EFFECT OF TEMPERATURE ON MOISTURE SORPTION ISOTHERMS AND MONOLAYER MOISTURE CONTENT OF BERMUDA GRASS (CYNODON DACTYLON)
Keywords:
equilibrium relative humidity, drying, Bermuda grass, artificial neural networksAbstract
Bermuda grass is widely grown in Saudi Arabia as a turf grass. It is highly tolerant to drought and hot weather. It can be
compressed to form pellets, which can be used as livestock, or energy pellets similar to charcoals. Drying is required to process
the grass into a safe storage condition. Moisture sorption isotherms are required to design and optimize the drying process
of the grass. Therefore, moisture sorption isotherms were studied using gravimetric methods at temperatures ranging from
20 to 40oC. Both conventional analytical moisture sorption isotherms (MSI) and artificial neural networks (ANNs) were used
to model the relationship between equilibrium moisture content (EMC) and equilibrium relative humidity (ERH). The results
showed that Modified Halsey equation was the best representative of MSIs. However, ANNs were also found to outperform
MSI analytical models with R2 = 0.991 and a root mean square error (RMSE ) = 1.17. Monolayer moisture content was also
found to decrease linearly with EMC from 0.074 to 0.047 (decimal w.b.) over the temperature range investigated.
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