“…In recent years, the FBA approach has been applied to several different plant species, such as maize (Zea mays;Dal'Molin et al, 2010;Saha et al, 2011), barley (Hordeum vulgare;Grafahrend-Belau et al, 2009b;Melkus et al, 2011;Rolletschek et al, 2011), rice (Oryza sativa; Lakshmanan et al, 2013), Arabidopsis (Arabidopsis thaliana; Poolman et al, 2009;de Oliveira Dal'Molin et al, 2010;Radrich et al, 2010;Williams et al, 2010;Mintz-Oron et al, 2012;Cheung et al, 2013), and rapeseed (Brassica napus; Schwender, 2011a, 2011b;Pilalis et al, 2011), as well as algae (Boyle and Morgan, 2009;Cogne et al, 2011;Dal'Molin et al, 2011) and photoautotrophic bacteria (Knoop et al, 2010;Montagud et al, 2010;Boyle and Morgan, 2011). These models have been used to study different aspects of metabolism, including the prediction of optimal metabolic yields and energy efficiencies Boyle and Morgan, 2011), changes in flux under different environmental and genetic backgrounds (Grafahrend-Belau et al, 2009b;Dal'Molin et al, 2010;Melkus et al, 2011), and nonintuitive metabolic pathways that merit subsequent experimental investigations (Poolman et al, 2009;Knoop et al, 2010;Rolletschek et al, 2011). Although FBA of plant metabolic models was shown to be capable of reproducing experimentally determined flux distributions (Williams et al, 2010;Hay and Schwender, 2011b) and generating new insights into metabolic behavior, capacities, and efficiencies (Sweetlove and Ratcliffe, 2011), challenges remain to advance the utility and predictive power of the models.…”