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.

The aim of this work was to characterize the physiological performance and some of the yield attributes of maize seeds in response to periods of temporary flooding. The study was conducted in an experimental design of randomized blocks, with four treatments composed by four replications, being evaluated the germination, the first count of germination, the germination speed index, the thousand seed weight, the number of seeds per ear, the number of rows per ear, the electrical conductivity in seeds, the length of shoot and primary root and the dry matter of shoot and primary root. Thousand seed weight, number of seeds per ear, number of rows per ear and electrical conductivity in seeds were reduced when plants were exposed to a 72 h flooding period. The flooding period of 72 h adversely affects the growth, the physical characteristics and the vigor of maize seeds.

Late season crops in planossoil are prone to waterlogging associated with high temperatures that are characteristic of the season, during brief periods of time in early summer. The aim of the present study was to evaluate growth, assimilate partitioning and seed vigor of bean plants subjected to periods of waterlogging and high temperatures during late season. Bean plants of the IPR Tuiuiú genotype were submitted to conditions of soil field capacity and to waterlogging for 8, 16 and 24 h. In order to obtain growth data, plants were collected in regular intervals of seven days until the end of the crop cycle, starting after sowing, dry matter content and leaf area were determined and used to estimate dry matter production, relative growth and net assimilation rates, leaf area index, solar energy conversion efficiency and organs' dry matter partitioning. Seeds were collected at the end of the developmental cycle and used for seedling emergence test and evaluation of initial growth. The level of stress imposed by waterlogging and high temperatures is time dependent, paralyzing dry matter allocation in bean plants and reducing the conversion efficiency of solar energy. Seeds produced by plants under this stress present low vigor and reduced initial growth.