Nondestructive Prediction of Moisture and Sodium Chloride in Cold Smoked Atlantic Salmon ( Salmo salar)
ABSTRACT: Salt and moisture contents in cold‐smoked salmon were determined using short‐wavelength near‐infrared (SW‐NIR) reflectance spectroscopy (600 to 1100 nm). Partial least square (PLS) regression models yielded the best results among 3 linear regression methods tested. Back‐propagation neural...
Published in: | Journal of Food Science |
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Main Authors: | , , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
Wiley
2002
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Subjects: | |
Online Access: | http://dx.doi.org/10.1111/j.1365-2621.2002.tb08773.x https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1111%2Fj.1365-2621.2002.tb08773.x http://onlinelibrary.wiley.com/wol1/doi/10.1111/j.1365-2621.2002.tb08773.x/fullpdf |
Summary: | ABSTRACT: Salt and moisture contents in cold‐smoked salmon were determined using short‐wavelength near‐infrared (SW‐NIR) reflectance spectroscopy (600 to 1100 nm). Partial least square (PLS) regression models yielded the best results among 3 linear regression methods tested. Back‐propagation neural networks (BPNN) exhibited a somewhat better capability to model salt and moisture concentrations (Salt: R 2 = 0.824, RMS = 0.55; Moisture: R 2 = 0.946, RMS = 2.44) than PLS (Salt: R 2 = 0.775, RMS = 0.63; Moisture: R 2 = 0.936, RMS = 2.65). Selection of samples from different axial locations on a fish did not affect the prediction error for salt or WPS but affected the prediction error for moisture. |
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