Classification of Green Bristle Grass, Yellow Foxtail and Chinese Pennisetum Seeds via HATR-FT-IR Combined with Chemometrics
Author(s) -
Peng Yu,
Chayan Wan,
Changshun Wu,
Jia-Ni Shou,
Cungui Cheng
Publication year - 2012
Publication title -
journal of spectroscopy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.323
H-Index - 21
eISSN - 2314-4920
pISSN - 2314-4939
DOI - 10.1155/2013/531747
Subject(s) - setaria , foxtail , setaria viridis , bristle , biology , pennisetum , botany , horticulture , materials science , brush , weed , composite material
Fourier transform infrared (FT-IR) and horizontal attenuated total reflectance (HATR) technique are used to obtain the FT-IR spectra of the seed of green bristle grass (the seed from Setaria viridis (L.) Beauv), yellow foxtail seed (the seed from Setaria glauca (L.) Beauv), and the Chinese pennisetum seed (the seed from Setaria faberii Herrum). In order to extrude the difference among them, cluster analysis is considered to identify the three kinds of plant seeds. Because they belong to the sibling plant seeds, and have similar chemical components and close FT-IR spectra. The result of Cluster analysis is not satisfactory. The discrete wavelet transformation (DWT) and a support vector machine (SVM) were used for further study. The compression detail 3 and 4 in DWT are used to extract the feature vectors, which are used to train SVM. The trained SVM is used to classify seed of green bristle grass, yellow foxtail seed and Chinese pennisetum seed. The seed samples are collected from different places around the country. With 40 testing samples we could effectively identify the sibling plants, seed of green bristle grass, yellow foxtail seed and Chinese pennisetum seed by FT-IR with discrete wavelet feature extraction and SVM classification
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