Abbas Haghshenas, Yahya Emam, Saeid Jafarizadeh (Shiraz University)
|Scale||Organs, Whole_plant, Field|
|Operating system||MacOs, Windows, Linux, Any|
|Format of model inputs and outputs||Images|
Green-gradient based canopy segmentation: A multipurpose image mining model with potential use in crop phenotyping and canopy studiesAbbas Haghshenas,Yahya EmamComputers and Electronics in Agriculture, 2020 View paper
Green-gradient based canopy segmentation model (GSM) is a novel technique for canopy phenotyping. This image-mining model represents the canopy as a simple graph (entitled GSM graph) consisted of two exponential curves with separate equations. These curves show the trends of variations in the red and blue colors of the vegetation parts, relative to the 1:1 linear trend of the changes in the green color (RGB color system). It has been evidenced that the GSM graph is highly sensitive to the environmental conditions (and probably to genotype); so the model outputs, including the coefficients of equations, and also the total set of 510 values of the curve points) can be used for datamining and high-throughput phenotyping approaches. The user-friendly version of the model has been published on Code Ocean, which has provided the opportunity of running the scientific codes without any specific software or hardware requirements (except a web browser).
Some case studies