ILs are low symmetric weak intra-molecular organic cationic salts in cyclic, aromatic and long alkyl chains with good distribution of charges. These remain in liquid phase below 100°C. ILs can solubilize different lignocellulosic biomass, including softwood, hardwood and all grasses at low temperature. In addition, using ILs can reduce the cost of saccharification enzymes. Factors including high costs and the difficulty in recycling ILs are major barriers in the commercialization of this technology. The current market price of imidazolium IL is around $500/kg (Drapcho et al. 2008).

Commercial forage harvest systems include those that produce (1) small bales; (2) large cylindrical solid bales; (3) large rectangular solid bales; (4) loosely chopped material; (5) pressed modules based on cotton module systems; and (6) chopped relatively wet material for ensilage

systems (Cundiff 1996; Cundiff and Marsh 1996; Worley and Cundiff 1996; Sokhansanj and Turhollow 2002; Gallagher et al. 2003; Kumara and Sokhansanj 2007). Given these conventional forage harvest technologies, for large volumes of dry matter, and to collect for field storage and transport substantial distances, large rectangular solid bales is the least-cost system for harvesting biomass from perennial grasses in the Southern Plains (Thorsell et al. 2004).

Table 5 includes an enterprise budget prepared to produce an estimate of the cost to produce biomass from an established stand of switchgrass (Epplin 1996). Established stands are expected to require no tillage or herbicide. Field operations are limited to fertilizer application, mowing with a self propelled windrower, and baling. Harvesting costs were based on an average yield of 8.97 dry Mg/ha/yr. The budget reflects a cost of $82.64/ ha for establishment with conventional tillage (from Table 3), $116.63/ha for fertilizer and fertilizer application, and $111.20/ha for land rent. The budgeted rate of fertilizer includes 90 kg/ha/yr of N and 22 kg/ha/yr of P2O5. Based on reported custom rates, the windrowing activity is budgeted to cost $33.56/ha and the baling activity $17.25/bale (Doye and Sahs 2012). Windrowing (mowing and preparing a windrow) is modeled as a per hectare cost while baling and hauling is modeled as a function of yield. The budget assumes that biomass is baled at 15 percent moisture into rectangular solid bales (1.22m x 1.22m x 2.44m, 635 kg), loaded, and transported from the

field by a tractor trailer truck. The key cost parameters are biomass yield, land rental rate, harvesting costs, and the cost to transport the biomass to a conversion facility.

Cost to transport is assumed to be a function of yield and distance. The average transportation distance from the field to the biorefinery is assumed to be 48 km. Wang (2009) estimated the cost of transportation specifically for moving biomass from a field to a conversion plant. She assumed that a standard flatbed trailer truck could carry an average load of 14.5 dry Mg. For a diesel fuel price of $0.79/L, Wang’s equation can be summarized as the cost $/dry Mg = 0.8796 + 0.1983 * km (one way distance).

Costs per hectare and costs per dry Mg are computed for yields of 4.48, 8.97, and 13.45 Mg dry matter/ha. The estimated breakeven costs are $65/Mg for a 13.45 dry Mg/ha yield and $121/Mg for a 4.48 Mg/ha yield. Table 6 contains a summary of findings to changes in the estimated breakeven price of biomass when the costs of several important cost items are doubled. For a yield of 8.97 Mg/ha, doubling the cost of land would increase the breakeven price by 17 percent from $79 to $92/Mg. Doubling the transportation cost would increase the breakeven price by 13 percent, and doubling the fertilizer cost would increase the cost by 16 percent. Doubling the cost to bale the material increases the cost by 34 percent if the

“Fertilizer is assumed to be applied in February or March.

bThe price of urea ($0.44/kg) is presented in the budget. This cost translates into a price of $0.96/kg of actual nitrogen.

cIf soil test values of phosphorus are sufficient, no P2O5 is recommended. The budgeted DAP application includes 9 kg N/ha and 22 kg P2O5/ha. The budget reflects the cost of 81 kg N from urea and 9 kg N from DAP to achieve the level of 90 kg of actual N/ha. dHarvest is budgeted to occur in October or November.

eAverage transportation distance is assumed to be 48 km. Estimated transportation cost is based on a diesel fuel price of $0.79/L and the equation ($/dry Mg) = 0.8796 + 0.1983 * km (one way) (Wang 2009).

yield is 8.97 Mg/ha and by 42 percent if the yield is 13.45 Mg/ha. By this measure, the estimated cost to deliver feedstock is sensitive to baling cost. The cost to deliver a flow of feedstock may depend critically on managing baling and other harvest cost.

