2005
DOI: 10.2135/cropsci2005.0018
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Evaluation of Multienvironment Trials of Peanut Cultivars

Abstract: Multienvironment yield trials (MET) for advanced peanut lines are conducted each year at the EEA‐Manfredi Peanut Breeding Program, the main INTA program for developing new peanut (Arachis hypogaea L.) cultivars for cultivation in the Argentinean crop area. The main objective of this work was the simultaneous analysis of several multienvironment yield tests first to identify superior cultivars for the peanut crop area in Argentina, and second to investigate if different megaenvironments exist. The simultaneous … Show more

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Cited by 51 publications
(32 citation statements)
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“…This makes selection and recommendation of suitable varieties difficult (Caliskan et al, 2007) across the cowpea growing environments. In this case, heritability can be improved by increasing the number of replications, locations, and years (Casanoves et al, 2005).…”
Section: Pc1 -6615%mentioning
confidence: 99%
“…This makes selection and recommendation of suitable varieties difficult (Caliskan et al, 2007) across the cowpea growing environments. In this case, heritability can be improved by increasing the number of replications, locations, and years (Casanoves et al, 2005).…”
Section: Pc1 -6615%mentioning
confidence: 99%
“…ABDULAHI et al Acta Agronomica Hungarica, 57, 2009 186 are essential because of the presence of genotype × environment (GE) interactions, i.e. differential genotypic responses to different environments (Casanoves et al, 2005). The GE interaction complicates the identification of superior genotypes and needs to be modelled and interpreted.…”
Section: Introductionmentioning
confidence: 99%
“…SREG biplot analysis was successfully used in various investigations for mega-environment exploration (Yan et al 2000, Butron et al 2004, Kang et al 2005, Casanoves et al 2005, Malvar et al 2005, Preciado-Ortiz et al 2006, Fan et al 2007, Mohammadi et al 2010and Goyal et al 2011). The comparison of GGE biplot patterns across years and combined data is important because exclusion or inclusion of locations offers more precise evaluations of mega-environment differentiation and of genotype location interaction.…”
Section: Discussionmentioning
confidence: 99%