Data for geometry-based greenness index comparisons in lettuce biophysical estimations

The data shows that using swarm intelligence based optimization and the introduction of saturation and value component rectification increases the sensitivity of vODGIabc to green color pixels resulting to subtracted non-vegetation pixels in the image even with the presence of shadow and bright light sources. TGI and vODGIabc images are discriminated against the ground truth images annotated using superpixel and watershed transformation.

To further the analysis, each ground truth image is accompanied with actual measurement of biophysical signatures of lettuce. The use of computational intelligence for lettuce fresh weight, height, number of spanning leaves, leaf area index and growth stage estimation is of significant consideration. Matlab codes for optimization, and machine learning and deep transfer network estimations are also included.