Tighe M, Forster N, Guppy C, Savage D, Grave P, Young I M
School of Environmental and Rural Science, University of New England, Armidale, NSW 2351, Australia.
138 Toms Gully Road, Black Mountain, NSW 2365, Australia.
Sci Rep. 2018 Feb 16;8(1):3162. doi: 10.1038/s41598-018-21530-7.
The provenance or origin of a soil sample is of interest in soil forensics, archaeology, and biosecurity. In all of these fields, highly specialized and often expensive analysis is usually combined with expert interpretation to estimate sample origin. In this proof of concept study we apply rapid and non-destructive spectral analysis to the question of direct soil provenancing. This approach is based on one of the underlying tenets of soil science - that soil pedogenesis is spatially unique, and thus digital spectral signatures of soil can be related directly, rather than via individual soil properties, to a georeferenced location. We examine three different multivariate regression techniques to predict GPS coordinates in two nested datasets. With a minimum of data processing, we show that in most instances Eastings and Northings can be predicted to within 20% of the range of each within the dataset using the spectral signatures produced via portable x-ray fluorescence. We also generate 50 and 95% confidence intervals of prediction and express these as a range of GPS coordinates. This approach has promise for future application in soil and environmental provenancing.
土壤样本的来源或出处在土壤法医学、考古学和生物安全领域备受关注。在所有这些领域，高度专业化且通常成本高昂的分析通常会与专家解读相结合，以估算样本来源。在这项概念验证研究中，我们将快速且无损的光谱分析应用于直接土壤溯源问题。这种方法基于土壤科学的一个基本原理——土壤发生过程在空间上是独特的，因此土壤的数字光谱特征可以直接与地理参考位置相关联，而不是通过单个土壤属性。我们研究了三种不同的多元回归技术，以预测两个嵌套数据集中的GPS坐标。通过最少的数据处理，我们表明，在大多数情况下，使用便携式X射线荧光产生的光谱特征，可以将东坐标和北坐标预测到数据集中每个坐标范围的20%以内。我们还生成了50%和95%的预测置信区间，并将其表示为一系列GPS坐标。这种方法在土壤和环境溯源的未来应用中有前景。
