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Journal Articles LWT - Food Science and Technology Year : 2024

Nutritional optimization through linear programming of climate-smart and gluten free pasta

Abstract

Designing food formulations is an important approach to meet a set of nutritional needs and to address malnutrition issues. Linear programming is an appropriate tool for designing novel nutritionally optimized formulations based on a combination of gluten-free climate-smart crops. Four nutritionally optimized cowpea-based pasta formulations in association or not with teff and/or amaranth leaves (AL) were designed to meet a woman's protein requirements in terms of quantity and quality, fibers, ω6/ω3, iron, zinc and B9 vitamin, while limiting antinutritional factors such as phytates. To predict the processability of the flours into pasta and the visual acceptance of future pasta by consumers, the antioxidant and oxidant capacities of flours were measured and their color compared with the color of durum wheat semolina (DWS). The formulation combining cowpea and AL had the highest nutritional composition and lowest impact of phytates. The formulation with cowpea, teff and AL seems to be the easiest to process thanks to its lower lipoxygenase activity and the higher antioxidant capacity, followed by the teff-cowpea formulation. The color of the formulation that only contained cowpea was closest to DWS.
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licence : CC BY NC ND - Attribution - NonCommercial - NoDerivatives

Dates and versions

hal-04489378 , version 1 (05-03-2024)

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Attribution - NonCommercial - NoDerivatives

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Pauline Pinel, Sophie Drogué, Marie-Josephe Amiot, Clothilde Vannier, Claire Bourlieu-Lacanal, et al.. Nutritional optimization through linear programming of climate-smart and gluten free pasta. LWT - Food Science and Technology, 2024, 197, pp.115899. ⟨10.1016/j.lwt.2024.115899⟩. ⟨hal-04489378⟩
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