growth and GSH production more precisely than second-order-response-surface models.",

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T1 - Medium optimization for glutathione production by Saccharomyces cerevisiae

AU - Liu, Chi Hsien

AU - Hwang, Chin Fa

AU - Liao, Chii Cherng

PY - 1999/1/1

Y1 - 1999/1/1

N2 - Glucose, peptone and magnesium sulphate were found to be suitable components for the cell growth and glutathione (GSH) production in the yeast strain. Saccharomyces cerevisiae CCRC 21727. The Box-Behnken design and response surface methodology were employed to derive a statistical model to investigate the effects of glucose, peptone and magnesium sulphate concentrations on GSH production. Neural networks were compared with a second-order-polynomial model in predicting the effects of component concentrations on the production of GSH and dry cell weight (DCW). Neural network models can predict cell growth and GSH production more precisely than second-order-response-surface models.

AB - Glucose, peptone and magnesium sulphate were found to be suitable components for the cell growth and glutathione (GSH) production in the yeast strain. Saccharomyces cerevisiae CCRC 21727. The Box-Behnken design and response surface methodology were employed to derive a statistical model to investigate the effects of glucose, peptone and magnesium sulphate concentrations on GSH production. Neural networks were compared with a second-order-polynomial model in predicting the effects of component concentrations on the production of GSH and dry cell weight (DCW). Neural network models can predict cell growth and GSH production more precisely than second-order-response-surface models.

KW - Glutathione

KW - Medium optimization

KW - Neural network prediction

KW - Response- surface model

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M3 - 文章

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SN - 1359-5113

VL - 34

SP - 17

EP - 23

JO - Process Biochemistry

JF - Process Biochemistry

IS - 1

ER -

Medium optimization for glutathione production by Saccharomyces cerevisiae

Abstract

Keywords

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