Switchgrass, along with big bluestem (Andropogon gerardii), little bluestem (Schizachyrium scoparium), and indiangrass (Sorghastrum nutans), were the grasses that accounted for nearly all of the aboveground primary production of the tallgrass prairie. Tallgrass prairie once covered 56 million ha of the central USA, but today less than 4% remains in native vegetation (Rahmig et al. 2008). Switchgrass has a long history of grazing as a component of the tallgrass prairie and grazing switchgrass monocultures has occurred for more than 40 years (Kreuger and Curtis 1979). The first switchgrass cultivar, ‘Nebraska 28’, was released jointly by the USDA and the University of Nebraska in 1949. It was developed from native seed collections in Holt County, Nebraska for livestock forage production and conservation purposes. Nebraska 28 produced steer average daily gains (ADG) of 0.93 kg hd-1 d-1 and body weight gains of 147 kg ha-1 (Kreuger and Curtis 1979). Switchgrass ADG was less than that for indiangrass, but greater than that for big bluestem. Grazing switchgrass with monogastrics is not recommended due to potentially lethal concentrations of saponins, especially for horses (Lee et al. 2009). Commercially available switchgrass cultivars bred specifically for livestock forage production includes ‘Trailblazer’ (Vogel et al. 1991) and ‘Shawnee’ (Vogel et al. 1996). Trailblazer had a 23% increase in body weight gain per hectare when compared to the cultivar ‘Pathfinder’ (Vogel et al. 1991) and Shawnee had greater in vitro dry matter digestibility (IVDMD) than ‘Cave-in-Rock’ and greater forage yield than Trailblazer (Vogel et al. 1996).

Switchgrass biofuel development began in 1984 when the U. S. Department of Energy (DOE) funded field evaluations for about 34 herbaceous species at 31 sites in seven states for their suitability for biomass production (Wright 2007; Vogel et al. 2011; Parrish et al. 2012). Switchgrass was one of the top biomass producers at most of the sites and was selected as a model biofuel feedstock by DOE in 1991 (Wright 2007). Switchgrass is a broadly-adapted native with cultivars available for most US regions, it can be grown from seed, there is an existing seed industry, and it can be grown and harvested with available hay equipment (Vogel et al. 2011). The DOE funded switchgrass production and breeding research through the Biofuels Feedstock Development Program from 1992 to 2002 (McLaughlin and Kszos 2005; Wright 2007; Vogel et al. 2011). In 2002, DOE discontinued the Feedstock Development Program (McLaughlin and Kszos 2005; Sanderson et al. 2006) and focused on crop residues like maize stover for bioenergy because of the assumed availability and low cost (Vogel et al. 2011). USDA-ARS expanded funding for bioenergy in 2002 to include switchgrass genetics, breeding, and management, focusing on its potential use on marginal croplands similar to land that is currently held out of production in CRP (Vogel et al. 2011). Vogel et al. (2011) reported new research programs were initiated on perennial energy crops like switchgrass in 2006 in the USA and estimated that over $1 billion has been invested in the USA on biomass energy research since 2006 by both government and commercial companies.

The increased scientific importance of switchgrass is demonstrated by the number of publications focusing on switchgrass. Parrish et al. (2012) reported that the number of switchgrass publications has increased exponentially since 1990, but the volume of switchgrass research is very small compared to other crops. Reports on switchgrass averaged 8 per year from 1990 through 1994, but increased to 16 articles per year in the second half of the decade (Parrish et al. 2012). In 2010, 165 publications were reported for switchgrass, whereas 5,610 publications were reported for maize (Parrish et al. 2012). Research efforts are not limited to the USA, but have been reported in more than 20 countries including Australia, Canada, China, Colombia, Germany, Greece, Ireland, Italy, the Netherlands, Spain, and the United Kingdom, as well as other areas throughout Europe and Asia (Parrish et al. 2012).

