EVALUATION OF SELECTED CELLULOSIC ENERGY CROPS FOR THE 
SOUTHEASTERN UNITED STATES  
 
by 
 
Ping Huang 
 
 
 
 
A dissertation submitted to the Graduate Faculty of 
Auburn University 
in partial fulfillment of the 
requirements for the Degree of 
Doctor of Philosophy 
 
Auburn, Alabama 
December 8, 2012 
 
 
 
 
Keywords: cellulosic energy crops; annuals; perennials; aboveground biomass yield; soil 
impacts; biomass feedstocks 
 
Copyright 2012 by Ping Huang 
 
 
Approved by 
 
David I. Bransby, Chair, Professor, Department of Agronomy and Soils  
Edzard van Santen, Professor, Department of Agronomy and Soils 
Francisco J. Arriaga, Affiliate Associate Professor, Department of Soil Science 
Haitao Zuo, Associate Professor, Beijing R&D Center for Grass and Environment
 
ii 
 
 
 
 
 
 
 
 
ABSTRACT 
 
 
 Encouraging progress towards commercial production of cellulosic biofuels has 
recently raised the importance of identifying economically feasible and environmentally 
sustainable cellulosic biomass supply chains. In this regard, dedicated cellulosic energy 
crops are superior to agricultural residues due to their higher yield which results in less 
area needed to produce a given quantity of biomass and, therefore, lower transportation 
costs. A substantial amount of research has been conducted on perennial cellulosic 
energy crops such as switchgrass (Panicum virgatum L.), giant reed (Arundo donax L.) 
and mimosa (Albizia julibrissin Durazz.), but relatively little attention has been paid to 
annuals that could be rotated with existing row crops without competing with them for 
land. Moreover, little or no information is available on long-term (>10 years) yields and 
soil impacts of energy crops and the yield responses to critical economic factors. 
Therefore, the overall goal of research reported in this dissertation was to evaluate yield 
and soil impacts of selected potential energy crops for the southeastern United States. 
The first-two experiments of the project evaluated three common winter annuals 
(black oat (Avena strigosa Schreb.), rye (Secale cereale L. subsp. cereale) and annual 
ryegrass (Lolium multiflorum Lam.)) and three summer annuals (forage sorghum 
(Sorghum bicolor spp.), pearl millet (Pennisetum americanum (L.) R. Br.) and sorghum-
sudangrass (Sorghum bicolor (L.) Moench nothosubsp. drummondii (Steud.) de Wet ex 
Davidse)) in a range of crop rotation systems. Compared to black oat and ryegrass, rye 
was the most suitable winter crop for biomass production in rotation with cotton 
 
iii 
 
 
(Gossypium hirsutum L.), peanuts (Arachis hypogaea L.) and soybeans (Glycine max (L.) 
Merr.). For the three winter annuals in rotation with the three summer crops for year-
round biomass production, with either conventional-till or no-till management, double-
cropping systems that included pearl millet or forage sorghum under no-till management 
were superior to other cropping systems under either tillage treatment in the first year. 
However, within each tillage treatment, double-cropping systems that included forage 
sorghum or sorghum-sudangrass were superior to other cropping systems in the second 
and third years. 
The other five experiments in the project evaluated giant reed, mimosa and 
switchgrass for biomass production. Giant reed and mimosa provided much higher 
biomass yield than switchgrass in long-term experiments, even though they received no 
fertilization, while switchgrass received a medium amount of N fertilizer annually. In 
contrast to traditional summer row crops such as corn, cotton and soybeans, rainfall did 
not have large effects on biomass yields of these three perennials, and neither did age of 
stand. Biomass yield of switchgrass increased at a declining rate as N levels increased, 
but subsoiling did not improve yield and interseeding crimson clover actually decreased 
yield. Biomass yield of giant reed was not improved by application of broiler litter. While 
there was no difference in biomass yield between annual and biennial harvests in winter, 
biennial harvesting will likely result in lower cost Mg-1. Biomass production of giant reed 
was reached a maximum in mid-September to mid-November. Long-term biomass 
production of giant reed and switchgrass tended to decrease topsoil pH and extractable 
Mg and Ca contents compared to an adjacent area under bahiagrass (Paspalum notatum 
Fl?gg?), and giant reed seemed to increase extractable P and K.   
  
 
 
iv 
 
 
 
 
 
 
 
 
ACKNOWLEDGMENTS 
 
 
The author would like to thank Dr. David Bransby for the support, inspiration, 
scientific advice and guidance provided during the past four and half years. The author 
would also like to thank the advisory committee, Dr. Edzard van Santen, Dr. Francisco 
Arriaga, and Dr. Haitao Zuo for their help and support throughout and for input in 
editing. Thank you to Dr. van Santen for help and guidance through statistical analysis. A 
special thanks to Susan Sladden for help with data collection. The author would also like 
to thank the team at the E.V. Smith Plant Breeding Unit and Field Crop Unit for their 
help with field work. Thank you to the rest of the Agronomy and Soils department for 
making my experience enjoyable. Special thanks are also expressed to my parents, wife 
and friends who gave me confidence, support and love throughout this process. 
 
 
 
 
 
 
 
 
 
 
v 
 
 
 
 
 
 
 
 
TABLE OF CONTENTS 
 
 
ABSTRACT ........................................................................................................................ ii 
ACKNOWLEDGMENTS ................................................................................................. iv 
LIST OF TABLES .............................................................................................................. x 
LIST OF FIGURES ........................................................................................................... xi 
LIST OF PLATES ........................................................................................................... xiv 
CHAPTER 1    EVALUATION OF WINTER ANNUALS FOR BIOMASS 
PRODUCTION IN ROTATION WITH TRADITIONAL SUMMER 
ROW CROPS ............................................................................................ 1 
ABSTRACT ................................................................................................................ 1 
1.1 INTRODUCTION ................................................................................................. 2 
1.2 MATERIALS AND METHODS .......................................................................... 4 
1.2.1 Treatments and experimental design ...................................................... 4 
1.2.2 Crop rotation ........................................................................................... 4 
1.2.3 Data collection ........................................................................................ 5 
1.2.4 Data analysis ........................................................................................... 6 
1.3 RESULTS AND DISCUSSIONS.......................................................................... 7 
1.3.1 Weather conditions ................................................................................. 7 
1.3.2 Winter biomass yield .............................................................................. 7 
1.3.3 Summer row crop yield .......................................................................... 8 
1.4 CONCLUSION...................................................................................................... 8 
1.5 REFERENCES ...................................................................................................... 8 
 
vi 
 
 
CHAPTER 2    EVALUATION OF WINTER ANNUALS IN ROTATION WITH 
TRADITIONAL SUMMER FORAGE CROPS FOR YEAR-ROUND 
BIOMASS PRODUCTION IN ALABAMA .......................................... 18 
ABSTRACT .............................................................................................................. 19 
2.1 INTRODUCTION ............................................................................................... 20 
2.2 MATERIALS AND METHODS ........................................................................ 22 
2.2.1 Treatments and experimental design .................................................... 22 
2.2.2 Crop rotation ......................................................................................... 23 
2.2.3 Data collection ...................................................................................... 23 
2.2.4 Data analysis ......................................................................................... 24 
2.3 RESULTS AND DISCUSSIONS........................................................................ 24 
2.3.1 Weather conditions ............................................................................... 24 
2.3.2 Winter biomass yield ............................................................................ 25 
2.3.3 Summer biomass yield .......................................................................... 26 
2.3.4 Total annual biomass yield of winter and summer seasons .................. 28 
2.4 CONCLUSIONS ................................................................................................. 30 
2.5 REFERENCES .................................................................................................... 30 
CHAPTER 3    LONG-TERM YIELDS AND SOIL IMPACTS OF GIANT REED, 
SWITCHGRASS AND MIMOSA GROWN FOR BIOMASS 
PRODUCTION IN ALABAMA ............................................................. 49 
ABSTRACT .............................................................................................................. 49 
3.1 INTRODUCTION ............................................................................................... 50 
3.2 MATERIALS AND METHODS ........................................................................ 53 
3.2.1 Treatments and experimental design .................................................... 53 
3.2.2 Data collection ...................................................................................... 54 
3.2.3 Data analysis ......................................................................................... 55 
3.3 RESULTS AND DISCUSSIONS........................................................................ 55 
 
vii 
 
 
3.3.1 Weather conditions ............................................................................... 55 
3.3.2 Biomass yield ........................................................................................ 56 
3.3.3 Soil impacts .......................................................................................... 57 
3.4 CONCLUSIONS ................................................................................................. 58 
3.5 REFERENCES .................................................................................................... 59 
CHAPTER 4    EFFECTS OF NITROGEN FERTILIZATION AND SUBSOILING ON 
BIOMASS YIELD OF ESTABLISHED SWITCHGRASS ................... 72 
ABSTRACT .............................................................................................................. 72 
4.1 INTRODUCTION ............................................................................................... 73 
4.2 MATERIALS AND METHODS ........................................................................ 75 
4.2.1 Treatments and experimental design .................................................... 75 
4.2.2 Data collection ...................................................................................... 76 
4.2.3 Data analysis ......................................................................................... 76 
4.3 RESULTS AND DISCUSSIONS........................................................................ 76 
4.3.1 Weather conditions ............................................................................... 76 
4.3.2 Biomass yield ........................................................................................ 77 
4.4 CONCLUSIONS ................................................................................................. 78 
4.5 REFERENCES .................................................................................................... 78 
CHAPTER 5    EFFECTS OF NITROGEN FERTILIZATION AND INTERSEEDING 
CRIMSON CLOVER ON BIOMASS YIELD OF ESTABLISHED 
SWITCHGRASS ..................................................................................... 87 
ABSTRACT .............................................................................................................. 87 
5.1 INTRODUCTION ............................................................................................... 88 
5.2 MATERIALS AND METHODS ........................................................................ 89 
5.2.1 Treatments and experimental design .................................................... 89 
5.2.2 Data collection ...................................................................................... 90 
 
viii 
 
 
5.2.3 Data analysis ......................................................................................... 90 
5.3 RESULTS AND DISCUSSIONS........................................................................ 91 
5.3.1 Weather conditions ............................................................................... 91 
5.3.2 Biomass yield ........................................................................................ 91 
5.4 CONCLUSIONS ................................................................................................. 92 
5.5 REFERENCES .................................................................................................... 93 
CHAPTER 6    EFFECTS OF HARVEST TIME AND FREQUENCY AND 
APPLICATION OF BROILER LITTER ON BIOMASS AND 
RHIZOME YIELD OF GIANT REED IN ALABAMA ....................... 104 
ABSTRACT ............................................................................................................ 104 
6.1 INTRODCUTION ............................................................................................. 105 
6.2 MATERIALS AND METHODS ...................................................................... 107 
6.2.1 Treatments and experimental design .................................................. 107 
6.2.2 Data collection .................................................................................... 108 
6.2.3 Data analysis ....................................................................................... 108 
6.3 RESULTS AND DISCUSSIONS...................................................................... 109 
6.3.1 Weather conditions ............................................................................. 109 
6.3.2 Biomass yield ...................................................................................... 109 
6.3.3 Rhizome yield ..................................................................................... 111 
6.4 CONCLUSIONS ............................................................................................... 112 
6.5 REFERENCES .................................................................................................. 113 
CHAPTER 7    SEASONAL GROWTH PATTERNS OF GIANT REED IN ALABAMA
 ............................................................................................................... 123 
ABSTRACT ............................................................................................................ 123 
7.1 INTRODUCTION ............................................................................................. 124 
7.2 MATERIALS AND METHODS ...................................................................... 124 
 
ix 
 
 
7.2.1 Treatments and experimental design .................................................. 124 
7.2.2 Data collection .................................................................................... 125 
7.2.3 Data analysis ....................................................................................... 126 
7.3 RESULTS AND DISCUSSIONS...................................................................... 127 
7.4 CONCLUSIONS ............................................................................................... 129 
7.5 REFERENCES .................................................................................................. 130 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
x 
 
 
 
 
 
 
 
 
LIST OF TABLES 
 
 
Table 1-1     Monthly and growing season precipitation 2007-2010. ............................... 11 
Table 1-2     Yields of summer row crops in 2008-2010. ................................................. 12 
Table 2-1     Cultivars, seeding rates, planting dates and harvest dates of winter annuals 
and summer crops. ........................................................................................ 32 
Table 2-2     Monthly and growing season precipitation 2007-2010. ............................... 33 
Table 3-1     Soil pH and P, K, Mg and Ca content for giant reed, switchgrass, mimosa 
and adjacent bahiagrass in 2009. .................................................................. 63 
Table 3-2     Yield and N content of leaf material shed by mimosa during the growing 
season in 2009, 2010 and 2011. .................................................................... 64 
Table 4-1     Monthly and growing season precipitation 2007-2010. ............................... 81 
Table 4-2     Cost of N per additional Mg of biomass by year and level of N fertilization.
 ...................................................................................................................... 82 
Table 5-1     Monthly and growing season precipitation 2007-2010. ............................... 95 
Table 5-2     Regression equations, pseudo R2, and maximum economic yield (MEY) of 
Alamo switchgrass for nitrogen treatments. ................................................. 96 
Table 5-3     Cost of N per additional Mg of biomass by year and level of N fertilization.
 ...................................................................................................................... 97 
Table 6-1     Monthly and summer growing season precipitation 1998-2011. ............... 115 
Table 6-2     Soil analyses by treatment. ......................................................................... 116 
Table 7-1     Monthly and growing season (March to October) precipitation 2009-2011
 .................................................................................................................... 132 
Table 7-2     Biomass yield of giant reed at different harvest times in the 2010 and 2011 
growing seasons. ......................................................................................... 133 
 
 
xi 
 
 
 
 
 
 
 
 
LIST OF FIGURES 
 
 
Figure 1-1   Average daily air and soil temperatures from November 2007 to October 
2010. ............................................................................................................. 13 
Figure 1-2   Monthly chill hours in winter seasons between 2007 and 2010. .................. 14 
Figure 1-3   Average daily solar radiation in each month of winter seasons between 2007 
and2010. ....................................................................................................... 15 
Figure 1-4   Monthly minimum air temperature in winter seasons between 2007 and 
2010. ............................................................................................................. 16 
Figure 1-5   Biomass yields of the three winter annuals within each winter growing 
season. .......................................................................................................... 17 
Figure 1-6   Biomass yields of each winter annual crop across the three winter growing 
seasons. ......................................................................................................... 18 
Figure 2-1   Monthly chill hours in winter seasons between 2007 and 2010. .................. 34 
Figure 2-2   Average daily solar radiation in each month of the winter seasons between 
2007 and 2010. ............................................................................................. 35 
Figure 2-3   Monthly minimum air temperature in winter seasons between 2007 and 
2010. ............................................................................................................. 36 
Figure 2-4   Biomass yield for conventional tillage and no-till management for black oat, 
rye and ryegrass across winter seasons. ...................................................... 37 
Figure 2-5   Biomass yield for black oat, rye and ryegrass across winter seasons and 
tillage method. .............................................................................................. 38 
Figure 2-6   Biomass yield for black oat, rye and ryegrass over time and across tillage 
method. ......................................................................................................... 39 
Figure 2-7   Biomass yield for pearl millet, forage sorghum and sorghum-sudangrass over 
time and across tillage method. .................................................................... 40 
Figure 2-8   Effect of tillage method on biomass yields of pearl millet (PM), forage 
sorghum (S) and sorghum-sudangrass (SS) over time. ................................ 41 
 
xii 
 
 
Figure 2-9   Biomass yield of pearl millet, forage sorghum and sorghum-sudangrass as 
influenced by year and tillage method. ......................................................... 42 
Figure 2-10 Biomass yield of pearl millet, forage sorghum and sorghum-sudangrass as 
influenced by tillage method and winter crops (black oat (BO), rye (R), and 
ryegrass (RG)). ............................................................................................. 43 
Figure 2-11 Effect of winter crop on biomass yield for pearl millet (PM), forage sorghum 
(S) and sorghum-sudangrass (SS) under different tillage methods. ............. 44 
Figure 2-12 Effect of tillage method and winter crop on biomass yields of pearl millet 
(PM), forage sorghum (S) and sorghum-sudangrass (SS). ........................... 45 
Figure 2-13 Total annual biomass yield among different double-cropping systems (black 
oat+pearl millet (BOPM), black oat+forage sorghum (BOS), black 
oat+sorghum-sudangrass (BOSS), rye+pearl millet (RPM), rye+forage 
sorghum (RS), rye+sorghum-sudangrass (RSS), ryegrass+pearl millet 
(RGPM), ryegrass+forage sorghum (RGS), ryegrass+sorghum-sudangrass 
(RGSS))  across years. .................................................................................. 46 
Figure 2-14 Total annual biomass yield  for the nine double-cropping systems (black 
oat+pearl millet (BOPM), black oat+forage sorghum (BOS), black 
oat+sorghum-sudangrass (BOSS), rye+pearl millet (RPM), rye+forage 
sorghum (RS), rye+sorghum-sudangrass (RSS), ryegrass+pearl millet 
(RGPM), ryegrass+forage sorghum (RGS), ryegrass+sorghum-sudangrass 
(RGSS))  over time and across tillage methods. ........................................... 47 
Figure 2-15 Total annual biomass yield for the nine double-cropping systems (black 
oat+pearl millet (BOPM), black oat+forage sorghum (BOS), black 
oat+sorghum-sudangrass (BOSS), rye+pearl millet (RPM), rye+forage 
sorghum (RS), rye+sorghum-sudangrass (RSS), ryegrass+pearl millet 
(RGPM), ryegrass+forage sorghum (RGS), ryegrass+sorghum-sudangrass 
(RGSS))  across years and tillage methods. ................................................. 48 
Figure 3-1   Growing season (March to October) precipitation from 1989 to 2011 ......... 65 
Figure 3-2   Annual biomass yield of mimosa from the eighth year to 2011, giant reed and 
switchgrass from the third year to 2011, with the long term mean value 
indicated as a horizontal line. ....................................................................... 66 
Figure 3-3   Effect of stand age (x) on yield (y) of switchgrass (a), giant reed (b) and 
mimosa (c). ................................................................................................... 67 
Figure 3-4   Effect of growing season rainfall (x) on biomass yield (y) of switchgrass (a), 
giant reed (b) and mimosa (c). ...................................................................... 68 
 
xiii 
 
 
Figure 3-5   Effect of growing season rainfall (x) on grain yield (y) of yellow corn (a) and 
cotton lint yield (y) (b) grown in central Alabama during the 2000-
2011period. ................................................................................................... 69 
Figure 3-6   Relationship between rainfall (March to September) (x) and grain yield (y) of 
soybean cultivars in maturity group IV (a), V (b), and VI (c) grown in 
central Alabama during the 2000-2011 period. ............................................ 70 
Figure 4-1   Biomass yield of Alamo switchgrass under different N rates across years. . 83 
Figure 4-2   Biomass yield of Alamo switchgrass under the same nitrogen fertilizer 
treatment over time. ...................................................................................... 84 
Figure 5-1   Aboveground dry matter yield of Alamo switchgrass under different nitrogen 
fertilization rates by year. ............................................................................. 98 
Figure 5-2   Biomass yield of Alamo switchgrass over time by N rate. ........................... 99 
Figure 5-3   Effect of fertilizer N rate on aboveground biomass yield of Alamo 
switchgrass in 2011. ................................................................................... 100 
Figure 5-4   Biomass yield of Alamo switchgrass in 2010 and 2011 with no N fertilization 
and with or without interseeded crimson clover. ........................................ 101 
Figure 6-1   Monthly minimum and maximum temperatures from November 1998 to 
October 2011. ............................................................................................. 117 
Figure 6-2   Annual biomass yield of giant reed with or without application of broiler 
litter by year. ............................................................................................... 118 
Figure 6-3   Annual biomass yield of giant reed under different harvesting regimes by 
year. ............................................................................................................ 119 
Figure 6-4   Annual biomass yield of giant reed over time and harvest treatment. ........ 120 
Figure 6-5   Biomass yield of giant reed rhizomes under different harvesting regimes in 
2009. ........................................................................................................... 121 
Figure 7-1   Monthly maximum and minimum air temperatures from November 2009 to 
October 2011. ............................................................................................. 134 
Figure 7-2   Change in plant height of giant reed with time. .......................................... 135 
Figure 7-3   Changes in plant height and growth rate of giant reed with time. .............. 136 
Figure 7-4   Change in biomass yield of giant reed with time. ....................................... 137 
Figure 7-5   Changes in biomass yield and growth rate of giant reed with time. ........... 138 
 
xiv 
 
 
 
 
 
 
 
 
LIST OF PLATES 
 
 
Plate 3-1     Mimosa leaf residue collection at the end of the 2009 growing season. ....... 71 
Plate 4-1     Switchgrass with subsoiling (a) and without subsoiling (b) in June 2011. ... 85 
Plate 4-2     Switchgrass 10 days after applying N treatments in June 2011. ................... 86 
Plate 5-1     Switchgrass 10 days after applying N treatments in June 2011. ................. 102 
Plate 5-2     Switchgrass with and without interseeding crimson clover in April 2011. . 103 
Plate 6-1     Giant reed in spring 2012. ........................................................................... 122 
Plate 7-1     Giant reed on October 8th, 2010 (a) and November 18th, 2010 (b). ............. 139 
 
 
 
 
 
1 
 
 
 
 
CHAPTER 1    EVALUATION OF WINTER ANNUALS FOR BIOMASS 
PRODUCTION IN ROTATION WITH TRADITIONAL SUMMER ROW CROPS   
 
ABSTRACT 
Encouraging progress in commercial production of cellulosic biofuels, together 
with a need to avoid disruption of current food, feed and fiber supplies, could rapidly lead 
to a shortage of land to produce biomass. However, millions of acres used for production 
of traditional summer row crops in the Southeast are idle during the winter, and could be 
used to produce biomass from winter annuals. This 3-yr small plot study evaluated three 
winter annuals (black oat (Avena strigosa Schreb.), rye (Secale cereale L. subsp. cereale) 
and annual ryegrass (Lolium multiflorum Lam.)) for biomass production, in rotation with 
three summer row crops (cotton (Gossypium hirsutum L.), peanuts (Arachis hypogaea L.) 
and soybeans (Glycine max (L.) Merr.)) that are widely grown in the Southeast. All plots 
were disked and fertilized during the summer, according to standard recommendations by 
the Alabama Cooperative Extension Service. Rye provided higher (P<0.10) biomass 
yield over the three years (9.0, 5.9 and 4.6 Mg/ha in 2007-08, 2008-09 and 2009-10 
winter seasons, respectively) than black oat and ryegrass. The variation in biomass yields 
over time was related to low temperature and solar radiation. Yields of the three summer 
crops were higher following rye, relative to yields following black oat and ryegrass in 
2008 and 2010. In 2009, this trend was not observed, possibly because of the very high 
rainfall during the summer growing season. It is concluded that, compared to black oat 
 
2 
 
 
and ryegrass, rye was the most suitable winter crop for biomass production in rotation 
with the three summer crops evaluated in this study.  
 
