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Agronomy Journal Abstract -

A Peanut Simulation Model: I. Model Development and Testing


This article in AJ

  1. Vol. 87 No. 6, p. 1085-1093
    Received: July 27, 1994

    * Corresponding author(s): graemeh@apsrusg.sth.dpi.qld.gov.au
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  1. Graeme L. Hammer ,
  2. Thomas R. Sinclair,
  3. Kenneth J. Boote,
  4. Graeme C. Wright,
  5. Holger Meinke and
  6. Mike J. Bell
  1. D PI/CSIRO Agric. Prod. Systems Res. Unit, P.O. Box 102, Toowoomba, QLD 4350, Australia
    U SDA-ARS and Agronomy Dep., Univ of Florida, Gainesville, FL 32116
    A gronomy Dep., Univ. of Florida, Gainesville, FL 32116
    D PI, P.O. Box 23, Kingaroy, QLD 4610, Australia



A biophysically robust crop simulation model can assist industry planning and farmer decision-making via simulation analyses to quantify production potential and production risks. Accordingly, we developed a simple, yet mechanistic peanut simulation model for use in assessing climatic risks to production potential for both irrigated and dryland conditions. The model simulates pod yield, biomass accumulation, crop leaf area, phenology, and soil water balance and is suitable for application over a diverse range of production environments. The model uses a daily time step, utilizes readily available weather and soil information, and assumes no nutrient limitations. The model was tested on numerous data from experiments spanning a broad range of environments in the tropics and subtropics. The model performed satisfactorily, accounting for 89% of the variation in pod yield on data sets derived from independent experiments, which included crops yielding from 1 to 71 t ha−1. Limitations of the model and aspects requiring better understanding to improve quantification are discussed. Despite some limitations, the model attains a useful degree of predictive skill for a broad range of situations and environments. This outcome is testimony to the utility of the simple, generic framework used as the basis for this model. The model is suitable for simulation studies aimed at assisting industry planning and farmer decision-making.

Contribution from the Agricultural Production Systems Res. Unit, Queensland Dep. of Primary Industries, and the Commonwealth Scientific and Industrial Res. Org., P.O. Box 102, Toowoomba, QLD 4350, Australia.

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