A New Spin on an Old Crop for Bioenergy: Sorghum 
 
by 
 
Alexandre Caldeira Rocateli  
 
 
 
A thesis submitted to the Graduate Faculty of 
Auburn University 
in partial fulfillment of the 
requirements for the Degree of 
Master of Science 
 
Auburn, Alabama 
August 9, 2010 
 
 
 
 
Keywords:  Cellulosic biomass, irrigation, conservation tillage, 
soil properties, biomass drying 
 
Copyright 2010 by Alexandre Caldeira Rocateli 
 
 
Approved by 
 
Randy L. Raper, Chair, Affiliate Professor of Agronomy and Soils 
Francisco J. Arriaga, Affiliate Assistant Professor of Agronomy and Soils  
Kipling S. Balkcom, Affiliate Assistant Professor of Agronomy and Soils  
David Bransby, Professor of Agronomy and Soils  
Brenda V. Ortiz, Assistant Professor of Agronomy and Soils  
 
 
 
 
 
 
ii 
 
Abstract 
 
 
According to Renewable Fuels Standard (RFS) ? Energy Policy Act of 2005, the 
U.S. must reduce foreign oil dependence, where the target is to produce 36 billion gallons 
of oil equivalent in 2022 (RFA, 2010). Cellulosic material is considered an alternative 
source for bioenergy production, because it is renewable and environmentally friendly 
(Peters and Thielman, 2008). Annual crops, such as sorghum (Sorghum bicolor L.) can be 
cultivated in current row-crop production systems, which could provide grain and 
cellulosic feedstock production in Southeastern U.S. However, the impacts of removing 
cellulosic biomass on agricultural soils must not be ignored, and sorghum biomass has 
relatively high moisture content which should be dried before transported to reduce costs.  
Different experiments were established at the E.V. Smith Research Station, Shorter, AL 
to evaluate quantity and quality of sorghum biomass production, to monitor soil impacts 
due to biomass production/removal, and determine the best approach to drying sorghum 
biomass.  Three types of sorghum: grain sorghum ? NK300 (GS), high biomass forage 
sorghum ? SS 506 (FS), and photoperiod sensitive forage sorghum - 1990 (PS) and a 
forage corn (Zea mays L.) ? Pioneer 31G65 were grown for two consecutive years (2008 
and 2009) under irrigated and non-irrigated treatments, and under two different tillage 
systems: conventional (total disked area, 0.15 m depth) and conservation tillage (in-row 
subsoiling, 0.30 m depth). The results indicated that irrigation affected aboveground dry 
matter (ADM) positively in both years, but conservation system 
iii 
 
improved ADM production only in 2009. Holocellulose, lignin and ash content 
differences among crops for both evaluated years were lower than 8.3%, 2.0% and 1.9 % 
respectively, and they were considered minor. PS was considered the best crop for ADM 
production, respectively, 26.04 and 30.13 Mg ha-1 at 18 and 24 weeks after planting in 
2008. ADM production in 2009 decreased due to leaf losses caused by Anthracnose 
(Colletotrichum graminicola) disease which affected all sorghum varieties. Furthermore, 
changes in soil characteristics were detected after 2 years of cropping. Soil organic 
carbon (SOC) increased near soil surface (0.10 ? 0.15 m), but it decreased from 0.40 ? 
0.45 m. SOC losses were higher in conventional than conservation tillage. Total nitrogen 
in soil (N) drastically increased in deep layers due to percolation. Additionally, bulk 
density (Bd) values increased at all evaluated depths. Irrigated plots had higher Bd than 
non-irrigated plots at both 0.05 ? 0.10 and 0.20 ? 0.25 m soil layers. And cone index (CI) 
values showed restrictive layers at depths of 0.15 m for conventional plots. Therefore, 
conservation tillage and photoperiod sensitive sorghum (1990) ? PS  were recommended. 
In another experiment, sorghum-sudan hybrid was harvested with two different headers 
on a self-propelled windrower:  a Massey Ferguson 9145 (sickle) and a Massey Ferguson 
9185 (disc).  The disc header was comprised of two pairs (rear/front) of metal conditioner 
rollers which used three different pressures (0, 3500, and 7000 kPa), and two different 
gaps (0 and 0.02 m). Sorghum-sudan biomass moisture content (%) was evaluated daily 
until it remained constant. Results revealed that the higher pressures and smaller gaps 
resulted in faster drying of biomass. The best settings for the disc header were ?7000 kPa 
? 0 m? or ?7000 kPa ? 0.02 m? which showed, respectively, moisture content levels of 
13.6 % and 16.8 % after 14 days.  These results indicate that proper setting of the disc 
iv 
 
header including properly setting the pressures and gaps are important to achieve 
optimum drying of sorghum biomass.
v 
 
Acknowledgments 
 
 
I would like to thank the committee members: Dr. Francisco J. Arriaga, Dr. 
Kipling S. Balkcom, Dr. Brenda V. Ortiz and Dr. David I. Bransby for all guidance 
through this project.  I am heartily grateful to Dr. Randy L. Raper, major professor of the 
advisory committee for believing in my potential and giving me the opportunity to pursue 
my goals. I would like to acknowledge Eric B. Schwab for support, advice and friendship 
during these 3 years of hard work. I thank Karlson E. Mannschreck, Morris G. Welch, 
Dexter LaGrand, Bobby Durbin and the crew at the E.V. Smith Field Crops Research 
Unit for managing the experiment and data collection.  I want to extend my gratitude to 
Dr. Juan Rodriguez, Susan E. Sladden, and Brenda H. Wood for their help with 
laboratory analysis and procedures. 
This thesis is dedicated to my parents: Luiz Antonio Rocateli and Maria Diva 
Caldeira Rocateli for unconditional love and support during all my life, to my 
grandparents: Luisa, Maria, Jose and Angelo for my absence during difficult times, and to 
my brother: Leandro who strongly handled all son and grandson?s responsibilities alone 
during my absence. 
 
 
 
 
 
 
 
vi 
 
Table of Contents 
 
 
Abstract ............................................................................................................................... ii 
Acknowledgments................................................................................................................v  
List of Tables ................................................................................................................... viii  
List of Figures .................................................................................................................... xi  
Literature Review  ...............................................................................................................1 
 1. Fossil fuels shortage and biofuels as an alternative source..................................1 
 2. Bioethanol production ..........................................................................................4 
 3. Corn and sorghum cellulosic biomass to bioenergy production ..........................5 
 4. Water availability and cellulosic biomass production .......................................10 
 5. Tillage and cellulosic biomass production .........................................................13 
 6. Relevant soil characteristics to cellulosic biomass production ..........................17 
 7. References ..........................................................................................................25 
I. Sorghum Biomass Production for Cellulosic Bioenergy under Different 
Irrigation/Tillage Systems in Southeastern U.S .....................................................37 
 
 Abstract ..................................................................................................................37 
 1. Introduction ........................................................................................................40 
 2. Material and Methods ........................................................................................42 
vii 
 
 3. Results and Discussion ......................................................................................50 
 4. Conclusions ........................................................................................................69 
 5. References ..........................................................................................................71 
II. Effect of Sorghum Biofuel Production Systems on Soil Characteristics in Southeastern 
U.S. ......................................................................................................................108 
 
 Abstract ................................................................................................................108 
 1. Introduction ......................................................................................................110 
 2. Material and Methods ......................................................................................112 
 3. Results and Discussion ....................................................................................118 
 4. Conclusions ......................................................................................................125 
 5. References ........................................................................................................127 
III. Rapidly Drying Sorghum Biomass for Potential Biofuel Production ........................175 
 Abstract ................................................................................................................175 
 1. Introduction ......................................................................................................177 
 2. Material and Methods ......................................................................................178 
 3. Results and Discussion ....................................................................................181 
 4. Conclusions ......................................................................................................184 
 5. References ........................................................................................................186 
 
 
 
 
 
 
 
 
viii 
 
List of Tables 
 
 
 
Table1-1: Results of the type 3 test of treatments and effects from PROC MIXED for rye 
dry matter (Mg ha-1) yield for 2008 and rye dry matter yield (Mg ha-1)  and 
spontaneous vegetation (Mg ha-1) in 2009  ............................................................78 
 
Table 1-2: Results of the type 3 test of treatments and effects from PROC MIXED for 
sunn hemp dry matter (Mg ha-1) yield for fall 2008 ..............................................79 
 
Table1-3: Precipitation (mm) in irrigated and non irrigated plots monitored by rain 
gauges installed in field from planting to 14 weeks after planting for                 
both years ...............................................................................................................80 
 
Table 1-4: Results of the type 3 test of treatments and effects from PROC MIXED for 
Plant population within each culture during growing season and harvest time in 
2008 and 2009 ........................................................................................................81 
 
Table 1-5: Results of the type 3 test of treatments and effects from PROC MIXED for 
Stomatal conductance (mmol m-2 s-1) yield for 2008  ............................................82 
 
Table 1-6: Results of the type 3 test of treatments and effects from PROC MIXED for 
Stomata conductance (mmol m-2 s-1) yield for 2009  .............................................83 
 
Table 1-7: Results of the type 3 test of treatments and effects from PROC MIXED for 
Plant height (m) in 2008  .......................................................................................84 
 
Table 1-8: Results of the type 3 test of treatments and effects from PROC MIXED for 
Plant height (m) in 2009 ........................................................................................85 
 
Table 1-9: Results of the type 3 test of treatments and effects from PROC MIXED for 
Aboveground dry matter (Mg ha-1) for 2008 and 2009  ........................................86 
 
Table 1-10: Results of the type 3 test of treatments and effects from PROC MIXED for P, 
K, Ca, and Mg aboveground dry matter uptake (mg kg-1) for all sampling periods 
in 2008  ..................................................................................................................87 
 
Table 1-11: Results of the type 3 test of treatments and effects from PROC MIXED for P, 
K, Ca, and Mg aboveground dry matter uptake (mg kg-1) for all sampling periods 
in 2009 ...................................................................................................................88
ix 
 
Table 1-12: Results of the type 3 test of treatments and effects from PROC MIXED for 
Cu, Fe, and Zn aboveground dry matter uptake (mg kg-1) for all sampling periods 
in 2009 ...................................................................................................................89 
 
Table 1-13: Results of the type 3 test of treatments and effects from PROC MIXED for 
Cu, Fe, and Zn aboveground dry matter uptake (mg kg-1) for all sampling periods 
in 2009 ...................................................................................................................90 
 
Table 1-14: Results of the type 3 test of treatments and effects from PROC MIXED for 
corn grain dry matter (Mg ha-1) yield for 2008 and 2009  .....................................91 
 
Table 1-15: Results of the type 3 test of treatments and effects from PROC MIXED for P, 
K , Ca and Mg corn grain uptake (mg kg-1) for all sampling periods in 2008 and 
2009........................................................................................................................92 
 
Table 1-16: Results of the type 3 test of treatments and effects from PROC MIXED for 
Cu, Fe, and Zn corn grain uptake (mg kg-1) for all sampling periods in 2008 and 
2009........................................................................................................................93 
 
Table 1-17: Results of the type 3 test of treatments and effects from PROC MIXED for 
GS grain dry matter (Mg ha-1) yield for 2008 and 2009 ........................................94 
 
Table 1-18: Results of the type 3 test of treatments and effects from PROC MIXED for P, 
K, Ca, and Mg GS grain uptake (mg kg-1) for all sampling periods in 2008 and 
2009........................................................................................................................95 
 
Table 1-19: Results of the type 3 test of treatments and effects from PROC MIXED for 
Cu, Fe, and Zn GS grain uptake (mg kg-1) for all sampling periods in 2008 and 
2009........................................................................................................................96 
 
Table 1-20: Results of the type 3 test of treatments and effects from PROC MIXED for 
Aboveground dry matter holocellulose, lignin and ash content (g kg-1) for all 
sampling periods in 2008 .......................................................................................97 
 
Table 1-21: Results of the type 3 test of treatments and effects from PROC MIXED for 
Aboveground dry matter holocellulose, lignin and ash content (g kg-1) for all 
sampling periods in 2009 .......................................................................................98 
 
Table 2-1: Comparison of Marvyn loamy sand SOC (Mg ha -1) within depth between 
2008 and 2009 (Least Square Means; LS means) ................................................131 
 
Table 2-2: Comparison of Marvyn loamy sand TN (Mg ha -1) within depth between   
2008 and 2009. P-values denote significant differences between TN          
LSmeans ...............................................................................................................132 
 
x 
 
Table 2-3: Comparison of Marvyn loamy sand bulk density (Mg m-3) within depth 
between 2008 and 2009 .......................................................................................133 
 
Table 2-4: Results of the type 3 test of treatments and effects from PROC MIXED for 
Cone index (MPa) for Marvyn loamy sandy at 0 ? 0.1 m soil layer in all sampling 
periods of 2008 and 2009. Letters denote significant differences (L.S. means 
S.E.(0.10) within treatment and sampling period) .....................................................134 
 
Table 2-5: Results of the type 3 test of treatments and effects from PROC MIXED for 
Cone index (MPa) for Marvyn loamy sandy at 0.1 ? 0.2 m soil layer in all 
sampling periods of 2008 and 2009. Letters denote significant differences (L.S. 
means S.E.(0.10) within treatment and sampling period) .........................................135 
 
Table 2-6: Results of the type 3 test of treatments and effects from PROC MIXED for 
Cone index (MPa) for Marvyn loamy sandy at 0.2 ? 0.3 m soil layer in all 
sampling periods of 2008 and 2009. Letters denote significant differences (L.S. 
means S.E.(0.10) within treatment and sampling period) .........................................136 
 
Table 2-7: Results of the type 3 test of treatments and effects from PROC MIXED for 
Cone index (MPa) for Marvyn loamy sandy at 0.3 ? 0.4 m soil layer in all 
sampling periods of 2008 and 2009. Letters denote significant differences (L.S. 
means S.E.(0.10) within treatment and sampling period) .........................................137 
 
Table 2-8: Results of the type 3 test of treatments and effects from PROC MIXED for 
Cone index (MPa) for Marvyn loamy sandy at 0.4 ? 0.5 m soil layer in all 
sampling periods of 2008 and 2009. Letters denote significant differences (L.S. 
means S.E.(0.10) within treatment and sampling period) .........................................138 
 
Table 2-9: LS means of gravimetric water content (GWC) of a Marvyn loamy sand at the 
time of Cone Index readings by depth .................................................................139 
 
Table 3-1: Settings applied in both self-propelled windrowers. Massey Ferguson 9185 
(disc header and Massey Ferguson 9145 (sickle header) .....................................187 
 
Table 3-2: Daily average temperature and precipitation during drying period (AWIS 
Weather Services, Inc., 2009) ..............................................................................188
xi 
 
List of Figures 
 
 
 
Figure 1-1: Mean monthly 2008, 2009, and long-term (1999?2009) precipitation at 
experimental location near E. V. Smith Alabama Agricultural Station ? Field 
Crop Units, Shorter, AL  ........................................................................................99 
 
Figure 1-2: Crops effect on plant height at 6, 9, 14, 18 and 24 weeks after plant in 2008. 
Vertical error bars denote significant differences ? Difference of L.S. means 
S.E.(0.10). PS: photoperiod sensitive sorghum (1990), FS: forage sorghum (SS506), 
GS: grain sorghum (NK300), Corn: Pioneer31G65. ...........................................100 
 
Figure 1-3: Crops effect on plant height at 6, 9, 14, 18 24 weeks after plant in 2009. 
Vertical error bars denote significant differences ? Difference of L.S. means 
S.E.(0.10). PS: photoperiod sensitive sorghum (1990), FS: forage sorghum (SS506), 
GS: grain sorghum (NK300), Corn: Pioneer31G65. ...........................................101 
 
Figure 1-4: Irrigation effect on aboveground dry matter (Mg ha-1) for both years. Letters 
denote significant differences ? Difference of L.S. means S.E.(0.10) means 
separation between treatments at the same year ..................................................102 
 
Figure 1-5: Tillage effect on aboveground dry matter (Mg ha-1). Letters denote significant 
differences ? Difference of L.S. means S.E.(0.10) means separation between 
treatments at the same year ..................................................................................103 
 
Figure 1-6: Crops effect on aboveground dry matter production (Mg ha-1) during 3 
different periods in 2008. Letters denote separation significant differences ? 
Difference of L.S. means S.E.(0.10) among all treatments in any period. PS: 
photoperiod sensitive sorghum (1990), FS: forage sorghum (SS506), GS: grain 
sorghum (NK300), Corn:    Pioneer31G65. .........................................................104 
 
Figure 1-7: Crops effect on aboveground dry matter production (Mg ha-1) during 3 
different periods in 2009. Letters denote significant differences ? Difference of 
L.S. means S.E.(0.10) separation among all treatments in any period. PS: 
photoperiod sensitive sorghum (1990), FS: forage sorghum (SS506), GS: grain 
sorghum (NK300), Corn: Pioneer31G65. ............................................................105
xii 
 
Figure 1-8: Crops x irrigation interaction effect on aboveground dry matter (Mg ha-1) 
during 3 different periods in 2008. Vertical error bars denote significant 
differences ? Difference of L.S. means S.E.(0.10). WAP: weeks after planting, PS: 
photoperiod sensitive sorghum (1990), FS: forage sorghum (SS506), GS: grain 
sorghum (NK300), Corn:     Pioneer31G65.  .......................................................106 
 
Figure 1-9: Crops x treatments interaction effect on aboveground dry matter (Mg ha-1) 
during 3 different periods in 2009. Vertical error bars denote significant 
differences ? Difference of L.S. means S.E.(0.10). WAP: weeks after planting, PS: 
photoperiod sensitive sorghum (1990), FS: forage sorghum (SS506), GS: grain 
sorghum (NK300), Corn:    Pioneer31G65. .........................................................107 
 
Figure 2-1: Soil organic carbon (Mg ha-1) at non trafficked middle row affected by crop 
treatments in 2009, and overall SOC before planting in 2008. Horizontal error 
bars indicate variety significant differences - Difference of L.S. Means S.E. (0.10). 
PS: photoperiod sensitive sorghum (1990), FS: forage sorghum (SS506), GS: 
grain sorghum (NK300), Corn: Pioneer31G65. ...................................................140 
 
Figure 2-2: Soil organic carbon (Mg ha-1) at non trafficked middle row affected by 
irrigation treatments in 2009, and overall SOC before planting in 2008. Horizontal 
error bars indicate irrigation significant differences - Difference of L.S. Means 
S.E. (0.10)  ..............................................................................................................141 
 
Figure 2-3: Soil organic carbon (Mg ha-1) at non trafficked middle row affected by tillage 
treatments in 2009, and overall SOC before planting in 2008. Horizontal error 
bars indicate tillage significant differences - Difference of L.S. Means S.E. (0.10) 142 
 
Figure 2-4: Total nitrogen (Mg ha-1)  at non trafficked middle row affected by variety 
treatments in 2009 and overall TN before planting in 2008. Horizontal error bars 
indicate crop significant differences - Difference of L.S. Means S.E. (0.10). PS: 
photoperiod sensitive sorghum (1990), FS: forage sorghum (SS506), GS: grain 
sorghum (NK300), Corn: Pioneer31G65. ............................................................143 
 
 Figure 2-5: Total nitrogen (Mg ha-1)  at non trafficked middle row affected by irrigation 
treatments in 2009 and overall TN before planting in 2008. Horizontal error bars 
indicate irrigation significant differences - Difference of L.S. Means S.E. (0.10) .144 
 
Figure 2-6: Total nitrogen (Mg ha-1)  at non trafficked middle row affected by tillage 
treatments in 2009, and overall TN before planting in 2008. Horizontal error bars 
indicate tillage significant differences - Difference of L.S. Means S.E. (0.10) ......145 
 
Figure 2-7: Bulk density (Mg m-3) at non trafficked middle row affected by crop 
treatments in 2009 and overall Bulk density before planting in 2008. Horizontal 
error bars indicate crop significant differences - Difference of L.S. Means S.E. 
(0.10). PS: photoperiod sensitive sorghum (1990), FS: forage sorghum (SS506), GS: 
grain sorghum (NK300), Corn: Pioneer31G65. ...................................................146 
xiii 
 
Figure 2-8: Bulk density (Mg m-3) at non trafficked middle row affected by irrigation 
treatments in 2009 and overall Bulk density before planting in 2008. Horizontal 
error bars indicate irrigation significant differences - Difference of L.S. Means 
S.E. (0.10) ...............................................................................................................147 
 
Figure 2-9: Bulk density (Mg m-3) at non trafficked middle row affected by tillage 
treatments in 2009, and overall Bulk density before planting in 2008. Horizontal 
error bars indicate tillage significant differences - Difference of L.S. Means S.E. 
(0.10) .......................................................................................................................148 
 
Figure 2-10:.Contour graphs of penetration isolines using Cone Index ? CI (MPa) values 
for Marvyn loamy sand at tillage treatments in all sampling periods of 2008. 
Spring CI values were collected 1 week after planting. Fall CI values were 
collected 1 week after harvesting .........................................................................149 
 
Figure 2-11: Contour graphs of penetration isolines using Cone Index ? CI (MPa) values 
for Marvyn loamy sand at tillage treatments in all sampling periods of 2009. 
Spring CI values were collected 1 week after planting. Fall CI values were 
collected 1 week after harvesting  ........................................................................150 
 
Figure 2-12: In row soil water content at 0.10 m deep affected by crop treatments for 
Marvyn loamy sand in 2008. Vertical error bars denote significant differences ? 
Difference of L.S. means S.E.(0.10). WAP: weeks after planting, PS: photoperiod 
sensitive sorghum (1990), FS: forage sorghum (SS506), GS: grain sorghum 
(NK300), Corn:   Pioneer31G65. .........................................................................151 
 
Figure 2-13: In row soil water content at 0.20 m deep affected by crop treatments for 
Marvyn loamy sand in 2008. Vertical error bars denote significant differences ? 
Difference of L.S. means S.E.(0.10). WAP: weeks after planting, PS: photoperiod 
sensitive sorghum (1990), FS: forage sorghum (SS506), GS: grain sorghum 
(NK300), Corn:   Pioneer31G65.  ........................................................................152 
 
Figure 2-14: In row soil water content at 0.40 m deep affected by crop treatments for 
Marvyn loamy sand in 2008. Vertical error bars denote significant differences ? 
Difference of L.S. means S.E.(0.10) .......................................................................153 
 
