Dataset Information

Estimating parametric phenotypes that determine anthesis date in Zea mays: Challenges in combining ecophysiological models with genetics.

ABSTRACT: Ecophysiological crop models encode intra-species behaviors using parameters that are presumed to summarize genotypic properties of individual lines or cultivars. These genotype-specific parameters (GSP's) can be interpreted as quantitative traits that can be mapped or otherwise analyzed, as are more conventional traits. The goal of this study was to investigate the estimation of parameters controlling maize anthesis date with the CERES-Maize model, based on 5,266 maize lines from 11 plantings at locations across the eastern United States. High performance computing was used to develop a database of 356 million simulated anthesis dates in response to four CERES-Maize model parameters. Although the resulting estimates showed high predictive value (R2 = 0.94), three issues presented serious challenges for use of GSP's as traits. First (expressivity), the model was unable to express the observed data for 168 to 3,339 lines (depending on the combination of site-years), many of which ended up sharing the same parameter value irrespective of genetics. Second, for 2,254 lines, the model reproduced the data, but multiple parameter sets were equally effective (equifinality). Third, parameter values were highly dependent (p<10-6919) on the sets of environments used to estimate them (instability), calling in to question the assumption that they represent fundamental genetic traits. The issues of expressivity, equifinality and instability must be addressed before the genetic mapping of GSP's becomes a robust means to help solve the genotype-to-phenotype problem in crops.

SUBMITTER: Lamsal A

PROVIDER: S-EPMC5909614 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Estimating parametric phenotypes that determine anthesis date in Zea mays: Challenges in combining ecophysiological models with genetics.

Lamsal Abhishes A Welch Stephen M SM White Jeffrey W JW Thorp Kelly R KR Bello Nora M NM

PloS one 20180419 4

Ecophysiological crop models encode intra-species behaviors using parameters that are presumed to summarize genotypic properties of individual lines or cultivars. These genotype-specific parameters (GSP's) can be interpreted as quantitative traits that can be mapped or otherwise analyzed, as are more conventional traits. The goal of this study was to investigate the estimation of parameters controlling maize anthesis date with the CERES-Maize model, based on 5,266 maize lines from 11 plantings a ...[more]

PMID: 29672629

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Project description:Root hydraulic properties play a central role in the global water cycle, in agricultural systems productivity, and in ecosystem survival as they impact the canopy water supply. However, the existing experimental methods to quantify root hydraulic conductivities, such as the root pressure probing, are particularly challenging, and their applicability to thin roots and small root segments is limited. Therefore, there is a gap in methods enabling easy estimations of root hydraulic conductivities in diverse root types. Here, we present a new pipeline to quickly estimate root hydraulic conductivities across different root types, at high resolution along root axes. Shortly, free-hand root cross-sections were used to extract a selected number of key anatomical traits. We used these traits to parametrize the Generator of Root Anatomy in R (GRANAR) model to simulate root anatomical networks. Finally, we used these generated anatomical networks within the Model of Explicit Cross-section Hydraulic Anatomy (MECHA) to compute an estimation of the root axial and radial hydraulic conductivities (k x and k r , respectively). Using this combination of anatomical data and computational models, we were able to create a root hydraulic conductivity atlas at the root system level, for 14-day-old pot-grown Zea mays (maize) plants of the var. B73. The altas highlights the significant functional variations along and between different root types. For instance, predicted variations of radial conductivity along the root axis were strongly dependent on the maturation stage of hydrophobic barriers. The same was also true for the maturation rates of the metaxylem vessels. Differences in anatomical traits along and across root types generated substantial variations in radial and axial conductivities estimated with our novel approach. Our methodological pipeline combines anatomical data and computational models to turn root cross-section images into a detailed hydraulic atlas. It is an inexpensive, fast, and easily applicable investigation tool for root hydraulics that complements existing complex experimental methods. It opens the way to high-throughput studies on the functional importance of root types in plant hydraulics, especially if combined with novel phenotyping techniques such as laser ablation tomography.

Project description:BackgroundHealth risks arising from heavy metal pollution have attracted global attention. As a result, many studies on the accumulation of heavy metals in soil-plant systems have performed human health risk assessments.ObjectivesWe aimed to examine the ability of Zea mays (maize) to accumulate heavy metals and assess the bioaccumulation factor (BAF) by collecting, collating, and analyzing data on heavy metal concentrations in Zea mays.MethodsThis study reviewed the accumulation of five selected heavy metals, cadmium (Cd), chromium (Cr), lead (Pb), copper (Cu), and zinc (Zn) in soil and the corresponding BAF of Zea mays grown on those soils using a systematic search of peer-reviewed scientific journals. A total of 27 research works were reviewed after screening 52 articles for subject matter relevancy, including dumpsites, industrially polluted soils, inorganically fertilized soils, mining sites, smelting sites, municipal wastewater irrigated soils, and a battery waste dumpsite.ResultsAmong the reviewed sites, concentrations of Cd and Cr were highest at a tin mining site, where prolonged mining, mineral processing and other production activities contributed heavy metal pollution in the soil. The soil at a battery waste dumpsite exhibited the highest Pb concentration, while the soil at a Zn smelting site presented the highest concentration of Zn. The highest soil Cu concentration was found in an area where sewage irrigation had been carried out over a long period. The BAF of the five heavy metals in Zea mays increased with the metal concentrations in the soil. The BAF of Cd, Cr, Pb, Cu, and Zn in Zea mays from the study areas fall within the ranges of 0-0.95, 0-1.89, 0-1.20, 0.011-0.99, and 0.03-0.99, respectively. Cadmium and Zn had the highest bioconcentration factors values in maize plants, likely due to their higher mobility rate compared to the other heavy metals.ConclusionsThe study concluded that Zea mays is capable of accumulating high amounts of heavy metals, although accumulation of these heavy metals is influenced by multiple factors including soil texture, cation exchange capacity, root exudation and especially soil pH and chemical forms of the heavy metals. Zea mays should not be planted on metal-contaminated soils because of its potential to act as a hyperaccumulator.Competing interestsThe authors declare no competing financial interests.

Dataset Information

Estimating parametric phenotypes that determine anthesis date in Zea mays: Challenges in combining ecophysiological models with genetics.

Publications

Estimating parametric phenotypes that determine anthesis date in Zea mays: Challenges in combining ecophysiological models with genetics.

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