Back to Search Start Over

Simulated Individual Best Linear Unbiased Prediction versus Mass Selection in Sugarcane Families.

Authors :
Brasileiro, Bruno Portela
de Paula Mendes, Thiago Otávio
Peternelli, Luiz Alexandre
da Silveira, Luís Cláudio Inácio
de Resende, Marcos Deon Vilela
Barbosa, Márcio Henrique Pereira
Source :
Crop Science; Mar/Apr2016, Vol. 56 Issue 2, p570-575, 6p
Publication Year :
2016

Abstract

The purpose of this study was to compare the method BLUPIS (best linear unbiased prediction individual simulated) with mass selection in terms of efficiency in identifying the best genotypes in sugarcane (Saccharum officinarum L.) families. Mass selection was performed by two breeders with 25 yr of experience. The BLUPIS procedure selected families with higher means for tons of cane per hectare (TCH) than the over-all mean. The number of plants selected per family was calculated by n<subscript>k</subscript> = (ĝ<subscript>k</subscript> / ĝ<subscript>j</subscript> )n<subscript>j</subscript>, where ĝ<subscript>k</subscript> indicates the genotypic value of the kth family; ĝ<subscript>j</subscript> the genotypic value of the best family; and n<subscript>j</subscript> is equal to the number of plants selected in the best family, determined as n<subscript>j</subscript> = 45 in this study. Out of 20 best clones forwarded to the third test phase (T3), BLUPIS selected all in the first test phase (T1) and mass selection only two. Therefore, 100% of the clones in the second test phase (T2) had been selected by BLUPIS. The BLUPIS was most efficient in detecting the best genotypes, since all clones that were promoted up to phase T3 were descendants from the best families. The BLUPIS method should be applied in sugarcane breeding programs to ensure the selection of the best genotypes. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
0011183X
Volume :
56
Issue :
2
Database :
Complementary Index
Journal :
Crop Science
Publication Type :
Academic Journal
Accession number :
113860275
Full Text :
https://doi.org/10.2135/cropsci2015.03.0199