Rapid Detection of Live and Dead Escherichia coli in a Suspension Using Spectroscopy and Chemometrics

Pranita Jaiswal; Shyam N. Jha; Shweta Lawania; Neha Singh

doi:10.52151/jae2019563.1690

Authors

Pranita Jaiswal CCUBGA, Division of Microbiology, Indian Agricultural Research Institute, New Delhi Author
Shyam N. Jha Indian Council of Agricultural Research, Krishi Anusandhan Bhawan - II, New Delhi Author
Shweta Lawania Department of Engineering, Bundelkhand University, Jhansi-284401 Author
Neha Singh Sam Higginbottom University of Agriculture, Technology and Sciences. Prayagraj- 211007 Author

DOI:

https://doi.org/10.52151/jae2019563.1690

Keywords:

Classification, principal component analyses, SIMCA, UV-Vis spectroscopy, wavelength range

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.

Author Biographies

Pranita Jaiswal, CCUBGA, Division of Microbiology, Indian Agricultural Research Institute, New Delhi

Principal Scientist
Shyam N. Jha, Indian Council of Agricultural Research, Krishi Anusandhan Bhawan - II, New Delhi

Asstt. Director General (Process Engineering)
Shweta Lawania, Department of Engineering, Bundelkhand University, Jhansi-284401

Lecturer
Neha Singh, Sam Higginbottom University of Agriculture, Technology and Sciences. Prayagraj- 211007

M.Tech student (Food Engineering)

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