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001			65393
003			MX-TxCIM
005			20240919021233.0
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020			_a978-3-030-90672-6
020			_a978-3-030-90673-3 (Online)
024			_ahttps://doi.org/10.1007/978-3-030-90673-3_32
040			_aMX-TxCIM
041			_aeng
100	1		_aCrossa, J. _gGenetic Resources Program _8CCJL01 _959
245	1	0	_aChapter 32. Theory and practice of phenotypic and genomic selection indices
260			_bSpringer Nature, _c2022. _aSwitzerland :
500			_aOpen Access
520			_aThe plant net genetic merit is a linear combination of trait breeding values weighted by its respective economic weights whereas a linear selection index (LSI) is a linear combination of phenotypic or genomic estimated breeding values (GEBV) which is used to predict the net genetic merit of candidates for selection. Because economic values are difficult to assign, some authors developed economic weight-free LSI. The economic weights LSI are associated with linear regression theory, while the economic weight-free LSI is associated with canonical correlation theory. Both LSI can be unconstrained or constrained. Constrained LSI imposes restrictions on the expected genetic gain per trait to make some traits change their mean values based on a predetermined level, while the rest of the traits change their values without restriction. This work is geared towards plant breeders and researchers interested in LSI theory and practice in the context of wheat breeding. We provide the phenotypic and genomic unconstrained and constrained LSI, which together cover the theoretical and practical cornerstone of the single-stage LSI theory in plant breeding. Our main goal is to offer researchers a starting point for understanding the core tenets of LSI theory in plant selection.
546			_aText in English
650		7	_aWheat _2AGROVOC _91310
650		7	_aBreeding _2AGROVOC _91029
650		7	_aPlant breeding _gAGROVOC _2 _91203
650		7	_aPhenotypes _2AGROVOC _93634
700	1		_91932 _aCeron Rojas, J.J.
700	1		_911082 _aMartini, J.W.R. _8001712002 _gGenetic Resources Program
700	1		_8001712000 _aCovarrubias-Pazaran, G. _gFormerly Research & Partnership Program _gFormerly Excellence in Breeding _917249
700	1		_91935 _aAlvarado Beltrán, G. _8N1202289 _gGenetic Resources Program
700	1		_91999 _aToledo, F.H. _8I1706676 _gGenetic Resources Program
700	1		_9880 _aVelu, G. _8INT2983 _gGlobal Wheat Program
773			_dSwitzerland : Springer Nature, 2022. _gp. 593–616 _tWheat improvement : food security in a changing climate _w65358 _z978-3-030-90672-6
856			_yOpen Access through DSpace _uhttps://hdl.handle.net/10883/22207
942			_cBP _n0 _2ddc
999			_c65393 _d65385