基于元素代谢组学的化学计量学对地理起源和植物类型蜂蜜进行鉴定。
Geographical origin and botanical type honey authentication through elemental metabolomics via chemometrics.
机构信息
Chemistry Laboratory, Department of Food Science and Human Nutrition, Agricultural University of Athens, 75 Iera Odos, 118 55 Athens, Greece.
Chemistry Laboratory, Department of Food Science and Human Nutrition, Agricultural University of Athens, 75 Iera Odos, 118 55 Athens, Greece; FoodOmics.GR Research Infrastructure, Greece.
出版信息
Food Chem. 2021 Feb 15;338:127936. doi: 10.1016/j.foodchem.2020.127936. Epub 2020 Aug 25.
The trace and rare earth elements content of 93 honeys of different botanical type and origin have been studied through ICP-MS. Discriminant Analysis (DA) was successful for botanical type and geographical origin classification while Cluster Analysis (CA) was successful only for botanical type. Through Probabilistic Neural Network (PNN) analysis, 85.3% were correctly classified by the network according to their geographical origin and 73.3% according to their organic characterization. A Partial Least Squares (PLS) model was constructed, giving a prediction accuracy of more than 95%. Information obtained using Rare Earths (Y, La, Ce, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb, Lu) and trace elements (Li, Mg, Mn, Ni, Co, Cu, Sr, Ba, Pb) via chemometric evaluation facilitated classification of honey samples.
通过电感耦合等离子体质谱法（ICP-MS）研究了 93 种不同植物来源和产地的蜂蜜中的痕量和稀土元素含量。判别分析（DA）可成功用于植物种类和地理来源的分类，而聚类分析（CA）仅可成功用于植物种类的分类。通过概率神经网络（PNN）分析，根据产地和有机特性，网络分别有 85.3%和 73.3%的样本被正确分类。建立了一个偏最小二乘（PLS）模型，其预测准确率超过 95%。通过化学计量评估获得的稀土元素（Y、La、Ce、Pr、Nd、Sm、Eu、Gd、Tb、Dy、Ho、Er、Tm、Yb、Lu）和微量元素（Li、Mg、Mn、Ni、Co、Cu、Sr、Ba、Pb）信息有助于对蜂蜜样品进行分类。
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