Penalized discriminant analysis for the detection of wild-grown and cultivated Ganoderma lucidum using Fourier transform infrared spectroscopy

Spectrochimica Acta. Part A, Molecular and Biomolecular Spectroscopy
Ying Zhu, Tuck Lee Tan

Abstract

An effective and simple analytical method using Fourier transform infrared (FTIR) spectroscopy to distinguish wild-grown high-quality Ganoderma lucidum (G. lucidum) from cultivated one is of essential importance for its quality assurance and medicinal value estimation. Commonly used chemical and analytical methods using full spectrum are not so effective for the detection and interpretation due to the complex system of the herbal medicine. In this study, two penalized discriminant analysis models, penalized linear discriminant analysis (PLDA) and elastic net (Elnet),using FTIR spectroscopy have been explored for the purpose of discrimination and interpretation. The classification performances of the two penalized models have been compared with two widely used multivariate methods, principal component discriminant analysis (PCDA) and partial least squares discriminant analysis (PLSDA). The Elnet model involving a combination of L1 and L2 norm penalties enabled an automatic selection of a small number of informative spectral absorption bands and gave an excellent classification accuracy of 99% for discrimination between spectra of wild-grown and cultivated G. lucidum. Its classification performance was superior to that of the PLD...Continue Reading

References

Jan 10, 2004·Integrative Cancer Therapies·Daniel Sliva
May 2, 2006·Statistical Applications in Genetics and Molecular Biology·Jian J DaiDavid Rocke
Mar 29, 2007·Applied Spectroscopy·Sevgi Turker GorguluFeride Severcan
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Jan 25, 2011·Spectrochimica Acta. Part A, Molecular and Biomolecular Spectroscopy·Aneta BombalskaElżbieta A Trafny
Aug 14, 2012·Spectrochimica Acta. Part A, Molecular and Biomolecular Spectroscopy·Xianliang ChenXin Wang

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