Strategies for Improving Switchgrass Vegetative Growth and Biomass Yield

Increasing biomass yield is one of the main goals in switchgrass breeding programs (Schubert 2006; Sticklen 2006; Bouton 2007). In general, delaying flowering can extend and promote vegetative growth thereby increasing biomass yield. Biomass accumulation in plants can stop when transitioning from vegetative to reproductive growth. Therefore, controlling flowering time could be an effective strategy to change the biomass yield in switchgrass genetic improvement. For most plant species, flowering is one of the complex traits regulated by many factors, including genetic and environmental components (temperature, photoperiod and other factors) (Distelfeld et al. 2009; Jung and Muller 2009). Several miRNAs have been implicated in this process. As mentioned above, miR156 has been used to modify flowering time and biomass production in switchgrass (Chuck et al. 2011; Fu et al. 2012). MiR156s delay vegetative growth phase by repressing the expression of their targeted SPL genes, which are positive regulators of another miRNA, miR172 (Xie et al. 2006; Wang et al. 2009; Wu et al.

2009) . In Arabidopsis, miR172 acts downstream of miR156 through SPL9 and represses one of its target SMZ, which represses the transcription of FLOWERING LOCUS T (FT) (Mathieu et al. 2009). This pathway conserves in many plant species, so it is possible to manipulate miR172 and its target genes to regulate flowering time and biomass yield in switchgrass. It also has been reported that overexpression of miR319 leads to down-regulation of several TCP targets and results in delayed flowering in Arabidopsis (Palatnik et al. 2003) and rice (Yang et al. 2013). This suggests that miR319 might be another candidate useful for adjusting flowering time and biomass production in switchgrass.

Proper timing is critical for any success, and perhaps no group is more acutely aware of this than farmers. Numerous activities must be completed to promote success in agronomic production systems, but the overarching factor is getting the work done in a timely fashion. For switchgrass establishment, timing plays an essential role in ensuring adequate soil moisture and temperature, at providing the best chance for favorable precipitation patterns, and for minimizing weed competition. Planting date is thus a key management consideration for successful switchgrass establishment (Smart and Moser 1997; Parrish et al. 2008)—and perhaps the subject of some controversy.

A review of the recommended planting seasons for successful switchgrass establishment may prove confusing to the uninitiated. Planting in mid-spring (late April to mid-May) has been recommended in Missouri in order to reduce weed competition and avoid risks associated with high temperature and soil moisture deficits common in summer months (Hsu and Nelson 1986a, b), but timing planting to avoid weed pressure will likely need to vary by region or even by field given differences in weed types and pressures by season and location. Timing recommendations (mid-spring) for Nebraska were similar where atrazine was used for weed control (Vassey et al. 1985). However, other Nebraska researchers suggested early spring plantings would be most successful due to greater morphological development (Smart and Moser 1997). Mitchell et al. (2010b) recommend planting switchgrass 2 or 3 weeks before or after the recommended corn planting date in Nebraska.

In Virginia, late spring/early summer plantings have been recommended in order to avoid cool-season weed pressures and to catch warm soils (Wolf and Fiske 2009) that may be closer to optimum for seed germination (Hsu et al. 1985). Such practice requires planting seed of low dormancy—either by planting aged seed that are after-ripened (Shen et al. 2001) or by using stratification techniques (Wolf and Fiske 2009). However, on-farm stratification can prove impractical for large plantings.

Oklahoma research has shown that both late summer/early autumn and late spring plantings can be successful for upland ecotypes which had fewer weed control issues (Foster et al. 2012). At low latitudes in the southern Great Plains, seedling growth with fall plantings can be sufficient to give upland switchgrass ecotypes an earlier start in spring and may also decrease soil erosion in fields over the winter. However, autumn plantings of lowland ecotypes were not recommended at this latitude (Foster et al. 2012) and winter seedling survival becomes a critical issue as one moves to greater latitudes.

As noted by Foster et al. (2012), late autumn/early winter planting dates have some potential utility for stand establishment. Perhaps one of the greatest benefits of such seeding timings is that they can naturally overcome the dormancy associated with new crop seed—that is, as long as this remains an issue.

From this section the reader should recognize that the data are clear in their equivocation. That is to say site-specific management considerations need to be made for decisions on time of seeding. General rules of thumb would be that late autumn/winter or spring (dormant season) plantings are viable if weed control is manageable; later spring plantings may be appropriate if seed dormancy is low and soil moisture is adequate. Windows of planting opportunity are likely to expand if varieties with high germination rates at low temperatures are commercialized (as, e. g., in Seepaul et al. 2011).

