Abstract
Pseudomonas spp. counts (PC) is a good indicator for spoilage evaluation, but its detection with traditional techniques is time-consuming, destructive and inefficient. The aim of this study was to evaluate the potential of near-infrared (NIR) hyperspectral imaging to predict PC distribution in salmon fillets. Full wavelength data were related to PC values by partial least square regression (PLSR), resulting in coefficient of determination (RP2) of 0.90 and root mean square error of prediction (RMSEP) of 0.52. Most effective wavelengths (MEW) were selected by regression coefficients (RC), successive projections algorithm (SPA) and competitive adaptive reweighted sampling (CARS) algorithm, respectively, to optimise the PLSR model. CARS-PLSR model built with ten MEWs of 941, 1105, 1161, 1178, 1222, 1242, 1359, 1366, 1628 and 1652 nm performed better with RP2 of 0.91 and RMSEP of 0.49. Colour maps were finally generated and PC distribution was visualised. NIR-HIS shows a great promise for evaluating PC distribution of salmon flesh during cold storage.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.