MODELING OPTIMAL ALFALFA HARVEST SCHEDULING USING SHORT-RANGE WEATHERFORECASTS

Alfalfa (Medicago sativa L.) harvest is ideally scheduled to avoid rai n damage to the cut forage while it is still in the field. The problem of timing alfalfa harvest in relation to available weather forecasts is addressed here using a dynamic programming approach. The modeled cu tting decision is faced daily, and it must balance increasing yield an d decreasing forage quality if cutting is deferred, with potential wea ther-related losses evaluated using probability forecast information f or the upcoming 24-h period. Specific results for central New York con ditions produce a four-cut system in most years, and indicate that alf alfa preservation as wilted silage is probably preferable to either di rect-cut silage or dry hay. Using weather forecasts to schedule alfalf a cutting is estimated to increase average annual crop value by about 5-10%, while decreasing income variability.