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

旱稻根系结构与磷肥利用的成本效益分析:三维模拟凸显S型侧根对缩短投资回报期的重要性

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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.

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