Optimizing nitrogen topdressing for winter wheat by coupling remote sensing data with the DSSAT model.

Abstract

Introduction Excessive fertilization not only causes environmental pollution and degrades water and soil quality but also increases production costs and reduces agricultural sustainability. Methods Based on two consecutive years of field experiments, this study developed a two-step data assimilation strategy for nitrogen (N) topdressing recommendations for winter wheat. First, a data assimilation system was established by minimising the discrepancy between aboveground dry biomass (AGB) estimated from remote sensing and that simulated by the crop growth model using a particle swarm optimization approach. Second, target yields under varying growth conditions were constructed using the DSSAT model and N economic return curves to enable optimised N fertilization recommendations. Results AGB monitoring model was developed, achieving satisfactory results in both the calibration and validation datasets, with determination coefficient (R²) (normalised root mean square error (nRMSE)) values of 0.94 (13.62%) and 0.82 (15.42%), respectively. Based on the data assimilation system, the data assimilation stability for AGB and yield are relatively high. The nRMSE values for AGB are 11.20% and 19.44% for the training and validation datasets, respectively. The nRMSE values for yield are 6.35% and 11.22% for the training and validation datasets, respectively. The data assimilation-based recommended fertilization shows a negative power-law relationship with AGB at the jointing stage (R² = 0.65). Under different yield levels, fertilization was reduced by 6.69%-34.08% compared with that under high yield levels. Conclusion This study balances yield and production costs by developing a data assimilation strategy for N fertilization recommendations, which can maintain high productivity and sustainability.

Plant phenotyping relevance

リモートセンシングから小麦の地上部乾物量を推定するモデルを開発・検証し、データ同化に組み込んでいるため、施肥推薦が主目的でも植物形質取得法が実質的に中心的役割を持つ。

Code and data availability

The supplied blocks describe UAV multispectral imagery, AGB/yield measurements, and a DSSAT-PSO data assimilation framework, but contain no data availability statement, public repository deposit, or author code/model release. The only URLs mentioned (data.cma.cn for meteorological data and ndrc.gov.cn for price data) p

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