Identification of human and non-human bloodstains on rough carriers based on ATR-FTIR and chemometrics

In criminal cases, bloodstains are the most common body fluid spots. It is very important to identify them quickly. However, there are few reports on establishing a fast identification and prediction model for the direct detection of bloodstains on rough carriers. In this study, we used Fourier Transform infrared spectroscopy (FTIR) and chemometrics to establish a prediction model for rapid identification of bloodstains on rough carriers. The results of principal component analysis (PCA) showed that the difference of human and non-human bloodstains between cotton and napkin carrier groups was mainly related to protein changes. Then partial least squares discriminant analysis (PLS-DA) was used to evaluate the classification ability of training data sets and test data sets. Cotton group were 0.921 and 0.947 (sensitivity and specificity), respectively. Napkin group were 0.872 and 0.912 (sensitivity and specificity), respectively. The classification results of test data set were 0.867 and 0.944 (sensitivity and specificity) in cotton group, respectively. Napkin group were 0.767 and 0.963 (sensitivity and specificity), respectively. In addition, the classification model of cattle and sheep on rough carrier was constructed, and good classification ability was obtained. In conclusion, FTIR has the advantages of nondestructive, rapid, objective and strong identification ability. The analysis of forensic cases under actual natural conditions has great potential.