Among nutrient inputs, nitrogen is the most critical for maintaining the productivity of established switchgrass stands. Nitrogen management and the feedbacks associated with harvest management have significant consequences for biomass yield, feedstock quality, environmental impact, and system economics. Consensus regarding appropriate recommendations for nitrogen management may be harder to find, however (Parrish and Fike

2005) . The broad range of responses to applied N is a function of inherent demand and capacity for recycling, soil type and N status, precipitation and atmospheric deposition, and harvest timing. For example, in a summary of yield responses to added N (vs. a 0-N control), Brejda (2000) found biomass yield increased from 0 to 6.2 Mg ha-1.

Long-term stand sustainability will be best supported by fertility management that replaces similar amounts of N in the harvest biomass (Lemus, Parrish, and Abaye 2008). Greater N inputs are required for

biomass (or especially forage) systems that collect multiple harvests (Parrish and Fike 2005; Fike et al. 2006a, b; Guretzky et al. 2011). Given the added costs associated with such management, one end-of-season harvest is the prevailing recommendation for bioenergy cropping. However, in some cases, multiple harvests may provide value to the system as a whole (Cundiff 1996; Fike et al. 2007; Cundiff et al. 2009) by reducing logistic constraints, and we will consider this further in a subsequent section.

Compared with many other potential energy crops, switchgrass has low nutrient demand. Although N needs during the growing season may be relatively high on a mass basis, plant N concentrations decline during the growing season (Waramit et al. 2011), and N is returned to roots and rhizomes at the end of the growing season (Beaty et al. 1978; Lemus et al. 2008; Garten et al. 2011). This ability to translocate nutrients to belowground storage structures is a major component of the apparent thriftiness of many perennial, warm season grasses (e. g., see Hargrave and Seastedt 1994). End — of-season nitrogen concentrations often are in the range of 5 to 8 g kg1 for plants harvested after senescence (Madakadze et al. 1999; Fike et al. 2006a, b; Guretzky et al. 2011). Fertility practices also affect switchgrass morphology, as plants grown at a higher level of N fertility apparently conduct a greater proportion of nutrients to shoots (vs. roots) than plants grown at a lower plane of nutrition (Heggenstaller et al. 2009; Garten et al. 2011). Nitrogen- fertilized switchgrass may also have fewer tillers, particularly under one-cut management (Fike et al. 2006a; Muir et al. 2001). These changes in plant morphology may not affect biomass yields (Muir et al. 2001) but may have consequences for carbon sequestration and greenhouse gas emissions (Garten et al. 2010). The relationships of N fertility to overall system sustainability in terms of increased biomass vs. reduced soil organic carbon stocks bears further investigation (Jung and Lal 2011).

Across regions, the data regarding switchgrass N requirements—and consequent recommendations—may seem rather disparate. Some of the greatest responses to applied N have occurred in sandy soils with little nutrient retention capacity (Ma et al. 2001; Muir et al. 2001). In contrast, Stout and Jung (1995) reported little response to N for switchgrass grown on soils with high levels of N in the soil organic pool. Along with inherent soil fertility, there is increasing evidence that bacterial-based biological nitrogen fixation and plant growth stimulation occurs with switchgrass in some settings (Tjepkema 1975; Riggs et al. 2002; Ker et al. 2010; Ker et al. 2012). Such reports help to further explain the negligible responses to N often reported for switchgrass (Parrish and Fike 2005) and increase the appeal of a plant that already gets high marks for its ability to capture, sequester, and recycle N from soils.

As input costs increase, the economics of applying fertilizer nutrients may be marginal in low-value, high-volume biomass production systems. Under such circumstances, developing management strategies with alternative nutrient sources may provide an important route to the production and economic sustainability of these systems. Several researchers have reported that animal manures can support switchgrass production (Sanderson et al. 2001; Lee et al. 2007, 2009) and Lee et al. (2007) suggest they may improve stand composition, but long-term increases in soil phosphorus and other nutrients will require monitoring. Adding legumes to these systems may be another approach for reducing N input costs. However, finding compatible species that do not reduce biomass production may be a challenge in some locations (El Hadj 2000; Springer et al. 2001; Bow et al. 2008) although some researchers have reported success with this strategy (Springer et al. 2001; Bow et al. 2008).