Keywords: winter annuals; cellulosic biomass production; crop rotation; summer row 
crops; cellulosic energy crops 
 
1.1 INTRODUCTION 
First generation bioenergy feedstocks include food crops such as sugarcane, corn 
and soybeans, which are high in sugar, starch and/or oil content, and can be converted 
into liquid biofuels using existing technology. Two well-known processes in commercial 
production of first-generation biofuels are sugarcane-to-ethanol in Brazil and corn-to-
ethanol in the US. Unlike first-generation bioenergy feedstocks, next-generation 
bioenergy feedstocks, (i.e., ligno-cellulosic biomass) are derived from non-food sources, 
including wood, tall grasses, and forestry and crop residues, which are harvested for their 
cellulosic biomass and can only be converted into liquid biofuels by more complex 
conversion technologies that are still under development. Advances in recent years have 
indicated that numerous technologies which can use a variety of cellulosic biomass 
feedstocks to produce various liquid biofuels, including cellulosic ethanol, green 
gasoline, diesel and jet fuel, are currently under development (Kunkes et al., 2008; 
Regalbuto, 2009). Commercial production of cellulosic drop-in replacement biofuels at a 
cost that is competitive with fossil fuels could occur within the next five years (Solecki et 
al., 2012), thus increasing the need to develop economically viable and environmentally 
sustainable cellulosic biomass supply chains.  
 
3 
 
 
The Energy Independence and Security Act of 2007 (EISA) mandated that 16 
billion gallons of biofuel be produced from cellulosic biomass and used in the US by 
2022. At a conversion ratio of 90 gallons per dry ton of cellulosic biomass, this means 
that 180 million dry tons of cellulosic material will have to be available annually by 2022 
(USDA, 2009). Together with a need to avoid disruption of current food, feed and fiber 
supplies, this could rapidly lead to a shortage of land to produce cellulosic biomass. 
Meeting the ambitious targets that have been set by EISA is a major challenge. Some 
have suggested establishing low-input prairie on degraded agricultural lands for cellulosic 
biomass production (Tilman et al., 2006), but others argue that this approach is 
inadequate to meet target production (Russelle et al., 2007). With this background of 
considerable controversy, it is evident that a wide variety of approaches is needed to meet 
the cellulosic biofuel goals of EISA, and also minimize any negative impacts on existing 
commodities.  
One possible approach may be to include cellulosic biomass production in 
existing summer row crop systems that are currently fallow in winter: millions of acres 
are currently used for production of traditional summer row crops in the Southeast, but 
are idle during the winter and could be used to produce biomass from winter annuals. 
Winter crops in a double cropping system are commonly planted as unharvested cover 
crops to improve soil and water conditions for subsequent summer crops. The benefits of 
planting winter cover crops include preventing soil erosion and enhancing soil organic 
matter (SOM) , thus improving soil quality and productivity (Calonego and Rosolem, 
2010). For example, over-seeding rye into standing corn increased corn yield (Schroder et 
al., 1996; Kuo et al., 2000; Coelho et al., 2005). Cereal rye, annual ryegrass and oats are 
 
4 
 
 
common winter cover crop species, and are well adapted to cool conditions that prevail in 
the fall-winter-spring season in the southeastern U.S. However, little is known about 
using winter annuals for biomass production in rotation with traditional summer row 
crops. Therefore, the objective of this study was to evaluate three common winter annuals 
(black oat, rye and ryegrass) for biomass production, in rotation with three summer row 
crops (cotton, peanuts and soybean) that are widely grown in the Southeast.  
 
1.2 MATERIALS AND METHODS 
1.2.1 Treatments and experimental design 
This experiment was initiated in the winter of 2007 and conducted for 3 years at 
the E.V. Smith Research Center, Plant Breeding Unit of the Alabama Agricultural 
Experiment Station near Tallassee, Alabama on a Wickham sandy loam (fine-loam, 
mixed, semiactive, thermic Typic Hapludult). The field had been planted with white lupin 
(Lupinus albus L.) in the previous season. The experiment was laid out as a two-factor 
factorial randomized complete block (RCB) design with four replicates. Nine different 
double cropping systems evaluated in this study included all combinations of three winter 
annuals and three summer crops: specifically rye, black oat or ryegrass in winter, 
followed by cotton, peanuts or soybeans in summer. Plot size was 3.6? 9.0m. 
 
1.2.2 Crop rotation 
Tillage operations, fertilizer application and planting were conducted within one 
day in early November for all winter seasons. Plots were disked to a depth of 10-15 cm 
and chisel plowed to a depth of 15 cm, followed by leveling, then fertilization with 
 
5 
 
 
ammonium nitrate at a rate of 112 kg N ha-1. After applying fertilizer, black oat, rye and 
annual ryegrass were seeded using a grain drill set at a row spacing of 17.8 cm.  
For the summer season, tillage operations and planting were also conducted 
within one day in mid-May for all three summer crops. After removing biomass of winter 
annuals, plots were disked, chisel plowed and leveled as described above for winter 
season crops, then planted with cotton, peanuts and soybean using a planter set at a row 
spacing of 91.4 cm. Given that peanuts and soybean are legumes, N fertilizer was only 
applied to cotton plots in the form of ammonium nitrate at a rate of 67 kg N ha-1. In 
addition, P and K were applied based on soil test results.  
All plots were cultivated, and herbicide and pesticide treatments were applied 
when necessary over the three years. Glyphosate (Roundup) herbicide was applied to all 
plots 12 days before planting summer row crops, aldicarb (Temik) pesticide was applied 
to cotton and peanut plots and pentachloronitrobenzene (Terraclor) fungicide was applied 
to all plots at planting. To control leaf spot and white mold diseases, chlorothalonil 
(Echo/ Equus) fungicides were applied to peanuts six times at two week intervals starting 
about 35 to 45 days after planting in each summer season.  
 
1.2.3 Data collection 
At the end of each growing season, the center six rows of each winter annual plot 
were cut to a 5-cm stubble height with a sickle bar mower. Fresh biomass weight of 
harvested material from each plot was measured using a hanging scale in the field. 
Biomass subsamples taken from each plot were dried at 60?C for 72 h for dry matter 
determination. At maturity, cotton defoliants including S,S,S-Tributyl 
 
6 
 
 
phosphorotrithioate (Def-6), ethephon (BollBuster) and Thidiazuron (Takedown) were 
used for the removal of leaves from cotton plants. Seed cotton was then picked in the 
central two rows of each cotton plot, using a John Deere 9920 (John Deere, Dumas, 
Arkansas) two row spindle cotton picker. Cotton lint yield was estimated by assuming a 
39% ginning efficiency. Peanuts and soybeans were harvested from the central two rows 
of each plot with a peanut combine and soybean plot combine, respectively. Grain 
moisture was measured at harvest using a moisture meter and reported grain yields were 
adjusted accordingly. After harvesting border rows, cotton, peanut and soybean plots 
were mowed and prepared for planting winter annuals. 
 
1.2.4 Data analysis 
Statistical analysis of yield data from both summer and winter seasons were 
conducted using SAS v9.2 PROC GLIMMIX. Block was considered a random factor, 
whereas year, summer and winter crop factors and their interactions were tested as fixed 
effects. The critical P-value of 0.10 was used as cutoff for testing these fixed effects, and 
determination of differences in least-squares means was based on adjusted P-value 
obtained by using the option ADJUST=SIMULATE in the LSMEANS statement. 
Biomass yield data from the 2008-09 and 2009-10 winter seasons were first 
analyzed to determine the yield performance of the three winter annuals as affected by 
the different summer row crops. Since there was no difference in biomass yields of the 
three winter annuals under different summer row crop systems in the 2008 and 2009 
winter seasons, all winter biomass yield data were pooled to determine the yield of the 
 
7 
 
 
three winter annuals over the three years. For each summer crop species, yield data from 
the three years were also pooled for analysis.  
 
1.3 RESULTS AND DISCUSSIONS 
1.3.1 Weather conditions 
Daily temperature and monthly precipitation patterns are presented in Figure 1-1 
and Table 1-1, respectively. Rainfall was close to long term averages in the 2007, 2008 
and 2010 growing seasons, but very high in 2009. The summer (May to October) and 
winter (November to April) growing season rainfall for 2009 was 941 and 814 mm, 
respectively, which is 324 and 48 mm higher than the average rainfall received during the 
past 10 years. The cumulative chill hours (temperatures below 7.2 ?) in the winter 
season of 2009 was higher than that in winter seasons of 2007 and 2008 (1211, 1171 and 
1576 hours in 2007-08, 2008-09 and 2009-10 winter seasons, respectively) (Figure 1-2) 
probably because of lower cumulative solar radiation (Figure 1-3). However, monthly 
minimum temperatures were very similar in winter seasons of 2007 and 2009 (Figure 1-
4).   
 
1.3.2 Winter biomass yield 
Biomass yield of winter annuals was not affected by summer row crops, but was 
higher for rye than for annual ryegrass and black oat for which yield did not differ 
(Figure 1-5). A year ? crop species interaction was observed, with yield of rye decreasing 
relatively less with lower temperatures and less sunlight than that of black oat and annual 
ryegrass (Figures 1-2, 1-3, 1-4 and 1-6). In particular, biomass yields for rye, black oat 
 
8 
 
 
and ryegrass in the 2009-10 winter season decreased by 16.9%, 68.1% and 67.9%, 
respectively, when compared to yields in the 2008-09 season (Figure 1-6). This suggests 
that rye is more cold tolerant than the other two winter annuals, which is consistent with 
the observations of others (Stichler, 1997; Lemus, 2008). 
 
1.3.3 Summer row crop yield 
 A winter crop ? year interaction was observed for summer row crop yields. All 
three summer crop yields were highest after rye, followed by yields after black oat and 
ryegrass in 2008 and 2010 (Table 1-2). Based on studies by Barnes and Putnam (1986), 
Bauer and Reeves (1999), and Price et al., (2008), this result could be due to differences 
among these winter crops in allelopathic effects.  In 2009, differences in yield of summer 
crops following the three winter crops were not observed, possibly because of the very 
high rainfall during the summer growing season which could have reduced allelopathy, as 
observed by Eerens et al. (1998). 
 
1.4 CONCLUSION 
Due to rye providing the highest biomass yield and having the lowest negative 
impact on summer row crop yield, rye appears to be better for winter biomass production 
than black oat and annual ryegrass when grown in rotation with cotton, peanuts or 
soybeans in the southeastern US.  
 
1.5 REFERENCES 
Barnes, J.P., A. R. Putnam. 1986. Evidence for allelopathy by residues and aqueous 
extracts of rye (Secale cereale). Weed Science 34: 384-390.  
 
9 
 
 
   
Bauer, P.J., Reeves, D.W. 1999. A comparison of winter cereal species and planting dates 
as residue cover for cotton growth with conservation tillage. Crop Science 39: 
1824-1830.  
 
Calonego, J.C., C.A. Rosolem. 2010.  Soybean root growth and yield in rotation with 
cover crops under chiseling and no-till. Europ. J. Agronomy 33: 242-249.  
 
Coelho, B., R. Roy and A. Bruin. 2005. Long-term effects of late-summer overseeding of 
winter rye on corn grain yield and nitrogen balance. Can. J. Plant Sci. 85 (3): 543-
554. 
 
Eerens, J.P.J., R.J. Lucas, H.S. Easton, J.G.H. White. 1998. Influence of the ryegrass 
endophyte (Neotyphodium lolii) in a cool moist environment. 1. Pasture production. 
New Zealand Journal of Agricultural Research 41: 39-48.  
 
Kunkes, E. L., D.A. Simonetti, R.M. West, J.C. Serrano-Ruiz, C.A. Gartner, and J.A. 
Dumesic. 2008. Catalytic conversion of biomass to monofunctional hydrocarbons 
and targeted liquid-fuel classes. Science 332: 417-421. 
 
Kuo, S., U.M. Sainju, and  E. Jellum. 1996. Winter cover cropping influence on nitrogen 
mineralization, presidedress soil nitrate test, and corn yields. Biol. Fertil. Soils 22: 
310-317. 
 
Lemus, R. 2008. Cool-season forages establishment and Maintenance. Extension service 
of Mississipi State University. 
http://msucares.com/crops/forages/newsletters/08/10.pdf 
 
Price, A.J., M.E. Stoll, J.S. Bergtold, F.J. Arriaga, K.S. Balkcom, T.S. Kornecki, R.L. 
Raper. 2008. Effect of cover crop extracts on cotton and radish radicle elongation. 
Communications in Biometry and Crop Science 3 (1): 60-66. 
 
Regalbuto, J. R. 2009. Cellulosic biofuels-got gasoline? Science 325: 822-824.  
 
Russelle, M., R. Morey., J. Baker., P. Porter., H. Jung. 2007 Comment on ?Carbon-
negative biofuels from low-input high-diversity grassland biomass?. Science 316: 
5831. 
 
Schroder, J.J., W. Vandijk, and W.J.M. Degroot. 1996. Effects of cover crops on the 
nitrogen fluxes in a silage maize production system. Neth. J. Agric. Sci. 44: 293-
315. 
 
Solecki, M., A. Dougherty, and B. Epstein. 2012. E2 Report: Advanced Biofuel Market 
Report 2012. www.e2.org/ext/doc/E2AdvancedBiofuelMarketRrport2012.pdf. 
 
 
10 
 
 
Stichler, C. 1997. Managing of annual winter forages in Southwest Texas. Extension 
Service of Texas A&M University. 
http://baylor.agrilife.org/files/2011/06/managingannualwinterforagesswtexas_14.pdf 
 
The Energy Independence and Security Act of 2007 (EISA). 
http://frwebgate.access.gpo.gov/cgi-
bin/getdoc.cgi?dbname=110_cong_bills&docid=f:h6enr.txt.pdf 
 
Tilman, D., J. Hill, and C. Lehman. 2006. Carbon-negative biofuels from low-input high-
diversity grassland biomass. Science 314 (5805): 1598-1600.
 
11 
 
 
 
 
 
 
 
 
Table 1-1 Monthly and growing season precipitation 2007-2010. 
 
Year 
Precipitation (mm)   
Month Winter  growing 
season 
Summer  
growing 
season Jan. Feb. Mar. Apr. May Jun. Jul. Aug. Sept. Oct. Nov. Dec. 
2007           55 94 540  
2008 111 102 77 101 64 50 126 252 19 83 93 82 685 594 
2009 52 105 244 109 262 100 75 192 148 164 154 276 814 941 
2010 152 76 124 32 176 56 128 122 46 31       560 
Average  
(1997-2006) 107 127 181 129 92 141 118 97 104 65 123 104 766 617 
 
12 
 
 
 
 
 
 
 
 
 
 
Table 1-2 Yields of summer row crops in 2008-2010. 
 
Year Winter crop Yield of summer row crop (kg ha
-1) 
Cotton lint Peanut grain Soybean grain 
2008 
Ryegrass 893?79a 3746?222b 2080?153c 
Black oat 951?79a 3864?222b 2757?210b 
Rye 1001?144a 4905?222a 3244?66a 
2009 
Ryegrass 57?25a 2300?49a 1654?295a 
Black oat 68?25a 1894?222b 1816?210a 
Rye 60?25a 2582?427a 1051?210b 
2010 
Ryegrass 286?25b 214?49b 1221?210b 
Black oat 360?79ab 221?49b 1675?210ab 
Rye 534?79a 343?49a 1960?295a 
 
Means within each column and in the same year with different superscripts differ 
(P<0.10). 
 
 
 
 
 
 
 
 
 
 
13 
 
 
 
 
 
 
  
Figure 1-1 Average daily air and soil temperatures from November 2007 to October 2010.  
 
 
-10
0
10
20
30
40
Nov De
c
Jan Feb Mar Apr May Jun Jul Aug Se
p
Oc
t
Nov De
c Jan
Fe
b
Ma
r
Apr May Jun Jul Aug Se
p
Oc
t
Nov De
c Jan
Fe
b
Mar Apr May Jun Jul Aug Sep Oc
t
2007 2008 2009 2010
Air temperature at 1.5m
Soil temperature at 10 cm
Te
mpe
rature
 (?
) 
 
14 
 
 
 
 
 
 
 
 
  
 
Figure 1-2 Monthly chill hours in winter seasons between 2007 and 2010. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
0
100
200
300
400
500
600
Nov. Dec. Jan. Feb. Mar. Apr.
2007-2008 2008-2009
2009-2010 Average 1997-2006
Mont
hly
 chil
l hours 
 
Month 
 
15 
 
 
 
 
 
 
 
 
 
 
  
Figure 1-3 Average daily solar radiation in each month of winter seasons between 2007 
and 2010. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
0
2
4
6
8
Nov. Dec. Jan. Feb. Mar. Apr.
2007-2008 2008-2009
2009-2010 Average 1997-2006
Ave
rag
e da
ily
 solar
 ra
diation 
 
(kW
/m
2 )
 
Month 
 
16 
 
 
 
 
 
 
 
 
  
Figure 1-4 Monthly minimum air temperature in winter seasons between 2007 and 2010.  
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
-12
-9
-6
-3
0
3
6
Nov. Dec. Jan. Feb. Mar. Apr.
2007-2008
2008-2009
2009-2010
Average 1997-2006
Monthly
 minimum
 te
mpe
ratur
e 
(?
) 
Month 
 
17 
 
 
 
 
 
 
 
 
 
 
  
Figure 1-5 Biomass yields of the three winter annuals within each winter growing season.  
 
Means within each year with different letters differ (P<0.10). 
 
 
 
 
 
 
 
 
 
 
 
 
 
a 
a 
a 
b 
b 
b 
b 
b 
b 
0
2
4
6
8
10
12
2007-08 2008-09 2009-10
Rye
Black oat
Ryegrass
Winter season 
Above
ground
 biom
ass  y
ield 
 
(Mg
/ha)
 
 
18 
 
 
 
 
 
 
 
 
 
  
Figure 1-6 Biomass yields of each winter annual crop across the three winter growing 
seasons. 
 
Means within each winter annual crop with different letters differ (P<0.10). 
 
 
 
 
 
 
 
 
 
 
 
 
a 
a 
a 
b 
b b 
b 
c c 
0
2
4
6
8
10
12
Rye Black oat Ryegrass
2007-08 winter season
2008-09 winter season
2009-10 winter season
Winter annual crop 
Above
ground
 biom
ass  y
ield 
 
(Mg
/ha
) 
Above
ground
 biom
ass  y
ield 
 
(Mg
/ha
) 
 
19 
 
 
 
 
CHAPTER 2    EVALUATION OF WINTER ANNUALS IN ROTATION WITH 
TRADITIONAL SUMMER FORAGE CROPS FOR YEAR-ROUND BIOMASS 
PRODUCTION IN ALABAMA   
 
ABSTRACT 
Compared to annuals, dedicated perennial energy crops are currently receiving 
more attention for cellulosic biomass production, partly because they avoid annual seed 
and planting costs, and appear to be affected less by low rainfall. However, perennial 
crops are often difficult to establish and slow to reach maximum yield, and are typically 
warm-season species which grow rapidly for only a few months in the year. Warm-
season and/or cool-season annuals could alleviate these limitations. Therefore, the 
objective of this 3-yr small plot study was to evaluate three common winter annuals 
(black oat (Avena strigosa Schreb.), rye (Secale cereale L. subsp. cereale) and annual 
ryegrass (Lolium multiflorum Lam.)) in rotation with three summer forage crops (forage 
sorghum (Sorghum bicolor spp.), pearl millet (Pennisetum americanum (L.) R. Br.) and 
sorghum-sudangrass (Sorghum bicolor (L.) Moench nothosubsp. drummondii (Steud.) de 
Wet ex Davidse)) for year-round biomass production under conventional-till and no-till 
management in central Alabama.  
Biomass yield of all winter annuals was higher under conventional tillage than 
under no-till management, and ryegrass provided higher biomass yield than black oat and 
rye. Similarly, compared to no-till treatment, conventional tillage produced much higher 
 
20 
 
 
biomass yield for all three summer crops in the third summer season, although 
conventional tillage did not result in greater production versus no-till for biomass 
production of the three summer forage crops in the first two summer seasons. Yield 
differences among summer crops as affected by different winter crops were relatively low 
under both tillage treatments except for sorghum-sudangrass under no-till, in which case 
yield was higher following rye than after black oat and ryegrass. Except for the second 
year of the study when biomass yields of sorghum-sudangrass and pearl millet did not 
differ, forage sorghum and sorghum-sudangrass provided higher biomass yield than pearl 
millet under both tillage treatments. For total annual biomass production, double-
cropping systems with forage sorghum or sorghum-sudangrass under conventional tillage 
generally provided higher biomass yield than other double-cropping systems under both 
tillage treatments, although a yield advantage for double-cropping systems with pearl 
millet or forage sorghum was observed under no-till management in the first year.  
 It is concluded that forage sorghum and sorghum-sudangrass under conventional 
tillage would be suitable for biomass production in a long term system.  
 
