Rice increases phosphorus uptake in strongly sorbing soils by intra-root facilitation.

Upland rice (Oryza sativa) is adapted to strongly phosphorus (P) sorbing soils. The mechanisms underlying P acquisition, however, are not well understood, and models typically underestimate uptake. This complicates root ideotype development and trait-based selection for further improvement. We present a novel model, which correctly simulates the P uptake by a P-efficient rice genotype measured over 48 days of growth. The model represents root morphology at the local rhizosphere scale, including root hairs and fine S-type laterals. It simulates fast- and slowly reacting soil P and the P-solubilizing effect of root-induced pH changes in the soil. Simulations predict that the zone of pH changes and P solubilization around a root spreads further into the soil than the zone of P depletion. A root needs to place laterals outside its depletion- but inside its solubilization zone to maximize P uptake. S-type laterals, which are short but hairy, appear to be the key root structures to achieve that. Thus, thicker roots facilitate the P uptake by fine lateral roots. Uptake can be enhanced through longer root hairs and greater root length density but was less sensitive to total root length and root class proportions.

Simulating Crop Root Systems Using OpenSimRoot.

Functional-structural plant models are valuable modeling tools in analyzing plant development. A functional-structural plant model combines a three-dimensional representation of plant structure with models for physiological functions in order to better understand plant development. We present a guide to simulating crop root systems with OpenSimRoot, a feature-rich, highly cited, and open-source functional-structural root architecture model. We describe in detail how to create your own input files in conjunction with some examples. The aim of this guide is to highlight the potential of computational modeling in biology and to make modeling more accessible to the plant science community.

Spatially Resolved Root Water Uptake Determination Using a Precise Soil Water Sensor.

To answer long-standing questions about how plants use and regulate water, an affordable, noninvasive way to determine local root water uptake (RWU) is required. Here, we present a sensor, the soil water profiler (SWaP), which can determine local soil water content (θ) with a precision of 6.10-5 cm3 ⋅ cm-3, an accuracy of 0.002 cm3 ⋅ cm-3, a temporal resolution of 24 min, and a one-dimensional spatial resolution of 1 cm. The sensor comprises two copper sheets, integrated into a sleeve and connected to a coil, which form a resonant circuit. A vector network analyzer, inductively coupled to the resonant circuit, measures the resonance frequency, against which θ was calibrated. The sensors were integrated into a positioning system, which measures θ along the depth of cylindrical tubes. When combined with modulating light (4-h period) and resultant modulating plant transpiration, the SWaP enables quantification of the component of RWU distribution that varies proportionally with total plant water uptake, and distinguishes it from soil water redistribution via soil pores and roots. Additionally, as a young, growing maize (Zea mays) plant progressively tapped its soil environment dry, we observed clear changes in plant-driven RWU and soil water redistribution profiles. Our SWaP setup can measure the RWU and redistribution of sandy-soil water content with unprecedented precision. The SWaP is therefore a promising device offering new insights into soil-plant hydrology, with applications for functional root phenotyping in nonsaline, temperature-controlled conditions, at low cost.

Modelling strategies for assessing and increasing the effectiveness of new phenotyping techniques in plant breeding.

New types of phenotyping tools generate large amounts of data on many aspects of plant physiology and morphology with high spatial and temporal resolution. These new phenotyping data are potentially useful to improve understanding and prediction of complex traits, like yield, that are characterized by strong environmental context dependencies, i.e., genotype by environment interactions. For an evaluation of the utility of new phenotyping information, we will look at how this information can be incorporated in different classes of genotype-to-phenotype (G2P) models. G2P models predict phenotypic traits as functions of genotypic and environmental inputs. In the last decade, access to high-density single nucleotide polymorphism markers (SNPs) and sequence information has boosted the development of a class of G2P models called genomic prediction models that predict phenotypes from genome wide marker profiles. The challenge now is to build G2P models that incorporate simultaneously extensive genomic information alongside with new phenotypic information. Beyond the modification of existing G2P models, new G2P paradigms are required. We present candidate G2P models for the integration of genomic and new phenotyping information and illustrate their use in examples. Special attention will be given to the modelling of genotype by environment interactions. The G2P models provide a framework for model based phenotyping and the evaluation of the utility of phenotyping information in the context of breeding programs.

