用激发-发射荧光光谱法和化学计量学自动鉴别牛奶的地理来源。

Lu Xu, De-Hua Deng, Chen-Bo Cai, Hong-Wei Yang
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引用次数: 1

摘要

本文介绍了用激发-发射荧光光谱法和化学计量学自动判别滇西高原区和中国东部地区牛奶产地的方法。真正的高原牛奶(n = 60)和来自中国东部的牛奶(n = 89)在180-300 nm的激发区和200-800 nm的发射区进行扫描。研究并比较了不同数据分析方法对不同产地牛奶的鉴别效果:(1)分别基于激发光谱和发射光谱的双向偏最小二乘判别分析(PLSDA);(2)基于激发光谱和发射光谱融合的双向PLSDA;(3)基于激发-发射矩阵光谱的三向PLSDA。采用激发光谱、发射光谱和激发光谱与发射光谱融合的双向PLSDA方法对牛奶样品的正确率分别为91.3%、88.6%和95.3%;而三向PLSDA的总准确率为96.0%。结果表明,结合激发光谱和发射光谱的双向数据足以表征和识别高原乳。考虑到模型的准确性和所需的分析时间,结合激发光谱和发射光谱的双向PLS-DA被推荐为一种可靠、快速的高原牛奶和普通牛奶鉴别方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Automatic discrimination of the geographical origins of milks by excitation-emission fluorescence spectrometry and chemometrics.

Automatic discrimination of the geographical origins of milks by excitation-emission fluorescence spectrometry and chemometrics.

Automatic discrimination of the geographical origins of milks by excitation-emission fluorescence spectrometry and chemometrics.

Automatic discrimination of the geographical origins of milks by excitation-emission fluorescence spectrometry and chemometrics.

This paper presents the automatic discrimination of geographical origins of milks from Western Yunnan Plateau areas and eastern China by excitation-emission fluorescence spectrometry and chemometrics. Genuine plateau milks (n = 60) and milks from eastern China (n = 89) are scanned in the regions of 180-300 nm for excitation and 200-800 nm for emission. Different options of data analysis are investigated and compared in terms of their performance in discriminating milks of different geographical origins: (1) two-way partial least squares discriminant analysis (PLSDA) based on excitation and emission spectra, respectively; (2) two-way PLSDA based on fusion of excitation and emission spectra; (3) three-way PLSDA based on excitation-emission matrix spectra. The two-way PLSDA methods with excitation spectra, emission spectra, and fusion of excitation and emission spectra correctly classify 91.3%, 88.6%, and 95.3% of the milk samples, respectively; while the total accuracy of three-way PLSDA is 96.0%. The results demonstrate the two-way data combining excitation and emission spectra are sufficient to characterize and identify the plateau milks. Considering both model accuracy and the analytical time required, two-way PLS-DA with fusion of excitation and emission spectra is recommended as a reliable and quick method to discriminate plateau milks from ordinary milks.

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