Artificial Neural Expert Computing Models for Determining Shelf Life of Processed Cheese

SUMIT GOYAL, Gyanendra Kumar Goyal


Time-delay single and multi layer models were developed for predicting shelf life of processed cheese stored at 30oC. Processed cheese is very nutritious dairy product, rich in milk proteins and milk fat. For developing computational neuroscience models,experimental data relating to body & texture, aroma & flavour, moisture, free fatty acids were taken as input variables, while sensory score as output variable. Mean Square Error, Root Mean Square Error, Coefficient of determination and Nash - Sutcliffo Coefficient were applied in order to compare the prediction performance of the developed computational models. The results of the study established excellent correlation between experimental data and the predicted values, with a high determination coefficient. From the study it was concluded that artificial neural expert time-delay models are good for predicting the shelf life of processed cheese.



Artificial Neural Network; Shelf Life Prediction, Time-Delay, Processed Cheese; Central Nervous System

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International Journal of Electrical and Computer Engineering (IJECE)
p-ISSN 2088-8708, e-ISSN 2722-2578