Publications by authors named "James Burridge"

14 Publications

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An Analysis of Soil Coring Strategies to Estimate Root Depth in Maize () and Common Bean ().

Plant Phenomics 2020 8;2020:3252703. Epub 2020 Nov 8.

The Pennsylvania State University, Department of Plant Science, Tyson Building, University Park, PA 16802, USA.

A soil coring protocol was developed to cooptimize the estimation of root length distribution (RLD) by depth and detection of functionally important variation in root system architecture (RSA) of maize and bean. The functional-structural model was used to perform soil coring at six locations on three different maize and bean RSA phenotypes. Results were compared to two seasons of field soil coring and one trench. Two one-sided -test (TOST) analysis of data suggests a between-row location 5 cm from plant base (location 3), best estimates whole-plot RLD/D of deep, intermediate, and shallow RSA phenotypes, for both maize and bean. Quadratic discriminant analysis indicates location 3 has ~70% categorization accuracy for bean, while an in-row location next to the plant base (location 6) has ~85% categorization accuracy in maize. Analysis of field data suggests the more representative sampling locations vary by year and species. and field studies suggest location 3 is most robust, although variation is significant among seasons, among replications within a field season, and among field soil coring, trench, and simulations. We propose that the characterization of the RLD profile as a dynamic rhizo canopy effectively describes how the RLD profile arises from interactions among an individual plant, its neighbors, and the pedosphere.
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http://dx.doi.org/10.34133/2020/3252703DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7706327PMC
November 2020

Root metaxylem and architecture phenotypes integrate to regulate water use under drought stress.

Plant Cell Environ 2021 01 30;44(1):49-67. Epub 2020 Sep 30.

Department of Plant Science, The Pennsylvania State University, University Park, Pennsylvania, USA.

At the genus and species level, variation in root anatomy and architecture may interact to affect strategies of drought avoidance. To investigate this idea, root anatomy and architecture of the drought-sensitive common bean (Phaseolus vulgaris) and drought-adapted tepary bean (Phaseolus acutifolius) were analyzed in relation to water use under terminal drought. Intraspecific variation for metaxylem anatomy and axial conductance was found in the roots of both species. Genotypes with high-conductance root metaxylem phenotypes acquired and transpired more water per unit leaf area, shoot mass, and root mass than genotypes with low-conductance metaxylem phenotypes. Interspecific variation in root architecture and root depth was observed where P. acutifolius has a deeper distribution of root length than P. vulgaris. In the deeper-rooted P. acutifolius, genotypes with high root conductance were better able to exploit deep soil water than genotypes with low root axial conductance. Contrastingly, in the shallower-rooted P. vulgaris, genotypes with low root axial conductance had improved water status through conservation of soil moisture for sustained water capture later in the season. These results indicate that metaxylem morphology interacts with root system depth to determine a strategy of drought avoidance and illustrate synergism among architectural and anatomical phenotypes for root function.
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http://dx.doi.org/10.1111/pce.13875DOI Listing
January 2021

ASTEROID: A New Clinical Stereotest on an Autostereo 3D Tablet.

Transl Vis Sci Technol 2019 Jan 28;8(1):25. Epub 2019 Feb 28.

Institute of Neuroscience, Newcastle University, Framlington Place, Newcastle upon Tyne, UK.

Purpose: To describe a new stereotest in the form of a game on an autostereoscopic tablet computer designed to be suitable for use in the eye clinic and present data on its reliability and the distribution of stereo thresholds in adults.

Methods: Test stimuli were four dynamic random-dot stereograms, one of which contained a disparate target. Feedback was given after each trial presentation. A Bayesian adaptive staircase adjusted target disparity. Threshold was estimated from the mean of the posterior distribution after 20 responses. Viewing distance was monitored via a forehead sticker viewed by the tablet's front camera, and screen parallax was adjusted dynamically so as to achieve the desired retinal disparity.

Results: The tablet must be viewed at a distance of greater than ∼35 cm to produce a good depth percept. Log thresholds were roughly normally distributed with a mean of 1.75 log arcsec = 56 arcsec and SD of 0.34 log arcsec = a factor of 2.2. The standard deviation agrees with previous studies, but ASTEROID thresholds are approximately 1.5 times higher than a similar stereotest on stereoscopic 3D TV or on Randot Preschool stereotests. Pearson correlation between successive tests in same observer was 0.80. Bland-Altman 95% limits of reliability were ±0.64 log arcsec = a factor of 4.3, corresponding to an SD of 0.32 log arcsec on individual threshold estimates. This is similar to other stereotests and close to the statistical limit for 20 responses.

