Citation Information

  • Title : Rational nitrogen fertilization in intensive cropping systems
  • Source : Fertilizer research
  • Publisher : Kluwer Academic Publishers
  • Volume : 42
  • Issue : 1-3
  • Pages : 89-97
  • Year : 1995
  • DOI : 10.1007/BF007505
  • ISBN : 10.1007/BF00750502
  • Document Type : Journal Article
  • Language : English
  • Authors:
    • Schepers, JS
    • Havlin, JL
    • Rice, CW
  • Climates:
  • Cropping Systems: Maize. No-till cropping systems.
  • Countries:

Summary

The objective of a rational N fertilization program is to account for the sources and fate of N while estimating crop N needs. Efficiency of N use will vary with cropping systems and N sources. Management technologies that affect N use efficiency include the amount of N applied, timing and placement of N fertilizer, and use of inhibitors. One of the main problems in making a fertilizer N recommendation is to account for the contribution of N mineralization to plant available N. Most laboratory procedures do not account for the environmental factors that affect N mineralization and only estimate the size of the mineralizable N pool. However, changes in soil moisture and temperature can dramatically affect the amount and rate of release of mineralized N. Field and modeling techniques are two possible techniques to estimate N mineralization. Field techniques can be divided into soil and plant approaches. Soil incubations in the field provide a quantitative approach while soil nitrate tests during the growing season provide a qualitative approach to estimating N mineralization. The plant is the ultimate integrator of N mineralization. Plant N uptake by an unfertilized crop can provide a quantitative approach with certain precautions. This approach may be costly, labor intensive, and site specific. Crop N uptake during the growing season can be estimated by measuring the tissue N content or using a chlorophyll meter. The chlorophyll meter measures the greenness of the plant and has been shown to be positively correlated to plant N status. Modeling may provide another option by including the factors that affect the rate of N mineralization from a known pool. The two most important variables include soil moisture and temperature. Realistic yield expectations and accounting for existing and projected amounts of available N can improve the accuracy of N recommendations.

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