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.
The objective of this work was to evaluate the agronomic performance of corn hybrids, the interrelations of the characters with the grain yield, and to genetically discriminate the corn hybrids by means of the dispersion analysis of the canonical variables. The experiment was conducted in the agricultural crop of 2013/2014, in an area belonging to the Federal University of Santa Maria, Campus of Frederico Westphalen, RS. The experimental design was a randomized block design, with four replications. The treatments were composed of seven maize hybrids with different genetic bases and maturation cycles. The LG 6304 modified simple hybrid has higher grain yield than the others. The characters plant height, spike insertion height and number of grains per row of spike have positive interrelations with grain yield of corn hybrids. Hybrids are not grouped according to the genetic basis and maturation cycle. The canonical variables explain 94.62% of the existing genetic variation, and allows the formation of five groups of maize hybrids.
The aim of this study was to determine associations of cause and effect agronomic traits with grain yield in contrasting growth habits of soybean genotypes, as well as to verify the magnitude of similar behaviors in different growing environments. The trials were conducted for one crop season using randomized blocks design arranged in factorial scheme, including two growing environments (Independência -RS and Tenente Portela -RS) x four genotypes (FPS Solimões RR e FPS Júpiter RR; BRS Tordilha RR and Fepagro 36 RR, 2 indeterminate and 2 determinate growing habits, respectively) in three replications. Ten important soybean yield components were evaluated. The data were subjected to individual analysis of variance for each environment and growing habits. For each environment within habits, the phenotypic path analysis was performed among the traits. The components number of pods on the main stem, number of ramifications, number of pods in the ramifications, and number of one and two-grain pods presented contrasting results in growing environments. The number of three-grain pods is among the components mostly related to grain yield for both determinate and indeterminate growing habit genotypes, regardless of the environment. The adoption of genotypes with higher weight of thousand grains may provide satisfactory results for grain yield, regardless of the growth habit and environment of cultivation.
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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