Greenhouse and Field Evaluation of Alamo and Two New Genotypes of 
Switchgrass for Biomass Production 
 
by 
 
Scottie Lynn Sklanka 
 
 
 
 
A thesis submitted to the Graduate Faculty of 
Auburn University 
in partial fulfillment of the 
requirements for the Degree of 
Master of Science 
 
Auburn, Alabama 
May 4, 2013 
 
 
 
 
 
Copyright 2013 by Scottie Lynn Sklanka 
 
 
Approved by 
 
David I. Bransby, Professor, Agronomy and Soils 
Kipling S. Balkcom, Affiliate Associate Professor, Agronomy and Soils 
Francisco J. Arriaga, Assistant Professor, Soil Science 
 
 
 
 
 
 
 
 
 
ii 
 
 
 
 
 
Abstract 
 
Due to its high yields and wide geographic range, switchgrass (Panicum 
virgatum) was chosen by the Department of Energy as a model herbaceous 
perennial bioenergy feedstock. Alamo is the highest yielding variety, and the 
?benchmark? recommended for the Deep South. Within the species, and even 
within this variety, large amounts of genetic variability exist, allowing for the 
development of cultivars with higher yields, and composition better suited for the 
needs of either biochemical or thermochemical conversion methods, through 
selective breeding.  Links between the physiological measurements during 
seedling growth and yield of the mature plant in the field are unknown, but could 
expedite breeding progress if they were available. Therefore, the objective of this 
study was to compare Alamo with two new genetic lines of switchgrass, GA-992 
and GA-993, in a field study and a study of seedling growth in a greenhouse, to 
examine whether seedling growth in a greenhouse was indicative of yield and 
other differences in the field experiment. The field experiment compared yield, 
cell wall, C, and N composition, and morphological characteristics of the three 
genetic lines over a 4-year period. Growth of seedlings from each line was 
measured weekly over a seven-week period in the greenhouse experiment which 
was conducted twice in 2008. Root measurements and partitioning of C and N in 
the roots and shoots of the seedlings were also measured. Data from the 
greenhouse experiment revealed complex interactions, with little or no difference 
iii 
 
among genetic lines for most variables measured. Height and weight of the two 
new lines were superior to that of Alamo on certain harvest dates, but this pattern 
was not consistent over time, and was not detected in the field study where there 
was mostly no difference in biomass yield among experimental entries. It is 
concluded that differences among the three genetic lines evaluated in this research 
were small or not detectable, and results in the field experiment could not be 
predicted from results in the greenhouse experiment.   
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
iv 
 
 
 
 
 
Acknowledgements 
 
 I have been lucky to have so many people to help me along the way and 
appreciate everything that they have done for me.  I would like to thank my 
advisor, Dr. Bransby, for all of his guidance throughout the process: for the 
opportunities he has allowed me and for his help with my completing everything.  
Also, Susan Sladden and all of the student workers who provided so much help, 
without them it may have taken me even longer to finish this.  I am very 
appreciative to Ping Huang for all of his help with statistics, even when I know he 
was very busy finishing his own work this fall.  Thank you to my committee who 
have come to help me despite the short notice.  To Dr. Sarah Lingle, who gave me 
help, encouragement, and just a little nagging to help pull me through.  And to the 
friends who stuck around and listened to me talk about little else for far too long.  
Of course, I thank my family for all of their encouragement during this whole 
process. 
 
This thesis is dedicated to all of these people but most especially to my 
grandfather, Glenn Gass. 
 
 
 
 
v 
 
 
 
 
 
Table of Contents 
 
Abstract ................................................................................................................... ii 
Acknowledgments.................................................................................................. iv  
List of Tables ........................................................................................................ vii  
List of Figures ........................................................................................................ ix  
I. Review of Literature   ...........................................................................................1 
 Historical Perspective on Bioenergy   ..........................................................1 
 Conversion Technologies  ...........................................................................2 
 Switchgrass as an Energy Crop ...................................................................5 
 Geographic Distribution, Morphology, and Crop Improvement   ...............6 
II. Introduction   .......................................................................................................8 
III. Materials and Methods  ....................................................................................10 
 Greenhouse Experiment  ............................................................................10 
 Field Experiment  .......................................................................................11 
IV. Results .............................................................................................................13 
 Greenhouse Experiment   ...........................................................................13 
 Field Experiment  .......................................................................................15 
V. Conclusions .......................................................................................................17 
VI. Literature Cited ................................................................................................18 
VII. Appendix ........................................................................................................22 
  
vi 
 
 
 
 
 
 
List of Tables 
 
 
Table 1. Average temperature per month during study and 10-year averages ......23 
Table 2. Total monthly rainfall for years studied and 10-year averages ...............24  
Table 3. Analysis of variance for weekly growth of seedlings in the greenhouse, 
April & August 2008 .............................................................................................25  
 
Table 4. Means of weekly growth measurements from the greenhouse experiment, 
beginning April 2008 .............................................................................................26  
 
Table 5. Means of weekly growth measurements from the greenhouse experiment, 
beginning August 2008 ..........................................................................................27  
 
Table 6. Percentage of nitrogen and carbon in roots and shoots of samples from 
the greenhouse experiment ....................................................................................32 
 
Table 7. Root measurements of samples from the greenhouse experiment ...........34 
 
Table 8. Harvest dates and biomass yields from the field experiment planted on 
6/12/2006 ...............................................................................................................36  
 
Table 9. Analysis of variance for weight of tiller components of samples from the 
field experiment, 2007 and 2008 ...........................................................................38  
 
Table 10. Means and standard deviations for weight of tiller components of 
samples from the field experiment, 2007 and 2008 ...............................................39  
 
Table 11. Analysis of variance for tiller length, diameter, and leaf number of 
samples from the field experiment, 2007 and 2008 ...............................................42  
 
Table 12. Analysis of variance for tiller length, diameter, and leaf number of 
samples from the field experiment, 2007 and 2008 ...............................................43  
 
Table 13. Analysis of variance for leaf cell wall composition of samples from the 
field experiment, 2007-2009 ..................................................................................47 
 
 
vii 
 
Table 14. Analysis of variance for stem cell wall composition of samples from the 
field experiment, 2007-2009 ..................................................................................49 
 
Table 15. Analysis of variance of the percentage of nitrogen and carbon in the 
leaves and stems of samples from the field experiment, 2007-2009 .....................51  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
viii 
 
 
 
 
 
 
List of Figures 
 
 
 
Figure 1. Changes in seedling dry weight of different genotypes with time for the 
greenhouse experiment starting in April 2008 .......................................................28  
 
Figure 2. Changes in seedling dry weight of different genotypes with time for the 
greenhouse experiment starting in August 2008 ....................................................28 
 
Figure 3. Changes in the tiller number of different  genotypes with time for the 
greenhouse experiment starting in April 2008 .......................................................29  
 
Figure 4. Changes in the tiller number of different  genotypes with time for the 
greenhouse experiment starting in August 2008 ....................................................29 
 
Figure 5. Changes in the leaf number of different  genotypes with time for the 
greenhouse experiment starting in April 2008 .......................................................30 
 
Figure 6. Changes in the leaf number of different  genotypes with time for the 
greenhouse experiment starting in August 2008 ....................................................30 
 
Figure 7. Changes in the seedling height of different  genotypes with time for the 
greenhouse experiment starting in April 2008 .......................................................31 
 
Figure 8. Changes in the seedling height of different  genotypes with time for the 
greenhouse experiment starting in August 2008 ....................................................31 
 
Figure 9. Percent nitrogen in roots and shoots  from the greenhouse experiment on 
a dry matter basis ...................................................................................................33 
 
Figure 10. Percent carbon in roots and shoots  from the greenhouse experiment on 
a dry matter basis ...................................................................................................33 
 
Figure 11. Average root length of samples from the greenhouse experiment .......35 
 
Figure 12. Average root diameter of samples from the greenhouse experiment ...35 
 
Figure 13. Total biomass yield (kg/ha) from the field experiment, 2006-2009 .....37 
 
ix 
 
Figure 14. Dry weight of whole, leaf, and stem components of tiller samples from 
the field experiment by year, 2007 and 2008 .........................................................40 
 
Figure 15. Dry weight of whole, leaf, and stem components of tiller samples from 
the field experiment by genotype, 2007 and 2008 .................................................40 
 
Figure 16. Leaf to stem weight ratio on a dry matter basis from the field 
experiment by year, 2007 and 2008 .......................................................................41 
 
