Nitrogen (N) is one of the main factors to increasing corn yield. Past research showed that N fertilizer application rates were strongly related to corn yield. The objective of this study was to estimate N fertilizer recommendations with EONR for waxy corn (Zea mays var. ceratina) using NDVI derived from canopy reflectance and images taken by a multispectral camera as a passive sensor mounted on unmanned aerial vehicle (UAV). Three site-years experiments were conducted during two consecutive dry seasons in 2017/18 and 2018/19 at Ban Nong Bua, Nong Bua District, Khon Kaen, Thailand. The experiments were laid out according to randomized complete block design (RCBD) with two replications. Treatments consisted of nine N rates in all site-years; 0, 50, 56.25, 112.50, 125, 168.75, 200, 225 and 281.25 kg N ha-1. The EONR and N fertilizer rates were determined by fitting quadratic plateau regression models for each whole plot treatment at each site. The relationship between relative NDVI and temporal data of EONR was evaluated to provide N fertilizer recommendation. The EONR was strongly related to relative NDVI (R2= 0.7492). The result presented here suggests that the reflectance data collected with the camera as a passive sensor mounted on UAV has the potential to be a useful tool for N fertilizer recommendation for waxy corn under a variety of management systems and conditions found in Northeastern Thailand.
|Number of pages||14|
|Journal||International Journal of Geoinformatics|
|Publication status||Published - 2020|
ASJC Scopus subject areas
- Geography, Planning and Development
- Earth and Planetary Sciences (miscellaneous)