Johannes A. Postma

Pot size matters: a meta-analysis of the effects of rooting volume on plant growth

The majority of experiments in plant biology use plants grown in some kind of container or pot. We conducted a meta-analysis on 65 studies that analysed the effect of pot size on growth and underlying variables. On average, a doubling of the pot size increased biomass production by 43%. Further analysis of pot size effects on the underlying components of growth suggests that reduced growth in smaller pots is caused mainly by a reduction in photosynthesis per unit leaf area, rather than by changes in leaf morphology or biomass allocation. The appropriate pot size will logically depend on the size of the plants growing in them. Based on various lines of evidence we suggest that an appropriate pot size is one in which the plant biomass does not exceed 1gL-1. In current research practice ~65% of the experiments exceed that threshold. We suggest that researchers need to carefully consider the pot size in their experiments, as small pots may change experimental results and defy the purpose of the experiment.

Root Cortical Aerenchyma Enhances the Growth of Maize on Soils with Suboptimal Availability of Nitrogen, Phosphorus, and Potassium

Root cortical aerenchyma (RCA) is induced by hypoxia, drought, and several nutrient deficiencies. Previous research showed that RCA formation reduces the respiration and nutrient content of root tissue. We used SimRoot, a functional-structural model, to provide quantitative support for the hypothesis that RCA formation is a useful adaptation to suboptimal availability of phosphorus, nitrogen, and potassium by reducing the metabolic costs of soil exploration in maize (Zea mays). RCA increased the growth of simulated 40-d-old maize plants up to 55%, 54%, or 72% on low nitrogen, phosphorus, or potassium soil, respectively, and reduced critical fertility levels by 13%, 12%, or 7%, respectively. The greater utility of RCA on low-potassium soils is associated with the fact that root growth in potassium-deficient plants was more carbon limited than in phosphorus- and nitrogen-deficient plants. In contrast to potassium-deficient plants, phosphorus- and nitrogen-deficient plants allocate more carbon to the root system as the deficiency develops. The utility of RCA also depended on other root phenes and environmental factors. On low-phosphorus soils (7.5 μm), the utility of RCA was 2.9 times greater in plants with increased lateral branching density than in plants with normal branching. On low-nitrate soils, the utility of RCA formation was 56% greater in coarser soils with high nitrate leaching. Large genetic variation in RCA formation and the utility of RCA for a range of stresses position RCA as an interesting crop-breeding target for enhanced soil resource acquisition.

Modelling root–soil interactions using three–dimensional models of root growth, architecture and function

BackgroundThree–dimensional root architectural models emerged in the late 1980s, providing an opportunity to conceptualise and investigate that all important part of plants that is typically hidden and difficult to measure and study. These models have progressed from representing pre–defined root architectural arrangements, to simulating root growth in response to heterogeneous soil environments. This was done through incorporating soil properties and more complete descriptions of plant function, moving into the realm of functional-structural plant modelling. Modelling studies are often designed to investigate the relationship between root architectural traits and root distribution in soil, and the spatio–temporal variability of resource supply. Modelling root systems presents an opportunity to investigate functional tradeoffs between foraging strategies (i.e. shallow vs deep rooting) for contrasting resources (immobile versus mobile resources), and their dependence on soil type, rainfall and other environmental conditions. The complexity of the interactions between root traits and environment emphasises the need for models in which traits and environmental conditions can be independently manipulated, unlike in the real world.ScopeWe provide an overview of the development of three–dimensional root architectural models from their origins, to their place today in the world of functional–structural plant modelling. The uses and capability of root architectural models to represent virtual plants and soil environment are addressed. We compare features of six current models, RootTyp, SimRoot, ROOTMAP, SPACSYS, R-SWMS, and RootBox, and discuss the future development of functional-structural root architectural modelling.ConclusionFunctional-structural root architectural models are being used to investigate numerous root–soil interactions, over a range of spatial scales. They are not only providing insights into the relationships between architecture, morphology and functional efficiency, but are also developing into tools that aid in the design of agricultural management schemes and in the selection of root traits for improving plant performance in specific environments.

