Physiological breeding

被引:192
作者
Reynolds, Matthew [1 ]
Langridge, Peter [2 ]
机构
[1] Int Maize & Wheat Improvement Ctr CIMMYT, Global Wheat Program, Mexico City, DF, Mexico
[2] Univ Adelaide, Sch Agr Food & Wine, Adelaide, SA, Australia
关键词
QUANTITATIVE TRAIT LOCI; GRAIN-YIELD; BREAD WHEAT; GENOMIC SELECTION; DROUGHT TOLERANCE; STRESS TOLERANCE; HEXAPLOID WHEAT; COMPLEX TRAITS; GENE DISCOVERY; CLIMATE-CHANGE;
D O I
10.1016/j.pbi.2016.04.005
中图分类号
Q94 [植物学];
学科分类号
071001 ;
摘要
Physiological breeding crosses parents with different complex but complementary traits to achieve cumulative gene action for yield, while selecting progeny using remote sensing, possibly in combination with genomic selection. Physiological approaches have already demonstrated significant genetic gains in Australia and several developing countries of the International Wheat Improvement Network. The techniques involved (see Graphical Abstract) also provide platforms for research and refinement of breeding methodologies. Recent examples of these include screening genetic resources for novel expression of Calvin cycle enzymes, identification of common genetic bases for heat and drought adaptation, and genetic dissection of trade-offs among yield components. Such information, combined with results from physiological crosses designed to test novel trait combinations, lead to more precise breeding strategies, and feed models of genotype-by-environment interaction to help build new plant types and experimental environments for future climates.
引用
收藏
页码:162 / 171
页数:10
相关论文
共 69 条
[11]   Pheno-Copter: A Low-Altitude, Autonomous Remote-Sensing Robotic Helicopter for High-Throughput Field-Based Phenotyping [J].
Chapman, Scott C. ;
Merz, Torsten ;
Chan, Amy ;
Jackway, Paul ;
Hrabar, Stefan ;
Dreccer, M. Fernanda ;
Holland, Edward ;
Zheng, Bangyou ;
Ling, T. Jun ;
Jimenez-Berni, Jose .
AGRONOMY-BASEL, 2014, 4 (02) :279-301
[12]   Plant adaptation to climate change-opportunities and priorities in breeding [J].
Chapman, Scott C. ;
Chakraborty, Sukumar ;
Dreccer, M. Fernanda ;
Howden, S. Mark .
CROP & PASTURE SCIENCE, 2012, 63 (03) :251-268
[13]   Large-scale characterization of drought pattern: a continent-wide modelling approach applied to the Australian wheatbelt spatial and temporal trends [J].
Chenu, Karine ;
Deihimfard, Reza ;
Chapman, Scott C. .
NEW PHYTOLOGIST, 2013, 198 (03) :801-820
[14]   Predicting the future of plant breeding: complementing empirical evaluation with genetic prediction [J].
Cooper, Mark ;
Messina, Carlos D. ;
Podlich, Dean ;
Totir, L. Radu ;
Baumgarten, Andrew ;
Hausmann, Neil J. ;
Wright, Deanne ;
Graham, Geoffrey .
CROP & PASTURE SCIENCE, 2014, 65 (04) :311-336
[15]   Genomic Prediction in Animals and Plants: Simulation of Data, Validation, Reporting, and Benchmarking [J].
Daetwyler, Hans D. ;
Calus, Mario P. L. ;
Pong-Wong, Ricardo ;
de los Campos, Gustavo ;
Hickey, John M. .
GENETICS, 2013, 193 (02) :347-+
[16]   Natural variation in photosynthetic capacity, growth, and yield in 64 field-grown wheat genotypes [J].
Driever, S. M. ;
Lawson, T. ;
Andralojc, P. J. ;
Raines, C. A. ;
Parry, M. A. J. .
JOURNAL OF EXPERIMENTAL BOTANY, 2014, 65 (17) :4959-4973
[17]   Ppd1, Vrn1, ALMT1 and Rht genes and their effects on grain yield in lower rainfall environments in southern Australia [J].
Eagles, H. A. ;
Cane, Karen ;
Trevaskis, Ben ;
Vallance, Neil ;
Eastwood, R. F. ;
Gororo, N. N. ;
Kuchel, Haydn ;
Martin, P. J. .
CROP & PASTURE SCIENCE, 2014, 65 (02) :159-170
[18]   Physiological phenotyping of plants for crop improvement [J].
Edmond Ghanem, Michel ;
Marrou, Helene ;
Sinclair, Thomas R. .
TRENDS IN PLANT SCIENCE, 2015, 20 (03) :139-144
[19]   Lights, camera, action: high-throughput plant phenotyping is ready for a close-up [J].
Fahlgren, Noah ;
Gehan, Malia A. ;
Baxter, Ivan .
CURRENT OPINION IN PLANT BIOLOGY, 2015, 24 :93-99
[20]   Cereal breeding takes a walk on the wild side [J].
Feuillet, Catherine ;
Langridge, Peter ;
Waugh, Robbie .
TRENDS IN GENETICS, 2008, 24 (01) :24-32