A non-traditional disease of cotton, Gossypium hirsutum L., was first reported in South Carolina in 1999 and can be caused by opportunistic strains of the bacterium Pantoea agglomerans (Ewing and Fife). Unlike typical fungal diseases, bolls infected with P. agglomerans continue to appear normal externally, complicating early and rapid detection of diseased bolls. We examined the use of a commercially-available electronic nose (e-nose) to distinguish between liquid Luria Bertani (LB) cultures of P. agglomerans and another non-traditional, opportunistic bacterial boll pathogen, Klebsiella pneumoniae (Schroeter). We also examined whether the e-nose could accurately discriminate between P. agglomerans infected and non-infected bolls. The e-nose was trained to recognize headspace collections of volatiles emitted from treatments established in each experiment. Cross-validation of the training data sets indicated the smell prints of the LB medium and each species of bacteria cultured in the medium could be discriminated with 69% accuracy. However, upon testing samples of each treatment solution, only 49% of the samples were correctly identified. In the second experiment, cross-validation of the training set indicated the smell prints of P. agglomerans-infected and non-infected bolls at one and two weeks post-infection could be distinguished with 62.5% accuracy. However, upon testing the discrimination accuracy of the e-nose, < 30% of the test bolls were correctly classified. In light of the marginal performance of the Cyranose 320 in our experiments, vast improvements in the discriminatory accuracy of this particular e-nose is needed before it can be recommended and adopted as a cotton crop disease management tool.