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Use of handheld X-ray fluorescence as a non-invasive method to distinguish between Asian and African elephant tusks

机译:使用手持式X射线荧光作为非侵入性方法来区分亚洲和非洲象牙

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摘要

We describe the use of handheld X-ray fluorescence, for elephant tusk species identification. Asian (n = 72) and African (n = 85) elephant tusks were scanned and we utilized the species differences in elemental composition to develop a functional model differentiating between species with high precision. Spatially, the majority of measured elements (n = 26) exhibited a homogeneous distribution in cross-section, but a more heterologous pattern in the longitudinal direction. Twenty-one of twenty four elements differed between Asian and African samples. Data were subjected to hierarchical cluster analysis followed by a stepwise discriminant analysis, which identified elements for the functional equation. The best equation consisted of ratios of Si, S, Cl, Ti, Mn, Ag, Sb and W, with Zr as the denominator. Next, Bayesian binary regression model analysis was conducted to predict the probability that a tusk would be of African origin. A cut-off value was established to improve discrimination. This Bayesian hybrid classification model was then validated by scanning an additional 30 Asian and 41 African tusks, which showed high accuracy (94%) and precision (95%) rates. We conclude that handheld XRF is an accurate, non-invasive method to discriminate origin of elephant tusks provides rapid results applicable to use in the field.
机译:我们描述了使用手持式X射线荧光来识别象牙物种。扫描了亚洲人(n = 72)和非洲人(n = 85)象牙,我们利用元素组成的物种差异建立了可区分物种的高精度功能模型。在空间上,大多数被测元素(n = 26)在横截面上显示出均匀的分布,但是在纵向上却表现出更多的异质性。亚洲和非洲样本之间二十四个要素中的二十一个有所不同。对数据进行层次聚类分析,然后进行逐步判别分析,以识别功能方程式的元素。最好的方程式由Si,S,Cl,Ti,Mn,Ag,Sb和W之比组成,其中Zr为分母。接下来,进行了贝叶斯二元回归模型分析,以预测象牙源自非洲的可能性。确定了一个临界值以改善歧视。然后,通过扫描另外30个亚洲象牙和41个非洲象牙来验证此贝叶斯杂种分类模型,这些象牙显示出较高的准确度(94%)和准确度(95%)。我们得出结论,手持式XRF是区分象牙起源的准确,非侵入性方法,可提供适用于该领域的快速结果。

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