FTIR and UV spectra for the prediction of triterpene acids in Macrohyporia cocos

Abstract The aim of this study was to exploit the potential of rapid and simple spectroscopic techniques combined with partial least squares (PLS) regression using for the content prediction of five triterpene acids in Macrohyporia cocos. Ultraviolet of 80% ethanol extract (UV1), ultraviolet of ethyl acetate extract (UV2), Fourier transform mid-infrared (FT-MIR) and Fourier transform near-infrared (FT-NIR) spectra of samples were collected. The data processing methods of spectral pretreatment, feature extraction and data fusion were adopted to improve prediction performance. The results showed that: (1) UV1, UV2 and FT-MIR did work for content prediction except FT-NIR. (2) Variable importance for the projection (VIP) outperformed interval PLS in feature extraction for the prediction of triterpene acids of M. cocos. Data fusion had no distinct advantage compared with single set analysis (3) Both UV1 and FT-MIR could achieve the prediction of poricoic acid A, and UV1 outperformed FT-MIR. (4) The UV1 subjected by second-order derivative pretreatment and VIP extraction was satisfactory for predicting poricoic acid A and dehydrotumulosic acid. The UV2 preprocessed by first-order derivative could achieve approximate prediction of dehydrotrametenolic acid. This study demonstrated that ultraviolet and mid-infrared spectral data were promising techniques for the rapid prediction of poricoic acid A (UV1 and FT-MIR), dehydrotumulosic acid (UV1) and dehydrotrametenolic acid (UV2) in M. cocos, and ultraviolet spectroscopy was superior to infrared one.