Highlights Method for determining the discoloration of potato tissue samples induced by mechanical stress. Model of the discoloration susceptibility of specific potato tissue. Particle segmentation algorithm in the Discrete Element Method for contact localization in post-processing. Development of the "Discrete Element Method Blackspot Potato Tuber Model" capable of predicting internal blackspot damage in potato tubers. Abstract. Blackspot damage caused by mechanical load during the harvesting and processing stages of potato tubers remains difficult to mitigate. Field tests are inadequate as it takes around two days to develop blackspot discoloration, making it unclear when and where the initial damage occurs. Particle simulation, particularly with the Discrete Element Method (DEM), offers opportunities to improve machine performance and reduce crop losses. However, the DEM cannot predict local blackspot damage, making it unsuitable for reducing potato tuber damage. To address this, the “DEM blackspot potato tuber model” presented in this contribution integrates a discoloration function and a segmentation algorithm of DEM particles to predict and analyze blackspot damage during harvesting and processing. Based on mechanical experiments on tuber tissues with different loading conditions, a discoloration function was proposed dependent on strain and strain rate. The segmentation algorithm adapts to the varying potato tuber particle size by varying the number of segments to generate segments of average blackspot size. Two different validation tests are used to identify the single and multiple impact capabilities of the model. The preliminary results show that the discoloration induced by single impact events is well predicted in terms of the number of damaged tubers as well as the average damage per tuber. Damage of multiple impacts is less accurately predicted since the model does not take into account the accumulation of damage. Keywords: Blackspot, Damage model, Discrete Element Method, Potato handling, Simulation.