Plant tissues produce or regulate different hormones to respond to internal and external cues during practically every aspect of plant growth and development. Bacterial endophytes have the ability to produce plant hormones and regulate their balance as well. Auxin, a hormone associated with plant growth promotion, influences many plant cellular functions and is an important regulator of growth and development. Bacterial endophytes are commonly capable of producing auxin which, at the genetic level, may either be constituently expressed or inducible (Mattos et al. 2008). Auxin producing bacterial endophytes increased the number and length of lateral roots in wheat (Barbieri and Galli 1993). Increased root length, root surface area and the number of root tips were observed in hybrid poplar inoculated with auxin producing bacteria, resulting in enhanced uptake of nitrate and phosphorus and boosting biomass by 60% compared with non-inoculated plantlets (Taghavi et al. 2009). Furthermore, Pseudomona flourescen significantly increased the growth of maize plant radicles under laboratory conditions via the production of auxin (Montanez et al. 2012). To date, multiple auxin biosynthesis pathways have been identified in bacteria, and their regulation is controlled by several different genetic and environmental factors (Bertalan et al. 2009). The production of native auxin, indole-3-acetic acid (IAA) by bacteria has been documented in species such as Rhizobium, Pseudomonas, Azospirillum, Azotobacter and Bacillus (Hayat et al. 2010).

Cytokinins are a diverse range of compounds that, like other plant hormones, are involved in many activities of plant growth and development. As a group, they have been shown to regulate cell division, seed dormancy and germination, senescence, new bud formation, and leaf expansion. They also play roles in controlling plant organ development, mediating responses to various extrinsic factors and the response to biotic and abiotic stresses (Spichal 2012). Researchers have demonstrated that certain endophytic bacteria are able to produce cytokinins and promote lateral root growth (Senthilkumar et al. 2009). Zeatin, a native plant growth promotive hormone, belonging to the cytokinin family, has been found in significantly higher levels in the beneficial bacteria B. subtilis and P. putida (Sgroy et al. 2009).

Gibberellins are native plant growth promotive hormones. Many plant growth promoting endophytes also produce gibberellins to enhance host plant growth (Joo et al. 2009; Fernando et al. 2010). For example, one Penicillium citrinum isolate, IR-3-3 from the sand dune flora, produced higher physiologically active gibberellins and stimulated Waito-c rice and Atriplex gemelinii seedling growth (Khan et al. 2008). Gibberellic acid levels were also high in the plant associated bacteria Lysinibacillus fusiformis, Achromobacter xylosoxidans, Brevibacterium halotolerans, and Bacillus licheniformis (Sgroy et al. 2009).

Ethylene, a simple organic molecule (CH2=CH2), is commonly thought to be a growth inhibitive hormone. It is typically produced when plants are exposed to environmental stress, repressing plant growth and development until the stress disappears or the levels of ethylene decrease (Gamalero and Glick 2012). Ethylene inhibits stem elongation, promotes lateral swelling of stems, and causes stems to lose their sensitivity to gravi-trophic stimulation (Glick 2005). In biomass production as in agriculture generally, it is important to keep ethylene low in order to maximize yields. An enzyme, 1-aminocyclopropane-1-carboxylate (ACC) deaminase produced by bacteria, interferes with the physiological processes of the host plant by decreasing ethylene levels (Hardoim et al. 2008) via metabolizing ACC, a precursor to ethylene so ethylene levels are reduced in plants, and plant growth is promoted. Activity of ACC deaminase is a common feature found in plant-growth promoting bacteria such as Enterobacter, Pseudomonas and Burkholderia (Shah et al. 1998; Sessitsch et al. 2005; Govindasamy et al. 2008). Burkholderia phytofirmans strain PsJN stimulates growth of many plant species, including potato, tomato, grapevine, and switchgrass (Pillay and Nowak 1997; Nowak et al. 1998; Barka et al. 2002; Kim et al. 2012) and was reported to have a high activity of ACC deaminase (Sessitsch et al. 2005). Endophytes that produce ACC deaminase have also been shown to increase host plant growth in soils with high salinity (Egamberdieva 2012; Siddikee et al. 2012) and increase drought tolerance (Arshad et al. 2008; Belimov et al.

2009) . Pseudomonas sp. strain A3R3 showed higher ACC deaminase activity and increased plant growth in nickel contaminated soil (Ma et al. 2011).

Abscisic acid (ABA) is involved in responses to environmental stresses such as heat, drought, and salt, and is also produced by endophytes.

Endophytic bacterial strains SF2, SF3, and SF4 isolated from sunflowers (Helianthus annuus) had the ability to produce ABA and jasmonic acid, which increased under drought conditions (Forchetti et al. 2007), implying these endophytes enhance stress tolerance of host plants. Two strains of Azospirillum brasilensis, successfully used to increase the yield of maize and wheat in field conditions, were both able to produce different plant growth regulators such as IAA, gibberellic acid, zeatin and ABA (Perrig et al. 2007), highlighting the ability of endophytes to confer multiple mechanisms of growth promotion.

