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.

运输酸奶时，振动和剧烈运动会损坏酸奶的质量。这项研究开发了一个模型，该模型将酸奶质量的变化与运输距离联系起来，如振动总数所模拟的。线性回归分析表明，在相同的运输距离下，酸奶的持水量和硬度之间存在显着的负相关性（p  <0.05）。通过将主成分分析与反向传播人工神经网络模型相结合，建立了酸奶振动模型。训练迭代次数为2669，相关系数为0.96611，表明该模型是可靠的。确定最佳运输距离在20 rpm持续8 h到100 rpm持续4 h的范围内。