ESTIMATING DRYING TIME FOR A STOCK PEANUT CURING DECISION SUPPORT SYSTEM

Abstract

A decision support system to manage commercial peanut drying facilities was developed. Empirical equations topredict peanut drying time were developed using PNUTDRY, a bulk peanut curing model. Input data for the empirical modelincludes daily maximum/minimum ambient temperature, maximum allowable plenum temperature, maximum allowable temperaturerise, initial and final pod moisture content, and airflow rate. Using kernel moisture content instead of pod moisturecontent, as required in the original simulation model, had minimal impact on predicted drying time. Regression equationscomparing actual drying times to estimated drying times had an R2 of 0.72. When data from loads dried with ambient air wereincluded, the R2 decreased to 0.48. The equations presented have been incorporated into a software module to manage peanutcuring facilities, released as FarmSuite by the Peanut Foundation.