Figure 2-15: In row soil water content at 0.60 m deep affected by crop treatments for 
Marvyn loamy sand in 2008. Vertical error bars denote significant differences ? 
Difference of L.S. means S.E.(0.10). WAP: weeks after planting, PS: photoperiod 
sensitive sorghum (1990), FS: forage sorghum (SS506), GS: grain sorghum 
(NK300), Corn:    Pioneer31G65. ........................................................................154 
 
Figure 2-16: In row soil water content at 0.10 m deep affected by irrigation treatments for 
Marvyn loamy sand in 2008. Vertical error bars denote significant differences ? 
Difference of L.S. means S.E.(0.10). WAP: weeks after planting. .........................155 
 
xiv 
 
Figure 2-17: In row soil water content at 0.20 m deep affected by irrigation treatments for 
Marvyn loamy sand in 2008. Vertical error bars denote significant differences ? 
Difference of L.S. means S.E.(0.10) WAP: weeks after planting. ..........................156 
 
Figure 2-18: In row soil water content at 0.40 m deep affected by irrigation treatments for 
Marvyn loamy sand in 2008. Vertical error bars denote significant differences ? 
Difference of L.S. means S.E.(0.10). WAP: weeks after planting. .........................157 
 
Figure 2-19: In row soil water content at 0.60 m deep affected by irrigation treatments for 
Marvyn loamy sand in 2008. Vertical error bars denote significant differences ? 
Difference of L.S. means S.E.(0.10) WAP: weeks after planting. ..........................158 
 
Figure 2-20: In row soil water content at 0.10 m deep affected by tillage treatments for 
Marvyn loamy sand in 2008. Vertical error bars denote significant differences ? 
Difference of L.S. means S.E.(0.10) WAP: weeks after planting. ..........................159 
 
Figure 2-21: In row soil water content at 0.20 m deep affected by tillage treatments for 
Marvyn loamy sand in 2008. Vertical error bars denote significant differences ? 
Difference of L.S. means S.E.(0.10) WAP: weeks after planting. ..........................160 
 
Figure 2-22: In row soil water content at 0.40 m deep affected by tillage treatments for 
Marvyn loamy sand in 2008. Vertical error bars denote significant differences ? 
Difference of L.S. means S.E.(0.10). WAP: weeks after planting.. ........................161 
 
Figure 2-23: In row soil water content at 0.60 m deep affected by tillage treatments for 
Marvyn loamy sand in 2008. Vertical error bars denote significant differences ? 
Difference of L.S. means S.E.(0.10). WAP: weeks after planting. .........................162 
 
Figure 2-24: In row soil water content at 0.10 m deep affected by crop treatments for 
Marvyn loamy sand in 2009. Vertical error bars denote significant differences ? 
Difference of L.S. means S.E.(0.10). WAP: weeks after planting, PS: photoperiod 
sensitive sorghum (1990), FS: forage sorghum (SS506), GS: grain sorghum 
(NK300), Corn:   Pioneer31G65. .........................................................................163 
 
Figure 2-25: In row soil water content at 0.20 m deep affected by crop treatments for 
Marvyn loamy sand in 2009. Vertical error bars denote significant differences ? 
Difference of L.S. means S.E.(0.10) WAP: weeks after planting, PS: photoperiod 
sensitive sorghum (1990), FS: forage sorghum (SS506), GS: grain sorghum 
(NK300), Corn:   Pioneer31G65. .........................................................................164 
 
Figure 2-26: In row soil water content at 0.40 m deep affected by crop treatments for 
Marvyn loamy sand in 2009. Vertical error bars denote significant differences ? 
Difference of L.S. means S.E.(0.10). WAP: weeks after planting, PS: photoperiod 
sensitive sorghum (1990), FS: forage sorghum (SS506), GS: grain sorghum 
(NK300), Corn:   Pioneer31G65. .........................................................................165 
 
xv 
 
Figure 2-27: In row soil water content at 0.60 m deep affected by crop treatments for 
Marvyn loamy sand in 2009. Vertical error bars denote significant differences ? 
Difference of L.S. means S.E.(0.10). WAP: weeks after planting, PS: photoperiod 
sensitive sorghum (1990), FS: forage sorghum (SS506), GS: grain sorghum 
(NK300), Corn:   Pioneer31G65. .........................................................................166 
 
Figure 2-28: In row soil water content at 0.10 m deep affected by irrigation treatments for 
Marvyn loamy sand in 2009. Vertical error bars denote significant differences ? 
Difference of L.S. means S.E.(0.10). WAP: weeks after planting ..........................167 
 
Figure2-29: In row soil water content at 0.20 m deep affected by irrigation treatments for 
Marvyn loamy sand in 2009. Vertical error bars denote significant differences ? 
Difference of L.S. means S.E.(0.10). WAP: weeks after planting ..........................168 
 
Figure 2-30: In row soil water content at 0.40 m deep affected by irrigation treatments for 
Marvyn loamy sand in 2009. Vertical error bars denote significant differences ? 
Difference of L.S. means S.E.(0.10). WAP: weeks after planting ..........................169 
 
Figure 2-31: In row soil water content at 0.60 m deep affected by irrigation treatments for 
Marvyn loamy sand in 2009. Vertical error bars denote significant differences ? 
Difference of L.S. means S.E.(0.10). WAP: weeks after planting ..........................170 
 
Figure 2-32: In row soil water content at 0.10 m deep affected by tillage treatments for 
Marvyn loamy sand in 2009. Vertical error bars denote significant differences ? 
Difference of L.S. means S.E.(0.10). WAP: weeks after planting ..........................171 
 
Figure 2-33: In row soil water content at 0.20 m deep affected by tillage treatments for 
Marvyn loamy sand in 2009. Vertical error bars denote significant differences ? 
Difference of L.S. means S.E.(0.10). WAP: weeks after planting  .........................172 
 
Figure 2-34: In row soil water content at 0.40 m deep affected by tillage treatments for 
Marvyn loamy sand in 2009. Vertical error bars denote significant differences ? 
Difference of L.S. means S.E.(0.10). WAP: weeks after planting  .........................173 
 
Figure 2-35: In row soil water content at 0.40 m deep affected by tillage treatments for 
Marvyn loamy sand in 2009. Vertical error bars denote significant differences ? 
Difference of L.S. means S.E.(0.10). WAP: weeks after planting ..........................174 
 
Figure 3-1: Massey Ferguson 9185 ? disc header (A); and Massey Ferguson 9145 ? sickle 
header (B).............................................................................................................189 
 
Figure 3-2: Sorghum moisture content (wet basis, %) for different disc header pressures 
for all sampled days .............................................................................................190 
 
Figure 3-3: Sorghum moisture content (wet basis, %) for different disc header gaps in all 
sampled days ........................................................................................................191 
xvi 
 
Figure 3-4: Sorghum moisture content (wet basis, %) for all treatments on October 16,          
2008......................................................................................................................192 
 
Figure 3-5: Sorghum moisture content (wet basis, %) for all treatments on October 23,          
2008......................................................................................................................193 
 
Figure 3-6: Sorghum moisture content (wet basis, %) for all treatments on October 30,           
2008......................................................................................................................194 
 
 
 
 
 
 
 
 
 
 
1 
 
LITERATURE REVIEW 
 
1. Fossil fuels shortage and biofuels as an alternative source 
 Fossil fuels such as coal, petroleum and natural gas are considered primary energy 
sources, accounting for over 85% of the world energy demand. Petroleum is the largest 
share of these energy sources, accounting for 40% of the world?s consumption. Oil 
demand is projected to increase by 1.7% per year from 2000 to 2030, when consumption 
will be about 2.4x109 L of oil equivalents. This continuous increment of oil demand is 
due to the economic growth that drives developing countries to become more motorized 
(IEA, 2002). 
  Therefore, the world energy demand based on fossil fuels is becoming 
troublesome, because those energy sources are non-renewable. Future shortages can be 
expected, resulting in economical and political issues among nations. The United States 
imported 582x106 L of crude oil in 2007 (EIA, 2010b), and was dependent on other 
countries to supply its primary energy demand. However, the interest in alternative 
energy supplies that can release the United States from oil dependence is increasing with 
research being focused on developing other energy source options that are able to replace 
fossil fuels, especially oil.  
  Among the alternatives to replace fossil fuels in the transportation sector, biofuels 
are an alternative source that should be carefully analyzed.  Production of biofuel results 
2 
 
in increased security of the U.S. energy supply and diminishes the effects of climate 
change which are two primary U.S. government policies (Peters and Thielman, 2008).  
The US government established the Energy Independence and Security Act of 2007 
amending the Renewable Fuels Standard (RFS) ? Energy Policy Act of 2005, in order to 
reduce foreign oil dependence, greenhouse gas emissions and provide meaningful 
economic opportunity in the U.S. The RFS target for the US is to produce 36 billion 
gallons in 2022 (RFA, 2010).  
Biofuel is defined as a liquid or gaseous fuel for the transportation sector that is 
predominantly produced from biomass (Demirbas, 2008). The Renewable Fuels Standard 
(RFS) set different definitions according to biofuel types, such as conventional biofuel, 
advanced biofuel, cellulosic biofuel and biomass-based diesel. Conventional biofuel is 
ethanol derived from corn starch and reduces greenhouse gas (GHG) emissions by 20% 
(RFA, 2010). Advanced biofuel is any renewable fuel that is derived from renewable 
biomass and reduces GHG emissions by 50%.  Cellulosic biofuel is renewable fuel from 
cellulose, hemicellulose or lignin derived from renewable biomass that reduces GHG 
emissions by 60% (RFA, 2010). Projections for 2022 predict corn (Zea mays L.) ethanol 
will be the largest biofuel produced, making 56.8x109 L available, with cellulosic ethanol 
contributing an additional 27.3x109 L (EIA, 2010a). 
 Alternative fuel sources should not only have similar performance as oil, but also 
be renewable and environmentally friendly. Among renewable fuels, ethanol appears as a 
superior alternative. The Renewable fuels Association ? RFA (2010) compared ethanol 
engine performance with a 113 octane rate against 87 for unleaded gasoline.  The studies 
revealed that ethanol reduced carbon dioxide emissions by 29%. Blending ethanol and 
3 
 
gasoline is an option to decrease petroleum dependence and Agarwal (2007) concluded 
that ethanol used as an additive to unleaded gasoline improved engine performance and 
exhaust emissions by decreasing CO and HC , however CO2 emissions increased 
marginally. 
 The main ethanol producers in 2005 were Brazil, US, and China, which produced, 
respectively, 16,500, 16,214 and 3,800 million ethanol liters and showed growth rates of 
7.1, 21.2 and 4.1% (Walter et al., 2007). In the US, the main producers are located in the 
Midwest (Iowa, Illinois, South Dakota and Minnesota). The produced ethanol is sold as 
octane enhancer or oxygenate blended with petrol covering up to 3% of the USA gasoline 
demand (RFA, 2006).  The Energy Information Administration (EIA, 2010a) listed two 
different uses of ethanol in U. S. transportation sector: E85 (fuel mixture of 85% ethanol 
and 15% gasoline) and Ethanol ? gasoline blending. The projections assume that the E85 
consumption will start with 127 quadrillions of kJ per year in 2015, reaching 928 
quadrillions of kJ per year in 2030, where the annual growth will be 33.5% during the 
period from 2006 to 2030. Therefore, the ethanol-gasoline blending is already being 
consumed, with 496 quadrillions of kJ being used in 2006. Ethanol is projected to have 
an annual growth rate of 3.7% reaching 1,192 quadrillions of kJ per year in 2030. 
 For these reasons, new paths for ethanol production should be developed in order 
to supply future demand, diminish international oil dependence and reduce GHG 
emissions.  
 
 
 
4 
 
2. Bioethanol production 
Bioethanol is the fuel derived from renewable sources of feedstock, such as wheat 
(Ttriticum aestivum L.), sugar beet (Beta vulgaris L.), corn, straw, cellulosic material, 
and others (Demirbas, 2008). Bioethanol production in the U.S. was 433 quadrillions of 
kJ in 2006, mostly from corn starch. In addition, projections are assuming that bioethanol 
from cellulose will be a new source by 2010, with a small contribution of 10.5 
quadrillions of kJ, but it will reach 612 quadrillions of kJ in 2010 when the total ethanol 
source amount is projected to be 2,121 quadrillions of kJ (EIA, 2010a). 
 Bioethanol production from cellulose is a recent technology. The conversion 
includes two processes: hydrolysis of cellulose in lignocellulosic materials to fermentable 
reducing sugars, and fermentation of the sugars to ethanol (Sun and Cheng, 2002). 
Ethanol derived from cellulosic material tends to have two advantages; environmental 
(reduced GHGs emissions) and economics (more cost effective and greater energy ratio) 
(Solomon et al., 2007). 
Any cellulosic material may be used to produce ethanol, including crop residues 
such as stover, straw, husks, etc., thus avoiding economic and social issues, e.g. food 
production shortage. Peters and Thielman (2008) concluded that biofuel production 
would have negative effects on living conditions due to increased land competition and 
implications for food market when land previously utilized for food production is 
redirected to fuel production. 
Therefore, crop residues from common commercial crops should be evaluated in 
quantity and quality of cellulosic biomass produced. In order to determine their potential, 
Kadam and McMillan (2003) suggested that collecting the total amount of residue from 
5 
 
fields may result in soil erosion and decreased organic matter. Consequently, the 
agricultural soil function diminishes. In this way, agricultural residues must be 
sustainably collected when part of the residues remains on site to conserve the soil. Kim 
and Dale (2004) listed tillage practice, topography, soil type and crop rotation as the 
factors that must be considered in order to determine the sustainable amount of residues 
that can be harvested. 
The principal component of plant tissue considered and quantified are cellulose, 
hemicellulose, lignin and carbohydrates. For example, crop residues with low lignin 
content are desirable for bioethanol production. Lignocellulosic biomass has an optimal 
conversion to biofuels when lignin is absent (low content or decomposed) (Weng et al., 
2008). 
 To evaluate crop residues from common commercial crops, several factors 
should be analyzed, not only to increase total amount of residue produced and exported 
from a field, but also to improve the crop residue quality. Among these factors, plant 
type/varieties, irrigation, tillage and plant composition are considered crucial and they 
will be discussed in detail.    
 
3. Corn and sorghum cellulosic biomass to bioenergy production. 
3.1. Corn 
 The U.S. produces 71% of the world corn crop, and is the top exporter. Corn is 
the largest crop in the U.S. in hectares produced and value (FAS, 2010). In 2007, 
37,895x103 ha of corn was planted (93,600x103 acres) and produced 332,077x103 metric 
tons of grain (13,073,893x103 bushels). The top states of production are Iowa, Illinois 
6 
 
and Nebraska. Alabama lags far behind with 137,593 ha planted that produced 562x103 
metric tons (NASS, 2010).  
Corn stover could be an income source for farmers because the residue could 
potentially be used in production of bioethanol.  The amount of corn stover produced can 
be predicted from Lindstrom et al. (1981) where the ratio of stover aboveground : corn 
harvest is approximately 1 : 1. However, just 35% of these residues should be extracted 
under conventional tillage while 70% is available under no-till farming (Lindstrom et al, 
1981). According to Kim and Dale (2004), conservation tillage requires at least 30% of 
ground cover, but 60% of ground cover should be considered due to uncertainties of 
locations. 
  In 2007, the U.S. corn stover production was estimated to be 282x106 metric tons 
of dry mass, considering 15% moisture content for the grain and using a 1 : 1 ratio of dry 
matter : corn grain. In addition, assuming a theoretical average of 41% of the produced 
corn residues could be collected from fields without prejudicial effects on environment 
(Kadam and McMillan, 2003), the cellulosic biomass produced from corn and available 
for ethanol production was estimated to be 113x106 metric tons of dry mass. 
Kim and Dale (2004) listed the composition of corn grain and corn stover as 
follows:  grain corn had 86.2% of dry matter, containing 0.60% lignin and 73.70% 
carbohydrates, against 78.5% of dry matter to corn stover, with 18.69% lignin and 
58.96% carbohydrates. Corn stover obviously has much higher lignin content than corn 
starch. For this reason, the theoretical ethanol yield for corn stover was approximately 
290 L dry ton-1 , which was lower than the theoretical ethanol yield for corn starch (460 L 
7 
 
dry ton-1) (Kim and Dale, 2004). Therefore, the potential ethanol that could be produced 
in 2007 from corn cellulosic biomass was estimated as 32,741,580x103 L.   
To produce both grain and stover that can be harvested for ethanol production, the 
selected corn variety should have the characteristics that provide good grain yield and 
high production of cellulosic biomass. However, varieties are developed for specific 
regions due to different climate and soil conditions in each region. In southeastern U.S., 
the corn variety ?Pioneer 31G65? is common, where Pioneer Hi-Bred International Inc. 
(2010) describes this variety as suitable to produce large amounts of crop residue.  This 
variety has a plant height of ?8? and a drought tolerance of ?8? on the scale of ?1? to ?9? 
with ?1? being poor and ?9? being outstanding. And the end-use segments for this variety 
are high total fermentables (Dry-Grind Ethanol) with high extractable starch (wet 
milling) and yellow food corn.  Therefore, the variety ?Pioneer 31G65? is considered a 
good choice both for grain and cellulosic biomass production. 
  
3.2. Sorghum 
The United States is considered the world?s top sorghum producer. In 2007,  
3,123x103 ha were planted with 2,754x103 ha being harvested for grain, and the 
remainder being harvested for silage, producing, respectively, 12x103 tons of grain and 
6,206x103 metric tons of biomass. The top states for sorghum grain production were 
Kansas (5.4x103 metric tons), Texas (4.1x103 metric tons), and Louisiana (602 metric 
tons). Additionally, Kansas was considered the top producer for sorghum silage 
(1,120x103 metric tons), followed by Arizona (408x103 metric tons) and California 
8 
 
(391x103 metric tons). Alabama only produced 3x103 metric tons of sorghum silage 
(NASS, 2010). 
Sorghum is considered an important crop for biomass production, and 
consequently, is an interesting source for bioethanol production from cellulose, where it 
is capable of producing total maximum dry matter yield of 27.33 tons ha-1in a short time 
(120 days) with a maximum mean daily growth rate of 22 g m-2. In contrast, corn showed 
lower values of total maximum dry matter yield, with 22.42 tons ha-1  but it had higher 
maximum mean daily growth rate (23 g m-2), reaching 51 g m-2 when fields were planted 
with higher densities (Loomis and Williams, 1963). In contrast, sorghum may not 
increase the maximum mean daily growth rate, because increased plant densities gave 
equivalent dry matter yields, and probably equivalent maximum mean daily growth rates 
(Habyarimana et al., 2004a). 
Ethanol yield from sorghum stover was considered to be 270 L dry ton-1, which is 
20 L dry ton-1 lower than corn stover ethanol yield (290 L dry ton-1) (Kim and Dale, 
2004). The lower conversion rate is due to higher contents of lignin (8%) and cellulose 
(42.4%) in sorghum residues compared to corn (7.3% of lignin and 38% of cellulose). 
Hemicellulose content was higher in corn (27.4%) than in sorghum (26%) (Amaducci et 
al., 2000). However, sorghum had higher dry matter production (26.1 tons ha-1) than corn 
(18.3 tons ha-1), especially when water was restricted (rainfed condition) (Farre and Faci, 
2006; Singh and Singh, 1995; Amaducci et al., 2000). Therefore, sorghum and corn 
residues should produce, respectively, 7,047 L ha-1 and 5,307 L ha-1 of ethanol, where 
sorghum ethanol production could be 32.78% higher than corn. 
9 
 
Many different commercial sorghum varieties and hybrids are available to 
farmers. Those different plants are basically separated into two groups: grain sorghum 
and forage sorghum. In order to reach high dry matter yields for ethanol production, it is 
appropriate to choose forage sorghum varieties/types, which are primarily selected to 
produce higher volumes of dry matter for silage. Among different forage sorghums, three 
hybrids are used in the study: (1) NK300, (2) Sucrosorgo506 (SS506) and (3) 1990. 
NK300 is highly qualified for dairy silage production, due to high grain to forage 
ratio (15-20%), with an average plant height of  2 m (6 to 7 feet), excellent standability, 
very good drought tolerance, average stalk sweetness (sugar content) and medium early 
maturity. NK300 is therefore important for both greenchop (harvesting without allowing 
the biomass to dry) and stalk grazing (Sorghum Partners, 2010).  
In contrast, SS506 is described as a late maturing sorghum, with a high plant 
height of 3.5m, very good standability, high tonnage yield performance and high stalk 
sweetness (sugar content). Thus, SS506 has limited use to greenchop, but it can be used 
for bioethanol production if biomass is dry harvested (Sorghum Partners, 2008b). 
Finally, 1990 is a photoperiod sensitive sorghum (headless), which needs less 
than 12 hours and 20 minutes of daylight to produce a grain head. It is described as 
having high plant height of 3.5 m, good standability, very high tonnage yield 
performance and average stalk sweetness (sugar content) (Sorghum Partners, 2008a). 
 
 
 
 
10 
 
4. Water availability and cellulosic biomass production 
 4.1. Corn  
In order to increase cellulosic biomass yield from corn fields, water availability 
has an important role. Roygard et al. (2002) pointed out that the main factor affecting 
corn development was water availability when comparing corn yields in different soils 
and years. However, water availability was also important for corn dry mass production.  
Pilbeam et al. (1995) concluded that higher precipitation resulted in higher corn 
transpiration efficiency and higher dry mass production. with values of transpiration 
efficiency during periods of high precipitation ( 475mm) being 109.9 kg ha-1 mm-1 and 
resulting in  dry mass production of 6.5 Mg ha-1 versus a transpiration efficiency of 67.8 
kg ha-1 mm-1 during  periods of low precipitation (158mm) resulting in dry mass 
production of 1.8 Mg ha-1. 
To increase water availability to plants, irrigation is considered an effective 
practice that increases not only corn yield, but also dry matter production, where each 
plant component (grain, cob, and stover) tends to increase when water is supplied from 
irrigation, but only up to a point where it becomes excessive (Payero et al., 2008) 
Cakir (2004) did not consider corn as a drought resistant plant, because plant 
height and leaf area were reduced due to water stress during vegetative and tasseling 
stages, where short-duration water stress during the rapid growth period was enough to 
decrease the corn dry matter weight by 28-32%. Thus, the plant height for irrigated plots 
reached 220 cm against 152 cm in non-irrigated plots. Additionally, Traore et al. (2000) 
found equivalent results, where water deficit during the vegetative period not only 
delayed leaf appearance and tasseling for 3 days, but also reduced leaf area by 33% and 
11 
 
crop height by 15%, which culminated in reduced yields for grain and biomass 
production. 
The water deficit in different periods affected corn development differently, by 
reducing grain yield and dry matter accumulation. For dry matter accumulation, Eck 
(1986) noticed that water stress beginning 41 days after planting (4 weeks deficit) 
decreased dry matter accumulation in leaves, stalks and ears, but water deficit applied 
after 55 days after planting (2 weeks deficit) only negatively affected stalk growth.  
 
