Date of this Version
Sensors and Actuators B 171– 172 (2012) 588– 594; http://dx.doi.org/10.1016/j.snb.2012.05.038
We report here on a novel methodology in detecting Mycobacterium bovis (M. bovis) infection in cattle, based on identifying unique volatile organic compounds (VOCs) or a VOC profile in the breath of cattle. The study was conducted on an M. bovis-infected dairy located in southern Colorado, USA, and on two tuberculosis-free dairies from northern Colorado examined as negative controls. Gaschromatography/ mass-spectrometry analysis revealed the presence of 2 VOCs associated with M. bovis infection and 2 other VOCs associated with the healthy state in the exhaled breath of M. bovis-infected and not infected animals, yielding distinctly different VOC patterns for the two study groups. Based on these results, a nanotechnology-based array of sensors was then tailored for detection of M. bovis-infected cattle via breath. Our system successfully identified all M. bovis-infected animals, while 21% of the not infected animals were classified as M. bovis-infected. This technique could form the basis for a real-time cattle monitoring system that allows efficient and non-invasive screening for new M. bovis infections on dairy farms.