Abstract

Commercially available digital cameras can be mounted on an unmanned aerial vehicle (UAV) for crop growth monitoring in open-air fields as a low-cost, highly effective observation system. However, few studies have investigated their potential for nitrogen (N) status monitoring, and the performance of camera-derived vegetation indices (VIs) under different conditions remains poorly understood. In this study, five commonly used VIs derived from normal color (RGB) images and two typical VIs derived from color near-infrared (CIR) images were used to estimate leaf N concentration (LNC). To explore the potential of digital cameras for monitoring LNC at all crop growth stages, two new VIs were proposed, namely, the true color vegetation index (TCVI) from RGB images and the false color vegetation index (FCVI) from CIR images. The relationships between LNC and the different VIs varied at different stages. The commonly used VIs performed well at some stages, but the newly proposed TCVI and FCVI had the best performance at all stages. The performances of the VIs with red (or near-infrared) and green bands as the numerator were limited by saturation at intermediate to high LNCs (LNC > 3.0%), but the TCVI and FCVI had the ability to mitigate the saturation. The results of model validations further supported the superiority of the TCVI and FCVI for LNC estimation. Compared to the other VIs derived using RGB cameras, the relative root mean square errors (RRMSEs) of the TCVI were improved by 8.6% on average. For the CIR images, the best-performing VI for LNC was the FCVI (R2 = 0.756, RRMSE = 14.18%). The LNC–TCVI and LNC–FCVI were stable under different cultivars, N application rates, and planting densities. The results confirmed the applicability of UAV-based RGB and CIR cameras for crop N status monitoring under different conditions, which should assist the precision management of N fertilizers in agronomic practices.

Highlights

  • Nitrogen (N) is a component of many important compounds in plants, and plays an important role in plant growth [1,2]

  • The applicability of digital cameras mounted on unmanned aerial vehicle (UAV) for monitoring the Leaf N Concentration (LNC) of winter wheat was evaluated in this study

  • The performances of normalized green–red difference index (NGRDI), Red green ratio index (RGRI), visible atmospherically resistance index (VARI), and Green normalized difference vegetation index (GNDVI) were limited by saturation at intermediate to high LNCs (i.e., LNC > 3.0%)

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Summary

Introduction

Nitrogen (N) is a component of many important compounds in plants, and plays an important role in plant growth [1,2]. Color indices from RGB cameras containing a large amount of information regarding crop status can be used to estimate the vegetation fraction, plant height, biomass, and yield [19,20,21]. Based on a newly-developed digital CIR camera system, Hunt et al, [25] found a strong correlation between the green normalized difference vegetation index (GNDVI) and leaf area index (LAI) in winter wheat. This CIR camera system has been used to assess winter crop biomass [26]. AA CCaannoonn 55DD MMaarrkk IIIIII ((CCaannoonn IInncc..,, JJaappaann)) ccoommmmeerrcciiaall ddiiggiittaall ccaammeerraa ((FFiigguurree 22bb)) wwaass mmoouunntteedd oonn tthhee UUAAVV aanndd ttooookk RRGGBB iimmaaggeess iinn ccoonnttiinnuuoouuss mmooddee.

MAaypril 8
Data Analysis and Evaluation
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