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Manuscript Number: Title: Biomass Production and Nutrient Utilization of Perennial Grasses under No Inputs in South Georg ia Article Type: Original Research Keywords: biomass crops; energycane; low

- input agriculture; napiergrass; switchgrass Corresponding Author: Joseph E. Knoll, Ph.D. Corresponding Author's Institution: USDA

- ARS First Author: Joseph E. Knoll , Ph.D. Order of Authors: Joseph E. Knoll, Ph.D.;William F. Anderson, Ph.D.;Timothy C. Strickland, Ph.D.;Robert K. Hubbard, Ph.D.;Ravindra Malik, Ph.D.1

Running Head: Perennial Grasses under No Inputs Article Type: Research Paper
Title: Biomass Production and Nutrient Utilization of Perennial Grasses under No Inputs in South Georgia
Authors: Joseph E. Knoll (corresponding author)
USDA

- ARS, Crop Genetics and Breeding Research Unit
P.O. Box 748 Tifton, GA 31793, USA Tel: (229) 386

- 3177 FAX: (229) 391

- 3701
E

- mail: joe.knoll@ars.usda.gov

William F. Anderson
USDA

- ARS, Crop Genetics and Breeding Research Unit
P.O. Box 748 Tifton, GA 31793, USA

Timo thy C. Strickland
USDA

- ARS, Southeast Watershed Research Unit
P.O. Box 748 Tifton, GA 31793, USA Manuscript Click here to download Manuscript: Biomass and Nutrient Usage of Perennial Grasses-JK-submission.docx2

Robert K. Hubbard
USDA

- ARS, Southeast Watershed Research Unit
P.O. Box 748 Tifton, GA 31793, USA

Ravindra Malik College of Sciences & Health Professions, Department of Natural Sciences Albany State University Albany, GA 31705 , USA

Abstract
Warm

- season perennial grasses have great potential for sustainable biomass production in
the Southeast , and should be productive on marginal lands . This study was ini tiated in fall 2005 at Tifton, GA, to assess the performance of perennial grasses under rainfed conditions and no fertilizer inputs. The test included one energycane ( Saccharum sp.) , two accessions of napiergrass ( Pennisetum purpureum Schum.), two experim ental lines of switchgrass ( Panicum virgatum L.) , and three giant reed ( Arundo donax L.) clones

. Each winter, dry matter (DM) yield, moisture, and biomass nutrient contents were analyzed. Soil samples (15 cm) were collected each year, and deep soil core s were sampled in 2009 to assess possible changes in soil
nutrients

. Napiergrass averaged 31.6 Mg DM/ha for the first two years, and energycane averaged 25.5 Mg DM/ha for the first three years. Though lower yielding, switchgrass had good biomass quality , tending to be lowest in nitrogen, ash, and moisture at harvest. N apiergrass took up large quantities of potassium in the first season (704 kg K/ha), but only about half as much3

the next season with similar DM yields. Energycane was found to utilize potassium more efficiently than napiergrass. Some evidence of potassium depletion in the soil profile was found for napiergrass, but no evidence of nitrogen depletion was observed in the soil

. Biomass nitrogen content was, however, correlated with DM yield for the energycane, one napiergrass, and one switchgrass, suggesting that this nutrient was limiting in later seasons.

Keywords : biomass crops, ener gycane, low

- input agriculture, n apiergrass, switchgrass

Abbreviations :
BNF

– Biological nitrogen fixation
DM

– Dry matter

Introduction Increasing energy demand with reduced reserves , irregular fluctuations in fuel prices, and concerns about climate change caused by burning of fossil fuels have brought about renewed
interes t in producing energy from renewable sources. Of particular interest is bioenergy, which is energy derived from biomass, either through direct combustion or through conversion to liquid fuel, such as bioethanol. Wood waste from milling and paper processi ng, as well as agricultural and municipal waste can all be burned to produce energy. In addition, over four billion gallons of bioethanol are produced in the U.S. each year, primarily from corn and other grains (Gray et
al. , 2006). However, these sources alone cannot meet the projected demand for renewable bioenergy, and the shift of corn and other food/feed sources to fuel production is raising concerns about effects on food prices. The EPA released the provisions of the Renewable Fuel Standard4

in 2008 to include production of 21 billion gallons of ethanol from non

- food sources (

. Additionally, production of fuel from annual grain crops is relatively energy

- inefficient. These concerns have led to the development of dedicated bioenergy crops. Perennial grasses have perhaps the greatest potential for production of biomass in the Southeastern U.S. The Southeast has warm summer temperatures and generally receives adequate, though sometimes erratic, rainfall, but generally has poorer soils when compared to the Great Plains. Perennial grasses, especially those which utilize the C 4 photosynthetic pathway, should be able to take advantage of the warmer temperatures, and their deeper, more extensive root systems should be able to adapt to poor soils and occasi onal droughts . Though initial establishment of perennial grasses may be more expensive and energy

- intensive than planting conventional annual crops, a substantial reduction in costs and energy inputs over the long

- term should be expected with perennials ( Boehmel et al. , 2008; Karp and Shield, 2008 ). In addition, evidence suggests that perennial agriculture would have fewer negative impacts on the environment in terms of water consumption and quality, soil loss, and nutrient loss, compared to annual system s (Glover, 2003). The milder winter temperatures in the Southeastern U.S. allow for the cultivation of subtropical perennial bunch grasses, including n apiergrass ( Pennisetum purpureum Schum.) , energy canes ( Saccharum hyb

. ), and Erianthus sp., a s well as th e more temperate C 3 grass giant reed ( Arundo donax L.). These grasses are generally propagated vegetatively from stem cuttings, similar to the method used to propagate sugarcane ( Saccharum officinarum L.) . In the Southeast stem cuttings are planted in late summer to early autumn so that growth begins before the onset of winter dormancy. Napiergrass, also known as elephantgrass, is native to tropical Africa. In tropical and subtropical areas it is an important forage species, where it is capable of pro ducing very high yields of biomass (Magalhães et al ., 2006; de Queiros Fil ho et al., 2000), even in poor5

soils (de Morais et al. , 2009). In Brazil, de Queiros Fil ho et al. (2000) reported dry matter (DM) yields of 30.9 Mg DM/ha at 100 days after planting using the cultivar ‘Roxo’. Also in Brazil, Magalhães et al

. (2006) reported a more conservative yield of 18.9 Mg DM/ha in n apiergrass harvested only 84 days after planting. These studies were conducted in plots with adequate nitrogen fertilizer, but de M orais et al. (2009) achieved similar yields in N

- depleted soils at nine months after planting. Subsequent harvests also yielded significant, though decreasing, quantities of biomass . In Puerto Rico, a yield of 52.8 Mg DM /ha/yr (85

- d cutting interval) was reported for the cultivar ‘Merkeron’ (Sotomayor

- Rios et al. , 1997). In tests conducted in Florida under irrigation and adequate fertilization, first

- seas on yields of PI

- 300086 and N51

n apiergrasses averaged 45.7 and 47 Mg DM /ha, respectively (Woodard and Prine, 1993). ‘Merkeron’, which was developed in Tifton, GA, has survived winter temperatures as low as

