Khoa is very popular milk product used to make variety of sweets in India. Khoa is made by milk thickening and heating it in an open iron pan. In this study, feedforward Backpropagation Neural Network (BPNN), Radial Basis Function Neural Network (RBFNN) and Multiple Linear Regression (MLR) models have been developed to predict shelf life of cow milk khoa stored at 37oC. Five input parameters, viz., moisture, titratable acidity, free fatty acids, tyrosine and peroxide value are considered to predict sensory score. The dataset comprised of 48 observations. The accuracy of these models was judged with percent Root Mean Square Error (%RMSE). The BPNN model with Bayesian regularization algorithm provided static and consistent results. The residual shelf life of khoa was also computed using regression equations based on sensory scores. The BPNN model exhibited the best fit (%RMSE, 4.38) followed by MLR model (%RMSE, 9.27) and RBFNN model (%RMSE, 10.84). © 2011 Springer-Verlag.
CITATION STYLE
Goyal, S., Sharma, A. K., & Sharma, R. K. (2011). Development of efficient artificial neural network and statistical models for forecasting shelf life of cow milk khoa - A comparative study. In Communications in Computer and Information Science (Vol. 169 CCIS, pp. 145–149). https://doi.org/10.1007/978-3-642-22577-2_20
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