000			02703nab|a22003497a|4500
999			_c64100 _d64092
001			64100
003			MX-TxCIM
005			20240919021231.0
008			200416s2022||||bl |||p|op||||00||0|eng|d
022			_a1678-992X (Online)
024	8		_ahttps://doi.org/10.1590/1678-992X-2020-0314
040			_aMX-TxCIM
041			_aeng
100	1		_aPereira, F.C. _922235
245	1	0	_aMega-environment analysis of maize breeding data from Brazil
260			_aPiracicaba, SP (Brazil) : _bEscola Superior de Agricultura Luiz de Queiroz, _c2022.
500			_aPeer review
500			_aOpen Access
520			_aThe development and recommendation of single cross maize hybrids (SH) to be used in extensive land areas (mega-environments), and in different crop seasons requires many experiments under numerous environmental conditions. The question we asked is if the data from these multi-environment experiments are sufficient to identify the best hybrid combinations. The aim of this study was to critically analyze the phenotype data of experiments of yield, established by a large seed producing company, under a high level of imbalance. Data from evaluation of 2770 SH were used from experiments conducted over four years, involving the first and second crop seasons, in 50 locations of different years and regions of Brazil. Different types of analysis were carried out and genetic and non-genetic components were estimated, with emphasis on the different interactions of the SH with the environments. Results showed that the coincidence of common hybrids in these experiments is normally small. The estimates of the correlations between of the hybrids coinciding in the environments two by two is of low magnitude. The hybrid × crop season interaction was always expressive; however, the interactions of hybrids and other environmental variables were also important. Under these conditions, alternatives were discussed for making with the information obtained from the experiments, can be more efficient on the process to obtain new hybrids by companies.
546			_aText in English
650		7	_2AGROVOC _91133 _aGenotype environment interaction
650		7	_2AGROVOC _99002 _aData
650		7	_aPlant breeding _gAGROVOC _2 _91203
650		7	_aMaize _gAGROVOC _2 _91173
651		7	_2AGROVOC _95489 _aBrazil
700	1		_aPatto Ramalho M.A. _91998
700	1		_aResende, M.F.R. _922236
700	1		_aVon Pinho, R.G. _922237
773	0		_tScientia Agricola _gv. 79, no. 2, e20200314 _dPiracicaba, SP (Brazil) : Escola Superior de Agricultura Luiz de Queiroz, 2022. _x1678-992X _wG76199
856	4		_uhttps://doi.org/10.1590/1678-992X-2020-0314 _yClick here to access online
942			_cJA _n0 _2ddc