A Method Based on Digital Image Analysis for Estimating Crop Canopy Parameters

This research is attempted to estimate the biomass and leaf area index through identifying the cotton canopy and background pixels accurately. Cotton canopy was captured in different growth period of cotton by using an Olympus C740 Ultra Zoom digital camera. A protocol mixed hue of HLS color space with R, G value was setup and multiple judgment process was designed to extract cotton canopy pixels from background noise. A computer program based on the protocol above was designed simultaneity. Relation between PGCV that derived from the designed program and cotton canopy biomass or LAI with different N application and in different growth stages suggested that PGCV could reliably evaluate both biomass and LAI, empirical statistical showed that a significantly high coefficient between PGCV and cotton canopy biomass or LAI reached (r=0.97, respectively). The results indicated that image analysis is a promising method for quick diagnosis of crop growth and development.