Matrix polysaccharides (i. e., hemicelluloses), are the second most abundant polymer in nature, and, as has been discussed, consist of heterogeneous polymers of pentoses (xylose, arabinose), hexoses (mannose, glucose, galactose), and sugar acids (Girio et al. 2010). Due to the abundance and functional importance of xylan in the cell walls of switchgrass, we focus here on the GHs that degrade xylan. However, enzymes that target every class of cell wall polysaccharide have been characterized (Table 3). Many microorganisms, such as Penicillium capsulatum and Talaromyces emersonii, possess complete degradation systems for grass glucuronoarabinoxylans (Filho et al. 1991). Like cellulose biodecomposition, total degradation of xylan also requires diverse enzymes for depolymerization and side-group cleavage. Endo-xylanases attack internal bonds in the main chains of xylans; exo-xylanases hydrolyze p-1,4-xylose linkages at chain ends to release xylobiose; and then p-xylosidase further hydrolyzes xylo-oligosaccharides and xylobiose to xylose (Gilbert et al. 2008). Side chains on xylose units block the action of some xylanases, leading to the evolution of diverse accessory enzymes to remove the side-chains and render the xylan backbone accessible for complete hydrolysis (Perez et al. 2002; Gilbert et al. 2008). Hydrolases with a-arabinofuranosidase and a-glucuronidase activities are responsible for removing arabinose and 4-O-methyl glucuronic acid substituents, respectively, from the xylan backbone. Furthermore, esterases hydrolyze linkages between xylose units and acetic acid (acetylxylan esterase) or between arabinose side chain residues and the hydroxycinnamic acids, ferulic acid (feruloylesterases) and p-coumaric acid (p-coumaric acid esterase).

Cellulosomes

The individual classes of hydrolases described above function within both non-complexed and complexed cellulase systems (Fig. 6) (Fontes et al. 2010). The non-complexed systems consist of individual polypeptides that can have multiple catalytic and CBM domains, but that otherwise act without interacting physically with other classes of hydrolases. In contrast, the complexed systems, also known as cellulosomes, are superstructural, multi-polypeptide enzyme complexes that adhere to cell walls of lignocellulolytic bacteria and fungi (Fontes et al. 2010). They consist of a multi-functional integrating subunit, called a scaffoldin, that is composed of multiple cohesion modules, and diverse enzymatic subunits with dockerin modules that interact with the scaffoldin. For example, the cellulosomes of C. cellulolyticium have the potential to contain numerous cellulases, xylanases, mannases, and even protease inhibitors (Blouzard et al. 2010).

Well-studied cellulosome-producing anaerobic bacteria include Clostridium species and Ruminococcus species (Doi et al. 2004). Cellulosome composition is dynamic and heterogenous, depending on the bacteria and composition of extracellular polysaccharides, and the relative amounts of the available dockerin-containing modules consistent with this (Raman et al. 2009). Cellulosomes have higher cellulose degradation efficiency compared with non-complexed enzymes since their adhesion to the cell surface prevents their products from being lost via diffusion or uptake by neighboring bacteria (Schwarz 2001). In vitro construction of mini — cellulosomes and self-assembly of cellulosomes on the surface of yeast significantly enhances cellulose hydrolysis compared with free enzymes (Wen et al. 2010; Fan et al. 2012; You et al. 2012).

Cellulosome-generating microorganisms also exhibit diversity in cellulosomal composition and architecture. For example, the Ruminococcus flavefaciens FD-1 genome encodes over 200 dockerin-containing proteins (Berg Miller et al. 2009); whereas, the Bacteroides cellulosolvens cellulosomes may possess more than 100 enzymes (Ding et al. 2000; Xu et al. 2004). This genomic diversity is likely functional. Proteomics of isolated cellulosomes from C. cellulolyticum confirmed the expression of 50 dockerin-containing proteins out of 62 predicted by bioinformatics (Blouzard et al. 2010). The complexity of the cellulosome is related to the availability and abundance of cellulosomal components, the expression of which is influenced by substrate induction and catabolite repression. For example, C. cellulolyticum grown on cellulose, expresses 36 cellulosome component enzymes. A partially distinct set of 30 cellulosome enzymes are detected on xylan; and 48 are expressed on wheat straw (Blouzard et al. 2010). Thus, cellulosomes are heterogeneous with varied components and stoichiometries. Moreover, some microbes exhibit even more diverse cellulosomes due to the presence of multiple types of scaffoldins within a single genome (Fontes et al. 2010). C. thermocellum contains four type II cohesion-containing anchoring scaffoldins (Bayer et al. 1998). For example, the cellulosomes assembled by the type II dockerin domain of CipA are further organized into a larger complex, called a polycellulosome, via type II cohesion-containing anchoring scaffoldins (Bayer et al. 1986; Raman et al. 2009). In short, cellulosomes generally have diverse content with heterogenous composition and architecture.

