Banca de QUALIFICAÇÃO: EWERTON LÉLYS RESENDE

Uma banca de QUALIFICAÇÃO de DOUTORADO foi cadastrada pelo programa.
DISCENTE: EWERTON LÉLYS RESENDE
DATA: 17/02/2022
HORA: 16:00
LOCAL: Google meet https://meet.google.com/khj-vvrp-vdy
TÍTULO:

EAR AND PLANT HIGH-THROUGHPUT PHENOTYPING: APPLICATION TO MAIZE BREEDING

PALAVRAS-CHAVES:

Aerial sensing; corn; Zea mays; crop phenotyping;

PÁGINAS: 16
GRANDE ÁREA: Ciências Agrárias
ÁREA: Agronomia
RESUMO:

Traditionally, field phenotypic traits have been obtained manually, which is laborious, non-automatic, and timeconsuming, limiting the number of measurable phenotypic traits. New technologies come to help with it.

Therefore, in this study, the goal was to estimate the correlation between vegetation index with grain yield and
determine the best period and optimal VIs for corn grain yield prediction and also to measure corn ear traits by
photographic quantification and correlate these traits to corn grain yield. Ten corn hybrids from two Reciprocal
Recurrent Selection (RRS) programs from the Federal University of Lavras – UFLA (AB and CD) were evaluated in
randomized complete blocks with three replications and three sites. Vegetation index and green leaves area was
estimated in different vegetative and reproductive growth stages using an unmanned aerial vehicle (UAV) to
correlated with grain yield. Furthermore, corn ear photographic was taken to estimate: length (L), width (W), and
the number total of grains (NTG) and compare it to manual measurement. The trails presented considerable
experimental quality in all locations where accuracy ranged from 79.07% to 95.94%. The UAV flights at the
begging of the growing crop cycle show a positive correlation of the index with yield. Regarding corn ear
phenotyping the regression coefficient (R²) for width was 0.92, for length was 0.88, and for (NTG) 0.62 showing
great association with the measurements. In conclusion, the best time for image collecting varied from location
and population, but in general, the initial crop cycle shows a positive correlation with yield. Ear phenotyping based
on digital images represents a promising alternative to measure corn yield components. This technique provided
greater efficiency and high correlation to manual evaluations.

MEMBROS DA BANCA:
Externo ao Programa - ADAO FELIPE DOS SANTOS - DAG/ESAL (Suplente)
Presidente - ADRIANO TEODORO BRUZI (Membro)
Externo à Instituição - CARLOS EDUARDO PULCINELLI - AOI (Membro)
Interno - JOSE AIRTON RODRIGUES NUNES (Suplente)
Interno - VINICIUS QUINTAO CARNEIRO (Membro)