Traits underlying yield differ in their contribution to adaptation across environmental conditions and have different levels of G×E. We provide a framework to study the performance of genotype-to-phenotype (G2P) modelling approaches.

We generated and analysed response surfaces, for yield and yield-related traits, emphasizing trait dynamics and interactions over time. We used the crop growth model APSIM-wheat with genotype-dependent parameters to simulate non-linear trait responses over time with complex trait dependencies, and applied it to Australian environments. Such simulated data offers opportunities to study the relationships between traits over time and across environments and to evaluate genotype-to-phenotype models for multiple traits and environments.

Daniela Bustos-Korts

Wageningen University

Daniela works as a researcher at Wageningen University (NL). She has an MSc in Crop Physiology (Universidad Austral de Chile). In 2017, she obtained her PhD from Wageningen University. Her thesis was about the use of statistical and crop growth models for phenotype prediction across multiple environments.

Daniela's research interests are in the development of strategies that combine statistical and crop growth models to help breeders designing effective phenotyping and prediction schemes that will help them improving response to selection. These strategies involve the use of crop growth models and linear mixed models for multi-trait and multi-environment genomic prediction.


About QAAFI Science Seminars

Queensland Alliance for Agriculture and Food Innovation (QAAFI) has been hosting a high-profile seminar series across the disciplines of agriculture, food and nutrition science since 2014. With a range of speakers from Australia and abroad, the series explores how high-impact science will significantly improve the competitiveness and sustainability of the tropical and sub-tropical food, fibre and agribusiness sectors.

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Level 3, Queensland Bioscience Precinct building 80, UQ St Lucia campus
3.142 Large seminar room