This study addresses the limitations of conventional seed spacing measurement methods, which, although accurate, remain labor-intensive, time-consuming, and unsuitable for real-time field decision-making. The purpose of this research is to develop and validate a real-time closed-loop seeding control system capable of dynamically regulating seed distribution during planting based on in-field feedback signals. The system integrates a mathematical model of the seeding process for inline seeders, incorporating key operational parameters such as tractor speed, mechanical transmission characteristics, and wheel-soil interaction effects. The proposed approach is based on continuous comparison between theoretical and measured seed spacing, enabling automatic correction of seed flow through an embedded actuation mechanism. The methodology combines real-time sensor data acquisition, mathematical modeling, and closed-loop control using a stepper-motor-driven adjustment system. System performance was evaluated using standard error (SE), coefficient of variation (CV), missing seed index (M), multiple seed index (D), and feed quality index (A), along with direct field validation of seed spacing accuracy under different seeding rates and operating speeds. Experimental results demonstrated an 11% reduction in coefficient of variation, a 0.9 cm improvement in mean seed spacing accuracy, a 1.4-point reduction in the missing seed index, and a 0.8-point reduction in the multiple seed index, while the feed quality index improved by 16%. Absolute measurement errors ranged from 0.08 to 0.32 cm, with relative errors between 3.16% and 6.12%, confirming strong agreement between sensor-based and field measurements. The system maintained stable performance across varying tractor speeds, indicating robust adaptive capability. A limitation of the study is that system validation was conducted under controlled field conditions and on a single crop type, which may limit generalization to highly heterogeneous environments. However, the findings demonstrate strong practical potential for low-cost precision seeding systems. The originality of this work lies in demonstrating that real-time seed spacing feedback can be directly used as a control variable for mechanical adjustment without reliance on external positioning systems or prescription maps. This provides a scalable and cost-effective alternative for precision agriculture in resource-limited farming systems, with significant implications for improving seeding efficiency and crop uniformity.