Analysis of the impact of damage rate on the performance of orange fruit harvesting robot
| dc.contributor.author | Zeeshan ,Sadaf | |
| dc.contributor.author | Aized, Tauseef | |
| dc.contributor.author | Riaz , Fahid | |
| dc.date.accessioned | 2026-01-22T07:58:00Z | |
| dc.date.available | 2026-01-22T07:58:00Z | |
| dc.date.issued | 2025 | |
| dc.description | The importance of damage rate in robotic orange picking extends far beyond the operational efficiency; it is fundamentally linked to the commercial success and sustainability of agricultural enterprises. While achieving a high success rate in harvesting operations is undoubtedly crucial for productivity, the quality of the harvested fruit is equally paramount. High damage rates not only result in financial losses due to spoiled or inferior-quality fruit but also tarnish the reputation of the brand or orchard. In today's discerning market, consumers prioritize not only quantity but also quality when making purchasing decisions. Fruits that are bruised, punctured, or otherwise damaged during harvesting not only result in lower prices but also face increased rejection rates from retailers and consumers alike. Therefore, minimizing damage rates is imperative not only for maximizing yield but also for ensuring the long-term viability and competitiveness of agricultural businesses in a market increasingly driven by quality and sustainability considerations. | |
| dc.description.abstract | Reducing damage rates is paramount for optimizing the efficiency of fruit harvesting robots and advancing their journey towards commercial viability. Despite the crucial role that damage rates play in determining fruit quality and marketability, there is a notable lack of comprehensive and in-depth studies analyzing this aspect, especially within the context of fruit harvesting robots. Most research tends to prioritize metrics such as success rate and accuracy of fruit picking, leaving the examination of damage rates relatively overlooked. This study fills this gap by conducting a thorough examination of the factors contributing to damage rates in fruit harvesting robots, including the causes of damage, the types and sizes of bruises incurred, and the impact of occlusion, illumination conditions, and end effector orientation. Additionally, the research investigates strategies for minimizing damage rates, offering insights into optimizing fruit harvesting techniques to reduce potential damage. Occlusion, illumination, and gripper angle were found to significantly influence fruit damage. Specifically, a 10 % increase in occlusion raised damage by 1.18 %, a 100 Lumen/m2 increase in illumination reduced damage by 10.5 %, and deviation from the optimal 90° gripper angle increased damage by 1.8 % per 10° shift. Overall, proper fruit orientation reduced damage by 40 %, minimal occlusion by 36 %, and optimal illumination by 25 %. A multiple linear regression model explained the variance in damage rate (R2 = 0.924) and achieved a low RMSE of 1.85 %, demonstrating high predictive accuracy and validating the model’s reliability in quantifying the influence of harvesting parameters. By investigating these aspects and exploring strategies for minimizing damage, the study aims to advance fruit harvesting robotics and contribute to the successful commercialization of this technology. Keywords Fruit harvesting robot, Occlusion, Damage rate, Fruit bruise, Fruit orientation, Illumination | |
| dc.identifier.citation | Zeeshan, S., Aized, T., & Riaz, F. (2025). Analysis of the impact of damage rate on the performance of orange fruit harvesting robot. Ain Shams Engineering Journal, 16(11), 103735. | |
| dc.identifier.doi | https://doi.org/10.1016/j.asej.2025.103735 | |
| dc.identifier.uri | https://repository.adu.ac.ae/handle/1/8078 | |
| dc.language.iso | en | |
| dc.publisher | Elsevier | |
| dc.title | Analysis of the impact of damage rate on the performance of orange fruit harvesting robot | |
| dc.type | Article |