ABSTRACT: Abiotic stresses, such as heat, drought and salinity, affect the development of wheat crop and hinder its expansion to the central region of Brazil. The identification of genotypes tolerant to these conditions is important for improving yield performance. The present research evaluated the impact of different abiotic stresses on germination and seedling development and selected wheat genotypes tolerant to these stresses, using multi-trait analysis. Heat, drought and salinity stresses were induced in seeds of 23 wheat genotypes. Seed germination, seedling length and dry mass were evaluated. An adaptability and stability model and a multi-trait selection index were applied to the data. Drought and salinity negatively affected the development of seedlings of the 23 evaluated genotypes. However, the VI 14055, ORS Madre Pérola and BRS 404 genotypes conferred the best adaptability and stability results and were selected by the MGIDI, which revealed that great performance can be achieved in regions with potential for abiotic stress, in the early stages of development. ABSTRACT heat Brazil multitrait multi trait analysis Heat 2 data However 14055 40 MGIDI stress 1405 4 140 14 1

RESUMO: Estresses abióticos como calor, seca e salinidade afetam o desenvolvimento da cultura do trigo e dificulta a sua expansão para a região central do Brasil. A identificação de genótipos tolerantes a estas condições são importantes para o melhoramento genético da cultura. Logo, objetivou-se avaliar o impacto de diferentes estresses abióticos sobre parâmetros de germinação e do desenvolvimento de plântulas de trigo via análise multi-trait. Estresses térmico por calor, seca e salinidade foram induzidos em sementes de 23 genótipos de trigo. Foram avaliados a germinação das sementes, comprimento e massa seca da plântula. Foram aplicados sobre os dados, modelo de adaptabilidade e estabilidade e índice de seleção multi-trait. Os ambientes de estresse abiótico por seca e salinidade afetaram negativamente o desenvolvimento das plântulas dos 23 genótipos avaliados. Contudo, os genótipos VI 14055, ORS Madre Pérola e BRS 404 combinam os melhores resultados de adaptabilidade e estabilidade e foram selecionados pelo MGIDI. Por meio disso, estes genótipos são potencias para serem recomendados às regiões em que se ocorre estes tipos de estresses abióticos. RESUMO calor Brasil Logo objetivouse objetivou multitrait. multitrait multi trait. trait multi-trait 2 plântula dados Contudo 14055 40 MGIDI disso 1405 4 140 14 1

ABSTRACT A large set of variables is assessed for progeny selection in a plant-breeding program and other agronomic fields. The meta-analysis of the coefficient of variation (CVe) produces information for researchers and breeders on the experimental quality of trials. This analysis can also be applied in the decision-making process of the experimental plan regarding the experimental design, the number of repetitions, and the treatments and plants/progenies to be measured. In this study, we evaluated the dataset distribution and the descriptive statistics of CVe through the Frequentist and Bayesian approaches, aiming to establish the credibility and confidence intervals. We submitted CVe data of ten wheat (Triticum aestivum L.) traits reported in 1,068 articles published to the Bayesian and Frequentist analyses. Sample data were analyzed via Gamma and normal models. We selected the model with the lowest Akaike Information Criterion (AIC) value, and then we tested three link functions. In the Bayesian analysis, uniform distributions were used as non-informative priors for the Gamma distribution parameters with three ranges of q~U (a,b,). Thus, the prior probability density function was given by: p θ = 1 β - α , θ ∈ α , β . The Bayesian and Frequentist approaches with the Gamma model presented similar results for CVe; however, the range Bayesian credible intervals was narrower than the Frequentist confidence intervals. Gamma distribution fitted the CVe data better than the normal distribution. The credible and confidence intervals of CVe were successfully applied to wheat traits and could be used as experimental accuracy measurements in other experiments.