As indicated previously, switchgrass is productive on sites that are poorly suited to annual crop production. The perennial nature of switchgrass will make stands productive for at least 10 years with good management (Mitchell et al. 2012a). However, the economic feasibility of switchgrass for bioenergy hinges on establishing stands with a harvestable yield in the planting year (Perrin et al. 2008). In the planting year, it is feasible to produce and harvest 50% of the yield potential of the cultivar after a killing frost and produce and harvest 75% to 100% of the yield potential of the cultivar in the first full growing season after planting (Vogel et al. 2011; Mitchell et al. 2012a, b). Adequate weed control and uniform stands in the planting year allows for full biomass potential one to two years after planting (Schmer et al. 2006). With upland cultivars, 4 to 5 Mg ha1 after a killing frost is typical during the planting year if precipitation is near the long-term average (Mitchell et al. 2012a, b). In the first year after seeding, fields can be near full production, producing 8 to 13 Mg ha1 after a killing frost in the central Great Plains (Mitchell et al. 2010). A switchgrass stand is considered mature and at full production in the second full production year (third growing season). Lowland cultivars like ‘Kanlow’ and ‘Alamo’ originated in southern latitudes and are typically adapted to areas south of 40° N. latitude and have not been evaluated at the field scale in the Great Plains and Midwest (Vogel et al. 2011). Alamo average biomass production fertilized at 168 kg N ha-1 yr-1 was 14.5 and 10.7 Mg ha-1 yr-1 at two Texas locations (Muir et al. 2001). Without applied N, biomass production declined over the years. Small plot trials of lowland ecotypes in Nebraska produced an average of 10.1 Mg ha1 in the year after seeding, with Kanlow producing 11.7 Mg ha1 in the year after seeding (Mitchell et al. 2010). Wullschleger et al. (2010) compiled a switchgrass biomass production database of 39 field sites in 17 states which supported the single harvest for bioenergy. Mean biomass yield across all locations was 8.7 ± 4.2 Mg ha1 for upland cultivars and 12.9 ± 5.9 Mg ha1 for lowland cultivars and the yield difference between ecotypes was significant. Yield trials in Nebraska indicate new material developed specifically for biomass provides a 2.2 Mg ha1 yield increase. Upland x lowland hybrids are promising for biomass energy, with hybrids increasing yield by 32 to 54% compared with parental lines (Vogel and Mitchell 2008). Deploying hybrid switchgrass to the field scale will result in potential harvestable yields of greater than 20 Mg ha1 in the Great Plains and Midwest (USDOE 2011).

Harvesting biomass removes large quantities of nutrients from the system (Mitchell et al. 2008, 2012b). Since nitrogen (N) is the most limiting nutrient for switchgrass production and is the most expensive annual production input, reducing N removal from the switchgrass production system has a positive effect on the economic and environmental sustainability of the system (Mitchell and Schmer 2012). Nitrogen removal is a function of N concentration and biomass yield, with biomass N concentration increasing as N fertilizer rates increase (Vogel et al. 2002). Biomass has been optimized when switchgrass is harvested at the boot to post-anthesis stage and fertilized with 120 kg N ha-1, with N removed similar to the N applied (Vogel et al. 2002). The interaction of N rate and harvest date must be considered to replace only the N needed to prevent over-fertilization. Harvesting 10 Mg ha-1 of switchgrass DM with whole — plant N of 1% removes 100 kg of N ha-1, but delaying harvest until after frost reduces whole-plant N to 0.6%, resulting in the removal of only 60 kg of N ha-1 (Mitchell et al. 2012b). Few studies have quantified the nutrient removal associated with growing switchgrass for bioenergy. In the Pacific Northwest under irrigation, Collins et al. (2008) reported that each kg of N produced 83 kg of biomass and the macronutrient export averaged 214 kg N ha-1, 40 kg P ha-1, 350 kg K ha-1, 15 kg S ha-1, 60 kg Ca ha-1, 38 kg Mg ha-1, and 6 kg Fe ha-1. Averaged across cultivars, switchgrass removed less than 1 kg ha-1 of B, Mn, Cu, and Zn. In southern Oklahoma, biomass yields of switchgrass averaged 17.8 Mg ha-1 and removed 40 to 75 kg N ha-1, 5 to 12 kg P ha-1, and 44 to 110 kg K ha-1, an indication of its utility as a low-input bioenergy crop (Kering et al. 2012). In the Northeast USA, delaying harvest until spring reduced ash content and leached nutrients from the vegetation (Adler et al. 2006). An evaluation of switchgrass harvest and storage management was published recently and covers this topic in more detail (Mitchell and Schmer 2012). Additional research is needed to match harvest date, nutrient removal, nutrient composition, and conversion platform to optimize nutrient management and limit over-fertilization and unnecessary nutrient contaminants in the feedstock production stream. Chapter 2 contains a more detailed discussion on switchgrass agronomics.

