Study of building quantitative analysis model for chlorophyll in winter wheat with reflective spectrum using OSC-PLS algorithm

Compared to the traditional laboratorial measure method, the spectroscopy method is more excellent and non-destructive to measure the content of chlorophyll. The aim of the paper was to determine the contents of chlorophyll in winter wheat by reflective spectroscopy. Pretreatment method of orthogonal signal correction (OSC) was used to reject uncorrelated variables in the original spectrums before building the Partial least squares method (OSC-PLS). The correlation coefficient( ^r ) of calibration set was 0.8379, the standard deviation(SD) and relative standard deviation(RSD) were 0.3626 and 10.02% respectively, and the correlation coefficient( r ) of predicted set was 0.9407, the standard deviation(SD) and relative standard deviation(RSD) were 0.3299 and 9.59% respectively. It shows the OSC-PLS is a useful method to set the model to predict the content of chlorophyll in winter wheat accurately, which meets fast analysis of agricultural products.