Figure 17. Leaf to stem weight ratio on a dry matter basis from the field 
experiment by genotype, 2007 and 2008 ...............................................................41 
 
Figure 18. Average tiller length from the field experiment by year, 2007 and 2008 
................................................................................................................................44 
 
Figure 19. Average tiller length from the field experiment by genotype, 2007 and 
2008........................................................................................................................44 
 
Figure 20. Average tiller diameter from the field experiment by year, 2007 and 
2008........................................................................................................................45 
 
Figure 21. Average tiller diameter from the field experiment by genotype, 2007 
and 2008 .................................................................................................................45 
 
Figure 22. Average number of leaves per tiller from the field experiment by year, 
2007 and 2008 ........................................................................................................46 
 
Figure 23. Average number of leaves per tiller from the field experiment by 
genotype, 2007 and 2008 .......................................................................................46 
 
Figure 24. Leaf cell wall composition from the field experiment by year, 2007-
2009........................................................................................................................48 
 
Figure 25. Leaf cell wall composition from the field experiment by genotype, 
2007-2009 ..............................................................................................................48 
 
Figure 26. Stem cell wall composition from the field experiment by year, 2007-
2009........................................................................................................................50 
 
Figure 27. Stem cell wall composition from the field experiment by genotype, 
2007-2009 ..............................................................................................................50 
 
Figure 28. Percent nitrogen in samples from the field experiment on a dry matter 
basis by year, 2007-2009 .......................................................................................52 
 
x 
 
Figure 29. Percent nitrogen in samples from the field experiment on a dry matter 
basis by genotype, 2007-2009................................................................................52 
 
Figure 30. Percent carbon in samples from the field experiment on a dry matter 
basis by year, 2007-2009 .......................................................................................53 
 
Figure 31. Percent carbon in samples from the field experiment on a dry matter 
basis by genotype, 2007-2009................................................................................53 
 
 
 
 
 
 
 
1 
 
 
 
 
Review of Literature 
 
 
Historical Perspective on Bioenergy 
 
Since the 1970?s during the oil embargo there has been interest in developing a cheap and 
domestic source of renewable transportation fuel.  The Department of Energy (DOE) became 
involved in programs supporting relevant research in 1976, and in 1977 began field studies co-
funded by the United States Department of Agriculture (USDA) (Wright, 1992).  Oak Ridge 
National Laboratory (ORNL) was asked to provide advice and support to the program and by 
1982 the DOE had fully transferred management of their Short Rotation Woody Crops Program 
to ORNL.  In 1984 the Herbaceous Energy Crops Program (HECP) began, funded by the DOE.  
The goal of this program was to gain the necessary information for using herbaceous biomass as 
a viable source of feedstock for fuel production, and to do so in a way that would minimize 
adverse effects on the environment (Berger et al., 1984). 
 Herbaceous crops were desirable because they would likely be relatively easy to 
incorporate into preexisting agricultural practices, and because they could serve as an alternative 
crop for a depressed farm economy.  Also, herbaceous crops seemed more suitable to the 
conversion methods of the time: enzymatic hydrolysis and fermentation to alcohol, and 
anaerobic digestion (Young, 1986).   
The program focused initially on screening a wide variety of species to identify potential 
candidates for commercialization (McLaughlin and Kszos, 2005).  These crops must be suited to 
grow on marginal land as defined by criteria such as having a high potential for erosion, being 
2 
 
excessively wet or dry, possessing poor soil quality, and with nutrient or rooting constraints.  
Other desired traits in these crops included being a native species, a perennial and established by 
seed, as well as having the ability to enhance soil and wildlife (McLaughlin and Kszos, 2005).  
Six universities and one private company were selected by the HECP to participate in an initial 
herbaceous screening process (Cushman et al., 1985) and each one chosen was required to screen 
at least two potential feedstock candidates. 
Although affected by severe droughts, Parrish et al. reported in 1990 that in the four years 
after establishment, switchgrass(Panicum virgatum) outperformed all other species being tested.  
Although annual species had better yields in years with higher rainfall, perennials outperformed 
them in lower rainfall years (Bransby et al., 1990).  Switchgrass showed little response to 
differing amounts of precipitation and after the first establishment year showed high, consistent 
yields.  Six of the seven intuitions included switchgrass in their recommendations for further 
study (Wright, 1992).  Due to higher production costs and high variability, annuals were dropped 
from the study.  Bransby?s discovery of the high yield potential of the switchgrass variety Alamo 
was a major factor in selecting switchgrass as the HECP?s model species for herbaceous energy 
crop production (Sladden et al., 1991).   
 
Conversion Technologies 
There are two broad methods for converting biomass into liquid fuels, biochemical and 
thermochemical.  While an economical feedstock with consistently high yields is the factor most 
important to all conversion methods, conversion efficiency of each method is affected by 
feedstock composition. 
3 
 
Biochemical conversion is the production of ethanol either by direct fermentation of 
sugars or by the enzymatic hydrolysis of starch or lingo-cellulosic material to sugars, and 
subsequent fermentation (Carpita, 1996).  Therefore, in biochemical conversion, the composition 
of the feedstock is critically important.  The soluble sugars and cellulose portion of the feedstock 
are most readily converted while hemicellulose, and much more so, lignin, require more 
pretreatment beforehand to avoid adversely affecting conversion efficiency (Chang and 
Holtzapple, 2000).  Feedstocks high in available cellulose and low in lignin are best for 
biochemical conversion (Himmel et al., 1997). 
Both feedstock composition and maturity can affect the conversion to ethanol.  While 
desired carbohydrate contents increase as switchgrass matures, their extraction becomes more 
challenging and an increase in pretreatment severity may be needed to compensate and could 
possibly lead to lower yields of hemicellulosic sugars (Sanderson et al., 2006).   
In order for cellulosic ethanol to become economically viable, improvements must be 
made to pretreatment processes, and to the feedstocks themselves for more effective release of 
fermentable sugars.  In other words, both plant breeding or genetic modifications to improve the 
feedstock composition along with improvements to the effectiveness of the pretreatment process 
would lower the cost of generating fermentable sugars (Himmel, 2007; Sticklen, 2006). 
Another broad method of bioenergy production is thermochemical conversion which 
includes direct combustion, gasification, and pyrolysis.  For these methods the cell wall structure 
of plants does make a small difference, but the physical properties of the biomass are more 
important.  Specifically, these processes generally benefit from the ability to deliver the 
feedstock in smaller particles which create more surface area to allow greater access of heat to 
4 
 
the biomass, and therefore, more efficient conversion (Kumar, 2009).  In this regard, the physical 
structure of switchgrass makes size reduction easier.   
While the non-combustible portion (ash) is only a small fraction of the feedstock, it is 
extremely important: biomass low in ash and minerals such, as N, P, K, and Si are best for 
thermochemical methods.  In particular, ash causes slagging and plugging of downstream 
equipment that leads to the need for expensive remediation (Kumar, 2009).  In addition, when 
gasified, most of the preexisting nitrogen contained in the feedstock results in formation of NOx 
(Kumar, 2009), which is a harmful emission. 
As the field continues to develop, a better understanding of the interaction between the 
feedstock and processing performance will help guide the selection of improved crops that are 
tailor-made to provide feedstocks for specific thermochemical or biological conversion 
technologies in a low-cost, efficient, and sustainable manner (Koonin, 2006; Ragauskas et al., 
2006). Switchgrass, the selected model herbaceous feedstock, continues to show strong potential 
as one such crop.  With its high energy density and low alkali content, it is a relatively clean fuel 
attractive as a thermochemical feedstock (McLaughlin et al., 1999).  Current genetic research 
and breeding will continue to improve the yield and other properties of switchgrass for more 
efficient conversion (Sanderson et al., 2006). 
An absence of operational commercial biorefineries in the continental United States leads 
to uncertainty in how best to optimize feedstocks for particular conversion processes.  However, 
research on the production of switchgrass and other feedstocks on rain-fed marginal land on a 
large scale appears to be an achievable goal (Sarath, 2008), and should be pursued in parallel 
with research on conversion technologies. 
 
