Optimisation of Physical Properties of Ready to Cook Fish Incorporated Noodles using Response Surface Methodology
Optimisation of Physical Properties of Ready to Cook Fish Incorporated Noodles using Response Surface Methodology
Date
2015
Authors
Kamalakanth, C.K.
Gopal, T.K.S.
Joshy, C.G.
Ginson, J. J.
Ravishankar, C.N.
Journal Title
Journal ISSN
Volume Title
Publisher
Central Institute of Fisheries Technology, Cochin, India
Abstract
Combination of fish mince and refined wheat flour was optimized for the development of fish incorporated noodles by using response surface methodology. Effect of different level of pink perch (Nemipterus japonicus) mince on physical properties like water
absorption index, bulk density, colour values, cooking time, cooking loss, rehydration test, shearing strength and sensory score were evaluated. D-optimal mixture experimental design with 9 runs was formulated to optimize the different levels of fish
mince and refined wheat flour. Linear, quadratic and cubic mixture polynomial regression was fitted to the experimental data and appropriate model was selected
based on highest goodness of fit values (R2). From the analysis, it was found that water absorption index decreased as the percentage of fish mince increased. Bulk density reduced and found to be maximum for fish incorporated noodles. Lightness reduced as fish concentration was increased, whereas a* and b* values were found to increase. Cooking time increased significantly as the percentage of fish mince increased; whereas, cooking loss was found to decrease on incorporation of fish mince to noodles.
Rehydration test values were good for 10 and 15% fish mince incorporated samples. There was a decrease in shearing strength after 10% fish incorporated sample.
Based on the desirability function calculation of multiple response samples, 15% fish mince incorporated samples were found most acceptable based on the physical properties and sensory score.
Description
Keywords
Extrusion, fish mince, noodles, response surface methodology, desirability function
Citation
Fishery Technology 2015: 52 (2), 109 - 117