4.2. Sorghum 
Cellulosic biomass production under minimal water resources is possible if plants 
that are able to produce considerable cellulosic biomass under low water supplies are 
selected. Sorghum is considered a drought resistant plant, where large amounts of 
biomass were produced in water-limited conditions and larger amounts of biomass 
produced when sorghum was irrigated (Habyarimana et al., 2004a).  
On the other hand, Amaducci et al. (2000) found that sorghum dry matter did not 
differ significantly between irrigated and non-irrigated plots. Similar results were found 
by Habyarimana et al. (2004b), where drought resistant sorghum varieties (sorghum 
landraces-hybrids) reached the same biomass production levels in both irrigated and non-
irrigated environments.  This statement can be explained by a high degree of 
heterogeneity for the sorghum types that were evaluated, because Haussmann et al. 
(2006) found hybrids to be superior when comparing grain yield and above-ground 
biomass under drought stress conditions. 
12 
 
Sorghum drought resistance has not been considered during the entire growing 
season. Sorghum?s drought resistance tended to change according to development stages, 
in which sorghum was more sensitive to drought stress in early stages (?leaf? stages), 
where the biomass productivity decreased substantially if water deficiency was applied 
(Mastrorilli et al., 1999). Their results showed that sorghum plants begin to close stomata 
after reach the wilting point (-0.4 MPa). Therefore, irrigation should be used in early 
growth stages and is necessary any time in which soil water falls below wilting point.  
Another factor that affects sorghum drought resistance is plant density.  Sorghum 
plants have the ability to compensate, where lower plant density resulted in higher leaf 
weight per plant, higher grain weight per panicle and higher tillering ability 
(Habyarimana et al., 2004a). Additionally, it was recommended that sorghum population 
be between 150,000 and 200,000 plants/ha. 
Several studies compared corn and sorghum in different water regimes, in order to 
verify the best option when water availability is limited. Sorghum was considered a better 
option than corn under uncertain and inadequate water sources, due to the fact that 
sorghum always had a higher dry matter production than corn under extensive periods of 
water deficit (Singh and Singh, 1994; Amaducci et al., 2000; Farre and Faci, 2006), 
where sorghum and corn biomass produced under rainfed plots was, respectively, 26.1 
and 18.3 t ha-1 (Amaducci et al., 2000). This statement was explained based on the 
different ability of sorghum and corn to extract water from soils, whereas corn absorbed 
more water from top soil (0 ? 0.45 m) while sorghum absorbed more water from sub-soil 
(0.45 ? 1.35 m) (Farre and Faci, 2006; Habyarimana et al., 2004a). 
13 
 
However, studies that evaluated sorghum and corn under irrigated plots, where 
water availability was not limited, showed different results. Farre and Faci (2006) 
reported that corn had higher production when both crops were evaluated in little or 
minimal water deficit. Conversely, sorghum and corn showed the same dry matter 
production under continuous irrigation (Singh and Singh, 1995). Amaducci et al. (2000) 
concluded that sorghum produced more dry matter than corn, in irrigated areas, with 26.3 
tons ha-1 for sorghum and 19.7 tons ha-1 for corn. 
 
5. Tillage and cellulosic biomass production. 
5.1. Corn 
Different tillage systems (no-tillage, minimum tillage, and conventional tillage) 
affect soil characteristics and consequently plant development. Corn plants can be 
affected not only in grain production, but also in aboveground mass production, where 
the potential bioethanol production in corn fields can also be influenced. 
Tilled soils (conventional tillage and deep tillage) showed improved soil condition 
(density and porosity) and corn plant growth (plant height, corn yield and harvest index) 
compared to no-tilled soils (Khan et al., 2007). Similar results were found by Diaz-Zorita 
(2000) where vegetative yield was higher in tillage plots with or without deep tillage 
compared with no-tillage plots. Allmaras et al. (2004) also reported that fields treated 
with both moldboard plow and chisel plow had higher corn stover yields than in fields 
with no-tillage. 
The explanations for these results were that no-tillage resulted in higher bulk 
density which culminated in reduced porosity, reduced water availability to plants and 
14 
 
reduced root development (Diaz-Zorita, 2000). On the other hand, Khan et al. (2007) 
argued that these results were a consequence of the ?transitional state?, whereby initial 
production suppression in crops happened due to conversion from a conventional to 
conservation tillage system.  
   Conversely, other studies found different results regarding corn dry matter 
production. Angers et al. (1997) concluded no significant differences among 2-year 
averages of surface tillage, ridge tillage, and moldboard plowing of silage corn yields. 
Linden et al. (2000) reported that harvest index (grain dry matter divided by total 
harvestable dry matter) for corn was not significantly different when compared among 
no-till, chisel plow, and moldboard systems. Shirani et al. (2002) concluded that reduced 
tillage (disk harrowing) and conventional tillage (moldboard plowing) showed no 
significant differences for soil properties and corn biomass production. No statistical 
differences in soil properties under different tillage systems were found, because the 
measurements were taken 5 months after tillage system application, with enough time for 
the soil physical properties to return to pre-tillage conditions.  
  Similar corn dry matter production was related to the fact that surface layers could 
offer sufficient nutrients for corn development, resulting in the same biomass production 
for fields under different tillage treatments. Therefore, deeper root development in tillage 
plots did not improve corn plant growth (Shirani et al., 2002). But, corn dry matter and 
grain yield tended to decrease after 5 years with continued no-tillage system as reported 
by Linden et al. (2000).   
 Another relevant study was performed by Al-Kaisi et al. (2005), which tested 5 
different soil associations under no till and chisel plow.  They pointed out that a no-tillage 
15 
 
system was more suitable for corn when applied in soil associations with good drainage 
because higher corn yields (6.7%) were found in these soils.  However, crop residue 
biomass production was similar under different treatments, but biomass quality showed 
significant differences, with no-tillage plots producing 13% higher N concentrations than 
chisel plow plots. 
 Finally, corn emergence and development were also studied for different tillage 
systems.  Results showed that corn emergence rate and plant height (three different days 
after emergence) were higher in moldboard plow, lower in no-till, and intermediate for 
both chisel plow and till plant. Dry matter accumulation followed the same tendency in 
the first year for plant height, but in the second year dry matter between treatments had 
no significant difference. Although, differences were found during corn development, the 
measured parameters were not significantly different at the end of the growing season 
(Al-Darby and Lowery, 1987). 
 
5.2. Sorghum 
 In order to select tillage managements that match soil conservation and high 
yields of grain and biomass, several authors studied the behavior of sorghum crops under 
different tillage systems. However, different results were reported, mostly due to different 
water content in soils and sorghum root growth. 
 Some authors, such as Pritchard et al. (2006) reported that sorghum grain yield 
was greater (6%) in conventional plots than in conservation. Sharma et al. (2005) 
reported that both sorghum grain and biomass yields were greater in conventional tillage 
(1476 kg ha-1 ) than in minimum tillage (1003 kg ha-1) under the highest nitrogen rate., 
16 
 
Sainju et al. (2006) found similar results, where sorghum fields had higher grain, biomass 
yield and nitrogen uptake under chisel till (3,900 kg ha-1 for grain and 15,100 kg ha-1 for 
biomass) and strip till (3,400 kg ha-1 for grain and 13,900 kg ha-1 for biomass) than no-till 
(2,200 kg ha-1 for grain and 8,300 kg ha-1 for biomass). 
 The lower yields found in no-tillage plots were related to a shallow rooting 
system through the soil profile in those fields (Pritchard et al., 2006), where sorghum 
plants had less soil volume for water uptake than in plots that received tillage. However, 
another study also showed that no-tillage had lower production for both grain and straw 
yields in the second crop year; but, controversially, the first year had no significant 
differences between tillage and no-tillage plots (Ouedraogo et al., 2007). 
 Other results also showed that no-tillage had similar performance as other tillage 
management systems. For example, Baumhardt and Jones (2002) concluded that no-
tillage treatments had higher sorghum grain production than stubble mulch-tillage and 
was unaffected by subsoil tillage practices (paratill, no-paratill).  Moreover, Cogle et al. 
(1997) observed no significantly statistical differences among three different tillage 
managements (zero-tillage, shallow tillage ? 10 cm, and deep tillage ? 20 cm) for both 
corn and sorghum grain yields. The aboveground mass production was not significantly 
different among those tillage managements, but sorghum aboveground mass was always 
superior than corn in any treatment applied.  
 Not only tillage, but also residue management was investigated by Sow  et al. 
(1997), who conducted a study using four different management systems: furrow disking 
(FD), conventional tillage (CT), and conservational tillage with (NT+) or without (NT-) 
wheat residue maintained on soil surface. The results showed that FD (4840 kg ha-1) had 
17 
 
the highest sorghum yield followed by NT+ (4690 kg ha-1), and both treatments NT- and 
CT had the lowest yields, respectively, 4070 kg ha-1 and 4020 kg ha-1. The authors 
explained that these different yields were due to different soil water content within the 0-
30 cm of soil layer, where more evaporation occurred under CT and NT- due to residue 
absence, which resulted in less water availability for sorghum plants. Moreover, Thomas 
et al. (1990) studied sorghum development under different tillage management systems: 
disc (D), blade (B) and no-till (Z) tillage and also had two different residue treatments 
from previous crops: retained (+) and removed (-) for seven subsequent years. It was 
observed that plant establishment was lower in Z (high residue retention on surface). The 
plant dry matter during crop growth was lower in 3 years for Z-, where the other 
treatments showed similar values. Additionally, the grain yield was not significantly 
different between D+ and B+, but it was lower in Z+. Finally, the different treatments 
affected rooting distribution, because deeper roots (1.0-1.4 m) were found in B+, Z+ and 
D-, and shallower roots found in Z- (0.1-0.2 m). 
 
6. Relevant soil characteristics to cellulosic biomass production. 
6.1. Soil organic carbon, soil nitrogen and cellulosic biomass 
  Biofuel production based on cellulosic biomass must diminish GHGs emissions 
in atmosphere by 60% (RFA, 2010). GHGs such as CO2 and NO2 can be reduced from 
atmosphere in two different ways: decreasing their emissions and/or trapping them in 
soils. Therefore, cellulosic biofuels should capture high amount of GHGs in soils when 
produced and release less amount of them when combusted. Quantifying soil organic 
carbon (SOC) and nitrogen (N) balance in soils must be considered a fundamental tool in 
18 
 
order to monitor the exchange of CO2 and NO2 between soil and atmosphere. Thus, SOC 
was considered the most powerful factor to monitor soil quality (Shukla et al., 2006; 
Brejda et al, 2000a, 2000b). SOC affected soil water content, movement and production 
(Shukla et al, 2006).  
Several studies suggested that tillage was the major factor responsible for 
releasing and trapping C and N in soils. Reicosky et al. (1995) suggested that keeping 
organic matter at surface by reducing tillage diminished erosion and carbon dioxide 
release to atmosphere. Conservation tillage increased CO2 retention up to 1.3 Mg ha-1 in 
top soil layers. Kern and Johnson (1993) also cited that no-tillage systems had a positive 
impact on soil, because it increased SOC. 
Several authors found similar results. Potter et al. (1998) concluded that SOC 
changes were related to climatic conditions and soil management. Intense tillage 
management resulted in lower SOC than no-tillage in surface soil layers. Motta et al. 
(2002) concluded that SOC and N accumulation at 0.25 m surface layer was inversely 
proportional to tillage intensity. Zibilske et al. (2002) found higher SOC and N in no-
tillage and conservation tillage treatments than conventional tillage in 0.08 m surface soil 
layer. Edwards et al. (1992) cited that SOC was increased to 56% at 0.10 to 0.15 m deep. 
Metay et al. (2007) found conservation tillage and no-tillage as the management system 
that accumulated more C in agriculture fields. 
 On the other hand, SOC and N were considered not significantly different under 
different tillage management, such as no-tillage, conservation tillage and conventional 
tillage by Angers et al. (1997) and Needelman et al. (1999). Other studies suggested that 
no-tillage and conservation tillage just redistributed SOC and N in soil, where their 
19 
 
contents increased at surface layers, but the reverse tendency was found in deep layers 
(Dick et al., 1991; Torbert et al., 1999). Kay and VandenBygaart (2002) concluded 
similar SOC trend under no-tillage and conservation tillage, but they argued that those 
surface gains may persist longer than losses in deeper layers over time.  Conservation 
tillage accumulates C and N via soil and biomass while conventional tillage just tends to 
accumulate these nutrients on soil, due to biomass incorporation followed by 
decomposition (oxidative environment) (Jabro, 2008). 
Some studies have compared SOC and N under different irrigation regimes. In 
semi-arid agricultural lands, irrigation increased SOC accumulation in soils due to higher 
C sequestration inside microaggregates (Gillabel et al., 2007).  Follet (2001) cited 
supplemental irrigation may have been beneficial, because increased water availability 
might result in soil C sequestration due to more biomass production. Similar studies 
reported no significant differences in SOC or N among different irrigation regimes 
(Churchman and Tate, 1986; Sommerfeldt et. al, 1988). However, Jabro et al. (2008) 
reported that soil CO2 flux was higher in irrigated plots, where these plots released more 
than 7 Mg CO2 ha-1 yr-1 than non-irrigated plots. Additionally, they found that no-tillage 
had lower CO2 emissions than conventional tillage due to slower plant residue 
decomposition than when incorporated. Therefore, rational irrigation and adoption of less 
intensive tillage managements were recommended to reduce soil CO2 flux. 
 
6.2 Soil compaction and cellulosic biomass. 
Several authors cited prejudicial effect of soil compaction on plant production. 
Hamza and Anderson (2005) cited that soil compaction negatively affected root growth in 
20 
 
soils, which directly reduced biomass production. Similar conclusions were reported by 
Batey and McKenzie (2006) which additionally cited that soilborne diseases may have a 
higher incidence in plants under soil compaction stress. Therefore, soil compaction is a 
crucial factor to be considered when producing cellulosic biomass which must be 
monitored to avoid yield losses. Furthermore, bulk density (Bd) and cone index (CI) were 
considered two important soil measurements that are for the express purpose of 
measuring and assessing excessive soil compaction (Raper, 2005). 
Soil water content was cited as the most important factor influencing soil 
compaction because wet soils were considered easy to compact due to reduced load 
support and increased deformation capacity (Hamza and Anderson, 2005). Raper (2005) 
also cited wet soils as an erosion factor because wet soil showed reduced soil strength 
and could be easily removed by running water.  
 
6.2.1 Bulk density and tillage 
 Bulk density was defined as soil mass per unit volume which is a useful tool to 
quantify soil compaction (Raper, 2005).  High bulk density values coincided with 
reduced soil porosity which was undesirable to plant production (Batey and McKenzie, 
2006).  Tillage has been used to reduce compacted soil profiles thus improving crop 
performance.  However, in many cases this practice showed temporary benefits because 
the soil condition after tillage combined with natural soil wetting and drying cycles 
resulted in soil densification (Mapa et al., 1986).   
Numerous authors have concluded that reduced tillage resulted in higher bulk 
density values. Yoo and Wander (2006) found high bulk densities in no-tillage fields 
21 
 
which indicated soil consolidation. Potter and Chichester (1993) reported that controlled-
traffic and no-till showed higher bulk density than conventional tillage.  Lopez-Fando et 
al. (2007) suggested that no-tillage fields needed to be zone-till subsoiled to improve soil 
physical characteristics, such as bulk density. Conversely, other studies concluded that 
no-tillage systems showed lower bulk density values than conventional tillage (Edwards 
et al., 1992; Lal et al., 1994).  Blanco-Canqui et al. (2004) also found that bulk density 
was not affected by different tillage systems (no-tillage vs. conventional). 
 A plausible explanation for these contrasting results was proposed by Raper and 
Kirby (2006). They argued that high values of bulk density in conservation tillage fields 
were found during the first few years of conversion from conventional tillage, which may 
not affect production negatively.  Long-term conservation tillage systems may ultimately 
result in reduced bulk density values. Edwards et al. (1992) reported that the low bulk 
density values found in long term conservation tillage systems were related to 
accumulation of organic matter in soil.  
 
6.2.2. Cone Index and tillage 
 Cone index was defined by ASAE standard S313.3 and EP 542 as the insertion 
force divided by the cross-sectional area of the base of the cone (ASAE Standards, 
1999a; ASAE standards, 1999b), which was considered an easy approach to quantify 
compaction in the entire soil profile.  However, cone index was greatly affected by soil 
moisture which could limit comparisons between soil conditions. Additionally, soil 
profiles with cone index values exceeding 2 MPa restricted root growth (Raper, 2005). 
22 
 
 Varsa et al. (1997) concluded that deep tillage (0.6 and 0.9 m) increased corn root 
proliferation and grain yields due to reduction in penetrometer resistance (cone index 
values). Those beneficial results were considered temporary, because soil resistance 
increased with soil consolidation eventually taking place (Raper et al., 2005; Mapa et al., 
1986). 
Moreover, conservation tillage increased cone index values after conversion from 
conventional tillage (Raper et al., 2005). Other studies showed similar results. Potter and 
Chichester (2003) reported that no tilled fields showed higher cone index than tilled 
fields. Thus, cone index values were lower at a soil depth of 0.10 m than at 0.20 m. 
However, no-tillage systems were considered suitable for cropping, because penetrometer 
resistance never reached levels which restricted root growth (2 MPa). Conversely, Lopez-
Fando et al. (2007) cited no-tillage fields with cone index values close to 3 MPa at a soil 
depth of 0.15 m which restricted root growth and reduced production.  In-row subsoiling 
was applied to decrease soil resistance from 3 to less than 1 MPa. Other studies also 
reported non-inversion deep tillage as a means to alleviate compaction when high soil 
resistance was observed in conservation fields (Schwab et al., 2002; Wells et al., 2005; 
Sojka et al., 1997). 
Wilkins et al. (2002) also affirmed that cone index values increased with reduced 
tillage. However, cone index values tended to decrease in a long term period (17 years) 
after conversion, reaching similar conditions to soils heavily tilled. 
 
 
 
23 
 
6.3. Soil water content and biomass production 
 
 Water is an essential factor for plant production because it influences all physical, 
chemical and biological activities in soil. Adequate soil water availability for plants is 
crucial to produce great amounts of cellulosic biomass. Some authors affirmed that 
reduced tillage was beneficial to soil water.   Fabrizzi et al. (2005) cited that a no-tillage 
system showed higher soil water content than minimum tillage. No- tillage accumulated 
more water in soils during critical corn growth stage (from V11 to R1). The differences in 
soil water content were attributed to low evaporation in no-tillage system. Triplett, Jr. et 
al. (1968) reported that not only water storage, but also infiltration was higher in no 
preplant tillage plots than in conventional plots. They suggested that beneficial results in 
no- tillage plots were associated with higher surface residue cover. Jones et al. (1968) 
found similar results and concluded that high soil water storage under conservation tillage 
systems resulted in higher biomass and grains yield.  
 Conversely, other studies reported higher soil water content under conventional 
than in conservation fields. Furthermore, they suggested that deep tillage was the best 
approach to improve soil water contents (Busscher and Sojka, 1987; Sojka et al., 1997; 
Lopez-Fando et al., 2007). However, Xu and Memoud (2001) reported less total available 
water content in deep tilled fields (subsoiling). They explained that it occurred due to 
reduced volume of small pores (<10?m diameter) in subsoiled zone combined with an 
increase in the number of big pores (>50?m diameter) which increased infiltration. 
Those contrasting conclusions may be explained by Buczko et al. (2006). They 
concluded that conservation tillage systems were beneficial in fine textured soils, such as 
silt loam, but was not significantly different than conventional tillage in coarse texture 
24 
 
soils, such as sandy loam. Therefore, they argued that soil texture was an important factor 
when comparing water content in soils. They further stated that the tillage effect on soil 
water behavior varied according to soil texture, and pore size.  
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
25 
 
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37 
 
I. SORGHUM BIOMASS PRODUCTION FOR CELLULOSIC BIOENERGY 
UNDER DIFFERENT IRRIGATION/TILLAGE SYSTEMS IN  
SOUTHEASTERN U.S. 
 
