The More Fractal the Architecture the More Intensive the Color of Flower: A Superpixel-Wise Analysis towards High-Throughput Phenotyping

A breeder can select a visually appealing phenotype, whether for ornamentation or landscaping. However, the organic vision is not accurate and objective, making it challenging to bring reliable phenotyping intervention into implementation. Therefore, objective of this study was develop an innovative solution predict intensity flower’s color upon external shape crop. We merged single linear iterative clustering (SLIC) algorithm box-counting method (BCM) framework extract useful imagery data biophysical modeling. Then, we validated our approach by fitting Gompertz function on fractal dimension (SD) architecture white-flower, yellow-flower, red-flower varieties Portulaca umbraticola. The SLIC segmented images uniform superpixels, enabling BCM precisely capture SD architecture. ranged from 1.938315 1.941630, which corresponded pixel-wise intensities 220.85 47.15. Thus, more compact intensive flower. sigmoid predicted such relationship at radj2 > 0.80. This provide further knowledge progress field’s prominence in developing breakthrough strategies toward improving control visual quality breeding ornamentals.