Erroneous data affect the quality of yield map. Data from combines working close to each other may differ widely if one of the monitors is not properly calibrated and this difference has to be adjusted before generating the map. The objective of this work was to develop a method to correct the yield data when running two or more combines in which at least one has the monitor not properly calibrated. The passes of each combine were initially identified and three methods to correct yield data were tested: a) Machine by machine - (1) select the combine with more data (larger harvested area in the field); (2) compute the average yield value from each combine; (3) a correction factor is generated at each point with the ratio between the average of the combine and the nearest combine; (4) yield data from the nearest combine are multiplied by the correction factor;  (5) if more than two combines are involved, identifies the nearest combine and repeat step (4) and (5) to all combines. b) Track by track - this method is similar to the previous, however the average yield values are extracted only at points within the pass closest to the combine 1 and the pass of the nearest combine. c) Point by point - a correction factor is generated through the medium of yield ratio of the closest points between the combine with the largest harvested area and the nearest combine; yield data will be multiplied by this factor and these steps will be repeated for all combines. It is very important to have the total production and field area for control and comparison.  The closer are the two values, the greater will be the efficiency of post processing of data. The three methods were evaluated by using raw data from corn, cotton and wheat harvesting and were able to correct the data with distinct characteristics. The model should be selected according to each area and with user needs. Therefore, there is no standard method to be used for the correction of yield data.