Open AccessDirect classification of related species of fungal endophytes ( Epichloë spp.) using visible and near‐infrared spectroscopy and multivariate analysis
Author(s) -
Petisco Cristina,
Downey Gerard,
Murray Ian,
Zabalgogeazcoa Iñigo,
GarcíaCriado Balbino,
GarcíaCiudad Antonia
Publication year - 2008
Publication title -
fems microbiology letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.899
H-Index - 151
eISSN - 1574-6968
pISSN - 0378-1097
DOI - 10.1111/j.1574-6968.2008.01186.x
Subject(s) - partial least squares regression , multivariate statistics , biology , linear discriminant analysis , botany , chemometrics , near infrared spectroscopy , mathematics , chemistry , chromatography , statistics , neuroscience
Abstract The aim of this work was to investigate the potential of visible and near‐infrared (Vis‐NIR) reflectance spectroscopy for the classification of three morphologically similar species of fungal endophytes of grasses. Vis‐NIR spectra (400–2498 nm) from 34 isolates of Epichloë sylvatica , 32 of Epichloë typhina and 38 of Epichloë festucae were recorded directly from fresh mycelium growing in potato dextrose agar plates. Multivariate procedures applied to the spectral data were discriminant modified partial least squares regression, soft independent modelling of class analogy and discriminant partial least squares regressions (PLS1, PLS2). Several types of data pretreatments were tested to develop the classification models. The best predictive models were achieved with PLS2 analysis; with this method, 90% of E. typhina and 100% of E. festucae and E. sylvatica external validation samples were successfully classified. These results show the potential of Vis‐NIR spectroscopy combined with multivariate analysis as a rapid method for classifying morphologically similar species of filamentous fungi.