| 000 | 02808naa a22003977a 4500 | ||
|---|---|---|---|
| 001 | G90291 | ||
| 003 | MX-TxCIM | ||
| 005 | 20240919020941.0 | ||
| 008 | 240513s2007 ne ||||| |||| 00| 0 eng d | ||
| 020 | _a978-1-4020-5904-9 | ||
| 020 | _a978-1-4020-5906-3 (Online) | ||
| 024 | 8 | _ahttps://doi.org/10.1007/1-4020-5906-X_3 | |
| 040 | _aMX-TxCIM | ||
| 041 | _aeng | ||
| 090 | _aCIS-5196 | ||
| 100 | 1 |
_aMalosetti, M. _912182 |
|
| 245 | 1 | 0 | _aChapter 3. Multi-trait multi-environment QTL modelling for drought-stress adaptation in maize |
| 260 |
_aDordrecht (Netherlands) : _bSpringer, _c2007. |
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| 340 | _aComputer File|Printed | ||
| 490 |
_aWageningen UR Frontis Series ; _vNo. 21 |
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| 520 | _aWater shortage is a major cause of yield loss in maize. Thus, breeding for adaptation to waterstressed environments is an important task for breeders. The use of quantitative-trait loci (QTL) models in which the response of complex phenotypes under stressed environments is described in direct relation to molecular information can improve the understanding of the genetic causes underlying stress tolerance. Mixed QTL models are particularly useful for this type of modelling, especially when the data stem from multi-environment evaluations including stressed and non-stressed conditions. The study of complex phenotypic traits such as yield under water-limited conditions can benefit from the analysis of trait components (e.g., yield components) that can be exploited in indirect selection. Multi-trait multi-environment QTL models help to identify the genome regions responsible for genetic correlations, whether caused by pleiotropy or genetic linkage, and can show how genetic correlations depend on the environmental conditions. With the objective of identifying QTLs for adaptation to drought stress, we present the results of a multi-trait multi-environment QTL-modelling approach using data from the CIMMYT maize-breeding programme. | ||
| 536 | _aGeneration Challenge Program|Genetic Resources Program | ||
| 546 | _aText in English | ||
| 594 | _aINT1991|CCJL01 | ||
| 650 | 7 |
_2AGROVOC _91081 _aDrought stress |
|
| 650 | 7 |
_2AGROVOC _91853 _aQuantitative Trait Loci |
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| 650 | 7 |
_2AGROVOC _91173 _aMaize |
|
| 700 | 1 |
_9835 _aRibaut, J.M. _gIntegrated Breeding Platform _8INT1991 |
|
| 700 | 1 |
_aVargas, M. _93542 |
|
| 700 | 1 |
_aCrossa, J. _gGenetic Resources Program _8CCJL01 _959 |
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| 700 | 1 |
_aBoer, M.P. _933948 |
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| 700 | 1 |
_aEeuwijk, F.A. van _99549 |
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| 711 | 2 |
_933949 _aFrontis Workshop of Scale and Complexity in Plant Systems Research: Gene-Plant-Crop Relations _d(24-26 Apr 2006 : _cWageningen, Netherlands) |
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| 773 | 0 |
_dDordrecht (Netherlands) : Springer, 2007. _gp. 25-36 _tScale and complexity in plant systems research: gene-plant-crop relations _z978-1-4020-5906-3 |
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| 942 |
_cCPA _2ddc _n0 |
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| 999 |
_c6135 _d6135 |
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