Performance management in coffee growing: A multivariate analysis applied to coffee production in the main Brazilian regions

This study evaluates the operational performance of Brazil’s leading Arabica and Conilon coffee producers across two harvest cycles (2018–2019 and 2020–2021) using Principal Component Analysis (PCA). As the world’s largest coffee producer facing climate and market challenges, Brazil requires robust metrics to assess productivity-sustainability tradeoffs. The research combines quantitative and qualitative methods through a descriptive, inductive analysis of 33 producers across 12 key regions participating in CIM/UFLA’s Campo Futuro project. Data collection employed semi-structured questionnaires following field research protocols. Key findings reveal distinct production strategies between cycles: the 2018–2019 harvest prioritized intensive input use (fertilizers, correctives, pesticides) to maximize yields, while 2020–2021 showed increased adoption of sustainable practices through targeted technology investments. The PCA-derived performance indices demonstrate: (1) 18% average productivity growth in optimized regions, (2) emergence of sustainability indicators (water/energy efficiency metrics), and (3) comparable benchmarks for cyclical performance assessment. These results provide coffee cooperatives and policymakers with: (a) validated metrics for evaluating sustainable intensification, (b) region-specific best practice guidelines, and (c) a replicable framework for monitoring climate-smart production transitions. The study advances agricultural performance measurement by integrating traditional productivity indicators with emerging sustainability parameters in tropical coffee systems.