Pesquisa Agropecuária Brasileira | |
Spatial statistical analysis and selection of genotypes in plant breeding | |
João Batista Duarte2  Roland Vencovsky1  | |
[1] ,Universidade Federal de Goiás Escola de Agronomia e Engenharia de Alimentos Goiânia GO ,Brazil | |
关键词: augmented design; mixed model; information recovery; autocorrelation; correlated data; geostatistics; delineamento aumentado; modelo misto; recuperação de informação; autocorrelação; dados correlacionados; geoestatística; | |
DOI : 10.1590/S0100-204X2005000200002 | |
来源: SciELO | |
【 摘 要 】
The objective of this study was to evaluate the efficiency of spatial statistical analysis in the selection of genotypes in a plant breeding program and, particularly, to demonstrate the benefits of the approach when experimental observations are not spatially independent. The basic material of this study was a yield trial of soybean lines, with five check varieties (of fixed effect) and 110 test lines (of random effects), in an augmented block design. The spatial analysis used a random field linear model (RFML), with a covariance function estimated from the residuals of the analysis considering independent errors. Results showed a residual autocorrelation of significant magnitude and extension (range), which allowed a better discrimination among genotypes (increase of the power of statistical tests, reduction in the standard errors of estimates and predictors, and a greater amplitude of predictor values) when the spatial analysis was applied. Furthermore, the spatial analysis led to a different ranking of the genetic materials, in comparison with the non-spatial analysis, and a selection less influenced by local variation effects was obtained.
【 授权许可】
CC BY
All the contents of this journal, except where otherwise noted, is licensed under a Creative Commons Attribution License
【 预 览 】
Files | Size | Format | View |
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RO202103040056366ZK.pdf | 148KB | download |