Alexopoulou, E, Zanetti, F, Scordia, D, Zegada Lizarazu, W, Christou, M, Testa, Giorgio, Cosentino, Salvatore, Monti, A., Scordia, Danilo, Alexopoulou, Efthymia, Zanetti, Federica, Scordia, Danilo, Zegada-Lizarazu, Walter, Christou, Myrsini, Testa, Giorgio, Cosentino, Salvatore L., and Monti, Andrea
Uncertainty in predictions of long-term yields of perennial grasses makes business plans untenable in the short run. Long-term data across varied environments, including marginal lands, will help in preventing uncertainty while providing farmers and entrepreneurs with sound information to estimate reliable and affordable strategies on what, where, and how long to grow perennial grasses. In the present study, the long-term yields (11 to 22years) of switchgrass (Panicum virgatum L.), miscanthus (Miscanthus × giganteus Greef et Deuter), and giant reed (Arundo donax L.) grown in northern and southern Mediterranean environments are reported. Switchgrass was grown in Greece and northern Italy, giant reed in southern and northern Italy, and miscanthus in southern Italy. Furthermore, lowland and upland switchgrass ecotypes were compared in Greece. Despite similar biomass productions (9.8 and 10.0Mg DM ha−1 for uplands and lowlands, respectively), the upland ecotypes showed a significantly higher yield stability (CV of 24 and 32% for uplands and lowlands, respectively) over a 17-year period. Biomass yield varied considerably across years and locations; giant reed outperformed switchgrass under northern Italy environment (21.2 and 13.6Mg DM ha−1 for giant reed and switchgrass, respectively). Annual yield of switchgrass was 30% higher in the north than south Mediterranean; miscanthus showed intermediate production compared to giant reed and switchgrass (average of 22years) and a CV similar to switchgrass. In summary, these results evidence that multi-location, long-term trials are strongly needed to reduce uncertainties on crop yield variability and provide more accurate data from which optimized socio-economic and environmental predictions can be achieved.