Dataset Information

3D Food Printing: Principles of Obtaining Digitally-Designed Nourishment.

ABSTRACT: Three-dimensional printing (3DP) technology gained significance in the fields of medicine, engineering, the food industry, and molecular gastronomy. 3D food printing (3DFP) has the main objective of tailored food manufacturing, both in terms of sensory properties and nutritional content. Additionally, global challenges like food-waste reduction could be addressed through this technology by improving process parameters and by sustainable use of ingredients, including the incorporation of recovered nutrients from agro-industrial by-products in printed nourishment. The aim of the present review is to highlight the implementation of 3DFP in personalized nutrition, considering the technology applied, the texture and structure of the final product, and the integrated constituents like binding/coloring agents and fortifying ingredients, in order to reach general acceptance of the consumer. Personalized 3DFP refers to special dietary necessities and can be promising to prevent different non-communicable diseases through improved functional food products, containing bioactive compounds like proteins, antioxidants, phytonutrients, and/or probiotics.

SUBMITTER: Varvara RA

PROVIDER: S-EPMC8541666 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature

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3D Food Printing: Principles of Obtaining Digitally-Designed Nourishment.

Varvara Rodica-Anita RA Szabo Katalin K Vodnar Dan Cristian DC

Nutrients 20211015 10

Three-dimensional printing (3DP) technology gained significance in the fields of medicine, engineering, the food industry, and molecular gastronomy. 3D food printing (3DFP) has the main objective of tailored food manufacturing, both in terms of sensory properties and nutritional content. Additionally, global challenges like food-waste reduction could be addressed through this technology by improving process parameters and by sustainable use of ingredients, including the incorporation of recovere ...[more]

PMID: 34684618

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Project description:To develop an algorithm for computing realistic digitally reconstructed radiographs (DRRs) that match real cone-beam CT (CBCT) projections with no artificial adjustments.The authors used measured attenuation data from cone-beam CT projection radiographs of different materials to obtain a function to convert CT number to linear attenuation coefficient (LAC). The effects of scatter, beam hardening, and veiling glare were first removed from the attenuation data. Using this conversion function the authors calculated the line integral of LAC through a CT along rays connecting the radiation source and detector pixels with a ray-tracing algorithm, producing raw DRRs. The effects of scatter, beam hardening, and veiling glare were then included in the DRRs through postprocessing.The authors compared actual CBCT projections to DRRs produced with all corrections (scatter, beam hardening, and veiling glare) and to uncorrected DRRs. Algorithm accuracy was assessed through visual comparison of projections and DRRs, pixel intensity comparisons, intensity histogram comparisons, and correlation plots of DRR-to-projection pixel intensities. In general, the fully corrected algorithm provided a small but nontrivial improvement in accuracy over the uncorrected algorithm. The authors also investigated both measurement- and computation-based methods for determining the beam hardening correction, and found the computation-based method to be superior, as it accounted for nonuniform bowtie filter thickness. The authors benchmarked the algorithm for speed and found that it produced DRRs in about 0.35 s for full detector and CT resolution at a ray step-size of 0.5 mm.The authors have demonstrated a DRR algorithm calculated from first principles that accounts for scatter, beam hardening, and veiling glare in order to produce accurate DRRs. The algorithm is computationally efficient, making it a good candidate for iterative CT reconstruction techniques that require a data fidelity term based on the matching of DRRs and projections.

Dataset Information

3D Food Printing: Principles of Obtaining Digitally-Designed Nourishment.

Publications

3D Food Printing: Principles of Obtaining Digitally-Designed Nourishment.

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