# MÉTODOS DE PREDIÇÃO E ESTIMAÇÃO DE VALOR GENOTÍPICO E ESTRATIFICAÇÃO AMBIENTAL PARA AVALIAÇÃO E RECOMENDAÇÃO DE CULTIVARES

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## Arquivos

## Data

2008-06-13

## Título da Revista

## ISSN da Revista

## Título de Volume

## Editor

Universidade Federal de Goiás

## Resumo

This research had the objective of evaluating the effects of different statistical
approaches for the selection and ranking of genotypes, in the context of maize varieties
trials. For that, data from real trials designed in lattice were used, in the Goiás State, Brazil,
in the growing seasons of 2002/2003, 2003/2004, 2004/2005 and 2005/2006, as well as
data from simulated experiments, aiming to cover situations related to that reality. The
study also intended to quantify the effects of the genotype by environment interactions
(GxE) from the real trials, aiming for the environmental stratification for the maize
cultivation in the State, pointing out the cultivar evaluation and recommendation.
Considering those objectives, the study is divided in three scientific articles. In the first one
(Chapter 3), the effects of approaches of fixed model (FF), mixed model with random
effect of blocks (AF), mixed model with random effect of treatments (FA), random model
(AA), and James-Stein s estimator (JS) were evaluated on the selection and ranking of
genotypes tested on the maize varieties trials, coordinated by the Agência Goiana de
Desenvolvimento Rural e Fundiário (AgenciaRural Goiás). The experiments, in number
of 47, were installed in lattice design, with three replications, during the four cited harvest
years. In the second article (Chapter 4), the same approaches were evaluated, in terms of
accuracy, mean predictive deviation and precision of their estimates/predictions,
considering the simulated trials, also in lattice. Forty-eight cases were considered,
corresponding to the combinations of different experimental sizes (15, 54, 105, and 450
treatments), genotypic determination coefficients h2' (6%, 15%, 25%, 48%, 63% and
82%), and two probability distributions for the generation of genotypic effects (normal and
uniform). One thousand trials were simulated for each case, reaching the total of 48,000
experiments. The third and last article (Chapter 5) refers to the study of the GxE
interaction, emphasizing the already mentioned environmental stratification, where the
winner genotypes approach in association with the AMMI analysis (additive main effects
and multiplicative interaction model) was adopted. Among the results and conclusions
achieved through this study, it is possible to point out: i) the adoption of statistical
approaches with shrinkage effect on the genotypic means results in the selection of a lower
number of genotypes, especially in those trials whose mean of the check cultivars (baseline
to the genotypic selection) is higher than the experimental grand mean; this fact reduces
the number of genotypes with low yield potential in the next cycles of the selection
program; ii) the use of models with fixed effects of treatments leads to a higher percentage
of selected genotypes, mainly in the experiments whose check varieties mean overcomes
the experimental grand mean; iii) among the shrinkage statistic approaches evaluated, the
AA model must be preferred for the selection of genotypes, due to its capacity for better
predicting the parametric genotypic effects (higher accuracy and lower mean predictive
deviation), no matter if these effects are normally or uniformly distributed; iv) on the other
hand, the FF model shows the worst relative performance, except for the situations where
the variability among the genetic treatments is high (h2 ®1,0); v) considering low values
for h2 (6%), the FA model shows efficiency similar to the AA model; vi) two established environmental strata showed to be consistent throughout the years, even when the tested
genotypes were altered from one harvest season to the other: Ipameri, Inhumas and
Senador Canêdo (stable to four years), and Porangatu and Orizona (stable along three
years); vii) considering the obtained clustering, it is possible to reduce, at least 16%, the
number of test locations currently used, and/or substitute the redundant locations by test
places which better represent the recommended target region, aiming to increase the
evaluation efficiency of the GxE interaction, in the scope of the genetic plant breeding
program; viii) the ALBandeirante variety presents high yield potential and adaptability to
the maize cultivation conditions in the Goiás State.

