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A case study on precision nitrogen management in Dutch arable farming

Alphen, B.J. van.
Nutrient cycling in agroecosystems 2002 v.62 no.2 pp. 151-161
Triticum aestivum, precision agriculture, nitrogen, soil fertility, field experimentation, land management, simulation models, case studies, temporal variation, spatial variation, nitrogen content, Netherlands
Throughout Europe new environmental laws are being implemented to limit nitrogen (N) fertilization on arable land. This is particularly relevant in The Netherlands where arable farms rank among the most intensively managed in the world. An efficient use of inputs is therefore crucial. Precision agriculture aims at increasing this efficiency by incorporating spatial and temporal variation into fertilizer management. A method developed for this purpose is evaluated, based on two fertilizer experiments conducted in consecutive years (1998-1999) on different winter wheat fields (Triticum aestivum L.). A simulation model and real-time weather data were used to monitor soil mineral N levels in the experimental fields. Spatial variation was incorporated through management units, which were defined in terms of water regimes and N dynamics. Early warning was provided when soil mineral N concentrations dropped below a critical threshold. Used as a trigger, this information served to optimize the timing of four consecutive N fertilizations. Fertilizer rates were determined through exploratory simulations, which calculated the amount of mineral N required under normal conditions. Compared to conventional management, fertilizer input was reduced by 15-27% without affecting grain yield. Grain quality was either not affected (1999) or significantly increased (1998; P < 0.01). Soil mineral N residues measured after harvest were consistently lower under precision management. This is important since leaching of nitrates mainly occurs during winter when a precipitation surplus is present. Results provide an illustration of efficiency gains attained through precision N management. They also underline the relevance of managing temporal variation (along with spatial variation) on farms applying intensive and dynamic management strategies.