Use of an unmanned aerial vehicle as an alternative to assess the nutritional status of the cotton crop

Abstract

The use of unmanned aerial vehicles in photogrammetric studies allows obtaining spatial data in short periods of time and with high spatial resolution. In the research, multispectral images were processed for the study of nutritional conditions of the cotton crop (Gossypium hirsutum). An experimental design of the crop was developed, with different doses and nitrogen sources, in a factorial arrangement with 16 treatments and 4 repetitions in plots completely distributed at random. The EBEE SQ agricultural drone, equipped with the Parrot Sequoia camera, was used and a photogrammetric flight was planned, with the Emoticon AG software, which was synchronized with the drone to establish the flight parameters and capture the reflectance information of the visible spectrum, infrared and red border. The captured images were processed with the PIX4D Mapper software to generate the orthophoto and the 4 spectral bands used in the calculation of the chlorophyll index. Using map algebra tools from ArcGIS software on the results obtained, an analysis of variance was performed with the ANOVA model. With the calculated indices it was possible to show differences in the vigor of the crop depending on the treatments. The analysis of the results showed significant differences in the spectral response of the cotton crop fertilized with different sources (urea, pine nut cake, hen manure and bovine manure) and nitrogen doses (50, 100, 150 and 200 N kg.ha-1). Urea treatment at the 150 dose of N kg.ha-1 showed the best spectral response.