Modeling Silking Dynamics and Tip Kernel Abortion for Maize Breeding.

Using principles of quantitative genetics Corn breeders have contributed to the sustained increase crop production and stability in the last century. Population and economic growth challenges the capacity of agriculture to achieve and sustain food security with current rates of genetic improvement. The effectiveness of breeding strategies to support increased rates of genetic gains for yield could be increased if some of the complexities in gene-to-phenotype (G→P) relations could be captured in realistic and applicable G→P models. Crop models designed to simulate yields as the emergence consequence of the dynamic interplay of crop growth and development processes over the crop life cycle lay at the core of G→P models. Developing such models to support genetic improvement of maize requires developing a trait model that both captures essential determinants of kernel set and connects with high throughput phenotyping strategies. Despite major progress in our understanding of the physiological processes underpinning kernel set in maize a quantitative dynamic synthesis that could be used to inform breeding decisions is lacking. In this presentation we describe a physiological framework to simulate kernel set and tip kernel abortion in maize largely based on silking dynamics and their response to environmental stresses, resource allocation to the ear, ear and kernel growth, and competition among cohort of kernels. The framework is demonstrated at an early stage of maize product development.