- 18°C (Burton, 1989), so its potential range could be extended to cooler locations (USDA hardiness zone 7b, possibly zone 7a; USDA, U.S. National Arbo retum, 2002)

. Energy canes are derived from crosses between cultivated sugarcane ( S

. officinarum L.)
and related wild species ( S. spontaneum L., S. robustum Brandes & Jesw ex. Grassl. , Erianthus sp., etc.), and were developed specifically for the purpose o f producing biomass for energy production. They generally have much higher fiber content and better cold tolerance than
sugarcane varieties used for sucrose production ( Legendre and Burner, 1995 ). Energycane L 79

- 1002 yielded an average of 49.0 Mg DM/ha in first

- year growth in tests conducted near
Gainesville , F L, by Woodard and Prine (1993). A t St. Gabriel, LA, over five seasons this cultivar achieved an average annual yield of 66.6 Mg DM/ha (Bischoff et al. , 2008). Similarly high yields were reported for the cultivar US 72

- 1153 by Mislevy et al. (1995). Average yields of 43 and 52 Mg DM/ha over four years were reported at two different levels of nitrogen6

fertilization (168.1 and 336.1 kg N/ha/yr), though yie lds tended to decline significantly in the
third or fourth season. Giant reed (

Arundo donax L.) is a large C 3 grass that is used for various purposes, including the production of reeds for musical instruments. Because of its rapid growth and high
biomass production, it has recently gained attention as a potential bio energy crop in southern Europe ( Angelini et al. , 2005; Cosentino et al. , 2006; Mantineo et al. , 2009 ) and the Southeastern
U.S

. Among 39 clones of giant reed evaluated in southern Italy, an a verage yield of 10.6 Mg
DM/ ha in the first year and 22.1 Mg DM/ha in the second year were reported by Consentino et al. (2006). In the third year after planting giant reed in Sicily, Mantineo et al. (2009) reported a yield of 38.8 Mg DM/ha. Giant reed is tolerant of heavy metals ( Papazoglou , 2007 ) and high salinity (McWilliams, 2004), so it could potentially be grown on contaminated sites not suitable for production of other crops. It is relatively cold

- tolerant, growing as far north as southern
Illinois an d Missouri (USDA, NRCS, 2009). One potential drawback of these exotic grasses is their potential to become invasive weeds. Giant reed in particular has received considerable attention as an invasive pest in aquatic habitats where it had been i ntroduce d for erosion control (Quinn and Holt, 2008)

. Despite this limitation, giant reed could potentially be a useful bioenergy crop in specific locations if it is properly managed and not planted near aquatic habitats. Giant reed is limited to vegetative disp ersal; though it flowers in temperate environments, successful seed set has not been documented i n the U.S. (McWilliams, 2004). In some warmer locations, such as extreme southern Florida, n apiergrass and energycane may flower and set seed, and have the po tential to become invasive

. However, in areas where frost halts the growth and flowering of the plant, seed is not produced, thus reducing unintentional spread. Because all of these grasses are reproduced easily from stem pieces, care must be taken7

to eliminate accidental releases during transportation from production fields to the receiving bioenergy facilities. More research is also needed to determine the best methods (i.e. herbicides, mechanical control, etc.) for eradicating any unwanted releases of exotic bioenergy crops. Native prairie grasses have been proposed as a low

- input, ecologically sustainable source
of biomass for much of the U.S

. Unlike exotic species, native plants are generally considered

non
- invasive, and they provide ideal habita t for wildlife. In addition, natives should require fewer inputs as they are already adapted to local conditions and disease pressures. Native species considered for use as biomass include big bluestem ( Andropogon gerardii Vitman ) and switchgrass ( Panicu m virgatum L. ), two of the predominant species of the tallgrass prairies of
the Great Plains. Switchgrass has been extensively evaluated as a native biomass source . It is a relatively long

- lived perennial grass with a very broad range of adaptability. I t is propagated by seed and can also be used for forage or hay , and thus it may be readily adopted by growers with little to no investment in new equipment. Several high

- yielding improved varieties of switchgrass are already available . A yield of 34.6 Mg DM/ha has been reported for the lowland cultivar ‘Alamo’ (Sladden et al., 1991) , but typical yields are much lower

. Mooney et al. ( 2009 ) estimated average yields of 16.82 Mg/ha/yr for ‘Alamo’ switchgrass on good farmland in Tennessee, while Lemus et al. (2008) reported more modest yields averaging 6.8 Mg/ha for the upland cultivar ‘Cave

- in

- Rock’ in southern Iowa. Yields are typically lower for the more northerly

- adapted upland types. Ideally, biomass crops should be able to grow on marginal lands so th at they do not compete with other crops for better farmland. Also, because the per

- unit value of biomass is low compared to food, feed, and fiber crops, production under minimal inputs is desirable for growers to profit from producing biomass. Surprising ly, few studies have been conducted to8

compare the performance of different biomass feedstock species in the same field under low

input conditions. The purpose of the present study is to evaluate and compare the performance of several potential biomass cr ops for the Southeast under no inputs, with the aim of determining which species will be most adaptable to marginal conditions. Dry matter (DM) yield, moisture at harvest, and ash content were assessed each season. Uptake of nitrogen , potassium, and othe r nutrients was monitored throughout the study to determine which crops utilize these nutrients most effectively. Changes in nutrient content in the soil were also assessed. Lastly , the extensive root systems of perennial crops are expected to sequester a significant amount of carbon in the soil. Thus, the status of soil carbon w as also monitored throughout this study , and root biomass was measured in soil cores, to determine the extent to which these crops may contribute to soil improvement

.

Materials and Methods

Plant m aterial and experimental d esign This study was initi ated 2 Sept. 2005 at Tifton, GA, and was located on a Tifton loamy
sand ( fine

- loamy, kaolinitic, thermic Plinthic Kandiudults )

. In preceding years the site had been used for switchgrass plots, and for annual grain crops before that. The plots were laid out in a randomized complete block design with four replications. Plots measured 4 m × 7 m. Eight entries with potential for use in bioenergy production were in cluded in this test: one energycane ( Saccharum hyb .) L 79

- 1002; two n apiergrasses ( Pennisetum purpureum Schum.) ‘Merkeron’ and N51; two experimental switchgrass ( Panicum virgatum L.) line s , designated PV

- 1 and PV

- 2 (both are lowland ecotype) ; and three giant reed ( Arundo donax L.) clone s , AD

- S, AD

- E, and9

AD

- F

. Energycane and n apiergrass were planted as stem cuttings, with two whole stems planted in each row, buried horizontally 10 cm deep, with rows spaced 0.6 m apart (four rows/plot). The giant reeds were micropropagated transplants, derived from clones collected in the Southeast,
and were planted 0.6 m apart in rows 0.6 m apart. Switchgrass was seeded in rows 0.3 m apart ( seven rows/plot ) at a seeding rate of 11.2 kg seed /ha

. A bare

- ground plot was also included in each replication as a comparison for soil properties.

