The automatic measurement of external physical traits (i.e. phenotyping) of plant organs, such as root length –which is highly correlated with plant viability– is one of the current bottlenecks in academic and agricultural research. Although many root length measurement software tools are available to the community, plant scientists often find their usability is limited, the measurements they provide are not accurate enough or they are too limited to specific image characteristics. In response to that, this work describes MyROOT 2.0, an automatic software tool jointly developed by plant scientists and computer vision engineers to create a high throughput root length measurement tool that reduces user intervention to a minimum. Using Arabidopsis thaliana seedlings grown on agar plates as a case study, MyROOT 2.0 is capable of detecting the root regions of interest in a fully automatic manner with an accuracy of 98%. Furthermore, this work also presents previously unreported experiments to evaluate several constituting modules of MyROOT 2.0, such as the ability to determine image scale automatically with subpixel accuracy, or the influence of training the hypocotyl detector using wildtype or mutant samples. Finally, when compared to state-of-the-art root length measurement software tools, MyROOT 2.0 achieves the highest root detection rate, obtaining measurements which are four times more accurate than its competitors. This makes MyROOT 2.0 an attractive tool for high throughput root phenotyping.