| dc.creator | Brasileiro, Bruno Portela | |
| dc.creator | Peternelli, Luiz Alexandre | |
| dc.creator | Silveira, Luís Cláudio Inácio da | |
| dc.creator | Barbosa, Márcio Henrique Pereira | |
| dc.date | 2019-07-23T13:42:16Z | |
| dc.date | 2019-07-23T13:42:16Z | |
| dc.date | 2016-07 | |
| dc.date.accessioned | 2023-09-27T22:18:03Z | |
| dc.date.available | 2023-09-27T22:18:03Z | |
| dc.identifier | 1807-8621 | |
| dc.identifier | http://dx.doi.org/10.4025/actasciagron.v38i3.28424 | |
| dc.identifier | http://locus.ufv.br//handle/123456789/26312 | |
| dc.identifier.uri | https://repositorioslatinoamericanos.uchile.cl/handle/2250/8973345 | |
| dc.description | 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. | |
| dc.description | O objetivo desse trabalho foi avaliar a importância dos caracteres agronômicos durante o processo de seleção individual em cana-de-açúcar, além de avaliar o potencial do uso da regressão logística e da árvore de decisão na identificação dos melhores genótipos. Foram avaliados 7.719 seedlings na primeira fase de teste (T1) e 659 clones na segunda fase de teste (T2). Os caracteres número de colmos, saliência da gema e comprimento do entre-nó foram os de maior importância no processo de seleção massal realizado no T1. Vigor da planta, diâmetro de colmo e altura de colmo foram os mais importantes na seleção do T2. Pelo método massal foram selecionados 174 indivíduos no T1 e 113 no T2, enquanto a regressão logística selecionou 153 indivíduos no T1 e 79 no T2. A taxa de erro aparente dos modelos logísticos ajustados para as seleções no T1 e T2 foram de 0,8 e 5,10%, respectivamente. Com o uso da árvore de decisão foram selecionados 67 clones dentre os mais produtivos na fase T2. A elaboração de árvores de decisão apresenta grande aplicabilidade na identificação de clones potenciais nas fases iniciais dos programas de melhoramento genético da cana-de-açúcar. | |
| dc.format | pdf | |
| dc.format | application/pdf | |
| dc.language | eng | |
| dc.publisher | Acta Scientiarum. Agronomy | |
| dc.relation | v. 38, n. 3, p. 289- 297, jul.- set. 2016 | |
| dc.rights | Open Access | |
| dc.subject | Saccharum spp. | |
| dc.subject | Decision tree | |
| dc.subject | Crop breeding | |
| dc.subject | Árvore de decisão | |
| dc.subject | Melhoramento genético | |
| dc.title | Importance of agronomic traits in the individual selection process of sugarcane as determined using logistic regression | |
| dc.type | Artigo | |
