Optimization of Operating Conditions in Rice Heat Blast Process for Chinese Rice Wine Production by Combinational Utilization of Neural Network and Genetic Algorithms

Abstract

The rice heat blast process is a novel technique for gelatinizing raw starch. It uses heated air to replace steam for processing rice under high temperature fluidization in a short time period. This is a new technique for making rice wine with the characteristics of easy storage and zero water pollution. This study focused on three major performance indexes (starch gelatinization ratio, total fat content, and amino nitrogen content in the roasted rice), which largely affect the performance of the rice heat blast process and the rice wine quality. The relationship between these performance indexes and the corresponding operation variables were modeled by an artificial neural network (ANN) via learning sets of experimental data. Based on the ANN models obtained, genetic algorithms were used to optimize the operating conditions of the rice heat blast process. The results showed the power in determination of optimal operating conditions by the combinational utilization of artificial neural network and genetic algorithms.

Design and optimization of an efficient enzymatic extrusion pretreatment for Chinese rice wine fermentation

“…1).Therefore, this stage is a water-intensive, energy-and labor-consuming process. Large amounts of waste water are produced from the process, which in turn causes severe environmental problems (Zhu, Zhang, Shi, & Mao, 2004).…”

Characterization of Volatile and Semi-Volatile Compounds in Chinese Rice Wines by Headspace Solid Phase Microextraction Followed by Gas Chromatography-Mass Spectrometry

“…It is one of the most popular alcoholic beverages with an annual consumption of more than 2 million kiloliters in China, especially in the south 30 . Comparing sake which is typically described as having "caramel," "burnt," "heavy," and "complicated" characteristics 12 , Chinese rice wine has the characteristics of "yellow," "sweet aroma" and "abundant nutrition".…”

Application of Artificial Neural Networks (ANNs) in Wine Technology

“…For the topology with 20 hidden units, mean and standard deviation values of validation and test set classification errors were close to those obtained by the 16-hidden-node topology. Zhu et al (2004) studied optimization of operating conditions in rice heat blast process for Chinese rice wine production by combinational utilization of neural network and genetic algorithms. They focused on three major performance indexes (starch gelatinization ratio, total fat content, amino nitrogen content in the roasted rice), which largely affect the performance of the rice heat blast process and rice wine quality.…”