On the dynamic determinants of reproductive failure under drought in maize

Abstract Reproductive failure under drought in maize (Zea mays) is a major cause of instability in global food systems. While there has been extensive research on maize reproductive physiology, it has not been formalized in mathematical form to enable the study and prediction of emergent phenotypes,...

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Published inin silico plants Vol. 1; no. 1
Main Authors Messina, Carlos D, Hammer, Graeme L, McLean, Greg, Cooper, Mark, van Oosterom, Erik J, Tardieu, Francois, Chapman, Scott C, Doherty, Alastair, Gho, Carla
Format Journal Article
LanguageEnglish
Published US Oxford University Press 01.01.2019
Oxford Academic
Subjects
Computer Science
Life Sciences
Modeling and Simulation
Vegetal Biology
grain cohorts
fertilization
ear phenotypes
kernel abortion
water deficit
assimilate partitioning
Anthesis-silking interval (ASI)
crop growth model (CGM)
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Summary:Abstract Reproductive failure under drought in maize (Zea mays) is a major cause of instability in global food systems. While there has been extensive research on maize reproductive physiology, it has not been formalized in mathematical form to enable the study and prediction of emergent phenotypes, physiological epistasis and pleiotropy. We developed a quantitative synthesis organized as a dynamical model for cohorting of reproductive structures along the ear while accounting for carbon and water supply and demand balances. The model can simulate the dynamics of silk initiation, elongation, fertilization and kernel growth, and can generate well-known emergent phenotypes such as the relationship between plant growth, anthesis-silking interval, kernel number and yield, as well as ear phenotypes under drought (e.g. tip kernel abortion). Simulation of field experiments with controlled drought conditions showed that predictions tracked well the observed response of yield and yield components to timing of water deficit. This framework represents a significant improvement from previous approaches to simulate reproductive physiology in maize. We envisage opportunities for this predictive capacity to advance our understanding of maize reproductive biology by informing experimentation, supporting breeding and increasing productivity in maize.
ISSN:2517-5025
2517-5025
DOI:10.1093/insilicoplants/diz003