Aerial imaging for early assessment of yield potential in maize

Autores

  • Barbara Nascimento Santos UFS
  • Nartênia Susane Costa Aragão UFS
  • Mikaely Rosendo dos Santos UFS
  • Tâmara Rebecca Albuquerque de Oliveira UFS
  • José Jairo Florentino Cordeiro Junior UFS
  • Gustavo Hugo Ferreira de Oliveira UFS

Palavras-chave:

High-throughput phenotyping, Plant breeding, unmanned aerial vehicles, Zea mays L.

Resumo

The use of unmanned aerial vehicles imagery has become an established practice in high-throughput phenotyping for predicting the yield potential of maize (Zea mays L.), although applying these technologies presents challenges due to regional specificities. This study aimed to assess the effectiveness of RGB (red, green, and blue) aerial imagery for the early identification of yield maize genotypes during the vegetative stage. Four genotypes were evaluated using a randomized block design with four replications. The experiment involved seven flights at two heights. Twenty-nine RGB vegetation indices were derived from image processing to discriminate genotypes based on plot-level grain yield. Nested models were fitted to predict temporal Best Linear Unbiased Predictions (BLUPs), with the most repeatable indices selected for analysis. Significant differences were observed among genotypes and plant spacing. The optimal flight timing was identified as 43 days after planting at a height of 80 meters. The indices MRCC, RmB, and RCC exhibited the highest repeatability and showed strong correlations with grain yield, demonstrating potential for RGB-based phenotyping studies. These findings highlight the utility of RGB imagery as a tool for early maize genotype selection, enhancing efficiency and accuracy in breeding programs and contributing to advancements in precision agriculture.

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Publicado

2025-12-12

Como Citar

Santos, B. N., Aragão, N. S. C., Santos, M. R. dos, Oliveira, T. R. A. de, Cordeiro Junior, J. J. F., & Oliveira, G. H. F. de. (2025). Aerial imaging for early assessment of yield potential in maize. Revista Ceres, 72, e72038. Recuperado de https://ojs.ceres.ufv.br/ceres/article/view/8221

Edição

v. 72 (2025)

Seção

PLANT BREEDING APPLIED TO AGRICULTURE

Licença

Creative Commons License
Este trabalho está licenciado sob uma licença Creative Commons Attribution 4.0 International License.