期刊
FOOD CHEMISTRY
卷 156, 期 -, 页码 394-401出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.foodchem.2014.01.118
关键词
Drip loss; pH; Fish; Salmon; Hyperspectral imaging; Imaging spectroscopy; Partial least square regression (PLSR)
资金
- Irish Research Council for Science, Engineering and Technology under the Government of Ireland Postdoctoral Fellowship scheme
- Chinese Scholarship Council (under UCD-CSC funding programme)
Drip loss and pH are important indices in quality assessment of salmon products. This work was carried out for rapid and non-destructive determination of drip loss and pH distribution in salmon fillets using near-infrared (Vis-NIR) hyperspectral imaging. Hyperspectral images were acquired for salmon fillet samples and their spectral signatures in the 400-1700 nm range were extracted. Partial least square regression (PLSR) was used to correlate the spectra with reference drip loss and pH values. Important wavelengths were selected using the regression coefficients method to develop new PLSR models, leading to a correlation coefficient of cross-validation (r(cv)) of 0.834 with root-mean-square errors by cross-validation (RMSECV) of 0.067 for drip loss and a rcv of 0.877 with RMSECV of 0.046 for pH, respectively. Distribution maps of drip loss and pH were generated based on the new PLSR models using image processing algorithms. The results showed that Vis-NIR hyperspectral imaging technique combined with PLSR calibration analysis offers an effective quantitative capability for determining the spatial distribution of drip loss and pH in salmon fillets. (C) 2014 Elsevier Ltd. All rights reserved.
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