ORIGINAL RESEARCH article
Front. Plant Sci.
Sec. Sustainable and Intelligent Phytoprotection
Volume 16 - 2025 | doi: 10.3389/fpls.2025.1531377
Optimized design and performance evaluation of a highly precise variable rate mis-planting and replanting potato electronic-metering mechanism
Provisionally accepted
- 1Aswan University, Aswan, Aswan, Egypt
- 2Faculty of Agriculture, Mansoura universiy, Mansoura, Egypt
- 3Faculty of Engineering and Information Technology, University of Pécs, Pécs, Hungary
- 4Minia University, Minya, Minya, Egypt
- 5King Saud University, Riyadh, Riyadh, Saudi Arabia
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Precise seed placement during potato planting critically determines crop distribution and density, yet mis-planting remains a persistent agricultural challenge. Current manual detection and correction methods introduce inefficiencies, increase labor costs, and risk human error. To address these limitations, this study developed and evaluated a high-precision variable-rate electronic metering mechanism (EMM) capable of automated mis-planting detection and replanting under controlled laboratory conditions. The EMM was built to operate at different planting distances and travel speeds, with its design focusing on finding the best mechanical setup before testing it in the field at four different planting distances (24.12, 31.06, 34.87, and 41.24 cm) and five speeds (2.13-6.11 km/h). Results demonstrated optimal stability at lower speeds (2.13-3.07 km/h), where sensor accuracy remained consistent, achieving peak performance (QI=98.7%, RI=100%, minimal MPI) at 41.24 cm spacing and 2.13 km/h. Performance degraded significantly at higher speeds (3.94-6.11 km/h), with factorial analysis confirming both speed and spacing as statistically significant factors affecting all indices. Furthermore, the total cost of the developed system was approximately $130 USD. Future experiments will include further field experiments to study the influence of field variables such as soil type, surface irregularity, and environmental disturbances on the performance of the EMM.
Keywords: precision agriculture, Internet of Things, machine learning, qualified index, mis-planting index, seed monitoring system
Received: 21 Nov 2024; Accepted: 21 Apr 2025.
Copyright: © 2025 Elwakeel, Elbeltagi, Salem and Dewidar. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Ali Salem, Faculty of Engineering and Information Technology, University of Pécs, Pécs, Hungary
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