Evaluation of leaf chlorophyll content by a non-invasive approach

Abstract: Leaf chlorophyll is the most photochemically active compound present in the plant cells, which plays an important role in the process of photosynthesis by capturing light energy and converts it into chemical energy. Health status and nitrogen content in the plant can be determined by chlorophyll concentration, so a rapid image processing method has been proposed to measure the chlorophyll. The spectral properties of an image like Hue, Saturation and Intensity are modeled as linear correlation functions for chlorophyll content. A significant correlation was observed between the predicted chlorophyll by model and chlorophyll content measured by atLEAF meter. The value of R2 and Root Mean Square Error (RMSE) between the observed and estimated chlorophyll content was 0.95 and 2.045 respectively.

Keywords: Image analysis, RGB model, HSI model, hsi model, chlorophyll content, atLEAF meter, RMSE.