Abstract
This study aimed to evaluate the efficiency of multiple centroids to study the adaptability of alfalfa genotypes (Medicago sativa L.). In this method, the genotypes are compared with ideotypes defined by the bissegmented regression model, according to the researcher's interest. Thus, genotype classification is carried out as determined by the objective of the researcher and the proposed recommendation strategy. Despite the great potential of the method, it needs to be evaluated under the biological context (with real data). In this context, we used data on the evaluation of dry matter production of 92 alfalfa cultivars, with 20 cuttings, from an experiment in randomized blocks with two repetitions carried out from November 2004 to June 2006. The multiple centroid method proved efficient for classifying alfalfa genotypes. Moreover, it showed no unambiguous indications and provided that ideotypes were defined according to the researcher's interest, facilitating data interpretation.
Highlights
In the presence of genotype by environment interaction, it is necessary to obtain detailed information on the performance of each cultivar across environmental variations (Cruz et al, 2004)
Mohebodini et al (2006) used several methods to study in detail the genotype x environment interaction of 11 lentil genotypes (Lens culinaris M.)
The multiple centroid method requires that the environments are classified into favorable and unfavorable using the environmental index proposed by Finlay & Wilkinson (1963): where: Yij is the average of the genotype i in the environment j; Y.. is the total number of observations; a is the number of environments; and g is the number of genotypes
Summary
In the presence of genotype by environment interaction, it is necessary to obtain detailed information on the performance of each cultivar across environmental variations (Cruz et al, 2004). A number of methods of adaptability and stability analyses are described in the literature, including the Eberhart & Russell (1966) and the Bayesian method proposed by Nascimento et al (2011) that use the simple regression analysis as statistical principle. Nonparametric methods, such as those developed by Lin & Binns (1988), Nascimento et al (2010), centroid (Rocha et al, 2005) and its subsequent developments the multiple centroid (Nascimento et al, 2009a) and the extended centroid (Nascimento et al, 2009b) are reported. In addition to these, Barreto et al (2011) estimated the adaptability and stability of sweet potato genotypes in three environments in the South Central region of the State of Tocantins
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