Desirable feedstock qualities are largely dependent on the nature of processing technologies (Carroll and Somerville 2009). Currently, the two major biomass processing technologies are: thermal conversion and biological conversion. In thermal conversion (e. g., direct combustion or pyrolysis), it is more desirable to have feedstock with a lower amount of mineral residues and a higher energy content, which often correlates with a high lignin content of the biomass (Boateng et al. 2008). In biological conversion for biofuel production, the feedstock with lower lignin content has higher saccharification efficiency through enzyme hydrolysis, resulting in an increase in enzymatic fermentation efficiency (Fu et al. 2011a). Other cell wall components, such as hemicellulose (Lee et al. 2009) and pectin (Lionetti et al. 2010), also have a negative impact on bioenergy production using biochemical conversion technologies.

About 80 percent of the dry plant biomass is comprised of plant cell walls, which stores most of the biomass energy (Vogel and Jung 2001). Cellulose, hemicellulose, and pectin are the polysaccharide components of plant cell walls, of which cellulose is the primary component for biofuel (ethanol) production via fermentation (Carroll and Somerville 2009). Cell walls, especially secondary cell walls, are strengthened by lignin, a phenolic polymer derived from hydroxycinnamyl alcohols and produced by means of combinatorial radical coupling reactions (Boudet 2007). Lignin deposition reinforces plant cell walls to enable water transport, provide mechanical support and a barrier to pathogens, and help convey abiotic tolerance (Halpin 2004; Boudet 2007). However, high lignin content is not desirable for bioconversion of the lignocellulosic feedstock to biofuel for three reasons: 1) it prevents access of the hydrolytic enzymes to the polysaccharides, 2) it absorbs the hydrolytic enzymes, and 3) it inhibits the activities of the hydrolytic and fermentable enzymes used in the biofuel conversion process (Halpin 2004; Endo et al. 2008; Abramson et al. 2010). Studies using different alfalfa transgenic lines, with variable reduced lignin content, proved the negative correlation between lignin content and fermentable sugar release efficiency (Chen and Dixon 2007). Therefore, there is a strong interest in developing low-lignin content switchgrass cultivars for biofuel production.

The grass lignin polymer is usually composed of three monolignols [hydroxyphenyl (H), guaiacyl (G), and syringyl (S)] (Hatfield et al. 1999). Monolignols are derived from the amino acid phenylalanine through the monolignol biosynthesis pathway. The pathway has about ten key enzymes that catalyze the reaction steps and the pathway is evolutionarily conserved across angiosperms (Rastogi and Dwivedi 2008). Gene families encoding these key enzymes went through a rapid expansion after the divergence of monocots and dicots (Xu et al. 2009). By BLASTing against the switchgrass EST database, and utilizing phylogenetic analysis, we can find switchgrass homologs of all monolignol biosynthesis genes in model plant species. Through gene-expression patterns, in vitro enzymatic assays, and the generation of stable RNAi transgenic plants, a few switchgrass genes [4 Coumarate:Coenzyme A Ligase (4CL1,2), Cinnamyl Alcohol Dehydrogenase (CAD1,2), Catechol-O-methyltransferase (COMT)] in the monolignol biosynthesis pathway have been identified. RNAi: PvCOMT, RNAi: PvCAD2 and RNAi: Pv4CL1 transgenic plants have significantly less lignin content than wild type plants (Fu et al. 2011a, b; Saathoff et al. 2011a, b; Xu et al. 2011b).

Fu et al. (2011a) cloned a COMT cDNA and down-regulated its expression in cv. Alamo. Up to 90% of the COMT transcript was reduced and over 70% reduction in COMT enzyme activity was observed. Lignin content was reduced by 6 to 15% while the S/G ratio of the lignin was reduced from 0.69-0.71 in control plants to 0.37-0.40 in transgenics, mainly by reduction of S lignin content. The growth and development of transgenic plants appeared normal and the height and fresh and dry weight were similar to the controls under greenhouse conditions. Transgenic lines increased the ethanol yield by up to 38% using conventional biomass fermentation processes. The down-regulated lines required less severe pretreatment and 300-400% lower cellulase dosages for equivalent product yields using simultaneous saccharification and fermentation with yeast. Furthermore, fermentation of diluted acid-pretreated transgenic switchgrass using Clostridium thermocellum with no added enzymes showed better product yields than obtained with unmodified switchgrass. Therefore, this apparent reduction in the recalcitrance of transgenic switchgrass has the potential to lower processing costs for biomass fermentation-derived fuels and chemicals significantly (Fu et al. 2011a).

