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| Main Author: | |
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| Format: | Artículo científico |
| Language: | en |
| Published: |
Universidade Estadual de Maringá
2017
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| Subjects: | |
| Online Access: | https://www.redalyc.org/articulo.oa?id=303050431007 https://www.redalyc.org/journal/3030/303050431007/ https://www.redalyc.org/journal/3030/303050431007/html/ https://www.redalyc.org/journal/3030/303050431007/303050431007.epub https://www.redalyc.org/journal/3030/303050431007/movil |
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Table of Contents:
- Prediction of genetic gains by selection indexes and REML/BLUP methodology in a population of sour passion fruit under recurrent selection Fernando Higino de Lima e Silva Alexandre Pio Viana Eileen Azevedo Santos Jôsie Cloviane de Oliveira Freitas Daniele Lima Rodrigues Antonio Teixeira do Amaral Júnior Agrociencias Mixed models Passiflora edulis Sims simultaneous selection predicted genotypic values Breeding programmes must be improved to accelerate the development of new cultivars due to the commercial importance of passion fruit. This study compared four selection indexes and the REML/BLUP methodology in an assessment of predicted genetic gains in the traits of interest. A total of 81 full-sib progenies derived from the third cycle of recurrent selection were assessed for one harvest in one environment. The experiment was arranged in a randomized complete block design with five plants per plot. The following traits were assessed: number of fruits, total yield, fruit mass, fruit longitudinal diameter, fruit transverse diameter, fruit pulp percentage, shell thickness and content of soluble solids. The Mulamba & Mock index produced the best results for the selection of progenies. The REML/BLUP method was the most efficient and selected progenies with predicted genetic gains better than the selection indexes tested. 2017 artículo científico 1679-9275 https://www.redalyc.org/articulo.oa?id=303050431007 https://www.redalyc.org/journal/3030/303050431007/ https://www.redalyc.org/journal/3030/303050431007/html/ https://www.redalyc.org/journal/3030/303050431007/303050431007.epub https://www.redalyc.org/journal/3030/303050431007/movil en http://www.redalyc.org/revista.oa?id=3030 Acta Scientiarum. Agronomy application/pdf Universidade Estadual de Maringá Acta Scientiarum. Agronomy (Brasil) Num.2 Vol.39