| Registro completo |
| Provedor de dados: |
Agronomy
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| País: |
Brazil
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| Título: |
Importance of agronomic traits in the individual selection process in sugarcane determined using the logistic regression
Importance of agronomic traits in the individual selection process of sugarcane as determined using logistic regression
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| Autores: |
Brasileiro, Bruno Portela
Peternelli, Luiz Alexandre
Silveira, Luís Cláudio Inácio
Barbosa, Márcio Henrique Pereira
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| Data: |
2016-06-24
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| Ano: |
2016
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| Palavras-chave: |
Saccharum spp.
Decision tree
Crop breeding
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| Resumo: |
The aim of this study was to evaluate the relative importance of agronomic traits during the individual selection in sugarcane (Saccharum spp.), as well as evaluate the potential for using logistic regression and decision trees in identifying the best genotypes. A total of 7,719 seedlings of 128 half-sib families were evaluated in the first test phase (T1) and 659 clones were selected for the second (T2). Logistic regression was applied in both populations (T1 and T2). The number of stalks, bud prominence and length of the internode were the most important traits in selection the T1. Plant vigour, stalk diameter and stalk height were the most important traits in selection the T2. There were 174 individuals selected by the mass selection method in T1 and 113 individuals in T2, while logistic regression selected 153 individuals in T1 and 79 in T2. The apparent error rates of the logistic models fitted to the selections in T1 and T2 were 0.8 and 5.10%, respectively. By using a decision tree, 67 clones were selected among the most productive ones in phase T2. The formulation of decision trees is therefore highly applicable to identifying potential clones in the initial phases of genetic breeding programs.
The aim of this study was to evaluate the importance of agronomic traits during the selection of sugarcane (Saccharum spp.), as well as to evaluate the potential for using logistic regression and decision trees to identify the best genotypes. A total of 7,719 seedlings of 128 half-sib families were evaluated during the first test phase (T1), and 659 clones were selected for the second (T2). Logistic regression was applied to both populations. The number of stalks, bud prominence and length of the internode were the most important selection traits in the T1 population. The plant vigor, stalk diameter and stalk height were the most important selection traits in the T2 population. There were 174 individuals selected when using the mass selection method in T1 and 113 individuals in T2, whereas a logistic regression selected 153 individuals in T1 and 79 in T2. The apparent error rates of the logistic models fitted to the selections in T1 and T2 were 0.8 and 5.10%, respectively. By using a decision tree, 67 clones were selected among the most productive ones in phase T2. Therefore, the formulation of decision trees is highly applicable to identifying potential clones during the initial phases of breeding programs.
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| Tipo: |
Info:eu-repo/semantics/article
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| Idioma: |
Inglês
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| Identificador: |
http://periodicos.uem.br/ojs/index.php/ActaSciAgron/article/view/28424
10.4025/actasciagron.v38i3.28424
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| Editor: |
Universidade Estadual de Maringá
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| Relação: |
http://periodicos.uem.br/ojs/index.php/ActaSciAgron/article/view/28424/pdf
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| Formato: |
application/pdf
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| Fonte: |
Acta Scientiarum. Agronomy; v. 38, n. 3 (2016); 289-297
Acta Scientiarum. Agronomy; v. 38, n. 3 (2016); 289-297
1807-8621
1679-9275
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