Food and Bioprocess Technology

, Volume 12, Issue 7, pp 1185–1196 | Cite as

Assessing the 3D Printing Precision and Texture Properties of Brown Rice Induced by Infill Levels and Printing Variables

  • Meng-sha Huang
  • Min ZhangEmail author
  • Bhesh Bhandari
Original Paper


Three-dimensional (3D) printing is an emerging technology that can be applied to processing of wide range of food products. The aim of this paper was to assess the printability of brown rice and evaluate the effects of the three variables: nozzle size (0.84 mm, 1.20 mm, 1.56 mm), perimeters (3, 5, 7), and infill densities (15%, 45%, 75%) on the quality attributes of 3D printed samples. The dimensional properties, height and diameter, were used to evaluate the printing precision, and the texture properties were assessed as hardness and gumminess. Results indicated that the printed samples matched the designed one reasonably well with some deviations in dimension induced by the three variables. The nozzle size and perimeters both have effects on the dimensional properties of 3D printed samples, and the infill density has no effect on that. With the decrease of nozzle size from 1.56 to 0.84 mm, both height and diameter of printed samples are more closely to the designed ones, which means smaller size of nozzle has a good performance on the dimensional properties of 3D printed samples. The texture properties (hardness and gumminess) were strongly related to infill density, followed by perimeters and nozzle size, while the nozzle size was thought to not only change the void rate, but also change the number of layers deposited which indirectly affected the texture characteristics. Besides, the printing time can be reduced a lot due to the decrease of void rate, which suggests a good way to improve the efficiency of printing and reduce the hardness through creating internal structure.


3D food printing Brown rice paste Variables Dimensional properties Printing time Texture 



The authors acknowledge the measurement support from Prof. Ronghua Ju of Nanjing Forestry University.

Funding Information

The authors received financial support from the National Natural Science Foundation Program of China (No. 3187101297), China State Key Laboratory of Food Science and Technology Innovation Project (Contract No. SKLF-ZZA-201706), National First-class Discipline Program of Food Science and Technology (No. JUFSTR20180205), and Jiangsu Province Key Laboratory Project of Advanced Food Manufacturing Equipment and Technology (No. FMZ201803), which enabled us to carry out this study.


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© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.State Key Laboratory of Food Science and TechnologyJiangnan UniversityWuxiChina
  2. 2.Jiangsu Province Key Laboratory of Advanced Food Manufacturing Equipment and TechnologyJiangnan UniversityWuxiChina
  3. 3.International Joint Laboratory on Food SafetyJiangnan UniversityWuxiChina
  4. 4.School of Agriculture and Food SciencesThe University of QueenslandBrisbaneAustralia

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