Over the course of the last decade, molecular markers have revolutionized how we view and measure genetic diversity at the DNA level. Historically, the DNA marker of choice was the microsatellite or simple-sequence repeat marker because of its simple PCR-based assay and large numbers of alleles per locus. As reference genome sequencing has become routine, a radical shift in polymorphism detection was eminent. The new marker of choice, single nucleotide polymorphism (SNP), has taken polymorphism discovery and genotyping to a completely new level. In a typical grass species like maize, the level of genetic diversity is quite high (~1 substitution per 100 bp) (Tenaillon et al. 2001), and the genome complexity is largely a result of DNA rearrangements and the captured genome space in the reference contains ~70% or less of the species-wide genome space (Gore et al. 2009). As 2nd generation costs have declined, and multiplexing options increased, a new strategy to assess genetic diversity and develop SNP markers has transformed genotype-phenotype associations (trait mapping), germplasm characterization, and molecular breeding strategies (Elshire et al. 2011). The approach, termed Genotyping-by-Sequencing (GBS) or Genomic Selection essentially reduces the complexity of the genome through digestion with one or two methylation sensitive enzymes that maximizes the amount of fragmented gDNA in the 300bp range, indexed with Illumina barcodes, and sequenced in a multiplex fashion on the Illumina HiSeq. The resulting sequences are assembled bioinformatically to produce consensus sequences flanking restriction sites that can either be used from a de novo perspective or mapped to a reference genome for SNP discovery (Baird et al. 2008). With the promise as a bioenergy feedstock and urgent need for genome enablement, a GBS approach to explore genetic diversity has the potential to immediately increase the amenability of switchgrass breeding programs. A recent study conducted by Lu et al. (2013) applies GBS to 840 individuals generating a total of 350 GB of DNA sequence. Of particular importance from these authors is the development of a pipeline called Universal Network Enabled Analysis Kit (UNEAK) tailored to enable dense SNP discovery and genomic selection in genomes without reference assemblies. UNEAK removes terminal low quality bases at the ends of reads, reads are collapsed into tags, and pairwise alignment identifies tag pairs with single base mismatches as candidate SNPs (Lu et al. 2013). In large complex genomes like switchgrass, there is an additional filter that removes tags that pair as a result of repeats, paralogs, and errors (Lu et al. 2013). In switchgrass, the authors created a full-sib linkage population of 130 individuals, a half-sib linkage population with 168 individuals, and an association panel composed of 66 diverse populations and 540 individuals and after sequencing, identified ~1.2 million putative SNPs (Lu et al. 2013). An important finding through the deep genotyping efforts revealed that tetraploid switchgrass is similar to a diploid in genomic composition (Lu et al. 2013), but further genome analysis and a more comprehensive dataset through genome resequencing and reference mapping is necessary for corroboration. Through these efforts, the authors constructed a high-quality linkage map using 3,000 of the highest quality SNPs and placed into a context of the 18 chromosomes, also guided by synteny with foxtail millet. This resource will be invaluable in advancing the genome reconstruction efforts described above.

A recent review by Mitchell and Schmer (2012) addressed switchgrass harvest and storage considerations and provides more detailed information. Herein, an overview of harvest timing, nutrient management, and logistics will be addressed. Regionally-specific best management practices and extension guidelines have been developed from extensive research and are critical to the commercialization of switchgrass for bioenergy in a given region (Hancock 2009; Wolf and Fiske 2009; Mitchell et al. 2010b).

Individual bacterial colonies can be identified by morphology, or the observation of colony colors and physical shapes observed under a microscope. Gram positive or negative cultures can be distinguished with staining. More recently, 16S rRNA gene sequences have widely been used to identify bacterial species and to construct a phenogram. Bacterial genomic DNA needs to be isolated in order to amplify specific 16S rRNA gene sequences using a standard bacterial DNA isolation protocol (Sambrook et al. 1989). For general bacterial endophyte classification, universal PCR primers F27 (5′-AGA GTT TAT CMT GGC TCA G-3′) and R1492 (5′-GRT ACC TTG TTA CGA CTT-3′) are used to amplify partial bacterial 16S rDNA sequences (Diallo et al. 2004). The ability of bacterial endophytes to fix atmospheric nitrogen can be tested by growing bacteria in nitrogen — free medium for several cycles of cultures or PCR can be used to amplify the nifH gene, which is a conserved region in the dinitrogenase reductase gene complex. Fatty acid analysis, carbon source utilization, and antibiotic resistance (hygromycin, chloramphenicol, gentamycin, kanamycin, ampicillin, streptomycin, tetracycline, and rifampin) could be done for further identification.

