Abstract

Printing food consists of translating any idea of shape, dimension and internal architecture into a digital model, which may be replicated to get tangible food products. An intriguing and novel approach to use 3D printing – already used in the medical fields – is the mimicking of morphological properties of biological tissues aiming to replicate their unique functionalities. For the first time, we explored this approach and by utilizing the main morphological information of apple tissue contained in the microtomographic images we have generated innovative 3D printed snacks inspired by the plant tissues. While the morphologies of the printed sample satisfactorily matched the virtual model, the porosity fraction significantly changes from ∼15% of the apple tissue to 14.4%–18.2% for printed dough and to 41.93%–45.90% for the baked snacks. Hardness increased from 0.69 N to 11.25 as a function of the number of layers while the Young's modulus did not change significantly from 20.73 to 31.84 MPa for 2 to 6 layers. Our results proved the capability of 3D printing to reproduce the salient features of apple tissue microstructure; also, after defining the main mechanical properties of the reference materials, we modelled the texture properties of 3D printed samples with sufficient agreement with the estimated and experimental data. Our results proved the capability of 3D printing to reproduce the salient features of apple tissue microstructure; also, after defining the main mechanical properties of the reference materials, we modelled the texture properties of 3D printed samples with sufficient agreement with the estimated and experimental data. • A digital replica of the apple tissue was used to create innovative multi-layered cereal-based snacks. • 3D food printing was used to replicate faithfully the main morphological properties of the vegetable tissue. • A Finite Element Model was used to predict the mechanical properties of the snacks. • The estimated Young's modulus satisfactorily matched the experimental data.

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