Plant growth is usually limited by biotic and abiotic stresses. Abiotic stress includes various environmental stresses, such as drought, temperature, salinity, air pollution, heavy metals, pesticides and soil pH. Biotic refers to living organisms that cause diseases, such as bacterial and fungal pathogens, pests, insects, viruses, and nematodes. Symbiotic relationships with endophytes and mycorrhizal fungi have been shown to increase stress tolerance in host plants (Gibert and Hazard 2011).

Abiotic Stress Tolerance

Drought is one of the most wide spread and common abiotic stresses and causes economically important losses in agriculture and forestry crops every year. The mutualistic symbiosis between bacterial or fungal endophytes or AM fungi and host plants could enhance host plant drought tolerance. For example, Japanese Bitter Orange (Poncirus trifoliate) seedlings

inoculated with AM fungus Glomus mosseae enhanced plant height and

increased relative water and chlorophyll contents when seedlings were subjected to three days of water depletion (Fan and Liu 2011). Similar results were observed when AM fungus inoculated rice plants were under drought conditions, with increased levels of protective compounds, such as ascorbate and proline, produced in the plants (Ruiz-Sanchez et al. 2011). The evergreen tree Theobroma cacao infected with the endophytic fungus Trichoderma hamatum isolate DIS 219b exhibited delayed drought stress by changes in stomatal conductance, water potential, and net photosynthesis (Bae et al. 2009).

In grasses, endophytic associations also increased drought tolerance as some accessions of the perennial ryegrass (Lolium perenne) infected by N. lolli showed more tillers, greater tiller length and higher biomass than non-infected plants (Kane 2011). Endophytic inoculation of Epichloe festucae in Fetusca eskia enhanced seedling survival under drought conditions (Gibert and Hazard 2011). A perennial bunchgrass Achnatherum sibiricum infected with endophytic fungi showed a higher root/shoot ratio and net photosynthetic rate than non-inoculated plants under drought conditions (Han et al. 2011). The symbiosis between Agrotis hyemalis and Epichloe amarillans produced 40% more inflorescences, earlier flowering and greater seed mass than non-inoculated plants under drought conditions (Davitt et al. 2011). However, when Panicum rigidulum plants were subjected to drought conditions, endophyte Balansia benningsiana infected plants did not show any advantages over control plants during drought stress but endophyte infection helped rapid leaf regrowth during recovery (Ren and Clay 2009).

Cultivated soils are becoming more saline due to excessive fertilizer use, the use of wastewater from urban and peri-urban areas and agricultural drainage as well as the desertification processes (Bashan and de-Bashan

2010) . Plant growth promoting bacteria offer the potential to reduce the impact of this stress. For instance, cucumber plants inoculated with Paecilomyces formosus showed increased shoot length compared with that of non-inoculated plants under high salinity conditions (Khan et al. 2012). In studies with Salicornia brachiata, the most salt-tolerant plant species among Salicornia spp., Brachybacterium saurashtrense and Pseudomonas sp. bacterial endophytes significantly increased plant growth under salt stress conditions. The bacteria Pseudomonas putida and P. pseudialcaligens inoculation increased plant growth of chickpeas under saline conditions in pot experiments (Patel et al. 2012). Inoculation of AM fungi Glomus mosseae, G. deserticola and Gigaspora gergaria enhanced the growth of wheat (Triticum aestivium) under high salinity conditions as well as increased nutrient uptake (potassium, nitrogen, phosphorus and magnesium), proline levels, acid and alkaline phosphatase activities, and total soluble protein content (Abdel-Fattah and Asrar 2012).

