The approach for this study followed a comparison of three plant species with various anatomical differences; Japanese Knot Weed, Green Broccoli, and Chard. Two iPhone applications; Colour Analysis Lite and Colormeter RGB were used to observe the changes in RGB values correlated against the actual chlorophyll content of the leaves. Leaves were collected with a range of colours and pictures were taken in a lightbox in order to remove incident light. Calculations to find Standard RGB, rgb, and HSL were made for each set of leaves.
Results/Conclusions
The findings suggested that chlorophyll content had moderately correlated values with red and green values for both apps when using Japanese Knot Weed. The applications did not produce any correlations between RGB and Chlorophyll for both broccoli and chard. Both apps provided similar values suggesting that both apps provide consistently similar results. When comparing different surface textures, the apps were able to distinguish colour changes in Japanese knotweed but were not sufficient enough in recognizing changes in colour in broccoli and chard. The non-destructive techniques used by CAL and CM could not efficiently observe RGB colour changes in JKW, Broccoli, and Chard. Regression analysis suggested that plant pigment content could not be accurately predicted by current colour analysis smartphone applications to proceed with conversions to a predicted chlorophyll content value.