Optimization of Proximate and Minerals Compositions of Sweet Potato, Soybean and Rice Bran Composite Flours for Production of Low Glycemic Index Dough Meal

Authors

  • Awolu, O.O. Department of Food Science and Technology, Federal University of Technology, Akure, Nigeria. https://orcid.org/0000-0002-5499-1888
  • Ajibola, C.F. Department of Food Science and Technology, Federal University of Technology, Akure, Nigeria.
  • Adeloye, J.B. Department of Food Science and Technology, Federal University of Technology, Akure, Nigeria.
  • Ogwu, F. Department of Food Science and Technology, Federal University of Technology, Akure, Nigeria.

DOI:

https://doi.org/10.20448/journal.512.2020.71.79.88

Keywords:

Dough meal, Fibre, Glycemic index, Optimisation, Protein.

Abstract

Dough meal with low glycemic index was produced from sweet potato, soy bean and rice bran composite flours. Effect of the composite flour samples on the glycemic index, as well as proximate and minerals composition of the dough meal were optimised using optimal mixture design of response surface methodology. The dough meal had considerably high protein and fibre contents. The moisture and ash contents were low. The results indicated that the addition of sweet potato enhances the minerals composition, while soybean and rice bran had highest effect on the protein and fibre contents respectively. The results of the optimisation showed that the dough meal had glycemic index, meaning that the dough meal prepared from sweet potato (65.0-85.0 g/100g), soy bean (10.0-25.0 g/100g) and rice bran (2.5-10.0 g/100g) had acceptable glycemic index. The dough meal with 75.00 g/100g sweet potato flour, 15.00 g/100g soybean meal flour and 10.00 g/100g rice bran flour, however had the lowest glycemic index.

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Published

2020-05-18

How to Cite

O.O., A., C.F., A., J.B., A., & F., O. (2020). Optimization of Proximate and Minerals Compositions of Sweet Potato, Soybean and Rice Bran Composite Flours for Production of Low Glycemic Index Dough Meal. Agriculture and Food Sciences Research, 7(1), 79–88. https://doi.org/10.20448/journal.512.2020.71.79.88

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Articles