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This article in JEQ

  1. Vol. 35 No. 2, p. 658-669
    Received: Apr 22, 2005

    * Corresponding author(s): David.Crohn@ucr.edu
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Optimizing Organic Fertilizer Applications under Steady-State Conditions

  1. David M. Crohn *
  1. Department of Environmental Sciences, University of California, Riverside, CA 92521


Because organic N fertilizers must be mineralized before they become plant-available, application designs should consider time and temperature effects on N release as well as crop N requirements. This study presents deterministic (DOpt) and stochastic (SOpt) linear optimization models to determine sustainable land application schedules. The easily solved models minimize the amount of N that is applied while assuring than crop N demands are met as they develop. Temperature effects on N mineralization were included by using the Arrhenius equation to create a temperature-adjusted time series. Uncertainties associated with mineralization rates and the temperature-adjustment (Q 10) factor are considered by SOpt. Examples are presented for a summer maize (Zea mays L.) and winter triticale (Triticum aestivum L. × Secale cereale L.) rotation operated by a hypothetical dairy operation in Stanislaus County, California. Monte Carlo simulations were used to test the models. A closed-form solution for estimating the time until steady state is presented and steady-state conditions were reached within 7 yr after applications were initiated. Because of temperature effects, DOpt solutions were 12% greater during the winter and 29% lower during the summer than a reference approach that applied liquid manure at 130% of the crop N demand. Stochastic linear optimization values were 1.7% greater than DOpt values in the summer and 6.2% greater in the winter. Surplus N estimates from Monte Carlo simulations averaged 104 kg ha−1 for DOpt and 126 ka ha−1 for SOpt, but SOpt was much less likely to result in crop N deficits. Linear optimization is a viable tool for scheduling organic N applications.

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Copyright © 2006. American Society of Agronomy, Crop Science Society of America, Soil Science SocietyASA, CSSA, SSSA