The platform is accessible at and hosted on the iPlant cyber-infrastructure using high-throughput grid computing resources of the Texas Advanced Computing Center (TACC).
ConclusionĭIRT is an automated high-throughput computing and collaboration platform for field based crop root phenomics.
The DIRT platform seamlessly connects end-users with large-scale compute “commons” enabling the estimation and analysis of root phenotypes from field experiments of unprecedented size. DIRT is an online platform that enables researchers to store images of plant roots, measure dicot and monocot root traits under field conditions, and share data and results within collaborative teams and the broader community. Here, we present an open-source phenomics platform “DIRT”, as a means to integrate scalable supercomputing architectures into field experiments and analysis pipelines. Automated high-throughput phenotyping methods are increasingly used in laboratory-based efforts to link plant genotype with phenotype, whereas similar field-based studies remain predominantly manual low-throughput. Most prior approaches have solely focused on the estimation of root traits from images, yet no integrated platform exists that allows easy and intuitive access to trait extraction and analysis methods from images combined with storage solutions linked to metadata. Putting this potential into practice requires new methods and algorithms to analyze CRSA in digital images. These technologies have the potential to accelerate the progress in understanding the genetic control and environmental response of CRSA. Many new technologies have been developed to characterize crop root system architecture (CRSA).
They are also under-explored targets to meet global food and energy demands.
#P dirt 3 images drivers
Plant root systems are key drivers of plant function and yield.
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