000			03507nab a22004577a 4500
001			G74946
003			MX-TxCIM
005			20240919021143.0
008			210727s2001 xxu|||p|op||| 00| 0 eng d
022			_a1435-0645 (Online)
024	8		_ahttps://doi.org/10.2134/agronj2001.934949x
040			_aMX-TxCIM
041			_aeng
090			_aCIS-3096
100	1		_aVargas, M. _93542
245	1	0	_aInterpreting treatment x environment interaction in agronomy trials
260			_aUSA : _bASA : _bWiley, _c2001.
340			_aPrinted
500			_aPeer review
500			_aPeer-review: Yes - Open Access: Yes|http://science.thomsonreuters.com/cgi-bin/jrnlst/jlresults.cgi?PC=MASTER&ISSN=0002-1962
520			_aMultienvironment trials are important in agronomy because the effects of agronomic treatments can change differentially in relation to environmental changes, producing a treatment × environment interaction (T × E). The aim of this study was to find a parsimonious description of the T × E existing in the 24 agronomic treatments evaluated during 10 consecutive years by (i) investigating the factorial structure of the treatments to reduce the number of treatment terms in the interaction and (ii) using quantitative year covariables to replace the qualitative variable year. Multiple factorial regression (MFR) for specific T × E terms was performed using standard forward selection procedures for finding year covariables that could replace the factor year in those T × E terms. Subsequently, we compared the results of the final MFR with those of a partial least squares based analysis to achieve extra insight in both the T × E and final MFR model. The MFR model with a stepwise procedure used in this study for describing the T × E showed that the most important interaction with year was that due to different N fertilizer levels and the most important environmental variables that explained year × N interaction were minimum temperatures in January, February, and March and maximum temperature in April. Evaporation in December and April were important covariables for describing year × tillage and year × summer crop interactions, whereas precipitation in December and sun hours in February were important for explaining the year × manure interaction. We also discuss the parallels with extended additive main effect and multiplicative interaction analysis. Biological interpretation of the results are provided.
536			_aConservation Agriculture Program|Global Wheat Program|Genetic Resources Program
546			_aText in English
591			_aR01JOURN|0107|3
594			_aINT1511|CCJL01|CSAY01
595			_aCSC
650		7	_aAgronomic characters _2AGROVOC _91008
650		0	_aAnalysis _gAGROVOC _927824
650		7	_91133 _aGenotype environment interaction _2AGROVOC
650		7	_aStatistical methods _92624 _2AGROVOC
650		7	_aExperimentation _2AGROVOC _94432
650		7	_91190 _aNitrogen fertilizers _2AGROVOC
650		7	_aPlant breeding _gAGROVOC _2 _91203
700	1		_aCrossa, J. _gGenetic Resources Program _8CCJL01 _959
700	1		_99549 _aEeuwijk, F.A. van
700	1		_94612 _aSayre, K.D. _gSustainable Intensification Program _8CSAY01
700	1		_aReynolds, M.P. _gGlobal Wheat Program _8INT1511 _9831
773	0		_tAgronomy Journal _n629529 _gv. 93, no. 4, p. 949-960 _dMadison, WI (USA) : ASA : Wilye, 2001. _wG444482 _x1435-0645
856	4		_uhttps://hdl.handle.net/20.500.12665/358 _yAccess only for CIMMYT Staff
942			_cJA _2ddc _n0
999			_c22143 _d22143