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High-Resolution UAV-Based Hyperspectral Imagery for LAI and Chlorophyll Estimations from Wheat for Yield Prediction
摘要： The efficient use of nitrogen fertilizer is a crucial problem in modern agriculture. Fertilization has to be minimized to reduce environmental impacts but done so optimally without negatively affecting yield. In June 2017, a controlled experiment with eight different nitrogen treatments was applied to winter wheat plants and investigated with the UAV-based hyperspectral pushbroom camera Resonon Pika-L (400–1000 nm). The system, in combination with an accurate inertial measurement unit (IMU) and precise gimbal, was very stable and capable of acquiring hyperspectral imagery of high spectral and spatial quality. Additionally, in situ measurements of 48 samples (leaf area index (LAI), chlorophyll (CHL), and reflectance spectra) were taken in the field, which were equally distributed across the different nitrogen treatments. These measurements were used to predict grain yield, since the parameter itself had no direct effect on the spectral reflection of plants. Therefore, we present an indirect approach based on LAI and chlorophyll estimations from the acquired hyperspectral image data using partial least-squares regression (PLSR). The resulting models showed a reliable predictability for these parameters (R2 LAI = 0.79, RMSELAI [m2m?2] = 0.18, R2 CHL = 0.77, RMSECHL [μg cm?2] = 7.02). The LAI and CHL predictions were used afterwards to calibrate a multiple linear regression model to estimate grain yield (R2 yield = 0.88, RMSEyield [dt ha?1] = 4.18). With this model, a pixel-wise prediction of the hyperspectral image was performed. The resulting yield estimates were validated and opposed to the different nitrogen treatments, which revealed that, above a certain amount of applied nitrogen, further fertilization does not necessarily lead to larger yield.
关键词： hyperspectral,chlorophyll,UAV,pushbroom,regression,grain yield,LAI,nitrogen
更新于2025-09-19 17:15:36
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Wheat grain yield and nitrogen uptake prediction using atLeaf and GreenSeeker portable optical sensors at jointing growth stage
摘要： Rapid acquisition of information about nitrogen (N) uptake and grain yield is an essential step in making site-specific in-season fertilizer N management decisions. The objective of this study was to quantify and validate the relationships between N uptake and grain yield of wheat using in-season measurements with atLeaf chlorophyll meter and GreenSeeker optical sensor at Feekes 6 growth stage (jointing stage) of wheat. The relationships were developed using data generated from experiments with multi-rate fertilizer N treatments and conducted in two consecutive wheat seasons (2017/2018 and 2018/2019) at two locations in the western Nile Delta of Egypt. A power function based on atLeaf measurement at Feekes 6 stage of wheat could explain 55.3 % and 53.3 % variations in the N uptake at this stage and grain yield at maturity, respectively. Measurements with GreenSeeker were related with N uptake and yield of wheat through exponential function and could explain 68.5 % and 60.6 % of the variation in N uptake and grain yield, respectively. The developed models were validated on an independent data set from another field experiment on wheat. The normalized root mean square error for the relation between atLeaf measurements and N uptake and grain yield were fair, whereas the fits were good for measurements with GreenSeeker. This study reveals that atLeaf chlorophyll meter and GreenSeeker optical sensor can be successfully used for establishing site-specific N management strategies in wheat.
关键词： grain yield,GreenSeeker sensor,N uptake,atLeaf sensor,wheat
更新于2025-09-12 10:27:22