Saathoff et al. (2011b) demonstrated that switchgrass cv. Kanlow has at least two functional CAD genes. RNAi approach using 575 bp of PviCAD2 coding fragment (96% identical to the same region of PviCAD1 gene) was employed in an attempt to silence both CAD genes (Saathoff et al. 2011a). The CAD transcripts, protein amount and enzyme activities were substantially reduced in most transgenic lines. Four transgenic lines with single transgene copy were further analyzed. The lowest CAD activity found in these lines was less than 10% of that in the vector controls. The total lignin and cutin amount in these lines were reduced by 23% in average compared to the vector controls. Two transgenic lines had significantly higher glucose release after alkaline pretreatment and enzymatic saccharification. In a similar approach, Fu et al. (2011b) also cloned a CAD (PvCAD) cDNA from swithcgrass, which has 98-99% identity at amino acid level with the predicted proteins encoded by the PviCAD1 and 2 genes. Phylogenetic analysis suggests the gene is involved in lignin biosynthesis. For the eight RNAi transgenic plants analyzed, the extractable CAD activities were only 17-39% of that in control plants (using coniferaldehyde as a substrate). The transgenic plants grew normally in the greenhouse. Total lignin content in transgenic plants was 14-22% lower than in controls as determined by the acetyl bromide method, and both S and G lignins were reduced. In addition, chlorogenic acid, a soluble phenolic compound, was substantially increased in transgenic plants. Without acid pretreatment, transgenic plants released 28-59% more glucose with enzymatic hydrolysis than did the controls while 15-35% more glucose release was observed with pretreatment. Similarly, saccharification efficiency (total sugar release) increased by 19-89% without pretreatment, and by 19-44% with pretreatment. Sugar release was negatively correlated to lignin content but not to the S/G ratio, indicating reduced lignin content is the main reason for the improved sugar release.

Xu et al. (2011b) identified two 4CL genes in switchgrass. Phylogenetic and gene-expression pattern and enzymatic activity analyses suggest that Pv4CL1, but not Pv4CL2, is involved in monolignol biosynthesis. The RNAi:Pv4CL1 T0 transgenic plants downregulated Pv4CL1 expression to 0.05-0.73 fold of the WT controls. The 4CL enzyme activity was reduced by 80% on average as measured in T transgenic plants. The above-ground biomass yield of the transgenic plants was comparable to WT controls grown in the greenhouse conditions while brown color was seen in midvein, internodes, and mature roots of some transgenic plants. Pooled Tx transgenic plants had 22% reduction of the acid-insoluble lignin as well as total lignin. Lignin composition was also changed. T1 transgenic plants had 47% less G lignin and 45% more H lignin, than non-transgenic T segregates. Dilute acid-pretreated samples enhanced enzymatic hydrolysis of glucan but not xylan. With pretreatment, transgenic plant materials yielded 57.2% more fermentable sugar than the WT plants. In a similar effort, two highly homologous 4CL cDNAs were isolated and an RNAi construct attempting to suppress both genes were introduced into switchgrass. Up to 90% of the transcripts of both genes were suppressed. Although the total lignin content was not changed or only modestly reduced (up to 5.8%), the structure and composition of lignin appeared to have altered. That was reflected by significant reduction of acid insoluble lignin (up to 8.5) and increase of the ratio of acid soluble lignin vs. acid insoluble lignin (ASL/AIL increase by 21.4-64.3%), and by the increase of S/G ratio (11.8-164.5% higher in transgenic plants). Consequently, with alkaline pretreatment, glucan and xylan conversion efficiency of the best transgenic plant was increased by 16% and 18%, respectively (Wang et al. 2012).

