Abstract

Yerba mate samples from three different states of Brazil were evaluated in order to discriminate them regarding the presence of sugar and geographic origin. High-performance liquid chromatography (HPLC), phytochemical compounds, in vitro antioxidant activity, visible and near-infrared (NIR) spectroscopy, colorimetry, and electronic nose were used in tandem with chemometric methods. The multiblock exploratory analysis (ComDim) was able to discriminate the samples containing sugar; however, it was not possible to discriminate them by geographical origin. Furthermore, ComDim results showed the NIR spectra presented the best discriminating capacity. Partial least square discriminant analysis (PLS-DA) models constructed using NIR spectra classified the samples assertively according to the presence of sugar (100% of sensitivity and specificity for the prediction set), and reasonable models were also obtained for the geographic classification (80% of sensitivity and 93% of specificity for the prediction set). The multiblock approach allowed an overall evaluation of the data collected through different analytical methods. In addition, among the methods applied, NIR spectroscopy was faster and cheaper and allowed for better sample discrimination.

中文翻译：

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化学计量学方法，使用ComDim和PLS-DA进行商业Yerba Mate（Ilex paraguariensis St. Hil。）的区分和分类

摘要

对来自巴西三个不同州的耶尔巴伴侣样品进行了评估，以区分糖的存在和地理来源。高效液相色谱（HPLC），植物化学化合物，体外抗氧化活性，可见光和近红外（NIR）光谱，比色法和电子鼻与化学计量方法结合使用。多区块探索性分析（ComDim）能够区分含糖样品；但是，不可能通过地理来源来区分它们。此外，ComDim结果显示NIR光谱具有最佳识别能力。使用NIR光谱构建的偏最小二乘判别分析（PLS-DA）模型根据糖的存在（对预测集的敏感性和特异性为100％）自信地对样品进行分类，并且还获得了用于地理分类的合理模型（80预测集的敏感性百分比和特异性的93％）。多块方法允许对通过不同分析方法收集的数据进行整体评估。此外，在所应用的方法中，近红外光谱法更快，更便宜，并且可以更好地区分样品。多块方法允许对通过不同分析方法收集的数据进行整体评估。此外，在所应用的方法中，近红外光谱法更快，更便宜，并且可以更好地区分样品。多块方法允许对通过不同分析方法收集的数据进行整体评估。此外，在所应用的方法中，近红外光谱法更快，更便宜，并且可以更好地区分样品。