Probabilistic neural network classification for model β-Glucan suspensions

Authors:
Ratchadaporn Oonsivilai;Anant Oonsivilai
Affiliations:
School of Food Technology, Suranaree University of Technology, Nakhon Ratchasima, Thailand;School of Electrical Engineering, Suranaree University of Technology, Nakhon Ratchasima, Thailand
Venue:
SMO'07 Proceedings of the 7th WSEAS International Conference on Simulation, Modelling and Optimization
Year:
2007

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Abstract

The problems encountered in brewing commonly attributed to excess β-glucan levels include low extract yield, increased lauter runoff times, formation of gelatinous precipitates during aging, and decreased filtration efficiency. Several rheological techniques were used to determine C* or critical concentration where β-glucan aggregates begin to entangle and there was a relationship between intrinsic viscosity and C*. This study reports applying Probabilistic Neural Network (PNN) to get new data set of relation between reciprocal of logarithm of relative viscosity 1/log (ηrel) and β-glucan concentration in seven model buffer systems and thus could be used for C* valure determination with better statistical correlation.