Estimation of tomato drying parameters using artificial neural networks
نویسندگان
1 MSc. Graduated Student, Department of Food Science and Technology, Islamic Azad University, Sabzevar Branch
2 BSc. Student, Department of Food Science and Technology, Islamic Azad University, Sabzevar Branch
doi
10.22101/JRIFST.2012.05.21.116چکیده
In this research we have simulated drying tomato thin layer by hot air convection. Tomato slices were dried in two temperatures 60° and 70℃. Perceptron neural network was used to predict moisture ratio and drying rate of samples during the drying process. Best neural network topology for ANN-I based on one hidden layer 2 and 8 neuron per hidden layers for moisturizing ratio and the drying rate obtained respectively. Furthermore, best neural network topology for ANN-II based on one hidden layer 11 neuron for moisturizing ratio and the drying arte obtained. Generally, the results showed that ANN-II had preferable result to predict drying parameters of drying tomato.
