Journal
FOOD SCIENCE AND BIOTECHNOLOGY
Volume 29, Issue 7, Pages 889-896Publisher
KOREAN SOCIETY FOOD SCIENCE & TECHNOLOGY-KOSFOST
DOI: 10.1007/s10068-020-00741-7
Keywords
Stirred yogurt; Forward back propagation; Artificial neural network model; Physical and chemical properties
Categories
Funding
- National Natural Science Foundation of China [31741102]
- Major Science and Technology Projects of Zhejiang Province [2017C02033]
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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.
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