Conclusions: ASTEROID is reliable, easy, and portable and thus well-suited for clinical stereoacuity measurements.

Translational Relevance: New 3D digital technology means that research-quality psychophysical measurement of stereoacuity is now feasible in the clinic.
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http://dx.doi.org/10.1167/tvst.8.1.25DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6396686PMC
January 2019

Unifying models of dialect spread and extinction using surface tension dynamics.

Authors:
James Burridge

R Soc Open Sci 2018 Jan 3;5(1):171446. Epub 2018 Jan 3.

Department of Mathematics, University of Portsmouth, Portsmouth, UK.

We provide a unified mathematical explanation of two classical forms of spatial linguistic spread. The model describes the radiation of linguistic change outwards from a central focus. Changes can also jump between population centres in a process known as . It has recently been proposed that the spatial evolution of dialects can be understood using surface tension at linguistic boundaries. Here we show that the inclusion of long-range interactions in the surface tension model generates both wave-like spread, and hierarchical diffusion, and that it is surface tension that is the dominant effect in deciding the stable distribution of dialect patterns. We generalize the model to allow population mixing which can induce shrinkage of linguistic domains, or destroy dialect regions from within.
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http://dx.doi.org/10.1098/rsos.171446DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5792924PMC
January 2018

Infrequent social interaction can accelerate the spread of a persuasive idea.

Phys Rev E 2016 Dec 30;94(6-1):062319. Epub 2016 Dec 30.

Department of Mathematics, University of Portsmouth, Lion Terrace, Portsmouth PO1 3HF, United Kingdom.

We study the spread of a persuasive new idea through a population of continuous-time random walkers in one dimension. The idea spreads via social gatherings involving groups of nearby walkers who act according to a biased "majority rule": After each gathering, the group takes on the new idea if more than a critical fraction 1-ɛ/2<1/2 of them already hold it; otherwise they all reject it. The boundary of a domain where the new idea has taken hold expands as a traveling wave in the density of new idea holders. Our walkers move by Lévy motion, and we compute the wave velocity analytically as a function of the frequency of social gatherings and the exponent of the jump distribution. When this distribution is sufficiently heavy tailed, then, counter to intuition, the idea can propagate faster if social gatherings are held less frequently. When jumps are truncated, a critical gathering frequency can emerge which maximizes propagation velocity. We explore our model by simulation, confirming our analytical results.
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http://dx.doi.org/10.1103/PhysRevE.94.062319DOI Listing
December 2016

Genome-wide association mapping and agronomic impact of cowpea root architecture.

Theor Appl Genet 2017 Feb 18;130(2):419-431. Epub 2016 Nov 18.

Department of Plant Science, The Pennsylvania State University, 221 Tyson Building, University Park, PA, 16802, USA.

Key Message: Genetic analysis of data produced by novel root phenotyping tools was used to establish relationships between cowpea root traits and performance indicators as well between root traits and Striga tolerance. Selection and breeding for better root phenotypes can improve acquisition of soil resources and hence crop production in marginal environments. We hypothesized that biologically relevant variation is measurable in cowpea root architecture. This study implemented manual phenotyping (shovelomics) and automated image phenotyping (DIRT) on a 189-entry diversity panel of cowpea to reveal biologically important variation and genome regions affecting root architecture phenes. Significant variation in root phenes was found and relatively high heritabilities were detected for root traits assessed manually (0.4 for nodulation and 0.8 for number of larger laterals) as well as repeatability traits phenotyped via DIRT (0.5 for a measure of root width and 0.3 for a measure of root tips). Genome-wide association study identified 11 significant quantitative trait loci (QTL) from manually scored root architecture traits and 21 QTL from root architecture traits phenotyped by DIRT image analysis. Subsequent comparisons of results from this root study with other field studies revealed QTL co-localizations between root traits and performance indicators including seed weight per plant, pod number, and Striga (Striga gesnerioides) tolerance. The data suggest selection for root phenotypes could be employed by breeding programs to improve production in multiple constraint environments.
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http://dx.doi.org/10.1007/s00122-016-2823-yDOI Listing
February 2017

Birdsong dialect patterns explained using magnetic domains.

