TY - JOUR
T1 - Spectroscopic analysis of bacterial biological warfare simulants and the effects of environmental conditioning on a bacterial spectrum
AU - McIntosh, Alastair J S
AU - Barrington, Stephen J.
AU - Bird, Hilary
AU - Hurst, Daniel
AU - Spencer, Phillippa
AU - Pelfrey, Suzanne H.
AU - Baker, Matthew J.
PY - 2012/11/1
Y1 - 2012/11/1
N2 - The ability to distinguish bacteria from mixed samples is of great interest, especially in the medical and defence arenas. This paper reports a step towards the aim of differentiating pathogenic endospores in situ, to aid any required response for hazard management using infrared spectroscopy combined with multivariate analysis. We describe a proof-ofprinciple study aimed at discriminating biological warfare simulants from common environmental bacteria. We also report an evaluation of multiple pre-processing techniques and subsequent differences in cross-validation of two pattern recognition models (Support Vector Machines and Principal Component-Linear Discriminant Analysis) for a six-class classification (bacterial classification). These classifications were possible with an average sensitivity of 88.0 and 86.9 %, and an average specificity of 97.6 and 97.5 % for the SVM and the PC-LDA models, respectively. Most spectroscopic models are built upon spectra from bacteria that have been specifically prepared for analysis by a particular method; this paper will comment upon the differences in the bacterial spectrum that occur between specific preparations when the bacteria have spent 30 days in the simulated weather conditions of a hot dry climate.
AB - The ability to distinguish bacteria from mixed samples is of great interest, especially in the medical and defence arenas. This paper reports a step towards the aim of differentiating pathogenic endospores in situ, to aid any required response for hazard management using infrared spectroscopy combined with multivariate analysis. We describe a proof-ofprinciple study aimed at discriminating biological warfare simulants from common environmental bacteria. We also report an evaluation of multiple pre-processing techniques and subsequent differences in cross-validation of two pattern recognition models (Support Vector Machines and Principal Component-Linear Discriminant Analysis) for a six-class classification (bacterial classification). These classifications were possible with an average sensitivity of 88.0 and 86.9 %, and an average specificity of 97.6 and 97.5 % for the SVM and the PC-LDA models, respectively. Most spectroscopic models are built upon spectra from bacteria that have been specifically prepared for analysis by a particular method; this paper will comment upon the differences in the bacterial spectrum that occur between specific preparations when the bacteria have spent 30 days in the simulated weather conditions of a hot dry climate.
KW - bacteria
KW - biological warfare
KW - infrared spectroscopy
KW - pre-processing
KW - surface deposited Bacillus
UR - http://www.scopus.com/inward/record.url?scp=84870931349&partnerID=8YFLogxK
U2 - 10.1007/s00216-012-6382-z
DO - 10.1007/s00216-012-6382-z
M3 - Article
C2 - 22975803
AN - SCOPUS:84870931349
SN - 1618-2642
VL - 404
SP - 2307
EP - 2315
JO - Analytical and Bioanalytical Chemistry
JF - Analytical and Bioanalytical Chemistry
IS - 8
ER -