Keywords: cellulosic biomass production; crop rotation; winter annuals; summer forage 
crops 
 
2.1 INTRODUCTION 
 Unlike first-generation bioenergy feedstocks,  next-generation bioenergy 
feedstocks, (i.e., ligno-cellulosic biomass) are derived from non-food sources, including 
wood, tall grasses, and forestry and crop residues, which are harvested for their cellulosic 
 
21 
 
 
biomass and can only be converted into liquid biofuels by complex conversion 
technologies (Worldwatch Institute, 2007). Advances in recent years have indicated that 
numerous technologies which can use a wide range of cellulosic biomass feedstocks to 
produce various liquid biofuels, including cellulosic ethanol, green gasoline, diesel and 
jet fuel are currently under development (Kunkes et al., 2008; Regalbuto, 2009.). 
Commercial production of cellulosic drop-in replacement biofuels at a cost that is 
competitive with fossil fuels could occur within the next five years (Solecki et al., 2012). 
This progress towards  development of commercially viable conversion technologies, 
together with the Energy Independence and Security Act of 2007 (EISA), which 
mandated that 16 billion gallons of  biofuel  be produced from cellulosic biomass and 
used in the US by 2022, increases the need to develop economically viable and 
ecologically sustainable cellulosic biomass supply systems.  
Compared to annuals, dedicated perennial energy crops are currently receiving 
more attention for cellulosic biomass production, partly because they avoid annual seed 
and planting costs, and appear to be affected less by low rainfall. However, perennial 
crops are often difficult to establish and slow to reach maximum yield, and are typically 
warm-season species which grow rapidly for only a few months in the year. For example, 
to mitigate slow establishment and the related economic loss, a given area of land could 
be planted to annual biomass crops and replaced with a perennial by planting the 
perennial on just part of the area each year over a period of several years. In addition, 
under certain circumstances winter and summer annual biomass rotations may provide 
higher and more profitable yields than some perennials. Forage sorghum, sorghum-
sudangrass and pearl millet are forage crops that are commonly grown in the Southeast. 
 
22 
 
 
In addition, winter annuals such as cereal rye, annual ryegrass and oats are commonly 
planted in the region as unharvested or grazed cover crops to improve soil and water 
conditions for subsequent summer crops. Benefits of planting winter cover crops include 
preventing soil erosion and enhancing soil organic matter (SOM) thereby improving soil 
quality and productivity (Calonego and Rosolem, 2010). For example, studies showed 
that over-seeding rye into standing corn increased corn yield (Schroder et al., 1996; Kuo 
et al., 2000; Coelho et al., 2005). However, little is known about use of winter annuals in 
rotation with summer forage crops under conventional tillage or no-till management for 
year-round biomass production. Therefore, the objective of this study was to evaluate 
three common winter annuals (black oat, rye and ryegrass) in rotation with three summer 
forage crops (forage sorghum, sorghum-sudangrass and pearl millet) for year-round 
biomass feedstocks production under conventional tillage or no-till management in 
central Alabama.  
 
2.2 MATERIALS AND METHODS 
2.2.1 Treatments and experimental design 
This experiment was initiated in the winter of 2007 and conducted for 3 years at 
the E.V. Smith Research Center, Plant Breeding Unit of the Alabama Agricultural 
Experiment Station near Tallassee, Alabama on a Wickham soil (fine-loam, mixed, 
thermic Typic Hapludult). The field had been planted with wheat using conventional 
tillage in the 2006-07 winter season, and fallowed in the summer of 2007. The 
experiment was laid out in a split-plot design with four replications. Conventional tillage 
and no-till management were assigned to whole plots, and cropping systems were 
 
23 
 
 
assigned to sub-plots. The nine cropping systems that were evaluated included all 
combinations of rye, black oat or ryegrass in winter, followed by forage sorghum, 
sorghum-sudangrass or pearl millet in summer. Size of sub-plots was 3.6 ? 9.0m.   
 
2.2.2 Crop rotation 
Tillage operations, fertilizer application and planting were conducted within one 
day for all winter and summer seasons. Whole plots for conventional tillage treatment 
were disked to a depth of 10-15 cm, and chisel plowed to a depth of 15 cm. Seeds of 
winter and summer annuals were drilled to designated plots using a planter set at a row 
spacing of 17.8 cm. Four days after planting winter annuals, all plots were fertilized with 
112 kg N ha-1, 45 kg P ha-1 and 45 kg K ha-1 in all three winter seasons. For summer 
seasons, all plots were fertilized with 112 kg N ha-1.  Table 2-1 provides more details on 
cultivars, seeding rate, and planting and harvesting times.  
All plots were cultivated when necessary over the three years and glyphosate 
(Roundup) herbicide was applied to all plots 12 days before planting summer forage 
crops. 
 
2.2.3 Data collection 
At the end of each growing season, the central six rows of each winter and 
summer crop plot were cut to a 5-cm stubble height with a sickle bar mower. Fresh 
biomass weight of the harvested area in each plot was measured using a hanging scale in 
the field. Biomass subsamples taken from each plot were dried at 60?C for 72 h for dry 
 
24 
 
 
matter determination. After sampling central rows, border rows were cut off and removed 
from the plots.  
 
2.2.4 Data analysis 
Statistical analysis of biomass yield data from both summer and winter seasons 
was conducted using SAS v9.2 PROC GLIMMIX. Block was considered as a random 
factor, whereas tillage, year, and summer and winter crops and their interaction terms 
were tested as fixed effects. The critical P-value of 0.10 was used as cutoff for testing these 
fixed effects, and determination of differences in least-squares means was based on 
adjusted P-value obtained by using the option ADJUST=SIMULATE in the LSMEANS 
statement. 
  
2.3 RESULTS AND DISCUSSIONS 
2.3.1 Weather conditions 
Rainfall was close to long-term averages in the 2007, 2008 and 2010 growing 
seasons, but very high in 2009 (Table 2-2). The summer (May to October) and winter 
(November to April) growing season rainfall of 2009 were 941 and 814 mm, which are 
324 and 48 mm higher than the average of past 10 years, respectively. The accumulative 
chill hours (temperatures below 7.2?) in winter season of 2009 were higher than in 
winter seasons of 2007 and 2008 (1211, 1171 and 1576 hours in 2007-08, 2008-09 and 
2009-10 winter seasons, respectively) (Figure 2-1) probably because the accumulative 
solar radiation in this winter season was also lower (Figure 2-2). However, monthly 
 
25 
 
 
minimum temperatures were very similar in winter seasons of 2007 and 2009 (Figure 2-
3).     
 
2.3.2 Winter biomass yield 
Analysis of data from the second and third years of the study indicated that 
summer crops did not affect biomass yields of winter crops. Therefore, biomass yield 
data from all three years were pooled for further analysis, and this revealed a three-way 
interaction between year, tillage method and winter crop (Figures 2-4, 2-5 and 2-6) 
(P<0.01). When compared to no-till management, under conventional tillage yield was 
higher for black oat in the first and second years of the study compared to the third year, 
and for ryegrass it was higher in the second and third years compared to the first year 
(Figure 2-4). Within each tillage treatment, yield difference among the three winter 
annuals was relatively small in both the 2007-08 and 2008-09 winter seasons, but 
ryegrass provided higher biomass yield than black oat and rye under conventional tillage 
and higher yield than rye under no-till management in the 2009-10 winter season (Figure 
2-5). In addition, within each tillage treatment yields for all three winter annuals were 
high in the 2007-08 and 2008-09 winter seasons, but decreased substantially in the 2009-
10 winter season (Figure 2-6). This variation in biomass yield over time corresponded 
with the variation in average daily solar radiation, and cumulative chill hours (Figures 2-
1, 2-2 and 2-3), and was lowest for ryegrass, followed by black oat and rye. This result is 
not consistent with that from another study conducted at the same location over the same 
period which may be due to differences between the sites of the two experiments. In 
particular, the site of this experiment was subject to periodic waterlogging whereas the 
 
26 
 
 
other site was not, and it is possible that there is a difference in tolerance to waterlogging 
among the winter crops that were included in both studies. 
 
2.3.3 Summer biomass yield 
Analysis of biomass yield from summer crops indicated a year ? tillage ? summer 
crop interaction, and a tillage ? winter crop ? summer crop interaction (P<0.01).  
 
2.3.3.1 Interaction of year, tillage and summer crop 
Yield variation over time for the three summer forage crops by tillage treatment 
was complicated (Figure 2-7). Under both tillage treatments, sorghum-sudangrass 
achieved significantly higher biomass yield in the 2010 summer season than in the 2008 
and 2009 summer seasons, while biomass yield for pearl millet was higher in the 2008 
summer season than in the 2009 and 2010 summer seasons. For forage sorghum, biomass 
yield variation over time was totally different under the two tillage treatments: yield 
increased over time under conventional tillage, but decreased over time under no-till 
management. In general, biomass yield for the three summer forage crops under 
conventional tillage tended to increase over time, while yield for pearl millet and forage 
sorghum under no-till tended to decrease over time.     
Effect of tillage on biomass yield for the three summer forage crops was very 
consistent within each summer season (Figure 2-8). In the first season, all three summer 
crops except for sorghum-sudangrass provided significantly higher biomass yield under 
no-till management than under conventional tillage. The yield differences observed in the 
first season under no-till management were not observed in the second summer season: 
 
27 
 
 
yield difference between the two tillage treatments for the three summer forage crops was 
small. Conversely, conventional tillage enhanced biomass yield for all three summer 
crops in the third summer season when compared to no-till. This may be due to soil 
compaction increasing with time and limiting growth under no-till management. Forage 
sorghum and sorghum-sudangrass provided  higher biomass yield than pearl millet under 
all tillage systems within each year except in the 2008 summer season under no-till 
management (P<0.05) (Figure 2-9).  
 
2.3.3.2 Interaction of tillage, winter crop and summer crop 
Average biomass yield of pearl millet after all winter crops under both tillage 
treatments was lower than that of forage sorghum and sorghum-sudangrass, and forage 
sorghum provided similar biomass yields to those of sorghum-sudangrass under all 
combinations of winter crop and tillage method, except that after rye under no-till 
management sorghum-sudangrass produced higher biomass yield than forage sorghum 
(Figure 2-10).     
Average biomass yield for all three summer crops over the three summer seasons 
after the three winter annuals under both tillage treatments was not different except for 
sorghum-sudangrass under no-till treatment providing higher yields after rye than after 
black oat and ryegrass (Figure 2-11). This is possibly because ryegrass and black oat 
have greater allelopathic effects on sorghum-sudangrass under no-till treatment than that 
of rye, while conventional tillage dilutes such an effect. This suggestion is based on the 
fact that allelopathic effects of rye, ryegrass and black oat have been recorded on a 
 
28 
 
 
number of plant species such as white clover, corn and cotton (Barnes and Putnam, 1986; 
Bauer and Reeves, 1999; Price et al., 2008).  
Average biomass yield for forage sorghum and sorghum-sudangrass after all 
winter crops except for sorghum-sudangrass after rye was higher under conventional 
tillage than under no-till, while higher yield for pearl millet after all winter annuals was 
observed under no-till management, but not under conventional tillage (Figure 2-12).     
 
Notwithstanding the year ? tillage ? summer crop interaction and the tillage ? 
winter crop ? summer crop interaction, conventional tillage generally provided higher 
summer biomass yield than no-till management, and forage sorghum and sorghum-
sudangrass provided higher yields than pearl millet. 
 
2.3.4 Total annual biomass yield of winter and summer seasons 
Because summer biomass production produced 63.0 to 90.4% of total annual 
biomass yield, it follows that summer production had a greater effect on total yield than 
winter production. Analysis of total annual biomass yield data revealed a year ? tillage 
method ? cropping system interaction; yield differences among the nine double-cropping 
systems (black oat+pearl millet (BOPM), black oat+forage sorghum (BOS), black 
oat+sorghum-sudangrass (BOSS), rye+pearl millet (RPM), rye+forage sorghum (RS), 
rye+sorghum-sudangrass (RSS), ryegrass+pearl millet (RGPM), ryegrass+forage 
sorghum (RGS), ryegrass+sorghum-sudangrass (RGSS)) was not consistent over the 
three years and across tillage methods (Figure 2-13). Under conventional tillage, annual 
total biomass yield among the nine double-cropping systems was similar in 2008, while 
 
29 
 
 
in 2009 and 2010 systems containing forage sorghum or sorghum-sudangrass provided 
higher yields than systems which included pearl millet. Under no-till management, 
biomass yield for double-cropping systems containing pearl millet or forage sorghum was 
higher than that for cropping systems containing sorghum-sudangrass in 2008, with the 
exception of sorghum-sudangrass after rye. The yield trend among the nine double-
cropping systems was consistent in 2009 and 2010 under both tillage treatments: systems 
containing forage sorghum and sorghum-sudangrass produced higher biomass yield than 
systems that included pearl millet in 2009 and 2010. 
Annual total biomass yield variation over time for the nine double-cropping 
systems was inconsistent under different tillage management (Figure 2-14). Under 
conventional tillage, biomass yield for double-cropping systems containing forage 
sorghum or sorghum-sudangrass increased over time, while yield for cropping systems 
containing pearl millet decreased  over time. However, except for sorghum-sudangrass 
after rye under no-till treatment, biomass yield for all double-cropping systems decreased 
over time. Effect of tillage on total annual biomass yield for the nine double-cropping 
systems varied by year (Figure 2-15). In 2008, conventional tillage resulted in lower total 
biomass yield for all nine double-cropping systems, except for those involving sorghum-
sudangrass, while yield from the two tillage methods was similar for all cropping systems 
in 2009. Conversely, except for systems containing rye in 2010, conventional tillage 
enhanced total annual biomass yield for all double-cropping systems compared to no-till 
management.  
  In this study, highest summer yield and total annual biomass yield were 35.1 Mg 
ha-1 for sorghum-sudangrass and 41.9 Mg ha-1 for ryegrass+sorghum-sudangrass systems 
 
30 
 
 
under conventional-till in 2010, respectively, which are approximately twice that of 
Alamo switchgrass with fertilization at 112 kg N ha-1 in same year and location. 
 
2.4 CONCLUSIONS 
Even though data analysis in this study revealed several complex interactions, 
results still allow some useful general conclusions to be drawn: 
 summer crop and system yields were higher than those recorded for 
switchgrass at the same location 
 compared to production of summer crops in the rotation, winter crop yield 
was relatively low, suggesting that economic analysis should be conducted 
to determine if this phase of the system is economically viable; 
 conventional tillage generally provided higher biomass yields than no-till 
management, but again, economic analysis is needed to determine if the 
higher cost associated with conventional tillage would be offset by the 
higher yields; 
 systems that included forage sorghum or sorghum-sudangrass generally 
provided the highest yields, but sorghum-sudangrass would likely be 
easier to dry, so would be recommended if a dry feedstock is needed; and 
 additional research should include economic analysis and summer crops 
grown alone as well as in rotation with winter crops.  
 
2.5 REFERENCES 
Barnes, J.P., A.R. Putnam. 1986. Evidence for allelopathy by residues and aqueous 
extracts of rye (Secale cereale). Weed Science 34: 384-390.  
 
31 
 
 
 
Bauer, P.J., D.W. Reeves. 1999. A comparison of winter cereal species and planting dates 
as residue cover for cotton growth with conservation tillage. Crop Science 39: 
1824-1830.  
 
Calonego, J.C., C.A. Rosolem. 2010.  Soybean root growth and yield in rotation with 
cover crops under chiseling and no-till. Europ. J. Agronomy 33: 242-249.  
 
Coelho, B., R. Roy, and A. Bruin. 2005. Long-term effects of late-summer overseeding 
of winter rye on corn grain yield and nitrogen balance. Can. J. Plant Sci. 85(3): 
543-554. 
 
Kunkes, E. L., D.A. Simonetti, R.M. West, J.C. Serrano-Ruiz, C.A. Gartner, and J.A. 
Dumesic. 2008. Catalytic conversion of biomass to monofunctional hydrocarbons 
and targeted liquid-fuel classes. Science 332: 417-421. 
 
Kuo, S., U.M. Sainju, and  E. Jellum. 1996. Winter cover cropping influence on nitrogen 
mineralization, presidedress soil nitrate test, and corn yields. Biol. Fertil. Soils 22: 
310-317. 
 
Price, A.J., M.E. Stoll, J.S. Bergtold, F.J. Arriaga, K.S. Balkcom, T.S. Kornecki, R.L. 
Raper. 2008. Effect of cover crop extracts on cotton and radish radicle elongation. 
Communications in Biometry and Crop Science 3 (1): 60-66. 
 
Regalbuto, J.R. 2009. Cellulosic biofuels-got gasoline? Science 325: 822-824.  
 
Russelle, M., R. Morey, J. Baker, P. Porter, H. Jung. 2007 Comment on ?Carbon-
negative biofuels from low-input high-diversity grassland biomass?. Science 316: 
5831. 
 
Schroder, J.J., W. Vandijk, and W.J.M. Degroot. 1996. Effects of cover crops on the 
nitrogen fluxes in a silage maize production system. Neth. J. Agric. Sci. 44: 293-
315. 
 
Stichler, C. 1997. Managing of annual winter forages in Southwest Texas. Extension 
Service of Texas A&M University. 
http://baylor.agrilife.org/files/2011/06/managingannualwinterforagesswtexas_14.pdf 
 
The Energy Independence and Security Act of 2007 (EISA). 
http://frwebgate.access.gpo.gov/cgi-
bin/getdoc.cgi?dbname=110_cong_bills&docid=f:h6enr.txt.pdf 
 
Worldwatch Institute 2007. Biofuels for transport: global potential and implications for 
sustainable energy and agriculture. Earthscan, London, UK. 
 
 
32 
 
 
 Table 2-1 Cultivars, seeding rates, and planting dates and harvest dates of winter annuals and summer crops. 
 
Season Year Crop Variety Seeding rate Planting date Harvest date 
Fall/spring 2007/2008 Black oat Soil Saver 78 kg ha-1 November 14, 2007 April 29, 2008 
  Rye Winter Grazer 100 kg ha
-1 November 14, 2007 April 29, 2008 
  Ryegrass Marshall 11 kg ha
-1 November 14, 2007 April 29, 2008 
Summer 2008 Forage sorghum Evergreen BMR 17 kg ha-1 June 9, 2008 October 1, 2008 
  Pearl millet Pearlex II 17 kg ha
-1 June 9, 2008 October 1, 2008 
  Sorghum-sudangrass Sugar Grazer 2 17 kg ha
-1 June 9, 2008 October 1, 2008 
Fall/spring 2008/2009 Black oat Soil Saver 100 kg ha-1 November 12, 2008 May 6, 2009 
  Rye Elbon 100 kg ha
-1 November 12, 2008 May 6, 2009 
  Ryegrass Marshall 11 kg ha
-1 November 12, 2008 May 6, 2009 
Summer 2009 Forage sorghum Evergreen BMR 17 kg ha-1 June 19, 2009 October 2, 2009 
  Pearl millet Pearlex II 17 kg ha
-1 June 19, 2009 October 2, 2009 
  Sorghum-sudangrass Sugar Grazer 2 17 kg ha
-1 June 19, 2009 October 2, 2009 
Fall/spring 2009/2010 Black oat Soil Saver 100 kg ha-1 November 9, 2009 May 6, 2010 
  Rye Elbon 100 kg ha
-1 November 9, 2009 May 6, 2010 
  Ryegrass Marshall 11 kg ha
-1 November 9, 2009 May 6, 2010 
Summer 2010 Forage sorghum Evergreen BMR 28 kg ha-1 June 10, 2010 October 6, 2010 
  Pearl millet Pearlex II 17 kg ha-1 June 10, 2010 October 6, 2010 
  Sorghum-sudangrass Sugar Grazer 2 28 kg ha
-1 June 10, 2010 October 6, 2010 
 
33 
 
 
 
 
 
 
 
 
Table 2-2 Monthly and growing seasonal precipitation between 2007 and 2010. 
 
Year 
Precipitation (mm)   
Month Winter growing 
season 
Summer 
growing 
season Jan. Feb. Mar. Apr. May Jun. Jul. Aug. Sept. Oct. Nov. Dec. 
2007           55 94 540  
2008 111 102 77 101 64 50 126 252 19 83 93 82 685 594 
2009 52 105 244 109 262 100 75 192 148 164 154 276 814 941 
2010 152 76 124 32 176 56 128 122 46 31       560 
Average (1997-2006) 107 127 181 129 92 141 118 97 104 65 123 104 766 617 
 
 
 
 
 
 
 
 
 
 
 
34 
 
 
 
 
 
 
 
 
 
 
  
Figure 2-1 Monthly chill hours in winter seasons between 2007 and 2010.  
 
 
 
  
 
 
 
 
 
 
 
 
 
 
0
100
200
300
400
500
600
Nov. Dec. Jan. Feb. Mar. Apr.
2007-2008 2008-2009
2009-2010 Average 1997-2006
Mon
thl
y chil
l ho
urs 
 
Month 
 
35 
 
 
 
 
 
 
 
 
 
 
  
Figure 2-2 Average daily solar radiation in each month of the winter seasons between 
2007 and 2010. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
0
2
4
6
8
Nov. Dec. Jan. Feb. Mar. Apr.
2007-2008 2008-2009
2009-2010 Average 1997-2006
Ave
rag
e da
ily
 solar
 ra
diation 
 
(kW
/m
2 )
 
Month 
 
36 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
Figure 2-3 Monthly minimum air temperature in winter seasons between 2007 and 2010. 
 
 
 
 
 
 
 
 
 
-12
-9
-6
-3
0
3
6
Nov. Dec. Jan. Feb. Mar. Apr.
2007-2008
2008-2009
2009-2010
Average 1997-2006
Mont
hly
 mi
nim
um
 tempe
rature
 
(?
) 
Month 
 
37 
 
 
 
 
  
Figure 2-4 Biomass yield for conventional tillage and no-till management for black oat, rye and ryegrass across winter seasons. 
 
Means within each winter crop and winter season with different letters differ (P<0.05). 
  
 
 
 
a a a a 
a 
a 
a a 
a b 
a a 
b a 
b 
a a 
b 
0
2
4
6
8
10
Black oat Rye Ryegrass Black oat Rye Ryegrass Black oat Rye Ryegrass
2007-08 winter season 2008-09 winter season 2009-10 winter season
Conventional tillage No-till
Above
ground
 biom
ass
 yield
 
 (Mg
/ha)
 
 
38 
 
 
 
  
Figure 2-5 Biomass yield for black oat, rye and ryegrass across winter seasons and tillage method. 
 
Means within each tillage treatment and winter season with different letters differ (P<0.05) 
a 
b 
a 
a 
b 
ab 
a ab a 
a 
b 
b 
a 
a 
a 
a 
a 
a 
0
2
4
6
8
10
Conventional
tillage
No-till Conventional
tillage
No-till Conventional
tillage
No-till
2007-08 2008-09 2009-10
Black oat Rye Ryegrass
Above
ground
 biom
ass
 yield
 
 (Mg
/ha)
 
Winter season 
 
39 
 
 
  
Figure 2-6 Biomass yield for black oat, rye and ryegrass over time and across tillage method. 
 
