NJD Vilela, MAJ. Ferraz*, AT Bruzi, GLD. Vilela and GAS Ferraz
Published September 23, 2024
Genet. Mol. Res. 23 (3): gmr2380
DOI http://dx.doi.org/10.4238/gmr2380
About the Authors
NJD Vilela, MAJ. Ferraz*, AT Bruzi, GLD. Vilela and GAS Ferraz
Corresponding author:
Marcelo Araújo Junqueira Ferraz
E-mail: marcelo.ferraz1@estudante.ufla.br
ABSTRACT
Red‒green–blue (RGB) and multispectral remote sensing sensors onboard unmanned aerial vehicles (UAVs), which are nondestructive, economical and flexible tools, have been widely adopted in crop monitoring and management, especially for efficient monitoring and identification of foliar diseases in soybean crops. The objective of this study was to establish correlations between vegetation indices obtained by UAVs and the yield grain and Asian soybean rust and powdery mildew severity in soybean crops under tropical conditions. Six commercial soybean cultivars with INOX® technology (TMG 7060 IPRO, TMG 7063 IPRO, TMG 7262 RR, TMG 7062 IPRO, TMG 7363 RR, and TMG 7067 IPRO), one multiline cultivar (a mixture of lines) and one susceptible control cultivar for Asian soybean rust and powdery mildew (M6410 IPRO) were evaluated. The experiments were performed in Lavras, Ijaci and Nazareno in the state of Minas Gerais during the 2020/21 season. The experimental design encompassed randomized complete blocks, with treatments split into subdivided bands (four fungicide application treatments and seven cultivar treatments + one multiline treatment) in three replications. The fungicide applications were assigned to the main plots, while the cultivars were assigned to the subplots. Aerial images were collected by a DJI Mavic Pro equipped with an RGB sensor and a DJI Matrice 100 equipped with a Parrot Sequoia multispectral sensor. The traits evaluated included Asian soybean rust severity, powdery mildew severity, defoliation index, grain yield, normalized difference vegetation index (NDVI) and modified chlorophyll uptake ratio index (MPRI). Joint analyses (multienvironment) and analyses of the subdivided plots over time were conducted. The NDVI (ρ = 0,62) and MPRI (ρ = 0,76) exhibited significant correlations, facilitating the use of RGB and multispectral imaging in high-throughput phenotyping to assess the soybean grain yield in high-altitude tropical climates. Like the variable disease severity, whose NDVI and MPRI indices showed a correlation with the severity of Asian rust (ρ = – 0.95) and powdery mildew (ρ = -0.47), respectively.
Key words: Aerial images; Genotype × Environment interaction; Erysiphe difusa; Phakopsora pachyrhizi; Multispectral images.