Phytoremediation is the process by which plants can uptake, accumulate, or metabolize toxic compounds, such as heavy metals, from contaminated soil (Kumar et al. 1995). The plant-endophyte association has been used at phytoremediation sites to degrade toxic compounds for practical use (Van Aken et al. 2004). Brassica juncea inoculated with a plant growth promoting bacterium strain A3R3 showed increased plant growth when grown in soil at different concentrations of nickel, with the increases of fresh and dry weights by 50 and 45%, respectively at 450 mg nickel/kg soil compared with non-inoculated plants (Ma et al. 2011). Many plant growth — promoting endophytes could alleviate plant stress from contaminants by degrading such contaminants, and in return, could provide the products for plant use (Weyens et al. 2009a, b). For phytoremediation of toxic metals, endophytes may have a metal-resistant or sequestration system and could reduce metal toxicity and influence metal translocation to the aboveground plant parts. Metal-resistant endophytic bacteria have been found in the genera Pseudomonas, Methylobacterium, Microbacterium and Burkholderia. In tall fescue (Lolium arundinaceum) grown under greenhouse conditions in a solution contaminated with cadmium, endophytic fungus (Neotyphodium coenophialum) infection enhanced cadmium accumulation and increased cadmium transport from roots to the shoots (Ren and Gao 2011). In Festuca arundinacea and Festuca pratensis grasses, grown under high cadmium conditions, results showed higher biomass production and higher levels of cadmium accumulation in the roots and shoots of endophyte-infected plants versus uninfected plants (Soleimani et al. 2010). Under greenhouse conditions, the seedlings of guinea grass (Panicum maximum) cultivars inoculated with Pantoea spp. Jp3-3 exhibited significant alleviation from the negative effect caused by the stress of 300 pM copper (Huo et al. 2012). Switchgrass and two other grasses, bahia grass (Paspalum notatum) and Johnson grass (Sorghum halepenese), were inoculated with two AM fungi, Glomus mosseae and G. intraradices, and results showed that the aboveground biomass of these three grasses contained 26.3 to 71.7% of the total amount of 137Cs, and 23.8-88.7% of the total amount of 90Sr (Entry et al. 1999). The proportion of contaminant removal from the soils by these plant species was significantly increased, possibly due to root colonization by mycorrhizal fungi and the high density of roots (Entry et al. 1999).

AM fungi also have the ability to boost switchgrass plant growth under acidic soils. Of the AM fungi tested, Glomus clarum and G. diaphanum aided to increase the dry matter of plants on soils at pHca 4 and pHca 5 compared with the non-inoculated plants (Clark et al. 1999a). The benefits of AM fungi could be attributed to an increase in acquisition of mineral nutrients such as phosphorus and a decrease of the toxic elements ferrous, boron, aluminum and manganese (Clark et al. 1999b), which are present in acidic soils.

Biochemical conversion of pretreated lignocellulose into biofuels generally consists of four steps—glycosyl hydrolase production, enzymatic hydrolysis of cellulose and hemicellulose, hexose fermentation, and pentose fermentation (Lynd et al. 2002). Figure 5 shows the spectrum of processing platforms, which range from separately accomplishing each step to combining all steps, which when optimized is generally found to improve efficiency (Lynd et al. 2002). The more steps involved in the process, the more time required to complete a fermentation cycle and money used for capital equipment.

Separate enzyme hydrolysis and fermentation (SHF) completes each step as an independent unit. This process allows enzymatic hydrolysis and microorgnism-based fermentation to be carried out each at their own optimal conditions. However, a major problem accompanying separate hydrolysis is the inhibitory effects on cellulase activity caused by accumulated products, like glucose and cellobiose (Philippidis et al. 1993; Gruno et al. 2004). For instance, glucose at 3 g per L reduces p-glucosidase activity by 75% (Philippidis et al. 1993). To release the inhibitory effect, microorgnisms can be added to immediately ferment these products and maintain them at a low concentration.

This combination of enzymatic hydrolysis and fermentation to release enzymatic product inhibition generates another platform, simultaneous saccharification and fermentation (SSF) (Olofsson et al. 2008). This process has been successfully applied to convert lignocellulose to enthanol with higher yield, lower enzyme doses and less capital equipments than SHF (Olsson et al. 2006; Saha et al. 2011; Zhu et al. 2012). In a comparison with ethanol production by Saccharomyces cerevisiae from unpretreated cassava pulp under a variety of feeding regimes, SSF yielded ~50% more ethanol than the similar SHF process (Zhu et al. 2012). On the other hand, other reports showed that the accumulation of enthanol reversibly inhibits cellulase activity (Podkaminer et al. 2012). To maximize the fermentation efficiency of SSF, the key is to select hydrolases and fermenting microorgnisms with similar optimum temperature and pH. However, most microorgnisms need a lower optimum temperature than hydrolases, which makes
saccharification a limiting factor to SSF. One method that researchers trying to overcome this difficulty have designed is nonisothermal simultaneous saccharification and fermentation (NSSF), in which saccharification and fermentation occur simultaneously but in two separate bioreactors at different temperatures, coupled with recirculation of fermentation broth between these two bioreactors (Wu et al. 1998; Oh et al. 2000). So far, this system presents several advantages compared with SSF, including higher ethanol yields, shorter residence time and lower enzyme inputs.

