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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Sugarcane Harvester for In-field Data Collection: State of the Art, Its Applicability and Future Perspectives

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Corredo, Lucas de Paula [1] ; Canata, Tatiana Fernanda [1] ; Maldaner, Leonardo Felipe [1] ; de Lima, Jeovano de Jesus Alves [1] ; Molin, Jose Paulo [1]
Total Authors: 5
[1] Univ Sao Paulo, Precis Agr Lab, Dept Biosyst Engn, Luiz de Queiroz Coll Agr, BR-13418900 Piracicaba, SP - Brazil
Total Affiliations: 1
Document type: Review article
Source: SUGAR TECH; v. 23, n. 1, p. 1-14, FEB 2021.
Web of Science Citations: 7

Sugarcane harvesters have a high level of embedded technology and the opportunity to expand applications to become an important high-density data collection machine. The acquired data, such as yield, losses, and quality, would provide valuable information for site-specific management of sugarcane. This review describes the current instrumentation used by sugarcane harvesters to map yield with the current technologies that have the highest potential applications for losses and quality mapping. In sugarcane cultivation, the harvester cuts and processes the product along a single or double row, which makes it easier to evaluate yield, losses, and quality at the row level. However, studies that explore the holistic potential of the sensors and data processing from the harvester for within-row detailed spatial information are scarce. Over the years, several studies focused on sugarcane yield mapping; however, yield monitors are far from being popular among sugarcane producers due to its low accuracy. Yield monitors need to be robust and accurate; the data generated from default factory-installed sensors is a potential alternative to improve data collection. Also, the integration of the current data available on the harvesters and the use of sensors to estimate sugarcane parameters (i.e., yield, losses, and quality) may represent an important advance in the agricultural operations. This article provides some information regarding the automation of the machines and the operational improvements, such as logistics planning and machine performance. (AU)

FAPESP's process: 18/25008-8 - Sugarcane qualitative attributes determination and mapping by spectral sensors
Grantee:Lucas de Paula Corrêdo
Support Opportunities: Scholarships in Brazil - Doctorate