Crop growth is driven by the capture and utilisation of solar radiation. The most productive crop sequences are those that maximise the interception and use of solar radiation. However, there are yield trade-offs because of the timing of transitions between successive crops. A longer duration of one crop will mean that the following crop is sown later and will therefore produce a lower yield. Maximising the yield of a sequence involves a compromise between the yields of successive crops. We describe a case study of a forage cropping rotation in New Zealand, demonstrating how simulation models can be used to define the best compromise between the yields of successive crops, and thereby maximise the total yield of the full sequence. A case study using a series of long-term simulation experiments for four diverse environments in New Zealand was undertaken in a continuous, summer maize - winter cereal, cropping sequence. Maize sowing dates and hybrid durations, and cereal sowing and harvest times were varied systematically. The actual simulated crop and sequence yields varied from site to site, but there was a consistent trend identifying the most productive combinations of sowing date and hybrid duration. The sequence of comparatively late sowing date of maize (1 December) and a long-season hybrid maximised the total yield of the sequence. The highest sequence yields were achieved by balancing the need to capture a high level of annual solar radiation and the need to have a large proportion of solar radiation captured by maize, which has the greater RUE in summer. This analysis illustrates how crop simulation models can be used to design and understand the processes that give the most productive cropping sequences.