Biomass yield has been widely accepted as the major trait for improvement in breeding switchgrass as a bioenergy crop since the beginning of the US Department of Energy sponsored Bioenergy Feedstock Development Program (McLaughlin and Kszos 2005). Currently more than 10 switchgrass breeding programs have breeding efforts mainly focusing on improving biomass yield as the principal trait and developing superior cultivars with improvement in biomass yield and other selected traits (Casler et al. 2011). Biomass yield is considered to be the most important factor contributing to the development of an economically viable biofuel industry if switchgrass is selected as the major feedstock crop. Genetically improving biomass yield in switchgrass through the delivery of higher-yield cultivars will increase the profit margins of producers, reduce the cost per unit biomass yield, and decrease transport delivery distance of feedstock from farmer’s fields to a target biorefinery, consequently benefitting the whole chain of biofuel production. It is recommended for one-cut system by the end of a growing season to maximize yields or after the first frost to allow a longer harvest window and to increase retranslocation of nutrients to root systems or soil (Sanderson et al. 1999; McLaughlin and Kszos 2005; Makaju et al. 2012).

Biomass yield is a highly complex trait inherited in a quantitative manner and regulated by a large number of unknown genes, and heavily affected by environmental factors and genotype by environment interaction. Selection for biomass component traits may be feasible to indirectly improve biomass yield. Biomass yield is positively correlated with plant height with a significant coefficient of 0.69 and negatively correlated with plant maturity (r= -0.45) (Talbert et al. 1983). Lemus et al. (2002) also reported a high correlation between biomass yield and plant height. Using 11 lowland populations tested in two locations, Das et al. (2004) reported biomass yield was positively correlated with tiller number per plant with a coefficient of r=0.60 to 0.68, but not with plant height. The latter study suggested selection for more tillers per plant would be the most effective method for indirectly increasing biomass yield. Leaf blade length and width, stem diameter and node number per tiller have effects on biomass yield but are not consistent across locations (Das et al. 2004). Bhandari et al. (2010) reported positive correlations between biomass yield and tillering ability (r=0.73), and plant height (0.52), and stem thickness (0.38). Boe (2007) and Boe and Beck (2008) reported significant correlations between biomass yield and tiller weight, suggesting tiller weight can be used as a trait in indirect selection for biomass yield improvement. Overall, it is promising that use of tiller number, plant height and tiller diameter size as indirect selection traits for switchgrass biomass improvement.

In addition to biomass yield, many other traits, individually or in combinational forms have been included in breeding and selection activities. Seed dormancy is a long existing issue to the successful establishment of new stands using seed in switchgrass. Efforts to select for low post harvest seed dormancy have been made and led to a substantial increase in germination rates in ‘Alamo’ germplasm and a release of ‘TEM-LoDorm’ germplasm (Burson et al. 2009). Adaptation to target environments, cell — wall recalcitrance, abiotic stress (drought, cold) tolerance, and biotic stress resistance are some additional important traits in switchgrass breeding and selection process (Casler et al. 2011). Drought tolerance is critical as switchgrass is targeted to grow on marginal lands without supplementary irrigation. Leaf rust caused by Puccinia emaculata and smut by Tilletia maclagani are important diseases for switchgrass if grown in large areas (Parrish and Fike 2005).

Several experiments were conducted to estimate heritabilities for biomass yield and related traits, and forage quality traits. Forage use of switchgrass has taken place much before the identification of the species’ potential use as a bioenergy crop (Vogel 2004). One important trait for forage use is to improve forage quality, including dry matter digestibility. Godshalk et al. (1986) and Hopkins et al. (1993) reported moderate to medium narrow- sense heritability for in vitro dry matter digestibility (IVDMD). Phenotypic recurrent selection was effective in improving populations for increased IVDMD, which led to the development and release of ‘Trailblazer’ (Hopkins et al. 1993) and ‘Performer’ (Burns et al. 2008a). Among the traits related to biomass yield, heritabilities for days to heading and days to flowering are relatively high (Bhandari et al. 2010). For plant height, Talbert et al. (1983) reported high narrow-sense heritability, while estimates were low based on variance component analysis of half-sib families, and were medium based on parent-half-sib progeny regression by Bhandari et al. (2010). Similarly, narrow-sense heritability estimates for stem thickness, tillering ability, plant spread and spring regrowth are inconsistent due to differences in genetic structures (half-sib versus full — sib families) and data sources (individual plant data versus plot mean) in the experiments.

