Classification of honey applying high performance liquid chromatography, near-infrared spectroscopy and chemometrics
Classification of honey applying high performance liquid chromatography, near-infrared spectroscopy and chemometrics
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DOI：
10.1016/j.chemolab.2020.104037
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发表时间：
2020-07-15
影响因子：
3.9
通讯作者：
Biancolillo, Alessandra
中科院分区：
文献类型：
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作者：
Nasab, Shima Ghanavati;Yazd, Mehdi Javaheran;Biancolillo, Alessandra
研究了傅里叶变换近红外光谱（FT-NIR）和高效液相色谱二极管阵列检测（HPLC-DAD）结合多元数据分析对70份蜂蜜样品（属于7个不同品种）的植物来源进行分类的潜力。在第一部分工作中，通过将PLS-DA应用于单个数据块来实现分类：从预测的角度来看，这种方法导致了有希望的结果。在研究的第二部分中，通过数据融合技术处理了多块数据集，结果与分析单个矩阵获得的结果相当或更好。这些令人满意的结果证实了所提出方法的可行性，并鼓励开发类似的蜂蜜质量评估方法。
The potential of Fourier Transform Near-Infrared spectroscopy (FT-NIR) and High-Performance Liquid Chromatography with Diode-Array Detection (HPLC-DAD) in combination with multivariate data analysis was examined to classify 70 honey samples (belonging to 7 different varieties) according to their botanical origin. In the first part of the work, classification was achieved by applying PLS-DA to the individual data blocks: this approach led to promising results from the prediction point of view. In the second part of the study, the multi-block data set has been handled by data-fusion techniques which led to comparable or better results than those obtained by the analysis of individual matrices. These satisfactory results confirm the feasibility of the proposed methodology and encourage the development of similar approaches for honey quality assessment.