Experimental alternatives in the evaluation of families in the genetic improvement of bean plants

Citation
Ea. De Souza et al., Experimental alternatives in the evaluation of families in the genetic improvement of bean plants, PESQ AGROP, 35(9), 2000, pp. 1765-1771
Citations number
33
Categorie Soggetti
Agriculture/Agronomy
Journal title
PESQUISA AGROPECUARIA BRASILEIRA
ISSN journal
0100204X → ACNP
Volume
35
Issue
9
Year of publication
2000
Pages
1765 - 1771
Database
ISI
SICI code
0100-204X(200009)35:9<1765:EAITEO>2.0.ZU;2-#
Abstract
The aim of this work was to evaluate the viability of using the augmented b lock designs and spatial analysis methods for early-stage selection in bree ding programs for common bean (Phaseolus vulgaris L.). A total of 121 S-2 p rogenies were evaluated in three locations: Lavras, Lambari and Patos de Mi nas, Brazil. A simple 11 x 11 lattice design was employed by location. Addi tionally, two controls, Carioca and EMGOPA 201-Ouro, were included. The spl it plots were composed by two 2 m lines with 15 seeds/m. The data of the pr oduction (g/plot) were submitted to a variance analysis, considering the fo llowing strategies: lattice design, augmented block design, randomized comp lete block design, Papadakis' method, moving means method, and check plots method. The comparison between the different strategies was done considerin g their efficiency in controlling the experimental error and in relation to the precision of the estimates of genetic and phenotypic parameters obtain ed in each method. General results indicate that augmented block design is useful in earlier stage of selection, when the intensities of selection are moderate to low; however, this design is not useful for estimation of gene tic and phenotypic parameters due to lower precision of estimates; the use of check plots method did not improve the experimental precision; the neare st neighbour, Papadakis and moving means methods were efficient in removing the heterogeneity within blocks; this efficiency was equivalent to lattice analysis for estimation of genetic and phenotypic parameters.