The High Performance Computing (HPC) community aimed for many years to increase performance regardless of energy consumption. Until the end of the decade, a next generation of HPC systems is expected to reach sustained performances of the order of exaflops. This requires many times more performance compared to the fastest supercomputers of today. Achieving this goal is unthinkable with current technology due to strict constraints on supplied power. Therefore, finding ways to improve energy efficiency become a main challenge on state-of-the-art research. The present paper investigates energy efficiency on heterogeneous CPU+GPU architectures using a scientific application from the agroforestry domain as a case-study. Differently from other works, our work evaluates how the workload of the application may affect energy efficiency on hybrid architectures. Results point out that the power supplier constraints depend also on the workload.