5 
 
Switchgrass as an Energy Crop 
Selected as the model bioenergy crop by, switchgrass exhibits numerous beneficial 
characteristics to meet that selection criteria listed earlier.  It is a native C4 perennial grass that 
grows throughout much of North America in a wide variety of environments (Sanderson et al., 
1996).  Throughout its wide geographical range, it has been shown to produce consistently high 
yields (Fike et al., 2006) and has evolved to tolerate erodible soil with low nutrient or water 
requirements which avoids competition with food crop production that requires highly 
productive arable land (McLaughlin et al., 1994). 
Other agronomic traits also played a role in the selection of switchgrass.  Because it is 
able to be chopped or bailed, it can be harvested by preexisting farm practices which use hay- 
and silage-making equipment (Turhollow, 1994).  In addition, switchgrass is planted by seed 
which is less expensive to establish than some other potential feedstocks such as Miscanthus, 
which is vegetatively propagated by rhizomes, and energycane that is established by billets 
(Heaton et al., 2004).  As for hay crops, switchgrass can be dried by the sun in the field which 
provides a distinct advantage over other potential biomass crops that have been evaluated for 
southeastern production such as napiergrass, energycane, and giant reed (Knoll et al., 2012).  In 
addition, it is relatively low in ash and nitrogen concentrations compared to some other 
alternative crops, making it more preferable for direct thermochemical conversion. 
 Switchgrass grown for biomass provides environmental benefits as well.  It can provide a 
nesting habitat for migratory birds and cover for other native avian and animal species (Roth et 
al., 2005).  The deep roots of switchgrass allow not only for better drought tolerance, but can 
also play a role in capturing nutrients associated with non-point pollution (Ma et al., 2000).  
Switchgrass produces large amounts of biomass above ground for use as a bioenergy feedstock, 
6 
 
but also produces substantial root biomass that sequesters large amounts of atmospheric carbon 
(Ma et al., 2000).  Gains in root biomass are anticipated to continue to increase with long term 
production (McLaughlin et al., 1994). 
 
Geographic Distribution, Morphology, and Crop Improvement 
 Switchgrass can naturally tolerate a wide variety of habitats including open prairies, open 
woods and even brackish marshes.  It has a range from the eastern seaboard west into Wyoming, 
North Dakota and New Mexico and from Nova Scotia and Ontario in the north into Central 
America in the south (Hitchcock, 1971).  Both morphologically and genetically, switchgrass is 
divided into two distinct ecotypes, upland and lowland (Hultquist et al., 1996).  The lowland 
ecotype is tall and vigorous, has a bunch-type growth habit and is adapted to wetter conditions.  
The upland ecotype, on the other hand, is shorter, rhizomatous, thinner stemmed, and adapted to 
drier conditions (Sladden and Bransby, 1992).  The lowland ecotypes are tetraploid, while the 
upland ecotypes are octoploid (Lemus et al., 2002).  Switchgrass is largely self-incompatible, 
and breeding does not occur across ecotypes (McLaughlin and Kszos, 2005).  However, because 
of its wide range and varied environments, there are large variations in populations due to 
genetic factors such as genetic drift and mutation, along with environmental factors such as 
latitude, altitude, soil type, and climate variation, which have resulted in significant variation 
even within ecotype (Casler et al., 2007). 
 Switchgrass has only been studied as a potential crop for the last fifty years (Parrish and 
Fike, 2005) and for most of that time only as a possible forage crop: very little selective breeding 
has occurred for improved total biomass yield and composition with the objective to use it for the 
production of bioenergy.  Breeding aimed on its improvement as a forage crop involved mainly 
7 
 
upland ecotypes while new biofuel feedstock breeding research, especially the research in the 
Southeast, has shown that lowland switchgrass is the better suited ecotype and should be the 
basis for genetic improvement focus (Cassida et al., 2005). 
 One of the greatest issues in producing switchgrass as an energy crop has been 
developing protocols for the establishment of strong stands (McLaughlin and Kszos, 2005).  
Competition from fast growing weeds has been a problem in the first critical season and research 
within the HECP included studies to improve seed germination, evaluate herbicide treatments for 
weed control, and alter seedling vigor through breeding.  A large amount of the energy captured 
by switchgrass in the first two years is allocated by the plant to the development of a strong root 
system and full yield is typically not achieved until the third year after planting (McLaughlin and 
Kszos, 2005). 
 The varieties ?Alamo? and ?Kanlow? have been determined by long term studies in field 
research plots to be the best commercial varieties (McLaughlin and Kszos, 2005) with high 
yielding Alamo recommended for the deep south (Sanderson et al., 2006; Sladden et al., 1991). 
 With the yet unused adaptations of the many isolated populations and the natural 
variability within each population there are many sources of genetic material available for 
varietal improvement (Bouton, 2002).  Current genetic research and breeding can harness the 
diverse factors associated with these differences for better, improved varieties with higher yields, 
better establishment ability, and traits tailored to specific conversion methods (Sanderson, 2006). 
  
8 
 
 
 
 
 
Introduction 
 
Switchgrass has been chosen by The Bioenergy Feedstock Development Program 
initiated by the United States Department of Energy as a model bioenergy feedstock.  A native 
C4 perennial grass, switchgrass has a wide geographic range and is adapted to a variety of 
environmental conditions.  It can serve as a wildlife habitat and its deep roots can sequester large 
amounts of carbon. 
Among other advantages of switchgrass is primarily its potential for consistently high 
yields on marginal lands unsuitable for food production, and its ability to be utilized for both 
biochemical and thermochemical conversion methods.  However, even though current yields are 
impressive switchgrass has potential for even higher yields through selective breeding. 
The conversion technologies in which switchgrass biomass may be used as a feedstock 
can be divided into two categories, biochemical and thermochemical. While the feedstock trait 
most important to both categories is yield, other technology-specific biomass traits are beneficial 
as well.  In biochemical biomass conversion to ethanol, the cell wall composition of the 
feedstock is an important factor.  Specifically, soluble sugars and cellulose can be more readily 
converted into ethanol using this process, while hemicellulose and even more so, lignin, require 
more intensive pretreatment beforehand.  Feedstocks that are low in lignin are best for this 
method.  Thermochemical methods, comprised of combustion, gasification, and pyrolysis, are 
affected less by the cell wall components of a feedstock.  However, ash, nitrogen, and other non-
9 
 
combustible minerals create problems such as slagging and production of harmful emissions, so 
feedstocks which are low in these elements are desirable.  
 Relatively little selective breeding on switchgrass has been conducted to date and what 
has been done generally focused on potential of the crop to be used as a forage crop and mainly 
on the upland ecotypes.  There are two main commercial varieties of lowland switchgrass, 
Alamo and Kanlow, both of which are higher yielding than the upland varieties in studies 
performed in the eastern United States.  Alamo is the highest yielding and the ?benchmark? 
variety for use in the Deep South.  Even within varieties a large amount of genetic variability 
exists allowing for higher yielding strains to be produced from within this germplasm.  With 
emerging demand for improvements such as higher biomass yields, conversion specific 
composition, and more reliable establishment, interest in the production and evaluation of these 
strains has renewed breeding efforts. 
Selection of improved cultivars should focus on all three of the objectives but the 
ultimate goal is to improve yield and composition in mature stands.  Seedling vigor in both 
above ground growth and root development would lead to advantages in stand establishment. 
Links between seedling growth in a greenhouse and that of mature stands in the field are 
unknown.  However, if a consistent relationship existed between these two variables it could 
increase the rate of progress in genetic improvement which is currently severely constrained by 
the fact that switchgrass takes three years after planting to reach full production in the field.  
Therefore, the overall objectives of this study were to compare Alamo with two new genotypes 
of switchgrass, GA-992 and GA-993 and to determine whether seedling growth in a greenhouse 
was indicative of yield and other differences in a field experiment. 
 
