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Processing and optimisation of complementary food blends from roasted pearl millet (Pennisetum glaucum) and soybean (Glycine max) using response surface modeling

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Abstract

Adequate nutrition is vital during infancy but the high cost of supplemented infant formulae has forced inhabitants of Central and West Africa to depend solely on low-nutrient gruels. Response Surface modelling was used to process a complementary food from roasted pearl millet and Soybean flour. A central composite design was adopted to study the effects of feed composition X1 (5.86–34.14%) and roasting temperature X2 (126–154 °C) on the micronutrients, functional, and sensory profiles of the different blends. The responses were significantly (p < 0.05) affected by the independent factors. For the vitamins in mg/100 g, the thiamin, riboflavin, folate, and β-carotene content ranged from 0.17–0.33, 24–53.50, 1.32–2.29, and 7–22.98, respectively. For the minerals in mg/100 g, the zinc, calcium, potassium, and iron content ranged from 0.35–0.54, 39.5–62.75, 1.2–1.8, and 0.017–0.18, respectively. The viscosity, bulk density, swelling capacity, water absorption capacity, and pH ranged from 1577.5–942.5 cP, 0.74–0.79 g/cm3, 0.10–0.30 ml/g, 1.2–1.4 ml/g, and 4.70–5.70, respectively. The sensory scores were rated highly by the panelists. The optimum processing conditions with a desirability of 0.50 gave 29.28% and 130.39 °C feed composition and roasting temperature, respectively.

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Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

This work was supported by the Alexander von Humboldt Foundation (AvH), the German Ministry of Education and Research (BMBF) and the African-German Network of Excellence in Science (AGNES)

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OEC: Conceptualization (lead); Data curation (equal); Methodology (equal); Resources (equal); Software (equal); Validation (equal); Writing–original draft (equal). Supervision (lead); ECO: Investigation (lead); Project administration (lead); Visualization (equal); Writing—original draft (equal); Resources (lead) ECR: Project administration (equal); Supervision (equal); Validation (equal); Visualization (equal); Writing—original draft (equal); Writing—review and editing (equal). UEC: Methodology (equal); Writing–original draft (equal): Resources (equal): Writing—review and editing (equal). AMM: Writing–review and editing (lead): Data curation (equal); Validation (equal); Software (lead).

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Correspondence to Mumukom Maximus Anchang.

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Appendix 1: Pictorial representation of the complementary foods

Appendix 1: Pictorial representation of the complementary foods

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Omah, E.C., Eze, C.O., Eze, C.R. et al. Processing and optimisation of complementary food blends from roasted pearl millet (Pennisetum glaucum) and soybean (Glycine max) using response surface modeling. J Food Sci Technol 59, 4273–4287 (2022). https://doi.org/10.1007/s13197-022-05494-1

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