Using an Unmanned Aerial System to Collect Mid-Season Multispectral Data for Estimation of Plant Nitrogen Status in Cotton

Managing nitrogen (N) in cotton is critical for optimizing the ratio of vegetative and reproductive growth throughout the growing season, which maximizes the subsequent yield. At the field level, spatial variability of soil texture can lead to varying levels of nutrient uptake by the cotton crop. Unmanned Aerial Systems (UASs) have the ability to provide quick and efficient ways to detect spatial variability of N status to aid making in-season management decisions. This study was conducted during 2017 and 2018 on a research site in Tifton, GA. The main objective of the study was to correlate varying levels of plant tissue nitrogen (N) obtained from cotton tissue samples with vegetative indices (VIs) generated from multispectral imagery acquired with an UAS. Six N treatments consisting of 0, 34, 67, 101, 135 and 168 kg/ha rates were applied to attain varied levels of N in the tissue samples. Tissue samples were collected during the first, third, fifth, and seventh weeks of bloom to quantify N tissue levels temporally as a response to the applied N rate. Leaf blade and petiole tissue samples were collected and separated such that analyses provided leaf blade N (%) and petiole N (ppm). Multispectral imagery in the wavelengths of 550 nm (green), 660 nm (red), 735 nm (red-edge) and 790 nm (near infrared) was acquired during the cotton growth stages at the same time the tissue samples were collected by utilizing a commercially available quadcopter equipped with a high-resolution multispectral camera. Two vegetative indices (NDVI and NDRE) were analyzed for correlation with leaf blade and petiole tissue N levels at each sampling date and tracked temporally. Regression equations correlating the VIs to actual N levels were generated to evaluate the use of different VIs for accurately measuring N levels in the crop at the selected growth stages.