A Novel Recognition of Three Kinds of Sibling Plants Using FT-IR with Continuous Wavelet Feature Extraction Combined with an Artificial Neural Network

作者：Cheng Cungui^*; Xiong Wei; Tian Yumei; Zhang Changjiang

来源：Spectroscopy, 2009, 24(2): 58-+.

Fourier-transform infrared (FT-OR) and horizontal attenuated total reflectance (HATR) techniques are used to obtain the FT-IR spectra of the yellow foxtail seed (the seed from Setaria glauca (L.) Beauv), the giant foxtail seed (the seed from Setaria faberii Herrum), and the green foxtail seed (the seed from Setaria viridis (L.) Beauv). The similar FT-IR features among these three types of seeds are extracted by using continuous Wavelet transform (CWT). The decomposition levels 1, 13, and 3 are used to extract the feature vectors, which are used to train the artificial neural network (ANN). The trained neural network is used to classify the seeds. The seed samples are collected from different places around the country. With 180 testing samples, we could move effectively identify the sibling plants - yellow foxtail seed, giant foxtail seed, and green foxtail seed - by FT-IR with continuous wavelet feature extraction (CWFE) and ANN classification.

• 出版日期2009-2
• 单位浙江师范大学