The objective of this work was to evaluate the adaptability and multi-trait stability of wheat (Triticum aestivum) genotypes according to the phenotypic index of seed vigor (PIV). Thirty wheat genotypes were grown in seven environments in the state of Rio Grande do Sul, Brazil, during one crop season. In each environment, a randomized complete block design with three replicates was used. The PIV was elaborated from the following traits: first germination count, germination percentage, accelerated aging, and electrical conductivity. The evaluated phenotypic index makes it possible to define macroenvironments for the production of wheat seeds with high physiological potential and to understand the implications of the genotype x environment interaction. The phenotypic index of seed vigor is effective to rank genotypes considering multi-trait selection related to the vigor of wheat seeds produced in Southern Brazil.
ABSTRACT. The wheat crop presents sensitivity to the environmental conditions culminating in the genotype x environment interaction, being crucial the use of different methodologies to guide the positioning of genotypes to certain cultivation environments. The objective of this study was to estimate the adaptability and phenotypic stability of wheat genotypes grown in the State of Rio Grande do Sul using univariate and multivariate techniques and mixed models. The yield data of 42 2 V.J. Szareski et al. Genetics and Molecular Research 16 (3): gmr16039735wheat genotypes evaluated in five environments (Cachoeira do Sul, Passo Fundo, Santo Augusto, São Gabriel, and São Luiz Gonzaga) were used in the 2012 and 2013 crop seasons. In each experiment, a randomized complete block design was used, with three replicates. In the evaluation of the genotype x environment interaction, the sum of squares relative to contribution index, the methodology based on the univariate method of Annicchiarico (1992), the multivariate method (AMMI), and the mixed models (REML and MHPRVG) were used. The favorable environments expressed by the univariate method referred to São Gabriel, Cachoeira do Sul, Passo Fundo, Santo Augusto, and São Luiz Gonzaga; for the multivariate method, only Santo Augusto was favorable to the productivity character. The genotypes CD 121 and TBIO Tibagi were adapted and stable for the univariate and multivariate methods. The genotypes TBIO Sinuelo, Quartzo, BRS 327, Mirante, Topázio, Guamirim, TBIO Seleto, Ametista, TBIO Mestre, and BRS Louro were superior through the mixed model approach. The different strategies to estimate the adaptability and phenotypic stability allowed indicating and recommending the best environments and genotypes efficiently to obtain increases in wheat grain yield.
This work was aimed at determining stability and adaptability through Additive Main Effects and Multiplicative Interaction (AMMI) and Genotype Main Effects and Genotype Environment Interaction (GGE) methodologies, as well as to estimate and predict Restricted Maximum Likelihood/Best Linear Unbiased Prediction (REML/BLUP) parameters and employ them in multivariate models using wheat genotypes grown in the major wheat regions of Brazil. The trials were conducted during the 2017growing seasnon across 12 regions of Brazil, with nine wheat genotypes, arranged in three replicates. When there were significant G x E interactions, the AMMI and GGE methods were applied. The scores were represented in biplot graphs through multivariate methodology of the principal components. REML/BLUP estimates and predictions were employed in the GGE multivariate method to obtain inferences based on genetic effects, which was denominated predicted genetic GGE approach. The predicted genetic approach was superior to a phenotypic comparison to explain the effects of genotypes x ©FUNPEC-RP www.funpecrp.com.br Genetics and Molecular Research 17 (3): gmr18026 V.J. Szareski et al 2 environments interaction for wheat seed yield in Brazil. Specific adaptability for seed yield was established through phenotypic and genetic predicted approaches for genotypes BRS 331 and Marfimin the environment Itapeva, SP, as well as the genotype FPS Certerotoin the environment Cascavel. PR, and BRS 327 in the environment Cruz Alta, RS. The use of multivariate biometric methodologies along with the new predicted genetic approach enables reliable positioning of wheat genotypes for seed production across the main wheat regions of Brazil.
We appled a genetic and phenotypic multi-character predicted approach to the use of the multivariate methods Additive Main effects and Multiplicative Interaction (AMMI) and Genotype Main Effects and Genotype Environment Interaction (GGE). The experiment was carried out in the agricultural crop year of 2016 in the state of Rio Grande do Sul, Brazil. The experimental design was a randomized block design, with 14 growing environments x five wheat genotypes arranged in three replications. The characters were falling number, gluten strengthand protein content, which were used to make multi-character the technological index of the industrial quality of the wheat grains and multi-character the technological index of the industrial quality of the wheat grains. Multi-character selection can be a useful tool for identifying genotypes and growing environments that maximize the industrial quality of wheat grain. The GGE method provides greater explicability of the effects of genotype x environment interaction based on multi-character selection. The multicharacter genetic approach predicted for the ©FUNPEC-RP www.funpecrp.com.br Genetics and Molecular Research 18 (3): gmr18223 V.J. Szareski et al. 2 selection of the industrial quality of wheat grain results in reliable inferences in the indication of adaptability and stability for the AMMI method and for GGE.
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