Investigation of Malting Process Using Artificial Neural Network

Document Type : Research Article

Authors

Alireza Ghodsvali ¹

Mohsen Mokhtarian ²

Hamid Bakhshabadi ³

Fatemeh Arabamerian ²

¹ Golestan Research Center

² Islamic Azad University, Sabzevar Branch

³ Islamic Azad University, Gonbad Kavous Branch

https://doi.org/10.22067/ifstrj.v9i3.29604

Abstract

Malting is a complex biotechnological process that includes steeping; germination and drying of cereal grains
under controlled conditions of temperature and humidity. In this research malting process parameters were
predict by modular neural network with different activation function included, logsig-logsig, tanh-tanh, logsigtanh,
logsig-identity and tanh-identity. Steeping time (x1) and germination time (x2) were used as input
parameters and hot water extract (y1), malting yield (y2) and enzyme activity (β-Gluconase) (y3) were selected as
output parameters. The results showed that using perceptron neural network with tanh-identity activation
function had the best result among all of activation functions to predict effective parameters of malting process.
As well, this network was able to predict hot water extract, malting yield and enzyme activity (β - Gluconase)
with R2 value of 1, 0.984 and 0.995, respectively.

Keywords

Artificial neural network

Malt

prediction

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