To date, research on biomass has often been an "either-or" proposition, with the bulk of work to date focused on agronomic production or conversion engineering. However, neither of these two links in the supply chain exists independently, nor will they have any value without a well-designed logistics system to move material from farm to refinery and from refinery to market. While a discussion of logistics warrants its own chapter, we briefly consider the challenges of moving biomass to a refinery, particularly as it relates to the agronomic implications.

The sheer scale of a biomass industry that can provide a significant proportion of US energy supplies will make bioenergy production a prodigious undertaking. Huge quantities of biomass will need to be collected and stored safely to provide a constant feedstock supply to the biorefinery. Biorefineries are expected to store only a 72-hour feedstock supply on site, with the remaining feedstock stored at the edge of field or at satellite storage facilities (Hess et al. 2009; Resop et al. 2011). Offsite storage management will be critical to maintain desirable composition characteristics and to ensure feedstock access under variable weather conditions (Mitchell and Schmer 2012). Ideal storage conditions preserve switchgrass so that it enters and leaves the storage phase in an unaltered state (Hess eta l. 2007). Key factors that minimize DM loss and degradation are low moisture levels prior to storage, protection from moisture during storage, low relative humidity, and low temperatures during storage (Mitchell and Schmer 2012). In Texas, DM losses for switchgrass round bales stored for 6 to 12 months inside had 0 to 2% DM losses, whereas bales stored outside lost 5 to 13% of the original bale weight (Sanderson et al. 1997). Tarped and untarped large rectangular bales had DM losses of 7% and up to 25%, respectively, 6 months after harvest in Nebraska (Mitchell et al. 2010b). Proper storage is critical to limit DM losses and maintain quality, but these costs to the system must be weighed against the added costs of storage, handling and processing required for each system.

It is in this context that we reconsider the harvest frequency and timing issue. There is general agreement in the research literature supporting a single, end-of-season harvest as most advantageous. However, this research typically has been disconnected from the one critical factor, logistics, which might give support to alternative harvest timings. There are cost benefits, particularly for dedicated bioenergy production enterprises, when one increases the productive machine hours of equipment invested in the enterprise (Cundiff 1996). In contrast, the infrastructural demands for a system that must capture a year’s supply of biomass during the "off" season will be further magnified by variable weather and field conditions —especially on marginal sites—which will limit field operations. Viewed in this context, the disadvantages of opening the harvest window (in terms of reduced feedstock quality or greater nutrient inputs) may be more than offset by advantages to the system as a whole. Systems that can reduce costs of collection, transport, processing and storage—by spreading harvests through time—would have a competitive advantage, although such management will likely require incentives to the producer to account for the added production costs. While this treatment is a mere "scratching of the surface" of the issues here, it should be clear to the reader that there are numerous interacting factors to be considered all along a bioenergy supply chain (Fike et al. 2007). The costs and benefits of these different components and practices must not be determined independently but rather in the context of the entire system as bioenergy comes on-line.

Biochemical Conversion

Biochemical conversion of switchgrass straw, and other lignocellulosic biomass, to biofuel typically has the following three major steps: pretreatment, saccharification, and fuel synthesis. Biochemical conversion is also known as direct microbial conversion and biological conversion. First, the harvested and chopped biomass is pretreated to breakdown its microstructure and improve accessibility of the polysaccharides. Conventional pretreatments include a combination of heat, pressure, acid, and/or base treatment (Agbor et al. 2011). Use and recycling of ionic liquids is an example of a new and highly effective pretreatment (Li et al. 2010). In the second step, enzymes are added to the neutralized slurry to breakdown the cellulose and other polysaccharides into monosaccharides, a process known as saccharification. Finally, in the fuel synthesis step, microbial metabolism, typically fermentation, is enlisted to convert the sugars into fuel. The prototype fuel is ethanol, though recent research has demonstrated synthesis from sugars of higher energy-content fuels, including butanol, alkanes, and fatty acid esters, also known as biodiesel (Peralta-Yahya et al. 2010). In this chapter, we will provide essential information about each of these steps with a focus on how they relate in particular to the use of switchgrass as a bioenergy crop.

