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Abstract
This paper develops a stochastic multi-period decision model to analyse a continuous
wheat cropping system infested by wild oats (Avena fatua L.), in southern Australia. The
multi-period solutions is obtained by employing a dynamic programming model in conjunction
with a bioeconomic simulation model. An empirically estimated dose response function
is used to derive the optimal herbicide rate. Uncertainties due to environmental effects on
the performance of herbicide and crop yields are modelled and optimal decision rules
derived. The results indicate that substantial economic gains can be realised if herbicide
dose decisions are taken by considering future profit effects of current decisions, as opposed
to the more common approach of only considering the current-period effect.