AUTHOR=Lu Ning , Wang Wenhui , Zhang Qiaofeng , Li Dong , Yao Xia , Tian Yongchao , Zhu Yan , Cao Weixing , Baret Fred , Liu Shouyang , Cheng Tao 

TITLE=Estimation of Nitrogen Nutrition Status in Winter Wheat From Unmanned Aerial Vehicle Based Multi-Angular Multispectral Imagery

JOURNAL=Frontiers in Plant Science

VOLUME=10

YEAR=2019

URL=https://www.frontiersin.org/journals/plant-science/articles/10.3389/fpls.2019.01601

DOI=10.3389/fpls.2019.01601

ISSN=1664-462X

ABSTRACT=<p>Rapid, non-destructive and accurate detection of crop N status is beneficial for optimized fertilizer applications and grain quality prediction in the context of precision crop management. Previous research on the remote estimation of crop N nutrition status was mostly conducted with ground-based spectral data from nadir or oblique angles. Few studies investigated the performance of unmanned aerial vehicle (UAV) based multispectral imagery in regular nadir views for such a purpose, not to mention the feasibility of oblique or multi-angular images for improved estimation. This study employed a UAV-based five-band camera to acquire multispectral images at seven view zenith angles (VZAs) (0°, ± 20°, ± 40° and ±60°) for three critical growth stages of winter wheat. Four representative vegetation indices encompassing the Visible Atmospherically Resistant Index (VARI), Red edge Chlorophyll Index (CI<sub>red-edge</sub>), Green band Chlorophyll Index (CI<sub>green</sub>), Modified Normalized Difference Vegetation Index with a blue band (mND<sub>blue</sub>) were derived from the multi-angular images. They were used to estimate the N nutrition status in leaf nitrogen concentration (LNC), plant nitrogen concentration (PNC), leaf nitrogen accumulation (LNA), and plant nitrogen accumulation (PNA) of wheat canopies for a combination of treatments in N rate, variety and planting density. The results demonstrated that the highest accuracy for single-angle images was obtained with CI<sub>green</sub> for LNC from a VZA of -60° (<italic>R<sup>2</sup></italic> = 0.71, RMSE = 0.34%) and PNC from a VZA of -40° (<italic>R<sup>2</sup></italic> = 0.36, RMSE = 0.29%). When combining an off-nadir image (-40°) and the 0° image, the accuracy of PNC estimation was substantially improved (CI<sub>red-edge</sub>: <italic>R<sup>2</sup></italic> = 0.52, RMSE = 0.28%). However, the use of dual-angle images did not significantly increase the estimation accuracy for LNA and PNA compared to the use of single-angle images. Our findings suggest that it is important and practical to use oblique images from a UAV-based multispectral camera for better estimation of nitrogen concentration in wheat leaves or plants. The oblique images acquired from additional flights could be used alone or combined with the nadir-view images for improved crop N status monitoring.</p>