While higher and more consistent biomass yields for switchgrass and other bioenergy crops are essential, currently the cost and inefficiency of saccharification represent the greatest barriers to wide-spread commercial realization of lignocellulosic biofuel production (Lynd et al. 2008). This chapter will review the major research efforts dedicated toward optimizing lignocellulose composition and the enzymes that degrade it toward improving sugar yields from grasses. Research on plants has focused on understanding the synthesis and regulation of plant lignocellulose toward developing plant biomass that results in the highest yields of monosaccharides per unit mass (Carpita 2012; Youngs et al. 2012). Of course, stature and plant health must be maintained in the quality-optimized genotypes. Research on enzymes that hydrolyze lignocellulose has delved into understanding their basic mechanisms and the biophysics of their interactions with biomass. Moreover, researchers continue to use advanced methodologies to identify and generate additional hydrolase diversity. These two fields intersect with the overexpression of lignocellulolytic enzymes by plants themselves. This and other approaches to consolidate the steps of biofuel production are thought of as being important ways to improve biochemical biofuel production efficiency (Lynd et al. 2008). We note that the production of co-products, i. e., valuable uses for biomass components that do not become fuel, is extremely important in the life cycle analysis of the economic and environmental feasibility of biofuel production (Farrell et al. 2006; Lynd et al. 2008), especially via biological conversion, but will not be covered here.

DNA molecular markers started with restriction fragment length polymorphism (RFLP), which refers to the differences of restriction sites between two or more DNA samples. After a DNA sample is digested into pieces by restriction enzymes, the resulting restriction fragments are separated according to their lengths and detected by hybridization with labeled nucleotide probes. Although now largely outdated, RFLP was the first-generation DNA profiling technique used for genetic diversity analysis and linkage map construction in switchgrass (Hultquist et al. 1996; Missaoui et al. 2005b, 2006).

Next widely used first-generation marker system is random amplified polymorphic DNA (RAPD). RAPD does not require any information of the DNA sequence of a target organism, thus it is cheaper to develop than RFLP. It has been used for switchgrass genetic diversity and evolution studies (Gunter et al. 1996; Casler et al. 2007). One major disadvantage of RAPD is its low reproducibility and instability due to slippage and low specificity of random primer binding.

Simple sequence repeat (SSR) markers, also known as microsatellites, are repeats of short nucleotide sequences, usually equal to or less than six bases in length per core repeat. SSRs are highly variable in the number of repeats at a specific locus and distributed throughout the eukaryotic genomes. In addition, SSR markers are amplified using the polymerase chain reaction (PCR) with fewer experimental steps and a lower cost and smaller amount of DNA templates compared with RFLP, thus allowing for the rapid generation of data from a relatively small amount of plant tissues. They have been popularly used as the second-generation DNA markers in construction of linkage maps, QTL (quantitative trait loci) mapping, gene cloning, germplasm diversity study, cultivar identification, and marker — assisted selection.

The SSR markers in switchgrass are available. Tobias and colleagues reported the primer sequences of 32 effective SSR markers developed from a switchgrass expressed sequence tag (EST) project (Tobias et al. 2005,

2006) . Later, Tobias et al. (2008) developed additional 830 EST-derived SSR markers. Not long after, 185 and 1,030 genomic SSRs were developed from sequencing SSR-enriched genomic libraries by two research groups, respectively (Okada et al. 2010; Wang et al. 2011). Recently 538 effective EST-SSRs were reported by our group (Liu et al. 2013b). Our experiments clearly showed higher polymorphisms of genomic SSRs than EST-SSRs in switchgrass (Wang et al. 2011; Liu et al. 2012).

Single nucleotide polymorphisms (SNPs) are a single nucleotide variation in sequence, and represent the most abundant type of genetic polymorphisms in plant genomes (Kwok 2001). While the majority of the SNPs are of no biological consequences, a fraction of the substitutions have functional significance and are the basis for plant diversity. Compared to SSRs, SNPs are, to some extents, more amenable to high-throughput automated genotyping assays that allow samples to be genotyped faster and more economically (Rafalski 2002; Ha and Boerma 2008; Han et al.

