Investigating the Potential of a Newly Developed UAV-Mounted VNIR/SWIR Imaging System for Monitoring Crop Traits—A Case Study for Winter Wheat

UAV-based multispectral multi-camera systems are widely used in scientific research for non-destructive crop traits estimation to optimize agricultural management decisions. These typically provide data from the visible and near-infrared (VNIR) domain. However, several key absorption features related biomass nitrogen (N) located short-wave infrared (SWIR) Therefore, this study investigates a novel system prototype that addresses spectral gap with sensitivity 600 1700 nm by implementing dedicated bandpass filter combinations derive application-specific vegetation indices (VIs). In study, two VIs, GnyLi NRI, were applied using obtained on single observation date at winter wheat field experiment Germany. Ground truth destructively sampled entire growing season. Likewise, heights derived RGB image an improved approach developed within study. Based these variables, regression models estimate fresh dry biomass, moisture, N concentration, uptake. The relationships between NIR/SWIR-based VIs estimated successfully evaluated (R2: 0.57 0.66). Both further validated against ground 0.75 0.84). results indicate imaging system’s potential monitoring applications, but multitemporal validations needed.