Genetic parameters and selection of soybean lines based on selection indexes
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 locate...
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Veröffentlicht in: | Genetics and molecular research 2017-09, Vol.16 (3), p.1 |
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Sprache: | eng |
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Zusammenfassung: | 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 enabled the highest trait individual gains. The Williams (1962) index and the Smith (1936) and Hazel (1943) index presented the highest selection gain for the grain yield character. The genotype-ideotype distance index and the index of the sum of ranks of Mulamba and Mock (1978) presented higher values of total selection gain. The lines UFUS FG 12, UFUS FG 14, UFUS FG 18, UFUS FG 25, and UFUS FG 31 were distinguished as superior genotypes by direct selection methods and selection indexes. |
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ISSN: | 1676-5680 |
DOI: | 10.4238/gmr16039750 |