Abstract
Viability assessment of bacteria is critical in monitoring of food or environmental samples. Existing methods are time-consuming, labour-intensive or require trained manpower and costly chemicals. Potential of commonly used UV-visual spectrometer was explored for rapid viability detection of Escherichia coli (ATCC 8739). Spectra of samples (live and dead cells) mixed in different proportion revealed clear differences. Live bacterial suspension showed absorption peak at 260 nm with decreasing amplitude as the proportion of live bacteria was reduced in the suspension and vice-versa. Principal component analyses (PCA) of spectral data showed clear clustering of samples based on the level of live bacterial cells (5 % significance level). Soft Independent Modelling of Class Analogy (SIMCA) and Partial Least Square Discriminant Analysis (PLSDA) yielded 100 % correct classification with test samples. The percentage of live and dead bacteria in a suspension could be predicted with coefficient of determination (R2 ) of 0.980 and 0.977 for calibration and validation sample sets, respectively, in the range of 259-261 nm using Multiple Linear Regression (MLR). Low standard errors of calibration (4.5), prediction (4.8) and high R2 (0.98) indicated the potential of UV visual spectrometer to detect and predict live and dead cells of E. coli in a suspension.
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