1. Effective weed control is essential in field vegetables. However, the range of available herbicides has been continually reduced for commercial and toxicological reasons over the last decade. In order to predict the optimum weeding period and to apply alternative control strategies successfully, a realistic estimate is needed of the size, timing and duration of a flush of weed emergence in a crop. The soil weed seed bank is the primary source of future weed populations, and therefore provides a unique resource for predictive management purposes.
2. Models have previously been developed to predict the emergence of weed species from different burial depths and to simulate the vertical movement of weed seeds following seed bed preparation.
3. In this investigation a vertical movement model was extended to include the effects of four cultivation implements on the horizontal displacement of weed seeds. These implements were a rotavator, a spring tine, a spader and a power harrow.
4. The rotavator caused a backward movement of seeds; neither the spring tine nor spader had a significant effect on the horizontal displacement of seeds; whilst the power harrow had the greatest capacity to move seeds forward > 0·5 m in the soil.
5. This investigation combined depth of burial and vertical movement models to simulate the likely outcome of different sequences of spring tine, spader, rotavator and power harrow on subsequent weed seedling emergence. For example, sequences including multiple passes of a spader increased the numbers of emerged seedlings, whilst for those where the rotavator dominated the sequence, a marked reduction in seedling numbers was predicted. The findings of a series of simulations are viewed in the light of existing methods of weed control based on soil cultivation, for example the stale seed bed technique.
6. The combined model provides the basis for a decision support system to aid the control of weeds. Additionally, it provides a research tool to improve understanding of the dynamics of the weed seed bank and the implications of seed bed preparations for future populations. The combined model has helped to identify areas of weed seed ecology requiring further study, essential for the development of true dynamic models.