The emerging world of 3D food printing is reviewed. Its role in food manufacturing, including benefits and impacts, underemphasized gastrophysical aspects, and limitations are discussed. Foods can be digitally designed and physically prepared using the layer-by-layer deposition of food components, unleashing opportunities to deliver nutritionally personalized food and new food-human interactions. Existing bottlenecks, under-researched gastropsychophysical aspects, and the lack of harmonized standards hindering its use for mass production are mentioned.

Since its conception, the application of 3D printing in the structuring of food materials has been focused on the processing of novel material formulations and customized textures for innovative food applications, such as personalized nutrition and full sensory design. The continuous evolution of the used methods, approaches, and materials has created a solid foundation for technology to process dynamic food structures. Four-dimensional food printing is an extension of 3D printing where food structures are designed and printed to perform time-dependent changes activated by internal or external stimuli. In 4D food printing, structures are engineered through material tailoring and custom designs to achieve a transformation from one configuration to another. Different engineered 4D behaviors include stimulated color change, shape morphing, and biological growth. As 4D food printing is considered an emerging application, imperatively, this article proposes new considerations and definitions in 4D food printing. Moreover, this article presents an overview of 4D food printing within the current scientific progress, status, and approaches.

One of the widely used materials in food printing is soy protein isolate (SPI) due to its functional and nutritional properties. However, a major printing drawback of SPI gels is network brittleness due to extensive aggregation leading to rheological properties that are unsuitable for printing. In this study, 0.4 %, 0.8 %, 1.2 %, 1.6 % and 2.0 % w/w milled psyllium husk and apple fibers were integrated into 20 % w/w SPI inks to improve the network properties and printability. Microstructural, textural, rheological properties and printability were investigated by microscopy, texture profile analysis, rheometry and image analysis. Incorporating psyllium husk fibers resulted in an interpenetrating protein-fiber network. This led to an increase in the network strength from 2155.8 Pa to 4228.15 Pa, relative to soy protein inks only, making them less susceptible to deformation during extrusion. Additionally, the geometrical deviation of the printed cubes decreased from 37.00 ± 4.55 % (length) and 24.00 ± 4.45 % (height) in the control inks to 13.86 ± 1.61 % and 24.86 ± 3.17 % respectively at psyllium husk concentration of 2.0 w/w %. The results showed that psyllium husk improved ink flexibility due to the high water-holding capacity of the fibers while maintaining structural integrity. This study revealed that the interpenetrating network effect of soluble dietary fibers in SPI inks improved printability while apple fibers with a high fraction of insoluble fibers embedded in a soy protein ink network caused printing defects. The findings highlight the potential to understand the influence of dietary fiber with varying physicochemical properties on 3D food printing of protein inks.

3‐dimensional printing is a novel processing method used for the design and manipulation of food textures. The systematic characterization and modulation of 3D printed food textures is imperative for the future design of sensory profiles using additive manufacturing. For 3D printed closed‐cell food foams, the clarification of the deformation behavior in relation to design parameters is of interest for the processing of customized food textures. For this reason, we studied the deformation behavior of 3D printed and thermally stabilized closed‐cell starch‐based foams beyond the elastic regime. Periodic spherical bubble configurations at different porosity levels were used to modulate the deformation behavior of the printed foams. From a processing perspective, the integration of in‐line thermal stabilization was used to eliminate post‐processing and to control the moisture content of the starch‐based system. Compression analysis combined with FEM simulations were performed to characterize the strain rate dependency of textural properties, the stress relaxation, and the foam's stress–strain behavior with respect to the design porosity and bubble distribution. Results showed that the stress relaxation is solely dependent on cell wall properties while different stress–strain regimes showed distinct dependencies on design parameters such as bubble size and distribution. Consequently, the precise control of the large deformation behavior of foods using 3D printing is challenging due to the superposition of structural and geometrical dependencies. Finally, through the presented approach, the structure‐deformation relations of 3D printed closed‐cell food structures are adequately described.

Undesired dough adhesion is still a challenge during the production of baked goods. There are various methods for determining the adhesive texture properties of dough. In the majority of scientific papers, dough stickiness is measured analytically by the force‐distance recording of dough detachment. In this study, we describe a new multi‐scale approach to compare dough adhesion phenomena in a laboratory, pilot sale and human sensory assessment. In it, the adhesive material properties of dough were investigated using a pilot scale toppling device representing dough adhesion behavior in the production process, in the laboratory by texture analysis with the Chen–Hoseney method and furthermore with a new, implemented non‐oral human sensory analysis. To simulate different dough adhesion behavior, the dough mechanical and adhesion properties were varied by applying dough‐modifying enzymes and different dough storage times. The structural changes in the different wheat dough system were compared by rheological characterization. By characterizing the different adhesion phenomena of the doughs, the sample with bacterial xylanase showed the highest values after 80 min of storage time in all three methods. Correlation analysis revealed a strong relationship between the detachment time (pilot scale) and human sensory assessment attributes (Force R = 0.81, Time R = 0.87, Distance R = 0.92, Stickiness R = 0.80) after 80 min of storage time. Even though human sensory assessment showed limits in the detectability of differences in dough adhesion behavior compared to the Chen–Hoseney method, it was better suited to predict machinability.