Selection indices for agronomic traits in segregating populations of soybean

Bizari, Eduardo Henrique; Val, Bruno Henrique Pedroso; Pereira, Elise de Matos; Mauro, Antônio Orlando Di; Unêda-Trevisoli, Sandra Helena

doi:10.5935/1806-6690.20170012

Cited by 44 publications

(48 citation statements)

References 14 publications

(1 reference statement)

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“…While the direct selection for the number of days for maturity returned the lowest individual gain (4.58%) (Table 4), which matches the low CVg (3.93%) ( Table 1). Bizari et al (2017) found similar gains for direct selection in soybean, with higher productivity gains (35.70%). This gain occurs due to the greater genetic variation of this character.…”

Section: Resultssupporting

confidence: 52%

“…However, the Williams base index was treated in this study as the most appropriate criterion for the analyzed situation. Bizari et al (2017), when comparing different selection indices in soybean segregating populations, found that the rank-based index provided the most favorable gains in the study. It was also used the direct selection criteria, Smith and Hazel classic index, the Williams' base index, the index based on the desired gains of Pesek and Baker, and distance index genotype-ideotype.…”

Section: Resultsmentioning

confidence: 99%

“…Bizari et al (2017) determined that the characters with the highest heritability value were the number of days at maturity (91.7%), followed by oil content (86.21%), agronomic value (74.97%), and grain yield (71.31%). The lowest values were found for the number of pods (54.19%) and plant height at maturity (65.73%), agreeing with the results obtained in this study.…”

Section: Resultsmentioning

confidence: 99%

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Research Article Genetic parameters and selection of soybean lines based on selection indexes.

Teixeira¹,

Hamawaki²,

Nogueira³

et al. 2017

Genet. Mol. Res.

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ABSTRACT. Defining selection criteria is important to obtain promising genotypes in a breeding program. The objective of this study was to estimate genetic parameters for agronomic traits and to perform soybean line selection using selection indices. The experiment was conducted at an experimental area located at Capim Branco farm, belonging to the Federal University of Uberlândia. A total of 37 soybean genotypes were evaluated in randomized complete block design with three replicates, in which twelve agronomic traits were evaluated. Analysis of variance, the Scott-Knott test at the 1 and 5% level of probability, and selection index analyses were performed. There was genetic variability for all agronomic traits, with medium to high levels of genotype determination coefficient. Twelve lines with a total cycle up to 110 days were observed and grouped with the cultivars MSOY 6101 and UFUS 7910. Three lines, UFUS FG 03, UFUS FG 20, and UFUS FG 31, were highlighted regarding grain yield with higher values than the national average of 3072 kg/ha. The direct selection

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Section: Resultssupporting

confidence: 52%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Research Article Genetic parameters and selection of soybean lines based on selection indexes.

Teixeira¹,

Hamawaki²,

Nogueira³

et al. 2017

Genet. Mol. Res.

View full text Add to dashboard Cite

show abstract

“…Para NDM, valores semelhantes de h 2 também foram encontrados por Bizari et al (2017), ao avaliarem os índices de seleção para caracteres agronômicos em populações segregantes de soja em São Paulo. Bologna et al (2014) também obtiveram valores elevados de herdabilidade para o NDM em população F 3 de soja (0,76).…”

Section: Resultsunclassified

“…Vários trabalhos foram realizados em gerações iniciais na cultura da soja, para estimar parâmetros genéticos como a herdabilidade, coeficiente de relação genotípica e fenotípica e correlações fenotípicas, os quais foram avaliados em diferentes locais, como demonstram os de Costa et al (2008), Carvalho et al (2009), Matsuo et al (2012, Tavares et al (2013), Bologna et al (2014), Charnai et al (2014), Malek et al (2014), Bizari et al (2017) e Follmann et al (2017.…”

Section: Introductionunclassified