Jaime Hernán Caicedo Angel, Andrés Fernando García García, Julián Eduardo Antia Castaño, Jesús Adrián Díaz Bravo, David Alejandro Narváez
Colombian Sugarcane Research Center – Cenicaña, Km 26 Cali – Florida, Florida, Colombia: jcaicedo@cenicana.org
Precision agriculture has transformed the agricultural sector, especially in sugarcane farming, by increasing its efficiency and productivity using self-guided machinery, RTK drones, and robots, However, factors such as uncontrolled traffic, diversity of machinery brands, and differences in instrumentation among machines, alongside with the high cost of RTK mobile stations and the lack of standardization in correction signals, have hindered a widespread adoption of this technology. These challenges have affected the quality and monitoring of tasks, leading to increased soil compaction and trampling, and negatively impacting productivity and crop sustainability. The implementation of GNSS-based auto guidance technologies with RTK (Real Time Kinematic) correction has proven to be an effective solution, however, the cost and complexity of RTK mobile stations make their use impractical and imprecise. This paper presents the impact of a large-scale, multipurpose sectoral RTK network, which facilitates the scalability of various technologies, reduces implementation costs and encourages the adoption of new solutions. Installed and managed by Cenicaña since 2018, this RTK network consists of 10 base stations and 8 repeaters, covering 80% of the 240,000 ha of sugarcane fields in the Cauca River Valley. It is compatible with technologies from brands such as John Deere, Case, Trimble, and Topcon, and has optimized agricultural operations such as plowing, planting, and mechanized harvesting. Furthermore, it supports compatibility with computer vision products, such as post-processing drone images through kinematic post-processing (PPK) flights. This project demonstrates that a joint investment of an organized sector, with a shared goal, is both feasible and profitable.