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- Title
Utilizing Visible Band Vegetation Indices from Unmanned Aerial Vehicle Images for Maize Phenotyping.
- Authors
Coswosk, Guilherme Gonçalves; Gonçalves, Vivane Mirian Lanhellas; de Lima, Valter Jário; de Souza, Guilherme Augusto Rodrigues; Teixeira do Amaral Junior, Antônio; Pereira, Messias Gonzaga; de Oliveira, Evandro Chaves; Leite, Jhean Torres; Kamphorst, Samuel Henrique; de Oliveira, Uéliton Alves; Crevelari, Jocarla Ambrosim; dos Santos, Késia Dias; Marques, Frederico César Ribeiro; Campostrini, Eliemar
- Abstract
Recent advancements in high-throughput phenotyping have led to the use of drones with RGB sensors for evaluating plant traits. This study explored the relationships between vegetation indices (VIs) with grain yield and morphoagronomic and physiological traits in maize genotypes. Eight maize hybrids, including those from the UENF breeding program and commercial varieties, were evaluated using a randomized block design with four replications. VIs were obtained at various stages using drones and Pix4D Mapper 4.7.5 software. Analysis revealed significant differences in morphoagronomic traits and photosynthetic capacity. At 119 days after planting (DAP), the RGB vegetation index VARI showed a significant correlation (r = 0.99) with grain yield. VARI also correlated with female flowering (r = −0.87), plant height (r = −0.79), 100-grain weight (r = −0.77), and anthocyanin concentration (r = −0.86). PCA showed a clear separation between local and commercial hybrids, explaining 46.7% of variance at 91 DAP, 52.3% at 98 DAP, 64.2% at 112 DAP, and 66.1% at 119 DAP. This study highlights the utility of VIs in maize phenotyping and genotype selection during advanced reproductive stages.
- Subjects
AGRICULTURAL remote sensing; PRECISION farming; DRONE aircraft; GRAIN yields; BLOCK designs
- Publication
Remote Sensing, 2024, Vol 16, Issue 16, p3015
- ISSN
2072-4292
- Publication type
Article
- DOI
10.3390/rs16163015