The lignin biosynthesis pathway is regulated by complex transcription networks that involve many transcriptional activators and repressors. The transcriptional repressors could simultaneously inhibit the expression of several genes in the monolignol pathway, which could be another way to reduce lignin synthesis. Very recently, a transcription factor gene involved in lignin biosynthesis, PvMYB4, was cloned and characterized (Shen et al. 2012). PvMYB4 is an R2R3-MYB transcriptional repressor. PvMYB4 binds to the AC-rich AC-I, AC-II, and AC-III elements of monolignol pathway genes in vitro in EMSA assays, and down-regulates these genes in vivo. Ectopic overexpression of PvMYB4 in transgenic switchgrass, under control of the ZmUbi1 promoter, reduces lignin content by at least 40 to 50 percent; however, the S/G monolignol ratio remains unchanged. Additionally, the ester-linked p-CA: FA ratio in these plants is reduced by approximately 50 percent. Monosaccharide release after enzymatic saccharification, without acid pretreatment, is threefold higher in these transgenic plants.

However, total sugar release from cell wall residues remained the same. The morphology of the transgenic switchgrass was affected. The plant height was reduced by an average of 40 percent, but tiller numbers could be increased as much as 2.5 fold. Whether or not the total biomass was affected remains to be investigated (Shen et al. 2012).

Maize Corngrass1 (Cg1) gene encodes a grass-specific tandem repeat of miR156 gene, which "promotes juvenile cell wall identities and morphology" (Chuck et al. 2011). Overexpression of the gene, like in the maize mutant, increases biomass due to continuous initiation of tillers and leaves, and had less lignin and more glucose and other sugars in the leaves. Chuck et al. (2011) overexpressed Cg1 cDNA in switchgrass in an attempt to improve its biomass yield and the feedstock quality. In a field test, high and moderate expressers were dwarfed and had smaller leaves and lower yield of biomass whereas yield of low expressers were comparable to WT controls while producing four time more branches. The transgene affects flowering: none of the transgenic plants ever flowered after being grown in the field for two summers and a winter. This may be a favorite trait to prevent transgene flow. Total lignin content was moderately reduced in transgenic plants. Interestingly, the low expressers accumulated more than 250% starch in their stems compared to the WT controls. Consequently, saccharification using a mix of amyloglucosidase and a-amylase without pretreatment released 3-4 times more glucose from stems of the low expressers, which was similar to the amount released by dilute acid pretreatment, indicating that pretreatment could be reduced or completely eliminated in saccharification. In a similar approach, Fu et al. (2012) overexpressed a rice OsmiR156b precursor gene in switchgrass. Low expressers flowered normally, moderate expressers had reduced height and did not flower, while high expressers’ growth was severely stunted. Both low and moderate expressers had improved biomass yield: 58-101% more than the controls in greenhouse condition, mainly attributing to increase in tiller number. Solubilized sugar production (g/plant) after acid pretreatment and enzymatic hydrolysis increased by 40-72%.

Bio-oil upgrading through catalytic vapor cracking removes oxygen from the bio-oil in the forms of CO2, H2O or CO without using external hydrogen. The reactions take place at temperatures of 330-600°C and atmospheric pressure. Solid acid catalysts such as aluminosilicates and zeolite are used for the bio-oil cracking (Park et al. 2011). Atmospheric pressure reaction without the need of external hydrogen makes this process economically attractive. The higher aromatic content in the product results in better fuel quality as compared to the hydrodeoxygenation process. However, catalysts deactivate at a faster rate and H/C ratio of product is lower as compared to those of hydrodeoxygenation products (Graca et al. 2009; Hew et al. 2010; Mortensen et al. 2011). Reaction of cracking can be summarized in the following equation with respect to carbon of bio-oil (Mortensen et al. 2011).

CH14O04^0.9 CH2 + 0.1 CO2 + 0.2 H2O (2)

Where CH14O04 and CH2 represent bio-oil and hydrocarbon product, respectively.

There are two major components to mechanistic modeling: model parameterization and model validation using empirical data. Each model should be parameterized and validated at many locations to ensure that the plant parameters accurately reflect plant growth across space and time. Model parameterization for a site can be performed using detailed field data collected for functionally important plant traits or by gleaning reasonable values from previous findings in the literature. These functional traits may be morphological (i. e., leaf area), physiological (i. e., stomatal conductance or proportion of N in tissue) and phenological (i. e., date of green-up, senescence, and maximum growing degree days) characteristics. Model parameterization often requires significantly more data collection over time than model validation. Therefore, many studies do not independently parameterize each model but only change key variables known to vary between locations (Kiniry et al. 2008).

