Statistical methods to study adaptability and stability of wheat genotypes

• Main Authors: Elesandro Bornhofen, Giovani Benin, Lindolfo Storck, Leomar Guilherme Woyann, Thiago Duarte, Matheus Giovane Stoco, Sergio Volmir Marchioro
• Format: Article
• Language: English
• Published: Instituto Agronômico de Campinas
• Series: Bragantia
• Subjects: Triticum aestivum L.; univariate and multivariate methods; rank correlation; grain yield; multi-environment trials
• Online Access: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0006-87052017000100001&lng=en&tlng=en

ABSTRACT The sensitivity of wheat crop to environmental variations frequently results in significant genotype (G) x environment (E) interaction (GEI). We compared statistical methods to analyze adaptability and stability of wheat genotypes in value for cultivation and use (VCU) trials. We used yield performance data of 22 wheat genotypes evaluated in three locations (Guarapuava, Cascavel, and Abelardo Luz) in 2012 and 2013. Each trial consisted of a complete randomized block design with three replications. The GEI was evaluated using methodologies based on mixed models, analysis of variance, linear regression, multivariate, and nonparametric analysis. The Spearman’s rank correlation coefficient was used to verify similarities in the genotype selection process by different methodologies. The Annicchiarico, Lin and Binns modified methodologies, as well as the Harmonic Mean of the Genetic Values (HMGV) allowed to identify simultaneously highly stable and productive genotypes. The grain yield is not associated with Wricke, Eberhart and Russell stability parameters, scores of the first principal component of the AMMI1 method, and GGE biplot stability, indicating that stable genotypes are not always more productive. The data analyzed in this study showed that the AMMI1 and GGE biplot methods are equivalent to rank genotypes for stability and adaptability.