摘要：

The main solid waste generated in the olive oil production process is the olive cake (OC). However, one main drawback of using this waste product as biomass source is the cost of transport which is close related with its water content. Thus, the drying process contributes to a cleaner production with a significant reduction in the cost of transport and consequently it will be possible to improve the use of this waste product as bioenergy. The drying rate is one of the most relevant variables when performing an accurate modelling of rotary driers. To obtain the drying rate experimental, an accurate fitting of this variable as a function of parameters, such as gas temperature and speed, layer sample thickness and moisture content is required. In this sense, this work starts describing in detail the drying kinetics in OCs. Subsequently, several parametric approaches based on linear and non-linear functions have been assessed. With this contribution, it has been highlight that artificial neural networks (ANN) with automatic regularization are the best method to perform a mathematical fitting function of this variable. Consequently, drying kinetics for OCs open up new perspectives for the use of this waste product as bioenergy.

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