Cargando…
Prediction of Maize Single Cross Hybrids Using the Total Effects of Associated Markers Approach Assessed by Cross-Validation and Regional Trials
The present study aimed to predict the performance of maize hybrids and assess whether the total effects of associated markers (TEAM) method can correctly predict hybrids using cross-validation and regional trials. The training was performed in 7 locations of Southern Brazil during the 2010/11 harve...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2014
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4106173/ https://www.ncbi.nlm.nih.gov/pubmed/25110752 http://dx.doi.org/10.1155/2014/924348 |
_version_ | 1782327485344514048 |
---|---|
author | Melo, Wagner Mateus Costa Pinho, Renzo Garcia Von Balestre, Marcio |
author_facet | Melo, Wagner Mateus Costa Pinho, Renzo Garcia Von Balestre, Marcio |
author_sort | Melo, Wagner Mateus Costa |
collection | PubMed |
description | The present study aimed to predict the performance of maize hybrids and assess whether the total effects of associated markers (TEAM) method can correctly predict hybrids using cross-validation and regional trials. The training was performed in 7 locations of Southern Brazil during the 2010/11 harvest. The regional assays were conducted in 6 different South Brazilian locations during the 2011/12 harvest. In the training trial, 51 lines from different backgrounds were used to create 58 single cross hybrids. Seventy-nine microsatellite markers were used to genotype these 51 lines. In the cross-validation method the predictive accuracy ranged from 0.10 to 0.96, depending on the sample size. Furthermore, the accuracy was 0.30 when the values of hybrids that were not used in the training population (119) were predicted for the regional assays. Regarding selective loss, the TEAM method correctly predicted 50% of the hybrids selected in the regional assays. There was also loss in only 33% of cases; that is, only 33% of the materials predicted to be good in training trial were considered to be bad in regional assays. Our results show that the predictive validation of different crop conditions is possible, and the cross-validation results strikingly represented the field performance. |
format | Online Article Text |
id | pubmed-4106173 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-41061732014-08-10 Prediction of Maize Single Cross Hybrids Using the Total Effects of Associated Markers Approach Assessed by Cross-Validation and Regional Trials Melo, Wagner Mateus Costa Pinho, Renzo Garcia Von Balestre, Marcio ScientificWorldJournal Research Article The present study aimed to predict the performance of maize hybrids and assess whether the total effects of associated markers (TEAM) method can correctly predict hybrids using cross-validation and regional trials. The training was performed in 7 locations of Southern Brazil during the 2010/11 harvest. The regional assays were conducted in 6 different South Brazilian locations during the 2011/12 harvest. In the training trial, 51 lines from different backgrounds were used to create 58 single cross hybrids. Seventy-nine microsatellite markers were used to genotype these 51 lines. In the cross-validation method the predictive accuracy ranged from 0.10 to 0.96, depending on the sample size. Furthermore, the accuracy was 0.30 when the values of hybrids that were not used in the training population (119) were predicted for the regional assays. Regarding selective loss, the TEAM method correctly predicted 50% of the hybrids selected in the regional assays. There was also loss in only 33% of cases; that is, only 33% of the materials predicted to be good in training trial were considered to be bad in regional assays. Our results show that the predictive validation of different crop conditions is possible, and the cross-validation results strikingly represented the field performance. Hindawi Publishing Corporation 2014 2014-07-03 /pmc/articles/PMC4106173/ /pubmed/25110752 http://dx.doi.org/10.1155/2014/924348 Text en Copyright © 2014 Wagner Mateus Costa Melo et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Melo, Wagner Mateus Costa Pinho, Renzo Garcia Von Balestre, Marcio Prediction of Maize Single Cross Hybrids Using the Total Effects of Associated Markers Approach Assessed by Cross-Validation and Regional Trials |
title | Prediction of Maize Single Cross Hybrids Using the Total Effects of Associated Markers Approach Assessed by Cross-Validation and Regional Trials |
title_full | Prediction of Maize Single Cross Hybrids Using the Total Effects of Associated Markers Approach Assessed by Cross-Validation and Regional Trials |
title_fullStr | Prediction of Maize Single Cross Hybrids Using the Total Effects of Associated Markers Approach Assessed by Cross-Validation and Regional Trials |
title_full_unstemmed | Prediction of Maize Single Cross Hybrids Using the Total Effects of Associated Markers Approach Assessed by Cross-Validation and Regional Trials |
title_short | Prediction of Maize Single Cross Hybrids Using the Total Effects of Associated Markers Approach Assessed by Cross-Validation and Regional Trials |
title_sort | prediction of maize single cross hybrids using the total effects of associated markers approach assessed by cross-validation and regional trials |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4106173/ https://www.ncbi.nlm.nih.gov/pubmed/25110752 http://dx.doi.org/10.1155/2014/924348 |
work_keys_str_mv | AT melowagnermateuscosta predictionofmaizesinglecrosshybridsusingthetotaleffectsofassociatedmarkersapproachassessedbycrossvalidationandregionaltrials AT pinhorenzogarciavon predictionofmaizesinglecrosshybridsusingthetotaleffectsofassociatedmarkersapproachassessedbycrossvalidationandregionaltrials AT balestremarcio predictionofmaizesinglecrosshybridsusingthetotaleffectsofassociatedmarkersapproachassessedbycrossvalidationandregionaltrials |