Home

ABOUT

GxExM Symposium IV will bring together researchers, industry representatives, breeders, agronomists, modellers and agricultural innovators to explore the critical role of GxExM interactions in crop improvement.

Across two days of presentations, discussions and collaborative exchange, participants will examine new approaches and emerging insights that can advance experimental design, modelling and predictive methods to support future crop improvement strategies.

The symposium aims to foster interdisciplinary discussion and strengthen integrated approaches that connect genetics, agronomy, environmental understanding and on-farm outcomes.

5 & 6 November 2026

Brisbane, Australia

Registration is free; the event can be attended online via Zoom or in person. Presentations will be recorded and shared on YouTube, where speaker permission is provided.

KEYNOTE SPEAKERS

Daniel Tolhurst

University of Edinburgh

Huihui Li

Chinese Academy of Agricultural Sciences (CAAS)

Randall Wisser

French National Research Institute for Agriculture, Food and Environment (INRAE)

Greg Rebetzke

CSIRO

SESSION THEMES

Thursday 5 November, morning

Incorporating prior biological knowledge in predictive breeding technologies

Chair: Owen Powell

This session will explore how integrating biological understanding - such as molecular and regulatory biology, physiological processes, and evolutionary constraints - can enhance the accuracy, interpretability, and generalisability of predictive breeding technologies (e.g. genomic prediction

and breeding program simulations). Presentations will highlight emerging frameworks, case studies, and methodological advances that leverage biological

knowledge to improve breeding decisions and accelerate realised genetic gain.

Thursday 5 November, afternoon

Outlook in GxExM Research

Chair: Charlie Messina

Advances in omics technologies and predictive modelling have established G×E×M frameworks as powerful tools for understanding and predicting crop adaptation. Their successful application in commercial breeding programs points to new research frontiers with the potential to further accelerate genetic gain and enhance the resilience of food systems. Can G×E×M principles be extended beyond crops to livestock, integrated crop–livestock systems, and other managed biological systems? How will next-generation phenomic platforms, autonomous sensing networks, digital twins, and agentic AI transform our ability to characterise, predict, and design adaptation? As predictive algorithms evolve from statistical models into autonomous systems capable of hypothesis generation and decision support, G×E×M research is poised to advance from prediction to the design of resilient biological systems. In this Outlook, we bring together diverse perspectives to explore emerging opportunities, identify key challenges, and propose a research agenda for the next generation of G×E×M science.

Friday 6 November, morning

AI opportunities in relation to the modelling of GxExM data

Chair: Fred van Eeuwijk

Analysis of GxExM data has a long history in statistics and plant breeding. Since the 1990s, physiological perspectives have played an increasing role as well. Recently, deep learning approaches have started to occur as a complementary or alternative technique for modelling GxExM. Initially these attempts were driven mainly by deep learning models for extracting features from high throughput phenotyping and genomic data separately. Increasingly, deep learning architectures are offered for genotype-to-phenotype modelling. This session will present illustrations of deep learning for GxExM data with, among others, examples concerning genetic and environmental embeddings, the modelling of longitudinal phenotyping and environmental data, biology-informed neural networks, and integrations of deep learning and linear mixed models.

Friday 6 November, afternoon

Advancing from predicting GxExM interactions to design of breeding Gx(ExM), agronomy Mx(GxE) and integrated (GxM)xE applications

Chair: Mark Cooper

As the methods described in the previous three sessions have advanced to enable prediction of GxExM interactions, new

opportunities are emerging to act on the predictions by leveraging high-throughput phenotyping and enviromics capabilities enabled through combinations of proximal and remote sensing technologies. This session will focus on examples, case studies and proposals that illustrate applications of GxExM prediction capabilities to improve crop productivity and reliability of crop performance.

ABSTRACT SUBMISSIONS

Abstract submissions for oral and poster presentations are open now until 4 September 2026 at 11:59pm (AEST). Abstracts are welcome from both in person and virtual attendees. Upon registration, you will receive a link inviting you to submit an abstract. Presentation types include:

15-minute Symposium talk + 5 minutes of question time
5-minute Symposium talk - this option is targeted toward students
Poster Presentation - you will have an opportunity to speak about your poster for 1 minute during the Symposium and then display your poster at the poster session