Abstract
Structured-illumination reflectance imaging provides a new means for food quality detection. This original work investigated the capability of Structured-illumination reflectance imaging technique coupled with multivariate chemometrics to evaluate the microbial contamination in pork inoculated with Pseudomonas fluorescens and Brochothrix thermosphacta during storage at different temperatures. The prediction performances based on different spectrum and the textural features of direct component and amplitude component images demodulated from the SIRI pattern images, as well as their data fusion were comprehensively compared. Based on the full wavelength spectrum (420 – 700) nm of amplitude component images, the orthogonal signal correction coupled with support vector machine regression provided the best predictions of the number of Pseudomonas fluorescens and Brochothrix thermosphacta in pork, with the Rp2 values of 0.870 and 0.906, respectively. Besides, the prediction models based on the amplitude component or direct component image textural features and the data fusion models using spectrum and textural features from direct component and amplitude component images cannot significantly improve their prediction accuracy. Consequently, structured-illumination reflectance imaging can be further considered as a potential technique for the rapid evaluation of microbial contaminations in pork meat.
