Finite element analysis of corn kernel damage: a viscoelastic model approach for impact-induced damage prediction

BACKGROUNDIn the present study, we address the quality degradation of corn during post-harvest processing by developing a viscoelastic composite model to predict kernel damage during post-harvest processing. The model, based on high-resolution scanning and inverse modeling techniques, provides an accurate representation of the complex internal components of corn kernels, which allows for the analysis of their stress response and damage susceptibility trends under different impact conditions.RESULTSThe results show that the viscoelastic model has a relative error of 2.4% compared to the drop test data, thus demonstrating that the viscoelastic model has a very high accuracy in predicting impact damage and is able to accurately localize the flour-like endosperm as the main region of impact damage. The model showed a high correlation (0.99) between predicted and experimental damage rates by response surface methodology.CONCLUSIONKernel damage during processing is reduced by reducing the proportion of flour-like endosperm in maize kernels. A new method for reducing damage during food handling and processing operations is proposed, providing an important reference for improving kernel durability and contributing to the development of gentler processing techniques to improve the quality of maize products. (c) 2025 Society of Chemical Industry.