衰减全反射
人类血液
线性判别分析
傅里叶变换
傅里叶变换红外光谱
光谱学
偏最小二乘回归
人工智能
分析化学(期刊)
模式识别(心理学)
生物系统
材料科学
计算机科学
生物
化学
光学
数学
色谱法
物理
机器学习
生理学
数学分析
量子力学
作者
Ewelina Mistek,Igor K. Lednev
标识
DOI:10.1038/s42004-020-00424-8
摘要
Forensic chemistry is an important area of analytical chemistry. This field has been rapidly growing over the last several decades. Confirmation of the human origins of bloodstains is important in practical forensics. Current serological blood tests are destructive and often provide false positive results. Here, we report on the development of a nondestructive method that could potentially be applied at the scene for differentiation of human and animal blood using attenuated total reflection Fourier transform-infrared (ATR FT-IR) spectroscopy and statistical analysis. The following species were used to build statistical models for binary human-animal blood differentiation: cat, dog, rabbit, horse, cow, pig, opossum, and raccoon. Three other species (deer, elk, and ferret) were used for external validation. A partial least squares discriminant analysis (PLSDA) was used for classification purposes and showed excellent performance in internal cross-validation (CV). The method was externally validated first using blood samples from new donors of species used in the training data set, and second using donors of new species that were not used to construct the model. Both validations showed excellent results demonstrating potential of the developed approach for nondestructive, rapid, and statistically confident discrimination between human and animal blood for forensic purposes.
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