| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 10277666 | Journal of Food Engineering | 2013 | 5 Pages |
Abstract
⺠The rheological behavior of 34 commercial food dispersion is modeled. ⺠Artificial neuronal networks are used to successfully predict rheological properties. ⺠Increasing product database will improve predictive capabilities.
Related Topics
Physical Sciences and Engineering
Chemical Engineering
Chemical Engineering (General)
Authors
Jens Herrmann, Andrea Brito Alayón, Jon Trembley, Uwe Grupa,