Study of Feature Extraction Methods for Maize’s Near Infrared Spectra in Biomimetic Pattern Recognition
SHEN Li-feng1, JIA Shi-qiang1, GUO Ting-ting2, WU Wen-jin1, YAN Yan-lu1, AN Dong1*
1.College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China 2. National Maize Improvement Center of China, China Agricultural University, Beijing 100193, China
Abstract：Near infrared spectrum is an important step in near infrared spectrum qualitative analysis, which influences the qualitative analysis results directly. Diffuse transmittance measurements mode was used to collect spectral data of eight maize varieties. PCA, ICA, PLS-DA and wavelet transformation were used to extract features of pretreated data. Finally, we used the test set data to test the recognition models of eight maize varieties which were built based on biomimetic pattern recognition (BPR). We draw a conclusion that PLS-DA can make models get higher average correct recognition rate than PCA, ICA and Wavelet transformation.
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