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

• Published in: Frontiers in plant science Vol. 10; p. 1601
• Main Authors: Lu, Ning, Wang, Wenhui, Zhang, Qiaofeng, Li, Dong, Yao, Xia, Tian, Yongchao, Zhu, Yan, Cao, Weixing, Baret, Fred, Liu, Shouyang, Cheng, Tao
• Format: Journal Article
• Language: English
• Published: Frontiers 06.12.2019; Frontiers Media S.A
• Subjects: Agricultural sciences; Life Sciences; multi-angular; nitrogen status; unmanned aerial vehicle; vegetation index; wheat; zenith angle; vegetation index; multi-angular; wheat; unmanned aerial vehicle; zenith angle; nitrogen status
• ISSN: 1664-462X; 1664-462X
• DOI: 10.3389/fpls.2019.01601

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 degrees, +/- 20 degrees, +/- 40 degrees and +/- 60 degrees) for three critical growth stages of winter wheat. Four representative vegetation indices encompassing the Visible Atmospherically Resistant Index (VARI), Red edge Chlorophyll Index (CIred-edge), Green band Chlorophyll Index (CIgreen), Modified Normalized Difference Vegetation Index with a blue band (mND(blue)) 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 CIgreen for LNC from a VZA of -60 degrees (R-2 = 0.71, RMSE = 0.34%) and PNC from a VZA of -40 degrees (R-2 = 0.36, RMSE = 0.29%). When combining an off-nadir image (-40 degrees) and the 0 degrees image, the accuracy of PNC estimation was substantially improved (CIred-edge: R-2 = 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