Moreover, another decision tree analysis was performed including the three mineralogical groups, the gathered data about physicochemical parameters and the microbial community composition and function from the PLS. The PLS temperature and the MPN were the most relevant factors selected to explain the differences between the operation of the defined groups of strips. The group with the lowest chalcocite and highest chalcopyrite content, reached the highest PLS temperature and the highest MPN of ferrous iron oxidizing microorganisms and also the fastest kinetics of copper recovery.
The estimated temperature inside the heap following conservatively the available models for heaps loaded with agglomerated material, together with the sustainable occurrence of a moderate thermophile population and the confirmation of some chalcopyrite dissolution by analysis of tail allowed us to account the chalcopyrite as a microbial substrate in that industrial scale operation.
Those results confirmed the relationship between the microbial community function and the copper release and the hypothesis that the substrate availability is an important parameter to describe the microbial activity. Nevertheless, the model is not yet able to explain the low bacterial growth in the group with the highest chalcocite content that is considered a good microbial substrate. Then it is needed to perform another cycle of the KDD process to complete the model. This kind of information should be considered in defining models to describe and to predict copper recovery in ROM industrial bioleaching processes.