The development of precision agriculture and digitalisation has brought significant changes in agricultural technology and data-driven decision-making. Unmanned aerial vehicles (UAVs) and multispectral imaging technologies are effective tools for monitoring plant populations and detecting stress conditions (abiotic, biotic). Vegetation indices (NDVI, GNDVI, NDRE, LCI) provide detailed information about the physiological state of plants and the spatial distribution of stress factors. In the research conducted at the University of Debrecen, the ’MV Nádor’ winter wheat variety was examined in combinations of different tillage methods (autumn ploughing, strip tillage) and different nutrient supply treatments. During the multispectral data collection, high-resolution UAV images were used, which were analysed using the QGIS GIS software. The application of nutrients (nitrogen, phosphorus, potassium) and tillage methods had a significant impact on vegetation indices, which reflected the health status and homogeneity or heterogeneity of the plants. The results mean that higher nutrient levels showed more favorable growth and homogeneous plant stand. During the statistical analyses, we infer the spatial effects of stress factors based on the standard deviation and variance values. The values of NDVI and GNDVI indices showed an increasing trend with increasing nutrient levels, especially in the case of the 160 kg/ha nitrogen treatment, which ensures more uniform development. Based on the LCI and NDRE values, we obtained a much higher variance and SD value for the 160 kg N/ha treatment applied in autumn ploughing than for strip cultivation. Based on the data, precision technologies enable more sustainable and predictable crop production.