Dissecting durum wheat time to anthesis into physiological traits using a QTL-based model
2024
Martre, Pierre | Motzo, Rosella | Mastrangelo, Anna Maria | Marone, Daniela | De Vita, Pasquale | Giunta, Francesco | Écophysiologie des Plantes sous Stress environnementaux (LEPSE) ; Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier ; Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro) | Università degli Studi di Sassari = University of Sassari [Sassari] (UNISS) | Consiglio per la Ricerca in Agricoltura e l’analisi dell’economia agraria = Council for Agricultural Research and Economics (CREA) | Regional Government of Sardinia
International audience
Mostrar más [+] Menos [-]Inglés. Fine tuning crop development is a major breeding avenue to increase crop yield and for adaptation to climate change. We used an ecophysiological model that integrates our current understanding of the physiology of wheat phenology to predict the development and anthesis date of 91 recombinant inbreed lines (RILs) of durum wheat with genotypic parameters controlling vernalization requirement, photoperiod sensitivity, and earliness per se estimated using leaf stage, final leaf number, anthesis date data from a pot experiment with vernalized and nonvernalized treatments combined with short- and long-day length. Predictions of final leaf number and anthesis date of the QTL-based model was evaluated for the whole population of RILs in a set of independent field trials and for the two parents, which were not used to estimate the parameter values. Our novel approach reduces the number of environments and the time required to obtain the required data sets to develop a QTL-based prediction of model parameters. Moreover, the use of a physiologically based model of phenology gives new insight into genotype-phenology relations for wheat. We discuss the approach we used to estimate the parameters of the model and their association with QTL and major phenology genes that collocate at QTL.
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