Computerized Models for Shelf Life Prediction of Post-Harvest Coffee Sterilized Milk Drink

Abstract: For centuries, coffee has been brewed and consumed in households, hot shops and restaurants. Coffee is the second most important product in the international market in terms of volume trade and the most important in terms of value. In today’s highly competitive market consumers look for healthy and delightful food products. To attain good quality of food products, prediction of shelf life is necessary. Computerized models were developed for shelf life prediction of coffee sterilized milk drink. Colour and appearance, flavour, viscosity and sediment were taken as input parameters. The Overall acceptability was used as output parameter for developing the Artificial Neural Networks (ANN) models. The dataset was randomly divided into two disjoint subsets, namely, training set consisting of 40 observations (80 % of total observations) and testing set comprising of 10 observations (20 % of total observations). Number of neurons in each hidden layer varied from 1 to 30. The network was trained with 500 epochs. MSE, RMSE, R and E were used in order to compare the2 2 prediction performance of the developed computerized artificial intelligence models. The ANN models predicted 37.80 days shelf life which is within the experimentally determined shelf life of 45 days, suggesting that the product is acceptable. Key words: Coffee % ANN % Artificial Intelligence % Elman % Radial Basis % Prediction % Shelf Life INTRODUCTION m holding time so that it remains fit for huma