Variation in seasonal flowering-behaviour plays a key role in adapting wheat to different climates and geographical regions. This was important during the early development of the Australian grains industry. The first wheats to be introduced to Australia required prolonged winter cold to flower (vernalization) and consequently crops struggled to produce grain in the warm climates encountered. The introduction of genes (alleles of VERNALIZATION1) that allow flowering and grain production without prolonged winter cold was a critical step towards producing wheats adapted to the Australian climate and these genes allowed a massive expansion in the area where wheat can be cultivated. We are using variation in the flowering behaviour of Australian wheats as a model system to explore new ways to resolve gene-environment interactions and to understand how such interactions drive adaptation of plants to different climates. This presentation will examine current understanding of the molecular pathways controlling seasonal flowering of wheat and then introduce new research strategies that use machine-learning to resolve gene-environment interactions. A key message will be that transcending the concept of traits and shifting towards understanding natural variation at the level of molecular pathways will allow improved understanding and prediction of crop performance in different environments.