Texture profile analysis and stress relaxation characteristics of protein fortified sweetpotato noodles.

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2019
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Abstract
The mechanical stress relaxation and textual characteristics of starch noodles supplemented with soybean protein concentrate (SPC) was studied with an Instron texture analyzer. Noodles strength was observed to increase significantly with increased in SPC concentration from 0 to 20%. Noodles (ES30) formulated with the esterified starch and 30% SPC substitution had the highest deformation modulus index, initial break force, and maximum break force. The stress relaxation data was well fitted by the Maxwell and Peleg-Normand models though the latter was the most suited. The fitted parameters, F and λ had a higher sensitivity to changes in its viscoelastic properties when compared to k or %SR. A significant correlation was established between the stress relaxation index and textural parameters. The result of this study suggests that starch noodles with enhanced textural and break force characteristics can be formulated with 10-20% SPC substitution. PRACTICAL APPLICATIONS: Dried noodles are formulated from raw noodles which have been dehydrated either by hot-air drying or natural drying. It has the advantages of being low-cost, easy to cook, and longer shelf-life. Consumer's acceptance of cooked noodles depends majorly on its textural properties such as its elasticity, hardness, and smoothness. The extent of noodles hardness and its breakpoint features are an influencer of noodles breakage during packaging and shipping. The determination of modeling parameters describing these physical characteristics can help in the production of noodles with improved breakpoint index, textural features, and quality. Therefore, the effects of different percentage of SPC supplementation on the break force and stress relaxation characteristics of noodles formulated from sweet potato starch were evaluated in the present study.
Reference Key
kadiri2019texturejournal Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Kadiri, Oseni;Gbadamosi, Saka O;Akanbi, Charles T;
Journal journal of texture studies
Year 2019
DOI
10.1111/jtxs.12493
URL
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