000			03143nab a22004097a 4500
001			G89583
003			MX-TxCIM
005			20240919020945.0
008			210803s2006 xxu|||p|op||| 00| 0 eng d
022			_a1435-0653 (Online)
024	8		_ahttps://doi.org/10.2135/cropsci2006.04.0227
040			_aMX-TxCIM
041			_aeng
090			_aCIS-4852
100	1		_aCotes, J.M. _921792
245	1	2	_aA bayesian approach for assessing the stability of genotypes
260			_aUSA : _bCSSA : _bWiley. _c2006.
340			_aComputer File|Printed
500			_aPeer review
500			_aPeer-review: Yes - Open Access: Yes|http://science.thomsonreuters.com/cgi-bin/jrnlst/jlresults.cgi?PC=MASTER&ISSN=0011-183X
520			_aSeveral statistical models can be used for assessing genotype × environment interaction (GEI) and studying genotypic stability. The objectives of this research were to show how (i) to use Bayesian methodology for computing Shukla's phenotypic stability variance and (ii) to incorporate prior information on the parameters for better estimation. Potato [Solanum tuberosum subsp. andigenum (Juz. & Bukasov) Hawkes], wheat (Triticum aestivum L.), and maize (Zea mays L.) multi environment trials (MET) were used for illustrating the application of the Bayes paradigm. The potato trial included 15 genotypes, but prior information for just three genotypes was used. The wheat trial used prior information on all 10 genotypes included in the trial, whereas for the maize trial, noninformative priors for the nine genotypes was used. Concerning the posterior distribution of the genotypic means, the maize MET with 20 sites gave less disperse posterior distributions of the genotypic means than did the posterior distribution of the genotypic means of the other METs, which included fewer environments. The Bayesian approach allows use of other statistical strategies such as the normal truncated distribution (used in this study). When analyzing grain yield, a lower bound of zero and an upper bound set by the researcher's experience can be used. The Bayesian paradigm offers plant breeders the possibility of computing the probability of a genotype being the best performer. The results of this study show that although some genotypes may have a very low probability of being the best in all sites, they have a relatively good chance of being among the five highest yielding genotypes.
536			_aGenetic Resources Program
546			_aText in English
591			_aCrop Science Society of America (CSSA)
594			_aCCJL01
650		7	_2AGROVOC _92624 _aStatistical methods
650		7	_2AGROVOC _94013 _aBayesian theory
650		7	_2AGROVOC _91994 _aFood crops
650		7	_2AGROVOC _91134 _aGenotypes
650		7	_2AGROVOC _96345 _aStability
700	1		_aCrossa, J. _gGenetic Resources Program _8CCJL01 _959
700	1		_921793 _aSanches, A.
700	1		_99555 _aCornelius, P.L.
773	0		_tCrop Science _n634482 _gv. 46, no. 6, p. 2654-2665 _dUSA : CSSA : Wiley, 2006. _wG444244 _x1435-0653
856	4		_yAccess only for CIMMYT Staff _uhttps://hdl.handle.net/20.500.12665/334
942			_cJA _2ddc _n0
999			_c26522 _d26522