Means within each winter crop and tillage treatment with different letters differ (P<0.05). 
 
 
a 
a 
a a 
a a a a 
a a 
a 
a 
b b 
b b 
b 
b 
0
2
4
6
8
10
Black oat Rye Ryegrass Black oat Rye Ryegrass
Conventional tillage No-till
2007-08 winter season 2008-09 winter season 2009-10 winter season
Above
ground
 biom
ass
 yield
 
 (Mg
/ha)
 
 
40 
 
 
 
  
Figure 2-7 Biomass yield for pearl millet, forage sorghum and sorghum-sudangrass over time and across tillage method. 
 
Means within each summer forage crop and tillage treatment with different letters differ (P<0.05) 
 
 
 
 
 
a 
c 
b 
a a 
b 
b 
b 
b 
b 
b 
b 
ab 
a a 
c 
c 
a 
0
10
20
30
40
PM S SS PM S SS
Conventional tillage No-till
2008 summer season
2009 summer season
2010 summer season
Above
ground
 biom
ass
 yield
 
 (Mg
/ha)
 
 
41 
 
 
 
 
Figure 2-8 Effect of tillage method on biomass yields of pearl millet (PM), forage sorghum (S) and sorghum-sudangrass (SS) over 
time. 
 
Means within each summer forage crop and year with different letters differ (P<0.05) 
 
 
 
b 
b 
a 
a 
a 
a 
a 
a a 
a a 
a 
a 
a 
a 
b 
b 
b 
0
10
20
30
40
PM S SS PM S SS PM S SS
2008 summer season 2009 summer season 2010 summer season
Conventional tillage No-till
Above
ground
 biom
ass
 yield
 
 (Mg
/ha)
 
 
42 
 
 
  
Figure 2-9 Biomass yield of pearl millet, forage sorghum and sorghum-sudangrass as influenced by year and tillage method. 
 
Means within each tillage treatment and year with different letters differ (P<0.05). 
 
 
 
 
 
 
b 
a 
c b 
b 
c 
a 
a a 
a 
a 
b b 
b 
b 
a 
a 
a 
0
10
20
30
40
Conventional
tillage
No-till Conventional
tillage
No-till Conventional
tillage
No-till
2008 summer season 2009 summer season 2010 summer season
Pearl millet
Forage sorghum
Sorghum sudan
Above
ground
 biom
ass
 yield
 
 (Mg
/ha)
 
 
43 
 
 
 
  
Figure 2-10 Biomass yield of pearl millet, forage sorghum and sorghum-sudangrass as influenced by tillage method and winter crops 
(black oat (BO), rye (R), and ryegrass (RG)). 
 
Means within each winter crop and tillage treatment with different letters differ (P<0.05). 
 
 
 
b b b 
c c b 
a a 
a 
a 
b a 
a a a 
b 
a 
ab 
0
5
10
15
20
25
30
35
BO R RG BO R RG
Conventional tillage No-till
Pearl millet Forage sorghum Sorghum sudan
Above
ground
 biom
ass
 yield
 
 (Mg
/ha)
 
 
44 
 
 
 
  
Figure 2-11 Effect of winter crop on biomass yield for pearl millet (PM), forage sorghum (S) and sorghum-sudangrass (SS) under 
different tillage methods. 
 
Means within each summer crop and tillage method with different letters differ (P<0.0001). 
 
 
a 
a 
a 
a 
a 
b 
a 
a 
a 
a 
a 
a 
a 
a 
a 
a 
a 
b 
0
5
10
15
20
25
30
35
PM S SS PM S SS
Conventional tillage No-till
Black oat Rye Ryegrass
Above
ground
 biom
ass
 yield
 
 (Mg
/ha)
 
 
45 
 
 
 
 
 
 
 
Figure 2-12 Effect of tillage method and winter crop on biomass yields of pearl millet (PM), forage sorghum (S) and sorghum-
sudangrass (SS). 
 
Means within each summer crop and winter crop with different letters differ (P<0.05).   
b 
a 
a 
a 
a 
a 
a 
a 
a 
a 
b 
b 
a 
b 
a 
a 
b 
b 
0
10
20
30
40
PM S SS PM S SS PM S SS
Black oat Rye Ryegrass
Conventional tillage No-till
Above
ground
 biom
ass
 yield
 
 (Mg
/ha)
 
 
46 
 
 
 
 
  
Figure 2-13 Total annual biomass yield among different double-cropping systems (black oat+pearl millet (BOPM), black oat+forage 
sorghum (BOS), black oat+sorghum-sudangrass (BOSS), rye+pearl millet (RPM), rye+forage sorghum (RS), 
rye+sorghum-sudangrass (RSS), ryegrass+pearl millet (RGPM), ryegrass+forage sorghum (RGS), ryegrass+sorghum-
sudangrass (RGSS))  across years. 
 
Means within each tillage treatment and year with different letters differ (P<0.05).   
a 
a 
c bc 
b 
c 
a 
a 
a 
a 
a 
b 
a b bc 
ab 
a 
b a 
a 
c bc b 
c 
a 
a 
ab ab 
a 
b a 
b bc ab 
a 
b a 
a 
c c 
b 
c 
a 
a a 
a 
a 
b 
a 
ab 
abc 
a 
a 
a 
0
10
20
30
40
50
Conventional tillage No-till Conventional tillage No-till Conventional tillage No-till
2008 2009 2010
BOPM BOS BOSS
RGPM RGS RGSS
RPM RS RSS
Above
ground
 biom
ass
 yield
 
 (Mg
/ha)
 
 
47 
 
 
    
Figure 2-14 Total annual biomass yield  for the nine double-cropping systems (black oat+pearl millet (BOPM), black oat+forage 
sorghum (BOS), black oat+sorghum-sudangrass (BOSS), rye+pearl millet (RPM), rye+forage sorghum (RS), 
rye+sorghum-sudangrass (RSS), ryegrass+pearl millet (RGPM), ryegrass+forage sorghum (RGS), ryegrass+sorghum-
sudangrass (RGSS))  over time and across tillage methods. 
 
Means within each double-cropping system and tillage treatment with different letters differ (P<0.05). 
a c b a 
b 
b 
a 
b b 
a a 
a 
a a 
a 
a a a 
a 
b 
b 
a 
b 
b 
ab 
ab 
b 
b 
a 
a 
b 
b a 
b 
ab a 
b 
a 
a 
a 
a 
a 
b 
a a 
c 
b 
a 
c 
b a 
c 
b 
a 
0
10
20
30
40
50
BOPM BOS BOSS RGPM RGS RGSS RPM RS RSS BOPM BOS BOSS RGPM RGS RGSS RPM RS RSS
Conventional tillage No-till
2008 2009 2010
Above
ground
 biom
ass
 yield
 
 (Mg
/ha)
 
 
48 
 
 
 
  
Figure 2-15 Total annual biomass yield for the nine double-cropping systems (black oat+pearl millet (BOPM), black oat+forage 
sorghum (BOS), black oat+sorghum-sudangrass (BOSS), rye+pearl millet (RPM), rye+forage sorghum (RS), 
rye+sorghum-sudangrass (RSS), ryegrass+pearl millet (RGPM), ryegrass+forage sorghum (RGS), ryegrass+sorghum-
sudangrass (RGSS))  across years and tillage methods. 
 
Means within each cropping system and year with different letters differ (P<0.05).   
 
b 
 b a b 
b 
a b 
b a 
a 
a 
a 
a 
a 
a 
a 
a 
a 
a 
a 
a 
a 
a 
a 
a 
a a 
a a 
a 
a a 
a 
a a a 
a 
a 
a 
a 
a a 
a 
a a 
b 
b 
b 
b 
b b 
b 
b 
a 
0
10
20
30
40
50
BOPM B
OS
BOSS RGPM R
GS
RGSS R
PM RS RSS
BOPM B
OS
BOSS RGPM R
GS
RGSS R
PM RS RSS
BOPM B
OS
BOSS RGPM R
GS
RGSS R
PM RS RSS
2008 2009 2010
Conventional tillage No-till
Above
ground
 bioma
ss 
yie
ld 
 (Mg
/ha)
 
 
49 
 
 
 
 
CHAPTER 3    LONG-TERM YIELDS AND SOIL IMPACTS OF GIANT REED, 
SWITCHGRASS AND MIMOSA GROWN FOR BIOMASS PRODUCTION IN 
ALABAMA   
 
ABSTRACT 
Encouraging progress towards commercialization of technologies that can 
convert cellulosic biomass into various liquid biofuels is increasing the need to 
develop economically viable and environmentally sustainable biomass supply chains. 
Giant reed (Arundo donax L.) and switchgrass (Panicum virgatum L.) have been 
extensively evaluated for biomass production in southern Europe and the US, 
respectively, both with very favorable results. Mimosa (Albizia julibrissin Durazz.) is 
a perennial, woody cellulosic energy crop that also has high yield potential. However, 
no long-term (> 10 years) data are available on stand longevity, yield response to 
critical factors such as rainfall, and soil impacts of these three energy crops. 
Therefore, the aim of this research was to determine long-term biomass yields and soil 
impacts of giant reed, mimosa and switchgrass as influenced by age of stand and 
rainfall in Alabama. Average annual dry biomass yields for mimosa, giant reed, and 
switchgrass were 40.09, 35.46 and 23.49 Mg ha-1, respectively. In contrast to 
traditional summer row crops such as corn, cotton and soybeans, rainfall had 
relatively minor effects on biomass yields of these three perennial energy crops, and 
 
50 
 
 
effects of stand age were also relatively small. Compared to adjacent bahiagrass 
(Paspalum notatum Fl?gg?), soil pH and soil Mg and Ca contents appeared to be 
lower after long term production of giant reed and switchgrass, but soil P and K 
contents were higher in giant reed plots. 
  
Keywords: perennial cellulosic energy crops; giant reed; mimosa; switchgrass; 
cellulosic biomass production; long-term yield; soil impact  
  
3.1 INTRODUCTION 
Unlike first-generation feedstocks, next-generation feedstocks, i.e., ligno-
cellulosic biomass, are derived from non-food sources, including wood, tall grasses, 
and forestry and crop residues. Compared to starch and sugar feedstocks, these 
materials can only be converted into liquid biofuels by more complex, advanced 
conversion technologies (Worldwatch Institute, 2007). Several technologies that are 
currently under development can use a wide range of cellulosic biomass feedstocks to 
produce various liquid biofuels, including cellulosic ethanol, green gasoline, diesel, 
and jet fuel (Kunkes et al., 2008; Regalbuto, 2009.). Commercial production of 
cellulosic drop-in replacement biofuels at a cost that is competitive with fossil fuels 
could occur within the next five years (Solecki et al., 2012). This progress, together 
with the demand to meet the ambitious national goal mandated by the Energy 
Independence and Security Act of 2007 of producing 16 billion gallons of biofuels 
 
51 
 
 
from cellulosic biomass by 2022, emphasizes the need to develop economically viable 
and environmentally sustainable biomass supply systems.  
Dedicated perennial cellulosic energy crops have received considerable 
research attention because of their high productivity and relatively low feedstock 
costs when compared to agricultural residues. Giant reed (Arundo donax L.), mimosa 
(Albizia julibrissin Durazz.) and switchgrass (Panicum virgatum L.) have shown 
substantial potential as dedicated cellulosic energy crops in the southeastern US. 
Switchgrass, a native perennial grass, has been extensively evaluated since the 1980?s 
(Sanderson et al., 1996; McLaughlin and Walsh, 1998; Bransby et al., 1999; 
McLaughlin and Kszos, 2005). It is widely adapted to different climates and soil 
conditions because of its high levels of drought, cold and heat tolerance. After 
establishment, switchgrass can survive for a long time without the need for replanting. 
Among the cultivars that are commercially available, ?Alamo? was identified as the 
best in terms of yield potential in Texas and Alabama (Ocumpaugh et al. 2003; 
Crider, 2009). The typical yield of ?Alamo? switchgrass ranges from 16 to 35 Mg ha-1 
y-1 (Huang, 2010).   
Giant Reed is a perennial rhizomatous grass that is native to East Asia 
(Polunin and Huxley, 1987), occurring in both grasslands and wetlands, and it grows 
widely in the Mediterranean region. Unlike switchgrass, giant reed is sterile, so it 
must be propagated vegetatively from stem cuttings or rhizome pieces, or by micro-
propagation. Giant reed has been extensively evaluated since the 1980?s as a 
dedicated cellulosic energy crop for bioenergy production in southern Europe 
 
52 
 
 
(Vecchiet et al., 1996; Merlo et al., 1998; Hidalgo and Fernandez, 2001; 
Lewandowski et al., 2003). Biomass yields are typically 20-40 Mg ha-1 year-1 without 
any fertilization after establishment (Angelini et al., 2005; Cosentino et al., 2005; 
Angelini et al., 2009). Mimosa was introduced to the US in 1745 and is grown 
primarily for use as an ornamental shade tree because it produces clusters of pink 
flowers in early summer. Like switchgrass, mimosa can be established from seed by 
using conventional seed drills and this greatly reduces the cost of establishment 
compared to crops that need to be planted with vegetative material. Unlike giant reed 
and switchgrass, mimosa is a legume species, which means that less nutrient inputs 
are necessary to support growth. In the late 1990s, Bransby et al. (2000) started to 
evaluate mimosa as a dedicated energy crop for cellulosic biomass production and 
reported a biomass yield of 37.3 Mg ha-1 yr-1 in Alabama.  
Long-term biomass yield, stand longevity, and yield response to rainfall, and 
impacts on soil are important factors that influence the economic viability and 
environmental sustainability of cellulosic energy crops. However, no information is 
available on these factors as they relate to giant reed, mimosa and switchgrass. 
Therefore, this study aimed to provide long-term yield data for giant reed, mimosa 
and Alamo switchgrass grown in central Alabama, to evaluate soil impacts of the 
three dedicated energy crops after long-term biomass production, and to determine 
their yield responses to stand age and rainfall. 
 
 
53 
 
 
3.2 MATERIALS AND METHODS 
3.2.1 Treatments and experimental design 
Separate small plot experiments were conducted at the E.V. Smith Research 
Center, Plant Breeding Unit (PBU) and Field Crop Unit (FCU) of the Alabama 
Agricultural Experiment Station in central Alabama. Soils at PBU and FCU were a 
Wickham sandy loam (fine-loam, mixed, semiactive, thermic Typic Hapludult) and a 
Norfolk loamy sand (fine-loamy, kaolinitic, thermic Typic Kandiudult), respectively. 
The sites were fallowed prior to planting giant reed, mimosa and switchgrass. Each 
experiment contained four replicate plots which were disked and leveled before 
establishment. 
In the spring of 1988, Alamo switchgrass seed was drilled into prepared plots 
at the PBU with rows 20 cm apart at a seeding rate of 11.3 kg ha-1. Plots were 1.5 m 
wide and 6.0 m long, and received 84 kg N ha?1 annually, split into two equal 
applications in March and again after the first harvest. 
In the spring of 1989, mimosa seedlings were planted into prepared plots at the 
FCU at a density of 22,536 trees ha-1, with 91 cm between rows. Plots were 3.6 m 
wide and 6.0 m long, and received no fertilizer. 
In the spring of 1999, stem segments of giant reed that were approximately 1 
m long were obtained from southern California and hand-placed end-to-end in four 
furrows 75 cm apart, and covered with 5-7.5 cm of soil in each prepared plot at the 
PBU. Plots were 3 m wide and 9 m long. They were fertilized with ammonium nitrate 
at a rate of 112 kg N ha-1 in May 2000, but received no fertilizer in subsequent years.  
 
54 
 
 
 
3.2.2 Data collection 
After establishment, biomass from giant reed and mimosa were harvested in 
late October each year, and switchgrass was harvested in early August and again in 
late October. In each plot, giant reed plants in a 1-m2 area and switchgrass plants in 
the middle two rows of each plot were cut to a 5-cm above ground level. Mimosa 
plants were cut to a 20 cm above ground level from the two center rows of each plot. 
All harvested plant material was weighed immediately to determine fresh weight in 
the field by using a hanging scale. Subsamples taken from each plot were dried at 
60?C for 72 h for dry matter determination. Yield data for mimosa and giant reed 
were not recorded in 2004 and 2008, respectively.  In early August of 2009, 2010 and 
2011, fiberglass mesh sheets 0.58-m wide and 6.0-m long were placed between the 
central two rows of each mimosa plot to measure leaf residues that sloughed as the 
summer progressed (Plate 3-1). This material was dried at 60?C for 72 h for 
determination of dry matter, and its N content was measured by using a CNS 
Analyzer (LECO CNS-2000 Macro Analyzer; LECO Corp., St. Joseph, Michigan). In 
late fall 2012, one topsoil (0-20 cm) sample was taken from each switchgrass, giant 
reed and mimosa plot, and from adjacent areas colonized naturally with bahiagrass 
(Paspalum notatum Fl?gg?) that had been maintained by mowing periodically without 
removal of mowed material, and that had not been fertilized. These samples were 
used to determine soil pH, and soil extractable phosphorus (P), potassium (K), 
magnesium (Mg) and calcium (Ca) contents. 
 
55 
 
 
3.2.3 Data analysis 
For each species, biomass yield was analyzed by means of analysis of variance 
using SAS v9.2 PROC MIXED procedure, assuming year as a fixed effect. 
Regression analyses of biomass yield against age and rainfall were performed for 
giant reed, mimosa and switchgrass by using the SAS PROC REG procedure, and 
also for yield of corn, cotton and soybeans obtained from variety trials (Glass et al., 
2000-2011) with rainfall (March to September), to facilitate observational 
comparisons of crop responses to these variables. Since each perennial cellulosic 
energy crop was grown in a separate experiment, statistical comparisons across 
species were not valid. However, because these experiments were conducted for very 
long periods at the same time and location, and under the same weather conditions 
and similar soil conditions, observational differences (as opposed to statistical 
differences) are considered valuable, especially if they were large and consistent over 
time. 
 
3.3 RESULTS AND DISCUSSIONS 
3.3.1 Weather conditions 
Growing season (March to October) rainfall was close to the long term 
average (824 mm) in all years from 1989 to 2011, except for very high rainfall in 
1989, 2003 and 2009 and very low rainfall in 2000 and 2007 (Figure 3-1). Mean 
minimum air temperature in winter was -8.8 ? and mean maximum air temperature 
in summer was 37.5 ?. Air temperature over 40 ? was recorded in the summer of 
 
56 
 
 
2000 and 2007, and a minimum air temperature of -12 ? was recorded in the winter 
of 2002.   
 
3.3.2 Biomass yield 
By fall of 2011 switchgrass, giant reed and mimosa plots had been harvested 
annually for 23, 13 and 22 years after establishment, respectively, and there was no 
visual evidence of stand deterioration in plots of all three species. Biomass yield for 
each of the three perennial energy crops varied over time (P<0.05). During the 
experimental years, highest yields for switchgrass, giant reed and mimosa were 34.6, 
43.6 and 59.5 Mg ha-1, respectively (Figure 3-2). Overall, mimosa provided the 
highest biomass yield, followed by giant reed and switchgrass, even though mimosa 
and giant reed received no maintenance fertilizer. Average annual dry biomass yields 
for mimosa from the eighth year to 2011, giant reed and switchgrass from the third 
year to 2011were 40.09, 35.46, and 23.49 Mg ha-1, respectively. The remarkably high 
yields recorded for mimosa and giant reed suggest that both of these crops are able to 
fix N, even though giant reed is not a legume. In this case, endophytic bacteria and 
beneficial bacteria in the rhizosphere could be involved because several bacteria 
strains with strong N-fixing and/or P-solubilizing abilities have recently been isolated 
from giant reed in Alabama (Xu, 2011).  
Biomass yield of giant reed increased slightly with age of stand, but yields of 
mimosa and switchgrass were not affected by stand age (Figure 3-3). This suggests 
that under the management regimes implemented in this study, stands of giant reed, 
 
57 
 
 
switchgrass and mimosa can be expected to be productive for at least 13, 23 and 22 
years after establishment, respectively, before needing to be re-established. Biomass 
production of the three perennial cellulosic energy crops was not affected by rainfall 
(Figure 3-4). Recognizing that rainfall in 2000 and 2007 was among the lowest on 
record (Figure 3-1), these results indicate that all three perennial crops evaluated in 
this study are extremely resistant to drought, thus minimizing weather-related losses. 
In contrast, yield of traditional row crops such as corn, cotton and soybeans was 
strongly influenced by growing season rainfall (Figures 3-5 and 3-6), indicating that 
production of all of these annual crops is subject to high weather-related risk. A 
probable reason for the high resistance of the perennial crops to drought is existence 
of a large, deep and permanent root system, whereas the extent of the root system of 
annual crops is relatively limited, especially in the first half of the growing season. 
For example, at the same location as this study Ma (1999) discovered that mature 
switchgrass roots extended to a depth of over 3 m in the soil.  
 
3.3.3 Soil impacts 
Soil pH and nutrients from giant reed, switchgrass and mimosa plots appeared 
to be different when compared to adjacent bahiagrass. Soil obtained from giant reed, 
mimosa and switchgrass plots had lower Mg and Ca than that obtained from 
bahiagrass (Table 3-1). In particular, topsoil extractable Mg for giant reed, 
switchgrass and mimosa was 21, 49 and 320 kg ha-1 lower than that for bahiagrass, 
respectively, and soil extractable Ca was 353, 339 and 631 kg ha-1 lower. Soil pH for 
 
58 
 
 
switchgrass and giant reed was 0.3 and 1.5 units lower than that for bahiagrass, 
respectively, which is consistent with the level of soil extractable Ca. However, this 
trend was not evident for mimosa. Soil extractable P and K for switchgrass plots was 
74 and 157 Mg ha-1 lower, respectively, than that for bahiagrass, and for mimosa the 
values were 15 and 71 Mg ha-1 lower. However, for giant reed soil extractable P and 
K were 121 and 30 kg ha-1 higher than for adjacent bahiagrass, respectively.  
These apparent differences in soil impacts of the three perennial cellulosic 
energy crops evaluated in this study are likely related to differences among these 
species in morphology, physiology and association with beneficial microorganisms. 
For example, 80% of switchgrass roots are located in the topsoil (Bransby et al., 
1998) and giant reed accumulates extremely large amounts of biomass in rhizomes, 
which are also located in the topsoil (Huang and Bransby, 2010). However, since 
mimosa is a woody species, its roots are likely distributed more evenly in the soil 
profile. In addition, mimosa appears to shed a much larger amount of senesced leaf 
material (Table 3-2) in late summer compared to giant reed and switchgrass. Finally, 
since mimosa is a legume it would be expected to fix N, while giant reed and 
switchgrass are known to have associations with beneficial microorganisms (Xu, 
2011). 
 
