Estimating Energy Costs of Nonbeneficial Dryer Operation by Using a Peanut Drying Monitoring System

Abstract

Abstract. Knowledge of kernel moisture content during peanut drying is important to ensure that the bed of peanuts is dried appropriately. However, the lack of a commercially available, industry-accepted solution for real-time kernel moisture content determination during peanut drying makes its detection cumbersome and laborious. Samples of unshelled peanuts are extracted from the semitrailer by an operator periodically, and the samples have to be cleaned and shelled to determine kernel moisture content with the official meter. A peanut drying monitoring system that includes a microwave kernel moisture sensor, developed within the USDA ARS, provides a means for monitoring in-shell kernel moisture content in real-time. The system determines kernel moisture content with a standard error of prediction (SEP) of 0.55% moisture content when compared to the reference oven-drying method. During recent peanut harvest seasons, peanut drying monitoring systems were placed in 13.7-m (45-ft) drying semitrailers, one 3 m (10 ft) from the front of the trailer and the other 3 m (10 ft) from the back of the trailer. As the peanuts dried, pod and kernel moisture content, temperature of the drying peanuts, temperature and relative humidity of the air exhausted from the peanuts, and temperature and relative humidity of the air being blown into the peanuts were measured every 12 seconds. The continuous data, provided by the monitoring systems, were useful in observing the loss of moisture by the peanuts throughout drying. The data also revealed periods of at least 3 hours during which dryer operation did not result in loss of moisture from the peanuts; thus, identifying nonbeneficial dryer operation. Such periods cause a peanut buying point to accumulate unnecessary expenses for propane and/or electric energy which can total up to $3,250 annually for an average-size buying point. Keywords: Dielectric properties, Energy cost, In-shell kernel moisture content, Microwave sensing, Peanut drying, Real-time monitoring, Sensors.