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Digital imaging of root traits (DIRT): a high-throughput computing and collaboration platform for field-based root phenomics

机译:根性状的数字成像(DIRT):高通量计算和协作平台,用于基于字段的根表型

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Background Plant root systems are key drivers of plant function and yield. They are also under-explored targets to meet global food and energy demands. Many new technologies have been developed to characterize crop root system architecture (CRSA). These technologies have the potential to accelerate the progress in understanding the genetic control and environmental response of CRSA. Putting this potential into practice requires new methods and algorithms to analyze CRSA in digital images. 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. 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. Description Here, we present an open-source phenomics platform “DIRT”, as a means to integrate scalable supercomputing architectures into field experiments and analysis pipelines. 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. 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. Conclusion DIRT is an automated high-throughput computing and collaboration platform for field based crop root phenomics. The platform is accessible at http://www.dirt.iplantcollaborative.org/ and hosted on the iPlant cyber-infrastructure using high-throughput grid computing resources of the Texas Advanced Computing Center (TACC). DIRT is a high volume central depository and high-throughput RSA trait computation platform for plant scientists working on crop roots. It enables scientists to store, manage and share crop root images with metadata and compute RSA traits from thousands of images in parallel. It makes high-throughput RSA trait computation available to the community with just a few button clicks. As such it enables plant scientists to spend more time on science rather than on technology. All stored and computed data is easily accessible to the public and broader scientific community. We hope that easy data accessibility will attract new tool developers and spur creative data usage that may even be applied to other fields of science.
机译:背景技术植物根系是植物功能和产量的关键驱动因素。它们还是满足全球粮食和能源需求的探索目标。已经开发出许多新技术来表征作物根系体系结构(CRSA)。这些技术有可能加速对CRSA的遗传控制和环境响应的了解。将这种潜力付诸实践需要新的方法和算法来分析数字图像中的CRSA。大多数现有方法仅专注于从图像估计根性状,但尚不存在允许从图像中结合结合元数据的存储解决方案轻松直观地访问性状提取和分析方法的集成平台。在基于实验室的研究中,越来越多地使用自动化的高通量表型方法来将植物基因型与表型联系起来,而类似的基于现场的研究仍主要是人工的低通量。描述在这里,我们提出一个开源的表象学平台“ DIRT”,作为将可扩展的超级计算架构集成到现场实验和分析管道中的一种手段。 DIRT是一个在线平台,使研究人员能够存储植物根部图像,在田间条件下测量双子叶植物和单子叶植物的性状,并在协作团队和更广泛的社区中共享数据和结果。 DIRT平台将最终用户与大规模计算“通用”无缝连接起来,从而能够通过空前规模的田间试验估算和分析根表型。结论DIRT是用于基于田间作物根表型的自动化高通量计算和协作平台。该平台可在http://www.dirt.iplantcollaborative.org/上访问,并使用德州高级计算中心(TACC)的高吞吐量网格计算资源托管在iPlant网络基础设施上。 DIRT是面向植物根部植物科学家的高容量中央保藏库和高通量RSA特性计算平台。它使科学家能够使用元数据存储,管理和共享农作物根图像,并从数千幅图像中并行计算出RSA特征。只需单击几下鼠标,社区就可以使用高吞吐量的RSA特征计算。因此,它使植物科学家可以将更多的时间花在科学上而不是技术上。公众和更广泛的科学界都可以轻松访问所有存储和计算的数据。我们希望轻松的数据可访问性将吸引新的工具开发人员,并刺激甚至可能应用于其他科学领域的创造性数据使用。

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