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Frying of the Dispersion Droplets with Varying Contents of Chickpea Flour and Gum Arabic: Product Characterization and Modeling.

Shanthilal, J. and Baby Latha, R. and Navya, M. C. and Chakkaravarthi, A. and Suvendu, Bhattacharya (2018) Frying of the Dispersion Droplets with Varying Contents of Chickpea Flour and Gum Arabic: Product Characterization and Modeling. Journal of Food Science, 83 (3). pp. 648-660. ISSN 0022-1147

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Dispersions having chickpea (37%, 40%, and 43%, w/w) and gum arabic (0%, 1%, 2%, 3%, 4%, and 5%, w/w) solids were prepared. These dispersion droplets were fried, and the physical, sensory, and microstructural characteristics of the fried products were determined. The oil content in the fried snack decreased up to 20.3% when the level of chickpea and/or gum in the dispersions was increased. The compression curve for fried snack showed 5 major zones and exhibited the failure phenomenon. Failure force (6.5 to 11.4 N) increased with chickpea flour in the dispersions. Fracture strain (12.0% to 19.5%) indicated that all the fried samples were soft-crisp products. An increase in chickpea flour concentration offered an ovoid/oblong shape of dispersion droplets while falling to oil, and changed the spherical shape of the fried snack. The near-spherical product could be obtained by using 37% chickpea flour containing 0 to 2% of gum arabic, or with the 40% and 0 to 1% combinations. The hue or dominant wavelength increased from 578.5 nm (flour) to 581.0 to 582.7 nm (product) indicating a shift toward red coloration. A porous microstructure with scattered small cavities and large vacuoles of the fried snack were observed; big vacuoles were located in the inner portion of the fried product. The cells were divided into closed and open cells and were characterized by image analysis. The air cells usually had an elliptical shape with varying sizes; the cell wall thickness was between 12 and 80 μm. An artificial neural network (ANN) structure of 2-9-2 was developed for the prediction of sensory overall acceptability and oil content of the fried snack.

Item Type: Article
Uncontrolled Keywords: artificial neural network, frying, gum arabic, microstructure, texture
Subjects: 600 Technology > 08 Food technology > 14 Physical properties > 05 Texture
600 Technology > 08 Food technology > 18 Processed foods
600 Technology > 08 Food technology > 22 Legumes-Pulses
Divisions: Food Engineering
Food Packaging Technology
Depositing User: Food Sci. & Technol. Information Services
Date Deposited: 04 Jul 2018 10:31
Last Modified: 04 Jul 2018 10:31
URI: http://ir.cftri.com/id/eprint/13579

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