Potentiality of Multispectral Vegetation Indexes for Evaluating the Influence of the Sowing Technique on Durum Wheat Cultivation Density

Crop monitoring using multispectral sensors on board drones is a significant application in the agricultural sector. These sensors capture high-resolution images that can be used to assess crop vigor and health by calculating spectral indices. This enables a quick identification of areas with developmental issues due to biotic or abiotic stresses, facilitating precision agriculture strategies. This study focuses on monitoring the greenness of durum wheat cultivation (Sicily, Italy) from stem elongation to inflorescence emergence, comparing two sowing techniques: conventional (CS) and sod-seeding (SS). Five flight campaigns were conducted using a multispectral sensor mounted on a DJI quadcopter drone. Normalized Difference Vegetation Index (NDVI) and Normalized Difference Red Edge Index (NDRE) were calculated using ArcGIS, assessing potential differences among the sowing techniques. Preliminary results indicate that both vegetation indexes revealed significant differences among sowing techniques, with CS having generally significantly higher values than SS. Both sowing techniques exhibited similar standard deviation values, suggesting their equal effectiveness in durum wheat cultivation. Discrepancies between NDVI and NDRE were observed at high vegetation index values, highlighting the main limitation of NDVI, saturating at high crop development stages. This saturation was not observed in NDRE, becoming an alternative to NDVI when working with high biomass crops.