Being the major trait as targeted for developing the species as a bioenergy feedstock crop, biomass yield has narrow-sense heritability estimates ranging from 0.12 to 0.25 (Talbert et al. 1983; Godshalk et al. 1986; Rose et al. 2008; Bhandari et al. 2010 and 2011). The low values were estimated on the basis of variance components from data of individual plants among families. But in some of the same experiments, higher heritabilities were also obtained on plot yield mean data, suggesting heritability estimates from midparent-progeny regression tend to be biased upwards (Bhandari et al.

2011) . Collectively, the tested low heritability for biomass yield indicates that direct phenotypic selection for increased biomass yield may not be effective. Breeding and selection procedures capturing additive variation and increasing frequency of additive genes responsible for the trait need rigorous progeny evaluation in the improvement of breeding populations. Improved populations can serve as germplasm pools for making synthetics and even be released as cultivars per se.

It has been reported that miRNAs play an important part in regulating some key genes in their own biogenesis (Xie et al. 2003; Vaucheret et al. 2004; Vaucheret 2006). For example, DCL1 is the target of miR162, and AGO1 is the target of miR168, indicating a negative role miRNAs play in their own biogenesis (Xie et al. 2003; Vaucheret et al. 2004; Liu et al. 2005; Vaucheret 2006). Recent studies also discoverd that the primary transcripts of trans-acting siRNA (tasiRNA) TAS1, TAS2, TAS3 and TAS4 are cleaved by miR173-AGO1, miR390-AGO7 and miR828-AGO1, demonstrating that miRNAs are also involved in the regulation of siRNAs (Allen et al. 2005; Montgomery et al. 2008a, b; Cuperus et al. 2011).

Switchgrass MiRNAs

Herbicides for Establishment

Switchgrass has small seed (~600,000 to 900,000 seeds kg-1) that often are reported to be slow to establish (Aiken and Springer 1995). This characteristic provides a competitive advantage to weeds, resulting in excessive competition during establishment (Masters et al. 2004; Boydston et al. 2010; Mitchell et al. 2010a). Controlling weeds during the establishment year improves establishment and increases biomass production in subsequent years (Schmer et al. 2006; Mitchell et al. 2010a). Using current agronomic recommendations, it is feasible to produce 50% of the yield potential of the cultivar to be available for harvest after a killing frost in the planting year, and produce and harvest 75-100% of the yield potential of the cultivar in the first full growing season after planting (Mitchell et al. 2010a; Mitchell et al. 2012).

Warm-season annual grass weeds are the most detrimental to successful switchgrass establishment, since broadleaf weeds can easily be controlled with 2,4-D amine 2,4-dichlorophenoxyacetic acid, when switchgrass reaches the 4-leaf stage (Vogel 2004; Anonomous 2008b). Cool-season weeds are relatively easy to control since they can be controlled with glyphosate prior to planting (Sanderson et al. 2012). Use of a pre-emergence herbicide is typically recommended as an aid in establishing warm-season grasses. For example, application of metolachlor and/or atrazine [6-chloro-N-ethyl- N-(1-methylethyl)-1,3,5-triazine-2,4-diamine] was reported to improve biomass yield in big bluestem (Andropogon gerardii Vittman) during the second year (Masters 1997). In three environments in the central and northern Great Plains, pre-emergence application of atrazine and quinclorac (3,7-Dichloro-8-quinolinecarboxylic acid) resulted in acceptable stands and high biomass yields (Mitchell et al. 2010a). No differences were detected among switchgrass lowland and upland ecotypes for tolerance to atrazine and quinclorac. The use of a pre-emergence herbicide to control such weeds needs evaluations in other environments.

