Identification and measurement of gaps within sugarcane rows for site-specific management: Comparing different sensor-based approaches

Mapping Gaps in Sugarcane by UAV RGB Imagery: The Lower and Earlier the Flight, the More Accurate

“…Dynamics of growth and development and how it impacts on imaging is instrumental for analyzing the crop at specific stages, not only one portion but also for the entire cycle and without distinction. These are apparent limitations of earlier studies by Luna and Lobo [1], Souza et al [2] and Maldaner et al [3]. A series of flights to monitor the crop at sprouting, tillering and elongation could require an additional investment.…”

“…An advantage of our study, relative to existing literature [1][2][3], is the possibility of realistically mapping gaps without the need of an onboard photoelectric sensors and in-site calibration. An onboard photoelectric sensor by Maldaner et al [3] can perform accurate mapping. However, it requires an agricultural machine and experts for calibration.…”

“…It produces an accuracy of about 0.35 m. An onboard ultrasonic sensor can map gaps in sugarcane as accurately as a UAV. However, it is not as competent as an onboard photoelectric sensor [3]. The RMSE for the prediction of gap's length upon data from photoelectric sensor is about 0.20 m. The technology can outperform the ultrasonic sensor and vegetation index in mapping gaps.…”

“…Mapping gaps in sugarcane is instrumental for its sustainable production on an industrial scale. It provides support to producers for making decisions on replanting and fertilizing [1][2][3]. A method by Stolf [4] to determine gaps consists of measuring spaces between stalks larger than 0.5 m every 0.5 m along a 100-m sampling line.…”

“…UAVs are versatile. They can level the cost-effectiveness of commercially producing sugarcane [1][2][3]. Plainly, UAVs prove useful for sugarcane production.…”