ABSTRACT 
Seeking renewable energy sources is necessary due to oil price fluctuations and 
environmental concerns. Sorghum (Sorghum bicolor L.) may be a reasonable alternative 
as an energy crop in the Southeastern U.S. because it is drought and nematode resistant. 
An experiment was developed to evaluate several types of sorghum for their potential as 
a bioenergy crop in Southern Alabama.  The types of sorghum evaluated were: grain 
sorghum ? NK300 (GS), high biomass forage sorghum ? SS 506 (FS), and photoperiod 
sensitive forage sorghum - 1990 (PS). These 3 different varieties and a forage corn (Zea 
mays L.) ? Pioneer 31G65 were grown for two consecutive years (2008 and 2009) under 
irrigated and non-irrigated treatments, and under two different tillage systems: 
conventional (total disked area to a depth of 0.15 m) and conservation tillage (in-row 
subsoiling to a depth of 0.30 m) which resulted in a strip-split-plot design.  Additionally, 
a rye cover crop (Secale cereale L.) and sunn hemp (Crotalaria juncea L.) was integrated 
as a treatment to maximize the amount of biomass produced and provide ground cover 
during winter months. The parameters evaluated were: rye (RDM) and sunn hemp (SDM) 
dry matter production, plant population (PP), stomatal conductance (SC), plant
38 
 
height (PH), sorghum/corn aboveground dry matter (ADM), and biomass quality 
(holocellulose, lignin, and ash). Results showed that RDM were 0.26 Mg ha-1 and 2.57 
Mg ha-1 in 2008 and 2009, respectively with the higher RDM production in 2009 a result 
of favorable weather conditions (elevated temperatures in early spring). Sunn hemp, 
which was introduced on conservation plots in 2009, could have only had a minor effect 
on rye production due to low yields (0.62 Mg ha-1).All sorghum varieties had higher dry 
aboveground dry matter production than corn. ADM production was higher in 2008 than 
2009 for all crops due to high incidence of Anthracnose (Colletotrichum graminicola) 
and Southern corn leaf blight (Bipolaris maydis) diseases in 2009. Lodging was observed 
in PS and FS plots probably due to high plant populations (> 370,000 plants ha-1). 
Irrigation affected ADM positively in both years, but conservation system improved 
ADM production only in 2009. SC data indicated that high ADM yields in irrigated and 
conservation tillage were related to good soil water content which might increase plant 
metabolism and growth. Holocellulose, lignin, and ash content differences among crops 
were lower than 8.3%, 2.0% and 1.9 %, respectively, for both years and considered 
minor. Therefore, PS was considered the best variety for cellulosic biomass (ADM) 
production which produced 26.04 and 30.13 Mg ha-1 at 18 and 24 weeks after planting 
(WAP). SS 506 ? FS could be an alternative if harvest occurred at 14 WAP (21.27 Mg 
ha-1). Plant height readings clarified that PS had slower development than other crops. 
However, its prolonged vegetative stage due to the southeastern U.S. photoperiod 
condition resulted in high cellulosic biomass production in late harvests. Thus, reduced 
plant population and crop rotation were recommended to maximize cellulosic biomass for 
bioenergy production. 
39 
 
Key words: photoperiod-sensitive, soil properties, cover crop, conservation 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
40 
 
1. INTRODUCTION 
 
Seeking renewable energy sources is necessary due to oil price fluctuations and 
environmental concerns. U.S. oil demand is projected to increase 1.7 % per year from 
2000 to 2030, where the consumption will be about 15.3 million tons of oil equivalent; 
therefore, an oil shortage is predicted in the next decades (IEA, 2002). Finding alternative 
energy sources is necessary. Cellulosic material must be considered as an alternative 
source for bioenergy production, because it can result in U.S. energy independence 
(renewable) and diminish green house gas emissions. Much emphasis has been placed on 
perennial crops for cellulosic material production, such as switchgrass (Panicum 
virgatum L.) , which is cited as a reference for comparisons and the most probable 
feedstock for bioenergy (DOE, 2005). However, negative impacts on food production are 
expected when replacing conventional crops with perennial energy crops, because the 
agricultural land previously cultivated to produce food will be converted only to produce 
bioenergy feedstock (Peters and Thielman, 2008). Conversely, annual crops can be 
cultivated in a rotation system, where conventional crops and annual energy crops can be 
cultivated on the same agricultural land producing both food and bioenergy feedstock.  
Annual crops, which have largely been ignored for bioenergy production in the 
southeastern U.S., could provide a major source of biomass for cellulosic bioenergy 
production. Additionally, central and south Alabama agriculture has been negatively 
affected by drought conditions over the last several years which has dramatically reduced 
production. For these reasons, sorghum (Sorghum bicolor L.) may be a reasonable 
alternative as an energy crop in this region, because it is considered drought resistant and 
has high cellulosic biomass potential (Habyarimana et al., 2004a). Sorghum could be 
41 
 
integrated in a conservation system as part of a crop rotation with typical cash crops, such 
as peanuts (Arachis hypogaea L.) and, cotton (Gossipyum hirsutum L.), where part of its 
biomass would be used as soil cover and any additional amount of biomass would be 
harvested for potential biofuel production.  
 Many sorghum varieties have been tested in the southwest U.S. with great success 
under irrigated conditions; however, they have not been evaluated in the Southeast under 
our dryland conditions. In addition tillage impacts on biomass production must be also 
evaluated. Conservation systems, such as in-row subsoiling, combined with a winter 
cover crop are considered an alternative to increase crop productivity in our conditions 
(Hunt et al., 2004).  
  The objectives of our study were therefore: (1) to evaluate / compare 
sorghum and corn (Zea mays L.) biomass quantity and quality for biofuel production; (2) 
to determine the effect of irrigation and potential drought tolerance of sorghum and corn 
for potential biomass production, and (3) to determine the effect of conservation and 
conventional tillage on sorghum and corn for biomass production. 
 Additionally, a rye (Secale cereale L.) cover crop is integrated as a part of 
conservation system to maximize the amount of biomass produced and provide ground 
cover for conservation treatments during the winter months. Also, a new variety of sunn 
hemp (Crotalaria juncea L.)  was included in conservation system to evaluate the 
benefits of this legume to provide additional nitrogen for the rye winter cover. 
 
 
 
42 
 
2. MATERIAL AND METHODS 
 
2.1 Site description 
A study was initiated in November of 2007 and conducted for 2 years at the E. V. 
Smith Alabama Agricultural Station ? Field Crop Unit, Shorter, AL (85?:53?50? W, 
32?:25?22? N). The location had been cropped previously with cotton for 8 years in a 
conservation tillage system following Alabama Extension System recommendations. The 
soil type was Marvyn Loamy sand (fine-loamy, kaolinitic, thermic, typic Kanhapludults). 
In order to maximize the amount of biomass produced and provide ground cover during 
the winter months, the entire field was planted with a rye cover crop before planting corn 
and sorghum. Preceding the rye was a new variety of sunn hemp to provide nitrogen. 
 
2.2. Cultural practices and Treatments 
 Rye Elbon was planted at 100 kg ha-1, in early November each year using a no-till 
drill (Great Plains Mfg. Inc., Salina, KS)1.  Rye cultural practices were based on Alabama 
Cooperative Extension System recommendations. In early April each year, the rye cover 
crop was terminated with glyphosate (N-phosphonomethyl glycine). 
 In late April of each year, starter fertilizer was applied at a rate of 14, 4, 14 and 5 
kg ha-1 of N, phosphorus (P), potassium (K) and sulfur (S), respectively according to the 
Alabama Cooperative Extension System soil test recommendations (Adams and Mitchell, 
2000).  
                                                 
1 The use of company names or trade names does not indicate endorsement by Auburn 
University or USDA ? ARS. 
 
43 
 
Two different tillage systems were implemented shortly after fertilization: 
conventional and conservation systems. Conservation plots received in-row subsoiling 
with a narrow-shanked subsoiler (KMC, Kelley Manufacturing Co., Tifton, GA) to a 
depth of 0.35-0.40 m. Conventional plots were disked/leveled using a 950 John Deere 
Disk (Deere & Company, Moline, IL) to a depth 0.15 m. Then, all four bioenergy crops,  
including grain sorghum - NK300 (GS), forage sorghum - SS506 (FS), photoperiod-
sensitive sorghum - 1990 (PS), and hybrid corn Pioneer 31G65  were seeded in rows 
spaced at 0.92 m using a John Deere 1700 XP planter (Deere & Company, Moline, IL). 
Seeding rate was established by the company?s recommendations which were 407,700 
seeds ha-1 for FS, GS and PS (Sorghum Partners 2008a, 2008b, 2010c). Corn seeding rate 
was 78,300 seeds ha-1 (Pioneer Hi-bred International Inc., 2010). Tillage and planting 
were performed with a tractor equipped with a Trimble AgGPS Autopilot automatic 
steering system (Trimble, Sunnyvale, CA), with centimeter level precision. An additional 
110 kg N ha-1 of ammonium nitrate (34%) was side dressed with a liquid applicator in 
row middles during growing season each year.   
 The irrigation plots were managed with two different regimes: non-irrigated 
(rainfed) and irrigated. In the irrigated plots, water was applied in appropriate timing and 
amounts to provide plants with good water availability during the growing season. 
Irrigation was terminated at 16 weeks after planting in both years. Alabama Cooperative 
Extension System recommendations were used to apply all insecticides (ACES, 1988). 
 Grain from grain sorghum variety and corn were harvested in late August using a 
Gleaner G combine (AGCO Company, Duluth, GA). The remaining biomass was cut and 
baled. Sunn hemp was planted at a rate of 50 kg/ha immediately after harvest using a no-
44 
 
till drill (Great Plains Mfg. Inc., Salina, KS) in all conservation tillage plots. Photoperiod 
sensitive sorghum and forage sorghum were harvested in late October. 
 
2.3. Experimental Design and Statistical Analysis 
Bioenergy crops (crops), irrigation and tillage practices were evaluated in a strip-
split plot design (factorial 4x2x2). The four crop varieties studied were GS, FS, PS, and 
corn and served as the horizontal treatments. Two irrigation regimes (irrigated and non-
irrigated) served as the vertical plots, and two tillage systems (conservation and 
conventional) served as sub-plots. 
The experimental area (84 m long by 60 m) was divided into 4 replications. Each 
replication was divided into 4 areas which were separated by borders 9.1 m long by 3.7 m 
wide in order to evaluate the bioenergy crops: PS, FS, GS and corn. Plots were divided 
into two different irrigation regimes (irrigated, non-irrigated plots), which were also 
separated by borders 9.1-m long by 3.7-m wide. Irrigation regime plots were also divided 
in two different tillage systems (conservation and conventional systems) which resulted 
in 64 experimental units 9.1-m long by 3.7-m wide. Experimental units were composed 
of 4 rows with row spacings of 0.92 m. All measurements were collected from the two 
middle rows of each experimental unit.  
 Measurements were evaluated in a strip-split plot design with four replications, 
where crops, irrigation regimes and tillage systems were considered respectively 
horizontal, vertical and sub-treatments. Bioenergy crops were randomly assigned into 
each replication, irrigation regimes were assigned into each bioenergy crop, and tillage 
systems were randomly assigned into each irrigation regime. 
45 
 
 All data were analyzed using the appropriate strip-split-plot design with PROC 
MIXED of the Statistical Analysis System (SAS) (Littel et al., 1996).  Replication and its 
interactions with bioenergy crops (crops) and irrigation regimes were considered random 
effects and treatments and other interactions considered fixed. Data were analyzed and 
discussed considering both years, except when significant year x treatment interaction 
occurred. In this case, data were analyzed by year. Treatment means were separated by the 
LSMEANS procedure (SAS Inst. Inc., Cary, NC) when protected by F-tests significant at ? 
of 0.10, and are reported as least squares means ? SE. 
 
2.4. Data Collection 
2.4.1. Cover crops 
2.4.1.1. Rye dry matter samples 
 Rye dry matter samples were collected 1 week prior to planting for both years. 
Two 0.25 m2 frames were used to sample rye aboveground biomass from each 
experimental unit. Those samples were oven-dried at 55 ?C until constant weight in order 
to determine dry biomass yield. In 2008, rye aboveground samples were collected for all 
experimental units because rye was cropped across the entire experimental area. 
However, rye was just cropped in conservation plots in 2009 where aboveground samples 
were collected.  
2.4.1.2. Sunn hemp dry matter samples  
Sunn hemp biomass samples were collected prior to planting rye in 2009. Two 
0.25 m2 frames were used to sample sunn hemp aboveground biomass from the 
conservation plots. Those samples were oven-dried at 55 ?C until constant weight in 
order to determine biomass yield.  
46 
 
2.4.2. Precipitation 
 Natural rainfall and irrigation were monitored during the growing season. Eight 
ECH2O Rain gauges - Model ECRN (Decagon Devices, Pullman, WA) were installed in 
the field. Rain gauges were combined in four sets. Each set was composed of two rain 
gauges and an ECH2O logger ? Model Em5 (Decagon Devices, Pullman, WA).These 
four sets were placed in different field locations where one rain gauge was installed in a 
irrigated plot and the other one installed in non-irrigated plot. All rain gauges were 
located 0.6 m from two middle rows. 
  
2.4.3. Plant population 
 Sorghum and corn populations were calculated from the number of plants in 1.5 
m transects on both middle rows of each plot. Plant populations were determined 6 weeks 
after planting (growing season) and 14 weeks after planting (harvest time).  
 
2.4.4. Stomatal conductance 
 A SC-1 Leaf Porometer (Decagon Devices, Pullman, WA) was used to measure 
leaf stomatal conductance on the abaxial side of unshaded apical totally expanded leaves 
of corn and sorghum. Measurements were randomly taken from 5 different plants in the 
two middle rows of each plot. Stomatal conductance data were collected at three different 
times during the growing season of each year: 6, 12 and 16 weeks after planting. 
Measurements were collected in non-cloudy days when solar radiation was maximized. 
 
 
47 
 
2.4.5. Plant height  
 Plant height measurements were taken at five different times. Two sampling 
periods were done early during the growing season at 6 and 9 weeks after planting in both 
years. In 2008, the three remaining measurements occurred at 14, 18 and 24 weeks after 
planting. However, the fourth time period in 2009 was performed 20 weeks after planting 
instead of 18 weeks due to wet conditions in early September, 2009.  
Ten different plants in the two middle rows of each plot were randomly selected, 
and those plants were measured extending the uppermost leaves. The average of those 10 
plants was used for statistical analysis.   
 
2.4.6. Aboveground dry matter  
 Aboveground biomass was harvested at 3 different times each year. In 2008, 
aboveground biomass was sampled 14, 18 and 24 weeks after planting. However, 
aboveground biomass was sampled 14, 20 and 24 weeks after planting in 2009. The delay 
in second sampling period in 2009 was caused by high precipitation during this period.  
Aboveground biomass samples for corn and GS were not collected at the 24th week in 
2008 and 2009, because those crops were terminated at 18 weeks after planting. 
 In each of the two middle rows of all experimental units, aboveground biomass 
samples were collected in a 1.5 m long section. Grains, cobs and husks were separated 
from leaves and stems. 
 The wet biomass weights of leaves and stems were recorded. Sub-samples were 
collected, ground, weighed, and dried at 55? C until constant weight was achieved. Those 
sub-samples were reweighed to estimate aboveground dry matter production. 
48 
 
   2.4.7. Grain production 
 All grain, cobs, and husks were dried at 55? C until constant weight. Corn and 
sorghum grain were shelled to remove all trash. Then, the grains were weighed and grain 
moisture recorded to estimated dry grain weight. 
 
2.4.8. Aboveground biomass and grain nutrient removal  
Dry aboveground and grain subsamples (corn and GS) were ground using a Wiley 
(Thomas Scientific, Swedesboro, NJ) and a cyclone (UDY Corp., Fort Collins, CO) mills 
to pass a 0.02 m screen.  A 0.5 g plant tissue sample (dry aboveground dry matter 
subsample) was reduced to ash in a muffle furnace at 450 ?C for 12 hours. Remaining ash 
was sequentially dissolved in 0.01 L of 1 N HNO3, and in 0.10 L 1 N HCl (Hue and 
Evans, 1986). However, a 1.0 g grain sample was pre-digested over night in 0.025 L of 
70:30 nitric : perchloric acid. Remaining solution was sequentially digested on a heated 
block under a perchloric hood at 200 0C until the volume was reduced to 0.003 L or less, 
then  0.01 L of 1 N HCl was added (John, 1972).  The total Ca, Cu, Fe, K, Mg, P, and Zn 
content in the grain samples was analyzed by argon plasma (ICAP) spectroscopy (Spectro 
CIROS, CCD side on Plasma, Germany).  
 
2.4.9. Aboveground biomass quality 
 Dry aboveground samples were ground using a Wiley (Thomas Scientific, 
Swedesboro, NJ) sample mill to pass a 0.01 m screen. Neutral Detergent fibers (NDF) 
which represents the insoluble matrix of plant cell wall (holocellulose and lignin) 
(Robbins et al., 1975) were analyzed using Robertson and Van Soest (1977) procedures. 
49 
 
A 0.5 g sub-sample was treated in 0.1 L of neutral-detergent solution, and in 0.001 to 
0.002 L of amylase enzyme solution. The sample was then filtered, washed, filtered 
under vacuum, and completely dried in a forced air oven at 105?C for 8 hours. Cell wall 
residues were weighed for calculations. 
      Acid-Detergent Fiber (ADF) which is a rough partition of the insoluble cell 
wall into acid-detergent soluble hemicellulose and the insoluble lignin and cellulose was 
determined using the Association of Official Analytical Chemists official method 
(AOAC, 1975). A 1.0 g of ground sample was dissolved in 0.1 L of acid-detergent 
solution, and boiled to keep particles in suspension and refluxed for 1 hour. The 
suspended particles were then filtered, washed, and filtered under vacuum. ADF yield 
was determined in the same manner as NDF. 
 Klason lignin was used to determine lignin content (AOAC, 1975). ADF material 
was treated with 24 N sulfuric acid for 3 hours, filtered, rinsed well and oven dried over 
night at 105 0C. Acid Detergent Lignin (ADL) residues were weighed and ashed at 450 
0C over night. The acid insoluble ash residues were weighed and subtracted from ADL to 
provide ash-free lignin estimate. 
 To estimate ash content, a 1 g sample was placed into a crucible and oven-dried 
over night at 105 0C. The residues were weighed to estimate 100% dry biomass content 
and ashed overnight at 450 0C. Afterward, the ash residues were re-weighed to calculate 
ash content (AOAC, 1975).  
 Hemicellulose was estimated as the difference between NDF and ADF. Cellulose 
was estimated as the difference between ADF and Klason lignin. Holocellulose was 
estimated as the sum of cellulose and hemicellulose. 
50 
 
3. RESULTS AND DISCUSSION 
 
3.1. Cover crops 
3.1.1. Rye dry matter    
 In 2008, rye biomass production was low (0.26 Mg ha-1 ) and did not offer good 
soil cover because an average of 1.4 Mg ha-1 of rye dry matter is required to effectively 
protect soil from erosion (Kessavalou and Walters, 1997). Rye dry matter collected for all 
experimental units before planting sorghum and corn showed that plots prepared for 
different crops were not significantly different from each other (P = 0.3427). . No 
significant rye dry matter yields were found in plots for different tillage system (P = 
0.3585) nor irrigation (P = 0.2984) treatments.  
 In 2009, rye dry matter samples collected in conservation fields before planting 
the four tested crops showed no significant differences in yields (P = 0.7167). The total 
rye dry matter production for all conservation plots was 2.58 Mg ha-1 resulting in good 
soil cover (> 1.4 Mg ha-1). Irrigation was not applied during rye development, therefore 
no rye dry matter differences between irrigation treatments were found (P = 0.4790) 
(table1-1).  
 
3.1.2. Sunn hemp dry matter 
 Sunn hemp was cultivated only in conservation plots for GS and corn because 
those two crops were terminated early enough (late August) in 2008 to establish the sunn 
hemp. The other two sorghum varieties, PS and FS were terminated later (late October) 
and was followed with rye being planted in all conservation plots.  
51 
 
 Because no irrigation was applied during sunn hemp development, no significant 
differences in dry matter were found from previous irrigation treatments (P = 0.4777). 
However, fields previously cropped with corn showed higher sunn hemp yields 8 weeks 
after planting (WAP) than fields previously cropped with GS (0.87 and 0.37 Mg ha-1, 
respectively; P = 0.0198; table 1-2). Mansoer et al. (1997) reported 5.9 Mg ha-1 of sunn 
hemp dry matter after 9 WAP when working with a different sunn hemp cultivar, which 
resulted in good soil cover, and accumulated 120 kg ha-1 of N in two different locations 
for Alabama. Similar results were found by Schomberg et al. (2007) in Piedmont and 
Coastal Pain regions of the southeastern US. Therefore, low sunn hemp biomass 
production in our fields in 2009 probably had no significant effect on rye development. 
 
3.2. Precipitation 
 Weather data collected at E. V. Smith Alabama Agricultural Station indicated 
total rainfall in 2008 and 2009 were respectively 1,160 and 1,881 mm, therefore, 2009 
had additional 721 mm of rainfall during whole year. Figure 1-1 showed rainfall mean 
monthly for 2008 and 2009 (AWIS Weather Service Inc., 2010).  Rain gauges installed in 
field from planting to 14 weeks after planting showed also higher precipitation in 2009 
during growing season. The average precipitation measured during this time in 2008 and 
2009 were, respectively 337.5 and 570.0 mm (table 1-3). 
 In 2008, irrigated plots received a water increment of 132 mm distributed in 6 
different days, such as 17 (12 mm), 31 (8 mm), 50 (24 mm), 63 (32 mm), 77 (31 mm), and 
91 (25 mm) days after planting. However, the irrigated plots were watered on only 3 days 
52 
 
during 2009 season, such as 1 day before planting (14 mm), 21 (19 mm) and 30 (24 mm) 
days after planting. 
 
3.3. Plant Population 
 During growing season, all tested crops had no significant plant population 
differences for both years (P = 0.9081). FS, GS, PS and corn showed an average of 
380,325; 375,840; 359,470 and 78,694 plants ha-1 , respectively, at 6 weeks after planting 
(WAP) for both years.  Those plant population results were similar to the company?s seed 
planting density recommendations which were between 271,800 to 407,700 plants ha-1 
for FS, GS and PS (Sorghum Partners 2008a, 2008b, 2010c). Corn recommendations 
cited that the optimum plant population for this hybrid was 78, 300 plants ha-1 (Pioneer 
Hi-bred international Inc., 2010).  
 Conventional tillage had similar populations as conservation tillage (P = 0.542), 
and irrigation had similar populations as non-irrigated fields (P = 0.8471) for both years.  
Tillage and irrigation treatments were analyzed considering all evaluated crops in both 
years. 
Significant plant population differences at 6 WAP were found within each crop 
when comparing measurements collected in growing season (6 WAP) and aboveground 
biomass sampling time (14 WAP) for both years. FS and GS had significant population 
decreases for both years. FS had a population reduction of 8.15 % (356,106 vs. 327,012 
plants ha-1) and 28.7 % (362,834 vs. 258,558 plants ha-1) in 2008 and 2009, respectively 
(P ? 0.0001). GS had a population reduction of 5.4 % (376,064 vs. 355,882 plants ha-1) 
and 22.9 % (375,616 vs. 289,729 plants ha-1) in 2008 and 2009, respectively (P ? 
0.0001). However, PS showed significant aboveground dry matter production differences 
53 
 
only in 2009 when PS plant population decreased from 362,834 to 258,558 plants ha-1 
(28.7 % reduction),  P ?0.0001. Conversely, corn did not show significant differences in 
plant population (table 1-4).   
The plant population reduction in sorghum could be partially related to plant 
lodging after 12 weeks of planting for both years. . Marsalis et al. (2010) reported no 
plant lodging and similar dry matter yield when working with 3 plant populations 
249,383 (high), 214,815 (medium) and 185,185 plants ha-1 (low) for 2 forage sorghums. 
Habyarimana et al. (2004b) concluded that sorghum plants have the compensation ability, 
where lower plant density resulted in higher leaf weight per plant, higher grain weight per 
panicle and higher tillering ability. They recommended a sorghum population be between 
150,000 and 200,000 plants ha-1. 
 