The optimal lateral root branching density for maize depends on nitrogen and phosphorus availability

The optimal lateral root branching density in the maize root system depends on the relative availability of nitrate (a mobile soil resource) and phosphorus (an immobile soil resource), with the optimum shifting to more branches when the nitrate-to-phosphorus ratio is high. Observed phenotypic variation in the lateral root branching density (LRBD) in maize (Zea mays) is large (1–41 cm−1 major axis [i.e. brace, crown, seminal, and primary roots]), suggesting that LRBD has varying utility and tradeoffs in specific environments. Using the functional-structural plant model SimRoot, we simulated the three-dimensional development of maize root architectures with varying LRBD and quantified nitrate and phosphorus uptake, root competition, and whole-plant carbon balances in soils varying in the availability of these nutrients. Sparsely spaced (less than 7 branches cm−1), long laterals were optimal for nitrate acquisition, while densely spaced (more than 9 branches cm−1), short laterals were optimal for phosphorus acquisition. The nitrate results are mostly explained by the strong competition between lateral roots for nitrate, which causes increasing LRBD to decrease the uptake per unit root length, while the carbon budgets of the plant do not permit greater total root length (i.e. individual roots in the high-LRBD plants stay shorter). Competition and carbon limitations for growth play less of a role for phosphorus uptake, and consequently increasing LRBD results in greater root length and uptake. We conclude that the optimal LRBD depends on the relative availability of nitrate (a mobile soil resource) and phosphorus (an immobile soil resource) and is greater in environments with greater carbon fixation. The median LRBD reported in several field screens was 6 branches cm−1, suggesting that most genotypes have an LRBD that balances the acquisition of both nutrients. LRBD merits additional investigation as a potential breeding target for greater nutrient acquisition.

Complementarity in root architecture for nutrient uptake in ancient maize/bean and maize/bean/squash polycultures

BACKGROUND AND AIMS During their domestication, maize, bean and squash evolved in polycultures grown by small-scale farmers in the Americas. Polycultures often overyield on low-fertility soils, which are a primary production constraint in low-input agriculture. We hypothesized that root architectural differences among these crops causes niche complementarity and thereby greater nutrient acquisition than corresponding monocultures. METHODS A functional-structural plant model, SimRoot, was used to simulate the first 40 d of growth of these crops in monoculture and polyculture and to determine the effects of root competition on nutrient uptake and biomass production of each plant on low-nitrogen, -phosphorus and -potassium soils. KEY RESULTS Squash, the earliest domesticated crop, was most sensitive to low soil fertility, while bean, the most recently domesticated crop, was least sensitive to low soil fertility. Nitrate uptake and biomass production were up to 7 % greater in the polycultures than in the monocultures, but only when root architecture was taken into account. Enhanced nitrogen capture in polycultures was independent of nitrogen fixation by bean. Root competition had negligible effects on phosphorus or potassium uptake or biomass production. CONCLUSIONS We conclude that spatial niche differentiation caused by differences in root architecture allows polycultures to overyield when plants are competing for mobile soil resources. However, direct competition for immobile resources might be negligible in agricultural systems. Interspecies root spacing may also be too large to allow maize to benefit from root exudates of bean or squash. Above-ground competition for light, however, may have strong feedbacks on root foraging for immobile nutrients, which may increase cereal growth more than it will decrease the growth of the other crops. We note that the order of domestication of crops correlates with increasing nutrient efficiency, rather than production potential.

Phene Synergism between Root Hair Length and Basal Root Growth Angle for Phosphorus Acquisition

Long root hairs and shallow basal roots improve phosphorus uptake in common bean more in combination than in isolation. Shallow basal root growth angle (BRGA) increases phosphorus acquisition efficiency by enhancing topsoil foraging because in most soils, phosphorus is concentrated in the topsoil. Root hair length and density (RHL/D) increase phosphorus acquisition by expanding the soil volume subject to phosphorus depletion through diffusion. We hypothesized that shallow BRGA and large RHL/D are synergetic for phosphorus acquisition, meaning that their combined effect is greater than the sum of their individual effects. To evaluate this hypothesis, phosphorus acquisition in the field in Mozambique was compared among recombinant inbred lines of common bean (Phaseolus vulgaris) having four distinct root phenotypes: long root hairs and shallow basal roots, long root hairs and deep basal roots, short root hairs and shallow basal roots, and short root hairs and deep basal roots. The results revealed substantial synergism between BRGA and RHL/D. Compared with short-haired, deep-rooted phenotypes, long root hairs increased shoot biomass under phosphorus stress by 89%, while shallow roots increased shoot biomass by 58%. Genotypes with both long root hairs and shallow roots had 298% greater biomass accumulation than short-haired, deep-rooted phenotypes. Therefore, the utility of shallow basal roots and long root hairs for phosphorus acquisition in combination is twice as large as their additive effects. We conclude that the anatomical phene of long, dense root hairs and the architectural phene of shallower basal root growth are synergetic for phosphorus acquisition. Phene synergism may be common in plant biology and can have substantial importance for plant fitness, as shown here.