Model validation, comparing measured yields to simulated yields for many sites is becoming increasingly common as more field trials managed for biofuel production are being performed (Wullscheleger et al. 2010). A review by Wullschleger et al. (2010) revealed 17 switchgrass studies managed for biofuel production at 39 different locations. Management varies widely across these studies and can greatly impact biomass production. For example, yearly N fertilizer application in these studies ranges from 0 to 896 kg N ha1. Changes in management practices need to be carefully considered when validating model output using yields from several studies.

To our knowledge, there are currently 14 studies that have used mechanistic models of switchgrass growth to predict biomass production. The number of times each model has been parameterized and validated for switchgrass varies (Table 1). The ALMANAC model has been most extensively parameterized and validated with five studies parameterizing the model and six studies validating the estimated yields.

Safeners are a group of chemically diverse compounds with the unique ability to protect grass crops from herbicide injury without reducing herbicide activity in target weed species (Davies and Caseley 1999; Hatzios and Burgos 2004). Most herbicide safeners were developed for corn, sorghum (Sorghum bicolor L.), rice (Oryza sativa L.), and wheat (Triticum aestivum L.) (Walton and Casida 1995; Hatzios and Burgos 2004). Fluxofenin is an oxime ether derivative primarily used to protect grasses from chloroacetanilide herbicides like metolachlor (Anonymous 2002; Anonymous 2004; Hatzios and Burgos 2004). Griffin et al. (1988) reported that switchgrass seedlings were safened against metolachlor with NA (1,8-napthalic anhydride), which is no longer commercially available. There has been relatively little research evaluating seed safeners to improve forage establishment (Roder et al. 1987). Butler et al. (unpublished data) observed that applications of metolachlor, metolachlor + atrazine, and pendamethalin reduced switchgrass emergence by 89 to 99 percentage points relative to untreated seed. Fluxofenin applied at 2 to 8 g a. i. kg-1 did not improve switchgrass emergence with any of these herbicide treatments. All seedlings died within three weeks of emergence, presumably due to lack of root development. Thus, fluxofenin does not appear to have potential for improving switchgrass establishment with metolachlor.

Activated charcoal is a well-documented herbicide safener (Becker and Wilson 1978; Yelverton et al. 1991) due to its large surface area and high adsorptive capacity (Coffey and Warren 1969; Cheremisinoff and Morresi 1978). Lee (1973) reported that 336 kg ha-1 activated charcoal in a 2.5-cm band effectively safened six grass species when applied with atrazine and diuron 3-[3,4-dichlorophenyl]-1,1-dimethylurea. However, there is limited information on charcoal as an herbicide safener on switchgrass.

Butler et al. (unpublished data) found that coating switchgrass seeds with activated charcoal safened switchgrass seedlings against metolachlor and metalochlor + atrazine, but reduced germination and emergence by 51 to 59% when rainfall was greater than normal. In addition, charcoal coated seeds failed to germinate and emerge in the field when rainfall conditions were below normal. Because charcoal is negatively charged, it may actually repel water, requiring greater amounts of water for seed to germinate. Given these inconsistent results, activated charcoal would not be recommended at this time. However, activated charcoal may have potential in regions with greater rainfall or in specialized areas with irrigation. Further testing and economic analyses are needed since charcoal seed coating treatments cost an average of $0.15 per 1,000 seeds. Addition of charcoal coating would increase costs approximately $454 ha1. This calculation also did not include cost of seed ($44 kg1), chemical ($37 ha1), shipping, and other variable establishment costs (land preparation, fertilizer, drill, and labor). In order for charcoal coated seed to become viable, seeding rate would need to be reduced, charcoal coating cost must be reduced, and coating material should not impede water inhibition, germination, and emergence.

Abiotic stresses include various environmental factors such as hot and cold extremes, drought, salinity, metal contamination and synthetic chemicals, among others, and all may decrease performance of bioenergy crops like switchgrass in the field. To help the host plant tolerate abiotic stresses, endophytes and AM fungi have evolved a number of mechanisms that improve plant growth and health.

