Functional-structural plant modelling is an established approach to realistically represent plant growth, but testing and documenting realism beyond visual comparisons is challenging. We used elements of pattern-oriented modelling to test the realism of a new model of the annual growth module (AGM) of avocado (Persea americana, cv. Hass. Lauraceae).
Wang et al. use seven patterns characterising AGMs to calibrate the model, which then successfully predicted nine further patterns that were not used during calibration. Their model can thus be claimed to be structurally realistic, which implies that it will be able to predict the response of an AGM to changing environmental conditions.