3.4 CONCLUSIONS 
Data collected in this study suggest that the following conclusions can be 
drawn: 
 
59 
 
 
 long term biomass yields of mimosa and giant reed appear to be 
considerably higher than that of Alamo switchgrass; 
 if managed according to procedures followed in this study, mimosa 
and switchgrass stands in the southeastern US should remain 
productive for 20 years or more, and giant reed for 13 years or more; 
 unlike yield of traditional summer row crops such as corn, cotton and 
soybeans, biomass yield of the three perennial cellulosic energy crops 
evaluated in this study were affected very little by drought; and 
 preliminary soil data collected in this study suggest that detailed 
research on nutrient cycling for giant reed, switchgrass and mimosa is 
needed to develop soil management practices that will ensure 
sustainable long term biomass production.  
  
3.5 REFERENCES 
Angelini, L.G., L. Ceccarini, and E. Bonari. 2005. Biomass yield and energy balance 
of giant reed (Arundo donax L.) cropped in central Italy as related to different 
management practices. Europ. J. Agronomy 22: 375-389. 
 
Angelini, L.G., L. Ceccarini L, N.N. o Di Nasso, E. Bonari. 2009. Comparison of 
Arundo donax L. and Miscanthus?giganteus in a long-term field experiment in 
Central Italy: Analysis of productive characteristics and energy balance. 
Biomass and Bioenergy 33: 635-643. 
 
Bransby D.I., S.B. Mclaughlin, and D.J. Parrish. 1998. A review of carbon and 
nitrogen balances in switchgrass grown for energy. Biomass and Bioenergy 14: 
379-384. 
 
Bransby D.I., J. Bouton, B. Conger, S.B. McLaughlin, W.R. Ocumpaugh, D. Parrish, 
K. Taliaferro, K. Vogel, S. Wallschleger. 1999. Developing Switchgrass as a 
Bioenergy Crop.PotNewCropNewUses.AgronSHS.282-299. 
 
60 
 
 
 
Bransby, D.I., T.A. Morrison, and S.E. Sladden. 2000. Advantages of mimosa 
(Albizia julibrissin) over traditional short rotation woody crops. In: 
Proceedings of the first world conference on biomass for energy and industry, 
Sevilla, Spain, 5-9 June, 2000, pp. 1933-1934.  
   
Cosentino, S.L., V. Copani, G.M. D?Agosta, E. Sanzone, M. Mantineo. 2005. First 
results on evaluation of Arundo donax L. clones collected in Southern Italy. 
Industrial Crops and Products 23(2): 212-222. 
 
Crider, L. 2009. Composition and yield of eight switchgrass cultivars in Alabama. 
Masters Thesis, Auburn University, AL. 6p.  
http://etd.auburn.edu/etd/bitstream/handle/10415/1688/Crider_Thesis_Manuscr
ipt.pdf?sequence=1 
 
Glass, K. M., D.P. Delaney, and E. van Santen. 2000-2011. Alabama variety testing 
program.  http://www.ag.auburn.edu/agrn/alabamavarietytesting/. 
 
Hidalgo, M., J. Fernandez. 2001. Biomass production of ten populations of giant reed 
(Arundo donax L.) under the environmental conditions of Madrid (Spain). In: 
Kyritsis, S., Beenackers, A.A.C.M., Helm, P., Grassi, A., Chiaramonti, D. 
(Eds.), Biomass for Energy and Industry. Proceeding of the First World 
Conference, Sevilla, Spain, 5-9 June. James and James, Science Publisher Ltd, 
London, pp. 1181-1184. 
 
Huang, P., D. Bransby, S. Sladden, E. van Santen, L. Crider. 2010. Twenty-year 
biomass yields for eight switchgrass varieties in Alabama. ASA, CSSA, and 
SSSA 2010 International Annual Meetings, Oct. 31-Nov. 4, Long Beach, CA. 
 
Huang, P, and D. Bransby. 2010. Exceptionally high yields and carbon sequestration 
recorded for giant reed in Alabama. Agronomy Abstracts. 
 
Kunkes, E.L., D.A. Simonetti, R.M. West, J.C. Serrano-Ruiz, C.A. Gartner, and J.A. 
Dumesic. 2008. Catalytic conversion of biomass to monofunctional 
hydrocarbons and targeted liquid-fuel classes. Science 332: 417-421. 
 
Lewandowski, I., J.M.O. Scurlock, E. Lindvall, M. Christou. 2003. The development 
and current status of perennial rhizomatous grasses as energy crops in 
theUSand Europe. Biomass Bioenergy 25: 335-361. 
 
Ma, Zhiqin. 1999. Carbon sequestration by switchgrass. Ph.D Dissertation, Auburn 
University, AL. 78p. 
 
 
61 
 
 
McLaughlin, S. B., M.E. Walsh. 1998. Evaluating environmental consequences of 
producing herbaceous crops for bioenergy. Biomass and Bioenergy 14: 317-
324. 
 
McLaughlin, S. B. and L.A. Kszos. 2005. Development of switchgrass (Panicu 
virgatum) as a bioenergy feedstock in the United States. Biomass Bioenergy, In 
press. 
 
Merlo, L., B. Morgana, V. Sardo, F. La Loggia. 1998. Experiences with giant reed 
and perennial C4 grasses in Sicily. In: H. Kopetz, T. Weber, W. Pals, P. 
Chartier, G.L. Ferrero (Eds.), Proceedings of the International Conference on 
Biomass for Energy and Industry. Wurzburg, Germany, 8-11 June. CARMEN, 
Rimpar Germany, pp. 1006-1008. 
 
Ocumpaugh, W., M. Hussey, J. Read, J. Muir, et al. 2003. Evaluation of switchgrass 
cultivars and cultural methods for biomass production in the south central U.S.. 
https://bioenergy.ornl.gov/pdfs/ornlsub_03_19XSY091C.pdf 
 
Polunin, O., A. Huxley. 1987. Flowers of the Mediterranean. Hogarth Press, London. 
  
Regalbuto, J. R. 2009. Cellulosic biofuels-got gasoline? Science 325: 822-824.  
 
Sanderson, M.A., R.L. Reed, S.B. McLaughlin, S.D. Wullschleger, B.V. Conger, D.J. 
Parrish, D.D. Wolf, C. Taliaferro, A.A. Hopkins, W.R. Ocumpaugh, M.A. 
Hussey, J.C. Read, and C.R. Tischler.1996. Switchgrass as a sustainable 
bioenergy crop.Bioresour. Tech- nol. 56:83-93. 
 
Solecki, M., A. Dougherty, and B. Epstein. 2012. E2 Report: Advanced Biofuel 
Market Report 2012. 
www.e2.org/ext/doc/E2AdvancedBiofuelMarketRrport2012.pdf. 
 
The Energy Independence and Security Act of 2007 (EISA). 
http://frwebgate.access.gpo.gov/cgi-
bin/getdoc.cgi?dbname=110_cong_bills&docid=f:h6enr.txt.pdf 
 
Vecchiet, M., R. Jodice, G. Schenone. 1996. Agronomic research on giant reed 
(Arundo donax L.) management system and cultivation of two different 
provenances. In: Proceedings of the Ninth European Bioenergy Conference, 
Copenhagen, 24?27 June, pp.644-648. 
 
Xu, J., J.W. Kloepper, J. Mclnroy, C.H. Hu, R. Bonilla. 2011. Isolation and 
characterization of nitrogen-fixing and phosphate solubilizing bacteria from 
Aurndo donax L. (giant reed). In: Reddy, M.S., Wang, Q., Plant Growth-
Promoting Rhizobacteria (PGPR) for Sustainable Agriculture. Proceeding of 
 
62 
 
 
the Second Asian PGPR Conference, Beijing, P.R. China, 21-24 August. pp. 
409-415. 
 
Worldwatch Institute. Biofuels for transport: global potential and implications for 
sustainable energy and agriculture. Earthscan, London, UK. 2007. 
 
 
63 
 
 
 
 
Table 3-1 Soil pH and P, K, Mg and Ca content for giant reed, switchgrass, mimosa and adjacent bahiagrass in 2012. 
 
Treatments Soil pH Phosphorous Potassium Magnesium Calcium kg ha-1 
Giant reed 4.6 (0.2) b 242 (25) a 219 (37) a 93 (20) a 326 (100) b 
Adjacent bahiagrass 6.1 (0.1) a 121 (12) b 189 (37) a 114 (20) a 679 (12) a 
Switchgrass 5.8 (0.2) a 47 (8) b 32 (2) b 65 (9) b 340 (48) b 
Adjacent bahiagrass 6.1 (0.1) a 121 (12) a 189 (37) a 114 (20) a 679 (12) a 
Mimosa 6.7 (0.1) a 25 (6) a 89 (7) b 280 (10) a 1404 (85) a 
Adjacent bahiagrass 6.5 (0.1) a 40 (6) a 160 (10) a 600 (174) a 2035 (551) a 
 
Values in parentheses are standard errors.  
Means within each perennial energy crop species and each column with different letters differ (P<0.05).   
 
 
 
 
 
 
64 
 
 
 
 
 
 
 
 
Table 3-2 Yield and N content of leaf material shed by mimosa during the growing 
season in 2009, 2010 and 2011. 
 
Year Residue biomass yield (Mg ha-1) Nitrogen content (%) Nitrogen addition by residue (kg N ha-1) 
2009 1.30 (0.13) 2.26 (0.09) 29.38 
2010 1.37 (0.19) 2.38 (0.18) 32.61 
2011 2.30 (0.65) 2.17 (0.10) 49.91 
Average 1.66 2.27 37.3 
 
Values in parentheses are standard deviations.  
 
65 
 
 
 
 
 
 
 
Figure 3-1 Growing season (March to October) precipitation from 1989 to 2011. 
0
300
600
900
1200
1500
1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011
Year 
Gr
owing
 se
ason 
pre
cipi
tation
 (mm)
 
 
66 
 
 
 
 
Figure 3-2 Annual biomass yield of mimosa from the eighth year to 2011, giant reed and switchgrass from the third year to 2011, with the long 
term mean indicated as a horizontal line.  
 
Vertical bars represent the standard deviation.
23.49  
35.46 
40.09  
0
10
20
30
40
50
60
70
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011
Alamo switchgrass
Giant reed
Mimosa
Year 
Above
-ground
 dr
y matter
  y
ield 
(Mg
 ha
-1 )
 
 
 
67 
 
 
 
 
 
 
Figure 3-3 Effect of stand age (x) on yield (y) of switchgrass (a), giant reed (b) and 
mimosa (c).  
 
ns = non-significant. ** Significant at the 0.01 probability level. 
y = -0.0473x + 24.128 
R? = 0.002  ns 
0
20
40
60
80
0 5 10 15 20 25
Above
-ground
 biom
ass y
ield 
 
(Mg
 ha
-1 )
 
(a) 
y = 1.3249x + 25.121 
R? = 0.1716  ** 
0
20
40
60
80
0 5 10 15
Above
-ground
 biom
ass y
ield 
 
(Mg
 ha
-1 )
 
(b) 
y = 0.1187x + 38.26 
R? = 0.0023  ns 
0
20
40
60
80
0 5 10 15 20 25
Abov
e-g
round
 bi
om
ass 
yiel
d 
(Mg
 ha
-1 )
 
 
Age of stand 
(c) 
 
68 
 
 
 
 
 Figure 3-4 Effect of growing season rainfall (March to October) (x) on biomass yield (y) 
of switchgrass (a), giant reed (b) and mimosa (c). 
 
ns = non-significant. 
y = -0.0048x + 27.307 
R? = 0.0198   ns 
0
20
40
60
80
0 500 1000 1500
Abov
e-g
round
 bi
om
ass 
yiel
d 
(Mg
 ha
-1 )
 
 
(a) 
y = 0.0048x + 31.567 
R? = 0.0125  ns 
0
20
40
60
80
0 500 1000 1500
Abov
e-g
round
 bi
om
ass 
yiel
d 
(Mg
 ha
-1 )
 
 
(b) 
y = 0.0105x + 31.445 
R? = 0.0442  ns 
0
20
40
60
80
0 500 1000 1500
Abov
e-g
round
 bi
om
ass 
yiel
d 
(Mg
 ha
-1 )
 
 
Growing season rainfall (mm) 
(c) 
 
69 
 
 
 
 
  
 
 
Figure 3-5 Effect of growing season rainfall (March to September) (x) on grain yield (y) 
of yellow corn (a) and cotton lint yield (y) (b) grown in central Alabama 
during the 2000-2011period.  
 
*, **, *** Significant at the 0.05, 0.01 and 0.001 probability level, respectively. 
 
 
 
 
 
 
y = 8.6677x + 155.37 
R? = 0.3239  *** 
0
5000
10000
15000
20000
0 500 1000 1500
Yel
low
 cor
n g
rai
n y
iel
d  
(kg
 ha
-1 )
 
(a) 
Growing season rainfall (mm) 
y = 1.4667x + 226.87 
R? = 0.6483  *** 
0
1000
2000
3000
0 500 1000 1500
Cot
ton 
lint
 yi
eld 
 
(kg
 ha
-1 )
 
(b) 
Growing season rainfall (mm) 
 
70 
 
 
 
  
Figure 3-6 Relationship between rainfall (March to September) (x) and grain yield (y) of 
soybean cultivars in maturity group IV (a), V (b), and VI (c) grown in central 
Alabama during the 2000-2011 period.  
 
*, **, *** Significant at the 0.05, 0.01 and 0.001 probability level. 
y = 3.3845x - 16.644 
R? = 0.4898  *** 
0
2000
4000
6000
0 500 1000 1500
Soy
bea
n g
rai
n y
iel
d (
kg
 ha
-1 )
 
(a) 
y = 2.729x + 815.12 
R? = 0.4718  *** 
0
2000
4000
6000
0 500 1000 1500
Soy
bea
n g
rai
n y
iel
d (
kg
 ha
-1 )
 
(b) 
y = 2.6465x + 711.51 
R? = 0.4724  *** 
0
2000
4000
6000
0 500 1000 1500
Soy
bea
n g
rai
n y
iel
d (
kg
 ha
-1 )
 
Growing season rainfall (mm) 
(c) 
 
71 
 
 
 
 
 
 
 
 
 
 
 
  
Plate 3-1 Mimosa leaf residue collection at the end of the 2009 growing season. 
 
 
 
 
 
 
 
 
 
 
72 
 
 
 
 
CHAPTER 4    EFFECTS OF NITROGEN FERTILIZATION AND SUBSOILING ON 
BIOMASS YIELD OF ESTABLISHED SWITCHGRASS  
 
ABSTRACT 
Switchgrass (Panicum virgatum L.) has been extensively evaluated in the US as a 
potential cellulosic energy crop, and ?Alamo? is one of the highest yielding switchgrass 
cultivars in Southeast. Several studies indicated a positive response in biomass yield of 
Alamo switchgrass to added nitrogen fertilizer, but this response varies greatly, 
depending on climate and site. Moreover, information is not available on possible 
benefits of subsoiling compacted soil (which is common in the Southeast) under 
established switchgrass stands with a subsoiling plough. Therefore, the objectives of this 
study were to evaluate the effects of N rate and subsoiling on biomass yield of 
established Alamo switchgrass in central Alabama. A declining positive response was 
observed for biomass yield as N rate increased from 0 to 112 kg N ha-1, but there was no 
yield response to subsoiling. Average biomass yields for 0, 56 and 112 kg N  ha-1 over a 
three-year period were 4.85, 7.80 and 9.45 Mg ha -1, respectively. Assuming a biomass 
price of at least $44.1 Mg-1, application of N fertilizer was economically viable.  
  
Keywords: ?Alamo? switchgrass, nitrogen fertilizer, subsoiling, biomass yield. 
 
 
73 
 
 
4.1 INTRODUCTION 
Switchgrass (Panicum virgatum L.) is a native, warm-season perennial grass that 
has been extensively evaluated as a cellulosic energy crop in the US. It is popular because 
of its wide geographic adaptation, high biomass yield, desirable fuel characteristics, and 
compatibility with conventional farm practices (Sanderson et al., 1996; McLaughlin and 
Walsh, 1998; Bransby et al., 1999; Schmer, M. R., et al. 2006; Lemus et al., 2008).  
There are two ecotypes of switchgrass that facilitate its wide geographic 
adaptation: lowland ecotypes are heat and drought tolerant, and suitable for the Mid-west 
and southeastern US, whereas upland ecotypes are more cold tolerant, and suitable for the 
northern US, but are less productive (Bransby et al., 1999; Cassida et al., 2005 (a) and 
(b)). Currently, many commercial switchgrass cultivars are available, including two 
lowland types, ?Alamo? and ?Kanlow?, and six upland types, ?Cave-in-Rock?, 
?Blackwell?, ?Summer?, ?Trailblazer?, ?Pathfinder?, and ?Kansas-Native?.  
Switchgrass cultivars differ greatly in biomass yield. Sanderson et al. (1996 and 
1999) found that biomass yields of lowland cultivars including Alamo switchgrass are 
better than upland yields in Texas and Virginia. ?Alamo? switchgrass was also identified 
by Ocumpaugh et al. (2003) as the best variety in long-term studies in Texas. 
Furthermore, the results from a long-term cultivar trial of eight cultivars of switchgrass in 
Alabama listed above also demonstrated that lowland cultivars provided substantially 
higher biomass yields than upland cultivars: in this experiment, Alamo switchgrass was 
the best cultivar with highest average biomass yield of 23.4 Mg ha-1over a 20-year period 
and yield, was not influenced by rainfall and plot age (Crider, 2009; Huang, 2010). For 
 
74 
 
 
these reasons, Alamo switchgrass has received more research attention than other 
cultivars for production of cellulosic biomass in the southeastern US.  
Muir et al. (2001) found that biomass production of Alamo switchgrass grown 
without N fertilizer tended to decline over time in Texas. Several other studies indicated a 
positive response of Alamo switchgrass yield to added N fertilizer in Texas and 
Tennessee, but based on results from these studies, different N rates were recommended 
(Reed et al., 1995; Muir et al., 2001; Charles et al., 2011). Reed et al. found that biomass 
yield of Alamo switchgrass was maximized at about 224 kg N ha-1 in Beeville, Texas on 
a Wind thorst fine sandy loam soil, whereas Muir et al. reported a maximum yield of 22.5 
Mg ha-1 with 168 kg N ha-1 at Stephenville on the same soil type. This reflects variation 
in response of Alamo yield to N fertilization across different climates and sites. 
Furthermore, N fertilization must be optimized to balance the cost of fertilizer application 
and the revenues obtained from improved biomass yield. A projected economic optimum 
N fertilization level for Alamo switchgrass was about 120 kg N ha-1 even if maximum 
yield was observed at higher rates, since biomass yield responses are typically quadratic 
when high rates of N are tested (Ocumpaugh et al., 2003).   
Many soils in the Southeast are prone to compaction, suggesting that subsoiling 
might improve crop production. For instance, Izumi et al. (2009) found in a no-till wheat-
soybean rotation, wheat grain yield increased after subsoiling Since switchgrass is a 
perennial it is possible that soil compaction could be more limiting to growth than for 
annual crops due to complete elimination of tillage, and this suggests that subsoiling 
might increase biomass yield of established switchgrass stands. However, no information 
on this topic is available.        
 
75 
 
 
Therefore, the objective of this study was to evaluate the yield response of a 17-
year old Alamo switchgrass stand to added N fertilizer and subsoiling in central Alabama. 
 
4.2 MATERIALS AND METHODS 
4.2.1 Treatments and experimental design 
The experiment was conducted at the E.V. Smith Research Center, Field Crop 
Unit of the Alabama Agricultural Experiment Station near Shorter, Alabama. Soil at the 
site was classified as a Norfolk fine sandy loam (fine, loamy, siliceous, thermic Typic 
Kandiudult). In April 1992, Alamo switchgrass seed had been drilled 12 cm deep into 
plots in rows 20 cm apart at a seeding rate of 11.3 kg ha-1. Plots were fertilized with 56 
kg N ha-1 at planting, but after establishment received limited management and no 
fertilizer or irrigation for several years prior to the current experiment. The experiment 
was laid out in a randomized complete block factorial design with two treatments: 
subsoiling or no subsoiling, and one time application of 0, 56, or 112 kg N ha-1 each year 
over a three-year period starting in 2009. Plots measured 3 ? 9 m, and were blocked 
according to pre-treatment yields that were obtained in fall of 2008.  Plots were subsoiled 
to a depth of 25 cm in early March each year before switchgrass initiated growth by using 
a KMC subsoiler (Kelley Manufacturing Co., Tifton, Georgia) with blades set 60 cm 
apart (Plate 4-1). In early June 2009, 2010 and 2011, each N treatment plot received a 
single application of ammonium nitrate at its designated rate.  
 
 
76 
 
 
4.2.2 Data collection 
At the end of each growing season (October) the center two rows of each plot 
were cut to a 5-cm stubble height with a sickle bar mower. Fresh biomass weight from 
the harvested area in each plot was measured using a hanging scale in the field. Biomass 
subsamples taken from each plot were dried at 60?C for 48 h for dry matter determination 
and border rows were harvested right after sampling.  
 
4.2.3 Data analysis 
Analysis of variance was conducted using SAS v9.2 PROC MIXED procedure. 
Block was considered as a random factor, while year was considered a fixed factor. The 
critical P-value of 0.10 was used as cutoff for testing fixed effects, and determination of 
differences in least-squares means was based on adjusted P-value obtained by using the 
option ADJUST=SIMULATE in the LSMEANS statement. 
To determine the economic implications of N fertilization the N cost per 
additional Mg of biomass produced by N fertilization was calculated by dividing the cost 
of fertilizer per hectare by the difference in biomass yield between fertilized and 
unfertilized switchgrass for any particular fertilization level. Based on 2010 USDA data 
for fertilizer prices (USDA-ERS, 2010), a price of $1.30 kg-1 N was assumed.  
 
