Sumit Goyal

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Coffee as beverage is prepared from the roasted seeds (beans) of the coffee plant. Coffee is the second most important product in the international market in terms of volume trade and the most important in terms of value. Artificial neural engineering and regression models were developed to predict shelf life of instant coffee drink. Colour and appearance,(More)
Soft mouth melting milk cakes from water buffalo milk were prepared by using milk collected from Experimental Dairy, National Dairy Research Institute, Karnal, India. This milk was standardized to 6% fat. Time-delay and linear layer (design) intelligent computing expert system models were developed for predicting shelf life of soft mouth melting milk cakes(More)
This paper highlights the capability of artificial neural networks for predicting shelf life of milky white dessert jeweled with pistachio. Linear layer (train) and generalized regression models were developed and compared with each other. Neurons in each hidden layers varied from 1 to 30. Data samples were divided into two sets, i.e., 80% of data samples(More)
For centuries, coffee has been brewed and consumed in households, hot shops and restaurants. Today flavoured milks have become very popular and they contain nutrients as compared with soft drinks. Sterilized milk is the product made by heating milk to high temperature (121 C) with 15 m holding time so that it remains fit for human consumption for longer(More)
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(More)
Radial basis ( fewer neurons) artificial neural network (ANN) models were developed for predicting the shelf life of processed cheese stored at 7-8o C. Mean square error, root mean square error, coefficient of determination and nash sutcliffo coefficient were applied in order to compare the prediction ability of the developed models. Soluble nitrogen, pH;(More)
In this study feedforward and competitive artificial neural network models were developed for predicting shelf life of processed cheese stored at 30 C. Processed cheese is a food product generally made from Cheddar cheese. Processed cheese has several advantages over unprocessed cheese, such as extended shelf-life, resistance to separation when cooked, and(More)
Paneer resembling soft cheese is a well-known heat- and acid-coagulated milk product. It is very popular in the Indian subcontinent and has appeared in the western and Middle East markets. The shelf life of paneer is quite low and it loses freshness after two to three days when stored under refrigeration. Various preservation techniques, including chemical(More)
Artificial Neural Networks (ANNs) have been implemented in almost every field, viz., science, technology, medicine and engineering as they have proved useful tools for obtaining the desired output including the analyses and shelf life prediction in case of food products. This review discusses the systematic information available in the literature concerning(More)