Utilization of an Aerial Platform to Guide Replant Decisions.

Stand counts are commonly used to determine plant population across a given area. These measurements are important since population is one of the primary parameters utilized to determine if a marginal stand is present and if a replant is necessary. This method consists of measuring a selected linear distance of plant row, counting the number of plants within this selected distance, and repeating the counts in a few locations to estimate plant population for a given field. However, this approach is reliant upon a highly uniform plant population across the entire field and can be influenced by human bias (possible preference to higher or lower stands). One proposed use of unmanned aerial systems (UAS) is to produce quantitative data to support replant decisions by assessing plant stands.  Theoretically, an aerial approach could provide spatially dense information on plant populations across large areas quickly and remove human bias.  Therefore, the objectives of this research were: (1) to investigate the ability of a UAS system to accurately and precisely determine varying plant populations of cotton (Gossypum hirsutum, L.) stands and (2) to determine which vegetative indices/ratios correlate most strongly to actual plant populations.  A field study was planted in Grand Junction, TN on May 10^th, 2016.  Treatments were replicated four times and included seeding rates of 118970, 33990, 17000, and 8500 per hectare in order to produce a range of plant populations. After emergence, cotton plant stands were manually counted and images were obtained from two cameras mounted beneath a quad-copter UAS flying at an altitude of 30 m. Red, green, blue, near-infrared, and red edge spectral band images were collected from the two respective cameras and processed using Fiji (University of Wisconsin-Madison LOCI, Madison, WS). After processing, an automated and manual count of plants within each image were conducted within ImageJ (National Institute of Health, Bethesda, MD), and compared to actual plant populations. Based on initial results, the utilization of UAS aerial imagery may be a sufficient tool to improve accuracy and efficiency of plant stand assessment over current methods.