Using an image processing based technique and predictive models for assessing lipid oxidation in rainbow trout fillet

作者：Kamani Mohammad Hassan^*; Safari Omid; Mortazavi Seyed Ali; Atash Masoomeh Mehraban Sang; Azghadi Naser Morgan

来源：Food Bioscience, 2017, 19: 42-48.

DOI：10.1016/j.fbio.2017.05.005

• Image processing
• Rainbow trout
• Shelf-life prediction
• Oncorhynchus mykiss

The potential of image processing techniques in combination with multivariate regression analysis was studied for prediction of the lipid oxidation of stored trout fillets at 4 degrees C. Fillet images were acquired using an imaging system during the time intervals of 0, 5, 10, 15 and 20 days and the means of colorimetric parameters (L*, a*, b*, C* and h*) were obtained from the images. The multivariate regression models were built using a stepwise regression algorithm for prediction of the oxidative attributes. The models did well predicting the contents of FFA, PV and TBARS with the coefficient of determination (R-adjusted(2)) of 0.66, 0.78 and 0.94, respectively. Among all measured colorimetric parameters, hue angle (h*) and lightness (L*) showed more significant contributions in the modeling analyses. Overall, image processing techniques in combination with predictive models may possibly be useful as a precise and non-destructive method for assessment of oxidation in rainbow trout.

• 出版日期2017-9