Detection of nitrogen stress of corn with aerial multi-spectral imaging by UAV

 One of the most important challenges that agriculture has encountered with, is the overusing of nitrogen fertilizers. Excessive use of these fertilizers, not only proliferate the costs of production and harm human health but also expand environmental pollution. Improving the efficiency of the nitrogen fertilizers depends on monitoring the plant nitrogen status at the different stages of plant growth and applying a sufficient amount of fertilizer at the right time and right place. Considering the necessity for diminishing the harm of nitrogen fertilizer overuse on human health, research was conducted to identify nitrogen stress in the maize field as a new approach for optimization of the use of those fertilizers by means of a new, fast and non-destructive aerial multispectral remote sensing technology via UAVs. The experiment was carried out on a maize field in a randomized complete block design in 4 replications of urea fertilizer in 4 treatments including 0% (witness), 50% (critical range), 100% (adequate range), and 150% (maximum or toxic range). Urea fertilizer was utilized with irrigation water in two growth stages, including the 8-leaf stage (V8) and tasseling appearance stage (VT). Multispectral aerial imaging was accomplished in both maize growth stages. In order to ground Sampling, 10 specimens of maize plants were randomly selected from each treatment in those plant growth stages. At first, the amount of chlorophyll was measured for each sample, next, the amount of nitrogen was delineated by the Kjeldahl method. After taking the images, they were processed. The vegetation indices including NDVI, NRI, MTVI2, CI, GM, which were related to plant chlorophyll amount and nitrogen content, were calculated. Data analysis for nitrogen concentration stress indicators, with leaf chlorophyll content, considering their variable relationships, was performed by the fitting regression models. Based on our research, CI (R^2=0.88) and NRI (R^2=0.90) index were the most appropriate indicators for detecting nitrogen stress in the V8 and VT growth stage of maize, respectively. According to our results, aerial multi-spectral remote sensing is capable of detecting the variability and stress of nitrogen fertilizers in the maize field.