WS2 Nanotubes, 2D Nanomeshes, and 2D In-Plane Films through One Single Chemical Vapor Deposition Route.

We demonstrate a versatile, catalyst free chemical vapor deposition process on insulating substrates capable of producing in one single stream one-dimensional (1D) WO3- x suboxides leading to a wide range of substrate-supported 2H-WS2 polymorphs: a tunable class of out-of-plane (of the substrate) nanophases, with 1D nanotubes and a pure WS2, two-dimensional (2D) nanomesh (defined as a network of webbed, micron-size, few-layer 2D sheets) at its extremes; and in-plane (parallel to the substrate) mono- and few-layer 2D domains. This entails a two-stage approach in which the 2WO3 + 7S → 2WS2 + 3SO2 reaction is intentionally decoupled. First, various morphologies of nanowires or nanorods of high stoichiometry, WO2.92/WO2.9 suboxides (belonging to the class of Magnéli phases) were formed, followed by their sulfurization to undergo reduction to the aforementioned WS2 polymorphs. The continuous transition of WS2 from nanotubes to the out-of-plane 2D nanomesh, via intermediary, mixed 1D-2D phases, delivers tunable functional properties, for example, linear and nonlinear optical properties, such as reflectivity (linked to optical excitations in the material), and second harmonic generation (SHG) and onset of saturable absorption. The SHG effect is very strong across the entire tunable class of WS2 nanomaterials, weakest in nanotubes, and strongest in the 2D nanomesh. Furthermore, a mechanism via suboxide (WO3- x) intermediate as a possible path to 2D domain growth is demonstrated. 2D, in-plane WS2 domains grow via "self-seeding and feeding" where short WO2.92/WO2.9 nanorods provide both the nucleation sites and the precursor feedstock. Understanding the reaction path (here, in the W-O-S space) is an emerging approach toward controlling the nucleation, growth, and morphology of 2D domains and films of transition-metal dichalcogenides.

Second Harmonic Spectroscopy of Surface Lattice Resonances.

Because of their large figures of merit, surface lattice resonances (SLRs) in metal nanoparticle arrays are very promising for chemical and biomolecular sensing in both liquid and gas media. SLRs are sensitive to refractive index changes both near the surface of the nanoparticles (surface sensitivity) and in the volume between them (bulk sensitivity). Because of its intrinsic surface-sensitivity and a power law dependence on electric fields, second harmonic generation (SHG) spectroscopy can improve upon both the surface and volume sensitivities of SLRs. In this report on SHG spectroscopy of plasmonic nanoparticles, we show that the SHG signal is greatly increased (up to 450 times) by the SLRs. We also demonstrate very narrow resonances in SHG intensity (∼5 nm fwhm). We illustrate how the SHG resonances are highly sensitive to SLRs by varying the fundamental wavelength, angle of incidence, nanoparticle material, and lattice constant of the arrays. Finally, we identify an SHG resonance (10 nm fwhm) that is electric dipole forbidden and can be attributed to higher-order multipoles, enhanced by the strong near-fields of SLRs. Our results open up new and very promising avenues for chemical and biomolecular sensing based on SHG spectroscopy of SLRs.

Second-Harmonic Generation Optical Rotation Solely Attributable to Chirality in Plasmonic Metasurfaces.

Chiral plasmonic nanostructures, those lacking mirror symmetry, can be designed to manipulate the polarization of incident light resulting in chiroptical (chiral optical) effects such as circular dichroism (CD) and optical rotation (OR). Due to high symmetry sensitivity, corresponding effects in second-harmonic generation (SHG-CD and SHG-OR) are typically much stronger in comparison. These nonlinear effects have long been used for chiral molecular analysis and characterization; however both linear and nonlinear optical rotation can occur even in achiral structures, if the structure is birefringent due to anisotropy. Crucially, chiroptical effects resulting from anisotropy typically exhibit a strong dependence on structural orientation. Here we report a large second-harmonic generation optical rotation of ±45°, due to intrinsic chirality in a highly anisotropic helical metamaterial. The SHG intensity is found to strongly relate to the structural anisotropy; however, the angle of SHG-OR is invariant under sample rotation. We show that by tuning the geometry of anisotropic nanostructures, the interaction between anisotropy, chirality, and experimental geometry can allow even greater control over the chiroptical properties of plasmonic metamaterials.

