Modelling soybean and maize growth and grain yield in strip intercropping systems with different row configurations

Yushan Wu, Di He, Enli Wang*, Xin Liu, Neil I. Huth, Zhigan Zhao, Wanzhuo Gong, Feng Yang, Xiaochun Wang, Taiwen Yong, Jiang Liu, Weiguo Liu, Junbo Du, Tian Pu, Chunyan Liu, Liang Yu, Wopke van der Werf, Wenyu Yang

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review


Intercropping of two or more crop species increases the efficiency of resource use and often produces a greater yield per unit land area. The relative efficiency of intercropping depends on row configuration, but there is a shortage of modelling-based evaluation of alternative intercropping options due to the inadequacy of standard process-based crop models to simulate resource capture, growth and yield formation when the canopy is spatially structured in strips. We implemented a light interception model for strip crops into the APSIM Classic model and combined it with a quasi-Bayesian approach to derive the model parameters to simulate crop growth and grain yield in maize-soybean strip intercropping. We used 4 years of field data for 5 different row configurations to derive key model parameters for simulation of light interception, LAI dynamics, biomass growth and grain yield of maize and soybean intercrops. Key model parameters (e.g. RUE, k etc.) were found to change with row-spacing and configuration, posing challenges to simulate different configurations with a single parameter set. The potential ranges of these key parameters were derived by constraining the model to observed data. The model can be potentially used to evaluate impact of planting configurations on productivity of strip intercropping systems, but the variability of key model parameters among configuration treatments calls for further in-depth research to improve modelling physiology of strip intercrops.

Original languageEnglish
Article number108122
JournalField Crops Research
Publication statusPublished - 15 May 2021


  • Intercropping
  • Light interception
  • Modelling
  • Soybean

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