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Chemometric approach to evaluate trace metal concentrations in some spices and herbs

机译:化学计量学方法评估一些香料和草药中的痕量金属浓度

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Herbs (mint, thyme and rosemary) and spices (black pepper, chili pepper, cinnamon, cumin, sweet red pepper and turmeric) were analysed using atomic spectrometry and then subjected to chemometric evaluation in an attempt to classify them using their trace metallic analyte concentrations (As, Ba, Ca, Cd, Co, Cr, Cu, Fe, Mg, Mn, Ni, Sr and Zn). Trace metals in acid digests of these materials were determined using both inductively coupled plasma-atomic emission spectrometry and inductively coupled plasma-mass spectrometry. The chemometric techniques of principal component analysis (PCA), linear discriminant analysis (LDA) and cluster analysis (CA) were used for the classification studies. These herbs and spices were classified into five groups by PCA and CA. When the results of these techniques were compared with those from LDA, it was found that all group members determined by PCA and CA are in the predicted group that 100.0% of original grouped cases correctly classified by LDA.
机译:使用原子光谱仪分析草药(薄荷,百里香和迷迭香)和香料(黑胡椒,辣椒,肉桂,小茴香,甜红辣椒和姜黄),然后进行化学计量评估,以尝试使用痕量金属分析物浓度对它们进行分类(砷,钡,钙,镉,钴,铬,铜,铁,镁,锰,镍,锶和锌)。使用电感耦合等离子体原子发射光谱法和电感耦合等离子体质谱法测定这些材料的酸消化物中的痕量金属。分类研究使用主成分分析(PCA),线性判别分析(LDA)和聚类分析(CA)的化学计量学技术。 PCA和CA将这些药草和香料分为五类。将这些技术的结果与LDA的结果进行比较时,发现PCA和CA确定的所有组成员都在预测组中,原始分组病例的100.0%被LDA正确分类。

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