4.3 RESULTS AND DISCUSSIONS 
4.3.1 Weather conditions 
Rainfall was close to the long-term average in the 2010 and 2011 growing 
seasons, but very high in 2009 (Table 4-1). The summer (March to October) growing 
 
77 
 
 
season rainfall of 2009 was 1293 mm, which is 366 mm higher than the average of past 
10 years.  
 
4.3.2 Biomass yield 
Biomass yield increased with N rate in all three years (Figure 4-1), but this 
response varied by year, indicating an N rate ? year interaction. In particular, the 
response to N fertilization increased with time (Figure 4-2). This trend was not positively 
related to rainfall (Table 4-1), but might have been a cumulative response to N as a result 
of all plots receiving no N fertilization for several years prior to initiation of this 
experiment. When compared to the control (0 kg N ha-1), applying 56 kg N ha-1 increased 
biomass yield by a range of 34.6% to 72.8% in the three-year period, and applying 112 
kg N ha-1 by a range of 44.5% to 146.7%. This positive response of Alamo biomass yield 
to added N fertilizer was consistent with the findings of Reed et al. in 1995 and Muir et 
al. in 2001 in Texas. In addition, a distinct change in leaf color from light green to dark 
green was also observed on fertilized plots 10 days after fertilization, suggesting that 
control plots were severely deficient in N (Plate 4-2). 
Although subsoiling has been reported to increase yields in some traditional crops 
such as wheat and cotton (Izumi et al., 2009; Raper et al., 2007), it did not affect biomass 
yield of switchgrass in this experiment. A possible explanation for this is that subsoiling 
might have resulted in root damage of switchgrass. Although Alamo switchgrass has a 
well-developed deep root systems reaching to 3 m below the soil surface, more than 78% 
of roots are located at soil depth of 0-30 cm (Ma, 1999). Even though switchgrass was 
 
78 
 
 
planted in rows in this experiment, individual plants spread outward between rows, 
making root damage by subsoiling possible.  
The cost of N per additional Mg of biomass produced by N fertilization decreased 
substantially with time, and ranged between $19.15 and $65.00 (Table 4-2). Although N 
cost per Mg of switchgrass biomass produced was similar with the two N rates, a greater 
risk is assumed with the higher N rate. Therefore, the price of switchgrass biomass and 
the volatility of the market, would have a significant impact on the decision to use a 
higher N rate.  
 
4.4 CONCLUSIONS 
Results from this study allowed the following conclusions to be drawn: 
 biomass yield of a previously unfertilized mature stand of Alamo 
switchgrass increased with N fertilization up to 112 kg N ha-1; 
 this response increased over time, and was not related to precipitation; 
 assuming that the response of biomass yield to N fertilization was 
cumulative, results from the second and third years of this study suggest 
that if sale price of biomass was above $33.36 Mg-1, fertilization with N 
was justified from an economic point of view; and 
 subsoiling had no effect on biomass production. 
 
4.5 REFERENCES 
Bransby D.I., J. Bouton, B. Conger, S.B. McLaughlin, W.R. Ocumpaugh, D. Parrish, K. 
Taliaferro, K. Vogel, S. Wallschleger. 1999. Developing Switchgrass as a 
Bioenergy Crop. PotNewCropNewUses. AgronSHS: 282-299. 
 
 
79 
 
 
Cassida K.A., M.A. Hussey, J.P. Muir, W.R. Ocumpaugh, J.C. Read, B.C. Venuto. 2005. 
Biofuel Component Concentrations and Yields of Switchgrass in South Central 
U.S. Environments. Crop Sci. 45: 682-692. (a) 
 
Cassida K.A., M.A. Hussey, J.P. Muir, W.R. Ocumpaugh, J.C. Read, B.C. Venuto. 2005. 
Biomass Yield and Stand Characteristics of Switchgrass in South Central U.S. 
Environments. Crop Sci. 45: 673-681. (b)  
 
Charles, T.G Jr., D.J. Brice, H.F. Castro, et al. 2011. Response of ?Alamo? switchgrass 
tissue chemistry and biomass to nitrogen fertilization in West Tennesses, USA. 
Agriculture, Ecosystems and Environment 140: 289-297.    
 
Crider, L. 2009. Composition and yield of eight switchgrass cultivars in Alabama. 
Masters Thesis, Auburn University, AL. 6p.  
 
Huang, P., D. Bransby, S. Sladden, E. van Santen, L. Crider. 2010. Twenty-year biomass 
yields for eight switchgrass varieties in Alabama. ASA, CSSA, and SSSA 2010 
International Annual Meetings, Oct. 31-Nov. 4, Long Beach, CA. 
 
Izumi, Y., T. Yoshida, M. Iijima. 2009. Effects of subsoiling to the non-tilled field of 
wheat-soybean rotation on the root system development, water uptake, and yield. 
Plant Production Science 12: 327-335. 
 
Lemus, R., et al. 2008. Effects of nitrogen fertilization on biomass yield and quality in 
large fields of stablished switchgrass in southern Iowa, USA. Biomass &Bioenergy, 
32: 1187-1194. 
 
Ma, Zhiqin. 1999. Carbon sequestration by switchgrass. Ph.D Dissertation, Auburn 
University, AL. 78p. 
 
McLaughlin S.B., M.E. Walsh. 1998. Evaluating environmental consequences of 
producing herbaceous crops for bioenergy. Biomass and Bioenergy 14: 317-24. 
 
Muir, J.P., M.A. Sanderson, W.R. Ocumpaugh, R.M. Jones, R.L. Reed. 2001. Biomass 
production of Alamo switchgrass in response to nitrogen, phosphorus, and row 
spacing. Agronomy Journal 93: 896-901. 
 
Ocumpaugh, W., M. Hussey, J. Read, J. Muir, et al. 2003. Evaluation of switchgrass 
cultivars and cultural methods for biomass production in the south central U.S.. 
https://bioenergy.ornl.gov/pdfs/ornlsub_03_19XSY091C.pdf 
 
Raper, R.L., D.W. Reeves, J.N. Shaw, E. van Santen, P.L. Mask. 2007. Benefits of site-
specific subsoiling for cotton production in Coastal Plain soils. Soil & Tillage 
Research 96: 174-181. 
 
 
80 
 
 
Reed, R.L., M.A. Sanderson, and W.R. Ocumpaugh. 1995. Nitrogen and phosphorus 
responses of switchgrass grown for biomass. In Forage Research in Texas, 1994. 
CPR 5252 April 1995. 96-99. 
 
Sanderson, M.A., P.R. Adler. 2008. Perennial forages as second generation bioenergy 
crops. Int J Mol. Sci. 9: 768-778. 
 
Sanderson, M.A., R.L. Reed, S.B. McLaughlin, S.D. Wullschleger, B.V. Conger, D.J. 
Parrish, D.D. Wolf, C. Taliaferro, A.A. Hopkins, W.R. Ocumpaugh, M.A. Hussey, 
J.C. Read, and C.R. Tischler.1996. Switchgrass as a sustainable bioenergy crop. 
Bioresour. Tech- nol. 56: 83-93. 
 
Sanderson, M.A., R.L. Reed, W.R. Ocumpaugh, M.A. Hussey, G.VanEsbroeck, J.C. 
Read, C.R. Tischler, and F.M. Hons. 1999. Switchgrass cultivars and germplasm 
for biomass feedstock produc-tion in Texas. Bioresour. Technol. 67: 209-219. 
 
Schmer, M. R., et al. 2006. Establishment stand thresholds for switchgrass grown as a 
bioenergy crop. Crop Sci., 46: 157-161. 
 
 
81 
 
 
 
 
 
 
 
 
 
 
 
 
Table 4-1 Monthly and growing season precipitation 2007-2010. 
 
Year 
Precipitation (mm)  
Month Summer growing 
season Mar. Apr. May Jun. Jul. Aug. Sept. Oct. 
2009 244 109 262 100 75 192 148 164 1293 
2010 124 32 176 56 128 122 46 31 716 
2011 139 49 56 57 204 16 124 25 670 
Average  
(1997-2006) 181 129 92 141 118 97 104 65 927 
 
 
 
 
 
 
 
 
 
82 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Table 4-2 Cost of N per additional Mg of biomass by year and level of N fertilization. 
 
N rate (kg ha-1) Cost of N per additional Mg of biomass ($) 2009 2010 2011 
56 41.80 21.80 19.31 
112 65.00 33.36 19.15 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
83 
 
 
 
 
 
 
 
 
 
 
 
Figure 4-1 Biomass yield of Alamo switchgrass under different N rates across years.  
 
Different letters within each year indicate significant differences (P<0.10). 
 
 
 
 
 
 
 
 
 
 
 
 
 
b b b 
ab a 
ab 
a 
a 
a 
0
5
10
15
20
2009 2010 2011
0 kg N/ha 56 kg N/ha 112 kg N/ha
Above
ground
 biom
ass y
ield
 
 (Mg
 ha
-1 )
 
Year 
 
84 
 
 
 
 
 
 
 
 
 
 
 
  
Figure 4-2 Biomass yield of Alamo switchgrass sunder the same nitrogen fertilizer 
treatment over time.  
 
Different letters within each nitrogen treatment indicate differ (P<0.10). 
 
 
 
 
 
 
 
 
 
a 
a b 
a 
a b 
a 
a 
a 
0
5
10
15
20
0 56 112
2009 2010 2011
Above
ground
 biom
ass y
ield
 
 (Mg
 ha
-1 )
 
N rate (kg ha-1) 
 
85 
 
 
 
 
 
 
 
 
                                                            (a)                                                                                                  (b) 
 
Plate 4-1 Alamo switchgrass with subsoiling (a) and without subsoiling (b) in June 2011. 
 
 
 
 
 
86 
 
 
 
 
 
 
 
 
 
 
 
  
Plate 4-2 Alamo switchgrass 10 days after applying N treatments in June 2011. 
 
 
  
 
 
 
87 
 
 
 
 
CHAPTER 5    EFFECTS OF NITROGEN FERTILIZATION AND INTERSEEDING 
CRIMSON CLOVER ON BIOMASS YIELD OF ESTABLISHED SWITCHGRASS 
 
ABSTRACT 
Switchgrass (Panicum virgatum L.) has been extensively evaluated in the US as a 
potential cellulosic energy crop. ?Alamo? is one of the best switchgrass cultivars in the 
southeastern region. Nitrogen fertilizer is recognized as an important management 
practice for optimizing biomass production of switchgrass. Several studies indicated a 
positive response in biomass yield of ?Alamo? switchgrass to added nitrogen fertilizer, 
but this response varied greatly depending on climate and site history. Moreover, 
information on the effect of replacing nitrogen fertilization with intercropping a winter 
legume on switchgrass biomass production is not available. Therefore, the objective of 
this study was to evaluate the effects of nitrogen fertilization and intercropping crimson 
clover on biomass yield of switchgrass in central Alabama. Biomass yield showed a 
declining, positive response with an increase of nitrogen rate from 0 to 224 kg N ha-1. 
Average biomass yields for 0, 56 and 112 kg N ha-1 over a three-year period were 8.64, 
13.32 and 16.14Mg ha-1, respectively. Interseeding crimson clover (Trifolium incarnatum 
L.) did not increase biomass yield.  
 
Keywords: ?Alamo? switchgrass, nitrogen, winter legume, biomass yield. 
 
88 
 
 
5.1 INTRODUCTION 
Switchgrass (Panicum virgatum L.) is a native, warm-season perennial grass that 
has been selected as a model herbaceous energy crop in the US. It has wide geographic 
adaptation, high biomass yield potential, and is compatibility with conventional farm 
practices (Sanderson et al., 1996; McLaughlin and Walsh, 1998; Bransby et al., 1999). 
There are two ecotypes of switchgrass: lowland ecotypes are heat and drought 
tolerant, and suitable for the Midwest and southeastern United States, whereas upland 
ecoptypes are cold tolerant, and suitable for the Northern US (Bransby et al., 1999; 
Cassida et al., 2005 (a) and (b)). Currently, many switchgrass cultivars are commercially 
available, including two lowland types, ?Alamo? and ?Kanlow?, and six upland types, 
?Cave-in-Rock?, ?Blackwell?, ?Summer?, ?Trailblazer?, ?Pathfinder?, and ?Kansas-
Native?. In 1996 and 1999, Sanderson et al. found that biomass yields of lowland 
cultivars including Alamo switchgrass were better than upland yields in Texas and 
Virginia. Moreover, the results from a long-term cultivar trial in Alabama with the eight 
cultivars listed above also showed that lowland cultivars provided higher biomass yields 
than upland cultivars, and that Alamo switchgrass was the best cultivar with the highest 
average biomass yield of 23.4 Mg ha-1over a 20-year period (Crider, 2009; Huang, 2010), 
and that Alamo yields were not affected by rainfall or plot age. Muir et al. (2001) found 
that biomass production of Alamo switchgrass without N applied tended to decline over 
time in Texas. Several studies indicated a positive response of Alamo switchgrass yield to 
added N fertilizer in Texas and Tennessee, but different N rates were recommended for 
maximum yield production (Reed et al., 1995; Muir et al., 2001; Charles et al., 2011). 
Reed et al. found that biomass yield of Alamo switchgrass was maximized at about 224 
 
89 
 
 
kg N ha-1 in Beeville, Texas on a Windthorst fine sandy loam soil, whereas Muir et al. 
reported a maximum yield of 22.5 Mg ha-1 at 168 kg N ha-1 at Stephenville on the same 
type of soil. This reflects variation in response of Alamo yield to climate and site.  
The projected economic optimum N fertilizer level for Alamo switchgrass was 
about 120 kg N ha-1 even if maximum biomass yields occur at higher rates, since 
responses are typically quadratic when high rates are used (Ocumpaugh et al., 2003).   
Over-application of N fertilizer can cause environmental problems such as 
pollution of soil and water. These negative effects of N fertilizer might be avoided by 
inter-seeding a winter legume to supply the required N. However, no information on this 
possibility is available. Therefore, the objective of this experiment was to evaluate the 
yield response of a 2-year old ?Alamo? switchgrass stand to added N fertilizer and inter-
seeded crimson clover (Trifolium incarnatum L.) in central Alabama. 
 
5.2 MATERIALS AND METHODS 
5.2.1 Treatments and experimental design 
This experiment was located at the E.V. Smith Research Center, Plant Breeding 
Unit of the Alabama Agricultural Experiment Station near Tallassee, Alabama. Soil at the 
site was classified as a Wickham sandy loam (fine-loam, mixed, semiactive, thermic 
Typic Hapludult). The field was fallowed in the year prior to the planting of Alamo 
switchgrass.  In July 2007, Alamo seed was drilled into plots in rows 20 cm apart at a 
seeding rate of 11.3 kg ha-1. Plots had received no fertilizer or irrigation prior to the 
experiment which was laid out in a randomized complete block design with three 
treatments in 2009 (0, 56, and 112 kg N ha-1), four treatments in 2010 (0, 56, and 112 kg 
 
90 
 
 
N ha-1, and interseeded crimson clover) and six treatments in 2011 (0, 56,112, 168 and 
224 kg N ha-1, and interseeded crimson clover). Blocks and plots were separated by 1 m 
and 2 m wide alleys, respectively. Plots were 1.5 m wide and 9.0 m long. In early June 
2009, 2010 and 2011, each N treatment plot received a single application of ammonium 
nitrate at its assigned rate. Crimson clover was planted between switchgrass rows in 
separate plots in late November 2009 and 2010 after removing aboveground biomass, and 
received no N fertilizer. 
 
5.2.2 Data collection 
At the end of each growing season (October), biomass was harvested from the 
central two rows of each plot to a 5-cm stubble height with a sickle bar mower. Fresh 
biomass weight from the harvested area in each plot was measured using a hanging scale 
in the field. Biomass subsamples taken from each plot were dried at 60?C for 48 h for dry 
matter determination.  Border rows were harvested right after sampling.  
 
5.2.3 Data analysis 
Analysis of variance was conducted using SAS v9.2 PROC MIXED. Block was 
considered a random factor, while year was considered a fixed factor. The critical P-
value of 0.10 was used as cutoff for testing fixed effects, and determination of differences 
in least-squares means was based on adjusted P-value obtained by using the option 
ADJUST=SIMULATE in the LSMEANS statement. Regression analysis of biomass 
yield in 2011 against N rate was performed by using the SAS v9.2 PROC REG 
procedure. 
 
91 
 
 
To determine the economic implications of N fertilization the N cost per 
additional Mg of biomass produced by N fertilization was calculated by dividing the cost 
of fertilizer per hectare by the difference in biomass yield between fertilized and 
unfertilized switchgrass for any particular fertilization level. Based on 2010 USDA data 
for fertilizer prices (USDA-ERS, 2010), a price of $1.30 kg-1 N was assumed. Maximum 
economic yield (MEY) of Alamo switchgrass for nitrogen rates in 2011 was calculated 
when assuming biomass price at $65 and $100 Mg-1.  
 
5.3 RESULTS AND DISCUSSIONS 
5.3.1 Weather conditions 
Rainfall was close to the long-term average in the 2010 and 2011 growing 
seasons, but very high in 2009 (Table 5-1). The summer (March to October) growing 
season rainfall of 2009 was 1293 mm, which is 366 mm higher than the average of past 
10 years.  
 
5.3.2 Biomass yield 
 Biomass yield increased with level of N fertilizer in each of the three years of the 
study, but the relative effect of N fertilization varied by year, indicating a year x N level 
interaction (P<0.10) (Figures 5-1 and 5- 2). Differences in biomass response to N 
fertilization among years did not seem to be related to total growing season rainfall 
(Table 5-1).  In 2011, when the two additional levels of N fertilization were added, 
biomass yield increased quadratically with increasing N, and maximum yield of 14.9 Mg 
ha-1 was observed at an N rate of 168 kg N ha-1 (Figure 5-3). Maximum economic yields 
 
92 
 
 
were achieved at 167 and 189 kg N ha-1 when biomass prices were set at $65 and $100 
Mg-1, respectively (Table 5-2). In addition, a difference in leaf color from light green to 
dark green was also observed 10 days after N fertilization as N rates increased from 0 to 
50 kg N ha-1 (Plate 5-1), suggesting that plots that received no N fertilization were 
severely deficient in N. 
Interseeding crimson clover decreased biomass yield of Alamo switchgrass by 
30.2% in 2010, but this difference was smaller in 2011 (Figure 5-4). Possible reasons for 
this is that crimson clover may compete with switchgrass in the early part of the season 
(Plate 5-2), and/or drilling the crimson clover seed might have damaged the root system 
of the switchgrass. This suggests that investigation of the effects of a wider switchgrass 
row spacing and/or harvesting crimson clover prior to initiation of switchgrass growth in 
the spring may be justified.  
The cost of N per additional Mg of biomass produced by N fertilization decreased 
slightly from 2009 to 2010, but increased in 2011, and ranged between $11.65 and $24.19 
(Table 5-3).  
 
5.4 CONCLUSIONS 
Results from this study allowed the following conclusions to be drawn: 
 biomass yield of switchgrass increased with level of N fertilization, but the 
relative increase varied by year, was not related to rainfall or time, and 
was different from another study conducted at the same time and location, 
but on a different soil type; 
 
93 
 
 
 results suggest that if sale price of biomass was above $24.19 Mg-1, 
fertilization with N was justified from an economic point of view; and 
 interseeding crimson clover decreased biomass yield of switchgrass 
relative to the 0 kg N ha-1 control. 
 
5.5 REFERENCES 
Anderson, B., A.G. Matches. 1983. Forage yield, quality and persistence of switchgrass 
and Caucasian bluestem. Agronomy Journal 75:119-24. 
 
Bransby, D.I., J. Bouton, B. Conger, S.B. McLaughlin, W.R. Ocumpaugh, D. Parrish, K. 
Taliaferro, K. Vogel, S. Wallschleger. 1999. Developing Switchgrass as a 
Bioenergy Crop.PotNewCropNewUses. AgronSHS. 282-299. 
 
Cassida, K.A., M.A. Hussey, J.P. Muir, W.R. Ocumpaugh, J.C. Read, B.C. Venuto. 2005. 
Biofuel Component Concentrations and Yields of Switchgrass in South Central 
U.S. Environments. CropSci.SA. 45: 682-692. (a) 
 
Cassida, K.A., M.A. Hussey, J.P. Muir, W.R. Ocumpaugh, J.C. Read, B.C Venuto. 2005. 
Biomass Yield and Stand Characteristics of Switchgrass in South Central U.S. 
Environments. CropSci.SA. 45: 673-681. (b)  
 
Charles, T.G Jr., D.J. Brice, H.F. Castro, et al. 2011. Response of ?Alamo? switchgrass 
tissue chemistry and biomass to nitrogen fertilization in West Tennesses, USA. 
Agriculture, Ecosystems and Environment 140: 289-297.   
  
Crider, L. 2009. Composition and yield of eight switchgrass cultivars in 
Alabama.Masters Thesis, Auburn University, AL. 6p. 
 
  
Huang, P., D.I. Bransby, S. Sladden, E. van Santen, L. Crider. 2010. Twenty-year 
biomass yields for eight switchgrass varieties in Alabama. ASA, CSSA, and SSSA 
2010 International Annual Meetings, Oct. 31-Nov. 4, Long Beach, CA. 
 
McLaughlin, S.B., M.E. Walsh. 1998. Evaluating environmental consequences of 
producing herbaceous crops for bioenergy.Biomass and Bioenergy 14: 317-24. 
 
Muir, J.P., M.A. Sanderson, W.R. Ocumpaugh, R.M. Jones, R.L. Reed. 2001. Biomass 
production of Alamo switchgrass in response to nitrogen, phosphorus, and row 
spacing. Agronomy Journal 93: 896-901. 
 
 
94 
 
 
Ocumpaugh, W., M. Hussey, J. Read, J. Muir, et al. 2003. Evaluation of switchgrass 
cultivars and cultural methods for biomass production in the south central U.S.. 
https://bioenergy.ornl.gov/pdfs/ornlsub_03_19XSY091C.pdf 
 
Reed, R.L., M.A. Sanderson, and W.R. Ocumpaugh. 1995. Nitrogen and phosphorus 
responses of switchgrass grown for biomass. In Forage Research in Texas, 1994. CPR 
5252 April 1995: 96-99. 
 
