The objective of this work was to evaluate the spatial variability of banana production, in function of physical and chemical variables of soil and of farm physiographic characteristics, in order to select those with the greatest potential for use in site‑specific management program. One hundred thirty productive units of banana clone Williams (Cavendish AAA) distributed in four lots and tree soils units of the farm were georeferenced. The bunch weight and root functionality were determined for each plant, as well as 35 physical and chemical soil variables. The spatial variability of the production was evaluated in function of these soil variables, using four different strategies: axes as covariates; both physic and chemical soil properties as covariates; analysis made by individual plot; and analysis made by soil unit. The individual plot study was the best strategy to model the spatial variability of banana production. This analysis model allowed to set soil variable groups which were significantly correlated and precisely explained more than 69% of the bunch weight inside the plots. These groups of variables are the ones with higher potential for the establishment of a site‑specific management program.El objetivo de este trabajo fue evaluar la variabilidad espacial de la producción de banano en función de variables físicas y químicas del suelo y de las características fisiográficas de la finca, con miras a seleccionar aquellas con mayor potencial de uso en programas de manejo por sitio específico. Se georreferenciaron 130 unidades productivas de banano clon Williams (Cavendish AAA) distribuidas en cuatro lotes de la finca y tres unidades de suelo. Se determinó el peso del racimo y la cantidad de raíz funcional, para cada planta, y 35 variables físicas y químicas del suelo. Se relacionó la variabilidad espacial de la producción en función de las variables del suelo, a partir de cuatro estrategias: ejes coordenados como covariables; variables físicas y químicas del suelo y raíz funcional como covariables; división del análisis por lotes; y división del análisis por unidades de suelo. La división por lotes resultó ser la mejor estrategia para modelar la variabilidad espacial de la producción de banano. El análisis por este modelo permitió establecer grupos de variables del suelo que se relacionaron significativamente y explicaron más del 69% del peso de los racimos de banano dentro de cada lote. Estos grupos de variables son los de mayor potencial para el establecimiento de un programa de manejo por sitio específico.The objective of this work was to evaluate the spatial variability of banana production, in function of physical and chemical variables of soil and of farm physiographic characteristics, in order to select those with the greatest potential for use in site-specific management program. One hundred thirty productive units of banana clone Williams (Cavendish AAA) distributed in four lots and tree soils units of the farm were georeferenced. The bunch weight and root functionality were determined for each plant, as well as 35 physical and chemical soil variables. The spatial variability of the production was evaluated in function of these soil variables, using four different strategies: axes as covariates; both physic and chemical soil properties as covariates; analysis made by individual plot; and analysis made by soil unit. The individual plot study was the best strategy to model the spatial variability of banana production. This analysis model allowed to set soil variable groups which were significantly correlated and precisely explained more than 69% of the bunch weight inside the plots. These groups of variables are the ones with higher potential for the establishment of a site-specific management program
