Identification of spoilage bacteria using a simple colorimetric sensor array

Abstract

This paper demonstrates the application of a simple colorimetric sensor array response to the problem of identifying spoilage bacteria with the help of multivariate calibration. Four dominant spoilage bacteria from meat products, namely, Pseudomonas koreensis PS1, Bacillus fusiformis J4, Acinetobacter guillouiae P3, and Enterobacter cloacae P5, were tested in the study. We developed a novel colorimetric sensor array by printing 15 chemically responsive dyes (9 metalloporphyrins and 6 pH indicators) on a C2 reverse silica-gel flat plate. According to the chemical dyes response to volatile organic compounds (VOCs) produced by bacteria, a colorific change profile was obtained. We attempted multivariate calibrations to classify four bacterial strains, and linear discriminant analysis (LDA) achieved a good classification result by leave-one-out cross-validation. Besides, we systemically studied the internal relationship among four bacterial strains using this proposed method with the help of hierarchical cluster analysis (HCA). And HCA results using the proposed method are in agreement with the results using 16S rRNA sequences analysis. This work has demonstrated that the novel sensor array has a high potential for reliable identification of meat spoilage bacteria grown on solid media and on Petri dishes.