Phys Rev E 2016 Jun 1;93(6):062402. Epub 2016 Jun 1.

Department of Mathematics, University of Portsmouth, Portsmouth, PO1 3HF, United Kingdom.

The songs and calls of many bird species, like human speech, form distinct regional dialects. We suggest that the process of dialect formation is analogous to the physical process of magnetic domain formation. We take the coastal breeding grounds of the Puget Sound white crowned sparrow as an example. Previous field studies suggest that birds of this species learn multiple songs early in life, and when establishing a territory for the first time, retain one of these dialects in order to match the majority of their neighbors. We introduce a simple lattice model of the process, showing that this matching behavior can produce single dialect domains provided the death rate of adult birds is sufficiently low. We relate death rate to thermodynamic temperature in magnetic materials, and calculate the critical death rate by analogy with the Ising model. Using parameters consistent with the known behavior of these birds we show that coastal dialect domain shapes may be explained by viewing them as low-temperature "stripe states."
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http://dx.doi.org/10.1103/PhysRevE.93.062402DOI Listing
June 2016

Limit cycles and the benefits of a short memory in rock-paper-scissors games.

Authors:
James Burridge

Phys Rev E Stat Nonlin Soft Matter Phys 2015 Oct 5;92(4):042111. Epub 2015 Oct 5.

Department of Mathematics, University of Portsmouth, Portsmouth PO1 2UP, United Kingdom.

When playing games in groups, it is an advantage for individuals to have accurate statistical information on the strategies of their opponents. Such information may be obtained by remembering previous interactions. We consider a rock-paper-scissors game in which agents are able to recall their last m interactions, used to estimate the behavior of their opponents. At critical memory length, a Hopf bifurcation leads to the formation of stable limit cycles. In a mixed population, agents with longer memories have an advantage, provided the system has a stable fixed point, and there is some asymmetry in the payoffs of the pure strategies. However, at a critical concentration of long memory agents, the appearance of limit cycles destroys their advantage. By introducing population dynamics that favors successful agents, we show that the system evolves toward the bifurcation point.
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http://dx.doi.org/10.1103/PhysRevE.92.042111DOI Listing
October 2015

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

Plant Methods 2015 2;11:51. Epub 2015 Nov 2.

School of Biology, Georgia Institute of Technology, Atlanta, GA USA ; School of Interactive Computing, Georgia Institute of Technology, Atlanta, GA USA.

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.
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http://dx.doi.org/10.1186/s13007-015-0093-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4630929PMC
November 2015

Forgetfulness can help you win games.

Phys Rev E Stat Nonlin Soft Matter Phys 2015 Sep 14;92(3):032119. Epub 2015 Sep 14.

School of Physics and Astronomy, University of Nottingham, Nottingham, NG7 2RD, United Kingdom.

We present a simple game model where agents with different memory lengths compete for finite resources. We show by simulation and analytically that an instability exists at a critical memory length, and as a result, different memory lengths can compete and coexist in a dynamical equilibrium. Our analytical formulation makes a connection to statistical urn models, and we show that temperature is mirrored by the agent's memory. Our simple model of memory may be incorporated into other game models with implications that we briefly discuss.
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http://dx.doi.org/10.1103/PhysRevE.92.032119DOI Listing
September 2015

Formation and arrangement of pits by a corrosive gas.

Phys Rev E Stat Nonlin Soft Matter Phys 2015 Feb 6;91(2):022403. Epub 2015 Feb 6.

Department of Geography, University of Portsmouth, Portsmouth PO1 3HE, United Kingdom.

When corroding or otherwise aggressive particles are incident on a surface, pits can form. For example, under certain circumstances rock surfaces that are exposed to salts can form regular tessellating patterns of pits known as "tafoni." We introduce a simple lattice model in which a gas of corrosive particles, described by a discrete, biased diffusion equation, drifts onto a surface. Each gas particle has a fixed probability of being absorbed and causing damage at each contact. The surface is represented by a lattice of strength numbers which reduce after each absorbtion event, with sites being removed when their strength becomes negative. Regular formations of pits arise spontaneously, with each pit having a characteristic trapezoidal geometry determined by the particle bias, absorbtion probability, and surface strength. The formation of this geometry may be understood in terms of a first order partial differential equation and is a consequence of particle concentration gradients which arise in the pits. By viewing pits as particle funnels, we are able to relate the gradient of pit walls to absorbtion probability and particle bias.
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http://dx.doi.org/10.1103/PhysRevE.91.022403DOI Listing
February 2015

Image-based high-throughput field phenotyping of crop roots.

