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Research article - Peer-reviewed, 2018

Potential of the APSIM model to simulate impacts of shading on maize productivity

Dilla, Aynalem; Smethurst, Philip J.; Barry, Karen; Parsons, David; Denboba, Mekuria


A number of agroforestry models have been developed to simulate growth outcomes based on the interactions between components of agroforestry systems. A major component of this interaction is the impact of shade from trees on crop growth and yield. Capability in the agricultural production systems simulator (APSIM) model to simulate the impacts of shading on crop performance could be particularly useful, as the model is already widely used to simulate agricultural crop production. To quantify and simulate the impacts of shading on maize performance without trees, a field experiment was conducted at Melkassa Agricultural Research Centre, Ethiopia. The treatments contained three levels of shading intensity that reduced incident radiation by 0 (control), 50 and 75% using shade cloth. Data from a similar field experiment at Machakos Research Station, Kenya, with 0, 25 and 50% shading were also used for simulation. APSIM adequately simulated maize grain yield (r(2)=0.97) and total above-ground biomass (r(2)=0.95) in the control and in the 50% treatments at Melkassa, and likewise in the control (r(2)=0.99), 25% (r(2)=0.90) and 50% (r(2)=0.98) treatments at Machakos. Similarly, APSIM effectively predicted Leaf Area Index attained at the flowering (r(2)=0.90) and maturity (r(2)=0.94) stages. However, APSIM under-estimated maize biomass and yield at 75% shading. In conclusion, the model can be reliably employed to simulate maize productivity in agroforestry systems with up to 50% shading, but caution is required at higher levels of shading.


Agroforestry; LAI; Light; Modelling

Published in

Agroforestry Systems
2018, Volume: 92, number: 6, pages: 1699-1709
Publisher: SPRINGER

      SLU Authors

    • Parsons, David

      • Department of Agricultural Research for Northern Sweden, Swedish University of Agricultural Sciences
      • University of Tasmania

    Sustainable Development Goals

    SDG2 Zero hunger

    UKÄ Subject classification

    Forest Science
    Agricultural Science

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