快速检测婴儿配方奶粉中的微量营养成分,使用近红外光谱学
Shaoli Liu1, Ting Lei1, Guipu Li2
1School of Biological and Chemical Engineering, Zhejiang University of Science and Technology, Hangzhou, Zhejiang, China.
Frontiers in nutrition
|October 9, 2023
概括
这项研究开发了一种快速检测婴儿配方奶粉中银寡糖 (GOS),果寡糖 (FOS), (Ca) 和维生素C (Vc) 的方法. 汽车-SVR模型与光谱预处理相结合,为这些关键营养成分实现了准确的预测.
科学领域:
- 分析化学 分析化学
- 食品科学 食品科学 食品科学
- 频谱学是一种光谱学.
背景情况:
- 婴儿配方奶粉需要精确的营养分析来控制质量.
- 快速准确地检测GOS,FOS,Ca和Vc等微量营养素至关重要.
- 现有的方法可能耗时或缺乏实时监控的效率.
研究的目的:
- 开发一种快速准确的方法来检测婴儿配方奶粉中的GOS,FOS,Ca和Vc.
- 评估不同光谱预处理技术和波长选择算法的有效性.
- 建立可靠的化学测量模型,用于对这些成分进行定量分析.
主要方法:
- 获得婴儿配方奶粉的光谱数据.
- 预处理方法的应用:标准正常变量 (SNV),乘法散射校正 (MSC),规范化 (Nor) 和萨维茨基-戈莱光滑 (SG).
- 使用竞争性适应性重权取样 (CARS) 和随机青 (RF) 算法进行波长选择.
- 使用部分最小平方回归 (PLSR) 和支向量回归 (SVR) 开发预测模型.
主要成果:
- SNV预处理与CARS相结合,有效地提取了GOS和FOS检测的特征波长.
- 与CARS相结合的MSC预处理有效地提取了Ca和Vc检测的特征波长.
- 在适当的预处理后,CARS-SVR模型对GOS,FOS,Ca和Vc表现出有利的预测准确性.
结论:
- 开发的光谱分析方法为婴儿配方奶粉中关键微量营养素的快速在线检测提供了一个有希望的方法.
- 优化预处理和波长选择对于准确的化学度模型是非常重要的.
- 这种技术可以帮助在婴儿配方奶粉生产过程中进行质量控制和流程优化.
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