For processing hemicellulose-rich biomass, the aforementioned bioconversion processes all require an additional, separate pentose fermentation step with different microorgnisms in another bioreactor. Simultaneous saccharification and cofermentation (SSCF) aims to improve on SSF by fermenting both pentoses and hexoses in a single bioreactor, with a selected or engineered microorganism or community (Lynd et al. 2002). Recently SSCF has been applied to ferment commercial furfural, corn kernels, and pretreated wheat straw (McMillan et al. 1999; Zhu et al. 2007; Olofsson et al. 2010; Tang et al. 2011). As with other platforms, process details appear to have a large impact. In one recent example, Olofsson and associates were able to increase the xylose conversion from 40% to 50% with both enzyme and substrate continuous feeding compared to only substrate feeding (Olofsson et al. 2010). (Feeding refers to the addition of materials to the reactor.)

Cellulase purchase is a common and significant cost in all of the preceeding processes (Lynd et al. 2008). The newest concept in bioconversion processes is referred to as consolidated bioprocessing (CBP), which employs a microbial consortium for hydrolase production, saccharification and fermentation in a single step in a single bioreactor (Lynd et al. 2002). CBP offers the potential to lower production costs due to simpler conversion processing, lower energy and capital inputs and higher conversion efficiencies than other processes. However, the key challenge of CBP is that there are not yet ideal CBP-enbaled microorganism capable of efficient cellulose hydrolysis and biofuel synthesis. Lynd and colleagues have promoted two alternative strategies to enable CBP as follows: (i) engineering naturally occurring cellulolytic microorganisms to improve biofuel-related properties such as yield and titer, and (ii) engineering non-cellulolytic organisms that exhibit high biofuel yields and titers to express heterologous lignocelluolytic enzyme, enabling cellulose utilization (Lynd et al. 2005). For strategy (i), Clostridium species with native lignocellulose-degrading abilities have been metabolically engineered to synthesize a variety of biofuels, such as hydrogen, isopropanol, butanol and ethanol (Higashide et al. 2011; Lutke — Eversloh et al. 2011; Lee et al. 2012). So far for strategy (ii), E. coli and yeast have been engineered to directly convert cellulose and xylan to ethanol and biodiesel (Steen et al. 2010; Bokinsky et al. 2011; Goyal et al. 2011; Fan et al. 2012). To further promote biomass conversion efficiency, researchers have promoted the idea of co-cultures, in which non-biofuel products generated by one microorgnism could be further converted to biofuels by another organism, or in which the metabolism of one microorgnism could be boosted by the presence of another one. For instance, the co-culture of hyper-cellulase producer, Acremonium cellulolyticus C-1, and an ethanol producer, S. cerevisiae, realized one-pot bioethanol production (Park et al.

2012) . In another example, a co-culture of Clostridium strains produced H2 at higher rates and with similar yields compared to the pure strains (Masset et al. 2012). Nonetheless, numerous challenges need to be met prior to industrial application of CBP. Among the challenges are low fuel yields, and fuel inhibition of microbial growth.

Christopher Saski[11] and Hong Luo[12]‘*

Introduction

It is now widely accepted that we are in an era of unpredictable climate change as a result of accelerated global warming largely due to our ever — increasing use of the decreasing reserve of fossil fuels causing elevating emissions of detrimental greenhouse gases, a transition from nonrenewable carbon sources to renewable bioresources for energy generation is of great importance to address the concerns about energy challenges in relation to global climate change. The use of non-food energy crops as renewable fuels on a global scale has many advantages beneficial to current ecological and economic issues. The C4 perennial species, switchgrass (Panicum virgatum, L. Poaceae) has been identified as an herbaceous biomass fuel crop (Vogel 1996, 2004). Primarily planted for land conservation, and utilized for forage and hay (Moser and Vogel 1995), switchgrass produces 540% more renewable than consumed nonrenewable energy with its cellulosic ethanol emitting 94% less greenhouse gas than gasoline, serving as an excellent biofuel feedstock (Schmer et al. 2008). Trait modifications using conventional and molecular breeding as well as transgenic approaches

will significantly enhance the great capacity of switchgrass plants for more cost-effective bioenergy production. The development of genomics tools in this important bioenergy crop is the key to help facilitate and accelerate genetic improvement of switchgrass for enhanced biomass production and more efficient bioconversion. This chapter summarizes recent advances in switchgrass genomics research focusing on structural genomic resources development and their important applications. We also discuss the significance and prospects of developing functional genomics, proteomics and metabolomics tools as well as genome sequencing initiatives in switchgrass.

