Statistical Optimization of Culture Conditions for Enhanced Biomass Yield of Lactobacillus acidophilus CM1 Using Plackett-Burman and Response Surface Methodology

利用Plackett-Burman法和响应面法对嗜酸乳杆菌CM1的培养条件进行统计优化以提高生物量产量

阅读:1

Abstract

This study is aimed at enhancing the biomass yield of Lactobacillus acidophilus CM1 by identifying and optimizing critical growth parameters. Using the Plackett-Burman design (PBD), 11 physical and chemical variables were screened, of which pH, temperature, NaCl concentration, and inoculum size were found to significantly influence cell growth (p < 0.05). These statistically significant factors were subsequently optimized using response surface methodology (RSM) with a central composite design (CCD). Optimization led to a 1.45-fold increase in biomass yield, achieving a maximum of 1.948 g/100 mL. ANOVA confirmed model validity with an R (2) of 0.9689 and adequate precision of 52.77, indicating a strong predictive capability. The integration of PBD and RSM-CCD proved efficient for minimizing experimental runs while maximizing output, supporting the development of cost-effective cultivation strategies for probiotic production. This approach offers a scalable model for bioprocess optimization in industrial fermentation.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。