Sanderson, M.A., R.L. Reed, S.B. McLaughlin, S.D. Wullschleger, B.V. Conger, D.J. 
Parrish, D.D. Wolf, C. Taliaferro, A.A. Hopkins, W.R. Ocumpaugh, M.A. Hussey, 
J.C. Read, and C.R. Tischler.1996. Switchgrass as a sustainable bioenergy 
crop.Bioresour. Tech- nol. 56: 83?93. 
Sanderson, M.A., R.L. Reed, W.R. Ocumpaugh, M.A. Hussey, G.VanEsbroeck, J.C. 
Read, C.R. Tischler, and F.M. Hons. 1999. Switchgrass cultivars and germplasm 
for biomass feedstock production in Texas. Bioresour. Technol. 67: 209-219. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
95 
 
 
 
 
 
 
 
 
 
 
 
Table 5-1 Monthly and growing season precipitation 2007-2010. 
 
Year 
Precipitation (mm)  
Month Summer growing 
season Mar. Apr. May Jun. Jul. Aug. Sept. Oct. 
2009 244 109 262 100 75 192 148 164 1293 
2010 124 32 176 56 128 122 46 31 716 
2011 139 49 56 57 204 16 124 25 670 
Average  
(1997-2006) 181 129 92 141 118 97 104 65 927 
 
 
 
 
 
 
 
 
 
 
 
 
96 
 
 
 
 
 
 
 
 
 
 
 
Table 5-2 Regression equations, pseudo R2, and maximum economic yield (MEY) of 
Alamo switchgrass for nitrogen treatments. 
 
Year Biomass price ($ Mg-1) Regression equation R2 MEY for nitrogen treatment (kg N ha-1) 
2011 65 y=428.6428+3.6434x-0.0109x2 0.48 167 
2011 100 y=659.4504+6.3052x-0.0167x2 0.60 189 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
97 
 
 
 
 
 
 
 
 
 
 
Table 5-3 Cost of N per additional Mg of biomass by year and level of N fertilization. 
 
N rate (kg ha-1) Cost of N per additional Mg of biomass ($) 2009 2010 2011 
56 15.93 11.65 22.82 
112 19.28 16.30 24.19 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
98 
 
 
 
 
 
 
 
 
 
 
 
Figure 5-1 Biomass yield of Alamo switchgrass under different nitrogen rates by year. 
 
Different letters within each year indicate that treatments differ (P<0.10). 
 
 
 
 
 
 
 
 
 
 
 
c 
c 
c 
b 
b 
b 
a 
a 
a 
0
5
10
15
20
25
30
2009 2010 2011
0 kg N/ha 56 kg N/ha 112 kg N/ha
Year 
Above
ground
 biom
ass y
ield
 
 (Mg
 ha
-1 )
 
 
99 
 
 
 
 
 
 
 
 
 
 
 
Figure 5-2 Biomass yield of Alamo switchgrass over time by N rate.  
 
Yields with different letters in different years within each N rate differ (P<0.10).  
 
 
 
 
 
 
 
 
 
 
 
 
 
ab 
b 
b 
a 
a 
a 
b 
b 
b 
0
5
10
15
20
25
0 56 112
2009 2010 2011
Above
ground
 biom
ass y
ield
 
 (Mg
 ha
-1 )
 
Nitrogen level (kg N ha-1) 
 
100 
 
 
 
 
 
 
 
 
 
  
 
 
 
Figure 5-3 Effect of fertilizer N rate on aboveground biomass yield of Alamo 
switchgrass in 2011. 
 
Vertical bars represent standard errors. 
*** Significant at the 0.001 probability level. 
 
 
 
 
 
 
 
 
 
 
 
y = -0.0002x2 + 0.0761x + 6.5945 
R? = 0.7506   *** 
0
5
10
15
20
0 50 100 150 200 250
Observed
Poly. (Fitted quadratic curve)
Above
ground
 biom
ass y
ield
 
 (Mg
 ha
-1 )
 
 
Nitrogen rate (kg N ha-1) 
 
101 
 
 
 
 
 
 
 
 
 
 
 
Figure 5-4 Biomass yield of Alamo switchgrass in 2010 and 2011 with no N 
fertilization and with or without interseeded crimson clover.  
 
Treatments within each year with different letters differ (P<0.10). 
 
 
 
 
 
 
 
 
 
 
 
 
a 
a 
b 
a 
0
5
10
15
2010 2011
0 kg N/ha
Crimson clover
Above
ground
 biom
ass y
ield
 
 (Mg
 ha
-1 )
 
Year 
 
102 
 
 
 
 
 
 
 
 
 
 
 
 
  
 
Plate 5-1 Alamo switchgrass 10 days after applying N treatments in June 2011. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
103 
 
 
 
 
 
 
 
 
 
 
 
Plate 5-2 Alamo switchgrass with and without interseeded crimson clover in April 
2011. 
 
 
 
 
 
 
 
 
 
 
 
104 
 
 
 
 
CHAPTER 6    EFFECTS OF HARVEST TIME AND FREQUENCY AND 
APPLICATION OF BROILER LITTER ON BIOMASS AND RHIZOME YIELD 
OF GIANT REED IN ALABAMA  
 
ABSTRACT 
Giant Reed (Arundo donax L.), a perennial rhizomatous grass native to East 
Asia, has been extensively evaluated as a dedicated cellulosic energy crop in southern 
Europe.  Besides producing large quantities of shoot biomass, giant reed also 
sequesters a large amount of carbon below the ground in its rhizomes and roots. 
Studies on giant reed indicated an inconsistent response in biomass yield to added 
nitrogen fertilizer, which probably reflects variation in yield response to climate and 
site. Moreover, no information is available on yield response of giant reed to harvest 
frequency. Therefore, the objective of this study was to evaluate the biomass yield 
response of giant reed to harvest frequency and fertilization with broiler litter, and its 
potential for soil carbon sequestration in rhizomes in central Alabama. Broiler litter 
application reduced biomass yield. Annual and biennial harvesting in winter provided 
higher biomass and rhizome yield than harvesting in summer every year, and in 
summer and winter every year. Annual biomass yield for annual and biennial 
harvesting in winter did not differ but biennial harvesting in winter will likely result in 
lower cost Mg-1. Biennial harvesting in winter sequestered 50 Mg ha-1 of carbon, and 
 
105 
 
 
apparently resulted in higher soil extractable P and K than adjacent areas in which 
bahiagrass (Paspalum notatum Flugge) was growing.  
 
Keywords: cellulosic energy crop; giant reed; aboveground biomass yield; rhizome 
yield; harvest frequency; application of broiler litter; carbon sequestration 
 
6.1 INTRODCUTION 
Giant Reed (Arundo donax L.) is a perennial rhizomatous C3 grass native to 
East Asia (Polunin and Huxley, 1987) which is grown in both grasslands and 
wetlands, and is especially well adapted to Mediterranean environments. Since giant 
reed is sterile, it must be propagated vegetatively from stem cuttings or rhizome 
pieces, or by micro-propagation. It has been extensively evaluated as a dedicated 
cellulosic energy crop in southern Europe (Vecchiet et al., 1996; Merlo et al., 1998; 
Hidalgo and Fernandez, 2001; Lewandowski et al., 2003).  Most perennial grasses 
have poor yields during the year of establishment, but giant reed may be an exception:  
a first-year yield of over 16 Mg ha-1 was reported by Angelini et al. (2005) at a 
planting density of 20,000 plants ha-1. Biomass yields are typically 20-40 Mg ha-1 yr-1 
without any fertilization after establishment (Angelini et al., 2005; Cosentino et al., 
2005; Angelini et al., 2009). Calorific value of mature giant reed biomass is about 18 
MJ kg-1 (Angelini et al., 2005). The average energy input is approximately 2% of the 
average energy output over a 12-year period (Angelini et al., 2009). Unlike most other 
grasses, giant reed possesses a lignin content of 25%, which is similar to that of wood 
(Faix et al., 1989). This makes giant reed a desirable cellulosic energy crop for solid 
 
106 
 
 
biofuel production. Giant reed can also help mitigate carbon dioxide (CO2) emissions 
from fossil fuels because rhizomes sequester carbon into the soil, although very little 
quantitative information on below-ground carbon sequestration by giant reed is 
available.  
Because of its favorable characteristics, efforts to commercialize giant reed are 
being increased in Italy, Greece, France, Spain and Portugal. However, irresponsible 
attempts to use the crop for erosion control in riparian sites in the US, such as in 
southern California and along the Rio Grande in Texas, have led to the plant getting 
out of control in these watersheds. Consequently, it is listed as an invasive weed in 
California, Hawaii, Maryland, Tennessee and Texas (Bell, 1997). This has created 
apparently exaggerated perceptions in the US that there is a high risk involved in 
developing the crop for commercial cellulosic biomass production even if it is 
propagated outside riparian areas. However, research conducted in South Australia 
(Williams and Biswas, 2009) refutes this perception.  
In Italy Angelini et al. (2005) found that the optimum time for annual 
harvesting of giant reed is immediately prior to emergence of growth in spring, but no 
information is available on the combined effects of both harvest time and frequency. 
Responses of giant reed to N fertilization have been variable: in Greece Christou et al. 
(2001) observed no response, while in Italy Angelini et al. (2005) recorded a positive 
response in young stands. Therefore, the objective of this study was to determine the 
effect of fertilization with broiler litter on biomass yield of giant reed, and the 
response of biomass and rhizome yield to harvest time and frequency.  
 
107 
 
 
 
6.2 MATERIALS AND METHODS 
6.2.1 Treatments and experimental design 
The experiment was conducted at the E.V. Smith Research Center, Plant 
Breeding Unit of the Alabama Agricultural Experiment Station near Tallassee, 
Alabama on a Wickham sandy loam (fine-loam, mixed, semiactive, thermic Typic 
Hapludult). The site was fallow prior to planting giant reed. In the spring of 1999, 
plots were disked and leveled, and 1-m stem segments of a Californian accession of 
giant reed were hand-placed end-to-end in four furrows 75 cm apart, and completely 
covered with 5-7.5 cm of soil in each plot. Plots were 3 m wide and 9 m long. All 
plots were fertilized with ammonium nitrate at a rate of 112 kg N ha-1 in May 2000. 
After establishment, broiler litter was applied to designated plots in May, 2001 and 
2003 at a rate of 112 kg N ha-1, based on measured N content of the litter. In 2004 and 
2005, plots were harvested annually but did not receive fertilizer. From 2006 to 2011 
four harvest frequency treatments were applied: summer every year, winter every 
second year, winter every year, and summer & winter every year. The experimental 
design was a completely randomized design (CRD) with subsamplings for broiler 
litter trial, and an un-replicated CRD with subsamplings for harvest time and 
frequency trial. 
 
 
108 
 
 
6.2.2 Data collection 
Biomass harvests were carried out in late October of 2001, 2002 and 2003 for 
the broiler litter experiment. For the time and frequency of harvest experiment from 
2006 to 2011, summer harvests were conducted in early August, and winter harvests 
were conducted in late October. Plants in a 1-m2 area within each plot were harvested 
by cutting 5 cm above ground level and harvested material was weighed to determine 
fresh weight. In November 2009, rhizomes in a 1-m2 area were removed from each 
plot and weighed to determine fresh weight. Subsamples of biomass and rhizomes 
from each plot were dried at 60?C for 72 h for dry matter determination, and ground 
to 1mm for analysis of carbon content using a CNS Analyzer (LECO CNS-2000 
Macro Analyzer; LECO Corp., St. Joseph, Michigan). In October 2012, soil samples 
were collected from each plot, and also from adjacent sites on which bahiagrass was 
growing. These samples were then analyzed for pH, P, K, Ca and Mg to determine 
harvest treatment effects on these soil variables.  
 
6.2.3 Data analysis  
Statistical analysis of data from both fertilization and harvest time and 
frequency experiments were conducted using SAS v9.2 PROC MIXED. In order to 
analyze the harvest time and frequency data, an upper bound of 0.5 was placed for the 
intraclass correlation coefficient (ICC) by looking at current data and plugged into test 
statistic equations, and error degrees of freedom for testing the differences among 
harvest time and frequency treatments was based on the amount of within-treatment 
 
109 
 
 
subsampling (Perrett and Higgins, 2006). The critical P-value of 0.10 was used as cutoff 
for testing fixed effects, and determination of differences in least-squares means was 
based on adjusted P-value obtained by using the option ADJUST=SIMULATE in the 
LSMEANS statement. 
 
6.3 RESULTS AND DISCUSSIONS 
6.3.1 Weather conditions 
Summer growing season (March to October) rainfall was close to the long 
term average except for 2003 and 2009 in which it was very high, and 2000 and 2007 
in which severe droughts occurred (Table 6-1). Monthly maximum and minimum air 
temperatures were close to long term averages in all years except in 2000, 2002 and 
2007: air temperatures over 40 ? were recorded in the summer of 2000 and 2007, and 
a minimum air temperature of -12 ? was recorded in the winter of 2002 (Figure 6-1). 
Mean minimum air temperature in winter was -8.8 ? and mean maximum air 
temperature in summer was 37.5 ?.   
 
6.3.2 Biomass yield 
By the time this experiment started in 2001 giant reed plants had filled in the 
spaces between the rows in which the cane had been planted in 1999. Biomass yield 
for the broiler litter treatment was not different from the unfertilized control in the 
first year of the study, but by the third year it was actually lower (Figure 6-2). This 
result was different from experiments involving chemical N fertilizer in which 
 
110 
 
 
Christou et al. (2001) observed no response to N in Greece, and in which Angelini et 
al. (2005) recorded an increase in yield in Italy. These differences might be due, in 
part, to soil and climate differences across experimental sites. The average biomass 
yield of the control treatment in 2001 and 2003 was 31.31 Mg ha-1. This high biomass 
yield achieved without N fertilizer suggests that there might be endophytes and 
beneficial soil microorganisms involved. Xu et al. (2011) found that several strains of 
bacteria isolated from giant reed exhibited strong N-fixing capability.  
There was no difference among harvest treatments in biomass yield after the 
first two years, but differences developed after four years and persisted through the 
sixth year of the study (Figure 6-3), suggesting that treatments had a cumulative effect 
(Figure 6-4). In the fourth and sixth years of the study (Figure 6-3) harvesting in 
winter every year and every second year provided higher annual biomass yields than 
harvesting in summer or in summer and winter every year., In addition, a severe 
infestation with brambles was also observed on all summer harvest plots, whereas 
there were virtually no weeds in plots that were harvested in winter (Plate 6-1). 
Clearly, even if giant reed is harvested only once a year, harvesting in summer 
reduced yield. This is likely due partly to the plant not being able to replenish energy 
and nutrients extracted from rhizomes in the first phase of the growing season under 
summer harvesting regimes. Also of importance is that there was no difference in 
annual biomass yield of giant reed when it was harvested once a year or once every 
two years in winter. This result suggests that giant reed would offer considerable 
flexibility in harvest management of commercial plantations. For example, if for any 
 
111 
 
 
reason biomass produced in a particular year cannot be used in a commercial 
operation, it can be stored in the field with little or no loss, and harvested in the 
subsequent year. Alternatively, harvesting every second year might be justified as a 
standard practice because it should have harvesting cost advantages over annual 
harvesting.   
 
6.3.3 Rhizome yield  
  Besides providing higher biomass yield, harvesting in winter every year and 
every second year also provided two to three times higher rhizome yields than 
harvesting in summer or summer and winter every year (Figure 6-5). While the 
general difference among treatments was the same for biomass and rhizome yields, 
the relative difference in rhizome yields was considerably greater than the difference 
in biomass yields. Again, this suggests that summer harvests reduce biomass yield 
largely because they restrict replenishment of rhizomes. Over an 11-year period, 
rhizome biomass yields for harvests in winter every second year and every year were 
117.10 Mg ha-1 and 93.59 Mg ha-1, respectively. Since carbon content of rhizomes 
was 42.93%, this translated into sequestration of 50.3 and 40.2 Mg ha-1 of C, 
respectively, which is 6 to 8 times higher than that observed by Ma (1999) for C 
sequestration by the roots of switchgrass. Recognizing that these data reflect C 
sequestered only in rhizomes, if C contained in roots was also added, estimates of 
total below-ground C sequestration by giant reed in this study would have been even 
 
112 
 
 
higher. It follows that these high levels of below-ground C sequestration could have 
significant economic implications in regions where C trading is active.   
Soil analyses suggest that production of giant reed over a 13-year 
experimental period decreased soil Ca and Mg, and therefore, soil pH, relative to 
adjacent bahiagrass, while P and K were increased by production of this crop (Table 
6-2). In addition, the relative differences in these variables among treatments appear 
to be related to biomass and rhizome yield. In particular, data suggest that Ca and Mg 
are removed in harvested biomass, while P and K are absorbed by roots from deep in 
the soil profile and subsequently accumulate in the rhizomes, even though some of 
these nutrients would also be removed in harvested biomass. These trends have 
important soil management implications and, therefore, suggest that more detailed 
research on this topic is justified.  
 
6.4 CONCLUSIONS 
Conclusions that can be drawn from this study include the following: 
 over a 3-year period, fertilization with broiler litter decreased the yield 
of giant reed relative to the unfertilized control; 
 harvesting giant reed once a year or once every two years in winter 
provided higher biomass yield and rhizome accumulation than 
harvesting once a year in summer or in summer and winter every year; 
 rhizome accumulation after 11 years was 117.1 and 93.6 Mg ha-1 when 
giant reed was harvested every year or every two years in winter, 
 
113 
 
 
respectively, and the related soil carbon sequestration could have 
significant economic implications if carbon trading was active; and 
 trends in soil nutrients associated with production of biomass from 
giant reed suggest that further detailed research on this topic is justified. 
 
6.5 REFERENCES 
Angelini, L.G., L. Ceccarini, E. Bonari. 2005. Biomass yield and energy balance of 
giant reeed (Arundo donax L.) cropped in central Italy as related to different 
management practices. Europ. J. Agronomy 22: 375-389. 
 
Angelini, L.G., L. Ceccarini, N.N. o Di Nasso, E. Bonari. 2009. Comparison of 
Arundo donax L. and Miscanthus?giganteus in a long-term field experiment in 
Central Italy: Analysis of productive characteristics and energy balance. 
Biomass and Bioenergy 33: 635-643. 
 
Bell, G. 1997. Ecology and management of Arundo donax, and approaches to riparian 
habitat restoration in Southern California. In: Brock, J.H., Wade M., Pysek P., 
Green D., editors. Plant invasions: studies from North America and Europe, 
p.103-113. 
 
Christou, M., M. Mardikis, E. Alexopoulou. 2001. Research on the effect of irrigation 
and nitrogen upon growth and yields of Arundo donax L. in Greece. Aspects of 
Applied Biology, Biomass and Energy Crops 65: 47-55. 
 
Cosentino, S.L., V. Copani,G.M. D?Agosta, E. Sanzone, M. Mantineo. 2005. First 
results on evaluation of Arundo donax L. clones collected in Southern Italy. 
Industrial Crops and Products 23(2): 212-222. 
 
Faix, O., D. Meier, O. Beinhof. 1989. Analysis of lignocellulose and lignines from 
Arundo donax L. and Miscanthus sinensis Andress, and hydroliquefaction of 
Miscanthus. Biomass 18: 109-126.  
 
Hidalgo, M., J. Fernandez. 2001. Biomass production of ten populations of giant reed 
(Arundo donax L.) under the environmental conditions of Madrid (Spain). In: 
Kyritsis, S., Beenackers, A.A.C.M., Helm, P., Grassi, A., Chiaramonti, D. 
(Eds.), Biomass for Energy and Industry. Proceeding of the First World 
Conference, Sevilla, Spain, 5?9 June. James and James, Science Publisher Ltd, 
London, pp. 1181?1184. 
 
114 
 
 
 
Lewandowski, I., J.M.O. Scurlock, E. Lindvall, M. Christou. 2003. The development 
and current status of perennial rhizomatous grasses as energy crops in theUSand 
Europe. Biomass Bioenergy 25: 335?361. 
 
Ma, Z.Q. 1999. Carbon sequestration by switchgrass. Ph. D Dissertation, Auburn 
University, AL. 70p. 
 
Merlo, L., B. Morgana, V. Sardo, F. La Loggia. 1998. Experiences with giant reed 
and perennial C4 grasses in Sicily. In: Kopetz, H., Weber, T., Pals, W., Chartier, 
P., Ferrero, G.L. (Eds.), Proceedings of the International Conference on 
Biomass for Energy and Industry. Wurzburg, Germany, 8?11 June. CARMEN, 
Rimpar Germany, pp. 1006?1008. 
 
Perrett, J., J. Higgins. 2006. A method for analyzing unreplicated agricultural 
experiments. Crop Sci. 46:2482-2485. 
 
Polunin, O., A. Huxley. 1987. Flowers of the Mediterranean. Hogarth Press, London.  
 
Vecchiet, M., R. Jodice, G. Schenone. 1996. Agronomic research on giant reed 
(Arundo donax L.) management system and cultivation of two different 
provenances. In: Proceedings of the Ninth European Bioenergy Conference, 
Copenhagen, 24?27 June, pp.644?648. 
 
Williams, C., T. Biswas. 2009. Salinity tolerance, nutrient needs, weed risk 
management and carbon sequestration of Arundo donax for remediation of 
highly saline wastewaters for biofuel or pulp/paper feedstock production Final 
Report Project 56/2008 to South Australian Murray Darling Basin Natural 
Resource Management Board. pp20. 
 
Xu, J., J.W. Kloepper, J. Mclnroy, C.H. Hu, R. Bonilla. 2011. Isolation and 
characterization of nitrogen-fixing and phosphate solubilizing bacteria from 
Aurndo donax L. (giant reed). In: Reddy, M.S., Wang, Q., Plant Growth-
Promoting Rhizobacteria (PGPR) for Sustainable Agriculture. Proceeding of the 
Second Asian PGPR Conference, Beijing, P.R. China, 21-24 August. pp. 409-
415. 
 
 
 
 
 
 
115 
 
 
Table 6-1 Monthly and summer growing season precipitation 1998-2011. 
 