 
10 
 
 
 
 
 
 
Materials and Methods 
 
Greenhouse Experiment 
 The greenhouse study was conducted twice, the first beginning in April of 2008 and the 
second beginning in August of the same year in Auburn, Alabama.  The switchgrass seeds were 
planted in conetainers filled to approximately 1 cm from the top of the conetainer.  The substrate 
used was soil collected from the E.V. Smith Research Station, a Wickham soil (fine-loam, 
mixed, thermic Typic Hapludult), and sifted to remove large particles. 
 Approximately 200 conetainers of Alamo, and two new genotypes, GA-992 and GA-993, 
were planted with 3 to 5 seeds each and later thinned to one plant per conetainer.  They were 
placed in racks and watered daily to field capacity.  The racks of seedlings were rotated 
periodically.  Four weeks after germination, seedlings were randomly selected to fill seven racks 
with twenty seedlings each of Alamo, GA-992, and GA-993, per rack.  Racks were rotated 
periodically to minimize the effects of locational variations across the greenhouse bench. 
 Beginning four weeks after planting, and continuing once a week for seven weeks, the 
above ground biomass of the seedlings from one tray was harvested.  Just prior to cutting height, 
number of leaves, and number of tillers of each plant in the tray were recorded.  Each seedling 
was then cut level with the rim of the conetainer, approximately 1 cm above the soil surface.  
The harvested material of each individual seedling was separately dried at 60 C for 48 hours, and 
the dry weight of each seedling was recorded. 
11 
 
 During the last harvest period, ten of the remaining un-harvested seedlings from each 
new genotype as well as Alamo were also randomly selected for root analysis.  Roots were 
carefully washed with tap water to remove the soil, blotted dry, and separated from the rest of the 
plant.  Roots were scanned using a WinRHIZO Root Scanner (Model STD 1600+, Regent 
Instruments, Inc.) to determine the total root length and the average root diameter.  The root and 
top portions of the plant were dried separately at 60 C in a forced air oven for 72 hours and then 
analyzed separately for carbon and nitrogen. 
The seven weekly measurements of seedling growth were analyzed using PROC 
GLIMMIX.  Means were considered significant at P<0.05.  Analysis of root composition and 
root mass data was performed using the GLM procedure.  Differences in the percentages of 
carbon and nitrogen were determined using Tukey?s least squared means.  Duncan?s multiple 
range test was used in evaluating the differences in total root length and average root diameter. 
 
Field Experiment  
 A field experiment was conducted for four years, 2006-2009.  It was planted in June of 
2006, and located at the Plant breeding Unit of the E.V. Smith Research and Extension Center 
near Shorter, Alabama.  The site of the study was on a Wickham soil (fine-loam, mixed, thermic 
Typic Hapludult).  A randomized complete block design was used with the three genotypes, each 
with four replications, over four years.  Each plot was 3.05 m x 9.14 m with 0.76 m row spacing. 
Weather information was obtained from the AWIS Services, Inc., Auburn Alabama, ?E.V. 
Smith? monitoring (Alabama Mesonet Weather Data, 2009).  A 10-year average was calculated 
to estimate ?normal? monthly rainfall (Table 2) and temperatures (Table 1).  
12 
 
 At the time of harvest (Table 8), ten tillers were randomly selected from each plot.  They 
were manually cut 5 cm above the soil surface and saved for later analysis.  A 1.07 m x 9.14 m 
strip of switchgrass was then harvested, giving a total harvested area of 9.75 m2.  The biomass 
cut from each plot was weighed.  Subsamples were taken from the harvested biomass of each 
plot, weighed immediately.  Both the ten-tiller samples and harvested subsamples were dried at 
60 degrees Celsius for 72 hours in a forced air oven.  The dried biomass subsamples were 
weighted for dry matter determination and discarded. 
 Data collected from the tiller samples were length, stem diameter and number of leaves.  
Tillers were then separated into leaf and stem components, with leaf sheaths counting as stem 
material.  All leaves or stems for each individual plot were combined and weighed.  The 
separated biomass was then milled using a Wiley mill to pass through a 2-mm screen for 
compositional analysis.  Carbon, nitrogen, neutral detergent fiber (NDF), acid detergent fiber 
(ADF), acid detergent lignin (ADL), and ash analysis were then performed on samples using the 
procedure described by Goering and van Soest(1970).     
 The GLIMMIX procedure of SAS (SAS Institute Inc., Cary, NC) was used to conduct the 
analysis of variance for yield, composition and morphological traits.  Results were considered 
significant at P<0.05. 
  
13 
 
 
 
Results 
 
Greenhouse Experiment 
The greenhouse experiment comparing Alamo and the two new genetic lines, GA-992 
and GA-993 was performed twice, one beginning in April of 2008 and the other in August of 
2008.  Due to the large difference associated with trial dates, there was a treatment x date 
interaction (Table 3) and the results of the two different dates are presented separately. 
 
April 2008  
 During the April seedling growth study some differences between Alamo, GA-992, and 
GA-993 were observed (Table 4), most notably, the differences in dry weight during several 
weeks (Figure 1).  Differences in dry weight after week one were evident with Alamo having 
less than GA-993 and a lower yield than both GA-992 and GA-993 after week two.  GA-992 
again out performed Alamo in week 5.  There were no differences in the number of tillers 
(Figure 3) or number of leaves (Figure 5) among the three genotypes during the seventh and final 
week of the trial.  The only difference in seedling height (Figure 7) was in the second week when 
GA-992 had significantly higher growth than Alamo.  
 
August 2008 
 Greater differences were recorded in the August study than in April for all variables that 
were measured (Table 5).  Both number of tillers and number of leaves which showed no 
differences in April, were different among genotypes in the final week of the August study 
14 
 
(Figures 4&6).  GA-993 had a higher number of tillers and leaves than Alamo.  The dry weight 
of all seedling samples taken in August (Figure 2) show a more definitive trend than that of the 
April study (Figure 1).  Specifically, Alamo had significantly less dry weight than both of the 
new genotypes in three of the weeks, and in each it had less dry weight than at least one of them.  
After the first and second week, GA-992 had greater dry weight than Alamo.   After week three, 
GA-993 had a higher dry weight than Alamo, and in week four, both new genotypes out 
performed Alamo.  After week five, dry weight of all three were different from one another: GA-
992 had a higher dry weight than Alamo and GA-993, and GA-993 out yielded Alamo.  GA-992 
had greater dry weight than GA-993 and Alamo after week six and seven 
 In August of 2008 seedling height followed a similar trend as dry weight.  GA-992 was 
taller than Alamo after the first and second weeks.  There was no difference in the height after 
week three.  After weeks four, five, and six, height of Alamo was lower than that of both GA-
992 and GA-993.  In week seven, the final week of the study, Alamo and GA-993 had similar 
average seedling heights, while and GA-992 was taller than both of them. 
 
Seedling Root Study 
 Carbon content of shoots from GA-992 and GA-993 did not from one another, but was 
higher than that of Alamo (Table 6).  Nitrogen content of shoots from GA- 992 and GA-993 was 
not different, but that of Alamo was higher than that of both new genotypes (Figure 9). 
 The percentage of carbon in the roots was not different among Alamo, GA-992, and GA-
993 (Table 6).  However, differences among each in percent nitrogen in the roots were detected: 
as with the shoots, the new genotypes had a lower concentration of nitrogen than did Alamo and 
no difference between them (Table 6).   
15 
 
 The roots of the seedlings were scanned to compare both average root diameter and total 
root length.  GA-992 and Alamo were significantly different in total root length, with GA-992 
having a greater total length, while GA-993 did not differ from either (Table 7, Figure 11).  
There was no difference among entries in root diameter (Figure 12). 
 
Field Experiment 
 With 4-year average yields of 10732, 8644, and 10348 Mg/ha of dry matter for Alamo, 
GA-992, and GA-993 respectively, no significant difference was shown in the years studied.  
Year did have a significant impact on dry matter yields which were higher in 2008 than in 2006 
and 2007 (Table 9).   
 There was also no difference between Alamo, GA-992, and GA-993 in leaf weight, stem 
weight, ratio of leaves to stems, and the total tiller weight determined from samples collected at 
the time of harvest in 2007 and 2008 (Table 10).  However, in 2008 leaf weight, stem weight, 
leaf to stem ratio, and total weight, were higher than in 2007 (Table 10).  This was likely due to 
higher rainfall in 2008 (Table 2), and harvesting of biomass produced in 2007 in late winter 
(Table 9) which would have resulted in considerable loss of yield compared to a fall harvest. 
 Average tiller length and diameter, and leaf number did not vary among the three 
genotypes (Table 12).  Tiller length and leaf number did not differ between years but tiller 
diameter was larger in the 2007 harvest.  Analysis of compositional data also revealed few 
differences (Tables 14 and 15).  The exceptions were a higher level of hemicellulose in Alamo 
than in GA-992 (Figure 27), and a higher level of N in the leave of Alamo than in the leaves of 
GA-993 (Table 15, Figure 29).  
16 
 
 
 
 
 
 
Conclusions 
 
Greenhouse Experiment 
Conclusions that were drawn from the greenhouse experiment are as follows: 
 complex interactions were observed between treatments (genotypes) and time: 
 for most harvest dates there was no significant difference among treatments, and 
this was partly due to high variation among seedlings, and therefore high 
experimental error, and 
 in all cases where  treatment differences were evident, results from GA-992 
and/or GA-993 were superior to those for Alamo. 
 
Field Experiment 
Results from the field experiment allowed the following conclusions to be drawn: 
 no differences were observed among treatments: 
 yield differences were observed across years, and appeared to be partially related 
to rainfall and a late harvest of biomass produced in 2007; and 
 there appeared to be no relationship between results from the greenhouse 
experiment and results from the field experiment. 
  