3.4. Stomatal Conductance 
 Stomatal conductance results were analyzed separately by weeks and year 
because weather variation such as temperature and solar radiation among days may affect 
stomatal conductance readings. Data collected at 8 weeks after planting (WAP) in 2008 
(table 1-5) showed significant differences for crop and irrigation treatments, but tillage 
treatments and interactions were not significantly different from each other. In this 
sampling period, PS (342.08 mmol m-2 s-1) and FS (330.93 mmol m-2 s-1) was 
significantly higher than corn (295.99 mmol m-2 s-1) and GS (291.39 mmol m-2 s-1), P = 
0.0557. Irrigated plots (397.81 mmol m-2 s-1) showed higher stomatal conductance than 
non-irrigated plots (232.38 mmol m-2 s-1), P = 0.0005. According to soil moisture content 
readings collected at the same time, volumetric soil water content in irrigated plots was  
54 
 
25.3 %, and  19.2 % in non-irrigated plots  (P  = 0.0138), due to 25 mm of water applied 
in irrigated plots. This additional water application in irrigated plots might increase plant 
respiration resulting in higher stomatal conductance values, because plant stomata 
activity indicated by stomatal conductance responds to soil water availability in stable 
weather conditions (Li et al., 2004). Conversely, stomatal conductance readings 
performed during the same period (8 WAP) in 2009 (table 1-6) showed no significant 
differences for any treatment and interaction. Irrigation treatments showed also no 
significant stomatal conductance differences due to 27 mm of rainfall at 8 WAP in 2009. 
This rainfall caused similar soil water content in irrigated fields (28.02 %) than in non-
irrigated fields (27.19 %; P = 0.7116) which might result in similar plant respiration and 
stomatal activity. 
 After 12 WAP, crops showed no significant stomatal conductance differences, but 
PS and FS were numerically higher than GS and corn for both years. However, irrigation 
treatments were significantly different during this period for both years. In 2008, irrigated 
plots (235.51 mmol m-2 s-1) showed significantly higher stomatal conductance than non-
irrigated plots (210.04 mmol m-2 s-1). Soil moisture data in irrigated and non-irrigated 
plots were 30.63% and 21.91% (P = 0.0006), respectively, during this period. 
Conversely, soil water content was not significantly different between irrigated (26.21 %) 
and non-irrigated plots (24.81 %) in 2009 (P = 0.2488), but stomatal conductance was 
significantly different in irrigated versus non-irrigated plots, respectively, 271.44 and 
232.05 mmol m-2 s-1 (P = 0.0409). . Additionally, stomatal conductance readings in 
tillage treatments at 12 WAP were only significantly different in 2008, with conventional 
tillage (250.92 mmol m-2 s-1) having higher stomatal conductance values than 
55 
 
conservation tillage (194.63 mmol m-2 s-1; P = 0.0116). This result might be related to 
higher soil water content found in conventional tillage plots (27.22 %) than in 
conservation tillage plots (24.77 %; P < 0.0001).  
 Stomatal conductance readings collected near the end of growing season (16 
WAP) showed differences for crop treatments in 2008. GS (181.54 mmol m-2 s-1) and FS 
(151.75 mmol m-2 s-1) showed significantly higher stomatal conductance than corn (74.79 
mmol m-2 s-1). PS (126.63 mmol m-2 s-1) was also found to be significantly higher than 
corn, equal to FS and lower than GS.  The low values related to corn in 2008 are due to 
the fact that the crop was R6 to R7 growth stage development (senescent) during the 
period. No corn measurements were collected in 2009 because the crop was already 
terminated (R7 stage) at 16 WAP. Moreover, earlier stomatal conductance readings (at 14 
or 15 WAP) for corn were not possible due to cloudy and raining days during this period 
which could have resulted in inaccurate readings.  In 2009, the crops were not 
significantly different from each other. 
  Results showed that GS had the same or higher stomatal conductance than FS 
and PS at 16 WAP. It was expected that GS would have lower physiological activity than 
PS and FS, because GS was ending soft dough stage (growth stage development 7), and 
PS an FS were still in vegetative stage. However, Xin et al. (2009) concluded that 
different sorghum materials showed different enhanced transpiration efficiency (TE) 
which is defined as biomass accumulation per unit water transpired (g kg-1). Sorghum 
plants with high values of enhanced TE could produce more biomass with the same water 
availability. Thus, TE showed a low relationship with instantaneous transpiration 
efficiency (nTE) which was measured at leaf level (stomatal conductance). Therefore, 
56 
 
high stomatal conductance among different sorghum varieties did not explain higher 
biomass production in most cases.                 
The interaction ?crop x irrigation? was significant at 16 WAP for both years. In 
2008, stomatal conductance for irrigated GS (199.25 mmol m-2 s-1) was considered higher 
than irrigated FS (142.80 mmol m-2 s-1), PS (118.16 mmol m-2 s-1)  and corn (77.53 mmol 
m-2 s-1). Non-irrigated GS (163.83 mmol m-2 s-1) and FS (160.70 mmol m-2 s-1) were 
considered higher than non-irrigated PS (134.60 mmol m-2 s-1) and corn (72.05 mmol m-2 
s-1). Irrigated and non-irrigated corn was not significantly different from each other and 
showed the lowest values. In 2009, stomatal conductance in non-irrigated FS (372.85 
mmol m-2 s-1) was considered significantly higher than irrigated PS (249.45 mmol m-2 s-1) 
and non- irrigated GS (161.61 mmol m-2 s-1). The interaction ?crop x irrigation? occurred 
due to rainfall of 43 mm and 66 mm in 2008 and 2009, respectively, which diminished 
the irrigation effect in field.  
 
3.5. Plant Height 
Corn showed the highest plant height value at 6 weeks WAP for 2008 and 2009, 
1.50 and 1.66 m, respectively. In 2008, corn was followed by FS (1.37 m), GS (1.16 m), 
and PS (1.07 m). FS was significantly different from corn, GS, and PS. PS was not 
significantly different from GS (P = 0.0002). In 2009, the same trend was observed. Corn 
(1.66 m) showed the highest values followed by FS (1.25 m), GS (1.20 m) and PS (1.15 
m). However, sorghum varieties were not significantly different from each other, but they 
were significantly different from corn (P = 0.0016; table 1-8). High precipitation at 6 
WAP might have affected positively GS and PS in 2009. Mastrorilli et al. (1999) 
57 
 
concluded that most sorghum plants had high water demand during the first weeks, and 
irrigation should be emphasized in early stages and indispensible any time in which soil 
water is below wilting point.  
 At 9 WAP, PS overcame GS in both years. In 2008, corn (2.73 m) was higher 
than FS (2.13 m), PS (1.61 m), and GS (1.32 m; P ? 0.0001). The same trend was 
observed in 2009, where corn, FS, PS and GS were respectively 2.82, 2.01, 1.85 and 1.55 
m (P ? 0.0001; table 1-8). Additionally, PS and FS showed no significant plant height 
differences at 14 WAP for both years. PS and FS were 3.23 m in 2008, and 3.19 and 3.01 
m in 2009. Corn reached anthesis during this period, resulting in similar height as 9 
WAP. At 18 WAP in 2008, PS (3.67 m) was significantly higher than FS (3.25 m, P ? 
0.0001) because FS reached anthesis at 18 WAP which decreased vertical plant growth. 
The same results were found at 20 WAP in 2009, where PS was 3.83 m high. Finally, PS 
was continuously growing at 24 weeks after planting for both years reaching 3.84 m 
(2008), and 4.09 m (2009). This result might confirm the hypothesis that PS has a longer 
vegetative phase than FS and GS which might result in more dry matter production over 
longer periods. Figures 1-2 and 1-3 illustrate plant height variation over time for the 
different crops.   
Irrigation treatments were considered significantly different from each other in 
both years for all periods.  Irrigated plots were significantly higher in plant height values 
than non-irrigated plots in all evaluated periods, except at 6 WAP in 2009. Carmi et al. 
(2006) found similar results for forage sorghum varieties, and Sakellariou-Makrantonaki 
et al. (2007) concluded that irrigation resulted in taller sorghum plants. However, no 
significant differences between irrigation (1800 mm vs. 2500 mm) were found between 
58 
 
two different silage sorghums (Yosef et al., 2009). Additionally, non-irrigated plots (1.36 
m) were slighter higher in plant height values than irrigated plots (1.28 m) at 6 WAP in 
2009, because no irrigation was needed during the first 6 weeks during 2009 season due 
to 378 mm of rainfall.  
Significant crops x irrigation interactions were found at 14 and 18 WAP in 2008; 
and at 14 WAP in 2009. Those interactions suggested that irrigated GS and corn had 
lower plant height than FS and PS (data not shown). Irrigation could not improve GS and 
corn plant height after 14 WAP, since both varieties were mature while PS and FS were 
continuously growing (vegetative stage).   
 Conservation tillage (in-row subsoiling with a cover crop) showed significantly 
taller plants than conventional tillage (total disked area) for both years during all periods, 
except 24 WAP. Omer and Elamin (1997) suggested that in-row subsoiling (vertical soil 
disruption) showed improvement in soil aeration and infiltration resulting in taller 
sorghum plants.  
Significant crops x tillage interactions were found at 6 and 9 WAP in 2008. Corn 
was the only crop that showed higher plant height values in conservation plots at 6 WAP 
in 2008. However, conservation tillage improved plant height for PS, FS and corn, except 
GS at 8 WAP. In 2009, crops x tillage interactions were found at 20 WAP in 2009 (data 
not shown). Results suggested that tillage treatments were not significantly different for 
both PS and FS. Similar results were found at 24 WAP for both years.   
 
 
 
59 
 
3.6. Aboveground dry matter  
 Due to higher precipitation in 2009 (570 mm) than 2008 (337.5 mm), significant 
aboveground dry matter (ADM) differences among crops were found when comparing 
years (P ? 0.0001). Therefore the results of ADM were analyzed by year (table1-9). 
Conservation plots (18.47 Mg ha-1) and conventional plots (18.39 Mg ha-1) showed no 
significant differences in ADM values in 2008 (P = 0.8721; figure 1-5). Similar results 
were found by Shirani et al. (2002) and Angers et al. (1997). All sorghum varieties 
showed higher ADM production than corn for both years which is similar to results 
reported by Cogle et al. (1997) who reported no differences among different tillage 
systems, but also reported sorghum biomass yield was always higher than corn.  In 2009, 
conservation plots (12.26 Mg ha-1) showed higher ADM production than conventional 
plots (11.02 Mg ha-1), P = 0.0028 (figure 1-5). Several factors might influence these 
ADM differences between tillage treatments in 2009. Increased amounts of rye cover 
crop produced in 2009 than in 2008 for conservation tillage might result in better 
conditions for biomass production under conservation tillage. Conservation tillage was 
considered more suitable for soils which had good drainage (Al-Kaisi et al., 2005), and 
Marvyn soils were described as well drained, and moderately permeable (Official Series 
Description, 2010). Furthermore, in row-subsoiling in conservation tillage enhanced plant 
growth due to increased root proliferation and water infiltration than conventional tillage 
systems (Reeves and Toucthon, 1986).    
 In 2008, aboveground dry matter differences among crops were found when 
comparing LS means calculated from all tillage and irrigation treatments.  FS (21.27 Mg 
ha-1) showed the highest ADM production at 14 WAP, followed by PS (18.08 Mg ha-1), 
60 
 
GS (12.38 Mg ha-1) and corn (7.25 Mg ha-1). However, PS (26.04 Mg ha-1) overcame FS 
(22.83 Mg ha-1) at 18 WAP followed by GS (13.41 Mg ha-1) and corn (8.92 Mg ha-1). At 
24 WAP, PS showed higher yields than FS with, respectively, 30.13 Mg ha-1 and 24.00 
Mg ha-1. Thus, PS was the only variety that showed significantly higher ADM production 
at 24 WAP than at other sampling periods. Results indicated that PS had high cellulosic 
biomass production potential over long periods (from 18 WAP). On the other hand, FS 
showed no significant differences between 18 and 24 WAP which were just significantly 
higher than 14 WAP. GS and corn showed the same yields in both 14 and 18 WAP, P ? 
0.0001 (figure 1-6).  
Additionally, irrigated plots (20.50 Mg ha-1) had higher ADM yields than non-
irrigated plots (16.37 Mg ha-1) in 2008, P = 0.0090 (figure 1-4). Because irrigation was 
terminated at 16 WAP, crops x irrigation interaction showed that PS had no ADM 
differences between irrigation treatments at 18 and 24 WAP, 30.61 Mg ha-1 and 32.90, 
respectively. Thus, irrigated FS was not significantly different for any period in 2008, but 
non-irrigated FS had higher ADM yields at 24 (22.98 Mg ha-1) than 14 WAP (18.70 Mg 
ha-1), P = 0.0227 (figure 1-8). 
In 2009, the overall ADM yield (11.64 Mg ha-1) were drastically lower than 2008 
(18.43 Mg ha-1), P ? 0.0001.  Excessive water, Anthracnose disease in sorghum plants, 
and Southern Corn Leaf Blight ? SCLB (Bipolaris maydis) disease in corn plants 
decreased yields in 2009. At 14 WAP, PS (16.03 Mg ha-1), GS (13.71 Mg ha-1) and FS 
(12.26 Mg ha-1) showed no significant differences in yields, but corn (8.77 Mg ha-1) had 
lower ADM yields than sorghum varieties. However, PS (19.19 Mg ha-1) showed the 
highest yield at 20 WAP followed by GS (11.51 Mg ha-1), FS (9.62 Mg ha-1) and corn 
61 
 
(5.81 Mg ha-1). At 24 WAP, PS showed higher yields than FS, respectively, 13.21 Mg ha-
1 and 6.29 Mg ha-1. FS, GS and corn showed highest ADM values at 14 WAP. PS and FS 
showed lower yields at 24 WAP than 20 WAP. And FS, GS, and corn showed lower 
yields at 20 WAP than 14 WAP, P ? 0.0001 (figure 1-7). 
 Anthracnose (Colletotrichum graminicola) was reported as the major sorghum 
disease (Metha et al., 2005) and it reduces sorghum yields in hot and humid conditions 
(Ali and Warren, 1992).  High severity of anthracnose disease in sorghum varieties, such 
as 60 to 75% area diseased in FS at 24 WAP (data not shown) was related to lack of crop 
rotation. Moore et al. (2009) concluded that successive sorghum crops at same location 
resulted in lower yields due to high anthracnose incidence. And rice, soybeans, and corn 
planted before sorghum improved sorghum yields.  Furthermore, corn plants were 
affected by SCLB.  Ear leaf damage reached 21 to 30 % at 15 WAP (data not shown) 
which could be related to decrease in ADM at 20 WAP. 
 Irrigated plots (12.18 Mg ha-1) had higher ADM yields than non-irrigated plots 
(11.11 Mg ha-1) in 2009, P = 0.0637 (figure 1-4). But, crops x irrigation interaction (P = 
0.0396) showed that irrigated PS just showed higher ADM production than non-irrigated 
PS at 14 WAP, 17.7 Mg ha-1 and 14.36 Mg ha-1 respectively. FS showed similar yields 
for all periods in 2009. GS had higher yield in irrigated treatments at 14 and 20 WAP. 
And, corn showed higher ADM production in non-irrigated fields at 14 WAP, P = 
0.0396. The differences found in 2009 due to crops x irrigation interaction were difficult 
to explain because high precipitation diminished irrigation effect, and diseases may affect 
the crops differently (figure 1-9).  
 
62 
 
3.7. Corn grain dry matter  
Corn grain dry matter (CGDM) yields were significantly different when 
comparing different years. The average CGDM production was higher in 2008 (8.47 Mg 
ha-1) than in 2009 (7.62 Mg ha-1), P ?0.0001, therefore CGDM data were analyzed 
separated by year. These different yields might be related to higher precipitations in 2009 
which favored SCLB disease development and reduced corn grain yields. According to 
field evaluations performed at 20 weeks after planting (WAP), ear leaf damage reached 
21 to 30 % at 15 WAP (data not shown) which might have decreased CGDM yields in 
2009.  
In 2008, CGDM yields were significantly different between sampling periods, P = 
0.0233 (table 1-14). CGDM samples collected at 18 WAP showed higher yields than 
samples collected at 14 WAP, respectively, 8.76 Mg ha-1 and 8.17 Mg ha-1.  Irrigated 
plots (9.67 Mg ha-1) showed higher yields than non-irrigated (7.26 Mg ha-1), P = 0.0072. 
Several authors showed similar conclusions about corn development and dry matter 
production by concluding that irrigated corn plants had higher grain yields than non-
irrigated plants (Roygard et al., 2002; Pilbeam et al.,1995; Payero et al., 2008). No 
significant differences were found between conservation and conventional systems in 
2008, P = 0.5576. Several studies that worked with different tillage systems (conservation 
vs. conventional) also found no significant difference in CGDM yields among tillage 
systems. They concluded that both tillage systems resulted in similar soil conditions for 
corn plant development and grain production (Angers et al., 1997; Linden et. al., 2000; 
Shirani et al., 2002).    
63 
 
In 2009, CGDM produced at 20 WAP (8.18 Mg ha-1) were higher than in 14 
WAP (7.05 Mg ha-1), P = 0.0691. Irrigated plots were not significantly different from 
non-irrigated plots (P = 0.7247), because irrigation effects in 2009 were diminished due 
to high precipitation during growing season.  Tillage systems were also not significantly 
different from each other (P = 0.6013).  
 
3.8. Sorghum grain dry matter 
In 2008, GS showed no significant SGCM differences between 14 WAP (4.40 Mg 
ha-1) and 18 WAP (4.62 Mg ha-1), P = 0.5163. Irrigated plots (5.06 Mg ha-1) showed 
higher SGDM yields than non-irrigated plots (3.957 Mg ha-1), P = 0.0861 (table 1-17). 
Similar studies showed different results. They found that irrigated sorghum showed 
similar grain yields than rainfed sorghum (Amaducci et al., 2000; Habyarimana et al., 
2004a). But, Habyarimana et al. (2004b) concluded that sorghum planted at a high plant 
density showed more susceptibility to water availability, and they recommended a 
sorghum population be between 150,000 and 200,000 plants ha-1. GS were planted at a 
high plant density (407,700 seeds ha-1); which might result in more drought susceptibility 
and lower yields in non-irrigated plots. However, no significant SGDM differences were 
found between conservation tillage (4.53 Mg ha-1) and conventional system (4.49 Mg ha-
1) in 2008, P = 0.8212.   
 SGDM showed drastically lower yields at 20 WAP (1.54 Mg ha-1) in 2009 than 
any period in 2008. High precipitation during growing season diminished irrigation 
effect, and similar yields were found for irrigated (1.81 Mg ha-1) and non-irrigated (1.27 
Mg ha-1) fields.  Conservation system (1.86 Mg ha-1) produced same SGDM yields (1.52 
64 
 
Mg ha-1) as conventional system. Low yields and no differences between any treatments 
might be related to Anthracnose disease observed in field during 2009. Field evaluations 
showed that GS was 49% - 59% leaf area diseased at 18 WAP in 2009 (data not shown).  
  
3.9. Biomass quality 
3.9.1. Holocellulose content  
 Holocellulose is the desirable portion of cellulosic biomass, because it can be 
converted to carbohydrates (xylose, mannose, galactose and glucose). Consequently, 
those carbohydrates can be used by ethanol production.  
  Holocellulose content (HC) was significantly higher in 2009 (689.8 g kg-1) than 
in 2008 (682.3 g kg-1), P = 0.0009. High precipitation and high incidence of Anthracnose 
disease in 2009 might decrease holocellulose content.  Data were analyzed separated by 
years. 
 Significant differences were found at 14 weeks after planting (WAP) in 2008. 
During this period, PS (715.4 g kg-1) had significantly higher HC than corn (687.4 g kg-
1), GS (686.5 g kg-1), and FS ( 686.3 g kg-1) at 14 WAP (P = 0.0216). However, crops x 
irrigation effect (P = 0.0197) at same period indicated that PS had significantly higher 
HC than the other crops in irrigated condition, but there was no significant differences 
among crops under non-irrigated conditions. At 18 WAP (P = 0.0022), PS (700.6 g kg-1) 
showed significantly higher HC values than corn (675.9 g kg-1), FS (653.7 g kg-1) and GS 
(650.9 g kg-1), but FS were not significantly different from GS. At 24 WAP, FS (692.6 g 
kg-1) and PS (673.5 g kg-1) showed no significant HC differences (table 1-20).  
65 
 
 In 2009, corn (702.1 g kg-1) and PS (696.5 g kg-1) showed higher HC than FS 
(674.5 g kg-1) and GS (656.0 g kg-1) at 14 WAP (P = 0.0147). However, corn (765.9 g kg-
1) had significantly higher HC than PS (690.1 g kg-1), FS (684.0 g kg-1) and GS (683.5 g 
kg-1) at 20 WAP (P ? 0.0001). Furthermore, FS (682.0 g kg-1) had no HC significant 
differences from PS (663.47 g kg-1) at 24 WAP. A reasonable explanation for corn having 
higher HC than PS in 2009 is that high Anthracnose incidence on PS plants resulted in 
leaf losses. Leaves could have higher HC than stems, therefore lower HC in PS ADM 
could be related to leaf losses. 
 Irrigated fields only had higher HC than non-irrigated fields at 18 WAP in 2008 
(P = 0.0772). At this sampling period, irrigated treatments (676.7 g kg-1) showed higher 
HC than non-irrigated treatments (664.9 g kg-1). Tillage treatments showed no significant 
HC differences in 2008. Conversely, conservation treatments (713.1 g kg-1) had higher 
HC than conventional treatments (698.6 g k-1) at 18 WAP (P = 0.0049) in 2009 (table 1-
21). Statistical differences in tillage and irrigation treatments are considered minor 
because they are smaller than 2 and 4.6 %, respectively. 
 The U.S. Department of energy (DOE) cited switchgrass as the most probable 
cellulosic energy crop (DOE, 2005). Therefore, switchgrass was used as reference for 
bioenergy production. McLaughin et al. (1999) cited switchgrass holocellulose content 
ranging from 540 to 670 g kg-1. However, all tested crops showed higher or equal 
holocellulose content than switchgrass. PS, FS, GS and corn showed ranges of 663 ? 715 
g kg-1, 654 ? 693 g kg-1, 651 ? 686 g kg-1, and 676 ? 766 g kg-1 respectively.  
 
