Joel Morales1,2, Mario Muñoz1, Amílcar Velazquez1 and David Mera2
1Agricultural production, Azucarera Nacional. 0201 El Roble, Dist. Aguadulce, Coclé, Panamá; Joel_gua@hotmail.com
2Computer Graphics and Data Engineering (COGRADE), Department of Electronics and Computing, University of Santiago de Compostela, 15782 Santiago de Compostela, Spain
The objective of this paper was to describe the integration of information, algorithms, and technologies for quantitative risk assessment through forecasts, with the aim of optimizing agricultural management and achieving productivity and unit cost targets. Since 2022, at Azucarera Nacional, located in the central region of Panama, innovations in work planning and budgeting have been implemented, based on long-term climate and production forecasts. Teleconnections, such as the ENSO (El Niño-Southern Oscillation) index, were used to adjust the management plan and available resources, maximizing production. Additionally, digital monitoring tools, such as chlorophyll meters, soil-moisture sensors, and plant-tissue nutritional analysis, were integrated with short-term production forecasts based on satellite imagery and vegetation indices such as NDVI (Normalized Difference Vegetation Index). These technologies enabled precise identification of crop needs and evaluation of the positive effects of the applied management, facilitating the estimation of the impacts on final production. The agile and detailed integration of all this information reduced the risks associated with management decisions, achieving favorable results in the 2024 harvest. These included a 14.4% increase in cane yield per hectare, a 10.5% increase in sugar yield per hectare, and a reduction in unit production costs of standing cane by 18.8% in $/t cane and 9.7% in $/t sugar compared to the previous year.