When transporting yogurt, vibrations and sharp movements can damage its quality. This study developed a model to connect the changes in yogurt quality with the transportation distance as simulated by the total number of vibrations. Linear regression analysis showed that there was a significant negative correlation between the water holding capacity and hardness of the yogurt over the same transport distance (p < 0.05). The yogurt vibration model was established by combining principal component analysis with a Back-Propagation Artificial Neural Network model. The number of training iterations was 2669, with a correlation coefficient of 0.96611, indicating that the model was reliable. The optimal transportation distance was determined to be within the range from 20 rpm for 8 h to 100 rpm for 4 h.
Keywords: Artificial neural network model; Forward back propagation; Physical and chemical properties; Stirred yogurt.
© The Korean Society of Food Science and Technology 2020.