Few insects have been identified as potential pests of switchgrass, and early studies indicate the species is not a preferred host for many insect species (Davis 1914; Walkden 1943). Switchgrass typically is an inferior host relative to other warm-season crops (Nabity et al. 2011; Prasifka et al. 2011a), and fall armyworm (Spodoptera frugiperda (J. E. Smith) (Lepidoptera: Noctuidae)) has reduced survivorship on switchgrass compared with other grasses (Nabity et al. 2011). Variation in armyworm resistance among switchgrass strains cultivars also has been observed (Dowd and Johnson 2009).

While insect damage has been considered minimal, there is potential for this to increase if or when switchgrass for bioenergy systems scale up (Parrish and Fike 2005). Little published data is available on insect pressures during establishment. However, corn flea beetle Chaetocnema pulicaria (Chrysomelidae) damage has been common in Virginia plantings (Dale Wolf, personal communication) and insect pressures during the seedling stage likely represent greatest insect threat to the switchgrass stand productivity.

Grasshoppers (Saltatoria) are known to feed on switchgrass, but the extent of the damage has not been quantified (Parrish and Fike 2005). Schaeffer et al. (2011), in a baseline study of insects in Nebraska switchgrass stands, found that about 60% of arthropods collected were of the orders Thysanoptera and Hymenoptera; leafhoppers, grasshoppers, grass flies and wire worms were noted as the most abundant of potential pest species.

Life stages, geographic distribution, and the symptoms of a stem­boring caterpillar, Blastobasis repartella (Dietz.), recently have been described (Adamski et al. 2010; Prasifka et al. 2010). Switchgrass is the only known host for this caterpillar (Prasifka et al. 2011b), and in a distributional survey B. repartella was found both in cultivated and natural switchgrass stands in eight northern USA states (Prasifka et al. 2010). The species was not observed at southern locations (Arkansas, Louisiana, Oklahoma, and Texas) but lack of observation could not rule out presence at these latitudes. In four northern states (Illinois, Nebraska, South Dakota, and Wisconsin) 1 to 7% of tillers were damaged by B. repartella.

A new species of gall midge (Chilophaga virgate Gagne (Diptera: Cecidomyiidae)) was recently discovered in South Dakota, USA (Boe and Gagne 2011). Proportion of tillers infested with the gall midge in 10 switchgrass genotypes ranged from 7 to 22%. The mass of infested tillers was 35% lower than that of normal tillers, and infested tillers produced no appreciable seed. Such insect pests and associated yield reductions may well become more evident or more common as switchgrass is grown more extensively.

For endophytic fungal growth, surface-sterilized tissues are cut into small pieces or homogenized using a homogenizer and plated on Potato dextrose agar (PDA) or other fungal culture media, such as MEA medium (2% malt extract and 1.8% agar) (Vallino et al. 2009) supplemented with several antibiotics, such as ampicillin (100 mg/L), chloramphenicol (50 mg/L) and streptomycin (50 mg/L) to prevent bacterial growth (Ghimire et al. 2011; Craven K, personal communication). Plates containing tissues are incubated at 25-28°C for up to one month. Observations should be taken every day in order to isolate individual strains for further identification. The growing fungal colonies are then re-plated on fresh medium to obtain individual colonies.

Sexual and asexual reproduction systems and associated mechanisms are essential for the breeders to determine both general features of a breeding program and specific procedures of hybridization, selection and cultivar development. The inflorescence of switchgrass is a typical open and diffuse panicle of 20-60 cm in length and 20-40 cm in width (Fig. 1). Each panicle consists of many to hundreds of spikelets, with two dissimilar florets in each spikelet (Tyrl et al. 2002). The lower floret is staminate while the upper one is perfect (Fig. 2). Stigma of each perfect floret exerts out of lemmas about 1-3 days earlier than anthers.

