Steady-state values of stream properties (species flowrates) of a mineral processing circuit are usually estimated by averaging values sampled during a given time interval. A major source of data inaccuracy is the integration error, i.e. the error generated by the dynamic variations of the stream properties around their steady-state values. The paper shows that these sampling errors are significantly reduced by appropriate reconciliation methods based on material conservation equations. The optimal error compensation is obtained by minimizing a quadratic function where the weighting factors take into account the integration error covariance from stream to stream and species to species. The method is illustrated for a flotation circuit modelled by a state-space representation. The data variance reduction is compared for different weighting strategies of a quadratic reconciliation criterion. For the studied system, it seems that ignoring measurement error correlation, using a standard weighted least-squares criterion instead of the optimal quadratic function, does not degrade too much the ability of the reconciliation procedure to reduce the data variance.