Prediction of anthocyanin content in peony leaves based on visible/near-infrared spectra

The anthocyanin content in leaves can provide valuable information about the physiological conditions of plants and their responses to stress. Thus, there is a need for accurate, efficient and practical methodologies to estimate the biochemical parameters of vegetation. In this study, the peony leaves of different varieties in the early flowering stage were selected as the research objects to analyze the correlation between anthocyanin content in leaves and reflectance spectra. The predictive models were established based on a single band or different vegetation indices. The PLSR(Partial least squares regression) model was constructed to estimate anthocyanin content in leaves by using the reflectance spectra with correlation coefficient more than 0.52 in visible band as independent variables. The results showed that the maximum correlation coefficient between reflectance spectra and anthocyanin content was located at 544 nm. These predictive models which used the reflectance at 544 nm, ARI (Anthocyanin reflectance index) or MARI (Modified anthocyanin reflectance index) as independent variables could be used to estimate anthocyanin content in peony leaves in fact. The calibration and validation R2 of optimum model for predicting anthocyanin content in poeny leaves established by PLSR were 0.873 and 0.811, and the RMSE and RPD were 0.068 μmol/g and 2.352, respectively. This study can provide a method for nondestructive estimation of anthocyanin content in plant leaves, and make a reference for the assessment of physiological status of plants and early stress detection. ©, 2015, Chinese Society of Agricultural Machinery. All right reserved.