The lignocellulosic substrates include woody sub­strates such as hardwood (birch, aspen, etc.) and soft­wood (spruce, pine, etc.), agri residues (wheat straw, sugarcane bagasse, corn stover, etc.), dedicated energy crops (switchgrass, willow, hemp, Miscanthus, etc.), weedy materials (Eichhornia crassipes, Lantana camara, etc.), and municipal solid waste (food and kitchen waste, etc.). The diversity of raw materials will allow the decen­tralization of fuel production with geopolitical, eco­nomic, and social benefits (Van Dyck and Pletschke, 2012; Wyman, 2007). Despite the success achieved in the laboratory, there are limitations to success with lignocellulosic substrates on a commercial scale (Chan — del and Singh, 2011) as each source of biomass brings a unique technological challenge.

The advanced biomass-to-biofuels development platform has multiple goals, including the use of new enzymes to take full advantage of available carbohy­drates, the development of new lines of bioenergy crops with increased fermentation productivity (Carpita, 2012; Abramson et al., 2010), the development of new uses for coproducts, and the reduction of pro­cessing and energy costs. Lignocelluloses have three main components: cellulose, hemicelluloses, and lignin. Cellulose is the most abundant organic polymer on the earth. It is a homopolymer of sugars containing six carbon atoms linked together in a chain that constitutes the largest proportion of the plant cell wall. Hemicellu — loses are heteropolysaccharides consisting of short branched chains of hexoses, e. g. mannose units in mannans and pentoses such as xylose units in xylans (Chandel et al.,. 2010; Girio et al., 2010; Kuhad et al., 1997).

Table 2.4 summarizes the basic cell wall composition of some important lignocellulosic biomass used in bio­energy generation. In general, hardwoods contain 18—25% lignin, 45—55% cellulose, and 24—40% hemicel — luloses, while softwoods contain 25—35% lignin, 45—50% cellulose, and 5—35% hemicelluloses. Grasses normally contain 10—30% lignin, 25—40% cellulose, and 25—50% hemicelluloses (Balat, 2011; Sanchez, 2009; Howard et al., 2003; Malherbe and Cloete, 2003; Betts et al., 1991). Agri-biomass commonly comprises about 40% cellulose, 25% hemicellulose and 18% lignin. The structure and components of the cell walls of weeds are significantly different from those of most plant species, which may influence digestibility during the bioconversion process to bioethanol (Van Dyck and Pletschke, 2012; Chandel and Singh, 2011; Sarkar et al.,

2009) .

The hydrolytic breakdown of cellulose in nature involves the use of enzymes including cellobiohydro — lases, endoglucanases and b-glucosidases produced by microbes or other biological agents, alone or in combina­tion (Turner et al., 2010; Kuhad et al., 1997). More recent studies have shown that additional oxidoreductase enzymes (glycosyl hydrolase family 61 polysaccharide monooxygenases and cellobiose dehydrogenase) are essential components in a complete cellulose-degrading enzyme system (Horn et al., 2012; Kittl et al., 2012; Lang­ston et al., 2011). The sugar chains of cellulose can be hy­drolyzed to produce glucose and cellooligosaccharides, most of which can be fermented using ordinary baker’s yeast. To attain economic feasibility a high ethanol yield is a necessity. Producing monomer sugars from cel­lulose and hemicellulose at high yields is far more difficult than deriving sugars from sugar — or starch — containing crops, e. g. sugarcane or maize (Van Dyck and Pletschke, 2012; Tuohy et al., 1994). Therefore, although the cost of lignocellulosic biomass is far lower than that of sugar and starch crops, the cost of obtaining sugars from such materials for fermentation into bioethanol has historically been far too high to attract industrial interest. For this reason, it is crucial to solve the problems involved in the conversion of lignocellulosic biomass to sugar and further to ethanol (Agbor et al., 2011; Galbe and Zacchi, 2002).

The heterogeneity in feedstock and the influence of different process conditions on microorganisms and enzymes makes the biomass-to-ethanol process

(Continued)

complex. Ethanol can be produced from lignocellulosic materials in various ways. The main difference between the process alternatives is the hydrolysis steps, which as mentioned previously, can be performed by dilute acid, concentrated acid or enzymatically. Some of the process steps are more or less the same, independent of the hy­drolysis method used. For example, enzyme production will be omitted in an acid hydrolysis process; likewise, the recovery of acid is not necessary in an enzyme hy­drolysis process (Galbe and Zacchi, 2002).

To achieve lower production costs, the sustainable supply of cheap raw materials is a necessity. It is also essential to ensure that all components of the biomass are utilized and resulting by-products and wastes are used in a biorefinery system. When lignocellulosic raw materials are used, the main by-product is lignin, which can be used as an ash-free solid fuel for production of heat and/or electricity, for which there are no foresee­able market limits. However, in addition, lignin can be used for a range of additional high-value products that have the potential to enhance overall process economics significantly (Azadi et al., 2013; Lange et al., 2013; Doherty et al., 2011; Collinson and Thielemans, 2010). Accordingly, it will only be possible to produce large amounts of low-cost ethanol if lignocellulosic feedstocks such as fast-growing trees, grass, aquatic plants, waste products (including agricultural and forestry residues) and municipal and industrial waste are used
(Van Dyck and Pletschke, 2012; Wheals et al., 1999). The potential of using lignocellulosic biomass for energy production is even more apparent when one realizes that it is the most abundant renewable organic compo­nent in the biosphere (Claassen et al. 1999). Currently enzyme hydrolysis has high yields (70—85%) of biocon­version, and improvements are still possible (85—95%) (Van Dyck and Pletschke, 2012; Sills and Gossett, 2011; Redding et al., 2010; Hu and Wen, 2008).