An Image Processing Based Approach for Detection of Nitrogen Status in Winter Wheat Under Mild Drought Stress

Nitrogen is one of the most important agricultural inputs affecting crop growth, yield and quality in rain-fed cereal production. In this study an image processing based approach was used for detection of nitrogen status in winter wheat. Four N fertilization rates (0, 60, 120 and 240 kg N ha, in total) and two water regimes (irrigated and non-irrigated) were applied to winter wheat. Digital images of the plant canopy were acquired using a Canon camera during the growing season 2012. Different indices were extracted by processing of the images. According to the statistical analyses, all the indices were affected by both N and water supplies. However, Rm, RMB, NRMB, Hue and INT were less sensitive to water supply. Among the indices, crop coverage (CC) showed better results for detection of nitrogen status of the plant. We conclude that digital cameras can be used to assess nitrogen status of winter wheat.