Comparing digital image analysis and visual rating of gamma ray induced Bent grass (Agrostis stolonifera) mutants

Abstract

The effectiveness of digital image analysis (DIA) for determining turf quality over visual rating was judged. It provides an alternative method to measure the reflectance from vegetative surfaces and showed strong agreement with visual ratings in evaluating turf color. It is clear from the data that the correlations of hue and dark green colour index (DGCI) were significantly positive with the parameters of visual rating. There were non-significant correlation of brightness with quality and texture, and saturation and texture. The DGCI values were in line with each of these parameters when the slope of regression line was significantly different from zero (P<0.05). These relationships were better in DGCI and quality; DGCI and colour and DGCI and texture. Non-linear relationship was noticed between DGCI and saturation and DGCI and brightness. Therefore, digital photography and subsequent image analysis was capable of quantifying turf grass color in field experiments.