Title: Parental selection for high heterosis in sorghum [Sorghum bicolor (L.) Moench]–Combining ability, heterosis and their inter-relationships
Abstract: Combining ability analysis is routinely used to identify the best combiners among
a group of genotypes and superior hybrid combinations along with type of gene action
controlling the expression of a quantitative trait. Eighty-four sorghum hybrids generated
by crossing seven cytoplasmic male sterile lines and 12 fertility restorers in Line ×
Tester fashion were evaluated for grain yield and related traits in a replicated trial along
with standard checks. Significant heterosis values were observed for all the traits studied,
and hybrids displayed up to 139% grain yield advantage over better parent and 76% over
standard check. Variances due to general combining ability (gca) and specific combining
ability (sca) were significant for days to flowering, panicle length and grain yield indicating
role of both additive and non-additive gene action, while plant height and 100-seed
weight were completely under additive genetic control. For grain yield 27B, RS 673 and
CB 33 were good combiners, while for panicle length 27B, 296B, 2077B, RS 673 and
Indore 12 were good combiners among parents. Analysis of combining ability status
indicated that combinations of parents with non-significant gca can also result in hybrids
with significant sca as well as heterosis for grain yield and other traits. Significant
correlations were found between per se performance of hybrids and sca, per se performance
and heterosis, and sca of hybrids and heterosis. The study demonstrates that superior
hybrid combinations can be identified through appropriate field evaluation, and estimation
of combining ability as a tool to identify suitable parents among a set of genotypes has
to be relooked at.
Publication Year: 2012
Publication Date: 2012-01-01
Language: en
Type: article
Access and Citation
Cited By Count: 3
AI Researcher Chatbot
Get quick answers to your questions about the article from our AI researcher chatbot