Optimal collection plan of orchards using satellite data and mathematical programming: A case study of mango farmer in rural Cambodia for international cooperation

This study proposes a methodology to support the planning of smart and efficient harvesting techniques within the agricultural sector of developing countries. Even where labour costs are low in developing nations, repeated inefficient harvesting operations result in wasted time, effort, and money. While digital technology has advanced and various applications have been developed, these remain underutilised in developing countries due to cost constraints. Consequently, there is a need to develop methodologies that harness these applications to enhance harvesting efficiency. Therefore, Smart Optimal Collection Planning Method was developed in this research. This method determines the location coordinates of trees from aerial photographs freely available in many countries, including developing nations. It then uses visual or internet of things (IoT) technology to ascertain the number of fruits per mango tree, subsequently devising an optimal collection route that minimises harvesting costs. The proposed method was applied to a mango plantation in Cambodia to investigate optimal collection routes based on the number of harvesters. The results revealed that, compared to existing methods, the proposed approach achieves greater reductions in collection around 47 % time/cost when fewer harvesters are employed. This research is significant because the proposed methodology enables orchard farmers to calculate appropriate labour costs and implement efficient operations. Incorporating this into international cooperation frameworks is expected to contribute to sustainable agricultural support and food security.