The development of enhanced multitasking agricultural robots required a greater understanding of the mechanical properties of the crop in question. This study evaluated the physicomechanical properties (mass, failure force, failure energy, and compressibility) of eggplant (Melina F1) fruit to improve the performance of harvesting and sorting robots. Compression loading was applied to eggplant fruits of three sizes (small, medium, and large) at three fruit regions (head, middle and tail). The mechanical testing results revealed that fruit size and fruit region had a significant (p ≤0.01) effect on the mechanical properties of the fruits. The fruit mass increased significantly (p ≤0.01) as the fruit size increased. This study revealed that small fruits had the lowest body mass (225.9 g), while large fruits had the highest body mass (402.8 g). Similarly, the results showed that the failure force and energy increased significantly (p ≤0.01) as the fruit size increased from small to large, with the middle region having the highest values and the tail region having the lowest values. Small berries In terms of fruit compressibility, the results revealed that compressibility increased significantly (p ≤0.01) as fruit size increased from small to large, with the tail region having the highest compressibility and the head region having the lowest. Because agricultural robot optimization entailed optimizing the effectiveness of object identifiers, manipulators, and so on, the data obtained from this study will aid software expertise in developing an advanced agricultural robot for precision operations.
Food security has become a global major problem, due to the rapid increase in population growth. This has necessity the development of an effective agricultural products’ storage system, to alleviate the problem of food wastage. This study was embarked upon to develop a prototype of universal smart storage system for farm products, by using the internet of thing (IoT). The storage structure consists of four principal constituents which were; the power source, storage chamber, central processing system, and peripheral component interconnect (PCI) heater and PCI fan. The developed model was tested at a pre-set temperature and relative humidity of 32C and 62% RH respectively. The results revealed that the developed system had an efficiency of 85%. Though, the smart model had a failure rate of 15%, this smart prototype is a major breakthrough in the production of automated storage system for agricultural products.
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