Application of an Artificial Neural Network for Predicting the Texture of Whey Protein Gel Induced by High Hydrostatic Pressure
作者单位：College of Biosystems Engineering and Food ScienceZhejiang University Institute of Agro-Food Science & TechnologyChinese Academy of Agricultural Sciences
会议名称：《Computer and Computing Technologies in Agriculture VI——6th IFIP WG 5.14 International Conference(CCTA2012) Part I》
会议日期：2013年
学科分类：0832[工学-食品科学与工程（可授工学、农学学位）] 12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 0835[工学-软件工程] 083201[工学-食品科学] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）]
基 金：supported by the Zhejiang Key Scientific and Technological Innovation Team Project(2009R50001) the Department of Education of Zhejiang Province(Y201018520) the Fundamental Research Funds for the Central Universities
关 键 词：Hydrostatic high pressure Whey protein isolate Gelation Artificial neural network
摘 要：The effects of high hydrostatic pressure(HP),protein concentration,and sugar concentration on the gelation of a whey protein isolate(WPI) were *** concentrations of WPI solution in the presence or absence of lactose(0-20%,w/v) were pressurized at 200-1000 MPa and incubated at 30°C for 10 minThe hardness and breaking stress of the HPinduced gels increased with increasing concentration of WPI(12-20%) and *** decreased the hardness and breaking stress of the ***,these results were used to establish an artificial neural network(ANN)A multiple layer feed-forward ANN was also established to predict the physical properties of the gel based on the inputs of pressure,protein concentration,and sugar concentrationA useful prediction was possible,as measured by a low mean square error(MSE 0.99) between true and predicted data in all cases.