Banca de QUALIFICAÇÃO: CÉSAR PEDRO

Uma banca de QUALIFICAÇÃO de DOUTORADO foi cadastrada pelo programa.
DISCENTE: CÉSAR PEDRO
DATA: 08/05/2024
HORA: 14:00
LOCAL: Anfiteatro 02 Departamento de Biologia
TÍTULO:

Machine learning and biometric models applications for selecting high-performance interpopulation corn lines

PALAVRAS-CHAVES:

Zeas mays; conditional inference tree; genetic variability, stability.

PÁGINAS: 20
GRANDE ÁREA: Ciências Agrárias
ÁREA: Agronomia
SUBÁREA: Fitotecnia
ESPECIALIDADE: Melhoramento Vegetal
RESUMO:

A valuable source of genetic variability resides in commercially available maize hybrids. The study aims to test the effectiveness of combining CIT with conventional biometric methods in revealing the magnitude of genetic variability and patterns of relationships among traits of interpopulation lines derived from transgenic corn hybrids. Grain yield and prolificacy traits were evaluated across six corn populations in two environments in Lavras (CDCTA/UFLA and Queixada Farm). The experimental design was randomized complete blocks, and analyses were conducted by combining Conditional Inference Tree (CIT) with traditional biometric methods. CIT highlighted grain yield as a central factor for characterizing population variability across diverse environments, indicating a pattern of relationship with prolificacy that suggests high-yield lines. Biometric analysis revealed genetic variability within populations, associated with high-yielding performance, stability, and significant genetic gains. In all studied scenarios, populations PA and PC stood out. The combination of machine learning and biometric approaches proved effective in identifying line patterns in maize populations with desired traits, revealing the use of transgenic maize hybrids as a potential source of genetic variability for extracting superior lines for corn breeding programs.

MEMBROS DA BANCA:
Interno - VINICIUS QUINTAO CARNEIRO (Suplente)
Interno - TIAGO DE SOUZA MARCAL (Suplente)
Externo ao Programa - JOSE MARIA VILLELA PADUA - DAG/ESAL (Membro)
Interno - JOSE AIRTON RODRIGUES NUNES (Membro)
Presidente - JOAO CANDIDO DE SOUZA (Membro)
Interno - FLAVIA MARIA AVELAR GONCALVES (Membro)