A model was developed to predict mushroom substrate temperature during the phase I preparation process. Many mushroom production operations are beginning to use aeration to reduce odors and to reduce the time required to prepare the substrate. However, optimal aeration schemes have not been developed, and many operations use trial-and-error approaches or just set the aeration at a certain cycle. This experiment had two objectives: to develop a simulation model that predicts mushroom substrate temperatures under various aeration conditions, and to observe the effects of various aeration schemes on the substrate temperature. Aeration serves two purposes: to provide oxygen to microorganisms, and to remove heat from the substrate, allowing for better environmental control. The model, developed using the Stella simulation modeling package, is based on energy gains and losses and predicts substrate temperatures to determine optimal processing conditions. Model validation runs show good agreement between predicted and observed substrate temperature values when the model is adjusted to account for lags in the beginning of substrate heating. Overall root mean square error between predicted and observed substrate temperature was 8.1°C, the correlation between predicted and observed substrate temperature yielded an r2 value of 0.89, and the slope and intercept of the predicted vs. observed temperature linear regression curve are 0.975 and 3.10°C, respectively.
|Original language||English (US)|
|Number of pages||11|
|Journal||Transactions of the American Society of Agricultural Engineers|
|Publication status||Published - Jul 1 2004|
All Science Journal Classification (ASJC) codes
- Agricultural and Biological Sciences (miscellaneous)