There are very few herbicides currently labeled for use during switchgrass establishment. The scientific literature provides limited information on the phytotoxicity and efficacy of the herbicides used in other warm-season grasses when used for weed control in switchgrass establishment. Currently only quinclorac (Paramount®; Anonymous 2008c,

2010) is labeled in the USA, while nicosufuron (Accent®; Anonymous 2008a) has a supplemental label in the state of Tennessee for weed control during switchgrass establishment once it reaches the 2-leaf stage. In non-crop areas and Conservation Reserve Program (CRP) sites, sulfosulfuron (Outrider®; Anonymous 2011a) controls johnsongrass, and nutsedge (Cyperus sp.) when applied to newly seeded switchgrass after the 3-leaf stage. Use of atrazine, which is labeled for corn (Zea mays L.) and CRP plantings of switchgrass, has led to successful establishment of upland switchgrass as a companion crop in corn fields (Hintz et al. 1998). Although atrazine can improve switchgrass establishment by controlling broadleaf weeds and cool-season grasses (Martin et al. 1982; Bahler et al. 1984), it does not control warm — season annual grass weeds (Boydston et al. 2010; Mitchell et al. 2010a). Injury to switchgrass is reported to differ with herbicide used, application rates, growth stage at application, and the ecotype of switchgrass being evaluated. Research results have varied and are sometimes contradictory. Mitchell et al. (2010a) reported that lowland and upland ecotypes had comparable tolerances to atrazine and quinclorac that effectively controlled weeds and resulted in acceptable plant stands in both switchgrass ecotypes. ‘Pathfinder’, an upland ecotype, is reported to have greater tolerance to pre-emergent applications of atrazine, and the use of atrazine aids its establishment (Martin et al. 1982; Vogel 1987; Masters et al. 1996; Hintz et al. 1998). However, despite this tolerance, there are reports of increasing injury in Pathfinder as atrazine application rate increases from 1.1 to 2.2 kg ha1 (Martin et al. 1982; Vogel 1987; McKenna et al. 1991; Masters et al. 1996; Hintz et al. 1998). Imazapic (2-[4,5-dihydro-4-methyl-4-(1-ethylethyl)- 5-oxo-1H-imidazol-2-yl]-5-methyl-3-pyridinecarboxylic acid) often reduced switchgrass stands and is not recommended for switchgrass establishment (Mitchell et al. 2010a).

Despite these successes for atrazine use in upland ecotypes (Bovey and Hussey 1991), recommended that atrazine should not be used when establishing Alamo, a lowland switchgrass ecotype, due to excessive injury. Furthermore, the phytoxicity of atrazine may also be site specific. Bahler et al. (1984) reported that atrazine application reduced switchgrass seedling density, with the degree of damage being greater in loamy sandy soil than in silty clay loam soil. The upland switchgrass cultivar ‘Cave-in­Rock’ tolerated atrazine (1.1 kg a. i. ha-1), while a lowland strain derived from Alamo was killed by atrazine (T. J. Butler, unpublished data). Time to rainfall after planting appears to mediate atrazine activity on lowland switchgrass. In an Oklahoma study, atrazine application followed by rainfall the succeeding day resulted in complete lowland switchgrass mortality. The second year, however, rainfall did not occur for two weeks upon atrazine application, and the lowland switchgrass had only transient injury (T. J. Butler, unpublished data).

Some alternatives to atrazine have been evaluated. For example, an application of 1.6 kg a. i. siduron ha-1 effectively controlled large crabgrass with no effect on ‘Caddo,’ an upland switchgrass ecotype (McMurphy 1969). However, subsequent work indicated that a pre-emergence application of 2.2 kg ai siduron ha-1 caused significant injury to Alamo, a lowland ecotype (Bovey and Hussey 1991). Although Mitchell et al. (2010a) reported that both upland and lowland switchgrass ecotypes tolerated 560 g a. i. ha-1 quinclorac applied pre-emergence in the central and northern Great Plains, similar quinclorac pre-emergence applications in the southern Great Plains have reduced lowland switchgrass emergence (T. J. Butler, personal comm.). Masters et al. (1996) reported that imazethapyr improved big bluestem establishment (77-94%) similar to atrazine (18-95%) and proved a suitable replacement for atrazine when establishing big bluestem; however imazethapyr generally reduced switchgrass establishment (stand frequency) of the upland ecotype ‘Trailblazer’. Although the concern for using atrazine is valid in some regions, atrazine has been used effectively in hundreds of small plot trials and production scale fields on all available upland and lowland switchgrass strains in the central and northern Great Plains.

