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Grain yield potential strategies in an elite wheat double-haploid population grown in contrasting environments

Published on Jan 1, 2013in Crop Science1.64
· DOI :10.2135/cropsci2012.11.0669
Guillermo Ariel García6
Estimated H-index: 6
(UBA: University of Buenos Aires),
Ahmed Khairul Hasan4
Estimated H-index: 4
(Austral University of Chile)
+ 3 AuthorsDaniel J. Miralles33
Estimated H-index: 33
(UBA: University of Buenos Aires)
Abstract
The understanding of ecophysiological basis of wheat (Triticum aestivum L.) grain yield poten tial provides a useful framework to comple ment conventional breeding aimed at achieving genetic gains. This study analyzed the ecophysiological performance of an elite wheat mapping population (105 double-haploid lines derived from two modern cultivars, Bacanora and Wee bil, with similar phenology but different and stable combinations of grain number per area unit (GN) and grain weight (GW) resulting in high grain yield) grown in four contrasting high-yield ing environments, to determine the most suc cessful strategies to increase grain yield poten tial. Main effect of environment on grain yield was significant ( p  0.82, p 0.51, p < 0.0001), a wide range in both components (i.e., GN and GW) was observed across all environments. This population rep resents a valuable resource for prebreeding studies, as the transgressive segregation in physiological and numerical yield components in combination with favorable expression of all agronomic traits could allow a fine phenotyping and mapping to identify key traits and quantita tive trait loci linked with grain yield.
  • References (48)
  • Citations (21)
References48
Newest
#1Matthew P. Reynolds (CIMMYT: International Maize and Wheat Improvement Center)H-Index: 60
#2John Foulkes (University of Nottingham)H-Index: 13
Last.Gustavo A. Slafer (Catalan Institution for Research and Advanced Studies)H-Index: 59
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#1Marta S. Lopes (CIMMYT: International Maize and Wheat Improvement Center)H-Index: 20
#2Matthew P. Reynolds (CIMMYT: International Maize and Wheat Improvement Center)H-Index: 60
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#1Gisela Borràs-Gelonch (University of Lleida)H-Index: 4
#2Greg J. Rebetzke (CSIRO: Commonwealth Scientific and Industrial Research Organisation)H-Index: 42
Last.Ignacio Romagosa (University of Lleida)H-Index: 37
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#1Guillermo Ariel García (UBA: University of Buenos Aires)H-Index: 6
#2Román A. Serrago (UBA: University of Buenos Aires)H-Index: 11
Last.Daniel J. Miralles (UBA: University of Buenos Aires)H-Index: 33
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#1Martin A. J. Parry (Rothamsted Research)H-Index: 46
#2Matthew P. Reynolds (CIMMYT: International Maize and Wheat Improvement Center)H-Index: 60
Last.Robert T. Furbank (CSIRO: Commonwealth Scientific and Industrial Research Organisation)H-Index: 59
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#1M. John Foulkes (University of Nottingham)H-Index: 16
#2Gustavo A. Slafer (University of Lleida)H-Index: 59
Last.Matthew P. Reynolds (CIMMYT: International Maize and Wheat Improvement Center)H-Index: 60
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#1Matthew P. Reynolds (CIMMYT: International Maize and Wheat Improvement Center)H-Index: 60
#2Y. Manes (CIMMYT: International Maize and Wheat Improvement Center)H-Index: 1
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#1Victor O. Sadras (South Australian Research and Development Institute)H-Index: 52
#2R. Ford Denison (UMN: University of Minnesota)H-Index: 32
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#2Wen Yin (GAU: Gansu Agricultural University)H-Index: 7
Last.Jeffrey A. Coulter (UMN: University of Minnesota)H-Index: 15
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#1L. Gabriela Abeledo (UBA: University of Buenos Aires)H-Index: 8
#2Santiago Alvarez Prado (UBA: University of Buenos Aires)H-Index: 5
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#2Idan Ayalon (HUJI: Hebrew University of Jerusalem)H-Index: 2
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