Abstract
Time–delay artificial neural network (ANN) single layer and multilayer artificial models were developed for predicting the shelf life of processed cheese stored at 7-8o C. Soluble nitrogen, pH; standard plate count, yeast & mould count, and spore count were input variables, and sensory score was output variable. The results showed excellent agreement between training and validation data with high coefficient of determination and nash sutcliffo coefficient, thus suggesting that the developed models are good for predicting the shelf life of processed cheese.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
More From: Journal of Advanced Computer Science & Technology
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.