开源软件中的部分最小二次方程方法用于使用红外光谱学识别伪造的肌酸
Alyson Torres de Barros1, João Vitor Santos Mignoni de Melo2, Gabriely Silveira Folli1
1Chemometrics Laboratory, LabPetro, Federal University of Espírito Santo (UFES), Brazil.
Food chemistry
|April 10, 2025
概括
这项研究引入了一种使用减弱总反射-里埃变换红外光谱 (ATR-FTIR) 和多变量分析来检测肌酸改的新方法. 开发的模型准确地识别了伪造的肌酸补充剂,确保了运动员的产品质量.
科学领域:
- 分析化学 分析化学
- 频谱学是一种光谱学.
- 化学测量 化学测量 化学测量
背景情况:
- 肌酸是一种广泛使用的食补充剂,用于体力活动.
- 确保肌酸补充剂的纯度对于消费者安全和有效性至关重要.
- 添加剂与玉米粉等更便宜物质的改是令人担忧的.
研究的目的:
- 开发和验证一种用于检测肌酸造的新型分析方法.
- 为了区分纯粹的肌酸与用玉米粉 (CS) 伪造的肌酸.
主要方法:
- 减弱总反射-里埃变换红外光谱学 (ATR-FTIR) 与多变量分析的协会.
- 部分最小平方回归 (PLS) 和部分最小平方差分分析 (PLS-DA) 模型的开发.
- 使用GNU Octave进行模型开发和分析.
主要成果:
- 确定了关键的光谱特征,包括在CS中肌酸中碳酸基组的不对称拉伸带和糖基键,以进行歧视.
- PLS模型表现出强烈的实验匹配,预测的根平均平方误差 (RMSEp) 为9.15%.
- 在商业样本的盲目测试中,PLS-DA模型在区分纯与造的肌酸样本方面达到97%的准确性,准确率为95%,灵敏度为90%,特异性为100%.
结论:
- 综合ATR-FTIR和多变量分析方法是有效的选伪造的肌酸补充剂.
- 开发的PLS-DA模型提供了一种可靠的工具,用于质量控制和识别食品补充剂市场中的肌酸造.
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