Symbiotic microorganisms help with drought tolerance through the production of protective compounds such as peroxidase, ascorbate, and proline (Fan and Liu 2011; Ruiz-Sanchez et al. 2011). Plant associated microbes may also benefit the host plant by changing stomatal conductance, water potential, and net photosynthesis during drought (Bae et al. 2009).

Endophytes and AM fungi may modify carbohydrate metabolism and photosynthesis, or produce beneficial compounds to enhance cold tolerance in the host plant. When grapevine plants were exposed for five days to chilling conditions, net photosynthesis was higher compared with the levels of the control plants, helping them to withstand long periods of cold exposure (Fernandez et al. 2012a). Recently, it was found that B. phytofirmans PsJN modified trehalose metabolism, which may be a part of the mechanism under which B. phytofirmans PsJN increased chilling tolerance to grapevine (Fernandez et al. 2012b). In tomato plants, the AM fungus Glomus mosseae reduced membrane lipid peroxidation, increased photosynthetic pigments, accumulated osmotic adjustment compounds, and increased antioxidant enzyme activities (superoxide dismutase, catalase, peroxidase and ascorbate peroxidase), which lead to alleviating the damage caused by cold temperatures (Abdel Latef and He 2011). Chemical compounds produced by fungal endophytes may play important roles in host plant tolerance to cold temperatures. For example, a native grass Anchnatherun robustum (sleepygrass) infected with Neotyphodium spp. produced high levels of ergot alkaloids and demonstrated higher overwintering survival compared with non-infected plants, or even plants infected with Neotyphodium spp. with no alkaloid production (Faeth et al. 2010). These results indicate that alkaloids may protect plants against winter conditions.

Beneficial microbes could offer host plant tolerance to high salinity to aid in plant growth. To achieve increased tolerance to high salinity soils, beneficial organisms, both bacterial and fungal, may display a combination of traits such as the production of IAA, phosphate solubilisation, siderophore production, and ACC deaminase activity (Jha et al. 2012). The salt-tolerant Azospirillum brasilenses isolate NH produced IAA under salt — stress conditions, and it is believed that the production of this plant growth regulator may contribute to the increase in salt tolerance of inoculated wheat plants (Nabti et al. 2010). Under similar conditions, the endophytic strains, B. subtilis, B. pumilus, and P. putida isolated from the roots of Prosopis strombulifera (Argentine screwbean) produced significantly higher IAA (Sgroy et al. 2009).

Thus far, the majority of hydrolases expressed in plants have been thermostable, with activity maxima at temperatures greater than ambient (T > ~50°C). The logic for using thermostable enzymes is that pretreatment conditions will facilitate saccharification. Since thermostable enzymes often exhibit poor activity at ambient temperatures, such enzymes may also reduce deleterious effects on plant phenotype (Taylor et al. 2008). As will be discussed more below, these enzymes have been targeted to a variety of subcellular compartments—the cytosol, apoplast (cell wall), vacuole, and chloroplast. Subcellular targeting allows higher accumulation of proteins and limits enzymatic activity until cells are lysed during pretreatment or harvest (Ziegelhoffer et al. 2001; Hood et al. 2007). The most commonly used thermostable enzyme for in planta expression is the E1 endoglucanase (a cellulase) from Acidothermus cellulolyticus (Tucker et al. 1989). For example, E1 targeted to the cell wall of maize and tobacco increases biomass digestibility by up to 10% (Brunecky et al. 2011). Based on imaging data, the authors hypothesized that E1 acts by nicking cellulose chains as they are formed, creating more free chains for the plants’ endogenous exoglucanases to act upon (Brunecky et al. 2011).

Of special relevance to switchgrass and other grasses, a handful of studies have targeted in planta expression of ferulic acid esterases (FAEA) from Aspergillus. Ferulic acid esterases hydrolyze ester linkages between hydroxycinnamoyl esters and cell wall saccharides. Vacuolar targeting of FAEA in Lolium multiflorum and Festuca arundinacea decreased the feruloyl ester linkages in cell walls and ferulate dimers that cross-link polysaccharide chains (Buanafina et al. 2006; Buanafina et al. 2008). FAEA targeted to the ER, Golgi, and apoplast in Festuca arundinacea disturbed the ferulolyation process, enhancing biodegradability (Buanafina et al. 2010). Harholt and colleagues have also successfully targeted FAEA to the endosperm of wheat but with severe pleiotropic effects on fertility and with loss of seed mass (Harholt et al. 2010). Across all studies, the resultant digestibility increase was around 5-10%. Researchers found that the transformed plants compensate for the expression of FAEA by enhancing arabinoxylan synthesis and crosslinking. This indicates that multiple genes and/or inhibition of the cell wall biosynthesis signaling (Wolf et al. 2012) may be needed to produce a significant change in cell wall composition.