Biomass harvest
Total above

- ground biomass from the center of each plot (harvested area = 5 m × 1.2 m)

was mechanically harvested after senescence on Dec. 5, 2006, Dec. 11, 2007, and Dec. 9, 2008. The 2009 harvest was delayed until Feb. 3, 2010 due to mechanical problems with harvesting equipment and inclement weather. At harvest, a small sample of biomass from each plot was weighed fresh, dried comp letely at 65°C in an oven, and then weighed again to determine percentages of moisture and dry matter. Samples of dried biomass w ere then ground in a Wiley mill to pass a 2 mm screen prior to storage and further analyses.

Biomass nutrient analyses
Total carbon and nitrogen percentages in the dried plant samples were measured by dry
combustion in a Vario EL

- III Universal CHNOS Elemental Analyzer (Elementar Analysensysteme, Hanau, Germany) using approximately 5 mg dried, ground tissue

. The percentage of total ash in biomass was determined by combustion in a Muffle furnace at 450 °C
for six hours. Two replicates were also analyzed for percentages of individual mineral elements10

( K, P , Ca, Mg, Mn, and Zn) at the University of Georgia Agricultural and Environ mental
Services Laboratories (AESL) by inductively

- coupled plasma (ICP) spectro metr y.

Soil sampling and analysis Each year after harvest (Jan. 30, 2007; Jan. 15, 2008; and Apr. 2, 2010) surface layer (0

- 15 cm) soil samples were taken from each plot. Five to ten samples were taken from each plot
and were then combined. On Apr. 30, 2009 soil cores to a depth of 107 cm were collected from the center of each plot, immediately adjacent to a growing clump using a hydraulic tractor

mounted soil probe (Giddi ngs Machine Co. Fort Collins, CO ). Cores were separated into four portions for analysis (0

- 15 cm, 30

- 45 cm, 60

- 76 cm, and 91

- 107 cm). A subsample of each portion was used for estimation of root biomass (g dry roots/kg dry soil). All soil samples were

ov en
- dried and ground in a mill prior to storage and analysis. Soil samples were analyzed for C and N content by dry combustion. Approximately 50 mg dried, ground soil was sampled for this analysis. Roots from the soil cores were also dried, ground, and a nalyzed for C and N content (5 mg samples) ; pieces of rhizome (typically found in giant reeds) were not sampl ed

. Soil m ineral composition (K, P, Ca, Mg, Mn, and Zn) was determined in the core samples by the Mehlich

- I
extraction procedure followed by ICP a nalysis at the AESL

. Soil pH in the surface samples (2007, 2008, and 2010) was measured at the AESL using an AS

- 3000 pH Analys er (LabFit, Perth, Australia ) by mixing dry soil with 0.01 M CaCl 2 in a 1:1 (w/v) ratio. Equivalent pH in
water was then calcula ted by adding 0.6 pH units (Kissel and Sonon, 2008). Soil pH in the core sections (2009) was measured in

- house by mixing dry soil and deionized water in a 1:1 (w/v) ratio and reading the pH with an electrode after standing for 10 min. Due to differences in11

sampling, the C, N, and pH measurements f ro m the surface layer in the cores were not combined
with the yearly analyses.

Statistical procedure s All y early d ata were analyzed using the GLM procedure in SAS v. 9.2 (SAS Institute, Cary, NC) according to the following model:

y = μ + Y + R + E + (Y × R) + (Y × E) + (R × E) + ε
where y is the dependent variable, μ is the overall mean, Y is the year, R is the replication, E is the entry, and ε is the error term. Unless otherwise noted, all tests were conduc ted at a probability level of α = 0.05. Data from the 2009 soil cores were analyzed using a similar model, except that the variable year (Y) was replaced with the variable soil depth (D). Tests for differences between entries within years or soil depths were also conducted using PROC GLM. Tukey’s HSD test or the Tukey

- Kramer test was used to determine significant differences
between means and least

- squares means. Correlation analyses were conducted using PROC
CORR.

Results Total dry matter (DM) yield varied greatly between entries, and was strongly affected by year. The entry by year interaction was also significant (Table 1). In the first season, the two napiergrass entries (Merkeron and N51) and energycane L 79

- 1002 had the highest DM yields (30.6, 37.1, and 29.2 Mg DM/ha, respectively ; Table 2 ). These three entries maintained similar yields in the second season. Yields of switchgrass and g iant reed were generally much lower than for napiergrass and energycane, especially in the first two seasons

. However, i n the third12

season, dry matter yield of napiergrass had declined significantly to levels similar to that of giant reed and switchgrass. In contrast, energycane L 79

- 1002 maintained relatively consistent high yields over the first three seasons, averaging 25.5 Mg DM/ha. L 79

- 1002 had the highest yield in the third season (21.1 Mg DM/ha), but this was not statistically higher than the napiergrasses (Table 2). Yields of gi ant reeds and switchgrasses were relatively constant over the entire four years of the test, with a slight, but not statistically significant, peak in the second season. Both switchgrass entries performed si milarly in terms of DM yield, and t he three gian t reed entries also showed similar yield performance. Though giant reed clone AD

- S tended to yield slightly less than the other two clones, the difference was not sta tistically significant. All eight entries in the test had very low yields in the fourth year (2009), and the yield differences between them were not significant within that year , except for L 79

- 1002 (8.2 Mg DM/ha) and AD

- S (3.3 Mg DM/ha)

. Percent moisture of harvested material was significantly different among years, even though the first t hree years were all harvested in the first or second week of December. The first season showed the highest moisture content, and the lowest average moisture content was observed in the 2009 harvest, which was delayed until February, 2010. There was a sma ll entry by year interaction for moisture, but the most significant factor was the entries themselves. In 2006, 2008, and 2009 the entries fell into three distinct groupings based on moisture. Napiergrass and energycane had the highest moisture content, giant reed s were intermediate, and switchgrass had the least moisture ( Table 2 ). There was some overlap between these groupings in 2007, but the general trend was still observed. The interaction of years and entries was thus relatively small, and in gene ral, the moisture contents of napiergrass and energycane were only slightly affected by year. Giant reeds were slightly drier in the late harvest in 2009, but the13

differences between preceding years were only s ignificant for one clone, AD

- S. The effect o f year on moisture content was strongest for switchgrasses, which were significantly drier in 2009 , primarily due to the later harvest (average 22.3%) than in 2006 or 2007 (average 37.4% and 37.7%, respectively ; Table 2 ).
The aver age nitrogen percentage o f the combined biomass feedstocks was not significantly different between the first two years, but dropped significantly in both the third and fourth years. Nitrogen percentage also varied significantly between entries, and the year by entry
interaction w as also significant (Table 1). Giant reeds tended to have the highest nitrogen content (0.590

– 0.692 % in 2006, 0.297

– 0.334 % in 2009), while switchgrasses had the lowest (average 0.244% in 2006, average 0.177 % in 2009; Table 3 ). Nitrogen content was not significantly different between any entries in 2007. T he nitrogen contents of the switchgrasses

were also the lowest in 2008, but were not significantly different than L 79

- 1002 energycane or N51 napiergrass that year . In the final season, the nitro gen content of L 79