17 
 
 
 
 
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19 
 
 
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20 
 
 
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21 
 
 
 
 
 
Appendix 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
      
22 
 
Table 1. Average temperature per month during study and 10-year averages. 
 
  
T e n  Y e a r  P e r i o d  ( 2 0 0 0 - 2 0 0 9 )
M o n th 2005 2006 2007 2008 2009 M a x i mu m M i n i mu m A v e r a g e
J a n u a r y 9 . 4 * 1 1 . 0 9 . 5 6 . 8 8 . 3 1 1 . 0 6 . 8 9 . 0
F e b r u a r y 1 1 . 0 8 . 3 7 . 8 9 . 9 9 . 0 1 1 . 0 7 . 8 9 . 2
M a r c h 1 1 . 9 1 3 . 4 1 6 . 3 1 3 . 5 1 4 . 7 1 6 . 3 1 1 . 9 1 4 . 0
A p r i l 1 6 . 6 1 9 . 9 1 6 . 6 1 8 . 1 1 6 . 9 1 9 . 9 1 6 . 6 1 7 . 6
M a y  2 0 . 3 2 1 . 6 2 2 . 7 2 2 . 6 2 2 . 8 2 2 . 8 2 0 . 3 2 2 . 0
J u n e 2 5 . 5 2 6 . 0 2 7 . 3 2 7 . 2 2 7 . 1 2 7 . 3 2 5 . 5 2 6 . 6
J u l y 2 7 . 3 2 8 . 3 2 7 . 6 2 7 . 4 2 6 . 4 2 8 . 3 2 6 . 4 2 7 . 4
A u g u s t 2 7 . 1 2 8 . 3 3 0 . 4 2 6 . 9 2 6 . 6 3 0 . 4 2 6 . 6 2 7 . 9
S e p te mb e r 2 5 . 7 2 3 . 4 2 5 . 3 2 4 . 7 2 5 . 1 2 5 . 7 2 3 . 4 2 4 . 8
O c tob e r 1 8 . 3 1 7 . 6 2 0 . 5 1 7 . 8 1 8 . 4 2 0 . 5 1 7 . 6 1 8 . 5
N o v e mb e r  1 3 . 9 1 2 . 6 1 2 . 9 1 1 . 6 1 2 . 6 1 3 . 9 1 1 . 6 1 2 . 7
D e c e mb e r 6 . 8 1 1 . 0 1 1 . 5 1 1 . 1 8 . 3 1 1 . 5 6 . 8 9 . 8
A v er a g e T em p er a tu r e
* D a ta  e x p r e s s e d  a s  d e g r e e s  Ce l s i u s
23 
 
Table 2. Total monthly rainfall for years studied and 10-year averages. 
  
M o n th 2005 2006 2007 2008 2009 M a x i mu m M i n i mu m A v e r a g e
J a n u a r y 5 4 . 1 ? 1 1 2 . 3 1 5 0 . 4 1 1 0 . 7 5 2 . 1 1 5 0 . 4 5 2 . 1 9 5 . 9
F e b r u a r y 1 1 2 . 8 1 1 5 . 6 7 5 . 2 1 0 1 . 9 1 0 5 . 2 1 1 5 . 6 7 5 . 2 1 0 2 . 1
M a r c h 2 5 4 . 5 7 9 . 5 7 8 . 0 7 7 . 5 2 4 3 . 6 2 5 4 . 5 7 7 . 5 1 4 6 . 6
A p r i l 1 8 4 . 9 4 4 . 2 5 1 . 1 1 0 0 . 6 1 0 9 . 2 1 8 4 . 9 4 4 . 2 9 8 . 0
M a y  3 2 . 3 7 8 . 5 1 1 . 9 6 4 . 0 2 6 2 . 4 2 6 2 . 4 1 1 . 9 8 9 . 8
J u n e 3 9 . 1 1 8 . 3 2 9 . 2 5 0 . 3 9 9 . 6 9 9 . 6 1 8 . 3 4 7 . 3
J u l y 2 1 5 . 4 9 3 . 2 1 7 3 . 2 1 2 6 . 2 7 5 . 2 2 1 5 . 4 7 5 . 2 1 3 6 . 7
A u g u s t 8 6 . 6 9 9 . 3 8 2 . 8 2 5 2 . 0 1 9 1 . 8 2 5 2 . 0 8 2 . 8 1 4 2 . 5
S e p te mb e r 3 6 . 6 1 0 3 . 1 5 5 . 9 1 8 . 5 1 4 8 . 1 1 4 8 . 1 1 8 . 5 7 2 . 4
O c tob e r 4 5 . 0 1 1 0 . 7 7 5 . 4 8 3 . 1 1 6 3 . 6 1 6 3 . 6 4 5 . 0 9 5 . 6
N o v e mb e r  8 5 . 9 1 5 0 . 1 5 4 . 6 9 2 . 7 1 5 4 . 2 1 5 4 . 2 5 4 . 6 1 0 7 . 5
D e c e mb e r 5 1 . 8 6 2 . 2 9 4 . 5 8 2 . 3 2 7 6 . 4 2 7 6 . 4 5 1 . 8 1 1 3 . 4
T o ta l  1 1 9 8 . 9 1 0 6 7 . 1 9 3 2 . 2 1 1 5 9 . 8 1 8 8 1 . 1 2 2 7 6 . 9 6 0 7 . 1 1 2 4 7 . 8
* G r o w n i n g  S e a s o n 6 3 9 . 8 5 4 7 . 4 4 7 9 . 6 6 9 4 . 7 1 0 4 9 . 8 1 3 2 5 . 9 2 9 5 . 9 6 8 2 . 2
T o ta l  Ra i n f a l l
T e n  Y e a r  P e r i o d  ( 2 0 0 0 - 2 0 0 9 )
* T o ta l  g r o w i n g  s e a s o n  r a i n f a l l  ( A p r i l  to O c tob e r )
? D a ta  e x p r e s s e d  i n  mi l l i me te r s
24 
 
 
Table 3. Analysis of variance for weekly growth of seedlings in the greenhouse, April & August 
2008. 
 
 
 
 
 
 
 
 
P r o b a b i l i ty  o f  > F
D a te 1 2 0 8 9 . 3 < 0 . 0 0 1
2 1 5 7 . 4 < 0 . 0 0 1
2 9 . 0 0 . 0 0 0 1
D a y 6 1 0 6 1 . 5 0 . 0 0 0 0
6 9 2 . 6 < 0 . 0 0 1
12 2 . 6 0 . 0 0 2 3
12 5 . 5 < 0 . 0 0 1
D a te 1 2 7 5 1 . 8 < 0 . 0 0 1
2 1 1 6 . 2 < 0 . 0 0 1
2 1 2 . 7 < 0 . 0 0 1
D a y 6 8 8 7 . 3 0 . 0 0 0 0
6 6 9 . 7 < 0 . 0 0 1
12 2 . 7 0 . 0 0 1 4
12 4 . 1 < 0 . 0 0 1
D a te 1 7 7 7 . 0 < 0 . 0 0 1
2 1 2 . 3 < 0 . 0 0 1
2 1 0 . 7 < 0 . 0 0 1
D a y 6 1 6 9 . 8 < 0 . 0 0 1
6 6 9 . 1 < 0 . 0 0 1
12 1 . 3 0 . 2 3 9 1
12 2 . 2 0 . 0 0 8 8
N u m b e r  o f  T i l l e r s
D a te 1 2 8 5 . 1 < 0 . 0 0 1
2 1 4 . 4 < 0 . 0 0 1
2 2 . 3 0 . 1 0 0 8
D a y 6 1 3 5 . 9 < 0 . 0 0 1
6 4 5 . 3 < 0 . 0 0 1
12 2 . 5 0 . 0 0 2 9
12 1 . 2 0 . 2 6 1 6G e n o ty p e  x  D a te  x  D a y
G e n o ty p e  x  D a te
D a te  x  D a y
G e n o ty p e  x  D a te  x  D a y
N u m b e r  o f  L e a v e s
G e n o ty p e  x  D a te
D a te  x  D a y
G e n o ty p e  x  D a te  x  D a y
G e n o ty p e  x  D a te
D a te  x  D a y
G e n o ty p e
G e n o ty p e  x  D a y
G e n o ty p e
G r e e n h o u s e  G r o w th  
F s ta ti s ti c
G r a m s  D r y  M a tt e r
G e n o ty p e  x  D a te
E f f e c t D e g r e e s  o f  f r e e d o m
D a te  x  D a y
G e n o ty p e  x  D a te  x  D a y
H e i g h t
G e n o ty p e
G e n o ty p e  x  D a y
G e n o ty p e  x  D a y
G e n o ty p e  x  D a y
G e n o ty p e
25 
 
 
 
Table 4. Means of weekly growth measurements from the greenhouse experiment, beginning 
April 2008. 
  
