Field Crops Research ( IF 4.308 ) Pub Date : 2020-01-25 , DOI: 10.1016/j.fcr.2020.107722 Brendan Christy; Penny Riffkin; Richard Richards; Debra Partington; Tina Botwright Acuña; Angela Merry; Heping Zhang; Ben Trevaskis; Garry O’Leary
We developed a photoperiod-corrected thermal model that can predict wheat phenology based solely on the combination of photoperiod (Ppd) and vernalisation (Vrn) alleles to identify the phenological suitability of germplasm across the cropping region in southern Australia.
More than 200 wheat genotypes that vary in combinations of Ppd and Vrn alleles were grown at 17 locations spanning 11° Latitude, thus providing a wide range in temperature and daylength gradients. The phenological sensitivities of a genotype to varying basic temperature, photoperiod and vernalisation requirement was adjusted via optimisation to minimise the least square difference between the measured and predicted dates of both terminal spike (TS) and flowering (AN).
The model predicted dates of TS and AN to within 5 days of the field values. Information was used to identify the alleles required to achieve a wheat ideotype defined in a previous study. The optimum allelic combinations required to target the optimum flowering period for different locations when sown on different dates were also identified. The use of allelic based phenological models has the potential to reduce the costs to breeding programs and accelerate the release of better adapted germplasm to new and changing environments.