Root Cortical Senescence Improves Growth under Suboptimal Availability of N, P, and K.

Root cortical senescence (RCS) in Triticeae reduces nutrient uptake, nutrient content, respiration, and radial hydraulic conductance of root tissue. We used the functional-structural model SimRoot to evaluate the functional implications of RCS in barley (Hordeum vulgare) under suboptimal nitrate, phosphorus, and potassium availability. The utility of RCS was evaluated using sensitivity analyses in contrasting nutrient regimes. At flowering (80 d), RCS increased simulated plant growth by up to 52%, 73%, and 41% in nitrate-, phosphorus-, and potassium-limiting conditions, respectively. Plants with RCS had reduced nutrient requirement of root tissue for optimal plant growth, reduced total cumulative cortical respiration, and increased total carbon reserves. Nutrient reallocation during RCS had a greater effect on simulated plant growth than reduced respiration or nutrient uptake. Under low nutrient availability, RCS had greater benefit in plants with fewer tillers. RCS had greater benefit in phenotypes with fewer lateral roots at low nitrate availability, but the opposite was true in low phosphorus or potassium availability. Additionally, RCS was quantified in field-grown barley in different nitrogen regimes. Field and virtual soil coring simulation results demonstrated that living cortical volume per root length (an indicator of RCS) decreased with depth in younger plants, while roots of older plants had very little living cortical volume per root length. RCS may be an adaptive trait for nutrient acquisition by reallocating nutrients from senescing tissue and secondarily by reducing root respiration. These simulated results suggest that RCS merits investigation as a breeding target for enhanced soil resource acquisition and edaphic stress tolerance.

OpenSimRoot: widening the scope and application of root architectural models.

OpenSimRoot is an open-source, functional-structural plant model and mathematical description of root growth and function. We describe OpenSimRoot and its functionality to broaden the benefits of root modeling to the plant science community. OpenSimRoot is an extended version of SimRoot, established to simulate root system architecture, nutrient acquisition and plant growth. OpenSimRoot has a plugin, modular infrastructure, coupling single plant and crop stands to soil nutrient and water transport models. It estimates the value of root traits for water and nutrient acquisition in environments and plant species. The flexible OpenSimRoot design allows upscaling from root anatomy to plant community to estimate the following: resource costs of developmental and anatomical traits; trait synergisms; and (interspecies) root competition. OpenSimRoot can model three-dimensional images from magnetic resonance imaging (MRI) and X-ray computed tomography (CT) of roots in soil. New modules include: soil water-dependent water uptake and xylem flow; tiller formation; evapotranspiration; simultaneous simulation of mobile solutes; mesh refinement; and root growth plasticity. OpenSimRoot integrates plant phenotypic data with environmental metadata to support experimental designs and to gain a mechanistic understanding at system scales.

Surface-Enhanced Raman Spectroscopy: A Facile and Rapid Method for the Chemical Component Study of Individual Atmospheric Aerosol.

A simple and rapid method for detecting chemical components of individual aerosol particles on Klarite substrate with surface-enhanced Raman spectroscopy (SERS) is described. For both single simulated aerosol particles and ambient atmospheric particles, this new analytical method promotes the enhancement factor of the Raman signal. The spectra of ammonium sulfate and naphthalene particles at the microscopic level are enhanced by a factor of 6 and therefore greatly improve the detection of the chemical composition of an individual aerosol particle. When aerosol particles are found over a microscopic domain, a set of Raman spectra with chemical information can be obtained via SERS mapping. The maps illustrate the distribution of organic or inorganic species on the SERS substrate. This constitutes a facile and rapid method to study aerosol particles. This new method allows the analysis of chemical composition in single aerosol particles, demonstrating the power of SERS to probe the ambient atmospheric particles and to study the formation of aerosol particles.

Strong Rotational Anisotropies Affect Nonlinear Chiral Metamaterials.

Masked by rotational anisotropies, xthe nonlinear chiroptical response of a metamaterial is initially completely inaccessible. Upon rotating the sample the chiral information emerges. These results highlight the need for a general method to extract the true chiral contributions to the nonlinear optical signal, which would be hugely valuable in the present context of increasingly complex chiral meta/nanomaterials.