- 1002 energycane and
both n apiergrass es fell to levels similar to that of switchgrass. Nitrogen content of giant reeds remained the highest.
C arbon percentage in biomass varied significantly by year, and also by entry.
Interactions we re not significant (Table 1). Average carbon content of the biomass was not significantly different from 2006 to 2007, but then increased significantly in 2008 and again in 2009. Switchgrasses had the highest carbon content, averaging 47.2%. Carbon cont ent did not differ significantly among the other entries. The year by entry interaction for ash content was not found to be significant (Table 1) , but it should be noted that in 2007 no significant differences between entries were observed for ash percent age. Overall, m ean a sh content was relatively unchanged for the first two seasons (4.83% and 4.67%) , and then dropped significantly14

the next two years (3.96% in 2008, and 2.95% in 2009) . Switchgrasses generally had the lowest ash content, averaging 2.42% for PV

- 1, and 3.13% for PV

- 2 over four years . Energycane L 79

- 1002 also had relatively low mean ash content (3.54%), not differing significantly from PV

- 2
overall

. Napiergrasses and giant reeds had similar ash content (Table 4) . Ash and carbon percenta ges in biomass showed a strong negative correlation (R =

- 0.711). As mineral content decreases, the percentage of carbon increase s
. Nitrogen was positively correlated with ash (R = 0.694), and negatively correlated with carbon (R = 0.604).
Carbon to nit rogen (C:N) ratio of the harvested biomass varied significantly by years and entries. The year by entry interaction was also significant (Table 1). The average C:N ratio was not significantly different for the first two years, but then increased in 2008 and again in 2009. Overall the total DM yields of the switchgrasses were similar to those of the giant reeds, but switchgrass generally had higher C:N ratios . This is apparent in all but the 2007 season, where
there were no significant differences betwee n entries for nitrogen content and only two entries (Merkeron and PV

- 1) differed for C:N ratio ( Table 3 ). In 2008 switchgrasses had significantly higher C:N ratios than any other grasses in the test. However, in the first season, L 79

- 1002 energycane and N51 napiergrass also had C:N ratios similar to that of switchgrass. In the fourth
season both n apiergrass es and L 79

- 1002 energycane showed high C:N ratios , similar to that of the switchgrasses, though N51 napiergrass also did not differ significantly fr om giant reeds (Table 3 )

. Plant nitrogen contents in 2009 were substantially lower than in peak years for all entries (40

– 71% reductions, Table 3). These reductions were associated with decreases in dry matter yield for energycane, napiergrasses, and sw itchgrasses ( Table 4, Figure 1 ). The magnitude of this response was substantially greater for energycane (21 Mg/h a) and the napiergrasses (23.5

- 3215

Mg/h a) than for the switchgrasses (2.7

- 3.8 Mg/h a). Dry matter yields for the g iant r eeds did not appear to be responsive to plant nitrogen content across the ranges observed in this study , except
for AD

- E , but this correlation was only marginally significant ( α = 0.10; Table 4)

. The high dry matter yields obtained from energycane and the napiergrassess w ere co rrelated with plant
carbon

- to

- nitrogen ratio s, especially for Merkeron ( Table 4, Figure 1 ). The energy cane was able to sustain high dry matter yield over a C:N ratio range of 107

– 185 but declined when the ratio exceeded 200. The napiergrasses demonstrate d a much more narrow range of tolerance (74

– 102) with both entries demonstrating substantial dry matter yield decline s as the C:N ratio dropped below 100. While the switchgrasses also exhibited a drop in dry matter yield potential as the C:N ratio dropped below 200, the reductions in dry matter produced were much less substantial. This correlation was more significant for PV

- 1 than for the other switchgrass PV

- 2 (Table 4). Biomass mineral nutrient composition was analyzed in two replications over all fou r years of the test. Potassium content was very high in both napiergrass accessions (average 2.085% K) in the first growing season, significantly greater than for any other entries. In the second season it dropped significantly to an average of 1.178%, s till greater than the other
entries , but not significantly so, partially due to an increase in K content of the switchgrasses. In 2008 the K content of the switchgrasses was lower. Merkeron napiergrass and L 79

- 1002 energycane had significantly greater p otassium content than the switchgrasses in 2008 , and in
2009 L 79

- 1002 and the other napiergrass N51 were significantly greater in potassium . Giant reeds tended to have intermediate K content ( Table 5 ). Of the mineral element s analyzed in biomass, potass ium had by far the strongest year by entry interaction (Table 1). Potassium content also showed significant correlations with DM yield for both napiergrasses and for PV

- 2 switchgrass (Table 4, Figure 1). Phosphorus content of the biomass varied by entry and peaked16

in 2007, though the year by entry interaction was not significant. Averaged over all four years, napiergrasses had significantly higher P content than switchgrasses , while energycane and giant reeds were intermediate ( Table 6 ). Calcium content was significantly lower in 2009 and varied by entry. As with P, the year by entry interaction for Ca content was not significant. Giant reeds had the highest Ca content, though some of these did not differ from N51 or energycane. Magnesium content show ed a very similar pattern as calcium, dropping significantly in the fourth year. The year by entry interaction was significant, but very small ( p = 0.0246 ; Table 1 ). As with Ca, giant reeds also had the highest Mg content, but energycane and napiergrass had the least ( Table 6 ). Switchgrass DM yields showed strong correlations with both calcium content and magnesium content (Table 4, F igure 1 ). Zinc content of the biomass actually increased from 2006 to 2007, and again from 2007 to 2008, but there were no significant differences between
entries for biomass Zn content (Table 6 )

. Manganese content also varied between entries and years, with a small but significant interaction of these factors ( p = 0.0073 ; Table 1 )

. Overall, gi ant reeds tended to have the highest Mn content, and switchgrass the lo west (Table 6 ). The top 15 cm of soil was sampled in each plot, including the bare ground control, each spring after biomass harvest, but before new growth began. In 2007, the soil carbon content of
the various entries and bare ground control did not differ significantly. In succeeding years,

c arbon content of the soil tended to increase only slightly in some planted plots, though not significantly. Carbon content of the bare soil control decreased slightly, th ough also not significantly. However, by 2010 the soil carbon contents of PV

- 1 switchgrass and giant reed
clone AD

- F were significantly greater than the bare ground control (Figure 2 )

. Soil nitrogen
content showed a similar trend as soil carbon, these tw o factors being highly correlated (R = 0.868) across years . M ore significant differences between entries were noted for soil nitrogen.17

From 2007 to 2010, all planted plots maintained soil nitrogen percentage, or showed a slight increase in nitrogen, thou gh most of the changes were not significant. The bare ground control decreased slightly, but not significantly, in nitrogen percentage. However, by 2010, the bare ground control soil contained significantly less nitrogen than all planted plots, except fo r energycane L 79

- 1002 ( Figure 2 )

. In spring 2009, soil cores were taken and analyzed for carbon, nitrogen, and mineral nutrient composition. Carbon and nitrogen were generally highest in the surface layer and decreased significantly with each depth incre ment. Few differences were observed between entries or bare control for soil C and N content in the core sections. Napiergrass N51 did appear to have slightly higher carbon accumulation than the giant reeds at the 60

