在发酵中使用紫外线可见光谱和部分最小平方回归方法快速量化pullulan
Nageswar Sahu1, Biswanath Mahanty1, Dibyajyoti Haldar1
1Division of Biotechnology, Karunya Institute of Technology and Sciences, Coimbatore-641114, Tamil Nadu, India. nageswarsahu@karunya.edu.in.
Analytical methods : advancing methods and applications
|March 20, 2025
概括
一种新的方法使用部分最小平方 (PLS) 回归来量化pullulan,一个生物聚合物,在发酵. 这种方法提供了快速,非破坏性的分析,克服了生物过程监测中的瓶.
科学领域:
- 生物技术是生物技术.
- 分析化学 分析化学
- 频谱学是一种光谱学.
背景情况:
- 传统的外聚糖 (EPS) 量化涉及漫长,多步骤的样本准备,阻碍实时生物过程监测.
- 开发具有最小样本准备的非破坏性分析方法对于高效的生物过程控制至关重要.
研究的目的:
- 开发和验证一种快速,非破坏性的方法,使用光谱数据量化发酵中的普鲁兰.
- 为了比较部分最小平方 (PLS) 回归模型的不同光谱区域选择策略.
主要方法:
- 使用光谱数据 (204-400 nm) 开发了部分最小平方 (PLS) 回归模型,以量化拉力.
- 优化策略包括遗传算法,粒子群优化,竞争性自适应重量化采样和自适应自下而上的太空探索,用于光谱区域选择.
- 模型使用交叉验证进行了验证,评估了诸如交叉验证的根平均平方误差 (RMSE_CV) 和R平方 (R_CV^2) 等指标.
主要成果:
- 在PLS回归模型中,成功量化了pullulan,无论是无细胞的超浮体形式还是重新溶解的沉形式.
- 没有细胞的全频谱模型表现出高准确度 (RMSE_CV:0.020 g l^-1,R_CV^2:0.997).
- 自适应自下而上的太空探索产生了最好的结果,实现了低RMSE_CV值,具有最小的光谱变量,适合实时监测.
结论:
- 开发的基于PLS的光谱方法为发酵中的pullulan量化提供了快速,非破坏性和准确的替代方案.
- 这种方法显著减少了样品准备时间,解决了生物过程监测中的一个关键瓶.
- 该方法的适应性表明,有可能实时监测和控制涉及类似生物聚合物的生物过程.
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