Simulation‐Based Analysis of Effects of Vrn and Ppd Loci on Flowering in Wheat

Wiley - Tập 48 Số 2 - Trang 678-687 - 2008
Jeffrey W. White1, Markus Herndl2, R. C. Izaurralde3, Thomas Payne4, Gerrit Hoogenboom5,6
1USDA‐ARS, Arid Land Agricultural Research Center 21881 N. Cardon Ln. Maricopa AZ 85239
2Institute of Crop Production and Grassland Research (340) Univ. of Hohenheim Fruwirthstr. 23 D‐70599 Stuttgart Germany
3Dep. of Plant Agriculture, Crop Science Bldg., Univ. of Guelph, Guelph, ON, Canada N1G 2W1
4International Maize and Wheat Improvement Centre (CIMMYT) Ap. Postal 6‐641 06600 Mexico DF Mexico
5Dep. of Biological and Agricultural Engineering, College of Agricultural and Environmental Sciences Univ. of Georgia Griffin GA 30223‐1797
6Mention of a specific product name by the U.S. Department of Agriculture does not constitute an endorsement and does not imply a recommendation over other suitable products

Tóm tắt

Cereal production is strongly influenced by flowering date. Wheat (Triticum aestivum L.) models simulate days to flower by assuming that development is modified by vernalization and photoperiodism. Cultivar differences are parameterized by vernalization requirement, photoperiod sensitivity, and earliness per se. The parameters are usually estimated by comparing simulations with field observations but appear estimable from genetic information. For wheat, the Vrn and Ppd loci, which affect vernalization and photoperiodism, were logical candidates for estimating parameters in the model CSM‐Cropsim‐CERES. Two parameters were estimated conventionally and then re‐estimated with linear effects of Vrn and Ppd Flowering data were obtained for 29 cultivars from international nurseries and divided into calibration (14 locations) and evaluation (34 locations) sets. Simulations with a generic cultivar explained 95% of variation in flowering for calibration data (10 d RMSE) and 89% for evaluation data (10 d RMSE), indicating the large effect of environment. Nonetheless, for the calibration data, the gene‐based model explained 29% of remaining variation, and the conventional model, 54%. For the evaluation data, the gene‐based model explained 17% of remaining variation, and the conventional model, 27%. Gene‐based prediction of wheat phenology appears feasible, but more extensive genetic characterization of cultivars is needed.

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Wiley

Tập 48 Số 2

678-687

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