- 76 cm depth, but this
difference is o nly marginally significant (α = 0.10; data not shown). Some differences were noted between soil cores for potassium distribution ( Figure 3 ) . In the surface layer, napiergrasses had the highest soil K, but the only significant difference was between N51 (70.94 mg K/kg soil) and the bare control (22.96 mg K/kg soil). At the 30

- 45 cm depth switchgrass PV

- 1 and giant
reed AD

- S had slightly more soil K than energycane L 79

- 1002, though these differences are only significant at the α = 0.10 level. Napiergrasses also had lower soil K at this depth, but were not significantly different from the other entries. At the 60

- 76 cm depth, both napiergrass es had
the lowest soil K content (average 14.65 mg K/kg soil), significantly less than PV

- 1 switchgrass (30.51 mg K/kg soil) at α = 0.05 . The other switchgrass PV

- 2 also had high soil K (29.17 mg K/kg soil) at this depth, also significantly greater than n apiergrass, but only at a significance
level of α = 0.10. A lso a

t α = 0.10 giant reed AD

- S had greater soil K than either napiergrass at
the 60

- 76 cm depth

. No significant differences in soil K were observed in the deepest soil layer (91

- 107 cm). The ot her minerals (P, Mg, Mn, and Zn) showed typical distribution patterns in the18

soil cores, being highest in the upper soil layers, and decreasing with depth. Few significant
differences were observed between entries for these nutrients at the various soil d epths. Calcium had a more variable soil profile, being greatest in both the top soil layer (0

- 15 cm) and the 60

- 76 cm layer, and lowest in the 30

- 45 cm and 91

- 107 cm layers. However, no significant differences
between entries were observed (data not show n)

. R oots were quantified at diffe rent depths in the soil cores, and their n itrogen content was
also measured. N o significant differences between entries were found for root nitrogen content.
However , roots in the upper soil layer generally had slightly more nitrogen, and the difference was statistically significant. Roots in the upper soil layer averaged 0.55% nitrogen, while roots in the three lower soil layers averaged 0.39, 0.34, and 0.42% nitrogen , by increasing depth

. Root
biomass was estimated on a dry weight basis, based on the amount of roots found in the soil cores. Estimates of root biomass for giant reeds were highly variable at all soil depths (standard deviations exceeded means). It appears that the roots of giant reed tend to be large an d unevenly distributed, so that the method of sampling roots with relatively narrow soil cores is probably not suitable for this species. Also, the large rhizomes were not sampled, so the amount of underground biomass for these entries would be underestim ated. Thus, root data for giant reed were not included in further analyses. Among the other entries , significantly more roots were found in the uppermost soil layer (0

- 15 cm) than in deeper layers, and there were some differences found between entries fo r mean root biomass ( Figure 4 )

. Within soil layers, the differences in root biomass were only significant in the uppermost layer. Switchgrass PV

- 1 had significantly higher mean root biomass (0.8688 g roots/kg soil, dry basis averaged over all layers) tha n any other accession. The other four entries did not differ significantly from each19

other. Merkeron had more roots than the samples taken in the bare plots, though the difference was not statistically significant.

Discussion Yields reported in other s tudies of giant reed ( Cosentino et al., 2006; Mantineo et al.,
2009 ) are generally higher than those observed in this study, most likely due to the origin of the planting material. The giant reed plants used in this study originated from micropropagation, rather than from conventional vege tative material (cane cuttings or rhizomes). Yield reduction in
tissue culture

- derived sugarcane compared to conventionally propagated cane was reported by Bailey and Bechet (1989), thou gh the exact tissue culture procedure was not reported. In one sugarcane cultivar, out of three tested by Hoy et al. (2003), reduced yield was noted from plants generated from leaf

- roll callus, but not from apical meristem culture. Thus, it is certainly possible that in vitro propagation may decrease productivity in giant reed. Very low yields were observed for the entire test in 2009 , despite the fact that more rain was received during this growing season than in the previous three (Table 7) . Though so me differences in DM yield were observed between entries in 2009, most were not statistically significant. Most likely this yield reduction is due to depletion of nutrients from the soil, as is evidenced by the reductions in plant nitrogen and potassium c ontent s, the widening of plant C:N ratios, and the ir correlations with yield (Table 4)

. All of these responses would be expected with
no addition of fertilizer , but detailed studies are needed to determine the optimum fertilization requirements for these grasses. A small but significant fraction of yield loss in the 2009 season
may also be due to the lateness of the harvest (delayed until Feb., 2010), as a significant amount of leaves had fallen to the ground in some plots , and this biomass was not harves ted

. Though it20

was not quantified it appeared from visual observations that energycane and giant reed retain more leaves than switchgrass or napiergrass over the winter. Previous studies (de Morais et al ., 2009) have shown that leaves make up approximate ly 30 % of harvestable bioma ss in mature tall
varieties of napiergrass

. Despite the potential for yield loss, several studies have reported improvements in biomass quality or increased nutrient use efficiency in late harvesting of perennial grasses due to drying, nutrient translocation, and nutrient leaching ( Landström et al.,
1996 )

. It is unclear whether the decreased nitrogen contents of the energycane and napiergrasses in the 2009 harvest was due to the late harvest time or to other factors such as depletion of nutrients in the soil or age of the crop. The nitrogen content of most entries did tend to de crease as plant

- available nitrogen was presu mably depleted from the soil , though no evidence for nitrogen depletion was actually observed in the soil

. Nitrogen actually appeared to increase slightly i n the topsoil of planted plots. Because it was strongly correlated with soil carbon (R = 0.868) this increase is probably mostly from organic nitrogen, derived from leaf and root
residues

. Because no fertilizer was applied in this study, it is assumed that the nitrogen in the
harvested biomass was derived from residual nitrogen in the soil. However, t he possibility that some of the nitrogen uptake was derived from biological nitrogen fixation (BNF) should not be overlooked. It has been shown that sugarcane in the tropics can derive a s ignificant amount of nitrogen from associated nitrogen

- fixing (diazotrophic) bacteria (Urquiaga et al. , 1992). Endophytic diazotrophs have also been isolated from n apiergrass grown in Brazil (Kirchhof et
al. , 1997), and it is possible that they are present in cooler locations as well. Nitrogen

- fixing
bacteria have also been isolated from Miscanthus and Spartina pectinata grown in Germany, though at lower populations than those found in tropical n apiergrass (Kirchhof et al. , 1997).21

Nitrogen

- limiting conditions may actually promote the growth of nitrogen

- fixing bacteria in some grasses (Kirchhof et al. , 1997). BNF could partly explain the sustained growth for two or

even three seasons of the energycane and n apiergrasses with no added n itrogen in this study , and could account for part of the large amount of nitrogen that was removed with the biomass

. In this study napiergrasses removed around 385 kg N/ha over the first three years ( Figure 5 ), much more than giant reeds or switchgrass, t hough no depletion of nitrogen was observed in the soil cores taken in spring 2009. On two nitrogen

- depleted soils in Brazil, de Morais et al

. (2009) estimated that an average of 36 % of the nitrogen taken up by napiergrass was supplied by BNF

