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The Potential of UV-Visible Spectroscopy and Chemometrics for Determination of Geographic Origin of Three Specialty Coffees in Indonesia

机译:UV可见光光谱和化学计量学的潜力,用于确定印度尼西亚三种特色咖啡的地理起源

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The growing global trading market for specialty coffee increases the need for better coffee quality evaluation methods. Several Arabica coffees in Indonesia have high commercial value. For this reason, the development of analytical methods with high sensitivity and accuracy for detection of its adulteration was important. This research evaluated the potential of UV-visible spectroscopy and partial least squares discriminant analysis (PLS-DA) for determining the geographic origin of three specialty coffees (Gayo, Kintamani and Wamena) in Indonesia. In this research, 296 coffee samples from three different origins (Gayo, Kintamani and Wamena) were used. All coffee samples were ground using a home-coffee-grinder. We sieved all coffee samples through a nest of US standard sieves (mesh number of 40) on a Meinzer II sieve shaker for 10 minutes to obtain a particle size of 420 μm. All samples were extracted with distilled water and then filtered. For each sample, 3 mL of extracted sample then was pipetted into 10 mm cuvettes for spectral data acquisition. The spectral data were acquired using a Genesys 10s UV-visible spectrometer in the range of 190-1100 nm. A PLS-DA classification model was estimated to classify the origin of specialty coffees by their UV-visible spectra. The best PLS-DA model accurately classified the specialty coffee samples of the prediction sample set with prediction ability of 100% of correct classification for Gayo, Kintamani and Wamena, respectively. The results demonstrate that UV-visible spectroscopy coupled with PLS-DA provides a sensitive and accurate analytical method to distinguish ground roasted coffee samples geographically.
机译:越来越多的特种咖啡贸易市场增加了对更好的咖啡质量评价方法的需求。印度尼西亚的几个阿拉伯咖啡具有高商业价值。因此,具有高灵敏度和精度的分析方法的开发,用于检测其掺假的掺杂性很重要。该研究评估了UV可见光谱和偏最小二乘判别分析(PLS-DA)的潜力,用于确定印度尼西亚三种特色咖啡(Gayo,Kintamani和Wamena)的地理起源。在本研究中,使用了来自三种不同起源(Gayo,Kintamani和Wamena)的296个咖啡样本。所有咖啡样品都使用家用咖啡研磨机进行研磨。我们在Meinzer II筛振动器上通过美国标准筛网(网格数为40)的所有咖啡样本10分钟,以获得420μm的粒度。用蒸馏水萃取所有样品,然后过滤。对于每个样品,然后将3ml提取的样品移液到10mm比色皿中,用于光谱数据采集。在190-1100nm的范围内使用Genesys 10s UV可见光谱仪获取光谱数据。估计PLS-DA分类模型通过其UV可见光光谱分类特种咖啡的起源。最好的PLS-DA模型将预测样本的特殊咖啡样本分为预测能力分别为Gayo,Kintamani和Wamena的预测能力为100%。结果表明,与PLS-DA耦合的UV可见光光谱提供了一种敏感和准确的分析方法,用于在地理上区分植被烘焙咖啡样品。

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