IoT-Based Intelligent Environmental Control for Minimizing Spring Onion Bulb Weight Loss: A Grey-Taguchi Optimization

บทคัดย่อ

Post-harvest deterioration of spring onion bulbs presents a significant challenge for smallholder farmers in regions like Nakhon Phanom, Thailand, where high ambient temperatures and fluctuating humidity accelerate crop quality loss. These environmental instabilities contribute to substantial economic losses due to reduced shelf life and market value. This study proposes an integrated solution by developing an Internet of Things (IoT) based intelligent environmental control system, optimized using the Grey-Taguchi L9 method, to minimize weight loss during storage. The experimental setup evaluated nine distinct environmental conditions comprising different combinations of temperature, relative humidity, and light intensity over a three-month storage period. The IoT system enabled real-time monitoring and automated adjustments of key environmental parameters through embedded sensors and actuators. Statistical analysis, including signal-to-noise (S/N) ratio calculations and Grey Relational Analysis (GRA), was employed to determine optimal storage conditions. The results demonstrated that temperature and relative humidity were the most influential factors affecting weight loss, with optimal settings identified as 20°C and 65% RH, respectively. Under these conditions, average weight loss was minimized to 5.2 grams, and the model achieved a high R-squared value of 99.74%. In contrast, light intensity was found to have a negligible effect. This research offers a practical and scalable post-harvest solution for resource-constrained agricultural communities. By combining low-cost IoT technology with multi-response optimization, the proposed system contributes to sustainable agriculture and enhances food security by reducing storage-related losses in perishable crops.