In this research, the authors sought solutions to one of the most important challenges facing agriculture. The growth of the world's population and the decline and degradation of arable land pose new challenges for agriculture. Cereal crops play a key role in food production, with maize being of particular importance as it is grown worldwide. Precision farming is playing an increasingly important role in modern agriculture, making remote sensing and data analysis of paramount importance.
The weather conditions in 2024 were unusual: spring was rainy and warm, while the summer months were exceptionally hot with an above-average number of heat days. The experiments were conducted during four different phenological stages of corn development (V5, V10, R1, and R3). Outside the growing season, we used three types of flight settings: measurements without RTK, with RTK, and with a combination of RTK and altitude tracking. During the study, three hybrids with different FAO numbers were analyzed, and the results were evaluated at five different nutrient levels in addition to the control.
It was observed that in the early (V5 and V10) phenological phases, there was a closer correlation between NDVI values and crop yield, which can be explained by the favorable spring and early summer weather conditions of the year. The flight settings showed similar results at three measurement times, but differences appeared in the R1 phenological phase. It can be assumed that the large amount of pollen deposited on the leaves during flowering influenced the NDVI values. In addition, the creation of orthomosaics from RTK and altitude tracking images proved to be more time-consuming and, in some cases, required multiple attempts with the WebODM software used. These results provided valuable data and serve as a good starting point for further research.