The results showed the potential of a robust and reliable predictive model using multiple biomass species, with great variability in the chemical composition. Furthermore, this alternative sampling approach avoids some problems, such as expensive costs and time-consuming collection of diverse sample throughout years and different locations, favoring the fast biomass compositional analysis. In this work, three biomasses were investigated but this number can be even higher for a biomass belonging to the same applicability domain.