摘要
以猕猴桃切片的品质作为目标进行真空冷冻干燥试验,试验研究干燥室压力、切片厚度、加热板温度对猕猴桃切片品质的影响规律,运用Matlab对真空冷冻干燥的试验数据进行训练和模拟,并与真空冷冻干燥实测值进行比较,结果表明,利用BP神经网络得出的预测值较接近试验实测值,能良好的反映真空冷冻干燥工艺参数与猕猴桃品质之间的关系。
Vacuum freeze-drying experiments of Chinese gooseberry were conducted in order to improve the quality of products.The influences of drying house pressure,material thickness,heating temperature and the interaction of these three factors on products quality were studied.The BP neural network prediction model was established,and the training and the test were made by using Matlab software.The predicted values by BP neural network are closer to experimental values,which well reflect the relationship between the vacuum freeze-drying process parameters and the quality of Chinese gooseberry.
出处
《中国农机化学报》
2015年第4期135-138,共4页
Journal of Chinese Agricultural Mechanization
基金
辽宁省科技厅项目(20131094)
关键词
猕猴桃
切片
品质
模拟分析
BP神经网络
Chinese gooseberry
slice
quality
simulation analysis
BP neural network
