Operational and economic impacts of sugarcane row gaps

• Ano de defesa: 2025
• Autor(a) principal: Silva, Eudocio Rafael Otavio da
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Biblioteca Digitais de Teses e Dissertações da USP
• Palavras-chave em Português: Agricultura de precisão; Custo de oportunidade; Data filtering; Filtragem de dados; Opportunity cost; Precision agriculture; Remote sensing; Sensoriamento remoto
• Link de acesso: https://www.teses.usp.br/teses/disponiveis/11/11152/tde-07012026-181047/

The profitability and longevity of sugarcane (Saccharum spp.) cultivation are compromised by row gaps, which represent an underutilization of the field\'s productive potential. Although their occurrence is widely recognized, an analysis that economically quantifies their impacts, considering the spatial variability of the sugarcane field, constitutes a breach in the literature. This thesis hypothesizes that the economic impact of a gap is site-specific, depending on the productive potential of the area where it is located. Accordingly, the objective was to investigate the operational and economic impacts of gaps in sugarcane rows by modeling their financial effects on yield to support row-level management decisions. To this end, the study was structured into three complementary chapters. Chapter 1 conducted a chronological literature review on \"sugarcane row gaps\" (1900-2025), identifying 23 central studies. The analysis revealed that, despite methodological advances (from manual measurement to automated methods), knowledge has remained fragmented, with limited operational translation and underexploration of the economic impacts of gaps. For Chapters 2 and 3, commercial sugarcane fields located in São Paulo, in the Central-South region of Brazil, were explored, under different varieties, cuts, and field management; their respective mechanized harvest data and data on row reconstitution and gap distribution were obtained using unmanned aerial vehicle (UAV). In Chapter 2, an automatic filtering algorithm for yield data was developed and validated, based on a sliding window with variable statistical thresholds. The proposed filter eliminated the subjectivity of the cleaning process and preserved yield variability, achieving nearly 100% detection of medium and large outliers, enabling robust analyses (necessary for subsequent economic analyses). Chapter 3 addressed the breach identified in Chapter 1 by integrating high-resolution gap maps (obtained by UAV) and yield data to quantify unearned production and its associated costs. The results confirmed the central hypothesis: gaps of the same length result in distinct economic impacts, with the opportunity cost being significantly higher in high-yielding potential rows. The analysis of datasets from first to third ratoon fields revealed that 30-40% of the rows concentrate ≥70% of the economic costs (aligning with the Pareto Principle), which can optimize the prioritization of interventions, such as localized replanting and input applications in ON/OFF controller systems. A critical gap threshold of ≈16% was identified for ratoon cane, although this value is field-specific, reinforcing the need for localized modeling. It is concluded that the decision to replant or renovation must surpass the mere average percentage of gaps, based on an integrated analysis of multiple data layers (gap maps, yield, and economic and opportunity costs). This study provides a comprehensive framework from historical understanding to methodological development and economic analysis that redefines gaps as a primary variable for decision-support systems, enabling management that simultaneously optimizes longevity, profitability, and sustainability of sugarcane fields.