%0 Conference Proceedings
%T Application of an Artificial Neural Network for Predicting the Texture of Whey Protein Gel Induced by High Hydrostatic Pressure
%+ Zhejiang University
%+ Chinese Academy of Agricultural Sciences (CAAS)
%A He, Jinsong
%A Mu, Taihua
%< avec comité de lecture
%( IFIP Advances in Information and Communication Technology
%B 6th Computer and Computing Technologies in Agriculture (CCTA)
%C Zhangjiajie, China
%Y Daoliang Li
%Y Yingyi Chen
%I Springer
%3 Computer and Computing Technologies in Agriculture VI
%V AICT-392
%N Part I
%P 118-125
%8 2012-10-19
%D 2012
%R 10.1007/978-3-642-36124-1_15
%K Hydrostatic high pressure
%K Whey protein isolate
%K Gelation
%K Artificial neural network
%Z Computer Science [cs]Conference papers
%X The effects of high hydrostatic pressure (HP), protein concentration, and sugar concentration on the gelation of a whey protein isolate (WPI) were investigated. Differing 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 min. The hardness and breaking stress of the HP-induced gels increased with increasing concentration of WPI (12-20%) and pressure. Lactose decreased the hardness and breaking stress of the gel. Furthermore, 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 concentration. A useful prediction was possible, as measured by a low mean square error (MSE < 0.05) and a regression coefficient (R2  > 0.99) between true and predicted data in all cases.
%G English
%Z TC 5
%Z WG 5.14
%2 https://inria.hal.science/hal-01348089/document
%2 https://inria.hal.science/hal-01348089/file/978-3-642-36124-1_15_Chapter.pdf
%L hal-01348089
%U https://inria.hal.science/hal-01348089
%~ IFIP
%~ IFIP-AICT
%~ IFIP-TC
%~ IFIP-TC5
%~ IFIP-WG5-14
%~ IFIP-CCTA
%~ IFIP-AICT-392