Near infrared quantitative analysis of total flavonoid content in fresh Ginkgo biloba leaves based on different wavelength region selection methods and partial least squares regression

Total flavonoid concentration is often considered an important quality attribute of Ginkgo biloba leaf. Near infrared spectroscopy was used to determine total flavonoid concentration in fresh G. biloba leaf. The spectra of 120 leaf samples were acquired in the wavelength range of 10,000 cm(-1) to 4000 cm(-1). After pre-processing, interval partial least squares (iPLS), synergy interval partial least squares (SiPLS), genetic algorithm interval partial least squares (GA-iPLS) and simulation annealing algorithm interval partial least squares (SAA-iPLS) were used to select the most informative wavelength regions correlated with total flavonoid concentration. The number of wavelength regions and the number of PLS factors were optimised by cross-validation. The performance of the SAA-iPLS model developed in this study was better than PLS, iPLS and GA-iPLS models. The coefficient of determination (r(2)) and the root mean square error of prediction (RMSEP) for the prediction set samples using the SAA-iPLS model were 0.89 mg g(-1) and 3.0 mg g(-1), respectively. These results show that near infrared spectroscopy combined with SAA-iPLS has significant potential for the non-destructive quantitative analysis of total flavonoids in G. biloba leaf.