Preparing a Personalized Meal by Using Soy, Cricket, and Egg Albumin Protein Based on 3D Printing

Recently, personalized meals and customized food design by means of 3D printing technology have been considered over traditional food manufacturing methods. This study examined the effects of different proteins (soy, cricket, and egg albumin protein) in two concentrations (3% and 5%) on rheological,...

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Bibliographic Details
Published in:Foods 2022-07, Vol.11 (15), p.2244
Main Authors: Mirazimi, Farnaz, Saldo, Jordi, Sepulcre, Francesc, Gràcia, Alvar, Pujolà, Montserrat
Format: Article
Language:English
Subjects:
3-D printers
3D food printing
Albumin
Albumins
Amino acids
Backward extrusion
Customization
Eggs
Food products
Food science
Formulations
fortified food
Loss modulus
Meals
Multilayers
Nutrition
Printing
Processed foods
Product development
Production methods
Production processes
protein
Proteins
Rheological properties
Rheology
Storage modulus
texture
Three dimensional printing
Traditional foods
Viscosity
Yield stress
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Summary:Recently, personalized meals and customized food design by means of 3D printing technology have been considered over traditional food manufacturing methods. This study examined the effects of different proteins (soy, cricket, and egg albumin protein) in two concentrations (3% and 5%) on rheological, textural, and 3D printing characteristics. The textural and microstructural properties of different formulations were evaluated and compared. The addition of soy and cricket protein induced an increase in yield stress (τ₀), storage modulus (G′), and loss modulus (G″) while egg albumin protein decreased these parameters. The textural analysis (back extrusion and force of extrusion) demonstrated the relationship between increasing the amount of protein in the formula with an improvement in consistency and index of viscosity. These values showed a straight correlation with the printability of fortified formulas. 3D printing of the different formulas revealed that soy and cricket proteins allow the targeting of complex geometry with multilayers.
ISSN:2304-8158
2304-8158
DOI:10.3390/foods11152244