Novel strategy for optimizing of corn starch-based ink food 3D printing process: Printability prediction based on BP-ANN model.

Journal: International journal of biological macromolecules
PMID:

Abstract

Although starch has been intensively studied as a raw material for 3D printing, the relationship between several important process parameters in the preparation of starch gels and the printing results is unclear. In this study, the relationship between different processing conditions and the gel printing performance of corn starch was evaluated by printing tests, rheological tests and low-field nuclear magnetic resonance (LF-NMR) tests, and a back-propagation artificial neural network (BP-ANN) model for predicting gel printing performance was developed. The results revealed that starch gels exhibited favorable printing performance when the gelatinization temperature ranged from 75 °C to 85 °C, and the starch content was maintained between 15 % and 20 %. The R of the BP-ANN models were all reached 0.894, which indicated good predictive ability. The results of the study not only provide theoretical support for the application of corn starch gels in 3D food printing, but also present a novel approach for predicting the printing performance of related materials. This method contributes to the optimization of printing parameters, thereby enhancing printing efficiency and quality.

Authors

  • Xueyuan Jiao
    College of Food and Bioengineering, Henan University of Science and Technology, 471000 Luoyang, China.
  • Guangyue Ren
    College of Food and Bioengineering, Henan University of Science and Technology, 471000 Luoyang, China. Electronic address: rgy@haust.edu.cn.
  • Chung Lim Law
    Department of Chemical and Environmental Engineering, Malaysia Campus, University of Nottingham, Semenyih 43500, Selangor, Malaysia.
  • Linlin Li
    Department of Clinical Pharmacy, School of Pharmacy, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai'an, Shandong, 271016, China.
  • Weiwei Cao
    School of Biomedical Engineering (Suzhou), University of Science and Technology of China, Division of Life Sciences and Medicine, Hefei, 230026, Anhui, China.
  • Zhenjiang Luo
    R&D Center, Haitong Ninghai Foods Co., Ltd., Ninghai, Zhejiang, China.
  • Lifeng Pan
    R&D Center, Haitong Ninghai Foods Co., Ltd., Ninghai, Zhejiang, China.
  • Xu Duan
    College of Food and Bioengineering, Henan University of Science and Technology, 471000 Luoyang, China.
  • Junliang Chen
    College of Food and Bioengineering, Henan University of Science and Technology, Luoyang 471023, China.
  • Wenchao Liu
    College of Food and Bioengineering, Henan University of Science and Technology, 471000 Luoyang, China; Postdoctoral Practice Innovation Base, Luohe Vocational Technology College, 462002 Luohe, China; Henan Nanjiecun (Group) Co., Ltd., 462600 Linying, China. Electronic address: wen_chaoliu@163.com.