Application of AI-Driven Multi-Dimensional Food Printing Technology for Valorization of Food By-Products
Yuchen Ma, Ling Fu, Fatao He, Di Wu, Y. S. Lin, Dejian Huang +2 more
Journal of Agricultural and Food Chemistry
Abstract
Food by-products are rich in nutrients but are often discarded, causing resource waste and environmental burden. Traditional additive manufacturing (AM) struggles with these materials due to inconsistent rheology, unstable transformations, and complex multiaxis operations. This review explores integrating machine learning (ML) with multidimensional food printing (FP) to valorize by-products. It highlights the use of animal-, plant-, and oilseed-based by-products in 3D printing and their functional transformation in 4D printing. ML enhances the AM pipeline by predicting rheology, optimizing formulations, and enabling real-time process control. It supports adaptive printing, deformation prediction, and closed-loop path adjustments for improved product quality. While 5D/6D printing remains em