Year 
Precipitation (mm)  
Month Summer growing 
Jan. Feb. Mar. Apr. May Jun. Jul. Aug. Sept. Oct. Nov. Dec. season 
1998           28 35  
1999 164 67 115 43 104 217 131 37 65 95 52 77 806 
2000 123 37 97 47 45 33 46 52 99 13 156 121 432 
2001 83 81 333 130 92 155 66 65 37 30 77 68 907 
2002 92 71 158 66 77 124 47 39 117 92 112 104 720 
2003 61 134 153 226 136 147 187 120 109 27 107 77 1106 
2004 51 110 19 73 96 178 62 99 147 49 134 55 723 
2005 54 113 255 185 32 39 215 87 37 45 86 77 894 
2006 112 116 80 44 78 18 93 99 103 111 150 62 627 
2007 150 75 78 51 12 29 21 83 56 75 55 94 405 
2008 111 102 77 101 64 50 126 252 19 83 93 82 772 
2009 52 105 244 109 262 100 75 192 148 164 154 276 1294 
2010 152 76 124 32 176 56 128 122 46 31 52 59 715 
2011 57 100 139 49 56 57 204 16 124 25   670 
 
 
 
 
 
 
 
 
 
116 
 
 
 
 
 
 
  
Table 6-2 Soil nutrient content data by harvest treatment. 
 
Treatments Soil pH Phosphorous Potassium Magnesium Calcium kg ha-1 
Summer every year 6.4 (0.1) a 109 (12) b 301 (37) ab 181 (20) a 717 (67) ab 
Winter every second year 4.6 (0.2) c 240 (25) a 227 (22) b 87 (11) b 341 (67) c 
Winter every year 4.6 (0.2) c 242 (25) a 219 (37) ab 93 (20) b 326 (100) c 
Summer & winter every year 5.8 (0.1) b 127 (12) b 324 (22) a 128 (11) a 479 (67) bc  
Fallow bahiagrass 6.1 (0.1) ab 121 (12) b 189 (37) b 114 (20) a 679 (12) a 
 
Values in parentheses are standard errors.  
Means within each column with different letters differ (P<0.10).   
 
 
 
 
 
 
 
 
 
117 
 
 
 
 
 
    
Figure 6-1 Monthly minimum and maximum temperatures from November 1998 to October 2011. 
 
-20
-10
0
10
20
30
40
50
No
v
Fe
b
Ma
y
Au
g
No
v
Fe
b
Ma
y
Au
g
No
v
Fe
b
Ma
y
Au
g
No
v
Fe
b
Ma
y
Au
g
No
v
Fe
b
Ma
y
Au
g
No
v
Fe
b
Ma
y
Au
g
No
v
Fe
b
Ma
y
Au
g
No
v
Fe
b
Ma
y
Au
g
No
v
Fe
b
Ma
y
Au
g
No
v
Fe
b
Ma
y
Au
g
No
v
Fe
b
Ma
y
Au
g
No
v
Fe
b
Ma
y
Au
g
No
v
Fe
b
Ma
y
Au
g
1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011
Monthly maximum air temperature Monthly minimum air temperature
Te
mper
ature
 (?
) 
Year 
 
118 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 6-2 Annual biomass yield of giant reed with or without application of broiler litter by 
year. 
 
Means within each year with different superscripts differ (P<0.10). 
 
 
 
 
 
 
 
 
 
 
 
 
a 
a a a 
a 
b 
0
10
20
30
40
50
2001 2002 2003
0 kg N/ha 112 kg N/ha
Above
ground
 biom
ass y
ield
 
 (Mg
 ha
-1 )
 
Year 
 
119 
 
 
 
 
 
 
 
 
 
 
 
Figure 6-3 Annual biomass yield of giant reed under different harvesting regimes across 
years.  
 
Means within each year with different superscripts differ (P<0.05). 
 
 
 
 
 
 
 
 
 
 
 
 
a 
b b 
a 
a 
ab 
a 
a 
a 
a 
a 
b 
0
10
20
30
40
50
60
2007 2009 2011
Summer every year Winter every second year
Winter every year Summer & winter every year
Above
ground
 biom
ass y
ield
 
 (Mg
 ha
-1 )
 
Year 
 
120 
 
 
 
 
 
 
 
 
 
 
 
Figure 6-4 Annual biomass yield of giant reed over time and harvest treatment. 
 
Means within each harvest frequency with different superscripts differ (P<0.05). 
 
 
 
 
 
 
 
 
 
 
 
 
a a a 
ab 
b 
a 
a 
a 
b 
a 
a 
b 
0
10
20
30
40
50
60
Summer every year Winter every
second year
Winter every year Summer & winter
every year
2007 2009 2011
Above
ground
 biom
ass y
ield
 
 (Mg
 ha
-1 )
 
Harvest time and frequency 
 
121 
 
 
 
 
 
 
 
 
 
Figure 6-5 Biomass yield of giant reed rhizomes under different harvesting regimes in 2009. 
 
Means with different letters differ (P<0.10). 
 
 
 
 
 
 
 
 
 
 
b 
a 
a 
b 
0
30
60
90
120
150
Summer every
year
Winter every
second year
Winter every
year
Summer &
winter every year
Rhiz
ome 
biom
ass y
ield 
(Mg
 ha
-1 )
 
Harvest frequency 
 
122 
 
 
 
 
 
 
 
(a)                                                                 (b) 
 
Plate 6-1 Giant reed in spring 2012 showing (a) infestation with brambles under summer harvesting (right) and no infestation for winter 
harvesting (left), and (b) a closer view of brambles. 
 
 
123 
 
 
 
 
CHAPTER 7    SEASONAL GROWTH PATTERNS OF GIANT REED IN ALABAMA 
 
ABSTRACT 
Giant reed (Arundo donax) has been extensively evaluated for biomass production in 
southern Europe, with an emphasis on management practices, development of new cultivars, 
and determining differences among existing cultivars. Even though detailed information on 
the growth patterns of giant reed would assist in development of improved management 
practices, this information is not available. Therefore, the objective of this study was to 
describe the seasonal growth pattern of giant reed in Alabama. Changes in both plant height 
and biomass yield of giant reed with time were well described by a Gompertz function. The 
fastest growing period occurred at approximately 66 d after initiation of regrowth (mid-May), 
when the absolute maximum growth rate was of 0.045 m d-1 and 0.516 Mg ha-1 d-1. After 
mid-May, the rate of growth decreased until maturation at approximately 200 d after 
initiation of regrowth (mid- to late September). The observed maximum average plant height 
and biomass yield were 5.28 m and 48.56 Mg ha-1, respectively. Yield decreased following 
maturation up to 278 d after initiation (early to mid-December) of growth in spring, partly as 
a result of leaf loss, and was relatively stable thereafter.  
 
 
124 
 
 
Keywords: giant reed; cellulosic energy crop; growth curve; Gompertz function; plant height; 
aboveground biomass yield 
 
 
7.1 INTRODUCTION 
Giant reed (Arundo donax L.) is a perennial rhizomatous C3 grass native to East Asia 
(Polunin and Huxley, 1987). It grows in both grasslands and wetlands, and occurs widely in 
Mediterranean environments. The crop is sterile, so it must be propagated vegetatively, either 
from stem cuttings or rhizome pieces, or by means of micro-propagation. Giant reed has been 
extensively evaluated as a dedicated cellulosic energy crop in southern Europe (Vecchiet et 
al., 1996; Merlo et al., 1998; Hidalgo and Fernandez, 2001; Lewandowski et al., 2003). 
Biomass yields are typically 20-40 Mg ha-1 year-1 without any fertilization after establishment 
(Angelini et al., 2005; Cosentino et al., 2005; Angelini et al., 2009). Even though detailed 
information on the growth patterns of giant reed would assist in development of improved 
management practices, this information is not available in the southeastern US. Therefore, the 
objective of this study was to describe the seasonal growth pattern of giant reed in Alabama.  
 
7.2 MATERIALS AND METHODS 
7.2.1 Treatments and experimental design 
A small plot experiment was conducted at the E.V. Smith Research Center, Plant 
Breeding Unit of the Alabama Agricultural Experiment Station near Tallassee, Alabama on a 
 
125 
 
 
Wickham sandy loam (fine-loam, mixed, semiactive, thermic Typic Hapludult). The 
experimental site was fallow prior to the planting of giant reed. In the spring of 1999, 1-m 
stem segments of a giant reed accession from California were hand-placed end-to-end in 
furrows 75 cm apart and covered with 5-7.5 cm of soil in prepared plots that were 3 m wide 
and 9 m long. Plots were fertilized with ammonium nitrate at a rate of 112 kg N ha-1 in May 
2000, but received no fertilizer in subsequent years. Biomass was harvested annually each 
winter before this study began, and rhizomes had completely filled in the spaces between 
rows to form a solid stand.  
 
7.2.2 Data collection 
Giant reed emerged in mid- and early March in 2010 and 2011, respectively. Biomass 
was harvested by hand from a 1-m2 quadrat within each of four plots at approximate 30 d 
intervals from April 2010 to February 2012, with all material from plots being harvested in 
late February of each year. Cutting height was 5 cm above ground. More harvest date 
information is presented in Table 7-2. In the second growing season, each harvest was 
conducted on a different area within each plot from the quadrats that had been harvested in 
the previous season, to avoid any impact of cutting date in the previous season on second 
season results. All harvested plant material was weighed immediately after harvesting to 
determine fresh weight in the field by using a hanging scale. Five randomly identified plants 
from each plot were used for determination of plant height, which was measured from the 
base of the stem to the collar of the highest leaf. Subsamples taken from the harvested 
 
126 
 
 
material from each plot at each harvest date were dried at 60?C for 72 h for dry matter 
determination. 
 
7.2.3 Data analysis 
Analysis of variance for biomass yield data was performed by using the SAS v9.2 
PROC MIXED procedure. This analysis was conducted by year since harvest dates were 
slightly different between years. Determination of differences in least-squares means was 
based on adjusted P-value obtained by using the option ADJUST=SIMULATE in the 
LSMEANS statement. 
Scatter diagrams of plant height and biomass yield against time were drawn for each 
year to help determine the most appropriate function to describe the data. Generalized 
logistic, Gompertz and logistic functions were tested for describing changes in plant height 
and yield with time in the first part of the year starting in March, because the scatter diagrams 
suggested a sigmoid-shaped curve during this phase of growth. In the latter part of the year 
yield decreased steadily with time, so this suggested use of a linear function.  
Model fitting and parameter estimation of generalized logistic, Gompertz and logistic 
functions were performed by using the SAS v9.2 PROC NLIN procedure. Selection of the 
best fitting function was done based on the mean square error (MSE) rather than the residual 
sum of squares (RSS,) since the MSE also takes into account the number of parameters in the 
models.  
 
 
127 
 
 
7.3 RESULTS AND DISCUSSIONS 
Precipitation and temperature data are presented in Table 7-1 and Figure 7-1, 
respectively. Growing season rainfall (March to October) in both years was slightly below the 
average growing season rainfall from 1990 to 2009. Mean minimum air temperature in mid-
winter was -8.8 ? and mean maximum air temperature in mid-summer was 37.5 ?.   
Recognizing that experimental plots received no fertilizer and that giant reed is a C3 
species, growth rates and yields recorded for giant reed in this study were remarkably high: 
maximum yield was 47.11 Mg ha-1 and 48.56 Mg ha-1 in September of 2010 and 2011, 
respectively. In contrast, yields of unfertilized Alamo switchgrass during the same period and 
at the same location were 11.55 and 6.80 Mg ha-1 in 2010 and 2011, respectively. Biomass 
yield for consecutive harvests differed in the first three months of each year, but this 
difference was reduced or eliminated as maturity was reached and as yield declined in the 
latter part of the year (Table 7-2). 
A Gompertz function provided the best fit for changes in plant height with time, 
probably because the data were distinctly asymmetrical. Since no difference was detected 
between years, data from the two years were pooled. The resultant model is presented in 
Figure 7-2, based on model parameters as follows:  
 
       
 
 
128 
 
 
According to this model, an absolute maximum growth rate of 0.045 m d-1 or 0.32 m 
week-1 occurred 62 d after initiation of growth (mid-May) and at a plant height of 1.89 m 
(Figure 7-3). The rate of growth then started to decrease over time until maturity 
approximately 200 d after emergence (mid- to late September).  
Other studies have shown that growth of many annuals, such as corn and wheat are 
better described by a  logistical curve than by a Gompertz curve (Katsadonis et al., 1997; 
Karadavut et al., 2008), indicating that the data were distinctly symmetrical. Unlike these 
annual crops, but in agreement with the findings of another study on giant reed and 
miscanthus conducted in central Italy (Nassi o Di Nasso et al., 2011), a Gompertz function 
provided the best description of changes in biomass yield of giant reed with time until 
maturity in this study, and thereafter a linear function was used to describe the subsequent 
decline in yield. Again, since no difference was detected between years, data from the two 
years were pooled. The resultant model is presented in Figure 7-4, based on model 
parameters as follows:  
 
       
 
According to this model, inflection point was predicted on day 66 (mid-May) after 
initiation of growth, when biomass yield was 17.78 Mg ha-1 (Figure 7-5). At this inflection 
point, relative growth rate for biomass yield was 0.0293 Mg ha-1 d-1, which is very close to 
the findings by Nassi o Di Na in central Italy (Nassi o Di Nasso et al., 2011), and absolute 
 
129 
 
 
maximum growth rate was 0.516 Mg ha-1 d-1 or 3.61 Mg week-1.  The rate of growth 
subsequently decreased over time until maturation at approximately 200 d after emergence 
(mid- to late September) when a maximum yield of 46.94 Mg ha-1 was reached. After this 
point yield decreased steadily at a rate of 0.1069 Mg ha-1 d-1, or 0.75 Mg ha-1week-1, probably 
due mainly to leaf loss (Plate 7-1) and possibly translocation of nutrients from shoots to 
rhizomes. 
The asymmetrical nature of the growth curve of giant reed reflects extremely rapid 
growth following emergence, and attainment of the maximum growth rate within a third (66 
d) of the time it takes to reach maximum yield (200 d). This pattern is probably due to 
existence of an extensive permanent root system, and stored energy and nutrients in the very 
large rhizomes of giant reed, which facilitate rapid growth in the early part of the season. 
Therefore, while results from this study indicate that maximum yield is attained in mid- to 
late September, annual harvesting at this time might reduce long-term yields. Results from a 
companion study support this view by demonstrating that yield of giant reed is sensitive to 
time of harvest. Consequently, unless additional research indicates otherwise, harvesting 
giant reed after it reaches dormancy (November or December) will likely ensure the highest 
sustainable yields, even though this will result in approximately 6 to 9% reduction in short-
term yield when compared to harvesting in mid- to late September. 
 
7.4 CONCLUSIONS 
The following conclusions can be drawn from this study: 
 
130 
 
 
 recognizing that no fertilizer was applied to giant reed plots in this study,  
recorded growth rates and yields were extremely high; 
 the growth pattern of giant reed in Alabama is distinctly asymmetrical; 
 maximum growth rate is achieved approximately 60 d after emergence (mid-
May); 
 maximum yield is attained approximately 200 day after emergence (mid- to 
late September); and  
 harvesting giant reed after initiation of dormancy in November or December 
will probably be the best strategy to ensure sustainable long-term yields, even 
though this will result in a 6-9% reduction in short term yield compared to 
harvesting in mid- to late September, but further research is needed to verify 
this projection. 
 
7.5 REFERENCES 
Angelini, L.G., L. Ceccarini, E. Bonari. 2005. Biomass yield and energy balance of giant 
reeed (Arundo donax L.) cropped in central Italy as related to different management 
practices. Europ. J. Agronomy 22, 375-389. 
 
Angelini, L.G., L. Ceccarini, N.N. o Di Nasso, E. Bonari. 2009. Comparison of Arundo 
donax L. and Miscanthus?giganteus in a long-term field experiment in Central Italy: 
Analysis of productive characteristics and energy balance. Biomass and Bioenergy 
33:635-643. 
 
Cosentino S.L., V. Copani, G.M. D?Agosta, E. Sanzone, M. Mantineo. 2005. First results on 
evaluation of Arundo donax L. clones collected in Southern Italy. Industrial Crops and 
Products 23(2):212-222. 
 
Hidalgo, M., J. Fernandez. 2001. Biomass production of ten populations of giant reed 
 
131 
 
 
(Arundo donax L.) under the environmental conditions of Madrid (Spain). In: Kyritsis, 
S., Beenackers, A.A.C.M., Helm, P., Grassi, A., Chiaramonti, D. (Eds.), Biomass for 
Energy and Industry. Proceeding of the First World Conference, Sevilla, Spain, 5-9 
June. James and James, Science Publisher Ltd, London, pp. 1181?1184. 
 
Karadavt, U., S.A. Kayi, C. Palta, and O. Okur. 2008. A growth curve application to compare 
plant heights and dry weights of some wheat varieties. American-Eurasian J. Agric. & 
Environ. Sci. 3(6): 888-892. 
 
Katsadonis, N., G. Evangelidis , S. Bladenopoulou, A. Simonis. 1997. Nutrition of corn plant: 
I. Uptake and distribution of N, P, K in plant part of three corn hybrids. Geot Sci issues 
3: 17-24. 
 
Lewandowski, I., J.M.O. Scurlock, E. Lindvall, M. Christou. 2003. The development and 
current status of perennial rhizomatous grasses as energy crops in the US and Europe. 
Biomass Bioenergy 25, 335?361. 
 
Merlo, L., B. Morgana, V. Sardo, F. La Loggia. 1998. Experiences with giant reed and 
perennial C4 grasses in Sicily. In: Kopetz, H., Weber, T., Pals, W., Chartier, P., Ferrero, 
G.L. (Eds.), Proceedings of the International Conference on Biomass for Energy and 
Industry. W?rzburg, Germany, 8?11 June. CARMEN, Rimpar Germany, pp. 1006?
1008. 
 
Nassi o Di Nasso N., N. Roncucci, F. Triana, C. Tozzini, E. Bonari. 2011. Productivity of 
giant reed (Arundo donax L.) and miscanthus (Miscanthus x giganteus Greef et Deuter) 
as energy crops: growth analysis. Italian Journal of Agronomy 6:e22: 141-147.  
 
Polunin, O., A. Huxley. 1987. Flowers of the Mediterranean. Hogarth Press, London.  
 
Regalbuto, J. R. 2009. Cellulosic biofuels-got gasoline? Science 325: 822?824.  
 
Vecchiet, M., R. Jodice, G. Schenone. 1996. Agronomic research on giant reed (Arundo 
donax L.) management system and cultivation of two different provenances. In: 
Proceedings of the Ninth European Bioenergy Conference, Copenhagen, 24?27 June, 
pp.644-648. 
 
132 
 
 
 
 
 
 
 
 
 
 
 
Table 7-1 Monthly and growing season (March to October) precipitation 2009-2011. 
 
Year 
Precipitation (mm)  
Month Growing 
Jan. Feb. Mar. Apr. May Jun. Jul. Aug. Sept. Oct. Nov. Dec. season 
2009           154 276  
2010 152 76 124 32 176 56 128 122 46 31 52 59 716 
2011 57 100 139 49 56 57 204 16 124 25   670 
Average 
(1990-
2009) 
119 120 169 106 85 109 126 103 91 85 115 146 875 
 
 
 
 
 
 
 
 
133 
 
 
 
 
 
 
 
Table 7-2 Biomass yield of giant reed at different harvest times in 2010 and 2011 growing seasons. 
 
Harvest date Day after emergence Biomass yield (Mg ha-1) Harvest date Day after emergence Biomass yield (Mg ha-1) 
04/15/2010 36 3.81?1.71d 04/15/2011 44 4.09?0.99e 
05/14/2010 65 21.10?1.71c 05/19/2011 78 24.98?0.99d 
06/14/2010 96 31.07?1.71b 06/15/2011 105 32.01?0.99c 
07/15/2010 127 40.78?3.44ab 07/18/2011 138 41.94?0.99b 
08/16/2010 159 44.25?5.94ab 08/15/2011 166 46.80?2.93ab 
09/15/2010 189 47.11?5.94ab 09/20/2011 202 48.56?0.99a 
10/20/2010 224 42.48?5.84ab 10/21/2011 233 43.62?4.41abc 
11/15/2010 250 41.95?1.71a 12/14/2011 287 38.62?2.93abc 
12/03/2010 268 38.19?3.44ab 01/25/2012 329 32.74?2.93bcd 
01/21/2011 317 34.60?3.44ab    
02/18/2011 345 32.10?3.44ab    
 
abcde means within each column with different superscripts differ significantly (P<0.05). 
  
 
 
 
 
 
 
 
 
134 
 
 
 
 
Figure 7-1 Monthly maximum and minimum air temperatures from November 2009 to October 2011. 
 
-20
-10
0
10
20
30
40
50
Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sept Oct
2009 2010 2011
Monthly maximum air temperature
Monthly minimum air temperature
Te
mpe
ratur
e (
?)
 
Year 
 
135 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 7-2 Change in plant height of giant reed with time.  
 
Vertical bars represent standard errors.  
*** Significant at the 0.001 probability level. 
 
 
 
 
 
 
 
 
 
 
0
1
2
3
4
5
6
0 50 100 150 200 250
Observed
Fitted
Pla
nt he
ight 
(m)
 
Day after emergence 
 
  
   *** 
 
136 
 
 
 
 
 
 
 
 
 
 
 
Figure 7-3 Changes in plant height and growth rate of giant reed with time.  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
0.00
0.02
0.04
0.06
0.08
0
1
2
3
4
5
6
0 50 100 150 200 250
Predicted plant height
Growth rate
Pla
nt he
ight 
(m)
 
Gr
owth r
ate 
(m
 d-
1 )
 
Day after emergence 
 
137 
 
 
 
 
 
 
 
 
 
 
 
  
Figure 7-4 Change in biomass yield of giant reed with time.  
 
 
 
 
 
 
 
 
 
 
 
 
 
0
10
20
30
40
50
60
0 100 200 300 400
Observed
Fitted
Above
ground
 biom
ass y
ield
 (Mg
/ha)
 
Day after emergence 
   
R2adj = 0.9731   *** 
 
138 
 
 
 
 
 
 
 
 
 
  
 
Figure 7-5 Changes in biomass yield and growth rate of giant reed with time. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
0
0.2
0.4
0.6
0.8
0
10
20
30
40
50
60
0 50 100 150 200 250
Predicted biomass yield
Growth rate
Gr
owth r
ate 
(Mg
 ha
-1  
d-1
) 
Day after emergence 
Above
ground
 biom
ass y
ield
 (Mg
 ha
-1 )
 
 
139 
 
 
 
 
 
 
 
                                                                  (a)                                                                      (b) 
 
Plate 7-1 Giant reed on October 8th, 2010 (a) and November 18th, 2010 (b).