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.

间作两种或两种以上作物的作物可以提高资源利用的效率，并经常在单位土地面积上产生更高的产量。间作的相对效率取决于行的配置，但是由于基于过程的标准作物模型不足以模拟空间结构化的冠层的资源捕获，生长和产量形成，因此缺乏基于模型的替代间作方案评估条状。我们将带状作物的光拦截模型实现为APSIM Classic模型，并将其与准贝叶斯方法相结合，以导出模型参数，以模拟玉米-大豆带间作中的作物生长和谷物产量。我们使用了5年不同行配置的4年现场数据，得出了用于模拟光拦截，LAI动态，玉米和大豆间作作物的生物量增长和籽粒产量。关键模型参数（例如RUE，k等）随行距和配置的变化而变化，这给用单个参数集模拟不同配置带来了挑战。这些关键参数的潜在范围是通过将模型约束到观测数据而得出的。该模型可以潜在地用于评估种植配置对带间作系统生产力的影响，但是配置处理之间关键模型参数的可变性要求进一步深入研究以改善带间作的建模生理。