Three-Dimensional Printing Parameter Optimization for Salmon Gelatin Gels Using Artificial Neural Networks and Response Surface Methodology: Influence on Physicochemical and Digestibility Properties

Three-Dimensional Printing Parameter Optimization for Salmon Gelatin Gels Using Artificial Neural Networks and Response Surface Methodology: Influence on Physicochemical and Digestibility Properties

This study aimed to optimize the 3D printing parameters of salmon gelatin gels (SGG) using artificial neural networks with the genetic algorithm (ANN-GA) and response surface methodology (RSM). In addition, the influence of the optimal parameters obtained using the two different methodologies was ev...

Full description

Bibliographic Details
Main Authors: Nailín Carvajal-Mena, Gipsy Tabilo-Munizaga, Marleny D. A. Saldaña, Mario Pérez-Won, Carolina Herrera-Lavados, Roberto Lemus-Mondaca, Luis Moreno-Osorio
Format: Article
Language:English
Published: MDPI AG 2023-09-01
Series:Gels
Subjects:
salmon gelatin
3D printing
dimensional stability
artificial neural network
secondary structure
digestibility
Online Access:https://www.mdpi.com/2310-2861/9/9/766

Similar Items

Similar Items