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Proceedings Paper

Prediction of the light scattering patterns from bacteria colonies by a time-resolved reaction-diffusion model and the scalar diffraction theory
Author(s): Euiwon Bae; Nan Bai; Amornrat Aroonnual; Arun K. Bhunia; J. Paul Robinson; E. Daniel Hirleman
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Paper Abstract

In order to maximize the utility of the optical scattering technology in the area of bacterial colony identification, it is necessary to have a thorough understanding of how bacteria species grow into different morphological aggregation and subsequently function as distinctive optical amplitude and phase modulators to alter the incoming Gaussian laser beam. In this paper, a 2-dimentional reaction-diffusion (RD) model with nutrient concentration, diffusion coefficient, and agar hardness as variables is investigated to explain the correlation between the various environmental parameters and the distinctive morphological aggregations formed by different bacteria species. More importantly, the morphological change of the bacterial colony against time is demonstrated by this model, which is able to characterize the spatio-temporal patterns formed by the bacteria colonies over their entire growth curve. The bacteria population density information obtained from the RD model is mathematically converted to the amplitude/phase modulation factor used in the scalar diffraction theory which predicts the light scattering patterns for bacterial colonies. The conclusions drawn from the RD model combined with the scalar diffraction theory are useful in guiding the design of the optical scattering instrument aiming at bacteria colony detection and classification.

Paper Details

Date Published: 27 April 2009
PDF: 7 pages
Proc. SPIE 7315, Sensing for Agriculture and Food Quality and Safety, 73150A (27 April 2009); doi: 10.1117/12.818855
Show Author Affiliations
Euiwon Bae, Purdue Univ. (United States)
Nan Bai, Purdue Univ. (United States)
Amornrat Aroonnual, Purdue Univ. (United States)
Arun K. Bhunia, Purdue Univ. (United States)
J. Paul Robinson, Purdue Univ. (United States)
E. Daniel Hirleman, Purdue Univ. (United States)

Published in SPIE Proceedings Vol. 7315:
Sensing for Agriculture and Food Quality and Safety
Moon S. Kim; Shu-I Tu; Kaunglin Chao, Editor(s)

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