The use of near infrared spectroscopy and multivariate techniques to differentiate Escherichia coli and Salmonella Enteritidis inoculated into pulp juice

Abstract

This study shows the application and usefulness of near infrared (NIR) transflectance spectra measurements in the identification and classification of Escherichia coli and Salmonella Enteritidis from commercial fruit pulp (pineapple). Principal component analysis (PCA), soft independent modeling of class analogy (SIMCA) analysis and partial least-squares discriminant analysis (PLS-DA) were used in the analysis. It was not possible to obtain total separation between the samples using PCA and SIMCA. PLS-DA presented good performance achieving prediction ability of 87.5% for E. coli and 88.3% for S. Enteritidis, respectively. For the best models, the sensitivity and specificity was 0.87 and 0.83 for PLS-DA with second derivative spectra. These results suggest that NIR spectroscopy and PLS-DA can be used to discriminate and detect bacteria in fruit pulp for modeling linear class boundaries.