Rheological analysis in food processing: factors, applications, and future outlooks with machine learning integration | Synapse
January 25, 2026Open Access
Rheological analysis in food processing: factors, applications, and future outlooks with machine learning integration
Key Points
The aim is to explore how machine learning can improve rheological analysis in food processing.
Analyzed the role of machine learning in evaluating food texture and quality.
Investigated factors influencing food stability during processing.
Assessed applications of rheological analysis in quality assurance.
Machine learning provides in-depth insights into food texture and taste.
Improved methods for ensuring food quality and stability were identified.
Integration of AI in rheological processes shows promising potential for future applications.
Abstract
Integration of machine learning into rheological analysis provides meaningful insights on food texture, taste, stability, and overall quality, thereby further improving food processing and quality assurance.