In addition to hydrolytic enzymes, in planta expression of carbohydrate binding modules (CBMs) may offer a promising approach to increasing biomass conversion. Such domains are also encoded in plant genomes and in fungi, under the monikers of expansins and swollenins (Abramson et al. 2010). Simply adding CBMs to cell wall materials during saccharification enhances sugar yield from cellulase attack, which may be due to their ability to disrupt cellulose microfibrils (Pauly et al. 2008), and is consistent with the improvements of GH activity when fused with a CBM mentioned earlier (Mahadevan et al. 2011).

In a few cases, an interesting secondary effect has been observed in plants overexpressing certain foreign or endogenous hydrolases and CBMs—namely, an increase in growth rate and biomass accumulation in conjunction with enhanced digestibility. Earlier studies involving CBM expression showed that these proteins can enhance plant growth and biomass (Abramson et al. 2010). While the precise mechanism is unknown, it is thought that these proteins uncouple cellulose polymerization and crystallization, allowing enhanced cellulose biosynthesis. Additionally, Arabidopsis expressing a poplar cellulase, PaPopCel1, showed an increase in the size of leaf and stem cells and corresponding organs (Park et al. 2003). The authors suggested, based on chemical analysis and NMR, that the cellulase diminishes the intercalation of xyloglucans into cell walls, thereby permitting cellular expansion and growth. This hypothesis was further supported when overexpression of xyloglucanase from Aspergillus aculeatus in poplar caused enhanced growth and increased cellulose deposition in internode xylem (Park et al. 2004). Sengon trees (Paraserianthes falcataria) expressing PaPopCel1 also showed increased growth and higher levels of soluble xyloglucans (Hartati et al. 2008). As expected, the elimination of xyloglucan tethering also enhances saccharification. Examination of several poplar transgenic lines each expressing a xyloglucanase, cellulase, or xylanase showed that those overexpressing xyloglucanase had markedly greater cellulose degradation in the xylem compared with wild-type and cellulase — or xylanase-expressing genotypes (Kaida et al. 2009). A similar outcome was also seen due to overexpression of A. niger xyloglucanase in Acacia mangium (Kaku et al. 2011). The hypothesized loosening of xyloglucan intercalation between the cellulose microfibrils due to glucanase action enhanced saccharification of Acacia mangium biomass by 1.4-fold, resulting in 10%-15% higher production of ethanol (Kaida et al. 2009). These results are especially note-worthy as production of plants that are not only larger than their wild-type counterparts, but also easier to degrade, could greatly enhance the efficiency of biofuel production. Of course, the mechanisms behind this process and the consequences for plant development, growth, physiology, and stress resistance must be better understood before this can actually be applied in agriculture. Since xyloglucan is not abundant in grasses, it remains to be tested if xyloglucanase expression could enhance grass stature and saccharification, or if another class of GHs might have this effect.

Although extremely challenging, with the ongoing efforts from related research community, switchgrass whole genome sequencing could be expected to bear fruits in a foreseeable future. The availability of a completed reference genome of switchgrass is of great importance, which would not only facilitate a better understanding of critical biological pathways for complex traits such as biomass production and efficient bioconversion in this bioenergy crop, but also accelerate development of novel genomics, genetics and molecular tools for switchgrass feedstock improvement through conventional and molecular breeding for its cost-effect use for biofuel production. As the extant and emerging genomic tools for switchgrass unfold, a more robust molecular foundation will present opportunities for accelerated breeding and new cultivar development ushering switchgrass genetics and genomics into a new era of bioenergy crop development.

