Evaluation of hemp seedling size using ImageJ software

Abstract

In vitro hemp seed germination is crucial for investigating factors impacting production conditions. It is laborious and time-consuming to measure and evaluate the morphological traits of seedlings grown in vitro. One of the most well-known machine vision techniques is image processing, which offers detailed information and more reliability and accuracy than traditional counting and visual determination of seedlings. The study aimed to determine if hypocotyl images obtained with semi-automatic processing through SmartRoot could be replaced with faster, automatic processing. Seedlings were scanned in RGB color profile in 300 dpi, using an open lid flatbed scanner HP Scanjet G4050. The images were processed in ImageJ software.