Dynamic root growth and architecture responses to limiting nutrient availability: linking physiological models and experimentation.

In recent years the study of root phenotypic plasticity in response to sub-optimal environmental factors and the genetic control of these responses have received renewed attention. As a path to increased productivity, in particular for low fertility soils, several applied research projects worldwide target the improvement of crop root traits both in plant breeding and biotechnology contexts. To assist these tasks and address the challenge of optimizing root growth and architecture for enhanced mineral resource use, the development of realistic simulation models is of great importance. We review this research field from a modeling perspective focusing particularly on nutrient acquisition strategies for crop production on low nitrogen and low phosphorous soils. Soil heterogeneity and the dynamics of nutrient availability in the soil pose a challenging environment in which plants have to forage efficiently for nutrients in order to maintain their internal nutrient homeostasis throughout their life cycle. Mathematical models assist in understanding plant growth strategies and associated root phenes that have potential to be tested and introduced in physiological breeding programs. At the same time, we stress that it is necessary to carefully consider model assumptions and development from a whole plant-resource allocation perspective and to introduce or refine modules simulating explicitly root growth and architecture dynamics through ontogeny with reference to key factors that constrain root growth. In this view it is important to understand negative feedbacks such as plant-plant competition. We conclude by briefly touching on available and developing technologies for quantitative root phenotyping from lab to field, from quantification of partial root profiles in the field to 3D reconstruction of whole root systems. Finally, we discuss how these approaches can and should be tightly linked to modeling to explore the root phenome.

Phenotypic variability and modelling of root structure of wild Lupinus angustifolius genotypes

Background and aimsRoot plasticity in response to the edaphic environment represents a challenge in the quantification of phenotypic variation in crop germplasm. The aim of this study was to use various growth systems to assess phenotypic variation among wild genotypes of Lupinus angustifolius.MethodsTen wild genotypes of L. angustifolius selected from an earlier phenotyping study were grown in three different growth systems: semi-hydroponics, potting-mix filled pots, and river-sand filled pots.ResultsMajor root-trait data collected in the present study in the semi-hydroponic growth system were strongly correlated with those from the earlier large phenotyping trial. Plants grown in the two solid media had some of the measured parameters significantly correlated. Principal component analysis captured the major variability in three (semi-hydroponics) or four (solid media) principal components. The genotypes were grouped into five clusters for each growth media, but cluster composition varied among the media. We found genetic variation and phenotypic plasticity in some root traits among tested genotypes. Using input parameters derived from the semihydroponic phenotyping system, simulation models (ROOTMAP and SimRoot) closely reproduced the root systems of a diverse range of lupin genotypes.ConclusionsWild L. angustifolius genotypes displayed genetic variation and phenotypic plasticity when exposed to various growth conditions. The consistent ranking of genotypes in the semihydroponic phenotyping system and the two solid media confirmed the capacity of the semihydroponic phenotyping system of providing simple and relevant growing conditions. The results demonstrated the utility of this system in gathering the data for parameterising the simulation models of root architecture.

Quantitative 3D Analysis of Plant Roots Growing in Soil Using Magnetic Resonance Imaging

Magnetic resonance imaging (MRI) enables nondestructive 3D imaging and quantification of roots or root system architecture in soil and is suited for automated and routine measurements of root development. Precise measurements of root system architecture traits are an important requirement for plant phenotyping. Most of the current methods for analyzing root growth require either artificial growing conditions (e.g. hydroponics), are severely restricted in the fraction of roots detectable (e.g. rhizotrons), or are destructive (e.g. soil coring). On the other hand, modalities such as magnetic resonance imaging (MRI) are noninvasive and allow high-quality three-dimensional imaging of roots in soil. Here, we present a plant root imaging and analysis pipeline using MRI together with an advanced image visualization and analysis software toolbox named NMRooting. Pots up to 117 mm in diameter and 800 mm in height can be measured with the 4.7 T MRI instrument used here. For 1.5 l pots (81 mm diameter, 300 mm high), a fully automated system was developed enabling measurement of up to 18 pots per day. The most important root traits that can be nondestructively monitored over time are root mass, length, diameter, tip number, and growth angles (in two-dimensional polar coordinates) and spatial distribution. Various validation measurements for these traits were performed, showing that roots down to a diameter range between 200 μm and 300 μm can be quantitatively measured. Root fresh weight correlates linearly with root mass determined by MRI. We demonstrate the capabilities of MRI and the dedicated imaging pipeline in experimental series performed on soil-grown maize (Zea mays) and barley (Hordeum vulgare) plants.

OpenSimRoot: widening the scope and application of root architectural models

Summary 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.