使用Vis-NIR光谱仪精确估计黄中粉的混合方法
Madhusudan G Lanjewar1, Pranay P Morajkar2, Jivan S Parab1
1School of Physical and Applied Sciences, Goa University, Taleigao Plateau, India.
概括
这项研究开发了一种快速光谱方法,用于检测黄粉中粉的粉伪造. 先进的技术准确地识别污染物,确保黄的质量和消费者安全.
科学领域:
- 食品科学 食品科学 食品科学
- 分析化学 分析化学
- 频谱学是一种光谱学.
背景情况:
- 黄在东南亚是一个有价值的商品,被用作食品添加剂和保健补充剂.
- 它的经济重要性使得黄容易被粉等更便宜的物质改.
- 快速准确的检测方法对于确保黄的纯度和安全至关重要.
研究的目的:
- 开发和验证一种用于量化黄粉改的光谱方法.
- 评估各种光谱预处理和特征选择技术的有效性.
- 评估堆叠的概括模型的性能,以准确检测伪造剂.
主要方法:
- 收集了黄粉混合物 (0-50%粉) 的反射光谱 (400-2050 nm).
- 频谱数据经过预处理,包括多倍散射校正 (MSC) 和标准正常变量 (SNV),然后进行Savitzky-Golay (SG) 过.
- 特性选择使用了额外树回归器 (ETR),通过主要组件分析 (PCA) 减少维度,并使用K-最近邻居 (KNN),决策树 (DT),随机森林 (RF),后勤回归 (LRC) 和线性回归 (LR) 模型进行堆叠的概括.
主要成果:
- 提出的堆叠概括模型实现了优异的回归性能 (r2=0.999,RMSE=0.206,RPD=73.73,RER=480.58).
- 分类实现了100%的准确性,通过F1得分和马修的相关系数 (MCC) 表示.
- 该方法在检测和量化粉改方面表现出高灵敏度和准确性.
结论:
- 光谱分析与先进的化学测量方法相结合,为检测黄造提供了强大的解决方案.
- 开发的方法为食品行业的质量控制提供了可靠,快速和准确的工具.
- 确保黄的真实性保护消费者,维护市场的完整性.
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