 
 
 
 
 
 
W e e k 1 2 3 4 5 6 7
A l a mo 0 . 0 4 a * 0 . 0 8 a 0 . 1 3 ? 0 . 4 0 0 . 5 6 a 0 . 7 8 1 . 0 4
G A _ 9 9 2 0 . 0 6 a b 0 . 1 8 b 0 . 2 1 0 . 5 0 0 . 7 3 b 0 . 9 5 1 . 1 5
G A _ 9 9 3 0 . 0 9 b 0 . 1 6 b 0 . 1 8 0 . 4 1 0 . 7 1 a b 0 . 9 3 1 . 1 7
A l a mo 1 . 0 1 . 0 1 . 0 2 . 4 2 . 1 2 . 5 2 . 2
G A _ 9 9 2 1 . 0 1 . 0 1 . 0 2 . 8 2 . 7 2 . 7 2 . 7
G A _ 9 9 3 1 . 0 1 . 0 1 . 1 2 . 5 2 . 8 2 . 6 2 . 3
A l a mo 4 . 1 5 . 0 5 . 1 7 . 2 8 . 3 9 . 6 9 . 6
G A _ 9 9 2 4 . 9 5 . 1 5 . 4 8 . 2 9 . 3 1 0 . 7 1 1 . 5
G A _ 9 9 3 4 . 9 5 . 2 5 . 3 7 . 9 9 . 7 1 0 . 1 1 0 . 1
A l a mo 5 . 5 9 . 1 a 1 4 . 1 2 7 . 7 3 3 . 9 4 3 . 6 4 3 . 4
G A _ 9 9 2 8 . 7 1 3 . 8 b 1 7 . 3 2 9 . 0 3 9 . 3 4 4 . 9 5 0 . 7
G A _ 9 9 3 7 . 2 1 1 . 3 a b 1 7 . 1 2 9 . 1 4 0 . 0 4 3 . 8 5 0 . 9
? W e e k s  w i th  n o  l e tt e r s  s h o w e d  n o  d i f f e r e n c e  i n  th a t c a te g o r y .
* W e e k l y  c o l u mn s  w i th  d i f f e r e n t l e tt e r s ( a , b )  a r e   d i f f e r e n t a t P < 0 . 0 5 .   
S e e d l i n g  G r o w th  A p r i l  2 0 0 8
D r y  W e i g h t( g r a ms )
N u mb e r  o f  T i l l e r s
N u mb e r  o f  L e a v e s
H e i g h t( c m)
26 
 
 
 
Table 5. Means of weekly growth measurements from the greenhouse experiment, beginning 
August 2008. 
  
 
 
 
 
 
W e e k 1 2 3 4 5 6 7
A l a mo 0 . 0 1 a * 0 . 0 3 a 0 . 0 6 a 0 . 1 1 a 0 . 1 0 a 0 . 1 9 a 0 . 2 9 a
G A _ 9 9 2 0 . 0 4 b 0 . 0 8 b 0 . 0 9 a b 0 . 1 9 b 0 . 3 4 b 0 . 4 2 b 0 . 5 7 b
G A _ 9 9 3 0 . 0 2 0 . 0 6 a b 0 . 1 2 b 0 . 2 2 b 0 . 2 2 c 0 . 2 7 a 0 . 3 9 a
A l a mo 1 . 0 ? 1 . 0 1 . 0 1 . 1 1 . 0 1 . 5 1 . 5 a
G A _ 9 9 2 1 . 0 1 . 0 1 . 1 1 . 3 1 . 0 2 . 0 1 . 8 a b
G A _ 9 9 3 1 . 0 1 . 0 1 . 2 1 . 6 1 . 2 1 . 8 2 . 1 b
A l a mo 3 . 7 4 . 2 4 . 9 5 . 0 4 . 8 5 . 3 6 . 1 a
G A _ 9 9 2 4 . 3 4 . 6 5 . 0 4 . 5 4 . 0 4 . 7 6 . 4 a b
G A _ 9 9 3 4 . 4 4 . 6 4 . 9 5 . 0 4 . 9 5 . 6 7 . 6 b
A l a mo 2 . 3 a 3 . 8 a 6 . 4 8 . 5 a 7 . 8 7 a 1 1 . 5 5 a 1 9 . 9 a
G A _ 9 9 2 5 . 3 b 6 . 8 b 8 . 0 1 1 . 8 b 1 7 . 2 b 2 1 . 7 b 2 9 . 8 b
G A _ 9 9 3 3 . 5 a b 6 . 0 a b 8 . 3 1 3 . 7 b 1 2 . 5 b 1 6 . 8 b 1 9 . 6 a
S e e d l i n g  G r o w th  A u g u s t 2 0 0 8
D r y  W e i g h t( g r a ms )
N u mb e r  o f  T i l l e r s
N u mb e r  o f  L e a v e s
H e i g h t( c m)
* W e e k l y  c o l u mn s  w i th  d i f f e r e n t l e tt e r s ( a , b )  a r e  d i f f e r e n t a t P < 0 . 0 5 .   
? W e e k s  w i th  n o  l e tt e r s  s h o w e d  n o  d i f f e r e n c e  i n  th a t c a te g o r y .
27 
 
Figure 1. Changes in seedling dry weight of different genotypes with time for the greenhouse 
experiment starting in April 2008. 
  
 
 
 
 
 
 
 
Figure 2. Changes in seedling dry weight of different genotypes with time for the greenhouse 
experiment starting in August 2008. 
 
 
 
 
28 
 
Figure 3. Changes in the tiller number of different genotypes with time for the greenhouse 
experiment starting in April 2008. 
  
 
 
 
 
 
 
Figure 4. Changes in the tiller number of different genotypes with time for the greenhouse 
experiment starting in August 2008. 
  
 
 
29 
 
Figure 5. Changes in the leaf number of different genotypes with time for the greenhouse 
experiment starting in April 2008. 
  
 
 
 
 
 
Figure 6. Changes in the leaf number of different genotypes with time for the greenhouse 
experiment starting in August 2008. 
  
 
 
 
30 
 
Figure 7. Changes in seedling height of different genotypes with time for the greenhouse 
experiment starting in April 2008. 
  
 
 
 
 
 
 
Figure 8. Changes in seedling height of different genotypes with time for the greenhouse 
experiment starting in August 2008. 
  
 
 
 
31 
 
Table 6. Percentage of nitrogen and carbon in roots and shoot of samples from the greenhouse 
experiment. 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
A l a m o
G A - 9 9 2
G A - 9 9 3
*V a l u es  b a s ed  o n  t h e a v er a g e p er c en t  d r y  m a t t er  o f  t en  s a m p l es .
? C o l u m n s  w i t h  t h e s a m e l et t er  d o  n o t  d i f f er  ( P >0 . 0 5 ) .  
? S t a n d a r d  d ev i a t i o n s  ( S D )  i n  p a r en t h es es .
R o o t
1 . 4 1 *( 0 . 2 9 ) ?a ? 4 5 . 1 9 ( 0 . 5 5 ) a
S h o o t
C a r b o nN i t r o g enN i t r o g en C a r b o n
0 . 9 1 ( 0 . 1 3 ) a
4 4 . 2 7 ( 0 . 8 4 ) a
4 3 . 7 8 ( 1 . 2 0 ) a
4 3 . 8 7 ( 0 . 9 3 ) a
1 . 0 0 ( 0 . 2 0 ) b 4 4 . 3 3 ( 0 . 6 7 ) b 0 . 7 6 ( 0 . 1 0 ) b
0 . 9 0 ( 0 . 3 0 ) b 4 5 . 1 7 ( 0 . 3 0 ) b 0 . 7 1 ( 0 . 1 4 ) b
32 
 
Figure 9. Percent nitrogen in roots and shoots from the greenhouse experiment on a dry matter 
basis. 
 Root or shoot components with the same letter do not differ (P>0.05). 
 
 
 
 
 
 
Figure 10. Percent carbon in roots and shoots from the greenhouse experiment on a dry matter 
basis. 
 
Root or shoot components with the same letter do not differ (P>0.05). 
 
