过程理解和监测:对微型NIR光谱仪的数据策略进行一
Giulia Gorla1, Alberto Ferrer2, Barbara Giussani1
1Science and High Technology Department, Università degli Studi dell'Insubria, 22100, Como, Italy.
Analytica chimica acta
|May 24, 2024
概括
过程分析技术 (PAT) 能够实时监测发酵过程. 这项研究表明,小型近红外 (NIR) 光谱和统计分析如何识别工艺变化,并有助于监测开发酵.
科学领域:
- 生物技术是生物技术.
- 分析化学 分析化学
- 工艺工程的过程工程.
背景情况:
- 2004年FDA引入的过程分析技术 (PAT) 实施对制造商采用新监控系统提出了挑战.
- 关键的挑战包括传感器选择,数据解释,用于过程理解的统计策略评估和实际监测可行性.
- 由于其复杂的化学和物理转换与其他发酵过程相关,因此选择了酸奶发酵作为模型系统.
研究的目的:
- 通过手持近红外 (NIR) 数据提供对过程监控最佳实践的见解.
- 调查批量流程初步评估的关键方面,重点关注流程理解和监控能力.
- 探索实时过程监测和发酵中的终点确定的可能性.
主要方法:
- 使用小型的NIR (1350-2550nm) 光谱仪在开发酵过程中获取光谱数据.
- 使用各种统计工具从光谱数据中提取信息,并将其与过程变化相关联.
- 基于获得的光谱数据,研究了识别不同实验条件的策略.
主要成果:
- 展示了微型NIR光谱在发酵过程中代表各种实验条件的能力.
- 成功地运用统计策略来描述这些不同的情况.
- 确定了光谱数据,化学/物理变化和工艺变化之间的联系.
- 报告了在研究的NIR范围内的发酵特有的光谱特征.
结论:
- 验证了使用小型化的NIR光谱和统计方法来描述发酵条件.
- 强调了用于检测发酵变化的常见方法的优点和局限性.
- 探索了统计方法在发酵过程中的研究,开发,监测和终点检测方面的潜力.
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