2011) . Scanning for new SNPs can be divided into two methods: i. e., global and regional approaches. Global SNP discovery is generally time — and labor-consuming. It is limited by the amount of funding available and whole genome sequence to provide the reference against which all other sequencing data can be compared. In contrast, local SNP discovery are relatively inexpensive to develop and rely mostly on direct DNA sequencing. SNP detection technologies have evolved from expensive, time-consuming, and labor-intensive processes to some of the most highly automated, efficient, and relatively inexpensive methods of DNA marker detection (Kwok and Chen 2003; Han et al. 2011). Two complete switchgrass chloroplast (cp) genomes were sequenced from upland (‘Summer’) and lowland (‘Kanlow’) ecotypes, and totally 116 SNPs were identified (Young et al. 2011). As a marker system developed from cp genome, their application in breeding is limited due to maternal inheritance of cp genome. Recently, Ersoz et al. (2012) established EST libraries of leaf tissues from thirteen diverse switchgrass cultivars, which represented upland and lowland ecotypes, as well as tetraploid and octoploid genomes. These libraries were sequenced by ABI 3730 instruments, and 100,000 EST sequences were produced. Subsequently, they generated reduced-representation genomic libraries from the same samples, which were massively sequenced as short — reads (35 bp) on a first-generation Illumina Genome Analyzer. Using EST as reference framework, these short sequence reads were assembled, and over 149,000 SNPs were identified. In addition, through combining with previously published 500,000 ESTs by Tobias et al. (2005, 2008), 25,000 additional SNPs were identified from the entire EST collection (Ersoz et al. 2012).

Next-generation sequencing (NGS) technologies are making a substantial impact on crop breeding. Genotyping by sequencing (GBS) is an emerging technology based on the platform of NGS. It utilizes ample SNPs generated by sequencing for genetic research. Comparing to other marker systems, GBS reduces sample handling time, uses fewer PCR samples, lowers costs if in a high-resolution scale. In addition, restriction enzymes can be used to reduce genome complexity and avoid the repetitive sequences of the genome, which is essential to expand in switchgrass genome. In wheat and barley, NGS was proven effective and over 200,000 sequence tags were mapped (Elshire et al. 2011). Its use in switchgrass is ongoing (http:// www. maizegenetics. net/snp-discovery-in-switchgrass) and expected to have a substantial role for genotyping but, to a large degree, depending on funding availability.

Transgenic approach manipulating gene expression for trait modification is one of the effective strategies for switchgrass breeding and genetic improvement (Sticklen 2006; Gressel 2008; Li and Qu 2011; Mann et al.

2012) . As one of the important regulatory factors in plants, miRNA genes and their targets are potential candidates for this purpose. Although little is known about the functions of miRNAs in switchgrass, several miRNA families are evolutionarily conserved in plant species, so is the miRNA — mediated regulatory mechanism (Jones-Rhoades et al. 2006; Chen 2009; Voinnet 2009; Cuperus et al. 2011). Therefore, it is possible to make use of the miRNAs whose functions have been identified in other species to modify this bioenergy crop.

Use of syngas for electrical power and heat production is more adaptable and direct as compared to its use for fuels and chemicals production. Several demonstrations of heat and power generation using syngas generated from biomass and wastes are available in literature (Young and Pian 2003; Bengtsson 2011; Son et al. 2011). Technologies used for heat and power productions include external combustion engines such as steam engine, internal combustion engines such as reciprocating gas engines and gas turbines and fuels cells. However, challenges remain in using existing equipment because of low volumetric energy content of biomass-generated syngas (4-15 MJ/m3) as compared to that of fossil fuels such as natural gas (38 MJ/m3) (Wang et al. 2008), for which the engines are designed for. Use of gas turbines was demonstrated in a week-long tests for power production from wood chips-generated syngas in Sweden at the scale of 18 MW (thermal) (Bengtsson 2011). In developing countries, gasification of locally available biomass and wastes has potential to provide electricity (Abe et al.

2007) . However, the challenges in commercialization of biomass gasification for power generation are several: robust syngas cleaning technologies are needed; power is lower value product than liquid fuels; and infrastructure and equipment to use biomass is not well-established unlike fossil-based feedstocks such as coal and natural gas.

