| Summary: | Intensive greenhouse agriculture annually produces large amounts of residues. The present work focused on the study of the dynamic adsorption of cobalt from aqueous solutions over a vegetal residue from intensive greenhouse cultivation. The influence of three operating variables, feed-flow rate, inlet concentration of cobalt and bed height, was analyzed. According to the results, the variable that particularly affected the percentage of cobalt adsorbed was the feed-flow rate. The results were also fitted to an adaptive neuro fuzzy system (ANFIS) model to predict cobalt adsorption from aqueous solutions and choose the most favorable operating conditions. Results were evaluated using root mean squared error (RMSE), coefficient of determination (R2) and other typical statistic factors as performance parameters. The experimental and model outputs displayed acceptable result for ANFIS, providing R<sup>2</sup> values higher than 0.999 for both cobalt removal (%) and biosorption capacity (mg/g). In addition, the results showed that the best operating conditions to maximize the removal of cobalt were 4 mL/min of feed-flow rate, 25 mg/L of inlet concentration and 11.5 cm of bed-height.
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