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首页> 外文期刊>Applied Spectroscopy: Society for Applied Spectroscopy >Geographic Classification of Extra Virgin Olive Oils From the Eastern Mediterranean by Chemometric Analysis of Visible and Near-Infrared Spectroscopic Data
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Geographic Classification of Extra Virgin Olive Oils From the Eastern Mediterranean by Chemometric Analysis of Visible and Near-Infrared Spectroscopic Data

机译:通过可见和近红外光谱数据的化学计量分析对东地中海特级初榨橄榄油的地理分类

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摘要

Visible and near-infrared reflectance spectra have been examined for their ability to classify extra virgin olive oils from the eastern Mediterranean on the basis of their geographic origin. Classification strategies investigated were partial least-squares regression, factorial discriminant analysis, and k-nearest neighbors analysis. Discriminant models were developed and evaluated using spectral data in the visible (400-750 nm), near-infrared (1100-2498 nm), and combined (400-2498 nm) wavelength ranges. A variety of data pretreatments was applied. Best results were obtained using factorial discriminant analysis on raw spectral data over the combined wavelength range; a correct classification rate of 93.9% was obtained on a prediction sample set. Though the overall sample set was limited in numbers, these results demonstrate the potential of near-infrared spectroscopy to classify extra virgin olive oils on the basis of their geographic origin.
机译:已经检查了可见和近红外反射光谱,以根据其地理来源对来自地中海东部的特级初榨橄榄油进行分类的能力。研究的分类策略是偏最小二乘回归,阶乘判别分析和k最近邻分析。使用可见光(400-750 nm),近红外(1100-2498 nm)和组合(400-2498 nm)波长范围内的光谱数据来开发和评估判别模型。应用了各种数据预处理。使用因子判别分析对组合波长范围内的原始光谱数据可获得最佳结果;在预测样本集上,正确分类率为93.9%。尽管整个样本集数量有限,但这些结果证明了近红外光谱技术可根据地理来源对特级初榨橄榄油进行分类的潜力。

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