But the stigma is still receptive when anthers shed pollen grains on the same floret. The morphological structure and blooming behavior of florets provide specific conditions which may favor outcrossing over selfing. Switchgrass has long been recognized as a naturally cross-pollinating species (Jones and Brown 1951). The peak period of pollen shedding in a day occurs from 10 am to 4 pm (Jones and Brown 1951). Dispersal of pollen grains is facilitated by wind. Occasionally, pollen grains can form a visible tunnel (like a swirl) in the air over a large switchgrass planting. Anthesis duration of a panicle is about one to two weeks long, which may be affected by genotypes and environmental factors.

Talbert et al. (1983) reported that bagged inflorescences on average produced less than 1% seed yield as compared to open-pollinated inflorescences on the same plants in an experiment of 33 plants. Their results indicated that switchgrass produces seed primarily through cross pollination while self-pollination is minimal. Using verified tetraploid and octoploid plants in a greenhouse, Taliaferro and Hopkins (1996) concluded that there is a strong genetic barrier between tetraploid and octoploid plants. Martinez-Reyna and Vogel (2002) reported the cross­fertility between octoploid and tetraploid plants is inhibited by a post­fertilization incompatibility system. They observed tetraploid by octoploid or reciprocally fertilized zygotes have a much slower growth than tetraploid by tetraploid or octoploid by octoploid zygotes. However, the cross-fertility between tetraploid upland and lowland plants is substantial or quite normal, and switchgrass outcrossing behavior is enforced by self-incompatibility (Taliaferro and Hopkins 1996; Martinez-Reyna and Vogel 2002). However,

seed set of selfing octoploid plants was as high as 6% (a range of 0-35%) while less than 1% (0-1.5%) selfed seed is produced in bagged inflorescences of tetraploid plants (Taliaferro and Hopkins 1996). Martinez-Reyna and Vogel (2002) noted the self-incompatibility in switchgrass is controlled by a gametophytic prefertilization incompatibility system, which is similar to the S-Z incompatibility system commonly seen in many members of the Poaceae plants. It appears tetraploid plants tend to be less self-fertile than octoploid plants. In later experiments, Taliaferro (2002) reported some lowland switchgrass plants of ‘Alamo’ and ‘Kanlow’ produced more than 20 selfed (S1) seeds from bagged plants while selfing plants of ‘Caddo’, ‘Blackwell’ and ‘Cave-in-Rock’ produced 100 or more seeds.

Recently, molecular markers have been available and used to accurately identify breeding origin of progeny of two controlled crosses (Okada et al. 2010b; Liu and Wu 2012). Okada et al. (2010b) found about 4% progeny of a full-sib cross between a ‘Kanlow’ (female) and an ‘Alamo’ (male) parents are selfed. In an attempt to make a full-sib cross-fertilized mapping population, two lowland plants: ‘NL94 LYE16x13’ (NL94) and ‘SL93 7×15’ (SL93) were grown in a large growth chamber before they were blooming. From the seed harvested from the female parent NL94 plant, 456 progeny were grown in a greenhouse (Liu and Wu 2012). Using 12 simple sequence repeat markers, they identified 279 of the progeny population were selfed progeny of NL94 whereas only 39% (177) were crossed between the two parents. The selfed progeny percentage is much higher than those reported before. However, whether the NL94 plant would produce a similar amount of selfed and crossed progeny when grown under field conditions and when other crossing compatible switchgrass plants are available, is not known. The authors speculated that limited wind flow in the growth chamber enhanced NL94 self-fertilization and reduced cross fertilization. Similarly, it has been observed that some other switchgrass genotypes have a self­pollination rate as high as 50% as cited by Casler et al. (2011).

Switchgrass can be reproduced in asexual ways. In breeding programs, switchgrass clones are normally produced by digging selected field-grown stands and separating into individual ramets, which are used to establish new crossing blocks. But it is difficult to use the labor intensive method to produce a large amount of clones. A micropropagation method to produce switchgrass by nodal culture has been reported (Alexandrova et al. 1996). With nodal segments cultured on an optimized MS medium, 500 plantlet clones can be produced from one parent plant within a period of three months. In our own experience, mature nodes of switchgrass genotypes can be cut into 1- or 2-nodal segments, when grown into a good soil medium and maintained moisture for two or three weeks, new clonal plants will grow out from the buds on the nodes (Fig. 3a and 3b). The greenhouse-type nodal propagating methods may be useful in producing clonal plants of the same size, which are important in quantitative trait loci (QTL) mapping experiments.

