Evaluation of current and model-based site-specific nitrogen applications on wheat (Triticumaestivum L.) yield and environmental quality

Evaluation of current and model-based site-specific nitrogen applications on wheat... Crop growth models have been used in the past to study causes of yield variability and to estimate the economic consequences of variable nitrogen rate prescriptions. In this study, the APOLLO model, which is based on the DSSAT crop growth model family, was implemented to develop optimum site-specific nitrogen management prescriptions for wheat. The nitrogen prescription was targeted to maximize the long-term marginal net return, which includes an economic penalty for leaving excess nitrogen in the root zone at harvest. By using two constraints—yield and environmental quality—it is expected that the simulation can find prescriptions that maximize marginal net return while reducing the amount of nitrogen losses to surface and groundwater sources at the sub-field scale. Overall, the total amount of nitrogen applied in the control and the model-based treatment was about the same. Thus, for yield, environmental aspects and economic aspects no significant differences were identified between both treatments. However, the results indicated that the model-based nitrogen prescription considered the yield variability adequately for most grids, given by an increase in nitrogen use efficiency, and thus enabled the design of nitrogen prescriptions adapted to the nitrogen demand of the plants. The model-based nitrogen strategy helps to optimize the nitrogen application rate within the field over the long-term of about 30 years. To gain further advantages from model-based nitrogen prescriptions, it seems to be useful to additionally update the model with actual information derived for the current growing conditions. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Precision Agriculture Springer Journals

Evaluation of current and model-based site-specific nitrogen applications on wheat (Triticumaestivum L.) yield and environmental quality

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Publisher
Springer Journals
Copyright
Copyright © 2008 by Springer Science+Business Media, LLC
Subject
Life Sciences; Agriculture; Soil Science & Conservation; Remote Sensing/Photogrammetry; Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences; Atmospheric Sciences
ISSN
1385-2256
eISSN
1573-1618
D.O.I.
10.1007/s11119-008-9068-y
Publisher site
See Article on Publisher Site

Abstract

Crop growth models have been used in the past to study causes of yield variability and to estimate the economic consequences of variable nitrogen rate prescriptions. In this study, the APOLLO model, which is based on the DSSAT crop growth model family, was implemented to develop optimum site-specific nitrogen management prescriptions for wheat. The nitrogen prescription was targeted to maximize the long-term marginal net return, which includes an economic penalty for leaving excess nitrogen in the root zone at harvest. By using two constraints—yield and environmental quality—it is expected that the simulation can find prescriptions that maximize marginal net return while reducing the amount of nitrogen losses to surface and groundwater sources at the sub-field scale. Overall, the total amount of nitrogen applied in the control and the model-based treatment was about the same. Thus, for yield, environmental aspects and economic aspects no significant differences were identified between both treatments. However, the results indicated that the model-based nitrogen prescription considered the yield variability adequately for most grids, given by an increase in nitrogen use efficiency, and thus enabled the design of nitrogen prescriptions adapted to the nitrogen demand of the plants. The model-based nitrogen strategy helps to optimize the nitrogen application rate within the field over the long-term of about 30 years. To gain further advantages from model-based nitrogen prescriptions, it seems to be useful to additionally update the model with actual information derived for the current growing conditions.

Journal

Precision AgricultureSpringer Journals

Published: Jul 16, 2008

References

  • Managing uncertainty in site-specific management: What is the best model?
    Adams, ML; Cook, S; Corner, R
  • Spatial validation of crop models for precision agriculture
    Basso, B; Ritchie, JT; Pierce, FJ; Braga, RP; Jones, JW

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