Revolutionizing the Harvest: A Technical Review of the Meicott PT120 Cotton Monitoring System and Its Impact on Agricultural Traceability
DOI:
https://doi.org/10.65888/icraft.2.1.25Keywords:
Meicott, Cotton Harvesting, Digital Farming, Yield MonitoringAbstract
This paper provides a technical review of the Meicott PT120, a retrofittable system de-signed for cotton harvesting machines to provide real-time yield detection, moisture monitoring, and data logging. The primary challenge addressed is the lack of integrated digital weighing and tracea-bility systems in much of the existing cotton harvesting machinery, which leads to potential value loss and inefficiencies, particularly in accurately measuring yield and tracking the quality of harvested cotton. This review synthesizes information from academic literature on smart farming [1; 2; 3] and a detailed technical test report from the SÖKE Agricultural Training Center [4]. The methodology involved analyzing the system's components—including its control unit, hydraulic pressure and opti-cal sensors, moisture unit, and GNSS module—and the results of laboratory and field tests [4]. The findings indicate a high degree of accuracy, with an error margin between 0.1% and 0.9% when com-pared to certified scales [4]. The discussion highlights the system's significant benefits, including enhanced traceability, data-driven decision-making for farmers, contractors, and industrialists, and the provision of reliable, parcel-level data for governmental agricultural policy and support distribu-tion. The paper concludes that the Meicott PT120 is a viable and effective technology for modernizing the cotton value chain, aligning with the broader goals of precision agriculture.
References
1. Elijah, O., Rahman, T. A., Orikumhi, I., Leow, C. Y., & Hindia, M. N. (2018). An overview of the Inter-net of Things (IoT) and data analytics in agriculture: benefits and challenges. IEEE Internet of Things Jour-nal, 5(5), 3758-3773. https://doi.org/10.1109/JIOT.2018.2844392
2. Khanna, A., & Kaur, S. (2019). Evolution of Inter-net of Things (IoT) and its significant impact in the field of Precision Agriculture. Computers and Elec-tronics in Agriculture, 157, 218-231. https://doi.org/10.1016/j.compag.2018.12.039
3. Sharma, A., Jain, A., Gupta, P., & Chowdary, V. (2020). A review on smart farming technologies. In-ternational Journal of Agricultural and Statistical Sciences, 16(1), 329-335.
4. Anonymous, Zirai Üretim İşletmesi Tarımsal Yayım ve Hizmetiçi Eğitim Merkezi Müdürlüğü. (2023). Deney raporu: Pamuk toplamama-kinalarıverimtespitvenemtakipsistemi (Meicott Marka, PT120 Model, GNSS Alıcılı) (Report No: 2023/189). Söke, Turkiye.
6. Liu, R.; Sun, Y.; Li, M.; Zhang, M. Development and application experiments of a grain yield monitor-ing system. Comput. Electron. Agric. 2022, 195, 106851.
7. Cheng, S., Han, H., Qi, J., Ma, Q., Liu, J., An, D., & Yang, Y. (2023). Design and experiment of real-time grain yield monitoring system for corn kernel harvester. Agriculture, 13(2), 294
Published
Issue
Section
License
Copyright (c) 2026 Agricultural and Food Technologies

This work is licensed under a Creative Commons Attribution 4.0 International License.
This journal is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). This license permits anyone to copy, redistribute, remix, transmit and adapt the work provided the original work and source is appropriately cited.
