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531.
Subir Kumar Chakraborty A. Subeesh Rahul Potdar Narendra Singh Chandel Dilip Jat Kumkum Dubey Pramod Shelake 《野外机器人技术杂志》2023,40(6):1581-1602
The modernization of postharvest operations and penetration of emerging technologies in horticultural processing have provided intelligent solutions for reducing postharvest losses. Work environmental and occupational health issues require immediate attention as the awkward posture and continuous drudgery-prone on-farm sorting and grading activities may lead to musculoskeletal disorders. The main objective of this study was to develop an automatic farm-friendly machine for real-time citrus fruit washing, image-based sorting, and weight grading; designed optimally and equipped with an embedded system comprising a lightweight convolutional neural network (CNN) model. Also included in this study was a thorough ergonomic assessment of the developed machine in a real work environment. The parametric choice of the fruit washing and singulation system was performed by employing computational fluid dynamics modeling and response surface methodology designed optimization. It was observed that under steady-state conditions, the water jet would arrive at a velocity of 11.36 m/s which would eventually suit a singulation conveyor with a slope of 25°. A noninvasive grading and sorting approach for citrus fruits is presented in this paper that leverages deep learning to classify the fruits into “accept” and “reject” classes. The custom lightweight CNN model “SortNet” has shown excellent classification results with an overall accuracy of 97.6%. The ergonomic evaluation shows that the average body part discomfort score in case of operating an automatic fruit grading machine was much lower (12.3 ± 2.0) than the traditional method (30.9 ± 3.3). Further, in the case of machine operation, the percentage load on the muscles ranged from 28.67 to 34.31 reflecting that subjects can work for longer duration on the machine without fatigue as compared with the traditional manual operation. 相似文献
532.
Merugu Narendra Kishore Manapuram Saikumar Chakraborty Tanushree Karanam Sita Kumari Imandi Sarat Babu 《Food science and biotechnology》2023,32(5):599-620
Food Science and Biotechnology - Mutagens are chemical molecules that have the ability to damage DNA. Mutagens can enter into our body upon consumption of improperly cooked or processed food... 相似文献