Precision agriculture (PA) has been adopted in many countries and crop and country specific technologies have been implemented for different crops and agricultural practices. Although PA technologies have been developed mainly in countries such as USA, Europe, Australia, where field sizes are large, need of PA technologies has been also drawn in countries such as Japan and Korea, where field sizes are relatively small (about 1 ha). Although principles are similar, design concept and practical implementation of PA technologies shows variations by country due to agricultural conditions such as field and crop characteristics. Information on crop yield and quality is one of the most important data for successful implementation and evaluation of the PA systems. For this purpose, yield monitoring systems have been developed for different crops and harvesters. Yield monitoring system usually consists of components for real-time sensing and monitoring of the harvesting parameters in the harvester, and components to process the collected data and create yield maps in the office. Recently, a 55-kW full feed type combine harvester was developed to meet Korean field and cropping conditions. The target crops were soybean, rapeseed, barley, and wheat, normal operating speed was 1.7 m/s, and harvesting width was 2 m. In this paper, a post-processing software was developed to handle data for the 55-kW multi-crop combine harvester. The yield monitoring system consisted of an ultrasonic array grain flow sensor, a capacitance type grain water content sensor, an ultrasonic cutting width sensor, and a GPS receiver. Data from the yield monitoring system contained errors due to 1) unstable sensor performance (e.g., GPS signal loss), 2) changes in grain flow and traveling speed (e.g., sudden change), 3) transportation delay between the cutting and sensing locations, 4) and start and stop delay. First, available post-processing programs were surveyed, and the main functions were analyzed. Then, menu systems were designed and coded. Finally, the performance was demonstrated using the available data collected in Korean fields. The post-processing software will be improved through further tests and evaluation.