Biosecurity and biosafety are key concerns of modern society. Although nanomaterials are improving the capacities of point detectors, standoff detection still appears to be an open issue. Laser-induced fluorescence of biological agents (BAs) has proved to be one of the most promising optical techniques to achieve early standoff detection, but its strengths and weaknesses are still to be fully investigated. In particular, different BAs tend to have similar fluorescence spectra due to the ubiquity of biological endogenous fluorophores producing a signal in the UV range, making data analysis extremely challenging. The Universal Multi Event Locator (UMEL), a general method based on support vector regression, is commonly used to identify characteristic structures in arrays of data. In the first part of this work, we investigate fluorescence emission spectra of different simulants of BAs and apply UMEL for their automatic classification. In the second part of this work, we elaborate a strategy for the application of UMEL to the discrimination of different BAs’ simulants spectra. Through this strategy, it has been possible to discriminate between these BAs’ simulants despite the high similarity of their fluorescence spectra. These preliminary results support the use of SVR methods to classify BAs’ spectral signatures.
With the aim of identifying an approach to exploit the differences in the fluorescence signatures of biological agents
BAs, we have investigated the response of some BAs simulants to a set of different excitation wavelengths in the UV
spectral range (i.e. 266, 273, 280, 300, 340, 355 nm).
Our preliminary results on bacterial spores and vegetative forms, dispersed in water, showed that the differences in the
fluorescence spectra can be enhanced, and more easily revealed, by using different excitation wavelengths.
Specifically, the photo luminescence (PL) spectra coming from different species of Bacillus, in the form of spores (used
as simulants of <i>Bacillus anthracis</i>), show significant differences under excitation at all the wavelengths, with slightly
larger differences at 300, 340, 355 nm.
On the other hand, the vegetative forms of two Bacillus species, did not show any appreciable difference, i.e. the PL
spectra are virtually identical, for the excitation wavelengths of 266, 273, 280 nm. Conversely, small yet appreciable
difference appear at 300, 340, 355 nm.
Finally, large difference appear between the spore and the vegetative form of each species at all the wavelengths, with
slightly larger variations at 300, 340, 355 nm.
Together, these preliminary results support the hypothesis that a multi-wavelength approach could be used to improve
the sensitivity and specificity of UV-LIF based BAs detection systems.
The second step of this work concerns the application of a Support Vector Regression (SVR) method, as evaluated in our
previous work to define a methodology for the setup of a multispectral database for the stand-off detection of BAs.