This study investigated the potential of using hyperspectral imaging technology (900-1700 nm) to determine the thiobarbituric acid (TBA) value and pH for evaluation of lipid oxidation in Atlantic salmon (Salmo solar) fillets during cold storage for 0, 3, 6, 9 and 12 days at 1 +/- 1 degrees C. Good results were achieved for both parameters by using partial least square regression (PLR) calibration models with full spectral region. Two simplified models were then built by using forward stepwise-multiple linear regression (MLR) variable selection method to select 18 and 10 most important wavelengths for TBA value and pH, respectively. The optimised stepwise-MLR model for TBA value yielded satisfactory results with correlation coefficient (r(C)) of 0.921 and root mean square error of calibration (RMSEC) of 1.840 mu mol MDA/kg fish. This model was used to visualise the TBA value distributions during different storage days. Further improvements were achieved by applying particle analysis on the images to extract only the spectra from white stripes in salmon fillet. When in tandem with detrend pre-processing technique, the calibration model based on particle analysis demonstrated the best performance for TBA value prediction (r(C) = 0.957 and RMSEC = 1.449 mu mol MDA/kg). In addition, a novel chemometric strategy accomplished by the use of hyperspectrograms was also proposed in this work and satisfactory results were obtained. The overall results confirmed the capability of near-infrared hyperspectral imaging as a rapid and non-invasive technique to monitor lipid oxidation in salmon fillets. (C) 2015 Elsevier Ltd. All rights reserved.