SHF may be performed two different ways: separate hydrolysis and separate fermentation (SHSF) and separate hydrolysis and co-fermentation (SHCF). In SHSF, production of cellulolytic enzymes, hydrolysis of pretreated biomass and fermentation are performed in separate vessels. SHSF would allow performing each step at its corresponding optimum conditions. Generally, the production of cellulolytic enzymes using T. reesei is performed at 25-30°C and at pH 4.5-5.5. Hydrolysis of pretreated lignocellulosic biomass is performed in the temperature range of 50-55°C at pH 4.5-5.5. Ethanol fermentation is performed in the temperature range of 30-35°C at pH 5-6. Saccharomyces cerevisiae and Pichia stipitis may be respectively used to ferment both glucose and xylose to ethanol. However, P stipitis requires micro aeration (1 mmol of air per liter per hour) for xylose metabolism (Fig. 5). Iogen, Inc. (based in Canada) uses SHSF for the ethanol production. The optimal process integration would result in higher ethanol productivity.

SHCF is very similar to SHSF in that the hydrolysis of pretreated biomass and fermentation are performed in separate vessels. Unlike SHSF, in SHCF fermentation of different sugars (such as glucose and xylose) is performed in the same vessel. Simultaneous utilization of sugars for ethanol fermentation may be performed using either a single microorganism culture or co-culture of microorganisms. Most of the microorganisms use glucose as a carbon source to produce ethanol and are resistive to xylose uptake. The simultaneous utilization of xylose along with glucose for ethanol production could be approached several different ways.

Adhikari et al. (2009) has reported that the thermotolerant yeast Kluyveromyces sp. IIPE453 MTCC 5314 may consume a wide range of mono — and disaccharide sugars including glucose, xylose, mannose, arabinose simultaneously at temperature range of 40-65°C and pH range of 3.5-5.5 with ethanol productivity 13.8 gl-1h-1 on sugarcane bagasse in continuous

Figure 5. Overview of the xylose metabolic pathway found in yeasts such as Pitchia stipitis including the engineered xylose isomerase (XI) reaction (Pitkanen et al. 2005; Chu and Lee

2007).

Abbreviations: HXT, hexose transporters; Sym, symporter; XR, xylose redutase; XDH, xylitol dehydrogenase; XI, xylose isomerase; XK, xylulokinase; X5P, xylulose-5-phosphate; TKL, transketolase; TAL, transaldolase; S7P, sedoheptulose-7-phosphate; GA3P, glyceraldehyde — 3-phosphate; RPE, L-ribulose-5-phosphate 4-epimerase; Ru5P, L-ribulose 5-phosphate; RKI, ribose-5-phosphate isomerase; R5P, ribose-5-phosphate; E4P, erythrose 4-phosphate; F6P, fructose 6-phosphate; GND, 6-phosphogluconate dehydrogenase; 6PG, 6-phospho-D-gluconate; 6PGL, 6-phospho-D-glucono-1,5-lactone; ZWF, glucose-6-phosphate-1-dehydrogenase; G6P, glucose-6-phosphate; HXK, hexokinase; PFK, 6-phosphofructokinase; F6P, fructose — 6-phosphate; F16BP, fructose 1,6-bisphosphate; PGI, glucose-6-phosphate isomerase; FBA, fructose-bisphosphate aldolase; DHAP, dihydroxyacetone phosphate; GPD, glycerol-3- phosphate dehydrogenase; GO3P, glycerol-3-phosphate; GPP, glycerol-3-phosphatase; TPI, triose-phosphate isomerase; TDH, glyceraldehyde-3-phosphate dehydrogenase; BPG, 1,3-bisphosphoglycerate; PEP, phosphoenol pyruvate; PPPh, phosphoenolpyruvate phosphatase; PDC, pyruvate decarboxylase; ADH, alcohol dehydrogenase; ALD, acetaldehyde dehydrogenase; ACS, acetyl-CoA-synthetase; PYC, pyruvate carboxylase; PDB, pyruvate dehydrogenase beta subunit; PCK, phosphoenol pyruvate carboxykinase; AcCoA, acetyl coenzyme A; CIT, citrate synthase; CITR, citrate; ACO, aconitate hydratase; ICTR, isocitrate; AKG, alpha-ketoglutarate; IDP, isocitrate dehydrogenase kinase; KGD, alpha-ketoglutarate decarboxylase; SucCoA, succinyl CoA; LSC, succinyl-CoA ligase; SUC, succinate; SDH, succinate dehydrogenase; FUM, fumarate; FUMH, fumarate hydralase; MAL, malate; MDH, malate dehydrogenase; OAA, oxaloacetate; ICL, isocitrate lyase; GLO, glyoxylate; and, MLS, malate synthase.

fermentation. In addition, Kluyveromyces sp. IIPE453 MTCC 5314 may be recycled up to 20 days in the continuous process at 50°C (Adhikari et al. 2009).

