Designing a drone-based system for optimized seed ball deployment in reforestation applications

Drone-based system for seed ball deployment in aerial reforestation offer an innovative and efficient approach for restoring degraded ecosystems sustainably. This study primarily focuses on the design and development of a drone equipped with an automated seed ball dispensing mechanism for aerial reforestation applications. The developed drone system has a thrust-to-weight ratio of 1.8, ensuring stable flight performance during the aerial reforestation operations. The system enables controlled seed ball release using a servo-actuated mechanism and GPS-assisted positioning. The second objective of this study is to optimize seed ball parameters and dropping height to enhance aerial delivery and germination performance in reforestation. Taguchi analysis indicated that seed ball composition and dropping height have a greater influence on germination than seed ball weight. A composition, consisting of compost and mud, with a seed ball weight of 40 g, and a dropping height of 2 m, was found to be the optimal. The statistical influence of the parameters on the germination rate was further analysed using ANOVA. Finally, a predictive regression model was developed to estimate germination time based on seed ball composition, weight, and release height, and its accuracy was validated through confirmatory experiments. Thus, this work presents a practical, data-deriven approach for aerial reforestation that integrates optimized seed ball design with drone-based seed ball deployment to enhance ecological restoration outcomes.