 
 
 
 
 
 
 
33 
 
 
 
 
 
Table 7. Root measurement of samples from the greenhouse experiment. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
A l a m o
G A - 9 9 2
G A - 9 9 3
*V a l u es  b a s ed  o n  t h e a v er a g e p er c en t  d r y  m a t t er  o f  t en  s a m p l es .
1 1 3 8 . 3 ( 4 0 7 . 7 ) a b
0 . 3 5 2 ( 0 . 0 4 3 ) a
0 . 3 4 9 ( 0 . 0 6 0 ) a
? S t a n d a r d  d ev i a t i o n s  ( S D )  i n  p a r en t h es es .
R o o t  L e n g t h ( c m)
9 0 2 . 5 *( 3 1 2 . 4 ) ?a ?
R o o t  D i a me t e r ( mm )
0 . 4 0 4 ( 0 . 0 6 5 ) a
1 3 3 6 . 0 ( 3 2 0 . 3 ) b
?C o l u m n s  w i t h  t h e s a m e l et t er  d o  n o t  d i f f er  ( P >0 . 0 5 ) .
34 
 
 
 
 
Figure 11. Average root length of samples from the greenhouse experiment. 
 Values with the same letter do not differ (P<0.05). 
 
 
 
 
 
 
 
 
 
Figure 12. Average root diameter of samples from the greenhouse experiment. 
 
Values with the same letter do not differ (P<0.05). 
 
 
 
 
35 
 
 
Table 8. Harvest dates and biomass yields from the field experiment planted on 6/12/2006. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Y e a r A l a m o G A _ 9 9 2 G A _ 9 9 3
2006 7 0 0 9 * a ? 5481a 7682a
2007 9245a 9083a 8416a
2008 15645b 10331b 16418b
2009 11028ab 9681ab 8876ab
M e a n 10732 8644 10348
1 0 / 1 0 / 2 0 0 8
1 1 / 9 / 2 0 0 9
1 1 / 2 / 2 0 0 6
Y i e l d  a n d  H a r v e s t  D a t e s  -  S w i t c h g r a s s  F i e l d  E x p e r i me n t
A l a mo ,  G A - 9 9 2  a n d  G A - 9 9 3  -  P l a n t e d  6 / 1 2 / 0 6
* Y i e l d s  e x p r e s s e d  a s  k g  d r y  ma t t e r  p e r  h e c t a r e .
? M e a n s  w i t h  t h e  s a me  l e t t e r  d o  n o t  d i f f e r  a t  P < 0 . 0 5 .
D a t e  o f  H a r v e s t
2 / 2 9 / 2 0 0 8
36 
 
 
 Figure 13. Total biomass yield (kg/ha) from the field experiment, 2006-2009. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
37 
 
Table 9. Analysis of variance for weight of tiller components of samples from the field 
experiment, 2007 and 2008. 
 
 
 
 
 
  
Y e a r 1 6 5 . 8 0 . 0 0 0 0
G e n o ty p e 2 0 . 7 0 . 5 1 7 5
2 0 . 1 0 . 9 3 0 8
Y e a r 1 1 7 . 1 0 . 0 0 2 5
G e n o ty p e 2 0 . 2 0 . 8 1 0 3
2 0 . 2 0 . 8 4 4 0
Y e a r 1 5 2 . 2 0 . 0 0 0 1
G e n o ty p e 2 2 . 0 0 . 2 0 5 6
2 0 . 3 0 . 7 6 2 8
Y e a r 1 2 4 . 0 0 . 0 0 0 9
G e n o ty p e 2 0 . 1 0 . 8 7 5 7
2 0 . 1 0 . 8 8 6 1
G e n o ty p e  x  Y e a r
T o t a l  W e i g h t
G e n o ty p e  x  Y e a r
G e n o ty p e  x  Y e a r
L e a f : St e m  R a t i o
F s ta ti s ti c P r o b a b i l i ty  o f  > FE f f e c t
L e a f  W e i g h t
St e m  W e i g h t
G e n o ty p e  x  Y e a r
D e g r e e s  o f  f r e e d o m
38 
 
Table 10. Means and standard deviations of the weights of tiller components of samples from the 
field experiment, 2007 and 2008. 
 
 
 
L e a v e s S te ms T o ta l L e a f :S te m R a ti o
2007
A l a mo 5 . 1 5 * 5 6 . 8 2 6 1 . 9 7 0 . 0 9 1
( 1 . 5 1 ) ? ( 1 4 . 8 3 ) ( 1 5 . 9 6 ) ( 0 . 0 1 9 )
G A - 9 9 2 4 . 6 0 5 1 . 6 7 5 6 . 2 7 0 . 0 9 1
( 0 . 5 3 ) ( 9 . 2 8 ) ( 9 . 1 7 ) ( 0 . 0 2 0 )
G A - 9 9 3 4 . 3 9 4 8 . 1 6 5 3 . 6 5 0 . 1 1 4
( 2 . 6 1 ) ( 7 . 8 1 ) ( 8 . 6 8 ) ( 0 . 0 1 1 )
2008
A l a mo 1 5 . 0 0 7 7 . 5 0 9 2 . 5 0 0 . 1 9 3
( 4 . 0 8 ) ( 1 4 . 2 7 ) ( 1 7 . 8 2 ) ( 0 . 0 3 1 )
G A - 9 9 2 1 3 . 7 5 8 0 . 5 0 9 4 . 2 5 0 . 1 7 2
( 3 . 7 7 ) ( 2 0 . 3 4 ) ( 2 3 . 2 3 ) ( 0 . 0 3 7 )
G A - 9 9 3 1 2 . 6 0 7 6 . 2 5 9 2 . 0 0 0 . 2 1 6
( 7 . 5 4 ) ( 2 1 . 7 9 ) ( 2 3 . 4 2 ) ( 0 . 0 5 8 )
? S ta n d a r d  d e v i a ti o n  ( S D )  i n  p a r e n th e s e s
* A l l  V a l u e s  E x p r e s s e d  a s  G r a ms  D r y  M a tt e r
D a ta  B a s e d  o n  th e  T o ta l  D r y  M a tt e r  o f  th e  L e a v e s  a n d  S te ms  o f  T i l l e r s  Co l l e c te d  
39 
 
Figure 14. Dry weight of whole, leaf, and stem components of tiller samples from the field 
experiment by year, 2007-2008. 
 Values with the same letter do not differ (P<0.05). 
 
 
 
 
 
 
 
 
 
Figure 15. Dry weight of whole, leaf, and stem components of tiller samples from the field 
experiment by genotype, 2007-2008. 
 
Values with the same letter do not differ (P<0.05). 
 
 
 
 
40 
 
 
Figure 16. Leaf to stem weight ratio on a dry matter basis from the field experiment by year, 
2007-2008. 
 
Values with the same letter do not differ (P<0.05). 
 
 
 
 
 
 
 
 
Figure 17. Leaf to stem weight ratio on a dry matter basis from the field experiment by genotype, 
2007-2008. 
 
Values with the same letter do not differ (P<0.05). 
 
 
 
 
41 
 
 
Table 11. Analysis of variance for tiller length, diameter, and leaf number of samples from the 
field experiment, 2007 and 2008. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
E f f e c t
1 0 . 1 7 2 5
2 0 . 8 6 4 9
2 0 . 4 3 6 1
1 0 . 0 0 6 8
2 0 . 2 7 2 9
2 0 . 5 9 3 5
1 0 . 5 8 7 9
2 0 . 7 6 8 7
2 0 . 8 9 7 1
G e n o t y p e 0 . 1
G e n o t y p e  x  Y e a r 0 . 9
D i a m e t e r(m m )
D e g r e e s  o f  f r e e d o m F S t a t i s t i c
T i l l e r L e n g t h (c m )
Y e a r 2 . 4
0 . 1
1 2 . 2
1 . 5
G e n o t y p e  x  Y e a r 0 . 6
N u m b e r o f  L e a v e s
0 . 3
Y e a r
G e n o t y p e
Y e a r
G e n o t y p e
0 . 4
P r o b a b i l i t y  o f  > F
G e n o t y p e  x  Y e a r
42 
 
 
 