. Despite th e possible contributions of BNF, it is still unlikely that all of the nitrogen needs of these grasses can be met with no application of nitrogen fertilizer

. Based on the nutrient uptake data, future fertilization studies of napiergrass should probably inc lude N application rates around 200 kg N/ha. Energycane should be able to produce yields with N application rates
between 100

– 150 kg N/ha, based on the uptake rates observed in this study. Both napiergrasses took up an exceptionally large amount of potas sium in the first growing season (average 704 kg K/ha). In the next season, they only took up about half as much (average 345 kg K/ha ; Figure 5 ), but maintained high biomass yields. Napiergrass may be subject to luxury consumption of potassium, which may have significant implications for fertilization and biomass quality. These results suggest that fertilization rate studies for napiergrass focus the development of response curves up to a maximum of 300 kg K/ha. The soil core data suggested a possible d epletion of soil K at the 60

- 71 cm depth in napiergrass plots compared to switchgrass. The energycane L 79

- 1002 also took up a large quantity of potassium, but at a much lower rate than napiergrass. Also, K content in the energycane was less variable,

su ggesting that the energycane is a more efficient user of potassium. Efficient use of available22

soil K is likely one factor contributing to the relatively sustained yield of the energycane for three seasons. Based on the uptake data in this study, fertili zation rate studies for energycane should probably not exceed application rates of 200 kg K/ha. Studies are currently underway to more accurately assess the yield response of these species to fertilization rates. Switchgrass PV

1 showed a positive correlation between yield and N uptake, and PV

- 2 showed a positive correlation between yield and uptake of K , suggesting possible yield responses to availability of
these nutrients

. Yields of b oth switchgrasses were strongly correlated with Ca and Mg upta ke as well . Thomason et al. (2004) reported a limited response to applied N fertilizer in switchgrass, and also noted positive correlations between yield and K and Mg concentrations. Prior to establishment of this experiment, the test site had been used for switchgrass breeding plots, and for annual grain crops before that. All of these plots had been given adequate, if not e xcess, amounts of fertilizer , and most of the biomass was never removed from
the field

. Davis et al. (1996) reported potassium bui ldup in a Tifton loamy sand after r epeated yearly application s of potassium fertilizer (48 or 96 kg K/ha/yr) for eleven years under corn
cultivation , where only the grain and cobs were removed from the field

. In an eleven

- year study of bermudagrass on a n ewly

- cleared sandy soil in North Carolina (Eustis sand), Woodhouse (1968) reported that, at moderate application rates (46.5 and 93 kg K/ha/yr), more K was removed in forage than was applied (400

– 500 kg/ha over 11 years), and suggested that release
of na tive K from non

- exchangeable forms was occurring in the soil profile. At a higher application rate (186 kg K/ha/yr) some K accumulation was observed in the soil profile. I t is likely that residual nutrients had built up deep in the soil prior to planting the current study , and
these nutrients were being utilized by the perennial grasses. It is also possible that some non

exchangeable K was released and made available to the plants (Woodhouse, 1968)

. Roots were23

detected at the 91

– 107 cm depth for all acc essions, but due to the difficulty in deeper sampling, it
is not known just how far down they extend. Extraction of deep nutrient reserves could also account for the high rates of potassium and nitrogen removal that were observed in the napiergrass and energycane plots. The root profiles observed in this study for napiergrass agree with observations reported by Woodard and Prine (1993), who estimated t hat around 70% of the root biomass of napiergrass occurs in the top 25 cm of soil. However, Woodard and Prine (1993) also sampled only to a depth of 1 m, so the importance of deeper roots is still unclear. Switchgrass roots are known to extend beyond thr ee meters depth in prairie soils (McLaughlin and Walsh, 1998), and sugarcane roots have been observed at a maximum depth of 4.70 m only 332 days after planting in Brazil under rainfed conditions (Laclau and Laclau, 2009) . It certainly seems probable that the species tested in this study were able to tap dee p nutrient reserves. The increased potassium levels in the topsoil of some plots, specifically napiergrass and switchgrass, also suggest possible redistribution of potassium from deeper soil layers in to the topsoil by these
grasses. Moisture content of harvested biomass is an other important quality factor to consider.
T ransportation of wet biomass is more costly than moving dry biomass, but there are also costs associated with post

- harvest drying. Wet biomass may be difficult to store and would certainly be unfit for direct combustion, but for biochemical conversion to ethanol, moisture may be of
less concern. Although the delayed harvest of 2009 cannot be directly compared to other years in this resp ect, the switchgrasses were significantly drier in the 2009 harvest than in 2006 and 2007, sugg esting that their stems do dry in the field over winter. Switchgrasses averaged only
22.3% moisture in the 2009 harvest. Adler et al

. (2006) reported that swit chgrass harvested in the fall averaged 35% moisture, and only 7% moisture in late winter/early spring harvests in24

Pennsylvania. Similar observations have been reported in reed canarygrass ( Phalaris
arundinacea L.; Landström et al. 1996) and Miscanthus (Le wandowski and Heinz, 2002). Though biomass quality in grasses such as switchgrass tends to improve with later harvest, leaf drop, lodging, and breakage of brittle stem tops generally leads to some loss of biomass ( Adler et al., 2006 ) . Unlike switchgrass, energycane and napiergrass did not appear to lose moisture over
the winter. The moisture content of these grasses was relatively unaffected by years because their thick stems do not dry as well in the field , especially since the fall tends to have increa sed rainfall and lower temperatures

. . Giant reeds had less moisture at harvest than napiergrass and
energycane , but later harvesting appears to have only a minimal effect on further reducing the moisture content in this species. Studies are currently und erway to more precisely determine the effects of delayed harvest on biomass quality and nutrient composition in these species. To maximize biomass yields and quality from perennial grasses, most of the biomass will likely be harvested at the end of the gr owing season and throughout the winter months. Switchgrass , for example, can tolerate two harvests per growing season, though the nitrogen content of the biomass and the amount of nitrogen removed from the soil will be higher than with only one post

- senescence harvest (Reynolds et al., 2000). H arvesting certain varieties of

n apiergrass multiple times throughout the growing season is reported to reduce overall yields, and can lead to winter stand reductions in temperate areas (Woodard and Prine, 1991). Therefore, systems for storing harvested biomass for later use need to be d eveloped. For example, it has been shown that napiergrass and energycane biomass can be ensiled, with little loss of total biomass (Woodard et al. , 1991). Some of the seasonal demand for biomass could also be filled using annual crops such as sweet or fo rage sorghum ( Sorghum bicolor (L.) Moench; Saballos, 2008), or perennials that tolerate multiple harvests such as bermudagrass25

( Cynodon dactylon (L.) Pers.; Anderson et al. , 2008). Also, different soil types and climatic
conditions will affect which of th ese crops perform best in specific locations. In addition, different feedstocks have different properties, which may affect their suitability for specific applications, such as direct combustion or biochemical conversion to ethanol. Studies are also
unde rway to compare the biochemical conversion properties of these various feedstocks. For biomass production under low inputs in South Georgia, napiergrass and energycane show the greatest yield potential. These species establish quickly and in this study w ere able to produce acceptable yields the first and second years with no inputs , perhaps by tapping deep
accumulations of soil nutrients . Fertilization in subsequent years is, of course, recommended to maintain yields, and studies have been initiated to d etermine the optimum rates of fertilization for biomass production in these species. For marginal areas with the primary purpose of erosion control or wildlife refuge, switchgrass would be an ideal crop, as it is not generally considered invasive. Though establishment is slower, it is long

