Study on Varieties Identification of Kentucky Bluegrass Using Hyperspectral Imaging and Discriminant Analysis
XIAO Bo1，2, MAO Wen-hua3, LIANG Xiao-hong1, ZHANG Li-juan1, HAN Lie-bao1，2*
1. Institute of Turfgrass Science, Beijing Forestry University, Beijing 100083, China 2. College of Gardening and Horticulture, Yangtze University, Jingzhou 434023, China 3. State Key Laboratory of Soil Plant Machinery System Technology, Chinese Academy of Agricultural Mechanization Sciences, Beijing 100083, China
Abstract：Hyperspectral images of six varieties of Kentucky bluegrass were acquired using hyperspectral imager (550-1 000 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.
肖 波1，2，毛文华3，梁小红1，张利娟1，韩烈保1，2* . 基于高光谱图像和判别分析的草地早熟禾品种识别研究[J]. 光谱学与光谱分析, 2012, 32(06): 1620-1623.
XIAO Bo1，2, MAO Wen-hua3, LIANG Xiao-hong1, ZHANG Li-juan1, HAN Lie-bao1，2* . Study on Varieties Identification of Kentucky Bluegrass Using Hyperspectral Imaging and Discriminant Analysis . SPECTROSCOPY AND SPECTRAL ANALYSIS, 2012, 32(06): 1620-1623.
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