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Precision Estimation of Rice Nitrogen Fertilizer Topdressing According to the Nitrogen Nutrition Index Using UAV
Lijuan Wang1,2, Qihan Ling1, Zhan Liu3
1College of Resources and Environment, Southwest University, Chongqing 400716, China.
Abstract:
The precision estimation of N fertilizer application according to the nitrogen nutrition index (NNI) using unmanned aerial vehicle (UAV) multi-spectral measurements remains to be tested in different rice cultivars and planting areas. Therefore, two field experiments were conducted using varied N rates (0, 60, 120, 160, and 200 kg N ha-1) on two rice cultivars, Yunjing37 (YJ-37, Oryza sativa subsp. Japonica Kato., the Institute of Food Crops at the Yunnan Academy of Agricultural Sciences, Kunming, China) and Jiyou6135 (JY-6135, Oryza sativa subsp. indica Kato., Hunan Longping Gaoke Nongping seed industry Co., Ltd., Changsha, China), in southwest China. The rice canopy spectral images were measured by the UAV's multi-spectral remote sensing at three growing stages. The NNI was calculated based on the critical N (Nc) dilution curve. A random forest model integrating multi-vegetation indices established the NNI inversion, facilitating precise N topdressing through a linear platform of NNI-Relative Yield and the remote sensing NNI-based N balance approaches. The Nc dilution curve calibrated with aboveground dry matter demonstrated the highest accuracy (R2 = 0.93, 0.97 for shoot components in cultivars YJ-37 and JY-6135), outperforming stem (R2 = 0.70, 0.76) and leaf (R2 = 0.80, 0.89) based models. The RF combined with six vegetation index combinations was found to be the best predictor of NNI at each growing period (YJ-37: R2 is 0.70-0.97, RMSE is 0.02~0.04; JY-6135: R2 is 0.71-0.92, RMSE is 0.04~0.05). The RF surpassed BPNN/PLSR by 6.14-10.10% in R2 and 13.71-33.65% in error reduction across the critical rice growth stages. The topdressing amounts of YJ-37 and JY-6135 were 111-124 kg ha-1 and 80-133 kg ha-1, with low errors of 2.50~8.73 kg ha-1 for YJ-37 and 2.52~5.53 kg ha-1 for JY-6135 in the jointing (JT) and heading (HD) stages. These results are promising for the precise topdressing of rice using a remote sensing NNI-based N balance method. The combination of UAV multi-spectral imaging with the NNI-nitrogen balance method was tested for the first time in southwest China, demonstrating its feasibility and offering a regional approach for precise rice topdressing.
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