Employing gas sensor technologies for investigation of complex odor profiles

Abstract

In the case of a mass disaster, terror attack, murder, war, or other catastrophic events, it is of outmost importance to find and rescue survivors, and to identify victims and human remains. Cadaver-detection dogs (CDDs) are trained and employed in forensics investigations due to their extraordinary olfactory capability. They are considered the most rapid and efficient tool for odor detection. However, there are critical legal and ethical concerns about using CDD results as evidence in court. It is, therefore, necessary to find innovative solutions that may help investigators to overcome the existing constraints.

Here, we present our preliminary results on the use of gas sensor technologies and quantitative methods for identification and classification of organic compounds that are key in odor detection. Due to the existing restrictions in acquiring human remains training aids, we used animal remains as training aids for laboratory tests under controlled environmental conditions. By use of linear discriminant analysis as a statistical method to analyze and evaluate raw data, we were able to clearly distinguish different samples of fresh meat as well as rotten meat (reindeer, deer, and chicken).

With our study, we aim to contribute to a better understanding of the highly variable and complex odor profile of training aids for further enhancement and, eventually, standardization of the current CDD training practices used to find missing people.