Optimization of biocatalytic production of sodium gluconate using a dual-enzyme system

Sodium gluconate has a wide range of applications, including in the fields of construction, textiles, medicine, the chemical industry, and food, so the industrialized production of sodium gluconate is particularly important. However, the preparation process of sodium gluconate is not mature enough, and the production cost is high, which restricts the development of the industry. In this study, the optimization of process conditions for the catalytic production of sodium gluconate from glucose via a dual-enzyme system of glucose oxidase (GOD) and catalase (CAT) was investigated in detail. Factors such as pH, temperature, metal ions, enzyme addition, stirring speed, and aeration were examined. After optimizing these parameters through one-way experiments, the Box-Behnken design (BBD) was employed to refine the process further, focusing on stirring speed, enzyme addition, and aeration. The optimal reaction conditions were identified as follows: a reaction pH of 5.9, a reaction temperature of 38°C, enzyme addition of 0.2%, batch addition, 80% GOD at 0 h, 20% GOD at 2 h, stirring speed of 700 rpm, aeration amount of 1.2 vvm, and a tank pressure of 0.04 Pa. Under these conditions, the reaction cycle for sodium gluconate production was reduced to 7.75 ± 0.5 h. These optimized conditions significantly improve existing methods, offering a more efficient and cost-effective approach to sodium gluconate production. The findings provide valuable insights for scaling up biocatalytic processes, with the potential for a substantial industrial impact, particularly in reducing production costs and improving sustainability in the chemical and food industries.

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Publication Details

Journal
Frontiers in Bioengineering and Biotechnology
Published
2025-08-18
DOI
https://doi.org/10.3389/fbioe.2025.1607782
Primary Topic
Electrochemical sensors and biosensors
Type
article
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article

Optimization of biocatalytic production of sodium gluconate using a dual-enzyme system

Piwu Li, Chuanzhuang Guo, Jingli Ren, Xia Li et al.
Frontiers in Bioengineering and Biotechnology
Electrochemical sensors and biosensors
article

Optimization of biocatalytic production of sodium gluconate using a dual-enzyme system

Piwu Li, Chuanzhuang Guo, Jingli Ren, Xia Li, Junqing Wang, Xiaofeng Wei, Keyi Liu
article en

Abstract

Sodium gluconate has a wide range of applications, including in the fields of construction, textiles, medicine, the chemical industry, and food, so the industrialized production of sodium gluconate is particularly important. However, the preparation process of sodium gluconate is not mature enough, and the production cost is high, which restricts the development of the industry. In this study, the optimization of process conditions for the catalytic production of sodium gluconate from glucose via a dual-enzyme system of glucose oxidase (GOD) and catalase (CAT) was investigated in detail. Factors such as pH, temperature, metal ions, enzyme addition, stirring speed, and aeration were examined. After optimizing these parameters through one-way experiments, the Box-Behnken design (BBD) was employed to refine the process further, focusing on stirring speed, enzyme addition, and aeration. The optimal reaction conditions were identified as follows: a reaction pH of 5.9, a reaction temperature of 38°C, enzyme addition of 0.2%, batch addition, 80% GOD at 0 h, 20% GOD at 2 h, stirring speed of 700 rpm, aeration amount of 1.2 vvm, and a tank pressure of 0.04 Pa. Under these conditions, the reaction cycle for sodium gluconate production was reduced to 7.75 ± 0.5 h. These optimized conditions significantly improve existing methods, offering a more efficient and cost-effective approach to sodium gluconate production. The findings provide valuable insights for scaling up biocatalytic processes, with the potential for a substantial industrial impact, particularly in reducing production costs and improving sustainability in the chemical and food industries.

Frontiers in Bioengineering and BiotechnologyVol. 13
Qilu University of Technology (CN), Yebio Bioengineering (China) (CN)
Openalex Percentile: Top 80%
Electrochemical sensors and biosensors
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