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Noninvasive sensing of thermal treatments of J apanese seafood products using imaging spectroscopy
Author(s) -
ElMasry Gamal,
Nakauchi Shigeki
Publication year - 2015
Publication title -
international journal of food science and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.831
H-Index - 96
eISSN - 1365-2621
pISSN - 0950-5423
DOI - 10.1111/ijfs.12863
Subject(s) - spectroscopy , calibration , linear discriminant analysis , near infrared spectroscopy , core (optical fiber) , partial least squares regression , analytical chemistry (journal) , imaging spectroscopy , materials science , optics , chemistry , mathematics , statistics , physics , chromatography , quantum mechanics
Summary The potential of imaging spectroscopy for noncontact sensing of thermal treatments experienced on Japanese kamaboko was investigated. Samples were thermally treated at 100, 120, 140, 160, 180 and 200 °C to core temperatures of 45, 50, 55, 60, 65, 70, 75 and 80 °C and then promptly cooled and imaged in the short‐wave near infrared spectral range of 900–2500 nm. Partial least square ( PLS ) regression models were developed using the whole spectral range as well as using the most important wavelengths to predict the core temperature ( T C ) and thermal history ( TH ) yielding a reasonable level of accuracy of ( R P 2 = 0.86 and RMSEP = 3.9 °C) and ( R P 2 = 0.83 and RMSEP = 0.29 min), respectively. Moreover, a stepwise linear discriminant analysis ( LDA ) model was developed for identifying samples whose core temperatures reached a threshold of 65 °C. The LDA model yielded overall classification accuracy of 93.75% in both calibration and validation sets. The resulting discrimination function was then applied in a pixel‐wise manner to produce understandable classification maps to exhibit the difference among samples with high accuracy.