Efficiency of methods for genetic progress estimation in common bean breeding using database information
The final field trials to evaluate elite lines developed by the Embrapa national common bean breeding program generated a phenotypic database composed by agronomic traits of 84 elite lines and nine cultivars over a 16-year period (1993–2008) and 450 environments in all Brazilian growing areas. The m...
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Veröffentlicht in: | Euphytica 2018-09, Vol.214 (9), p.1-10, Article 164 |
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Sprache: | eng |
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Zusammenfassung: | The final field trials to evaluate elite lines developed by the Embrapa national common bean breeding program generated a phenotypic database composed by agronomic traits of 84 elite lines and nine cultivars over a 16-year period (1993–2008) and 450 environments in all Brazilian growing areas. The main goal of this study was to use this database as a model to compare the consistency of the results obtained from indirect methods for genetic progress estimation for grain yield in common bean breeding, using the direct method as a reference. Three indirect methods for genetic progress estimation were evaluated: (1) linear regression with unadjusted averages, (2) linear regression with averages adjusted by the mixed models, and (3) linear regression with averages adjusted by a fixed effects model with the error exception. The genetic progress estimated by the direct method was 31.3 kg ha
−1
per year (1.34%**). This value was considered as the reference estimate, since it was calculated using the grain yield data from final field trials with all common bean lines evaluated under the same environmental conditions. The estimate obtained using the regression with unadjusted averages of the three best lines by cycle was 25.66 kg ha
−1
per year (1.26%*), similar to the result obtained by the direct method. Considering both methods using fixed and mixed models, the genetic gain estimates were statistically null (0.42% and 0.45%, respectively). Therefore, the regression method with unadjusted means was more informative than the other indirect methods. |
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ISSN: | 0014-2336 1573-5060 |
DOI: | 10.1007/s10681-018-2246-8 |