Spatial averaging to the scale of the harvester also made little difference in the total information content of NDVI fit using Beta distributions as quantified using the Kullback-Leibler divergence. The variance in NDVI observations was “averaged out” at larger pixel sizes but only ~ 20% of the total variance was averaged out at the spatial scale of the harvester on some measurement dates. We sought to understand the optimal spatial scale for interpreting UAV observations given that the ~ 10 cm pixels yielded more than 12 million measurements at far finer resolution than the 12 m scale of the harvester. A multiple linear model using information from four (three) UAV flyovers was selected as the most parsimonious and predicted 26% (40%) of the variability in wheat yield (GPC). Landsat observations were poorly related to yield and GPC measurements. We measured yield and GPC in a winter wheat field in Sun River, Montana, USA, and tested the ability of normalized difference vegetation index (NDVI) measurements from an unoccupied aerial vehicle (UAV) on spatial scales of ~10 cm and from Landsat on spatial scales of 30 m to predict them. The price offered to producers depends not only on yield but also grain protein content (GPC), which are often negatively related at the field scale but can positively covary depending in part on management strategies, emphasizing the need to understand their variability within individual fields. Wheat is a staple crop that is critical for feeding a hungry and growing planet, but its nutritive value has declined as global temperatures have warmed. It is recommended that the confident deposition results, measurement methods and sampling approaches must be standardized for UAV sprayers according to the field conditions and controlled within artificial assessments. It can be concluded that variation in recorded depositing is due to the sampling material. The results also showed the water sensitive paper recorded an 80.3% higher deposition than that of the glass strip at zero position during the driving flight height 2 m and flight speed 2 ms−1 (T1 treatment). The results showed that the water-sensitive paper recorded the droplet deposition in the target zone with a range from 0.049 to 4.866 µLcm−2, whereas the glass strip recorded from 0.11 to 0.793 µLcm−2. The results showed a variation in the estimation of the spray deposits among the two applied sampling methods. In this study, two sampling approaches (water-sensitive paper, and glass strip collectors) were compared to analyze spray deposition in target and off-target zones. There are various approaches available for sampling spray deposition and drift, during the evaluation of ground sprayers used for the UAV sprayer assessment, under field conditions. A decisive stage in the measurement of spray deposition and drift is selecting an appropriate sampling approach under field conditions. Target and off-target spray depositions determine the spray’s effectiveness and impact on the environment.
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