Journal
LWT-FOOD SCIENCE AND TECHNOLOGY
Volume 62, Issue 1, Pages 11-18Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.lwt.2015.01.036
Keywords
Imaging; Pseudomonas; Near-infrared; Competitive adaptive reweighted sampling; Wavelength selection
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Funding
- Chinese Scholarship Council (under UCD-CSC funding programme)
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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 (R-P(2)) 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 R-P(2) 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. (C) 2015 Elsevier Ltd. All rights reserved.
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