Modelling the dynamics and phenotypic consequences of tiller outgrowth and cessation in sorghum
Graeme L. Hammer, Greg McLean, Jana Kholová and Erik van Oosterom1
in silico Plants, Volume 5, Issue 2, 2023, diad019,
Published 03 November 2023
https://doi.org/10.1093/insilicoplants/diad019
Abstract. Tillering affects canopy leaf area, and hence crop growth via capture of light, water and nutrients. Depending on the season, variation in tillering can result in increased or decreased yield. Reduced tillering has been associated with water-saving and enhanced yield in water-limited conditions. The objective of this study was to develop a generic model of the dynamics of tillering in sorghum incorporating key genetic and environmental controls. The dynamic of tillering was defined in four key phases—pre-tillering, tiller emergence, cessation of tiller emergence and cessation of tiller growth. Tillering commenced at full expansion of leaf four and thereafter was synchronized with leaf appearance. The potential total number of tillers (TTN) was dependent on a genetic propensity to tiller and an index of assimilate
availability dependent on the shoot source–sink balance. Cessation of tiller emergence could occur before TTN depending on extent of competition from neighbours. Subsequent cessation of growth of emerged tillers was related to the extent of internal competition for assimilate among plant organs, resulting in prediction of final fertile tiller number (FTN). The model predicted tillering dynamics well in an experiment with a range in plant density. Plausibility simulations of FTN conducted for diverse field conditions in the Australian sorghum belt reflected expectations. The model is able to predict FTN as an emergent property. Its utility to explore GxMxE crop adaptation landscapes, guide molecular discovery, provide a generic template for other cereals and link to advanced methods for enhancing genetic gain in crops were discussed.
Figure 1. Sorghum growing areas in NE Australia showing location of key sites used for model plausibility testing (after Hammer et al. 2014)