A peanut simulation model: I. Model development and testing

Hammer, Graeme L., Sinclair, Thomas R., Boote, Kenneth J., Wright, Graeme C., Meinke, Holger and Bell, Mike J. (1995) A peanut simulation model: I. Model development and testing. Agronomy Journal, 87 6: 1085-1093.

Author Hammer, Graeme L.
Sinclair, Thomas R.
Boote, Kenneth J.
Wright, Graeme C.
Meinke, Holger
Bell, Mike J.
Title A peanut simulation model: I. Model development and testing
Journal name Agronomy Journal   Check publisher's open access policy
ISSN 0002-1962
Publication date 1995-11
Sub-type Article (original research)
Volume 87
Issue 6
Start page 1085
End page 1093
Total pages 9
Place of publication Madison, WI, United States
Publisher American Society of Agronomy
Language eng
Formatted abstract
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.
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Non-UQ

Document type: Journal Article
Sub-type: Article (original research)
Collection: Queensland Alliance for Agriculture and Food Innovation
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Created: Mon, 07 Mar 2011, 15:32:16 EST