数字农科院2.0

Study on Varieties Identification of Kentucky Bluegrass Using Hyperspectral Imaging and Discriminant Analysis

文献类型： 外文期刊

作者： Xiao Bo;Liang Xiao-hong;Zhang Li-juan;Han Lie-bao;Xiao Bo;Han Lie-bao;Mao Wen-hua

作者机构：

关键词： Hyperspectral imaging;Discriminant analysis;Kentucky bluegrass;Variety identification

期刊名称： SPECTROSCOPY AND SPECTRAL ANALYSIS

ISSN： 1000-0593

年卷期： 2012 年 32 卷 6 期

页码：

收录情况： SCI

摘要： Hyperspectral images of six varieties of Kentucky bluegrass were acquired using hyperspectral imager (550-1000 nm) and the leaf spectral properties were extracted. Wilks'lambda stepwise method was used and 9 optimal wavelengths were selected from the original 94 wavelengths and the discriminant models for varieties identification of Kentucky bluegrass were built based on Fisher's linear discriminant function. The results showed that the Fisher's linear discriminant model with 9 wavelengths achieved classification accuracies of 100% for both training and testing samples. While for the models with three wavelengths and six wavelengths, classification accuracies reached 83.3% and 96.7% for the testing samples, respectively. It indicates that hyperspectral images combined with discriminant analysis might be a good method to identify the varieties of Kentucky bluegrass.

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