A simple approach to predict growth stages in winter wheat (Triticum aestivum L.) combining prediction of a crop model and marker based prediction of the deviation to a reference cultivar: A case study in France

摘要: Abstract Predicting wheat growth stages using ecophysiological models is of particular interest as it allows anticipating important agricultural managements. Numerous exist but they need cultivar-specific parameterization, which often costly and time consuming. The work presented here proposes a simple approach to predict the allelic composition cultivars. It relies on prediction modified version ARCWHEAT model for well parameterized reference cultivar (Soissons) marker-based predicted deviation in days cultivar. First, deviations Soissons beginning stem elongation (δZ30) heading date (δZ55) were calculated large panel Analysis variance showed prominent genetic effects δZ30 δZ55 possible genotype × environment interactions (G × E) δZ30. Genotypic means used association genetics revealing 90 83 markers associated these traits, respectively. Multiple linear regression predicting 11 (R2 = 76%) or 17 (R2 = 85%) obtained by stepwise procedure. Marker PPD-D1 had largest impact both models. Finally, added allowed Z30 Z55 independent validation dataset. root mean square error proposed this paper (6.8 4.7 days, respectively) was comparable one conventional with parameters values (6.5 4.1, respectively). appeared sufficient order cultivars cannot be such new coming out market. Moreover, involved multiple may provide interesting candidates unravel genes determining earliness winter wheat.