Modelling and optimization of proximate and anti-nutritional composition of breakfast cereals produced from blends of millet, mungbean and tigernut flour using response surface methodology

A.U. Eweama, J.N. Nwosu, C.I. Owuamanam and S.o Obeleagu
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A.U. Eweama: Department of Food Science and Technology, Federal University of Technology Owerri, Imo state, Nigeria
J.N. Nwosu: Department of Food Science and Technology, Federal University of Technology Owerri, Imo state, Nigeria
C.I. Owuamanam: Department of Food Science and Technology, Federal University of Technology Owerri, Imo state, Nigeria
S.o Obeleagu: Department of Food Science and Technology, Federal University of Technology Owerri, Imo state, Nigeria

International Journal of Research and Scientific Innovation, 2021, vol. 8, issue 8, 103-118

Abstract: Three components augmented simplex centroid design of Response Surface Methodology (RSM) was applied to model and optimized the proximate and anti-nutritional composition of breakfast cereals produced from blends of millet, mungbean and tigernut flour. Blends were variously pre-treated, millet by soaking, mungbean by malting and tigernut by defatting. The experimental values were obtained and subjected to regression analysis to generate regression equations. The linear, binary and ternary effects of the blends were generated and graphically expressed on 3-D surface plots. The developed models were validated at p

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:bjc:journl:v:8:y:2022:i:8:p:103-118

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