It appears there is large variation for breeding behavior in switchgrass. This is not surprising because switchgrass is genetically very diverse. Switchgrass is a predominantly wind-facilitated outcrossing species. Conventional breeding and selection methods have been developed and used based on the major mating system. It is also possible to inbreed switchgrass, at least in some genotypes. Breeding methods exploring the mating systems will be discussed in detail in latter sections.

MiRNAs are important regulators playing important roles in plant development and plant responses to biotic and abiotic stresses as well as in regulating miRNAs themselves and other small RNAs (Bartel 2009; Chen 2009; Chuck et al. 2009; Poethig 2009; Voinnet 2009; Zhu et al. 2009). Many miRNA families have multiple members with different temporal and spatial expression patterns (Palatnik et al. 2007; Nag et al. 2009; Voinnet

2009) . Mature miRNAs usually have multiple targets, which constitute a complicated regulatory network impacting different aspects of plant life (Axtell and Bowman 2008; Bartel 2009; Rubio-Somoza and Weigel 2011).

The 1992 Annual Progress Report of the DOE’s Biofuels Feedstock Development Program (Wright et al. 1993) supported the selection of switchgrass as a model bioenergy crop by stating, "the examination of data on yield potential, production economics, and regional site potential, led in 1991 to the selection of a perennial forage grass switchgrass as a model species for further research", recognizing that "more than one species will certainly be required ultimately, switchgrass was seen as an excellent beginning with the available programmatic resources". Several important characteristics such as being a widely adapted native species, a demonstrated capacity for high yields on relative poor quality sites, a significant capacity to improve soil quality by sequestering carbon, improved erosion control, reduced fertilizer and pesticide requirements, a capacity for providing wildlife cover, and a strong potential appeal to landowners supported this decision (Wright et al. 1993). Extensive research has continued to support the feasibility of switchgrass for bioenergy (Mitchell et al. 2012b).

Bioenergy efficiency and sustainability is held to a different standard than energy produced from petroleum since renewable fuels must have lower greenhouse gas (GHG) emissions and higher net energy values (NEV) than petroleum based transportation fuels (Mitchell et al. 2010a). The NEV, net energy yield (NEY), and the ratio of the biofuel output to petroleum input [petroleum energy ratio (PER)] have been used to quantify the energy efficiency and sustainability of ethanol produced from switchgrass (Schmer et al. 2008). Farrell et al. (2006) developed an energy model using estimated agricultural inputs and simulated yields and predicted switchgrass produced 700% more output than input energy. Schmer et al. (2008) validated the modeled results with actual inputs from switchgrass grown at the field scale on 10 farms in Nebraska, South Dakota, and North Dakota. They concluded that switchgrass produced 540% more renewable energy than non-renewable energy consumed over a 5-year period, had a PER of 13.1, and that average GHG emissions from switchgrass-based ethanol was 94% lower than estimated GHG emissions for gasoline (Schmer et al. 2008).

To sustain an agricultural production system, carbon inputs must equal or exceed the carbon outputs or soil organic carbon (SOC) will decline and overall system productivity will decline (Mitchell et al. 2010a). Historically, about half of the SOC present in pre-agricultural grasslands was presumed lost in the conversion of perennial grasslands to annual cropland that occurred after European settlement (Mitchell et al. 2010a). Consequently, SOC trend is an excellent indicator of the long-term sustainability of a production system. SOC increases rapidly when annual cropland is converted to switchgrass (Mitchell et al. 2010a). In just 5 years, growing and managing switchgrass for bioenergy on three marginally productive cropland sites in the Central Plains resulted in an average SOC increase of 2.9 Mg C ha1 yr-1 in the top 1.2 m of soil (Liebig et al. 2008). Growing switchgrass increased SOC at rates ranging from 1.7 to 10.1 Mg C ha1 yr-1 throughout North America (Garten and Wullschleger 2000, Zan et al. 2001, Frank et al. 2004; Lee et al. 2007). In irrigated switchgrass in the arid regions of the Pacific Northwest, 5-years of switchgrass cropping resulted in a 1.2 Mg ha-1 increase in SOC in the 0 to 15-cm depth, with no change below 15 cm (Collins et al. 2010).

