| Literature DB >> 32582451 |
Anna Lu1, Xinxin Wei1, Ruikang Cai1, Shujun Xiao1, Haina Yuan1, Jinyan Gong1, Bingquan Chu1, Gongnian Xiao1.
Abstract
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. © The Korean Society of Food Science and Technology 2020.Entities:
Keywords: Artificial neural network model; Forward back propagation; Physical and chemical properties; Stirred yogurt
Year: 2020 PMID: 32582451 PMCID: PMC7297902 DOI: 10.1007/s10068-020-00741-7
Source DB: PubMed Journal: Food Sci Biotechnol ISSN: 1226-7708 Impact factor: 2.391