使用便携式NIR光谱仪量化和区分精制糖的颜色指数的一种方法
José Eduardo Matos Paz1, Aline Macedo Dantas2, David Douglas de Sousa Fernandes3
1Center for Exact and Natural Sciences, Federal University of Paraíba, João Pessoa, PB, Brazil.
Food chemistry
|July 20, 2025
概括
配有化学测量的近红外 (NIR) 光谱学可以准确地评估糖的颜色,并将其分类为精制或未精制. 便携式设备为质量控制提供速度,低成本和样品保存.
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:
- 糖质量受到颜色的显著影响,影响其市场价值.
- 需要准确和高效的方法来评估和分类糖的颜色.
研究的目的:
- 开发和验证一种方法来评估糖的颜色,并将其分类为精制或未精制.
- 为了比较桌面和便携式近红外 (NIR) 光谱仪器的性能.
主要方法:
- 在89个糖样品上使用近红外 (NIR) 光谱学.
- 开发了使用部分最小平方回归 (PLS) 和多重线性回归 (MLR) 的校准模型.
- 采用了诸如连续投影算法 (SPA),遗传算法 (GA) 和间隔 SPA (iSPA) 等可变选择算法.
- 使用部分最小平方差分分析 (PLS-DA) 和线性差分分析 (LDA) 构建了分类模型.
主要成果:
- 便携式NIR设备在预测性能上表现出优异的性能,相比于长椅设备.
- 分类模型达到高达98.9%的准确性,预测的根平均平方误差 (RMSEP) 为5.087.
- 可变选择算法 (SPA,iSPA) 增强了模型性能.
结论:
- 与化学测量相结合的NIR光谱学为糖色分析提供了一种快速,具有成本效益和非破坏性的方法.
- 便携式NIR设备适用于糖的现场质量控制.
- 开发的模型可以根据颜色准确地将糖分为精制或未精制.
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