A Mathematical Model of Phloem Sucrose Transport as a New Tool for Designing Rice Panicle Structure for High Grain Yield

Abstract

Rice (Oryza sativa) is one of the most important food crops in the world. Numerous quantitative trait loci or genes controlling panicle architecture have been identified to increase grain yield. Yet grain yield, defined as the product of the number of well-ripened grains and their weight, is a complex trait that is determined by multiple factors such as source, sink and translocation capacity. Mechanistic modelling capturing capacities of source, sink and transport will help in the theoretical design of crop ideotypes that guarantee high grain yield. Here we present a mathematical model simulating sucrose transport and grain growth within a complex phloem network. The model predicts that the optimal panicle structure for high yield shows a simple grain arrangement with few higher order branches. In addition, numerical analyses revealed that inefficient delivery of carbon to panicles with higher order branches prevails regardless of source capacity, indicating the importance of designing grain arrangement and phloem structure. Our model highlights the previously unexplored effect of grain arrangement on the yield, and provides numerical solutions for optimal panicle structure under various source and sink capacities.

A Model of Silicon Dynamics in Rice: An Analysis of the Investment Efficiency of Si Transporters

“…To simulate the dynamics of mineral nutrients in rice, we have to simulate not only water flows in the xylem and phloem but also the transport and distribution of mineral nutrients via transporters. Models have been developed that simulate water flows in the xylem and phloem (Daudet et al, 2002; Lacointe and Minchin, 2008; Lobet et al, 2014; Seki et al, 2015) and transport of mineral nutrients from roots or mineral distribution at nodes (Sakurai et al, 2015; Yamaji et al, 2015). However, no study has been conducted on modeling the dynamics of mineral nutrients by considering both water flow and transporter expression level.…”

“…Water flows according to the difference in water potentials. Because the flow of water in the phloem is strongly related to sucrose concentration, some models treat water and sucrose dynamics simultaneously (Daudet et al, 2002; Lacointe and Minchin, 2008; Lobet et al, 2014; Seki et al, 2015). For the transportation of substances in plant, several different concepts are used to model transport of mineral elements and organic pollutants from roots.…”

Multi-scale modelling to synergise Plant Systems Biology and Crop Science

“…Although the area seems under-explored in Arabidopsis relative to crop species, these studies have already revealed interesting correlations between branching and seed yield, which also depend on the plant varieties, and identified some related QTL regions. Indeed, a recent mechanistic model of sucrose transport in rice also highlighted the effect of grain arrangement on yield (Seki et al, 2015), suggesting that the genetic tools to manipulate carbon partitioning in Arabidopsis will allow future models to contribute further quantitative understanding of this area.…”

Inferring vascular architecture of the wheat spikelet based on resource allocation in the branched headt (bht-A1) near isogenic lines

“…Based on a literature review, two contrasting modelsthe 'pipe' (Shinozaki et al 1964) and'aorta' models (McCulloh et al 2003) were suggested as working models for the architectural configuration of the vascular network system in plants. The main differences between the aorta and the pipe model is that the aorta transport networks are composed of several branching tube networks; while the pipe model is composed of multiple parallel or diverging vessels or tubes (McCulloh et al 2003;McCulloh and Sperry 2006;Seki et al 2015). Hence, unlike the pipe model, bifurcation of the mother tube into daughter tubes is a typical characteristic of the aorta model (Murray 1926;McCulloh et al 2003;Seki et al 2015).…”

“…The main differences between the aorta and the pipe model is that the aorta transport networks are composed of several branching tube networks; while the pipe model is composed of multiple parallel or diverging vessels or tubes (McCulloh et al 2003;McCulloh and Sperry 2006;Seki et al 2015). Hence, unlike the pipe model, bifurcation of the mother tube into daughter tubes is a typical characteristic of the aorta model (Murray 1926;McCulloh et al 2003;Seki et al 2015). Thus, the aorta model states that across branching generations, the sum of the conduit radii (r) cubed at every level (Sr 3 ) is proportional to the volume flow rate at any point (Murray 1926;McCulloh et al 2004;McCulloh and Sperry 2005).…”