1. – National Dairy Research Institute, Karnal, Haryana, India
2. – National Dairy Research Institute, Karnal, Haryana, India
| Received
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Accepted
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Published
10-Nov-2013 |
Abstract
Processed Cheese is one of the most popular varieties
among the types of cheeses. Radial Basis (Fewer
Neurons) and Multiple Linear Regression models were
developed for predicting the shelf life of processed
cheese stored at 7-8º C by taking body & texture,
aroma & flavour, moisture, free fatty acids as input
parameters, and sensory score as output parameter.
Mean square error, root mean square error, coefficient
of determination and Nash–Sutcliffe coefficient
were used for calculating the prediction capability of
the developed models. The comparison of the two
developed models revealed that the performance of
radial basis (fewer neurons) artificial neural network
model is better than that of statistical multiple linear
regression model for predicting the shelf life of
processed cheese.
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