Post-emergence herbicides have also demonstrated mixed results. However, in well-managed established stands, such herbicide application is seldom needed (Mitchell et al. 2010a). Applications of quinclorac at 0.56 kg a. i. ha-1 or pendimethalin at 1.1 kg a. i. ha-1 at the 1-2 leaf stage have been shown to improve weed control but reduce switchgrass in irrigated stands in the arid west (Boydston et al. 2010). Post-emerge quinclorac applications reduced switchgrass biomass at establishment by 33% compared to a control receiving pre-mergence atrazine only, but this effect was less than an yield 89% reduction with post-emerge pendimethalin application (Boydston et al. 2010). However, in rain-fed production in the central and northern Great Plains, the application of quinclorac to established upland and lowland switchgrass strains has not been observed to reduce stands. Work by Curran et al. (2011) showed that quinclorac applied 4 wk after planting achieved better weed control in Cave-in-Rock switchgrass than when applied 6 wk after planting. Additionally, application of 2.2 kg a. i. ha-1 MSMA to greenhouse grown lowland switchgrass at the 3-to-4-leaf stage did not cause significant injury compared to the control (Bovey and Hussey 1991). Kering et al. (2012b) evaluated lowland switchgrass establishment with competition from large crabgrass [Digitaria sanguinalis (L.) Scop.], broadleaf signalgrass [Urochloa platyphylla (Munro ex C. Wright) R. D. Webster], Johnsongrass [Sorghum halepense (L.) Pers.], and Texas panicum [Urochloa texana (Buckley) R. Webster] and reported that switchgrass establishment was improved with a combination or quinclorac + foramsulfuron + pendimethalin at the 1-2 leaf stage (13-26% stand) and MSMA at the 3-4-leaf stage (7-35% stand) compared to an untreated control (0-3% stand). However such results are less than satisfactory based on a minimum goal of 40% coverage at the end of the first season (Vogel 1987; Masters 1997).

The best outcomes for switchgrass establishment result from using sound agronomic practices for weed control. For example, when grass weeds are controlled the previous season, especially where glyphosate — tolerant soybeans, corn, or cotton are grown, switchgrass has a much greater chance of successful establishment (Christensen and Koppenjan 2010; Mitchell et al. 2010a). Mitchell et al. (2010a, 2012) provided recommendations that produce harvestable yields after a killing frost in the planting year if precipitation is adequate: 1) develop a good seedbed (no-till seed into soybean stubble or clean till and pack to leave a faint footprint); 2) plant within 3 weeks before or after the optimum maize planting date; 3) use high quality certified seed of adapted material; 4) plant at least 300 PLS m-2; 5) use a planter that controls depth and plant seeds 0.6 to 1.2 cm deep; 6) manage weeds with a pre-emergent application of 1.1 kg ha-1 of atrazine plus 560 g ha-1 of quinclorac then mow or spray broadleaf weeds with

Another mechanism of plant growth promotion by endophytes is bio­control of pathogens. Endophytes have evolved a diverse range of bio­control mechanisms including production of antibiotics, both antifungal and antibacterial, siderophore secretion, and enzyme production (reviewed by Compant et al. 2005b). Together, these bio-control properties enable endophytes to outcompete pathogens for their niche and limit damages caused by plant pathogens as well as protect their host plant, resulting in increased survival and growth.

Fungal endophytic colonization confers a positive impact on resistance to pests, mites, and nematodes in grasses (Schardl et al. 2004). Perennial ryegrass (L. perenne) plants colonized by N. lolii reduced aphid populations, adult life span and fecundity (Meister et al. 2006). Neotyphodium spp. form mutualistic associations with several grass genera and produce a range of bio-control agents, some of which have insecticidal properties whereas others are associated with health and welfare issues for grazing animals. Through selection, several novel endophytes that produce predominantly insecticidal bio-control agents have now been successfully commercialized in many temperate grassland areas in New Zealand, Australia, USA, and South America (Easton 2007).

One of the most commonly recognized bio-control mechanisms associated with endophytic plant growth promoting bacteria and fungi is the production of antibiotics. Agents produced include but are not limited to pyrrolnitrin, phenazines, herbicolin, and oomycin. Furthermore, many endophytic organisms are able to produce multiple agents, which have bio-cidal properties towards various organisms. Pyrrolnitrin, a secondary metabolite isolated from B. cepacia, was shown to have activities against both phytopathogenic fungi and bacteria (El-Banna and Winkelmann 1998). The gene cluster regulating the production of pyrrolnitrin is similar to the gene cluster in Pseudomonas and was suggested to have been acquired by horizontal gene transfer (de Souza and Raaijmakers 2003). Other strains of Burkholderia were reported to produce a large variety of anti-fungal agents such as occidiofungin and burkholdinesn (Lu et al. 2009; Tawfik et al. 2010). Burkholderia MP-1 produces at least four anti-fungal compounds including phenylacetic acid, hydrocinnamic acid, 4-hydroxyphenylacetic acid, and 4-hydroxyphenylacetate methyl ester (Mao et al. 2006). The small size of genes encoding antibacterial agents and the relatively small number of genes in bacteria and fungi may allow genes encoding antibiotic agents to be transformed to various growth promoting endophytes.