Abstract
While numerous wheat phenology prediction models are available, most of them are constrained to using variety-dependent coefficients. The overarching objective of this study was to calibrate a gene-based model to predict wheat heading date that allows breeders to select specific gene combinations that would head within the optimal window for a given environment independently of varietal genetic background. A dataset with a total of 49 Argentine wheat cultivars and two recombinant inbred lines was chosen to cover a wide range of allelic combinations for major vernalization, photoperiod, and earliness per-se genes. The model was validated using independent data from an Argentine wheat trial network that includes sites from a wide latitudinal range. Ultimately, using this gene-based model, simulations were made to identify optimal gene combinations (ideotypes) × site combinations in contrasting locations. The selected model accurately predicted heading date with an overall median error of 4.6 days. This gene-based crop model for wheat phenology allowed the identification of groups of gene combinations predicted to head within a low-risk window and can be adapted to predict other phenological stages based on accessible climatic information and publicly available molecular markers, facilitating its adoption in wheat-growing regions worldwide.
Published Version
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