Estimating nitrogen status of rice using the image segmentation of G-R thresholding method

Abstract

A camera can record spectral information of visible bands. In this study, a digital camera was used to take pictures of the canopies of 3 rice (Oryza sativa L.) cultivars with 6 different nitrogen (N) application rates. Canopy images were segmented by setting threshold values based on the magnitude and distribution of the green channel minus red channel (GMR) value, and then correlations were established between image feature parameters and the 3 plant indices (i.e., above-ground biomass, N content and leaf area index) before and after image segmentation. Results showed significant exponential relationships between the image parameters and the plant indices. Before the segmentation, the GMR values were closely related to the 3 plant indices, with correlation coefficient of 0.93**, 0.93** and 0.94**, respectively; while after the segmentation, the correlation coefficients between canopy cover (CC) and plant indices were 0.90**, 0.91** and 0.95**, respectively. We conclude that GMR and CC will be valid indicators in the application of N diagnosis both for japonica and indica rice. And the canopy image segmentation method is fast in data processing and easily adaptable.