- lived under good management, and produces reasonable yields of good

- quality low

- nitrogen biomass. In this study switchgrass was found to take up much less nitrogen than the other biomass crops. In addition, switchgras s has the ability to dry cons iderably in the field, and tended to have low ash content, making it the most suitable crop in this test for direct combustion applications ( Lewandowski and Kicherer, 1997; Adler et al., 2006 )

Acknowledgements
The authors wou ld like to acknowledge Freddie Cheek, Tony Howell, and Lorine Lewis for technical assistance. The authors would also like to thank Dr. Myron Parker ( Prof. Emeritus,26

University of Georgia) and Dr. C. Corley Holbrook (USDA

- ARS) for critical review s of th is manuscript.27

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Tables:
Table 1. Analysis of variance (ANOVA ) mean squares for biomass dry matter (DM) yield (Mg DM/ha), moisture percentage, and elemental composition of eight perennial grasses grown at Tifton, GA for four years unde r rainfed conditions with no additional inputs.
df DM Yield % Moisture % N % C C/N Ratio % Ash Year (Y) 3 1045.53 *** 704.78 *** 0.3807 *** 80.93 *** 84891.0 *** 22.97 *** Replicate (R) 3 16.27 ns 6.17 ns 0.0141 ns 1.00 ns 3679.0 ns 2.13 ns Entry (E) 7 680.82 *** 2701.00 *** 0.1997 *** 4.90 *** 48206.8 *** 14.20 ***
Y × R 9 10.18 ns 9.22 ns 0.0085 ns 0.49 ns 1366.3 ns 1.39 ns
Y × E 21 132.12 *** 28.96 ** 0.0220 ** 0.57 ns 5280.8 *** 0.90 ns
R × E 21 40.65 *** 8.20 ns 0.0155 ns 0.24 ns 1487.5 ns 0.48 ns
Error 63 a 13.18 15.80 0.0098 0.42 1336.7 0.82

df % K % P % Ca % Mg Mn (ppm) Zn (ppm) Year (Y) 3 0.931 *** 0.00130 * 0.0846 *** 0.0142 *** 1547.9 *** 216.17 *** Replicate (R) 1 0.021 ns 0.00000 ns 0.0043 ns 0.0006 ns 150.3 ns 0.02 ns34

Entry (E) 7 0.908 *** 0.00209 *** 0.0591 *** 0.0080 *** 4932.6 *** 35.84 **
Y × R 3 0.017 ns 0.00042 ns 0.0022 ns 0.0015 ns 176.0 ns 54.76 **
Y × E 21 0.139 *** 0.00032 ns 0.0105 ns 0.0017 * 395.3 ** 17.87 *
R × E 7 0.024 ns 0.00032 ns 0.0163 * 0.0016 ns 290.0 ns 13.82 ns
Error 21 0.033 0.00030 0.0055 0.0007 131.0 8.38

* = significant at α = 0.05, ** = significant at α = 0.01, *** = significant at α = 0.001, ns = not significant

a Error df = 60 for %N, 59 for %C and C/N Ratio , and 62 for % ash.35

T able 2. Yearly mean dry matter (DM) yields and biomass moisture percentages at harvest for eight perennial grasses grown at Tifton, GA for four years (2006

– 2009) under rainfed conditions with no additional inputs.

Yield (Mg DM/ha) % Moisture Entry 2006 2007 2008 2009 2006 2007 2008 2009
L 79

- 1002 29.2 26.1 21.1 8.2 64.2 59.1 62.5 58.5
AD

- S 5.3 8.8 5.5 3.3 52.6 44.7 49.2 39.6
AD

- E 7.0 12.3 6.4 5.6 47.5 49.4 44.5 40.2
AD

- F 7.2 12.9 8.2 6.5 48.4 47.8 44.7 41.8
Merkeron 30.6 30.5 11.4 7.1 70.1 67.8 62.7 57.4
N51 37.1 28.1 12.3 5.1 68.6 66.4 59.9 58.0
PV

- 1 9.2 13.0 8.3 6.5 37.5 36.4 30.8 21.9
PV

- 2 9.4 13.5 8.8 5.6 37.2 39.0 32.1 22.7
LSD 0.05 10.9 13.5 11.3 4.8 6.2 11.1 10.0 7.1

Least Significant Differences (LSD) were determined by Tukey’s HSD test at α = 0.05.36

Table 3
. Yearly mean nitrogen percentage and carbon:nitrogen (C:N) ratio in harvested biomass (whole shoots) for eight perennial grasses grown at Tifton, GA for four years (2006

– 2009) under rainfed conditions with no additional inputs.
% N C:N Ratio Entry 2006 2007 2008 2009 2006 2007 2008 2009
L 79

- 1002 0.320 0.435 0.260 0.170 184.6 107.1 179.7 286.9
AD

- S 0.692 0.451 0.434 0.334 65.8 102.1 109.6 143.6
AD

- E 0.590 0.559 0.470 0.325 83.4 88.5 102.0 150.1
AD

- F 0.673 0.435 0.449 0.297 69.5 114.7 107.2 168.2
Merkeron 0.614 0.546 0.404 0.179 73.6 87.2 123.6 279.7
N51 0.473 0.547 0.304 0.234 102.3 98.8 165.4 209.0
PV

- 1 0.245 0.295 0.153 0.171 190.8 163.0 308.1 293.4
PV

- 2 0.243 0.303 0.151 0.182 203.2 153.6 311.9 285.6
LSD 0.05 0.373 ns 0.202 0.077 99.6 75.3 94.1 89.9

Least Significant Differences (LSD) were determined by Tukey’s HSD test at α = 0.05

. ns = no significant differences.37

Table 4. Correlations of biomass nutrient contents with dry matter yield. Values are Pearson correlation coefficients (R). All correlations significant at α ≤ 0.05 are plotted in Figure 1.