This research had the objective of evaluating the effects of different statistical approaches for the selection and ranking of genotypes, in the context of maize varieties trials. For that, data from real trials designed in lattice were used, in the Goiás State, Brazil, in the growing seasons of 2002/2003, 2003/2004, 2004/2005 and 2005/2006, as well as data from simulated experiments, aiming to cover situations related to that reality. The study also intended to quantify the effects of the genotype by environment interactions (GxE) from the real trials, aiming for the environmental stratification for the maize cultivation in the State, pointing out the cultivar evaluation and recommendation. Considering those objectives, the study is divided in three scientific articles. In the first one (Chapter 3), the effects of approaches of fixed model (FF), mixed model with random effect of blocks (AF), mixed model with random effect of treatments (FA), random model (AA), and James-Stein s estimator (JS) were evaluated on the selection and ranking of genotypes tested on the maize varieties trials, coordinated by the Agência Goiana de Desenvolvimento Rural e Fundiário (AgenciaRural Goiás). The experiments, in number of 47, were installed in lattice design, with three replications, during the four cited harvest years. In the second article (Chapter 4), the same approaches were evaluated, in terms of accuracy, mean predictive deviation and precision of their estimates/predictions, considering the simulated trials, also in lattice. Forty-eight cases were considered, corresponding to the combinations of different experimental sizes (15, 54, 105, and 450 treatments), genotypic determination coefficients h2' (6%, 15%, 25%, 48%, 63% and 82%), and two probability distributions for the generation of genotypic effects (normal and uniform). One thousand trials were simulated for each case, reaching the total of 48,000 experiments. The third and last article (Chapter 5) refers to the study of the GxE interaction, emphasizing the already mentioned environmental stratification, where the winner genotypes approach in association with the AMMI analysis (additive main effects and multiplicative interaction model) was adopted. Among the results and conclusions achieved through this study, it is possible to point out: i) the adoption of statistical approaches with shrinkage effect on the genotypic means results in the selection of a lower number of genotypes, especially in those trials whose mean of the check cultivars (baseline to the genotypic selection) is higher than the experimental grand mean; this fact reduces the number of genotypes with low yield potential in the next cycles of the selection program; ii) the use of models with fixed effects of treatments leads to a higher percentage of selected genotypes, mainly in the experiments whose check varieties mean overcomes the experimental grand mean; iii) among the shrinkage statistic approaches evaluated, the AA model must be preferred for the selection of genotypes, due to its capacity for better predicting the parametric genotypic effects (higher accuracy and lower mean predictive deviation), no matter if these effects are normally or uniformly distributed; iv) on the other hand, the FF model shows the worst relative performance, except for the situations where the variability among the genetic treatments is high (h2 ®1,0); v) considering low values for h2 (6%), the FA model shows efficiency similar to the AA model; vi) two established environmental strata showed to be consistent throughout the years, even when the tested genotypes were altered from one harvest season to the other: Ipameri, Inhumas and Senador Canêdo (stable to four years), and Porangatu and Orizona (stable along three years); vii) considering the obtained clustering, it is possible to reduce, at least 16%, the number of test locations currently used, and/or substitute the redundant locations by test places which better represent the recommended target region, aiming to increase the evaluation efficiency of the GxE interaction, in the scope of the genetic plant breeding program; viii) the ALBandeirante variety presents high yield potential and adaptability to the maize cultivation conditions in the Goiás State.

This research had the objective of evaluating the effects of different statistical approaches for the selection and ranking of genotypes, in the context of maize varieties trials. For that, data from real trials designed in lattice were used, in the Goiás State, Brazil, in the growing seasons of 2002/2003, 2003/2004, 2004/2005 and 2005/2006, as well as data from simulated experiments, aiming to cover situations related to that reality. The study also intended to quantify the effects of the genotype by environment interactions (GxE) from the real trials, aiming for the environmental stratification for the maize cultivation in the State, pointing out the cultivar evaluation and recommendation. Considering those objectives, the study is divided in three scientific articles. In the first one (Chapter 3), the effects of approaches of fixed model (FF), mixed model with random effect of blocks (AF), mixed model with random effect of treatments (FA), random model (AA), and James-Stein s estimator (JS) were evaluated on the selection and ranking of genotypes tested on the maize varieties trials, coordinated by the Agência Goiana de Desenvolvimento Rural e Fundiário (AgenciaRural Goiás). The experiments, in number of 47, were installed in lattice design, with three replications, during the four cited harvest years. In the second article (Chapter 4), the same approaches were evaluated, in terms of accuracy, mean predictive deviation and precision of their estimates/predictions, considering the simulated trials, also in lattice. Forty-eight cases were considered, corresponding to the combinations of different experimental sizes (15, 54, 105, and 450 treatments), genotypic determination coefficients h2' (6%, 15%, 25%, 48%, 63% and 82%), and two probability distributions for the generation of genotypic effects (normal and uniform). One thousand trials were simulated for each case, reaching the total of 48,000 experiments. The third and last article (Chapter 5) refers to the study of the GxE interaction, emphasizing the already mentioned environmental stratification, where the winner genotypes approach in association with the AMMI analysis (additive main effects and multiplicative interaction model) was adopted. Among the results and conclusions achieved through this study, it is possible to point out: i) the adoption of statistical approaches with shrinkage effect on the genotypic means results in the selection of a lower number of genotypes, especially in those trials whose mean of the check cultivars (baseline to the genotypic selection) is higher than the experimental grand mean; this fact reduces the number of genotypes with low yield potential in the next cycles of the selection program; ii) the use of models with fixed effects of treatments leads to a higher percentage of selected genotypes, mainly in the experiments whose check varieties mean overcomes the experimental grand mean; iii) among the shrinkage statistic approaches evaluated, the AA model must be preferred for the selection of genotypes, due to its capacity for better predicting the parametric genotypic effects (higher accuracy and lower mean predictive deviation), no matter if these effects are normally or uniformly distributed; iv) on the other hand, the FF model shows the worst relative performance, except for the situations where the variability among the genetic treatments is high (h2 ®1,0); v) considering low values for h2 (6%), the FA model shows efficiency similar to the AA model; vi) two established environmental strata showed to be consistent throughout the years, even when the tested genotypes were altered from one harvest season to the other: Ipameri, Inhumas and Senador Canêdo (stable to four years), and Porangatu and Orizona (stable along three years); vii) considering the obtained clustering, it is possible to reduce, at least 16%, the number of test locations currently used, and/or substitute the redundant locations by test places which better represent the recommended target region, aiming to increase the evaluation efficiency of the GxE interaction, in the scope of the genetic plant breeding program; viii) the ALBandeirante variety presents high yield potential and adaptability to the maize cultivation conditions in the Goiás State.

## Descrição

## Citação

FELIPE, Cristiane Rachel de Paiva. Breeding value prediction and estimation methods and
environmental stratification for cultivar evaluation and recommendation.. 2008. 113 f. Tese (Doutorado em Ciências Agrárias) - Universidade Federal de Goiás, Goiânia, 2008.