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Boosting partial least-squares discriminant analysis with application to near infrared spectroscopic tea variety discrimination

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WOS被引频次:11
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成果类型:
期刊论文
作者:
Tan, ShiMiao;Luo, RuiMin;Zhou, YanPing*;Xu, Hui;Song, DanDan;Ze, Tan;Yang, TianMing;Nie, Yan
通讯作者:
Zhou, YanPing
作者机构:
[Song, DanDan; Zhou, YanPing; Luo, RuiMin; Tan, ShiMiao; Xu, Hui] Cent China Normal Univ, Coll Chem, Minist Educ, Key Lab Pesticide & Chem Biol, Wuhan 430079, Peoples R China.
[Ze, Tan] Hunan Univ, Coll Chem & Chem Engn, State Key Lab Chemo Biosensing & Chemometr, Changsha 410082, Hunan, Peoples R China.
[Nie, Yan] Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan 430079, Peoples R China.
[Yang, TianMing] S Cent Univ Nationalities, Coll Pharm, Wuhan 430074, Peoples R China.
通讯机构:
[Zhou, YanPing] Cent China Normal Univ, Coll Chem, Minist Educ, Key Lab Pesticide & Chem Biol, Wuhan 430079, Peoples R China.
语种:
英文
关键词:
boosting partial least-squares discriminant analysis;near infrared spectroscopy;tea variety discrimination
ISSN:
年:
2012
卷:
26
期:
1
页码:
34-39
文献类别:
WOS:Article
所属学科:
ESI学科类别:化学;WOS学科类别:Automation & Control Systems;Chemistry, Analytical;Computer Science, Artificial Intelligence;Instruments & Instrumentation;Mathematics, Interdisciplinary Applications;Statistics & Probability
入藏号:
基金类别:
National Natural Science Foundation [21105035]; CCNU from MOE [CCNU09A01012]; Fundamental Research Funds for the Central Universities [111016, 20110348]; State Key Laboratory of Chemo/Biosensing and Chemometrics of Hunan University [200910]; Hubei Province Natural Science Foundation [2010CBB00402]
机构署名:
本校为第一且通讯机构
院系归属:
化学学院
城市与环境科学学院
摘要:
In the present study, boosting has been combined with partial least-squares discriminant analysis (PLS-DA) to develop a new pattern recognition method called boosting partial least-squares discriminant analysis (BPLS-DA). BPLS-DA is implemented by firstly constructing a series of PLS-DA models on the various weighted versions of the original calibration set and then combining the predictions from the constructed PLS-DA models to obtain the integrative results by weighted majority vote. Coupled with near infrared (NIR) spectroscopy, BPLS-DA has been applied to discriminate different kinds of tea varieties. As comparisons to BPLS-DA, the conventional principal component analysis, linear discriminant analysis (LDA), and PLS-DA have also been investigated. Experimental results have shown that the inter-variety difference can be accurately and rapidly distinguished via NIR spectroscopy coupled with BPLS-DA. Moreover, the introduction of boosting drastically enhances the performance of an individual PLS-DA, and BPLS-DA is a well-performed pattern recognition technique superior to LDA. Copyright (C) 2012 John Wiley & Sons, Ltd.
参考文献:
Alain C, 2008, J AGR FOOD CHEM, V56, P9813
Bilal M, 2010, J AGR FOOD CHEM, V58, P3093, DOI 10.1021/jf903872r
Bjorn-Helge M, 2004, J CHEMOMETR, V11, P498
Centner V, 1998, ANAL CHIM ACTA, V376, P153, DOI 10.1016/S0003-2670(98)00543-1
Christoffer A, 2005, ANAL CHEM, V77, P1055

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