Thanks for sharing your updates @Hayan_Lee!
The brown roots and the green hose is likely to be hard to assign to the right class with color clustering. Because the clustering happens purely based on color - and a brown root is colorwise closer to the stones than to the green leave.
In other words, the algorithm has no concept of plants, or of actually any spatial structure.
You might be able to separate the white flowers into a separate class by increasing the number of clusters (doubleclick on SimpleKMeans).
But roots are tough. Can try to play with the channel selection.
If you want to teach the algorithm more you need a different tool - like Trainable Weka Segmentation (suggested by @schmiedc), or the separate software Ilastik which does very similar things.
Consider creating separate classes for plant parts which all belong to plants but do look very different. Fore example: (1) background, (2) green leaves, (3) roots
Alternatively you could also opt for getting a pretty good segmentation based on color and then correcting it manually.