MODELING OPTIMAL ALFALFA HARVEST SCHEDULING USING SHORT-RANGE WEATHER FORECASTS

Alfalfa (Medicago sativa L.) harvest is ideally scheduled to avoid rain 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 cutting decision is faced daily, and it must balance increasing yield and decreasing forage quality if cutting is deferred, with potential weather-related losses evaluated using probability forecast information for the upcoming 24-h period. Specific results for central New York conditions produce a four-cut system in most years, and indicate that alfalfa preservation as wilted silage is probably preferable to either direct-cut silage or dry hay. Using weather forecasts to schedule alfalfa cutting is estimated to increase average annual crop value by about 5-10%, while decreasing income variability.