TY - JOUR
T1 - Nitrogen fertilizer recommendation for waxy corn measured by canopy reflectance using UAV imaging passive sensor
AU - Jermthaisong, P.
AU - Kingpaiboon, S.
AU - Chawakitchareon, P.
AU - Kiyoki, Y.
N1 - Funding Information:
This research project was supported financially by the Agricultural Research Development Agency (Public Organization) or “ARDA”. I would like to sincerely thank the ARDA as well as the Graduate School, Khon Kaen University for the funding and support. I would also like to extend my gratitude to the Department of Agricultural Engineering, Khon Kaen University for providing information and allowing me to use research facilities. Lastly, I sincerely thank you to waxy corn small-holder farmers for their kind support in the process of research
Publisher Copyright:
© Geoinformatics International.
PY - 2020
Y1 - 2020
N2 - 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.
AB - 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.
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M3 - Article
AN - SCOPUS:85092397200
SN - 1686-6576
VL - 16
SP - 73
EP - 86
JO - International Journal of Geoinformatics
JF - International Journal of Geoinformatics
IS - 3
ER -
