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Type: Journal article
Title: Quantification of the effects of VRN1 and Ppd-D1 to predict spring wheat (Triticum aestivum) heading time across diverse environments
Author: Zheng, B.
Biddulph, B.
Li, D.
Kuchel, H.
Chapman, S.
Citation: Journal of Experimental Botany, 2013; 64(12):3747-3761
Publisher: Oxford University Press (OUP)
Issue Date: 2013
ISSN: 0022-0957
Statement of
Bangyou Zheng, Ben Biddulph, Dora Li, Haydn Kuchel, and Scott Chapman
Abstract: Heading time is a major determinant of the adaptation of wheat to different environments, and is critical in minimizing risks of frost, heat, and drought on reproductive development. Given that major developmental genes are known in wheat, a process-based model, APSIM, was modified to incorporate gene effects into estimation of heading time, while minimizing degradation in the predictive capability of the model. Model parameters describing environment responses were replaced with functions of the number of winter and photoperiod (PPD)-sensitive alleles at the three VRN1 loci and the Ppd-D1 locus, respectively. Two years of vernalization and PPD trials of 210 lines (spring wheats) at a single location were used to estimate the effects of the VRN1 and Ppd-D1 alleles, with validation against 190 trials (~4400 observations) across the Australian wheatbelt. Compared with spring genotypes, winter genotypes for Vrn-A1 (i.e. with two winter alleles) had a delay of 76.8 degree days (°Cd) in time to heading, which was double the effect of the Vrn-B1 or Vrn-D1 winter genotypes. Of the three VRN1 loci, winter alleles at Vrn-B1 had the strongest interaction with PPD, delaying heading time by 99.0 °Cd under long days. The gene-based model had root mean square error of 3.2 and 4.3 d for calibration and validation datasets, respectively. Virtual genotypes were created to examine heading time in comparison with frost and heat events and showed that new longer-season varieties could be heading later (with potential increased yield) when sown early in season. This gene-based model allows breeders to consider how to target gene combinations to current and future production environments using parameters determined from a small set of phenotyping treatments.
Keywords: Crop model
Triticum spp.
Rights: © The Author [2013].
DOI: 10.1093/jxb/ert209
Appears in Collections:Agriculture, Food and Wine publications
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