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| Main Authors: | , |
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| Format: | Preprint |
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2026
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| Online Access: | https://arxiv.org/abs/2603.22887 |
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| _version_ | 1866910129877680128 |
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| author | Miyatake, Yamato Punpongsanon, Parinya |
| author_facet | Miyatake, Yamato Punpongsanon, Parinya |
| contents | 3D food printing enables the customization of food shapes and textures, but typically produces uniform taste profiles due to the limited diversity of printable materials. We present TastePrint, a 3D food printing system that achieves layer-wise spatial taste distribution by dynamically applying liquid seasonings with a programmable airbrush during fabrication. The system integrates (1) a graphical user interface (GUI) that allows users to import 3D models, slice them into layers, and specify seasoning channels, spray positions, and intensities, and (2) a customized 3D food printer equipped with a multi-nozzle spray mechanism. We evaluated the system through technical experiments quantifying spray resolution and deposition accuracy, a minimal sensory discrimination study on taste localization, and an exploratory formative user-feedback study involving three home cooks. The spray-resolution model achieved $R^2 = 0.86$, and the spray-amount model achieved $R^2 = 0.99$. The filter-paper calibration showed broad consistency with measurements obtained on edible mashed-potato samples. In the sensory discrimination study, participants identified the centralized seasoning pattern as more localized in 27 of 40 trials (67.5 %). These findings indicate that TastePrint can provide repeatable hardware-level control over seasoning placement and quantity while offering initial evidence that spatial taste arrangement can remain perceptually meaningful after fabrication. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_22887 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | TastePrint: A 3D Food Printing System for Layer-wise Taste Distribution via Airbrushed Liquid Seasoning Miyatake, Yamato Punpongsanon, Parinya Human-Computer Interaction 3D food printing enables the customization of food shapes and textures, but typically produces uniform taste profiles due to the limited diversity of printable materials. We present TastePrint, a 3D food printing system that achieves layer-wise spatial taste distribution by dynamically applying liquid seasonings with a programmable airbrush during fabrication. The system integrates (1) a graphical user interface (GUI) that allows users to import 3D models, slice them into layers, and specify seasoning channels, spray positions, and intensities, and (2) a customized 3D food printer equipped with a multi-nozzle spray mechanism. We evaluated the system through technical experiments quantifying spray resolution and deposition accuracy, a minimal sensory discrimination study on taste localization, and an exploratory formative user-feedback study involving three home cooks. The spray-resolution model achieved $R^2 = 0.86$, and the spray-amount model achieved $R^2 = 0.99$. The filter-paper calibration showed broad consistency with measurements obtained on edible mashed-potato samples. In the sensory discrimination study, participants identified the centralized seasoning pattern as more localized in 27 of 40 trials (67.5 %). These findings indicate that TastePrint can provide repeatable hardware-level control over seasoning placement and quantity while offering initial evidence that spatial taste arrangement can remain perceptually meaningful after fabrication. |
| title | TastePrint: A 3D Food Printing System for Layer-wise Taste Distribution via Airbrushed Liquid Seasoning |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2603.22887 |