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Selection of Superior Inbred Progenies toward the Common Bean Ideotype
- Source :
- Agronomy Journal; March 2019, Vol. 111 Issue: 3 p1181-1189, 9p
- Publication Year :
- 2019
-
Abstract
- Partitioning of the progenies effect within populations has several advantages.FAI‐BLUP index capitalizes the progenies × growth seasons interaction.The selected inbreed progenies showed favorable genotypes for the target traits.Genetic breeding towards the common bean ideotype can accelerate the cultivar release. The goal of breeding programs is selection toward the ideal plant type. In this study, field experiments were performed to select common bean inbred progenies that maximize the probability of extracting superior lines. A total of 124 inbred progenies of three consecutive generations (F2:3, F2:4, and F2:5) were conducted in field experiments over three different environments (one generation in each environment). Seven different traits, related to disease severity, commercial acceptance grain, and yield, were evaluated by best linear unbiased prediction. This work underscored the importance of incorporating population information into the statistical model as a means of comparing progenies from different populations with higher efficacy, even when kinship information between populations is not available. Toward the common bean ideotype, 20 inbred progenies of greater potential were selected using the factor analysis and genotype‐ideotype distance (FAI‐BLUP) index. This index is based on the structural equation models by joining the factor analysis technique (exploratory factor analysis) with the ideotype design (confirmatory factor analysis). The predicted genetic gain was increased for all the traits in all generations. Selection strategies that capture the multitrait information capitalize the progenies × growth season interactions and are based on the ideotype, such as as the FAI‐BLUP index, have the potential for use in genetic breeding toward the common bean ideotype and can accelerate the release of more adapted cultivars.
Details
- Language :
- English
- ISSN :
- 00021962 and 14350645
- Volume :
- 111
- Issue :
- 3
- Database :
- Supplemental Index
- Journal :
- Agronomy Journal
- Publication Type :
- Periodical
- Accession number :
- ejs51846547
- Full Text :
- https://doi.org/10.2134/agronj2018.12.0761