Modelling uncertainty in field grown iceberg lettuce production for decision support

Uncertainty in terms of input parameters, particularly weather variables, has implications for the results of a deterministic crop prediction model. This manuscript describes the development of the Iceberg Predictor decision support system which uses a stochastic weather generator to provide three alternative scenarios for future weather. These are used to drive a mechanistic model which provides posterior distributions of potential crop outcomes including within-field variability, which are summarised for grower interpretation. Multiple crops can be simulated allowing improved management of uncertainty at the whole enterprise scale. Experimental work demonstrated that variation in transplant size is a major contributor to variability in the final harvest.