Table 12.  Means and standard deviations for tiller length, diameter, and leaf number of samples 
from the field experiment, 2007 and 2008. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
2007
A l a mo 1 2 4 . 9 8 4 . 6 6 7 . 5 8
( 1 5 . 6 6 ) * ( 0 . 8 7 ) ( 0 . 9 3 )
G A - 9 9 2 1 3 0 . 1 8 4 . 8 4 7 . 3 0
( 2 2 . 0 2 ) ( 0 . 7 8 ) ( 1 . 0 9 )
G A - 9 9 3 1 2 5 . 5 0 4 . 4 5 7 . 4 3
( 1 4 . 5 0 ) ( 0 . 7 6 ) ( 0 . 9 8 )
2008
A l a mo 1 2 4 . 9 8 4 . 3 4 7 . 4 0
( 1 8 . 3 4 ) ( 0 . 6 5 ) ( 1 . 2 4 )
G A - 9 9 2 1 1 6 . 0 0 4 . 1 1 7 . 3 0
( 1 8 . 5 0 ) ( 0 . 5 8 ) ( 1 . 4 7 )
G A - 9 9 3 1 1 8 . 4 5 3 . 8 3 7 . 2 3
( 1 8 . 5 3 ) ( 0 . 8 3 ) ( 1 . 6 7 )
A v e r a g e  M e a s u r e me n ts  o f  T i l l e r s  Co l l e c te d  f r o m E a c h  G e n o ty p e  ( 2 0 0 7 - 2 0 0 8 )
T i l l e r  L e n g th ( c m) D i a me te r ( mm) N u mb e r  o f  L e a v e s
* S ta n d a r d  d e v i a ti o n  ( S D )  i n  p a r e n th e s e s
43 
 
 
Figure 18. Average tiller length from the field experiment by year, 2007 and 2008. 
 Values with the same letter do not differ (P<0.05). 
 
 
 
 
 
 
 
 
 
 
 
Figure 19. Average tiller length from the field experiment by genotype, 2007 and 2008. 
 
Values with the same letter do not differ (P<0.05). 
 
 
 
44 
 
 
Figure 20. Average tiller diameter from the field experiment by year, 2007 and 2008. 
 Values with the same letter do not differ (P<0.05). 
 
 
 
 
 
 
 
 
 
 
 
Figure 21. Average tiller diameter from the field experiment by genotype, 2007 and 2008. 
 
Values with the same letter do not differ (P<0.05). 
 
 
 
45 
 
 
 
Figure 22. Average number of leaves per tiller from the field experiment by year, 2007 and 2008. 
 
Values with the same letter do not differ (P<0.05). 
 
 
 
 
 
 
 
 
 
Figure 23. Average number of leaves per tiller from the field experiment by genotype, 2007 and 
2008. 
 Values with the same letter do not differ (P<0.05). 
 
 
 
46 
 
 
Table 13. Analysis of variance for leaf cell wall composition of samples from the field 
experiment, 2007-2009. 
  
 
 
  
L e a f  Co mp o s i ti o n
P r o b a b i l i ty  o f  > F
N e u tr a l  D e te r g e n t F i b e r
G e n o ty p e 2 0 . 6 3 2 0 . 5 5 3 3
Y e a r 2 1 . 7 4 3 0 . 2 3 4 9
4 0 . 7 8 8 0 . 5 6 1 2
A c i d  D e te r g e n t F i b e r
G e n o ty p e 2 0 . 8 9 0 0 . 4 5 0 2
Y e a r 2 1 9 . 9 3 3 < 0 . 0 0 1
4 0 . 8 2 5 0 . 5 2 6 5
G e n o ty p e 2 0 . 9 9 9 0 . 4 1 2 5
Y e a r 2 3 6 . 9 0 9 < 0 . 0 0 1
4 1 . 5 6 6 0 . 2 5 0 0
A s h
G e n o ty p e 2 2 . 6 2 8 0 . 1 2 1 8
Y e a r 2 2 8 . 7 7 1 < 0 . 0 0 1
4 0 . 3 5 2 0 . 8 3 8 5
E f f e c t D e g r e e s  o f  f r e e d o m F s ta ti s ti c
G e n o ty p e  x  Y e a r
G e n o ty p e  x  Y e a r
A c i d  D e te r g e n t L i g n i n
G e n o ty p e  x  Y e a r
G e n o ty p e  x  Y e a r
47 
 
 
Figure 24. Leaf cell wall composition from the field experiment by year, 2007-2009. 
 Cell wall components with the same letter do not differ (P>0.05). 
 
 
 
 
 
 
 
 
Figure 25. Leaf cell wall composition from the field experiment by genotype, 2007-2009. 
 
Cell wall components with the same letter do not differ (P>0.05). 
 
 
 
 
48 
 
 
Table 14. Analysis of variance of stem cell wall composition of samples from the field 
experiment, 2007-2009. 
  
  
S te m Co mp o s i ti o n
P r o b a b i l i ty  o f  > F
N e u tr a l  D e te r g e n t F i b e r
G e n o ty p e 2 0 . 6 3 8 0 . 5 5 5 0
Y e a r 2 1 1 6 . 7 8 7 < 0 . 0 0 1
4 0 . 2 1 1 0 . 9 2 7 6
A c i d  D e te r g e n t F i b e r
G e n o ty p e 2 4 . 3 7 7 0 . 0 4 3 4
Y e a r 2 3 2 . 1 2 1 < 0 . 0 0 1
4 0 . 1 4 2 0 . 9 6 2 6
G e n o ty p e 2 2 . 2 8 2 0 . 1 4 9 6
Y e a r 2 5 5 . 6 0 4 0 . 0 0 0 1
4 0 . 1 7 7 0 . 9 4 0 1
A s h
G e n o ty p e 2 3 . 0 2 3 0 . 1 0 8 9
Y e a r 2 5 . 2 7 2 0 . 0 3 3 2
4 1 . 9 5 1 0 . 1 6 5 7
G e n o ty p e  x  Y e a r
E f f e c t D e g r e e s  o f  f r e e d o m F s ta ti s ti c
G e n o ty p e  x  Y e a r
A c i d  D e te r g e n t L i g n i n
G e n o ty p e  x  Y e a r
G e n o ty p e  x  Y e a r
49 
 
 
Figure 26. Stem cell wall composition from the field experiment by year 2007-2009. 
 
 
 
Cell wall components with the same letter do not differ (P>0.05). 
 
 
 
 
 
 
 
Figure 27. Stem cell wall composition from the field experiment by genotype, 2007-2009. 
 
 Cell wall components with the same letter do not differ (P>0.05). 
 
 
 
  
50 
 
 
Table 15. Analysis of variance of the percentage of nitrogen and carbon in the leaves and stems 
of samples from the field experiment, 2007-2009. 
  
P e r c e n ta g e  o f  Ca r b o n  a n d  N i tr o g e n  i n  L e a v e s  a n d  S te ms
E f f e c t
L e a v e s
G e n o ty p e 2 0 . 6 0 . 5 8 5 6
Y e a r 2 1 1 . 1 0 . 0 0 0 9
4 1 . 7 0 . 2 0 4 2
G e n o ty p e 2 5 . 7 0 . 0 2 0 6
Y e a r 2 1 5 . 6 0 . 0 0 1 1
4 0 . 4 0 . 7 9 5 9
S te ms
G e n o ty p e 2 0 . 1 0 . 8 6 7 6
Y e a r 2 8 . 9 0 . 0 0 4 7
4 0 . 9 0 . 5 2 8 4
N i tr o g e n
G e n o ty p e 2 1 . 2 0 . 3 7 0 5
Y e a r 2 3 6 . 7 < 0 . 0 0 1
4 0 . 3 0 . 8 6 1 2
F S ta ti s ti c P r o b a b i l i ty  o f  > F
N i t r o g e n
G e n o ty p e  x  Y e a r
G e n o ty p e  x  Y e a r
C a r b o n
G e n o ty p e  x  Y e a r
C a r b o n
G e n o ty p e  x  Y e a r
D e g r e e s  o f  f r e e d o m
51 
 
 
Figure 28. Percent nitrogen in samples from the field experiment on a dry matter basis by year, 
2007-2009. 
 Leaf or stem components with the same letter do not differ (P>0.05). 
 
 
 
 
 
 
 
Figure 29. Percent nitrogen in samples from the field experiment on a dry matter basis by 
genotype, 2007-2009. 
 
Leaf or stem components with the same letter do not differ (P>0.05). 
 
 
 
 
 
52 
 
 
 
Figure 30. Percent carbon in samples from the field experiment on a dry matter basis by year, 
2007-2009. 
 
Leaf or stem components with the same letter do not differ (P>0.05). 
 
 
 
 
 
 
Figure 31. Percent carbon in samples from the field experiment on a dry matter basis by 
genotype, 2007-2009. 
 Leaf or stem components with the same letter do not differ (P>0.05).