Penalized discriminant analysis for the detection of wild-grown and cultivated Ganoderma lucidum using Fourier transform infrared spectroscopy
详细信息 查看全文
- 作者：Ying Zhua ; ying.zhu@nie.edu.sg" class="auth_mail" title="E-mail the corresponding author ; Tuck Lee Tanb
- 关键词：Discrimination ; Feature selection ; Fourier transform infrared spectroscopy ; Penalized linear discriminant analysis ; Elastic net ; Principal component discriminant analysis ; Partial least squares discriminant analysis
- 刊名：Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy
- 出版年：2016
- 出版时间：15 April 2016
- 年：2016
- 卷：159
- 期：Complete
- 页码：68-77
- 全文大小：1399 K
文摘
- •
A successful combination of FTIR and penalized discriminant method to distinguish wild grown G.lucidum from cultivated one.
- •
Penalized discriminant models enabled an automatic selection of a small number of informative wavelengths for discrimination.
- •
The Elastic net model outperformed the PCDA and PLSDA with reduced model complexity and excellent classification accuracy.
- •
Results provided scientific evidence and interpretation of the major bioactive compounds in G.lucidum regarding its anti-cancer effects.