Xylose isomerase (XI) enzyme converts xylose to xylulose that could be easier to use as a carbon source by microorganisms such as yeast S. cerevisiae for ethanol production. Xylose isomerase can be used either separately or along with cellulolytic enzymes. The optimum activity of xylose isomerase is at a pH of 7-8 and at a temperature range of 60-80°C. However, a urease coated xylose isomerase could work under acidic conditions as urease coats a separate inner basic environment from the exterior acidic environment (Rao et al. 2007). Rao (2007) has mentioned that using the urease coated xylose isomerase along with 0.05 M tetrahydroxyborate could convert 86% of xylose into xylulose under acidic condition at temperature 34°C. However, the uptake of xylulose by yeast decreases with increasing ethanol concentration at less than 4% (w/v) in the media (Chiang et al. 1981; Chandrakant and Bisaria 1998).

The use of genetically engineered microorganisms such as Zymomonas mobilis and Escherichia coli may simultaneously consume both glucose and xylose in co-fermentation. The genetically engineered bacteria improve the ethanol yield from 0.39 g g-1 to 0.44-0.52 g g-1 with high productivity up to 0.18-0.96 g l1 h1 (Olsson and Hahn-Hagerdal 1996). The main issues with the genetically engineered strains are stability, reproducibility and regulatory issues with use of biomass byproduct for animal feed.

Compared to other lignocellulosic bioenergy crops, switchgrass rates well in its fertilizer, pesticide, and irrigation requirements (Groom et al. 2008). Switchgrass biomass does not appear to be sensitive to phosphorus (P) additions (Muir et al. 2001), and spring nitrogen (N) additions in some cases have had little effect on biomass outcomes when compared to control groups receiving no N at all (Thomason et al. 2005), consistent with switchgrass evolving in low N conditions. Other studies have shown N additions to increase biomass yields, but with diminishing returns such that N additions as low as 56 kg/ha having the highest fertilizer use efficiencies (Lemus et al. 2008). In a study based in Illinois, switchgrass production resulted in minimal N leaching compared to maize (1.4 kg N/ha/yr vs. 40 kg N/ha/ yr), and was slightly better in this capacity (though not statistically different) than Miscanthus x giganteus, a lignocellulosic alternative (Mclsaac et al. 2010). All evidence points towards switchgrass having excellent N-use efficiencies, and the ability to effectively partition nutrients to its roots towards the end of the growing season.

Water-use and water quantity and quality repercussions of switchgrass production are mixed. The amount of water used in the entire ethanol production process is not trivial, and can amount to > 2000 L water to produce 1 L ethanol in some locations (Chiu et al. 2009). This obviously brings forth the notion that areas of the world that rely heavily on irrigation (e. g., western U. S. states) may not be well-suited for future biofuel production. On the agronomic production side alone, evapotranspiration losses for all bioenergy crops are expected to increase in a warming and elevated-CO2 climate (Le et al. 2011). The jury is still out on how switchgrass compares to other bioenergy crop alternatives; some studies have shown that evapotranspiration losses for switchgrass are not as large of a problem as they are for Miscanthus x giganteus (McIsaac et al. 2010), while others essentially equate switchgrass with Miscanthus x giganteus but characterize them both as having higher losses than maize (Le et al. 2011). Subsequent alteration to the water cycle may have large impacts in areas that will experience conversion to bioenergy crop production. The impacts could well be tied to lower water quality via reduced surface runoff under certain land — use changes (Wu et al. 2012); however, models projecting sediment-, N-, and P-associated metrics indicate that perennial grasses, like switchgrass, may be better alternatives than row crops such as maize (Love and Nejadhashemi

2011) . Across large spatial scales, the water-use efficiency of switchgrass is notable; it is generally thought to be better than that exhibited by maize (VanLoocke et al. 2012), and undoubtedly will influence short — and long­term system-wide water quality and quantity issues.