Abstract: Precise sowing is one of the most fundamental procedures in modern agriculture. The quality of seed placement within the furrow can directly influence the maize yield, uniformity, and resource efficiency. Conventional seed metering monitoring systems can often rely on the optical or piezoelectric sensors that are mounted on the seed tube. Since they can only infer the seed flow from the metering device, they cannot assess the actual final quality of seed placement within the seed furrow after deposition. Some influencing factors (such as the seed bounce, furrow opener-induced soil disturbance, and covering dynamics) can also alter the seed spatial distribution, leading to the undetected miss-seeding or multi-seeding events. The compromise can also reduce the harvest potential. In this study, an integrated system was developed and then validated for the direct detection and assessment of the seeding quality in the furrow. A flexible piezoresistive sensor array was seamlessly integrated into the seed pressing tongue. There was direct contact with the seeds and soil in the closed furrow, thus ensuring intimate interaction with the seeding environment. Three primary components consisted of: the flexible piezoresistive sensor array embedded at the bottom of the seed pressing tongue, where the subtle pressure was captured when seeds passed through; a central controller for data acquisition from the real-time signals with minimal latency; and a signal processing module to interpret the raw data using advanced algorithms. The signals of the dynamic pressure were generated as the seeds went beneath the press wheel. Each seed shared a distinct pressure signature using its size, shape, and mechanical properties. The sensor array was used to record the number, duration, and intervals of the high-level output signals. The signal analysis was carried out to distinguish between the transient pressure spikes of individual seeds and the overlapping seeds, and the prolonged signals of multiple seeds in close proximity. Thereby, the misses and multiple seeding events were evaluated even in the challenging fields. An experimental protocol was executed to validate the system. Initial performance tests were conducted on the sensor to define its response curve, spatial sensitivity, and its ability to differentiate between the mechanical impedance of seeds and soil. Subsequently, a seed displacement test was carried out, where the seeds were tracked using high-speed cameras. The seeds were displaced significantly beyond their intended positions after the press wheel's action, in order to evaluate the seeding quality. Single-factor experiments were then performed to investigate the effects of the soil moisture content and forward speed on the detection accuracy, with each parameter varied while the rest was constant to isolate their impacts. Finally, a field validation test was conducted over three soil types under varying weather. The system's performance was then verified under real-world conditions, including temperature fluctuations and minor terrain undulations. The seed displacement test results show that the seed movement caused by the press wheel had a negligible impact on the quality assessment, with the average displacement at less than 5mm, fully meeting the acceptable tolerances during precise seeding. System performance shared a slight correlation with the forward speed. The accuracy decreased minimally as speed increased, likely due to the reduced signal resolution at higher velocities. Furthermore, the recognition accuracy for both single and overlapping seeds exceeded 98.0% at the lower speeds (4-6 km/h), indicating the exceptional precision. Meanwhile, the accuracy remained remarkably high (above 96.2%) even at higher operational speeds (6-10 km/h), indicating the effective function in the typical field operations. The optimal performance was achieved within a soil moisture content range of 15% to 25%, with the accuracy dropping slightly outside due to the soil's mechanical properties under pressure transmission. The overall detection errors were no greater than 0.39% and 1.39% at the low and high speeds, respectively, indicating the excellent robustness and adaptability in the varying environmental conditions. The better performance was achieved, compared with the previous indirect systems, on the assumption of seed flow. In conclusion, the system can be expected to effectively in-situ monitor the seeding quality within the seed furrow. The finding can provide a highly accurate and robust technical solution to reduce the input costs for high crop productivity, with potential applications in seed placement. A valuable reference can also offer guidance for the next-generation seed monitoring technologies in precision agriculture.