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Material requirements for printing cookie dough using a fused deposition modeling 3D printer

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Abstract

This study examined the requirements for using flour-based formulations in fused deposition modeling (FDM) of cone-shaped cookie dough. By considering the requirements of fidelity, shape retention, and extrudability, the rheological and mechanical parameters, which resulted in high printability (93.88‒96.49%) and dimensional stability (96.36‒97.15%), for formulations containing soft wheat flour, granulated sugar, water, and olive oil were determined to be: storage modulus (G′) of 7165‒12,590 Pa, loss modulus (G″) of 4161‒8297 Pa, shear modulus of 6613‒12,804 Pa, yield stress (τ0) of 50.22‒72.80 Pa, phase angle of 30.28‒33.52°, apparent viscosity of 181.25‒230.20 Pa·s, and hardness of 0.65–0.91 N. When olive oil and water were replaced with butter and egg, the formulations demonstrated higher values of G′, G″, shear modulus, τ0, and hardness; a smaller phase angle; and a wider range of apparent viscosity. These results provide quantitative information for developing cookie dough formulations suitable for 3D printing by FDM.

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Acknowledgements

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2019R1F1A1056308) and by Korea Institute of Planning and Evaluation for Technology in Food, Agriculture and Forestry (IPET) through High Value-added Food Technology Development Program, funded by Ministry of Agriculture, Food and Rural Affairs (MAFRA) (321047-03).

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  1. Jiwon In and Ha Eun Jeong have equally contributed to this work.

Authors and Affiliations

  1. Department of Food Science and Technology, Seoul Women’s University, 621, Hwarangro, Nowon-gu, Seoul, 01797, Republic of Korea

    Jiwon In, Haeun Jeong & Sea Cheol Min

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  1. Jiwon In
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  2. Haeun Jeong
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  3. Sea Cheol Min
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Correspondence to Sea Cheol Min.

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In, J., Jeong, H. & Min, S.C. Material requirements for printing cookie dough using a fused deposition modeling 3D printer. Food Sci Biotechnol 31, 807–817 (2022). https://doi.org/10.1007/s10068-022-01092-1

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  • DOI: https://doi.org/10.1007/s10068-022-01092-1

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