Precision agriculture for banana crops has been little investigated so far. The main difficulty to implement precision agriculture methods lies in the asynchronicity of this crop: after a few cycles, each plant has its own development stage in the field. It results in a diversity of the phenological stages within a field and also a continuous production of bananas over time. Therefore, maps of agronomic interest derived from plant responses are difficult to produce using existing methods. This study proposes a mapping approach that handles the diversity of phenological stages and the temporal continuity of production. It explores the feasibility of applying this general approach to a plant response parameter which is the time between flowering and maturity (time to harvest) of banana denoted tfm. The tfm gives an insight into the spatial distribution of vigour. The study was conducted using a large database (more than 395 000 observations) generated by two commercial farms in 2015 and 2016 in Cameroon. The temporal variability of tfm, which is induced by meteorological and operational constraints, and the spatial variability, which is assumed to be due to environmental factors, was assessed by decomposing the tfm variance. This method allowed mapping of the effect of the temporal variability as well as the effect of agri-environmental variables on tfm using a block kriging method. Spatial structures highlighted by this decomposition either at the farm level or at the field level, suggest that the map of the effect of environmental factors on tfm could be used to support agronomic decisions. This idea is reinforced by the identification of factors explaining the environmental variability of tfm and by the temporal stability of the spatial structures.