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Research Article Indices estimated using REML/BLUP and introduction of a super-trait for the selection of progenies in popcorn
- Source :
- Genetics and Molecular Research. 16
- Publication Year :
- 2017
- Publisher :
- Genetics and Molecular Research, 2017.
-
Abstract
- Selection indices commonly utilize economic weights, which become arbitrary genetic gains. In popcorn, this is even more evident due to the negative correlation between the main characteristics of economic importance - grain yield and popping expansion. As an option in the use of classical biometrics as a selection index, the optimal procedure restricted maximum likelihood/best linear unbiased predictor (REML/BLUP) allows the simultaneous estimation of genetic parameters and the prediction of genotypic values. Based on the mixed model methodology, the objective of this study was to investigate the comparative efficiency of eight selection indices estimated by REML/BLUP for the effective selection of superior popcorn families in the eighth intrapopulation recurrent selection cycle. We also investigated the efficiency of the inclusion of the variable “expanded popcorn volume per hectare” in the most advantageous selection of superior progenies. In total, 200 full-sib families were evaluated in two different areas in the North and Northwest regions of the State of Rio de Janeiro, Brazil. The REML/BLUP procedure resulted in higher estimated gains than those obtained with classical biometric selection index methodologies and should be incorporated into the selection of progenies. The following indices resulted in higher gains in the characteristics of greatest economic importance: the classical selection index/values attributed by trial, via REML/BLUP, and the greatest genotypic values/expanded popcorn volume per hectare, via REML. The expanded popcorn volume per hectare characteristic enabled satisfactory gains in grain yield and popping expansion; this characteristic should be considered super-trait in popcorn breeding programs.
- Subjects :
- 0106 biological sciences
Mixed model
Restricted maximum likelihood
04 agricultural and veterinary sciences
General Medicine
Best linear unbiased prediction
Selective breeding
01 natural sciences
Statistics
040103 agronomy & agriculture
Genetics
Trait
0401 agriculture, forestry, and fisheries
Plant breeding
Molecular Biology
Hectare
Selection (genetic algorithm)
010606 plant biology & botany
Mathematics
Subjects
Details
- ISSN :
- 16765680
- Volume :
- 16
- Database :
- OpenAIRE
- Journal :
- Genetics and Molecular Research
- Accession number :
- edsair.doi...........68b02e8719e62f2962a607917301c179