Optimized of Sensor Array and Detection of Moldy Degree for Grain by Electronic Nose
Optimized of Sensor Array and Detection of Moldy Degree for Grain by Electronic Nose
复制标题
传感器阵列优化及电子鼻检测谷物霉变程度
DOI：
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发表时间：
2007
期刊：
影响因子：
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通讯作者：
Tian Xiao
中科院分区：
文献类型：
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作者：
Tian Xiao
An electronic nose system was developed for the evaluation of moldy grain. The system has detected six different moldy degrees of rice. An initial eight sensors was simplified to six after a PCA(Principal component analysis) analysis detected redundancy between of the sensors, Data processing and classification performed by PCA analysis showed no significant performance differences between the complete and reduced sensor array. A feedforward artificial neural network with test data predict the aerobic bacterial count achieving average relative error of 1.010 30, max relative error of 3.942 57. Our results show that Electronic Nose system could predict the moldy rice with a high accuracy.
