关键质量属性是根据NIR结合可变选择方法优化和NIR结合的烟雾固化烟草的确定
1Beijing Haiguang Instrument Co., Ltd, Beijing 101312, China. ligaowei13@163.com.
Analytical methods : advancing methods and applications
|October 8, 2025
概括
近红外 (NIR) 光谱学与新型变量选择算法 (SCRPA) 结合,准确量化烟雾制烟草中的关键质量成分. 这种方法可以在现场进行快速分析,以改善烟草资源管理.
科学领域:
- 农业科学 农业科学
- 分析化学 分析化学
- 频谱学是一种光谱学.
背景情况:
- 烟草的关键质量属性 (CQAs) 对烟草的整体质量产生重大影响.
- 需要准确和快速的方法来确定烟草中的总糖 (TS),减少糖 (RS) 和总 (TN).
研究的目的:
- 建立和优化TS,RS和TN的定量化模型. 在烟雾固化烟草中.
- 评估近红外 (NIR) 光谱学与可变选择方法相结合的疗效,特别是拟议的单一相关回归参数算法 (SCRPA).
主要方法:
- 使用NIR光谱学的量化模型的开发和优化.
- 应用变量选择方法,包括新的SCRPA,以提取信息特征.
- 使用RMSEP和偏差指标验证预测性能.
主要成果:
- 通过SCRPA方法,TS,RS和TN的预测性能得到了改善.
- 获得的RMSEP值为TS的0.4399%,RS的0.8733%,TN的0.0233%.
- 观察到的较小偏差值:TS为0.2234%,RS为0.9483%,TN为0.0227%.
结论:
- 与SCRPA相结合的NIR光谱法是监测烟草质量的有希望和有效的方法.
- 开发的方法适用于现场分析,支持合理利用烟草资源.
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