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Topdressing accounts for approximately 40% of the total nitrogen (N) application of winter wheat on the Huang-Huai-Hai Plain in China. However, N use efficiency of topdressing is low due to the inadaptable topdressing method used by local farmers. To improve the N use efficiency of winter wheat, an optimization method for topdressing (THP) is proposed that uses unmanned aerial vehicle (UAV)-based remote sensing to accurately acquire the growth status and an improved model for growth potential estimation and optimization of N fertilizer amount for topdressing (NFT). The method was validated and compared with three other methods by a field experiment: the conventional local farmer’s method (TLF), a nitrogen fertilization optimization algorithm (NFOA) proposed by Raun and Lukina (TRL) and a simplification introduced by Li and Zhang (TLZ). It shows that when insufficient basal fertilizer was provided, the proposed method provided as much NFT as the TLF method, i.e., 25.05% or 11.88% more than the TRL and TLZ methods and increased the yields by 4.62% or 2.27%, respectively; and when sufficient basal fertilizer was provided, the THP method followed the TRL and TLZ methods to reduce NFT but maintained as much yield as the TLF method with a decrease of NFT by 4.20%. The results prove that THP could enhance crop production under insufficient N preceding conditions by prescribing more fertilizer and increase nitrogen use efficiency (NUE) by lowering the fertilizer amount when enough basal fertilizer is provided.

Optimization of Topdressing for Winter Wheat by Accurate Growth Monitoring and Improved Production Estimation