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.

This study aimed to determine and analyze landscape ecology metrics to characterize the spatial pattern of fragments of native forest in São Mateus River basin, Espírito Santo State, Southeastern Brazil. Fragments were divided into four size classes called C1 (50 ha). Metrics were grouped according to their nature in (i) area and density, (ii) edge, (iii) shape, (iv) central area and (v) proximity. In total, 4,286 native forest fragments were identified, which represented 7.80% of total area of the basin. There is a predominance of fragments with more regular shapes, small (<25.10 ha) and, consequently, with greater edge effect. Results showed that the drainage basin studied is highly fragmented, which reinforces the need for strategies aimed at forest conservation and restoration of degraded forests in this region.