Entry %N C:N Ratio % K % Ca % Mg
L 79

- 1002 0.563 **

- 0.646 *** 0.539 ns 0.358 ns 0.425 ns AD

- S 0.285 ns
- 0.407 ns 0.295 ns 0.479 ns 0.485 ns AD

- E 0.456 *

- 0.452 * 0.646 * 0.521 ns 0.315 ns AD

- F 0.266 ns
- 0.374 ns 0.377 ns 0.173 ns
- 0.122 ns Merkeron 0.730 ***

- 0.721 *** 0.805 ** 0.148 ns 0.384 ns N51 0.441 *

- 0.513 * 0.890 ***

- 0.116 ns
- 0.364 ns
PV

- 1 0.554 **

- 0.563 ** 0.525 ns 0.765 ** 0.728 **
PV

- 2 0.460 *

- 0.485 * 0.724 ** 0.853 *** 0.766 **

* = significant at α = 0.10, ** = significant at α = 0.05, *** = significant at α = 0. 01, ns = not significant38

Table 5
. Yearly mean ash and potassium (K) percentages in harvested biomass (whole shoots) for eight perennial grasses grown at Tifton, GA for four years (2006

– 2009) under rainfed conditions with no additional inputs.
% Ash % K Entry 2006 2007 2008 2009 2006 2007 2008 2009
L 79

- 1002 3.62 4.54 3.55 2.44 1.121 0.892 1.037 0.749
AD

- S 6.15 5.14 4.88 3.86 0.905 0.737 0.749 0.415
AD

- E 5.10 5.05 4.83 3.44 0.690 0.830 0.599 0.415
AD

- F 5.12 4.65 4.93 3.59 0.921 0.749 0.680 0.536
Merkeron 6.15 5.71 4.57 3.01 2.134 1.196 1.112 0.599
N51 5.94 4.82 4.26 3.69 2.037 1.159 0.870 0.749
PV

- 1 2.44 3.28 2.33 1.64 0.345 0.719 0.351 0.190
PV

- 2 4.09 4.16 2.33 1.92 0.286 0.601 0.323 0.207
LSD 0.05 2.65 ns 0.98 1.18 0.820 ns 0.618 0.478

Least Significant Differences (LSD) were determined by Tukey’s HSD test at α = 0.05. ns = no significant differences.39

Table 6
. Biomass mineral composition ( entry means and yearly means) for eight perennial grasses grown at Tifton, GA for four years (2006

– 2009) under rainfed conditions with no additional inputs.

K P Ca Mg Mn Zn Entry % ppm
L 79

- 1002 0.950 0.105 0.252 0.072 47.49 15.30
AD

- S 0.701 0.089 0.422 0.180 74.81 11.62
AD

- E 0.633 0.078 0.375 0.140 94.50 10.55
AD

- F 0.721 0.077 0.379 0.145 93.13 11.58
Merkeron 1.260 0.110 0.202 0.109 59.54 14.66
N51 1.204 0.110 0.262 0.110 42.89 15.37
PV

- 1 0.401 0.076 0.218 0.121 31.46 10.84
PV

- 2 0.354 0.072 0.227 0.130 36.65 14.78
LSD 0.05 0.303 0.029 0.125 0.044 19.19 ns Year % ppm 2006 1.055 0.081 0.297 0.150 59.01 8.74
2007 0.860 0.102 0.366 0.143 60.23 11.62
2008 0.715 0.087 0.314 0.126 72.51 17.12
2009 0.482 0.087 0.193 0.084 48.48 14.88
LSD 0.05 0.178 0.017 0.073 0.026 11.28 2.85

Least Significant Differences (LSD) were determined by Tukey’s HSD test at α = 0.05. ns = no significant differences.40

Table 7. Monthly rainfall (cm) recorded at Tifton, GA during the study period.

2005 2006 2007 2008 2009 2010
Jan

- 19.41 8.69 8.69 4.17 16.89
Feb

- 10.26 5.69 19.86 5.51 8.53
Mar

- 0.74 3.86 8.05 20.90 7.16 Apr

- 4.27 1.14 7.67 20.96

- May

- 6.86 0.33 4.65 16.61

- Jun

- 10.59 14.94 5.79 5.00

- Jul

- 7.29 9.09 8.38 19.76

- Aug

- 7.24 17.68 31.29 17.83

- Sep 0.05 5.13 6.65 0.38 4.32

- Oct 1.47 2.90 7.70 16.28 10.19

- Nov 10.49 7.42 2.31 9.86 6.71

- Dec 12.62 14.27 14.43 7.90 19.25

-41

Figure Captions :

Figure 1. Significant correlations between biomass nutrient content and dry matter yield. For clarity, only the yearly means are plotted. Pearson correlation coefficients (R) based on the actual raw data are given in Table 4.

Figure 2
. Yearly soil carbon and nitrogen percentages, measured in the top 15 cm of soil in plots of perennial grasses and bare ground control. C and N percentages are indicated on the y

axes, years on the x

- axes. Colors/symbols for individual entries are indicated in the legend at the bottom of the figure. Because of variability in sampling methods , data for 2009 are not included

.

Figure 3
. Soil potassium content (mg K/kg soil, dry basis) at four soil depths taken from cores
in 2009 before spring regrowth, after three years of growth of eight perennial grasses and bare ground control with no fertilizer inputs. Error bars indicate one standar d deviation of the mean.

Figure 4 . Root biomass (g roots/kg soil, dry basis) sampled from four depths of soil cores taken in spring, 2009. Because of extreme variability for this species, giant reeds (AD

- S, AD

- E, and
AD

- F) are not included. Error bars represent one standard deviation of the mean.

Figure 5
. Calculated y early removal of N, K, and P (kg element/ha) by eight perennial grasses grown at Tifton, GA for four years (2006

– 2009) under rainfed conditions with no additional inputs. Nutrients are i ndicated on the y

- axes, years on the x

- axes. Colors/symbols for individual entries are indicated in the legend at the bottom of the figure.4 6 8 10 12 14 16 18

0.0 0.1 0.2 0.3 0.4Yield (Mg DM/ha)

% Ca or % Mg in biomass

PV-1 %Ca PV-2 %Ca PV-1 %Mg PV-2 %Mg

0 5 10 15 20 25 30 35 40 45

0 1 2 3Yield (Mg DM/ha)

% K in biomass Merkeron N51 PV-2 0

5 10 15 20 25 30 35

0 100 200 300 400Yield (Mg DM/ha)

C:N Ratio of biomass L 79-1002 Merkeron PV-1

0 5 10 15 20 25 30 35

0 0.2 0.4 0.6 0.8Yield (Mg DM/ha)

% N in biomass L 79-1002 Merkeron PV-1 Figure 1 Click here to download Figure: Knoll-Fig1.eps0.40 0.45 0.50 0.55 0.60 0.65 0.70

2007 2008 2009 2010% C in Soil

0.020 0.025 0.030 0.035 0.040

2007 2008 2009 2010% N in Soil

L79-1002 AD-S AD-E AD-F Merkeron N51 PV-1 PV-2 Bare Figure 2 Click here to download Figure: Knoll-Fig2.epsFigure 3 Click here to download Figure: Knoll-Fig3.eps0.0 0.5 1.0 1.5 2.0 2.5 3.0

L79-1002

Merkeron

N51

PV-1

PV-2

Bare g roots/kg soil

0-15 cm
30-45 cm
60-76 cm
91-107 cm Figure 4 Click here to download Figure: Knoll-Fig4.eps0 50 100 150 200 250

2006 2007 2008 2009Yearly N Removal(kg N/ha)

0 100 200 300 400 500 600 700 800

2006 2007 2008 2009Yearly K Removal(kg K/ha)

0 20 40 60

2006 2007 2008 2009Yearly P Removal(kg P/ha)

L79-1002 AD-S AD-E AD-F Merkeron N51 PV-1 PV-2 Figure 5 Click here to download Figure: Knoll-Fig5.eps