Prediction, generation, and propagation of banana (Musa spp.) latent damage based on dynamic finite element method and multi-objective optimization method

초록

To address the problem of latent bruising in bananas during post-harvest operations, which makes early detection and accurate quantification difficult, a reverse engineering method was first used to establish three-dimensional solid models of three main banana varieties. Simultaneously, quasi-static mechanical property testing was conducted to obtain the multi-scale mechanical properties of the fruit (including peel and pulp) under different environmental conditions. Based on this, a dynamic model for fruit damage detection was constructed using the dynamic finite element method, and a total of 1944 virtual collision scenarios were set up, including different varieties, impact speeds, temperature and humidity, Young's modulus, and contact angles. Finally, by combining the response surface methodology based on empirical prediction models and the multi-objective optimization method based on physical experiments, the comprehensive effects of the interactions between experimental factors on fruit damage were qualitatively and quantitatively clarified. The results showed that key parameters used to qualitatively characterize the extent of damage (such as stress, contact force, and energy) varied depending on the experimental factors, which directly affected the mechanisms of internal damage caused by fruit dropping. Furthermore, the empirical models developed for quantitatively assessing bruising all achieved prediction accuracies exceeding 97%; and when the impact speed was 3.454 m/s and the contact angle was 0.3 °, packaging boxes or cushioning made of polyethylene were found to better protect the fruit from damage. This study demonstrates that dynamic finite element analysis and multi-objective optimization methods can effectively assist in the quantitative characterization and precise assessment of latent fruit damage during the robotic harvesting and sustainable storage and transportation of bananas. © 2026 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

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