Acknowledgements

The research in Luo’s lab has been supported by Biotechnology Risk Assessment Grant Program competitive grant no. 2007-33522-18489 and no. 2010-33522-21656 from the USDA National Institute of Food and Agriculture as well as the USDA grant CSREES SC-1700315 and SC-1700450. Technical Contribution No. 6111 of the Clemson University Experiment Station.

Biomass properties and composition vary widely. As a result, products from thermochemical conversion processes can be quite variable. The most routinely used biomass properties relevant for thermochemical conversions are heating value, proximate analysis, ultimate analysis and biochemical composition. Proximate analysis includes contents of moisture, volatiles, ash and fixed carbon. Ultimate analysis includes contents of carbon, hydrogen, oxygen, nitrogen, and sulfur. These contents can be reported on a dry basis (d. b.), wet basis (w. b.) or dry and ash-free basis (d. a.f.). The difference among these bases is the mass that the content (such as carbon content) is compared with. Content given in dry basis implies that the content is compared with moisture-free biomass. Content given in wet basis implies that the content is compared with biomass containing moisture. Content given in dry and ash-free basis implies that the content is compared with moisture and ash-free biomass material. Properties of several biomass are presented in Tables 1 (proximate analysis), 2 (ultimate analysis) and 3 (biochemical compositions). However, the above properties do not

completely characterize any biomass feedstock because biomass feedstocks with similar properties and composition stated above may differ in their polymer structure resulting in different products through thermochemical conversion processes.

To understand and reliably predict the effects of the biomass composition and properties on thermochemical conversion processes and products, several equipment have been used by researchers. The most common equipment includes thermogravimetric analyzer (TGA), dynamic thermogravimetric analyzer (DTA), pyrolyzer (Py), Fourier-transformed infrared spectrophotometer (FTIR), gas chromatography (GC) and mass spectrometer (MS) (Lapuerta et al. 2004; Dejong et al. 2007; Fahmi et al. 2007; Boateng et al. 2010; Pasangulapati et al. 2012; Ribechini et al. 2012). TGA provides weight loss of biomass as temperature is varied. Different weight loss stages in gasification and pyrolysis modes can be observed in the TGA data. The stages are separated more clearly using the derivative of the weight loss with time or temperature. Heating rates available in pyrolyzer is much higher than those in TGA, hence pyrolyzer is widely used to obtain volatiles simulating pyrolysis condition. The volatiles evolved from the biomass thermal degradation is detected by FTIR and MS.

The oxidative pretreatment involves the use of a strong oxidizing reagent such as hydrogen peroxide to achieve delignification. Sometimes sodium silicate of magnesium sulfate is added with hydrogen peroxide to make the solution more stable (Guald 1984). The concentration of hydrogen peroxide used is in the range of 1-10% by volume. More precisely, effective pretreatment requires the ratio of hydrogen peroxide to substrate of at least 0.25 g H2O2/g substrate under alkaline conditions (Guald 1984).

In alkaline conditions, hydrogen peroxide decomposes to form hydroxyl ions that further react with phenolic groups of lignin. Hydrogen peroxide also plays an important role in stabilizing the ends of cellulose and hemicellulose structures (Gupta 2008). Guald (1984) mentioned that alkaline peroxide pretreatment can achieve 50% or more delignification of lignocellulosic biomass with greater than 90% overall theoretical saccharification efficiency. However, the degree of saccharification for oak was 52.5% compared to 93.0% for wheat straw (Guald 1984).

Table 3 includes a switchgrass conventional tillage establishment budget. Table 4 includes a no-till establishment budget. Custom rates are used to reflect the cost of budgeted machine operations (Doye and Sahs 2012). These cost estimates depend on the assumption that a sufficient quantity of custom operators could be hired to perform the operations in a timely manner. Both establishment budgets include a mowing operation designed to clip weeds that extend over the top of the switchgrass. If weed pressure is minimal, this operation would not be necessary.

Establishment costs are estimated to be $498/ha for no-till and $580/ha for conventional tillage. Stands of established switchgrass are expected to thrive for a minimum of ten years. The establishment costs are amortized over ten years at a 7 percent rate. This estimated amortized cost of establishment is $83/ha/year for conventional tillage and $71/ha/year for no-till. The $83/ha/year charge is included on the maintenance and harvest budget (Table 5).