Application of visible and near-infrared spectroscopy to classification of Miscanthus species

doi:10.1371/journal.pone.0171360

CORC > 武汉植物园 > 中国科学院武汉植物园

	Application of visible and near-infrared spectroscopy to classification of Miscanthus species
	Jin, Xiaoli 1,2; Chen, Xiaoling 1,2; Xiao, Liang 3; Shi, Chunhai 1,2; Chen, Liang 4; Yu, Bin 5; Yi, Zili 3; Yoo, Ji Hye 6; Heo, Kweon 6; Yu, Chang Yeon 6
刊名	PLOS ONE
	2017-04-03
卷号	12 期号:4 页码:12
ISSN号	1932-6203
DOI	10.1371/journal.pone.0171360
英文摘要	The feasibility of visible and near infrared (NIR) spectroscopy as tool to classify Miscanthus samples was explored in this study. Three types of Miscanthus plants, namely, M. sinensis, M. sacchariflorus and M. fIoridulus, were analyzed using a NIR spectrophotometer. Several classification models based on the NIR spectra data were developed using line discriminated analysis (LDA), partial least squares (PLS), least squares support vector machine regression (LSSVR), radial basis function (RBF) and neural network (NN). The principal component analysis (PCA) presented rough classification with overlapping samples, while the models of Line_LSSVR, RBF_LSSVR and RBF_NN presented almost same calibration and validation results. Due to the higher speed of Line_LSSVR than RBF_ LSSVR and RBF_ NN, we selected the line_LSSVR model as a representative. In our study, the model based on line_LSSVR showed higher accuracy than LDA and PLS models. The total correct classification rates of 87.79 and 96.51% were observed based on LDA and PLS model in the testing set, respectively, while the line_LSSVR showed 99.42% of total correct classification rate. Meanwhile, the lin_LSSVR model in the testing set showed correct classification rate of 100, 100 and 96.77% for M. sinensis, M. sacchariflorus and M. fIoridulus, respectively. The lin_ LSSVR model assigned 99.42% of samples to the right groups, except one M. fIoridulus sample. The results demonstrated that NIR spectra combined with a preliminary morphological classification could be an effective and reliable procedure for the classification of Miscanthus species.
资助项目	DOE Office of Science, Office of Biological and Environmental Research (BER)[DE-SC0006634] ; DOE Office of Science, Office of Biological and Environmental Research (BER)[DE-SC0012379] ; Open Foundation of Hunan Provincial Key Laboratory for Germplasm Innovation and Utilization of Crop[15KFXM02]
WOS研究方向	Science & Technology - Other Topics
语种	英语
出版者	PUBLIC LIBRARY SCIENCE
WOS记录号	WOS:000399351000005
内容类型	期刊论文
源URL	[http://202.127.146.157/handle/2RYDP1HH/1389]
专题	中国科学院武汉植物园
通讯作者	Jin, Xiaoli
作者单位	1.Zhejiang Univ, Key Lab Crop Germplasm Resource Zhejiang Prov, Hangzhou, Zhejiang, Peoples R China 2.Zhejiang Univ, Dept Agron, Hangzhou, Zhejiang, Peoples R China 3.Hunan Agr Univ, Hunan Prov Key Lab Germplasm Innovat & Utilizat C, Changsha, Hunan, Peoples R China 4.Chinese Acad Sci, Wuhan Bot Garden, Wuhan, Hubei, Peoples R China 5.Wuhan Junxiu Hort Sci & Technol Co Ltd, Wuhan, Hubei, Peoples R China 6.Kangwon Natl Univ, Chunchon, Gangwon, South Korea 7.Hokkaido Univ, Field Sci Ctr Northern Biosphere, Sapporo, Hokkaido, Japan 8.Univ Illinois, Dept Crop Sci, Urbana, IL USA 9.China Natl Seed Grp Co Ltd, Life Sci & Technol Ctr, Wuhan, Hubei, Peoples R China
推荐引用方式 GB/T 7714	Jin, Xiaoli,Chen, Xiaoling,Xiao, Liang,et al. Application of visible and near-infrared spectroscopy to classification of Miscanthus species[J]. PLOS ONE,2017,12(4):12.
APA	Jin, Xiaoli.,Chen, Xiaoling.,Xiao, Liang.,Shi, Chunhai.,Chen, Liang.,...&Peng, Junhua.(2017).Application of visible and near-infrared spectroscopy to classification of Miscanthus species.PLOS ONE,12(4),12.
MLA	Jin, Xiaoli,et al."Application of visible and near-infrared spectroscopy to classification of Miscanthus species".PLOS ONE 12.4(2017):12.