Plant Physiol 2014 Oct 3;166(2):470-86. Epub 2014 Sep 3.

Schools of Biology (A.B., A.D. J.S.W.), Interactive Computing (A.B.), and Physics (J.S.W.), Georgia Institute of Technology, Atlanta, Georgia 30332; andDepartment of Plant Science (J.B., L.M.Y., E.N., J.P.L.) and Intercollege Graduate Degree Program in Ecology (L.M.Y.), Pennsylvania State University, University Park, Pennsylvania 16801.

Current plant phenotyping technologies to characterize agriculturally relevant traits have been primarily developed for use in laboratory and/or greenhouse conditions. In the case of root architectural traits, this limits phenotyping efforts, largely, to young plants grown in specialized containers and growth media. Hence, novel approaches are required to characterize mature root systems of older plants grown under actual soil conditions in the field. Imaging methods able to address the challenges associated with characterizing mature root systems are rare due, in part, to the greater complexity of mature root systems, including the larger size, overlap, and diversity of root components. Our imaging solution combines a field-imaging protocol and algorithmic approach to analyze mature root systems grown in the field. Via two case studies, we demonstrate how image analysis can be utilized to estimate localized root traits that reliably capture heritable architectural diversity as well as environmentally induced architectural variation of both monocot and dicot plants. In the first study, we show that our algorithms and traits (including 13 novel traits inaccessible to manual estimation) can differentiate nine maize (Zea mays) genotypes 8 weeks after planting. The second study focuses on a diversity panel of 188 cowpea (Vigna unguiculata) genotypes to identify which traits are sufficient to differentiate genotypes even when comparing plants whose harvesting date differs up to 14 d. Overall, we find that automatically derived traits can increase both the speed and reproducibility of the trait estimation pipeline under field conditions.
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http://dx.doi.org/10.1104/pp.114.243519DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4213080PMC
October 2014

Shocks generate crossover behavior in lattice avalanches.

Authors:
James Burridge

Phys Rev Lett 2013 Nov 18;111(21):218001. Epub 2013 Nov 18.

Department of Mathematics, University of Portsmouth, PO1 3HF, United Kingdom.

A spatial avalanche model is introduced, in which avalanches increase stability in the regions where they occur. Instability is driven globally by a driving process that contains shocks. The system is typically subcritical, but the shocks occasionally lift it into a near- or supercritical state from which it rapidly retreats due to large avalanches. These shocks leave behind a signature-a distinct power-law crossover in the avalanche size distribution. The model is inspired by landslide field data, but the principles may be applied to any system that experiences stabilizing failures, possesses a critical point, and is subject to an ongoing process of destabilization that includes occasional dramatic destabilizing events.
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http://dx.doi.org/10.1103/PhysRevLett.111.218001DOI Listing
November 2013

Crossover behavior in driven cascades.

Authors:
James Burridge

Phys Rev E Stat Nonlin Soft Matter Phys 2013 Sep 18;88(3):032124. Epub 2013 Sep 18.

Department of Mathematics, University of Portsmouth, Portsmouth PO1 3HF, United Kingdom.

We propose a model which explains how power-law crossover behavior can arise in a system which is capable of experiencing cascading failure. In our model the susceptibility of the system to cascades is described by a single number, the propagation power, which measures the ease with which cascades propagate. Physically, such a number could represent the density of unstable material in a system, its internal connectivity, or the mean susceptibility of its component parts to failure. We assume that the propagation power follows an upward drifting Brownian motion between cascades, and drops discontinuously each time a cascade occurs. Cascades are described by a continuous state branching process with distributional properties determined by the value of the propagation power when they occur. In common with many cascading models, pure power-law behavior is exhibited at a critical level of propagation power, and the mean cascade size diverges. This divergence constrains large systems to the subcritical region. We show that as a result, crossover behavior appears in the cascade distribution when an average is performed over the distribution of propagation power. We are able to analytically determine the exponents before and after the crossover.
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http://dx.doi.org/10.1103/PhysRevE.88.032124DOI Listing
September 2013