Measuring root system traits of wheat in 2D images to parameterize 3D root architecture models

Background and aimsThe main difficulty in the use of 3D root architecture models is correct parameterization. We evaluated distributions of the root traits inter-branch distance, branching angle and axial root trajectories from contrasting experimental systems to improve model parameterization.MethodsWe analyzed 2D root images of different wheat varieties (Triticum aestivum) from three different sources using automatic root tracking. Model input parameters and common parameter patterns were identified from extracted root system coordinates. Simulation studies were used to (1) link observed axial root trajectories with model input parameters (2) evaluate errors due to the 2D (versus 3D) nature of image sources and (3) investigate the effect of model parameter distributions on root foraging performance.ResultsDistributions of inter-branch distances were approximated with lognormal functions. Branching angles showed mean values <90°. Gravitropism and tortuosity parameters were quantified in relation to downwards reorientation and segment angles of root axes. Root system projection in 2D increased the variance of branching angles. Root foraging performance was very sensitive to parameter distribution and variance.Conclusions2D image analysis can systematically and efficiently analyze root system architectures and parameterize 3D root architecture models. Effects of root system projection (2D from 3D) and deflection (at rhizotron face) on size and distribution of particular parameters are potentially significant

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

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.DescriptionHere, 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.ConclusionDIRT is an automated high-throughput computing and collaboration platform for field based crop root phenomics. The platform is accessible at http://​dirt.​iplantcollaborat​ive.​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

Root biology never sleeps

11th Symposium of the International Society of Root Research (ISRR11) and the 9th International Symposium on Root Development (Rooting2021), 24–28 May 2021. Emerging frontiers: root and rhizosphere research in the context of global environmental change. Natural ecosystems and agricultural production have been threatened by multifaceted global environmental changes. Soil degradation, extreme drought and flooding events, shifting climatic patterns and other challenges have prompted many disciplines within plant science to pivot to find solutions. Accordingly, root research has expanded from fundamental studies on roots, as providers of physical support, water, and essential nutrients uptake, towards identification of beneficial traits for stress adaptation and control of key biological soil processes. Advances in trait identification, data acquisition, management and modelling are enabling root researchers to develop predictive models to support ecosystems in these changing environments. Through technical presentations, posters, industry exhibits and a root phenotyping workshop, the international, jointly presented, completely virtual International Society of Root Research (ISRR)11/Rooting2021 meeting provided a unique platform for researchers across disciplines to share recent advances in root biology, from molecular to ecosystem-level scales, in agricultural and natural ecosystems, addressing critical questions in response to climate change and its impact on crop productivity and ecosystem services. In this report, the 2021 ISRR Ambassador cohort provides an overview of the current root research landscape and reflection on the importance of frontier research for a more sustainable future

Physiological and biochemical parameters: new tools to screen barley root exudates allelopathic potential (*Hordeum vulgare* L. subsp. *vulgare*

peer reviewedMorphological markers/traits are often used in the detection of allelopathic stress, but optical signals including chlorophyll a fluorescence emission could be useful in developing new screening techniques. In this context, the allelopathic effect of barley (Hordeum vulgare subsp. vulgare) root exudates (three modern varieties and three landraces) were assessed on the morphological (root and shoot length, biomass accumulation), physiological (Fv/Fm and F0), and biochemical (chlorophyll and protein contents) variables of great brome (Bromus diandrus Roth., syn. Bromus rigidus Roth. subsp. gussonii Parl.). All the measured traits were affected when great brome was grown in a soil substrate in which barley plants had previously developed for 30 days before being removed. The response of receiver plants was affected by treatment with activated charcoal, dependent on barley genotype and on the nature of the growing substrate. The inhibitory effect was lower with the addition of the activated charcoal suggesting the release of putative allelochemicals from barley roots into the soil. The barley landraces were more toxic than modern varieties and their effect was more pronounced in sandy substrate than in silty clay sand substrate. In our investigation, the chlorophyll content and Fv/Fm were the most correlated variables with barley allelopathic potential. These two parameters might be considered as effective tools to quantify susceptibility to allelochemical inhibitors in higher plants