   
66 
 
3.9.2. Lignin content 
 Lignin is the undesirable portion of biomass when considering bioethanol 
production, because it cannot be converted into carbohydrates, and it has recalcitrant 
effect. In other words, lignin masks holocellulose (cellulose and hemicellulose) which 
forbids carbohydrate conversion. Therefore, low lignin content (LC) is desired in 
cellulosic materials in order to enhance bioethanol production (Weng et. al, 2008).  
 LC was significantly different between years (P ? 0.0001). Higher LC were found 
in 2009 (77.9 g kg-1) than in 2008 (69.2 g kg-1). Those differences could be related to 
higher precipitation in 2009, because better water status could increase lignin content on 
different forage species, such as sorghum (Amaducci et al., 2000). Furthermore, 
Anthracnose disease in sorghum plants and SCLB disease in corn plants resulted in leaf 
losses.  Because leaves had low lignin content than stems (Carmi et. al, 2006), high lignin 
content could be expected in 2009 season for all crops. 
 Irrigated fields showed higher LC than non-irrigated fields at 14 (P = 0.005), 18 
(P = 0.0101) and 24 (P = 0.0014) in 2008. In this year, irrigated treatments showed LC 
values of 70.1, 70.8 and 91.5 g kg-1 at 14, 18 and 24 WAP respectively; and, non-
irrigated treatments showed LC values of 56.4, 61.3 and 83.2 g kg-1 respectively. In 2009, 
irrigated treatments (68.5 g kg-1) had higher LC than non-irrigated treatments (62.4 g kg-
1, P = 0.0129). Carmi et al. (2006) found similar results. They cited that irrigation 
increased lignin content for different forage sorghum species.  No LC differences were 
found at 20 and 24 WAP. 
In both years, conservation tillage had significantly higher LC than conventional 
tillage at 14 WAP. Conservation and conventional tillage showed, respectively, 65.0 and 
67 
 
61.5 g kg-1 in 2008 (P = 0.0078); and 68.0 and 62.9 g kg-1 in 2009 (P = 0.0304), tillage 
treatments had no significant LC differences at other sampling periods for both years. 
 Crops were significantly different in LC for both years. In 2008, FS (71.4 g kg-1) 
had the highest LC which was significantly different from PS (65.7 g kg-1), GS (58.2 g 
kg-1) and corn (57.8 g kg-1) at 14 WAP (P ? 0.0001). However, at 18 WAP (P ? 0.0001), 
PS (67.0 g kg-1) showed significantly higher LC than FS (61.7 g kg-1), GS (58.9 g kg-1) 
and corn (57.7 g kg-1). Thus, PS and FS were significantly different in LC for all 
sampling periods, where FS (91.3 g kg-1) were significantly higher in LC than PS (83.5 g 
kg-1) at 24 WAP (P = 0.0629). However, GS and corn always showed no significant 
differences in LC at 18 WAP (table 1-20). 
 In 2009, FS (74.5 g kg-1) and PS (69.8 g kg-1) had significantly higher LC than GS 
(60.0 g kg-1) and corn (57.6 g kg-1) at 14 WAP (P ? 0.0001). However, at 20 WAP, all 
sorghum varieties: PS (94.1 g kg-1), GS (92.1 g kg-1) and FS (90.2 g kg-1) showed 
significantly higher LC than corn (74.3 g kg-1). Thus, FS (85.5 g kg-1) showed higher LC 
than PS (81.2 g kg-1) at 24 WAP, P = 0.0164 (table 1-12). 
 Switchgrass lignin content was cited as 190 g kg-1 (Lee et al., 2007). However, all 
tested crops showed lower lignin content than switchgrass. PS, FS, GS and corn showed 
ranges of 66 ? 94 g kg-1, 61 ? 91 g kg-1, 58 ? 92 g kg-1, and 58 ? 74 g kg-1, respectively. 
 
3.9.3. Ash content 
 Ash content (AC) in cellulosic materials is relevant information for thermal and 
biochemical technologies which produce electricity and fuel. Low ash content increases 
conversion efficiency and decreases slagging (Sanderson et al, 1996). Slagging is defined 
68 
 
as ash and inorganic deposits on boilers walls which decreases heat transfer and can make a 
power plant inoperable (Burner et. al., 2008). Therefore, low ash content is desirable to 
produce bioenergy. 
 Significant differences between years were found when comparing ash content 
(AC).  AC was slightly higher in 2009 (53.90 g kg-1) than in 2008 (49.74 g kg-1), P ? 
0.0001.  
Irrigation treatments were not significantly different in AC for both years, except 
to14 WAP at 2008 (P = 0.0041) where non-irrigated treatment (55.7 g kg-1) had higher 
AC than irrigated treatment (51.1 g kg-1).  
Tillage treatments were significantly different in AC for both years at 14 WAP. 
Conservation tillage (54.7 g kg-1) was significantly higher in AC than conventional tillage 
(52.1 g kg-1) in 2008 (P = 0.0063). Conversely, conventional tillage (65.6 g kg-1) showed 
higher AC than conservation tillage (58.1 g kg-1) in 2009 (P = 0.0002). Furthermore, 
irrigation x tillage interaction (P = 0.0081) in 2008 indicated that conventional tillage had 
higher AC just in non-irrigated conditions in 2008, where tillage treatments were not 
significantly different in AC under irrigated conditions.    
Crops were significantly different in AC for both years. In 2008, GS (58.0 g kg-1) and 
corn (55.8 g kg-1) were higher in AC than PS (52.0 g kg-1) and FS (47.8 g kg-1) at 14 WAP, 
but only GS were significantly different from FS at 14 WAP (P = 0.0136). The same trend 
was observed at 18 WAP (P = 0.0296), where GS, corn, PS and FS had AC values of 56.0, 
50.2, 43.20 and 43.9 g kg-1, respectively. But, GS was the only crop that showed 
significant LC differences from FS and PS. Thus, FS (51.7 g kg-1) showed significantly 
higher AC than PS (38.9 g kg-1) at 24 WAP (table 1-20), but those differences were valid 
just under irrigated treatments (crops x irrigation interaction; P = 0.0967).  
69 
 
In 2009, no significant AC differences were found among crops at 14 WAP. FS, GS, 
PS and corn had AC values of 65.2, 61.8, 60.5 and 59.8 g kg-1 respectively. GS (57.6 g kg-1) 
and FS (55.1 g kg-1) showed significantly higher AC than PS (44.6 g kg-1) and corn (39.0 
g kg-1) at 20 WAP (P = 0.0067). And, PS (56.3 g kg-1) showed higher AC than PS (39.2 g 
kg-1) at 24 WAP (P = 0.0094) (table 1-21). 
McLaughlin et al. (1996) cited switchgrass AC ranging from 45 to 58 g kg-1. 
However, all tested crops showed similar ash content. PS, FS, GS and corn showed 
ranges of 38 ? 60 g kg-1, 44 ? 65 g kg-1, 56 ? 62 g kg-1, and 50 ? 60 g kg-1, respectively.  
 
4. CONCLUSIONS 
 
All sorghum varieties showed higher biomass production than corn during all 
sampling periods in both years. All sorghum varieties were able to produce more yield 
than corn under all irrigation and tillage treatments which proved sorghum?s superiority 
in producing cellulosic biomass for a potential bioenergy industry. Higher cellulosic 
biomass production reported in 2008 than 2009 season was related to anthracnose and 
southern corn leaf blight diseases in sorghum and corn crops, respectively. Thus, crop 
rotation were recommended. Lodging which affected PS, FS and GS sorghum varieties 
could be related to high plant population. Therefore, sorghum plant population must be 
better evaluated for use in the southeastern U.S.  
Irrigated treatments affected cellulosic biomass production positively in both 
years.  Conservation system showed higher cellulosic biomass production than 
conventional tillage in 2009. Stomatal conductance readings showed that high yields 
under irrigated and conservation fields were related to plentiful amounts of water in soil 
70 
 
which might increase plant metabolism. A better rye soil cover was found in 2009 (2.57 
Mg ha-1) than 2008 (0.26 Mg ha-1) due to increased rye dry matter production in 2009 
caused by better weather conditions (elevated temperatures in early spring 2009).  
Cellulosic biomass quality parameters were only slightly significantly different 
among crops for all sampling periods. Holocellulose, lignin, and ash content variation 
among crops were less than 8.3, 2.0, and 1.9 % respectively. Therefore, cellulosic 
biomass quality was considered a minor factor and total cellulosic biomass production 
considered the major factor to select the best crop for bioenergy production. 
Therefore, PS was considered the best tested crop in order to produce cellulosic 
biomass (ADM) which produced 26.04 and 30.13 Mg ha-1 at 18 and 24 WAP. However, 
FS can be an alternative if harvesting occurs at 14 weeks after planting (21.27 Mg ha-1). 
Plant height readings clarified that PS had slower development than other crops. 
However, its? prolonged vegetative stage due to southeastern U.S. photoperiod condition 
resulted in high cellulosic biomass production in late harvests. 
 
 
 
 
 
 
 
 
 
71 
 
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78 
 
Table1-1: Results of the type 3 test of treatments and effects from PROC MIXED for rye 
dry matter (Mg ha-1) yield for 2008 and rye dry matter yield (Mg ha-1)  and spontaneous 
vegetation (Mg ha-1) in 2009. 
 
Rye dry matter 
Years 
2008* 2009** 
Rye Rye 
(total field) (conservation plots) 
Treatments ----Dry matter (Mg ha-1)---- ------Dry matter (Mg ha-1)------ 
Crops   
PS***  0.26 2.66 
FS *** 0.28 3.04 
GS *** 0.28 2.04 
Corn***  0.23 2.59 
Irrigation   
Irrigated 0.27 2.51 
non-irrigated 0.26 2.66 
Tillage   
conventional 0.27 --- 
conservation 0.25 --- 
   
Source of Error -------p-value------ -------------p-value------------ 
Crops (C) 0.3427 0.7167 
Irrigation (I) 0.2984 0.4790 
Tillage (T) 0.3583 --- 
CxI 0.8647 0.1297 
CxT 0.2788 --- 
IxT 0.1773 --- 
CxIxT 0.5802 --- 
 
* Rye cover crop planted in total field. 
** Rye cover crop planted just in conservation plots. 
***PS: photoperiod sensitive sorghum (1990), FS: forage sorghum (SS506), GS: grain 
sorghum (NK300), Corn: Pioneer31G65.   
 
 
 
 
 
 
 
 
 
79 
 
Table 1-2: Results of the type 3 test of treatments and effects from PROC MIXED for 
sunn hemp dry matter (Mg ha-1) yield for fall 2008. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
*
 
Significant at 0.10 level of probability. 
**GS: grain sorghum (NK300), Corn: Pioneer31G65. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Sunn hemp  dry matter Year 2008 
Treatments ---Dry matter(Mg ha-1)--- 
Crops 
GS** 0.37b 
Corn** 0.87a 
Irrigation 
Irrigated 0.57a 
Non-irrigated 0.67a 
  
Source of error ----------p-value---------- 
Crops 0.0198* 
Irrigation 0.4777 
Crops x Irrigation 0.1022 
80 
 
Table1-3: Precipitation (mm) in irrigated and non-irrigated plots monitored by rain 
gauges installed in field from planting to 14 weeks after planting for both years. 
 
 
 *Coefficient of variation. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Rain gauges set 
Precipitation (mm) 
2008 2009 
Irrigated Non-irrigated Irrigated Non-irrigated 
1 462 343 630 577 
2 473 329 616 554 
3 477 342 637 568 
4 467 336 641 581 
Mean 469.7 337.5 631.0 570.0 
C.V. (%)* 1.4% 1.9% 1.7% 2.1% 
81 
 
Table 1-4: Results of the type 3 test of treatments and effects from PROC MIXED for 
Plant population within each crop during growing season and harvest time in 2008 and 
2009. 
 
* Significant at 0.10 level of probability. 
**PS: photoperiod sensitive sorghum (1990), FS: forage sorghum (SS506), GS: grain 
sorghum (NK300), Corn: Pioneer31G65.   
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Weeks after 
planting 
Crops 
PS** FS** GS** Corn** 
6 weeks --------------------------------- Plants ha-1-------------------------- 
2008 356,106a 383,913a 376,064a 79,608a 
2009 362,834a 376,737a 375,616a 77,781a 
14 weeks  
2008 327,012a 337,942b 355,882b 77,141a 
2009 258,558b 208,326c 289,729c 73,553a 
p-value ?0.0001* ?0.0001* ?0.0001* 0.3739 
82 
 
Table 1-5: Results of the type 3 test of treatments and effects from PROC MIXED for 
Stomatal conductance (mmol m-2 s-1) yield for 2008. 
 
* Significant at the 0.10 level of probability. 
**PS: photoperiod sensitive sorghum (1990), FS: forage sorghum (SS506), GS: grain 
sorghum (NK300), Corn: Pioneer31G65. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Year 2008 Weeks after planting 8 12 16 
Treatments -----Stomatal Conductance (mmol m-2 s-1)----- 
Crops  
PS** 342.08a 257.45a 126.63b 
FS** 330.93a 241.48a 151.75ab 
GS** 291.39b 227.64a 181.54a 
Corn** 295.99b 164.53a 74.79c 
Irrigation  
Irrigated 397.81a 235.51a 134.56a 
Non-irrigated 232.38b 210.04b 132.79a 
Tillage  
Conventional 320.62a 250.92a 133.39a 
Conservation 309.58a 194.63b 133.96a 
    
Effect ------------------------?-value---------------------- 
Crops 0.0557* 0.2394 0.0011* 
Irrigation 0.0050* 0.0218* 0.9306 
Tillage 0.2603 0.0116* 0.9413 
Crops x Irrigation 0.3919 0.7319 0.0170* 
Crops x Tillage 0.3061 0.3677 0.7484 
Irrigation x Tillage 0.2894 0.4578 0.3459 
Crops x Irrigation x Tillage 0.8706 0.6214 0.4449 
83 
 
Table 1-6: Results of the type 3 test of treatments and effects from PROC MIXED for 
Stomata conductance (mmol m-2 s-1) yield for 2009. 
* Significant at the 0.10 level of probability. 
**PS: photoperiod sensitive sorghum (1990), FS: forage sorghum (SS506), GS: grain 
sorghum (NK300), Corn: Pioneer31G65. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Year 2009 Weeks after planting 8 12 16 
Treatments -----Stomata Conductance (mmol m-2 s-1)----- 
Crops  
PS** 323.70a 256.73a 277.81a 
FS** 307.54a 262.68a 377.99a 
GS** 323.16a 245.38a 233.84a 
Corn** 340.91a 242.18a --- 
Irrigation  
Irrigated 327.56a 271.44a 286.12a 
Non-irrigated 320.09a 232.05b 280.31a 
Tillage  
Conventional 309.46a 230.60a 297.39a 
Conservation 338.20a 272.80a 269.04a 
    
Effect ------------------------?-value---------------------- 
Crops 0.9576 0.9891 0.2050 
Irrigation 0.8991 0.0409* 0.8271 
Tillage 0.4957 0.0132* 0.1933 
Crops x Irrigation 0.3152 0.5122 0.0200* 
Crops x Tillage 0.7179 0.5529 0.5293 
Irrigation x Tillage 0.2454 0.6855 0.4199 
 Crops x Irrigation x Tillage 0.5396 0.0900* 0.4495 
84 
 
Table 1-7: Results of the type 3 test of treatments and effects from PROC MIXED for 
Plant height (m) in 2008. 
* Significant at the 0.10 level of probability. 
**PS: photoperiod sensitive sorghum (1990), FS: forage sorghum (SS506), GS: grain 
sorghum (NK300), Corn: Pioneer31G65. 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Year 2008 Weeks after planting 6 9 14 18 24 
Treatments -----------------Plant height (m)----------------- 
Crops  
PS** 1.07c 1.61c 3.23a 3.67a 3.84a 
FS** 1.37b 2.13b 3.23a 3.25b 3.43b 
GS** 1.16c 1.32d 1.70c 1.72c - 
Corn** 1.50a 2.73a 2.80b 2.74c - 
Irrigation    
Irrigated 1.34a 2.14a 3.00a 3.12a 3.90a 
Non-irrigated 1.21b 1.76b 2.44b 2.57b 3.37b 
Tillage    
Conservation 1.31a 2.01a 2.78a 2.89a 3.67a 
Conventional 1.24b 1.89b 2.67b 2.80b 3.61a 
      
Effect ------------------------?-value---------------------- 
Crops 0.0002* 0.0001* 0.0001* 0.0001* 0.0276* 
Irrigation 0.0517* 0.0046* 0.0068* 0.0012* 0.0178* 
Tillage 0.0024* 0.0001* 0.0177* 0.0535* 0.4223 
Crops x Irrigation 0.5508 0.4943 0.0153* 0.0717* 0.1632 
Crops x Tillage 0.0192* 0.0023* 0.3870 0.7846 0.4617 
Irrigation x Tillage 0.6238 0.1187 0.1740 0.7466 0.2549 
Crops x Irrigation x Tillage 0.9850 0.6852 0.7798 0.9218 0.4848 
85 
 
Table 1-8: Results of the type 3 test of treatments and effects from PROC MIXED for 
Plant height (m) in 2009. 
 
* Significant at the 0.10 level of probability. 
**PS: photoperiod sensitive sorghum (1990), FS: forage sorghum (SS506), GS: grain 
sorghum (NK300), Corn: Pioneer31G65. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Year 2009 Weeks after planting 6 9 14 20 24 
Treatments -----------------Plant height (m)----------------- 
Crops  
PS** 1.15b 1.85c 3.19a 3.83a 4.09a 
FS** 1.25b 2.01b 3.01a 3.05b 3.08b 
GS** 1.20b 1.55d 1.70c 1.76d - 
Corn** 1.66a 2.82a 2.58b 2.56c - 
Irrigation    
Irrigated 1.28b 2.14a 2.75a 2.95a 3.72a 
Non -irrigated 1.36a 1.97b 2.45b 2.65b 3.45b 
Tillage    
Conservation 1.48a 2.21a 2.71a 2.86a 3.62a 
Conventional 1.16b 1.90b 2.53b 2.75b 3.56a 
      
Effect ------------------------?-value---------------------- 
Crops 0.0016* 0.0001* 0.0001* 0.0001* 0.0018* 
Irrigation 0.0391* 0.0028* 0.0031* 0.0057* 0.0493* 
Tillage 0.0001* 0.0001* 0.0002* 0.0193* 0.4591 
Crops x Irrigation 0.4540 0.4943 0.0892* 0.4627 0.5319 
Crops x Tillage 0.2654 0.1055* 0.1712 0.0795* 0.3132 
Irrigation x Tillage 0.6791 0.0006* 0.0461* 0.0644* 0.5319 
 Crops x Irrigation x Tillage 0.6709 0.2620 0.0903* 0.1957 0.4848 
86 
 
Table 1-9: Results of the type 3 test of treatments and effects from PROC MIXED for 
Aboveground dry matter (Mg ha-1) for 2008 and 2009. 
 
* Significant at the 0.10 level of probability. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Aboveground dry matter (Mg ha-1) Years 2008 2009 
Source of Error ------------------------?-value---------------------- 
Crops 0.0001* 0.0001* 
Irrigation 0.0090* 0.0637* 
Tillage 0.8721 0.0028* 
Crops x Irrigation 0.0227* 0.0396* 
Crops x Tillage 0.7618 0.2716 
Irrigation x Tillage 0.6863 0.1431 
Crops x Irrigation x Tillage 0.1737 0.5302 
 
 
87 
Table 1-10: Results of the type 3 test of treatments and effects from PROC MIXED for P, K, Ca, and Mg aboveground dry matter 
uptake (mg kg-1) for all sampling periods in 2008. 
 
2008 Primary nutrients uptake Secondary nutrients uptake Phosphorus (P) Potassium (K) Calcium (Ca) Magnesium (Mg) 
14WAP** 18WAP** 24WAP** 14WAP** 18WAP** 24WAP** 14WAP** 18WAP** 24WAP** 14WAP** 18WAP** 24WAP** 
Effects -------------mg kg-1------------- -------------mg kg-1------------- -------------mg kg-1------------- -------------mg kg-1------------- 
Crops             
PS*** 1133a 1623 822 14490ab 11401b 8037b 2322b 2991 1718 2536a 2321a 1879 
FS*** 1087a 1172 1116 12887c 10301b 10974a 2145b 1929 1984 2128b 1958b 1588 
GS*** 893b 829 --- 15429a 13245a --- 2628a 2351 --- 2700a 2310a --- 
Corn*** 807b 1007 --- 14270b 10492b --- 2541a 2233 --- 1930b 1819b --- 
Irrigation             
irrigated 973 1030 1002 13474b 10943 9236 2351 2094 1798 2176 2057 1682 
non-irrigated 987 1284 937 15064a 11776 9775 2467 2658 1904 2371 2147 1785 
Tillage             
conservation 1029a 1348 962 14630a 11916a 9318 2344b 2630 1810 2312 2164 1725 
conventional 931b 967 976 13908b 10803b 9692 2474a 2122 1892 2335 2040 1742 
 -------------p-value------------- -------------p-value------------- -------------p-value------------- -------------p-value------------- 
Source of Error           
crops (C) 0.0034* 0.3307 0.1725 0.0100* 0.0100* 0.0329* 0.0077* 0.5653 0.2246 0.0011* 0.0010* 0.1725 
irrigation (I) 0.8333 0.4694 0.4935 0.0033* 0.3332 0.5855 0.1665 0.3136 0.4114 0.4303 0.4093 0.4400 
tillage (T) 0.0036* 0.1640 0.7569 0.0851* 0.0036* 0.2755 0.0575* 0.2916 0.3665 0.7471 0.1176 0.8710 
CxI 0.0016* 0.4663 0.4842 0.1532 0.3831 0.3966 0.0813* 0.4981 0.3163 0.0313* 0.6700 0.2584 
CxT 0.9872 0.3173 0.9806 0.3178 0.4481 0.6476 0.5356 0.3037 0.5798 0.2393 0.2697 0.4626 
IxT 0.2842 0.3819 0.1364 0.8528 0.6893 0.4137 0.9882 0.4782 0.0601* 0.9375 0.1680 0.0855* 
CxIxT 0.4402 0.4435 0.5953 0.4374 0.7668 0.6307 0.3209 0.4548 0.2986 0.3425 0.3882 0.7199 
             
* Significant at 0.10 level of probability. 
**Weeks after planting. 
***PS: photoperiod sensitive sorghum (1990), FS: forage sorghum (SS506), GS: grain sorghum (NK300), Corn: Pioneer31G65. 
 
