Cost-Benefit Analysis of the Upland-Rice Root Architecture in Relation to Phosphate: 3D Simulations Highlight the Importance of S-Type Lateral Roots for Reducing the Pay-Off Time

Abstract

The rice root system develops a large number of nodal roots from which two types of lateral roots branch out, large L-types and fine S-types, the latter being unique to the species. All roots including S-types are covered by root hairs. To what extent these fine structures contribute to phosphate (P) uptake under P deficiency was investigated using a novel 3-D root growth model that treats root hairs as individual structures with their own Michaelis-Menten uptake kinetics. Model simulations indicated that nodal roots contribute most to P uptake followed by L-type lateral roots and S-type laterals and root hairs. This is due to the much larger root surface area of thicker nodal roots. This thickness, however, also meant that the investment in terms of P needed for producing nodal roots was very large. Simulations relating P costs and time needed to recover that cost through P uptake suggest that producing nodal roots represents a considerable burden to a P-starved plant, with more than 20 times longer pay-off time compared to S-type laterals and root hairs. We estimated that the P cost of these fine root structures is low enough to be recovered within a day of their formation. These results expose a dilemma in terms of optimizing root system architecture to overcome P deficiency: P uptake could be maximized by developing more nodal root tissue, but when P is growth-limiting, adding more nodal root tissue represents an inefficient use of the limiting factor P. In order to improve adaption to P deficiency in rice breeding two complementary strategies seem to exist: (1) decreasing the cost or pay-off time of nodal roots and (2) increase the biomass allocation to S-type roots and root hairs. To what extent genotypic variation exists within the rice gene pool for either strategy should be investigated.

Keywords: L-type lateral roots; OpenSimRoot; Oryza sativa (L.); modeling; phosphate uptake; root branching; root hairs.

FIGURE 1

(A) Scan of a root system excavated 14 DAE from the greenhouse experiment showing the highly branched primary root as well as two nodal root classes and L-type and S-type lateral roots. Fast nodal roots start to develop between 7 and 14 DAE and therefore remain very small. (B) magnified region with a high density of S-type lateral roots. (C) Simulated root at 21 DAE where roots with their surrounding P depletion zones are shown for better visibility of lateral roots. Color coding identifies root classes: blue, primary root; dark red, branched nodal root; green, fast nodal root; yellow, L-type laterals; red, S-type laterals; light green, nodal roots from tillers. (D) Top-down view of a simulated root system at 28 DAE.qq.

FIGURE 2

(A) Distribution of root growth angles (RGA, in degree from the soil surface) of nodal roots excavated 28 DAE from the field experiment and (B) partially excavated root system used to determine RGAs. The fast nodal roots are indicated in comparison to their branched counterparts. (C) A branched nodal root growing at a shallow angle developing a large number of L-type and S-type laterals. (D) Micrograph of an L-type lateral root section with S-type lateral roots and root hairs.

FIGURE 3

Development of (A) nodal root number and (B) total root length over time comparing measured values from greenhouse and field experiments with simulated data from the model. Error bars represent standard deviations (n = 4).

FIGURE 4

Comparison of root class distributions between (A) measured and model data and (B) modeled contribution (%) by root classes including root hairs developing on respective classes for total root length, (C) surface area, and (D) volume.

FIGURE 5

Plant P content over time comparing measured values from greenhouse and field experiments with simulated data from the model. Error bars represent standard deviations (n = 4).