Abstract
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 (CIred-edge), Green band Chlorophyll Index (CIgreen), Modified Normalized Difference Vegetation Index with a blue band (mNDblue) 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° (R2 = 0.71, RMSE = 0.34%) and PNC from a VZA of -40° (R2 = 0.36, RMSE = 0.29%). When combining an off-nadir image (-40°) and the 0° image, the accuracy of PNC estimation was substantially improved (CIred-edge: R2 = 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.
Highlights
Nitrogen (N) status is a critical nutrient indicator in crop growth for optimizing fertilization management
The canopy reflectance varies with view zenith angle (VZA) for every band, and the spectral variation between view angles for the NIR band (800 nm) is more significant than that for other bands (Figure 4)
Among the four VIs, CIgreen yielded the highest accuracy for most VZAs (Figure 6) and visible atmospherically resistant index (VARI) exhibited the lowest accuracy for all VZAs. mNDblue and CIred-edge achieved moderate accuracies, with the former being superior to the latter from -40° to 40°
Summary
Nitrogen (N) status is a critical nutrient indicator in crop growth for optimizing fertilization management. Leaf N concentration (LNC) and plant N concentration (PNC) are important indicators for N fertilizer application at early growth stages (Hansen and Schjoerring, 2003; Li et al, 2018) and they are highly related to the final grain quality (Zheng et al, 2018b). Real-time and rapid detection of crop N status is beneficial for agricultural management practices and helps guide efficient fertilizer applications (Hansen and Schjoerring, 2003; Yao et al, 2010). Remote sensing has been proved to be an efficient tool and widely applied in rapid and non-destructive estimation of crop N status (Tilling et al, 2007; Li et al, 2010; Lee and Lee, 2013; Quemada et al, 2014; Yao et al, 2014)
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