Monitoring of maize cultivation with the aid of precision agriculture techniques

Vegetation indices derived from visible spectrum wavelengths (red, green, blue – RGB) have become increasingly important in agriculture for monitoring crop development. This study evaluates the potential of the Green Leaf Index (GLI) and the Visible Atmospherically Resistant Index (VARI) for monitoring corn crops under precision agriculture. A field experiment was conducted in 2020 using both the Conventional Planting System (CPS) and No-Tillage System (NTS), arranged in strips with three replications. Aerial images were captured using remotely piloted aircraft systems (RPAS) equipped with RGB sensors, and ground control points were collected with L1/L2 geodetic receivers in RTK mode. Georeferenced orthomosaics were generated to calculate GLI and VARI at different corn growth stages (V2, V5, V8, VT, R1, R3, R5). The indices were analyzed through Pearson’s correlation with agronomic traits including ear height, stem diameter, SPAD index, leaf nitrogen content, ear weight, and plant biomass. Results confirmed the potential of GLI and VARI, together with RPAS and geodetic receivers, for monitoring corn growth under CPS and NTS.