Modeling efforts and numerous field studies have demonstrated that growing and managing switchgrass for bioenergy on sites formerly in row crop production rapidly and significantly increases SOC, improves soil quality, and promotes long-term sustainability (Liebig et al. 2005, 2008; Schmer et al. 2011; Follett et al. 2012). A limitation with many modeling efforts is that SOC accumulation is usually only predicted for sampling depths of 30 to 40 cm (Follett et al. 2012) and may be underestimating actual SOC accumulation. For example, a 9-year study on rainfed switchgrass and maize had average annual increases in SOC that exceeded 2 Mg C ha1 year-1 for the 0 to 150 soil depth and over 50% of the SOC increase occurred below 30-cm (Follett et al. 2012). The SOC for switchgrass was 2 to 4 times greater in this study than that modeled in life-cycle assessments to date. They concluded that sampling soil to only 30 to 40 cm is inadequate and

future analyses and modeling should include deep soil sampling to fully account for SOC accumulations in both switchgrass and maize (Follett et al. 2012). Chapter 12 addresses specific approaches to modeling switchgrass biomass production.

Switchgrass production for bioenergy is economically feasible (Perrin et al. 2008; Mitchell et al. 2012a, b). A large regional field scale trial was conducted in 50 production environments on 10 farms in Nebraska, South Dakota, and North Dakota (Perrin et al. 2008). Actual on-farm production costs were tracked for each farm, including land costs, which accounted for nearly half of the production costs. The cost of production for switchgrass to the farm gate averaged $66 Mg-1 (Perrin et al. 2012). Five farmers delivered switchgrass to the farm gate at an average cost of $52 Mg-1over the 5-year period. The 5-year average cost for farmers with experience growing switchgrass was $39 Mg1, and one producer grew switchgrass for $34 Mg1. Switchgrass farm-gate costs tend to decline over time with highest costs occurring on a per mass basis during the establishment year; a result of high input costs and low biomass yields (Perrin et al. 2008). When the authors projected field production for 10 years, farm-gate delivery costs were reduced to $46 Mg-1. They concluded that, with experience, farmers could achieve switchgrass production costs of $40 to $55 Mg1. Assuming a conversion rate of 0.329 liters of ethanol per kg of switchgrass, the farm-gate feedstock cost would range from $0.12 to $0.16 L1 (Perrin et al.

2008) . Land and other production costs have increased since the regional field scale study was completed. Perrin et al. (2012) estimated an updated switchgrass farm-gate price of $75 Mg1 and $60 Mg1 for biomass yields of 6.7 Mg ha1 and 13.5 Mg ha1, respectively. Farm-gate costs in growing switchgrass for bioenergy are largely variable with respect to yield, with approximately 25% of total costs being fixed (Perrin et al. 2012). Farm-gate prices are also dependent on land type being converted, regional variations in land costs, yield potential, and rotation time length. An estimated 5.1 x 106 ha to 11.8 x 106 ha could be allocated to switchgrass production in the United States by 2030 assuming a farm gate price of $44 Mg1 to $66 Mg1 (USDOE 2011). Future improvements in large-scale harvest machinery and implementation of farm telematics will likely reduce variable switchgrass harvest and delivery costs. See Chapter 13 for a more detailed discussion of the economics of switchgrass feedstock production.

Conclusions

Switchgrass is the most advanced herbaceous perennial feedstock for bioenergy. Switchgrass research has been conducted for more than 75 years, with a focus on bioenergy for more than 20 years. Mitchell et al.

(2012) reported on the feasibility of growing switchgrass for bioenergy. They reported that all practices for growing switchgrass for biofuels including establishing, managing, and delivering to the biorefinery gate have been developed, with specific management requirements for most US agroecoregions (Mitchell et al. 2012). They concluded that the research to date fully supports that switchgrass for bioenergy is productive, protective of the environment, and profitable for the farmer. Additionally, switchgrass has been seeded on millions of hectares of CRP grasslands since 1986, so it is familiar to many producers. Further research on the processes of converting switchgrass to transportation fuels at the commercial scale is needed. Additionally, field-validating some of the models for deploying switchgrass at the landscape scale are needed to demonstrate the feasibility and environmental benefits, especially for wildlife, of large-scale feedstock production. Switchgrass has high biomass production potential, wide adaptability, low fossil fuel energy requirements, and is compatible with modern agriculture practices making it an ideal herbaceous energy crop for large-scale bioenergy production. Significant research has been conducted on switchgrass genetics, agronomic management, and harvest practices which will be invaluable for an emerging cellulosic bioenergy industry.