Three-dimensional printing technology can be used to develop futuristic novel functional foods. This study was conducted to formulate a multigrain dough and to establish optimal conditions through a detailed assessment of printability parameters for the development of 3D printed snacks. Multigrain flours were formulated using black rice flour (BRF), amaranth seed flour (ASF) and little millet flour (LMF) in varying proportions (w/w) of 50-80%, 10-30% and 10-30%, respectively. The composites were characterized using rheological analysis and in terms of their functional properties. A statistical design was used to determine the optimal 3D printing parameters, including nozzle diameter, extrusion rate, print speed and layer height. K-mean clustering and Pearson correlation analysis were conducted to study the interaction among printability factors and printing parameters. In rheological studies, the multigrain flours displayed a linear viscoelastic region of 0.1% to 1% shear strain, which suggested carbohydrate-instigated dilution of gluten protein. The composite with a BRF/ASF/LMF ratio of 50:30:20 was found have the most solid-like and enhanced elastic behaviour, which would be less susceptible to breakage and more extrudable. The 3D printing parameters significantly affected print fidelity (51.64%-99.68%), geometric deviations (0.79%-111.15%) and print weight (4.26 g-19.68 g). The optimum print was achieved at a 1.6 mm nozzle diameter, 120 pulse/µl extrusion rate, 7mm/s print speed and 1.2 mm layer height. This study holds promise for the mass customization and efficient extrusion of other gluten-free multigrain formulations with high dietary fiber and protein content.
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Assessing the properties of gluten-free flour for composite dough formulation and parametric analysis for the development of 3D-printed cookies
Published:
25 October 2024
by MDPI
in The 5th International Electronic Conference on Foods
session Innovation in Food Technology and Engineering
Abstract:
Keywords: Black rice; Rheological analysis; Functional analysis; 3D printing; Cluster analysis