 
88 
Table 1-11: Results of the type 3 test of treatments and effects from PROC MIXED for P, K, Ca, and Mg aboveground dry matter 
uptake (mg kg-1) for all sampling periods in 2009. 
 
2009 Primary nutrients uptake Secondary nutrients uptake Phosphorus (P) Potassium (K) Calcium (Ca) Magnesium (Mg) 
14WAP** 20WAP** 24WAP** 14WAP** 20WAP** 24WAP** 14WAP** 20WAP** 24WAP** 14WAP** 20WAP** 24WAP** 
Effects -------------mg kg-1------------- -------------mg kg-1------------- -------------mg kg-1------------- -------------mg kg-1------------- 
Crops             
PS*** 1460 1283a 1206 16263ab 10791b 10169b 2343c 1417c 1281 2601b 1835b 1520 
FS*** 1727 1331a 1211 17718a 15416a 15934a 2551bc 1317c 1500 2749b 1608c 1444 
GS*** 1672 1379a --- 14933b 13383a --- 2964ab 2032a --- 3453a 2574a --- 
Corn*** 1416 850b --- 14518b 7305c --- 3380a 1672b --- 2602b 1713bc --- 
Irrigation             
irrigated 1628 1257 1169 15309 11635 13153 2672 1613 1343 2765 1937 1423 
non-irrigated 1509 1164 1248 16406 11812 12915 2947 1606 1438 2938 1928 1540 
Tillage             
conservation 1451b 1170b 1221 14860b 12104a 13522a 2595b 1588 1332 2592b 1850b 1464 
conventional 1686a 1251a 1196 16856a 11344b 12581b 3024a 1631 1349 3111a 2015a 1499 
 -------------p-value------------- -------------p-value------------- -------------p-value------------- -------------p-value------------- 
Source of Error           
crops (C) 0.1057 0.0037* 0.9343 0.0844* 0.0008* 0.0100* 0.0193* 0.0003* 0.2020 0.0546* 0.0001* 0.6699 
irrigation (I) 0.4874 0.3363 0.3286 0.2465 0.7311 0.7855 0.1120 0.9131 0.1788 0.2638 0.8007 0.2097 
tillage (T) 0.0087* 0.0693* 0.7183 0.0061* 0.0549* 0.0595* 0.0004* 0.4905 0.1746 0.0001* 0.0035* 0.6067 
CxI 0.5858 0.4975 0.5671 0.3647 0.2625 0.7032 0.4704 0.3828 0.6793 0.6718 0.1385 0.8268 
CxT 0.0295* 0.0444* 0.1867 0.0036* 0.0249* 0.6779 0.0016* 0.0927* 0.5017 0.0015* 0.0584* 0.1822 
IxT 0.5996 0.6797 0.6381 0.6628 0.3004 0.9406 0.2833 0.7723 0.8385 0.7816 0.4084 0.7379 
CxIxT 0.8507 0.0430* 0.9348 0.8027 0.2343 0.8198 0.6605 0.8242* 0.5388 0.8896 0.7802 0.7134 
             
      * Significant at 0.10 level of probability. 
      **Weeks after planting. 
      ***PS: photoperiod sensitive sorghum (1990), FS: forage sorghum (SS506), GS: grain sorghum (NK300), Corn: Pioneer31G65. 
 
 
89 
Table 1-12: Results of the type 3 test of treatments and effects from PROC MIXED for Cu, Fe, and Zn aboveground dry matter 
uptake (mg kg-1) for all sampling periods in 2009. 
* Significant at 0.10 level of probability. 
** Weeks after planting 
***PS: photoperiod sensitive sorghum (1990), FS: forage sorghum (SS506), GS: grain sorghum (NK300), Corn: Pioneer31G65. 
2008 Micronutrients Copper (Cu) Iron (Fe) Zinc (Zn) 
14WAP** 18WAP** 24WAP**- 14WAP** 18WAP**- 24WAP** 14WAP** 18WAP** 24WAP** 
Effects -------------mg kg-1------------- -------------mg kg-1------------- -------------mg kg-1------------- 
Crops          
PS***  5.13 3.82 2.35b 157.05 186.84 138.18 23.92a 12.63 17.69 
FS*** 7.27 3.48 4.51a 105.33 174.20 170.53 19.98ab 18.27 20.54 
GS*** 5.83 3.54 --- 107.61 210.58 --- 19.86b 10.63 --- 
Corn*** 6.30 4.26 --- 114.50 174.40 --- 16.64b 15.54 --- 
Irrigation          
irrigated 5.75 3.95 3.91 130.57 197.63 161.99 18.85b 11.92 20.02 
non-irrigated 6.52 3.60 2.94 111.67 175.37 146.71 21.36a 16.66 18.21 
Tillage          
conservation 6.28 3.95 3.31 120.08 191.01 159.38 20.83a 15.21 19.58 
conventional 5.98 3.60 3.55 122.16 181.99 149.32 19.37b 13.38 18.65 
 -------------p-value------------- -------------p-value------------- -------------p-value------------- 
Source of Error        
crops (C) 0.8093 0.7785 0.0058* 0.3070 0.7872 0.5483 0.0559* 0.4884 0.4818 
irrigation (I) 0.5841 0.2522 0.5082 0.4314 0.4223 0.6459 0.0021* 0.1308 0.3094 
tillage (T) 0.7875 0.4451 0.7796 0.8959 0.3635 0.6010 0.0804* 0.3542 0.5905 
CxI 0.2875 0.8002 0.4972 0.3934 0.7305 0.4979 0.0631* 0.6424 0.8306 
CxT 0.0110* 0.1361 0.4443 0.7892 0.1118 0.3799 0.2551 0.0409 0.8204 
IxT 0.0898* 0.2642 0.4097 0.4081 0.1424 0.3839 0.7329 0.0294 0.8835 
CxIxT 0.4673 0.8062 0.1796 0.7994 0.1811 0.3558 0.1728 0.4842 0.9551 
          
 
 
90 
Table 1-13: Results of the type 3 test of treatments and effects from PROC MIXED for Cu, Fe, and Zn aboveground dry matter 
uptake (mg kg-1) for all sampling periods in 2009. 
 
2009 Micronutrients Copper (Cu) Iron (Fe) Zinc (Zn) 
14WAP** 20WAP** 24WAP** 14WAP** 20WAP** 24WAP** 14WAP** 20WAP** 24WAP** 
Effects -------------mg kg-1------------- -------------mg kg-1------------- -------------mg kg-1------------- 
Crops          
 PS*** 6.43 4.25 2.35b 107.05 169.86 152.48 15.75 20.80 18.94 
FS*** 9.87 5.42 4.30a 193.36 201.35 163.48 26.98 20.12 17.97 
GS*** 8.57 4.08 --- 131.04 173.04 --- 19.98 29.60 --- 
Corn*** 10.13 4.66 --- 128.47 147.56 --- 18.41 21.80 --- 
Irrigation          
irrigated 8.87 5.45a 3.40 157.09 192.50 185.67 20.24 22.63 19.52 
non-irrigated 8.63 3.76b 3.26 122.88 153.41 130.29 20.32 23.52 17.39 
Tillage          
conservation 7.29b 4.73 3.16 116.87b 172.09 167.03 19.22 24.79a 19.28 
conventional 10.21a 4.48 3.48 163.09a 173.82 148.93 21.34 21.36b 17.62 
    
Source of Error -------------p-value------------- -------------p-value------------- -------------p-value------------- 
crops (C) 0.1389 0.5764 0.0201* 0.6268 0.8252 0.7683 0.2796 0.5974 0.6812 
irrigation (I) 0.8261 0.0397* 0.7476 0.3448 0.4210 0.2174 0.9781 0.7017 0.5631 
tillage (T) 0.0007* 0.5339 0.5292 0.0020* 0.9220 0.5142 0.1789 0.0618* 0.4573 
CxI 0.2650 0.9655 0.9804 0.5321 0.2747 0.4875 0.0626 0.2217 0.5203 
CxT 0.0146* 0.1624 0.9438 0.3349 0.0070 0.7609 0.0033* 0.4627 0.3184 
CxT 0.1360 0.5860 0.4688 0.6424 0.7874 0.7429 0.0602* 0.5874 0.6454 
CxIxT 0.4068 0.2438 0.5736 0.0734 0.1189 0.7844 0.3996 0.1172 0.3119 
          
* Significant at 0.10 level of probability 
** Weeks after planting 
***PS: photoperiod sensitive sorghum (1990), FS: forage sorghum (SS506), GS: grain sorghum (NK300), Corn: Pioneer31G65. 
 
91 
 
Table 1-14: Results of the type 3 test of treatments and effects from PROC MIXED for 
corn grain dry matter (Mg ha-1) yield for 2008 and 2009. 
 
Corn grain yield Years 2008 2009 
Treatments --------Grain dry matter (Mg ha-1)------- 
Sampling period    
14 WAP** 8.17b 7.05b 
18 / 20 WAP*** 8.76a 8.18a 
Irrigation    
Irrigated 9.67a 7.76 
Non-irrigated 7.26b 7.48 
Tillage    
Conservation  8.54 7.77 
Conventional 8.40 7.46 
   
Source of Error ------------------?-value------------------- 
Sampling period (SP) 0.0233* 0.0691* 
Irrigation (I) 0.0072* 0.7247 
Tillage (T) 0.5576 0.6013 
SP x I 0.1785 0.4364 
SP x T 0.6689 0.4121 
I x T 0.6679 0.3760 
SP x I x T 0.6633 0.8692 
  
* Significant at the 0.10 level of probability. 
** Weeks after planting. 
*** Samples collected at 18 WAP** in 2008, and at 20 WAP** in 2009. 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
92 
Table 1-15: Results of the type 3 test of treatments and effects from PROC MIXED for P, K, Ca and Mg corn grain uptake (mg kg-1) 
for all sampling periods in 2008 and 2009. 
 
Corn  
Grain  
Primary nutrients uptake Secondary nutrients uptake 
Phosphorus (P) Potassium (K) Calcium (Ca) Magnesium (Mg) 
2008 2009 2008 2009 2008 2009 2008 2009 
Treatments -------------g kg-1------------- -------------g kg-1------------- -------------g kg-1------------- -------------g kg-1------------- 
Sampling period          
14WAP*** 3423.67a 3414.56a 4128.33a 4194.46a 62.75a 66.78 1378.88a 1363.01a 
 18 / 20 WAP** 2701.00b 2603.81b 3444.75b 2965.29b 47.38b 77.39 1057.10b 1083.16b 
Irrigation         
irrigated 2760.48b 2723.13b 3570.49b 3336.88b 46.95b 66.26 1103.11b 1094.73b 
non-irrigated 3364.19a 3295.24a 4002.58a 3822.87a 63.18a 77.91 1332.87a 1351.43a 
Tillage         
conservation 3161.31a 3065.43 3795.78 3571.66 54.40 66.85 1247.03a 1240.53 
conventional 2664.36b 2952.94 3777.30 3588.09 55.76 77.32 1188.95b 1205.64 
     
Source of Error -------------p-value------------- -------------p-value------------- -------------p-value------------- -------------p-value------------- 
Sampling period (SP) 0.0023* 0.0055* 0.0132* 0.0009* 0.0588* 0.6631 0.0017* 0.0052* 
irrigation (I) 0.0119* 0.0326* 0.0175* 0.0374* 0.0742* 0.4460 0.0063* 0.0395* 
tillage (T) 0.0375* 0.2464 0.8243 0.8455 0.6095 0.2706 0.0986* 0.4154 
SPxI 0.5312 0.0831* 0.0569* 0.4583 0.5604 0.3431 0.4366 0.0772* 
SPxT 0.8998 0.4226 0.6637 0.8788 0.3570 0.2660 0.7526 0.2830 
SPxT 0.3586 0.7666 0.1112 0.6933 0.7007 0.2844 0.7946 0.8945 
SPxIxT 0.3477 0.2649 0.9170 0.3276 0.3905 0.9230 0.5091 0.6993 
         
* Significant at the 0.10 level of probability. 
** Weeks after planting. 
*** Samples collected at 18 WAP** in 2008, and at 20 WAP** in 2009. 
 
 
 
93 
Table 1-16: Results of the type 3 test of treatments and effects from PROC MIXED for Cu, Fe, and Zn corn grain uptake (mg kg-1) for 
all sampling periods in 2008 and 2009. 
 
Corn**** 
Grain  
Micronutrients 
Copper (Cu) Iron (Fe) Zinc (Zn) 
2008 2009 2008 2009 2008 2009 
Treatments -------------g kg-1------------- -------------g kg-1------------- -------------g kg-1------------- 
Sampling period        
14WAP** 4.50 2.26 12.33 15.01a 26.22a 25.62a 
 18 / 20 WAP*** 1.60 1.58 21.76 6.39b 21.40b 19.69b 
Irrigation       
irrigated 4.07 1.82 13.36b 7.46 20.72b 19.91b 
non-irrigated 2.03 2.02 20.73a 13.94 26.91a 2541a 
Tillage       
conservation 4.05 1.89 15.83 9.49 24.82a 22.77 
conventional 2.05 1.95 18.25 11.91 22.80b 22.55 
    
Source of Error -------------p-value------------- -------------p-value------------- -------------p-value------------- 
Sampling period (SP) 0.2794 0.3614 0.3747 0.0508* 0.0145* 0.0037* 
irrigation (I) 0.4292 0.6727 0.0669* 0.3305 0.0064* 0.0663* 
tillage (T) 0.3558 0.7421 0.6909 0.4516 0.0661* 0.8377 
SPxI 0.4624 0.7965 0.8344 0.5384 0.2818 0.0112* 
SPxT 0.4323 0.1606 0.9546 0.3036 0.2229 0.5494 
SPxT 0.3351 0.1730 0.3132 0.6252 0.2150 0.8105 
SPxIxT 0.2722 0.3469 0.7416 0.4913 0.6712 0.1285 
       
* Significant at the 0.10 level of probability. 
** Weeks after planting. 
*** Samples collected at 18 WAP** in 2008, and at 20 WAP** in 2009. 
****Corn: Pioneer31G65. 
 
94 
 
Table 1-17: Results of the type 3 test of treatments and effects from PROC MIXED for 
GS grain dry matter (Mg ha-1) yield for 2008 and 2009. 
 
GS**** ? grain yield Years 2008 2009 
Treatments --------Grain dry matter (Mg ha-1)------- 
Sampling Period   
14 WAP** 4.40 --- 
18 / 20 WAP*** 4.62 1.54 
Irrigation   
Irrigated 5.06a 1.81 
Non-irrigated 3.96b 1.27 
Tillage   
Conservation  4.49 1.86 
Conventional 4.53 1.52 
   
Source of Error ------------------?-value------------------- 
Sampling Period (SP) 0.5163 --- 
Irrigation (I) 0.0861* 0.2659 
Tillage (T) 0.8212 0.3799 
SP x I 0.8787 --- 
SP x T 0.8553 --- 
I x T 0.8232 0.2842 
SP x I x T 0.0707* --- 
 
* Significant at the 0.10 level of probability. 
** Weeks after planting. 
*** Samples collected at 18 WAP** in 2008, and at 20 WAP** in 2009. 
*** GS: grain sorghum (NK300) 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
95 
Table 1-18: Results of the type 3 test of treatments and effects from PROC MIXED for P, K, Ca, and Mg GS grain uptake (mg kg-1) 
for all sampling periods in 2008 and 2009. 
 GS****    
Grain  
Primary nutrients uptake Secondary nutrients uptake 
Phosphorus (P) Potassium (K) Calcium (Ca) Magnesium (Mg) 
2008 2009 2008 2009 2008 2009 2008 2009 
Treatments -------------g kg-1------------- -------------g kg-1------------- -------------g kg-1------------- -------------g kg-1------------- 
Sampling period          
14WAP** 3154.26b --- 3628.78b --- 135.20 --- 1666.36b --- 
 18 / 20 WAP*** 4325.52a 3904.99 4355.52a 3463.38 131.16 221.04 2176.27a 2041.05 
Irrigation         
irrigated 3734.01 3707.02 3946.13 3365.56 105.90 218.57 1858.23 1956.66 
non- irrigated 3745.78 4102.95 4038.17 3561.19 160.46 223.51 1984.41 21.2544 
Tillage         
conservation 3818.45 3697.31 4054.85 3436.31 117.82b 190.60b 1916.88 1924.57b 
conventional 3661.33 4112.66 3929.45 3490.44 148.54a 251.48a 1925.76 2157.53a 
     
Source of Error -------------p-value------------- -------------p-value------------- -------------p-value------------- -------------p-value------------- 
Sampling period (SP) 0.0196* --- 0.0536* --- 0.8050 --- 0.0074* --- 
irrigation (I) 0.9393 0.1494 0.5076 0.5073 0.1363 0.8852 0.1370 0.3222 
tillage (T) 0.4815 0.1470 0.5294 0.8568 0.0576* 0.0610* 0.9361 0.0498* 
SPxI 0.9775 --- 0.3996 --- 0.4332 --- 0.9062 --- 
SPxT 0.9427 --- 0.9668 --- 0.9541 --- 0.9892 --- 
IxT 0.0772* 0.0847* 0.4731 0.2142 0.0670 0.1224 0.0914* 0.0912* 
SPxIxT 0.1229 --- 0.1314 --- 0.7033 --- 0.2172 --- 
         
* Significant at the 0.10 level of probability. 
** Weeks after planting. 
*** Samples collected at 18 WAP** in 2008, and at 20 WAP** in 2009. 
**** GS: grain sorghum (NK300) 
 
 
 
96 
Table 1-19: Results of the type 3 test of treatments and effects from PROC MIXED for Cu, Fe, and Zn GS grain uptake (mg kg-1) for 
all sampling periods in 2008 and 2009. 
GS**** 
Grain  
Micronutrients 
Copper (Cu) Iron (Fe) Zinc (Zn) 
2008 2009 2008 2009 2008 2009 
Treatments -------------g kg-1------------- -------------g kg-1------------- -------------g kg-1------------- 
Sampling period        
14WAP** 3.78 --- 28.02 --- 19.32b --- 
 18 / 20 WAP*** 1.82 3.03 47.52 23.4 29.64a 22.39 
Irrigation       
Irrigated 1.31 3.44a 32.70 19.15 21.66b 19.83b 
non-irrigated 4.28 2.61b 42.84 27.85 27.29a 24.95a 
Tillage       
Conservation 1.86 3.04 34.05 20.39 24.87 20.08b 
Conventional 3.74 3.01 41.48 26.61 24.09 24.71a 
    
Source of Error -------------p-value------------- -------------p-value------------- -------------p-value------------- 
Sampling period (SP) 0.2477 --- 0.1580 --- 0.0610* --- 
irrigation (I) 0.1911 0.0225* 0.3801 0.4604 0.0489* 0.0199* 
tillage (T) 0.1201 0.9600 0.4488 0.2756 0.6759 0.0125* 
SPxI 0.2313 --- 0.2350 --- 0.8760 --- 
SPxT 0.1688 --- 0.3045 --- 0.3266 --- 
IxT 0.1850 0.3698 0.7637 0.2522 0.2093 0.2000 
SPxIxT 0.1292 --- 0.1250 --- 0.2629 --- 
       
* Significant at the 0.10 level of probability. 
** Weeks after planting. 
*** Samples collected at 18 WAP** in 2008, and at 20 WAP** in 2009. 
**** GS: grain sorghum (NK300) 
 
 
 
97 
Table 1-20: Results of the type 3 test of treatments and effects from PROC MIXED for aboveground dry matter holocellulose, lignin, 
and ash content (g kg-1) for all sampling periods in 2008. 
2008 Biomass fiber and ash content Hollocellulose Lignin Ash 
14WAP** 18WAP** 24WAP** 14WAP** 18WAP** 24WAP** 14WAP** 18WAP** 24WAP** 
Effects -------------g kg-1------------- -------------g kg-1------------- -------------g kg-1------------- 
Crops          
PS*** 715.4a 700.6a 673.5 65.7b 67.0a 83.5b 52.0bc 43.2b 38.9b 
FS*** 686.83b 653.7c 692.6 71.4a 61.7b 91.3a 47.8c 43.9b 51.7a 
GS*** 686.5b 650.9c --- 58.2c 58.9c --- 58.0a 56.0a --- 
Corn*** 687.4b 675.9b --- 57.8c 57.7c --- 55.8ab 50.2ab --- 
Irrigation          
Irrigated 699.6 676.7a 682.5 70.1a 70.8a 91.5a 51.1b 46.6 44.8 
non-irrigated 688.2 664.9b 683.6 56.4b 61.3b 83.2b 55.7a 50.0 45.8 
Tillage          
Conservation 692.7 670.1 678.0b 65.0a 65.4 87.5 54.7a 49.4 45.5 
Conventional 695.1 670.5 688.1a 61.5b 66.7 87.3 52.1b 47.2 45.0 
 -------------p-value------------- -------------p-value------------- -------------p-value------------- 
Source of Error        
crops (C) 0.0216* 0.0022* 0.3817 0.0001* 0.0001* 0.0629* 0.0136* 0.0296* 0.0967* 
irrigation (I) 0.1631 0.0772* 0.7512 0.0005* 0.0101* 0.0014* 0.0041* 0.3224 0.8430 
tillage (T) 0.4781 0.9499 0.0030* 0.0078* 0.3382 0.9387 0.0063* 0.1619 0.8115 
CxI 0.0197* 0.1146 0.5314 0.1431 0.6888 0.6452 0.1421 0.5428 0.0767* 
CxT 0.2788 0.5611 0.4948 0.5754 0.1969 0.7504 0.7137 0.4186 0.3360 
IxT 0.2180 0.4027 0.2796 0.5530 0.6693 0.1069 0.0081* 0.4197 0.1523 
CxIxT 0.2341 0.8175 0.3533 0.0739* 0.2012 0.9542 0.0836* 0.7765 0.9701 
          
* Significant at the 0.10 level of probability. 
**Weeks after planting. 
***PS: photoperiod sensitive sorghum (1990), FS: forage sorghum (SS506), GS: grain sorghum (NK300), Corn: Pioneer31G65. 
 
