Optimizing an Electronic Nose for Analysis Honey from Different Nectar Sources

文献类型： 外文期刊

第一作者： Liu, Ningjing

作者： Liu, Ningjing;Qing, Zhaoshen;Ji, Baopin;Zhou, Feng;Shi, Bolin;Zhao, Lei;Tian, Wenli

作者机构：

关键词： Electronic Nose;Parameters Optimization;Sensors Selection;GA;SIMCA

期刊名称：SENSOR LETTERS （ 影响因子：0.558； 五年影响因子：0.58 ）

ISSN：

年卷期：

页码：

收录情况： SCI

摘要： Honey from different nectar sources was analyzed by electronic nose (e-nose), including litchi honey, rape honey, acacia honey, linden honey and vitex honey. Orthogonal experiments were done to optimize the measuring factors including weight of samples, head-space temperature, and incubation time so that a better performance can be obtained. Besides, combined with soft independent modelling of class analogy (SIMCA), genetic algorithm (GA) was applied in the selection of sensors to improve the quality of classifier and the accuracy of pattern recognition. The result indicated that the e-nose acquired a better performance of repeatability and discrimination at 60℃, with incubation time of 120 s and quantity of 6 g. With No. 2, 10, 14, 15, and 16 sensors selected, e-nose had better ability to classify different kinds of honey. The accuracy of SIMCA is 80% after the optimization.

分类号： TP212

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