Menchaca Patricia R, Graham Robert C, Younglove Theodore
Soil and Water Sciences Program, University of California, Riverside, CA, 92521-0424.
Chaffey College, Rancho Cucamongo, CA, 91737.
J Forensic Sci. 2018 Jul;63(4):1043-1052. doi: 10.1111/1556-4029.13723. Epub 2018 Jan 8.
The research sought to develop and test a forensic database of surface soil variability within previously mapped geologic and soil units in southern California. This type of database could be used to link suspects to crime scenes or determine source locations of soil sample evidence. Variability was evaluated using (i) color, (ii) magnetic susceptibility, and (iii) particle-size distribution. Soil properties were analyzed for their ability to discriminate source areas using stepwise discriminant analysis. The percent correct predictions for geologic unit groups ranged from 30% to 100%. A blind study experiment matched four of the 18 samples to their unit of origin with the first choice by stepwise discriminant analysis, and eight were matched as second and third choices. The probability of selecting the appropriate unit of origin increased by 54% over random chance and eliminated as much as 99% of the field area as a potential search location.
该研究旨在开发并测试一个关于南加州先前绘制的地质和土壤单元内表层土壤变异性的法医数据库。这类数据库可用于将嫌疑人与犯罪现场关联起来，或确定土壤样本证据的来源位置。使用（i）颜色、（ii）磁化率和（iii）粒度分布来评估变异性。利用逐步判别分析，分析土壤属性区分源区的能力。地质单元组的正确预测百分比范围为30%至100%。一项盲测实验通过逐步判别分析，将18个样本中的4个与它们的起源单元匹配为首选，8个匹配为第二和第三选择。选择合适起源单元的概率比随机选择提高了54%，并将多达99%的野外区域排除在潜在搜索位置之外。
