Please use this identifier to cite or link to this item:
Files in This Item:
File SizeFormat 
1-s2.0-S0023643822008131-main.pdf6,6 MBAdobe PDFView/Open
Title: Desirability-based optimization of bakery products containing pea, hemp and insect flours using mixture design methodology
Authors: Talens, Clara; Lago, Maider; Simó-Boyle, Laura; Odriozola-Serrano, Isabel; Ibarguen, Monica
Citation: LWT - Food Science & Technology, Volume 168, 1 October 2022, 113878
Abstract: Simplex lattice design was used to design 15 sponge cakes formulations combining pea (PP), hemp (HP) and insect (IP) flours representing 15% of dough composition. Moisture, protein content, baking loss, specific volume, texture and cost of the 15 samples plus the control (0% added protein) were analysed. Results showed that the effect of PP, HP and IP on cake properties could be modelled with linear regressions (96.80% < R2 < 99.96%). Ternary diagrams showed the effect of the combination of the three proteins in each response. The desirability function was used to obtain a multi-response optimization of the samples with maximum protein, maximum specific volume and minimum incremental cost. Sensory results of the 5 optimised samples showed that by combining 3.75% pea, 3.75% hemp and 7.5% insect it was possible to obtain a dairy- and egg-free sponge cake without significant differences from the control with animal-derived proteins.
Issue Date: 2022
Publisher: Elsevier
ISSN: 0023-6438
Appears in Publication types:Artículos científicos

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.