 
 
 
98 
Table 1-21: Results of the type 3 test of treatments and effects from PROC MIXED for aboveground dry matter holocellulose, lignin, 
and ash content (g kg-1) for all sampling periods in 2009. 
2009 Biomass fiber and ash content Holocellulose Lignin Ash 
14WAP** 20WAP** 24WAP** 14WAP** 20WAP** 24WAP** 14WAP** 20WAP** 24WAP** 
Effects -------------g kg-1------------- -------------g kg-1------------- -------------g kg-1------------- 
Crops          
PS*** 696.5ab 690.1b 663.5 69.8b 94.1a 81.2a 60.5 44.6b 39.2b 
FS*** 674.5bc 684.0b 682.0 74.5a 90.2a 85.5b 65.2 55.1a 56.3a 
GS*** 656.0c 683.5b --- 60.0c 92.1a --- 61.8 57.6a --- 
Corn*** 702.1a 765.9a --- 57.5c 74.3b --- 59.8 39.0b --- 
Irrigation          
Irrigated 686.04 707.3 675.4 68.5a 89.3 86.9 61.5 49.3 47.6 
non-irrigated 678.2 704.5 669.0 62.4b 86.1 79.7 62.1 48.8 47.9 
Tillage          
Conservation 683.6 713.1a 672.4 68.0a 89.0 83.9 58.1b 48.3 47.9 
Conventional 681.0 698.6b 673.0 62.9b 86.4 82.7 65.6a 49.8 47.5 
 -------------p-value------------- -------------p-value------------- -------------p-value------------- 
Source of Error        
crops (C)  0.0147* 0.0001* 0.1706 0.0001* 0.0010* 0.0164* 0.1885 0.0067* 0.0094* 
irrigation (I) 0.2251 0.5584 0.4269 0.0129* 0.3689 0.1254 0.7946 0.8884 0.8558 
tillage (T) 0.3839 0.0049* 0.9529 0.0304* 0.1809 0.6456 0.0002* 0.3252 0.8390 
CxI 0.4571 0.5794 0.3862 0.6709 0.7545 0.8239 0.2820 0.8065 0.9897 
CxT 0.3007 0.3728 0.5554 0.6107 0.7580 0.7427 0.0505* 0.0763* 0.1736 
IxT 0.7015 0.9937 0.8711 0.8194 0.2593 0.5265 0.1931 0.1994 0.9359 
CxIxT 0.3462 0.5613 0.6894 0.7474 0.9929 0.2016 0.9307 0.7705 0.9438 
          
* Significant at the 0.10 level of probability. 
**Weeks after planting. 
***PS: photoperiod sensitive sorghum (1990), FS: forage sorghum (SS506), GS: grain sorghum (NK300), Corn: Pioneer31G65.
 
99 
 
Figure 1-1: Mean monthly 2008, 2009, and long-term (1999?2009) precipitation at 
experimental location near E. V. Smith Alabama Agricultural Station ? Field Crop Units, 
Shorter, AL. 
 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
0
50
100
150
200
250
300
Jan Fev Mar Apr May Jun Jul Ago Sep Oct Nov Dez
Pr
ecip
tat
ion
 (m
m)
Month
2008 2009 1999-2009 mean
 
100 
 
Figure 1-2: Crops effect on plant height at 6, 9, 14, 18 and 24 weeks after plant in 2008. 
Vertical error bars denote significant differences ? Difference of L.S. means S.E.(0.10).  
PS: photoperiod sensitive sorghum (1990), FS: forage sorghum (SS506), GS: grain 
sorghum (NK300), Corn: Pioneer31G65. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
Plan
t heigh
t (m
)
weeks after planting
PS FS GS Corn
2008
 
101 
 
Figure 1-3: Crops effect on plant height at 6, 9, 14, 18, and 24 weeks after plant in 2009. 
Vertical error bars denote significant differences ? Difference of L.S. means S.E.(0.10). PS: 
photoperiod sensitive sorghum (1990), FS: forage sorghum (SS506), GS: grain sorghum 
(NK300), Corn: Pioneer31G65. 
 
 
 
 
 
 
 
 
 
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
Plan
t height 
(m
)
weeks after planting
PS FS GS Corn
2009
 
102 
 
Figure 1-4: Irrigation effect on aboveground dry matter (Mg ha-1) for both years. Letters 
denote significant differences ? Difference of L.S. means S.E.(0.10) means separation 
between treatments at the same year. 
 
 
 
 
 
 
 
 
 
 
 
 
a
a
b
b
0
5
10
15
20
25
Above
gr
oun
d dry 
mat
ter
 (M
g ha
-1 )
irrigated non-irrigated
2008 2009
 
103 
 
Figure 1-5: Tillage effect on aboveground dry matter (Mg ha-1). Letters denote 
significant differences ? Difference of L.S. means S.E.(0.10) means separation between 
treatments at the same year. 
 
 
a
a
a
b
0
5
10
15
20
25
1 2
Above
gr
oun
d dry 
mat
ter
 (M
g ha
-1 )
conservation conventional
2008 2009
 
 
104 
Figure 1-6: Crops effect on aboveground dry matter production (Mg ha-1) during 3 different periods in 2008. Letters denote separation 
significant differences ? Difference of L.S. means S.E.(0.10) among all treatments in any period. PS: photoperiod sensitive sorghum 
(1990), FS: forage sorghum (SS506), GS: grain sorghum (NK300), Corn: Pioneer31G65. 
 
d
b
a
c c
bc
e e
f
f
0
5
10
15
20
25
30
35
1 2 3
Abovegr
ou
nd
 dr
y m
atte
r (M
g h
a-1
)
Sampling time
PS FS GS Corn
18 weeks after planting14 weeks after planting 24 weeks after planting
2008
 
 
105 
Figure 1-7: Crops effect on aboveground dry matter production (Mg ha-1) during 3 different periods in 2009. Letters denote 
significant differences ? Difference of L.S. means S.E.(0.10) separation among all treatments in any period. PS: photoperiod sensitive 
sorghum (1990), FS: forage sorghum (SS506), GS: grain sorghum (NK300), Corn: Pioneer31G65. 
 
b
a
cdcd
ef
g
c
de
f
g
0
5
10
15
20
25
1 2 3
Abovegr
ou
nd
 dr
y m
atte
r (M
g h
a-1
)
Sampling time
PS FS GS Corn
20 weeks after planting14 weeks after planting 24 weeks after planting
2009
 
 
106 
Figure 1-8: Crops x irrigation interaction effect on aboveground dry matter (Mg ha-1) during 3 different periods in 2008. Vertical 
error bars denote significant differences ? Difference of L.S. means S.E.(0.10). WAP: weeks after planting, PS: photoperiod sensitive 
sorghum (1990), FS: forage sorghum (SS506), GS: grain sorghum (NK300), Corn: Pioneer31G65. 
 
0
5
10
15
20
25
30
35
40
1 2 3 4 5 6
Abovegr
ou
nd
 dr
y m
atte
r (M
g h
a-1
)
PS FS GS Corn
14 WAP 
Irrigated Non-irrigated
18 WAP 24 WAP 24 WAP 18 WAP 14 WAP 
2008
 
 
107 
Figure 1-9: Crops x treatments interaction effect on aboveground dry matter (Mg ha-1) during 3 different periods in 2009. Vertical 
error bars denote significant differences ? Difference of L.S. means S.E.(0.10). WAP: weeks after planting, PS: photoperiod sensitive 
sorghum (1990), FS: forage sorghum (SS506), GS: grain sorghum (NK300), Corn: Pioneer31G65. 
 
0
5
10
15
20
25
30
1 2 3 4 5 6
Abovegr
ou
nd
 dr
y m
atte
r (M
g h
a-1
)
PS FS GS Corn
14 WAP 
Irrigated Non-irrigated
20 WAP 24 WAP 24 WAP 20 WAP 14 WAP 
2009
 
108 
 
II. EFFECT OF SORGHUM BIOFUEL PRODUCTION SYSTEMS ON SOIL 
CHARACTERISTICS IN SOUTHEASTERN U.S. 
 
ABSTRACT 
 According to Renewable Fuels Standard (RFS) ? Energy Policy Act of 2005, the 
U.S. must reduce foreign oil dependence, where the target is to produce 36 billion gallons 
of oil equivalent in 2022 (RFA, 2010). Cellulosic material is considered an alternative 
source for bioenergy production, because it is renewable and environmental improved 
(Peters and Thielman, 2008). Annual crops, such as sorghum (Sorghum bicolor L.) can be 
cultivated in current row-crop production systems, which could provide food and 
cellulosic feedstock production. However, the impacts of removing cellulosic biomass on 
agricultural soils must not be ignored. The objective of this study was to evaluate the 
effect of tillage and irrigation on soil characteristics such as soil organic carbon (SOC), 
nitrogen (N), bulk density (Bd), cone index (CI), and volumetric water content (Wv) 
when producing cellulosic bioenergy feedstock from sorghum and corn in southeastern 
U.S.  Three sorghum varieties and one forage corn were evaluated. The types of sorghum 
evaluated were: grain sorghum ? NK300 (GS), high biomass forage sorghum ? SS 506 
(FS), and a variety of photoperiod sensitive forage sorghum - 1990 (PS). These 3 
different varieties and a forage corn (Zea mays L.) ? Pioneer 31G65 were grown for two 
consecutive years (2008 and 2009) under irrigated and non-irrigated treatments, and 
under two different tillage systems: conventional (total disked area to a depth
 
109 
 
of  0.15 m) and conservation tillage (in-row subsoiling to a depth of  0.30 m) which 
resulted in a strip-split-plot design.  Results showed that SOC increased near soil surface 
(0.10 ? 0.15 m), but it decreased from 0.40 ? 0.45 after 2 years of cropping. SOC losses 
were higher in conventional than conservation tillage. Total nitrogen in soil (N) 
drastically increased at all evaluated soil depths (0 ? 0.50 m). This N increment in soil 
might be related to high N application during both years. N was increased in deep layers 
due to percolation which could result in environmental degradation. Additionally, soil 
consolidation was observed after two years of cropping. Bulk density values increased at 
all evaluated depths after two year period, but those values were always lower than 
threshold for soil compaction (2 Mg ha-1).  PS showed significant lower Bd than corn in 
surface layers (0.05 ? 0.20 m). Irrigated plots had higher Bd than non-irrigated plots at 
both 0.05 ? 0.10 and 0.20 ? 0.25 m soil layers. In addition, conventional plots showed 
higher Bd at (0.15 ? 0.30 m). Higher Bd in conventional plots might restrict water 
drainage which could explain its higher Wv values at 0.10, 0.20 and 0.40 m soil depths in 
most days. Finally, CI values also showed improved soil conditions at in-row positions 
for conservation plots, with restrictive layers being found at depths of 0.15 m for 
conventional plots. Therefore, conservation tillage, PS and potentially reduced N 
applications were recommended in order to decrease farmer inputs, to improve soil 
condition, to maximize cellulosic biomass production and to prevent environmental 
degradation.            
Key words: Biofuels, biomass, sorghum, cone index, SOC, nitrogen, bulk density  
 
 
 
110 
 
1. INTRODUCTION 
 
 The US government established the Energy Independence and Security Act of 
2007 amending the Renewable Fuels Standard (RFS) ? Energy Policy Act of 2005, in 
order to reduce foreign oil dependence, greenhouse gas emissions and provide 
meaningful economic opportunity in US. The RFS target for the US is to produce 36 
billion gallons in 2022 (RFA, 2010). Cellulosic material must be considered as an 
alternative source for bioenergy production, because it can result in security of energy 
supply (renewable) and diminish green house gas emissions to the atmosphere (Peters 
and Thielman, 2008). In regards to food production, cellulosic biomass must be 
considered as a potential crop from agricultural lands. One potential bioenergy crop that 
could be produced in traditional row-crop systems is sorghum which could exist in a 
rotation system. However, one of the negative impacts of removing large amounts of 
cellulosic biomass from fields is the impact on agricultural soils which should not be 
ignored. 
    Southern Coastal Plain soils are highly weathered, erodible, carbon depleted and 
have low water holding capacity. Compounding the agricultural production problem in 
the southeastern U.S. is the prevalent droughts that have severely limited production over 
the last several years.  Appropriate soil and water management systems must be 
developed for sorghum production in order to achieve high amounts of cellulosic biomass 
production without land degradation. Conservation systems, including cover crops  
combined with in-row subsoiling have shown improvement in soil conditions (water 
retention, organic matter, and soil structure) when applied in southeastern conditions 
 
111 
 
(Reeves, 1994; Ess et al., 1998; Raper et al., 2000), therefore they should be evaluated for 
producing bioenergy feedstock in the southeast U.S.. 
 Different parameters are considered crucial to evaluate soil under different 
managements. Quantifying soil organic carbon (SOC) and nitrogen (N) balance in soils is 
considered a fundamental tool in order to monitor the exchange of CO2 and NO2 between 
soil and atmosphere. Thus, SOC is considered the most powerful factor to monitor soil 
quality (Shukla et al., 2006; Brejda et al, 2000a, 2000b).  SOC has been shown to affect 
soil water content, soil movement and overall production (Shukla et al, 2006).  
 Soil compaction has negatively impacted plant production. Hamza and Anderson 
(2005) cited that soil compaction negatively affected root growth in soils, which directly 
resulted in reduced biomass production. Therefore, soil compaction is a crucial factor to 
be considered in our Southeastern soils when producing sorghum cellulosic biomass to 
avoid yield losses. Furthermore, bulk density (Bd) and cone index (CI) were considered 
two important tools to monitor soil compaction (Raper, 2005). Additionally, soil water 
content is an important parameter for plant production, because it influences all physical, 
chemical and biological activities in soil. Good soil water content (Wv) for plants is 
crucial to produce high amounts of cellulosic biomass.  
 The objective of our study was to evaluate the effect of two tillage systems: 
conservation (in-row subsoiling to a depth of 0.30 m) and conventional (total disked area 
to a depth of 0.15 m) under two irrigation systems (irrigated vs. rainfed) on soil 
characteristics such as SOC, N, Bd, CI, and Wv when producing cellulosic bioenergy 
feedstock from sorghum and corn. 
 
112 
 
 Additionally, a rye (Secale cereale L.) cover crop was integrated as part of 
conservation system to maximize the amount of biomass produced and provide ground 
cover for conservation treatments during the winter months. Also, a new variety of sunn 
hemp (Crotalaria juncea L.) was included in conservation system to provide additional 
nitrogen for the rye winter cover. 
 
2. MATERIAL AND METHODS 
 
2.1 Site description 
A study was initiated in November of 2007 and conducted for 2 years at the E. V. 
Smith Alabama Agricultural Station ? Field Crop Units, Shorter, AL (85?:53?50? W, 
32?:25?22? N). The location had been cropped previously with cotton (Gossipyum 
hirsutum L.) for 8 years in a conservation tillage system following Alabama Extension 
System recommendations. The soil type was a Marvyn Loamy sand (fine-loamy, 
kaolinitic, thermic, typic Kanhapludults). In order to maximize the amount of biomass 
produced and provide ground cover during the winter months, the entire field was planted 
with a rye cover crop before planting corn and sorghum. Preceding the rye was a new 
variety of sunn hemp to provide nitrogen. 
 
 
 
 
 
 
113 
 
2.2. Cultural practices and Treatments 
 Rye Elbon was planted at 100 kg ha-1, in early November each year using a no-till 
drill (Great Plains Mfg. Inc., Salina, KS)1.  Rye cultural practices were based on Alabama 
Cooperative Extension System recommendations. In early April each year, the rye cover 
crop was terminated with glyphosate (N-phosphonomethyl glycine). 
 In late April of each year, starter fertilizer was applied at a rate of 14, 4, 14, and 5 
kg ha-1 of N, phosphorus (P), potassium (K) and sulfur (S), respectively according to the 
Alabama Cooperative Extension System soil test recommendations (Adams and Mitchell, 
2000).  
Two different tillage systems were implemented shortly after fertilization: 
conventional and conservation systems. Conservation plots received in-row subsoiling 
with a narrow-shanked subsoiler (KMC, Kelley Manufacturing Co., Tifton, GA) to a 
depth of 0.35-0.40 m. Conventional plots were disked/leveled using a 950 John Deere 
Disk (Deere & Company, Moline, IL) to a depth 0.15 m. Then, all four bioenergy crops,  
including grain sorghum - NK300 (GS), forage sorghum - SS506 (FS), photoperiod-
sensitive sorghum - 1990 (PS), and hybrid corn Pioneer 31G65  were seeded in rows 
spaced at 0.92 m using a John Deere 1700 XP planter (Deere & Company, Moline, IL). 
Seeding rate was established by the company?s recommendations which were 407,700 
seeds ha-1 for FS, GS and PS (Sorghum Partners 2008a, 2008b, 2010c). Pioneer 31G65 
seeding rate were 78,300 seeds ha-1 (Pioneer Hi-bred International Inc., 2010). Tillage 
and planting were performed with a tractor equipped with a Trimble AgGPS Autopilot 
automatic steering system (Trimble, Sunnyvale, CA), with centimeter level precision. An 
                                                 
1 The use of company names or trade names does not indicate endorsement by Auburn 
University or USDA ? ARS. 
 
 
114 
 
additional 110 kg N ha-1 of ammonium nitrate (34%) was side dressed with a liquid 
applicator in row middles during growing season each year.   
 During the growing season each year, the irrigation plots were managed with two 
different regimes: non-irrigated (rainfed) and irrigated. In the irrigated plots, water was 
applied in appropriate timing and amounts to provide plants with good water availability 
during the growing season. Irrigation was terminated at 16 weeks after planting in both 
years. Alabama Cooperative Extension System recommendations were used to apply all 
insecticides (ACES, 1988). 
 Grain from GS and corn were harvested in late August using a Gleaner G 
combine (AGCO Company, Duluth, GA). The remaining biomass was cut and baled. 
Sunn hemp was planted at a rate of 50 kg/ha immediately after harvest using a no-till drill 
(Great Plains Mfg. Inc., Salina, KS) in all conservation tillage plots. PS and FS were 
harvested in late October. 
 
2.3. Experimental Design and Statistical Analysis 
Bioenergy crops, irrigation and tillage practices were evaluated in a strip-split plot 
design (factorial 4x2x2). The four crops served as the horizontal treatments. Two 
irrigation regimes (irrigated and non-irrigated) served as the vertical plots, and two tillage 
systems (conservation and conventional) served as sub-plots. 
The experimental area (84 m long by 60 m) was divided into 4 replications. Each 
replication was divided into 4 areas which were separated by borders 9.1 m long by 3.7 m 
wide in order to evaluate the bioenergy crops: PS, FS, GS and corn. Plots were divided 
into two different irrigation regimes (irrigated, non-irrigated plots), which were also 
 
115 
 
separated by borders 9.1-m long by 3.7-m wide. Irrigation regime plots were also divided 
in two different tillage systems (conservation and conventional systems) which resulted 
in 64 experimental units 9.1-m long by 3.7-m wide. Experimental units were composed 
of 4 rows with row spacings of 0.92 m. All measurements were collected from the two 
middle rows of each experimental unit.  
 Measurements were evaluated in a strip-split-plot design with four replications, 
where crops, irrigation regimes and tillage systems were considered respectively 
horizontal, vertical and sub-treatments. Bioenergy crops were randomly assigned into 
each replication, irrigation regimes were assigned into each bioenergy crop, and tillage 
systems were randomly assigned into each irrigation regime. 
 All data were analyzed using the appropriate strip-split plot design with PROC 
MIXED of the Statistical Analysis System (SAS) (Littel et al., 1996).  Replication and its 
interactions with bioenergy crops (crops) and irrigation regimes were considered random 
effects and treatments and other interactions considered fixed. Data were analyzed and 
discussed considering both years, except when significant year x treatment interaction 
occurred. In this case, data were analyzed by year. Treatment means were separated by the 
LSMEANS procedure (SAS Inst. Inc., Cary, NC) when protected by F-tests significant at ? 
of 0.10, and are reported as least squares means ? SE.  
 
2.4. Data Collection 
2.4.1. Soil organic carbon (SOC) and total nitrogen (N).  
 Soil organic carbon and total nitrogen nutrient were determined from soil samples 
collected before planting in 2008, and after harvesting in 2009. In each experimental unit, 
soil core samples (9 cm of diameter) were collected in ten different depth ranges: 0 ? 
 
116 
 
0.05, 0.05 ? 0.10, 0.10 ? 0.15, 0.15 ? 0.20, 0.20 ? 0.25, 0.25 ? 0.30, 0.30 ? 0.35, 0.35 ? 
0.40, 0.40 ? 0.45, 0.45 ? 0.50 m for each of three different non-trafficked middle row 
positions.  The soil samples were oven dried at 55 ?C until constant weight, slightly 
crushed, sieved through 2 mm mesh, and then finely ground using a conveyor-belt roller 
mill.  Soil subsamples were submitted to dry combustion (Yeomans and Bremner, 1991) 
using LECO TruSpec analyzer (Leco Corporation, St. Joseph, MI). 
 
2.4.2. Soil bulk density (Bd). 
 Soil core samples were collected before planting in 2008, and after harvesting in 
2009 using a tractor mounted, hydraulically-driven, soil core sampler (9 cm diameter) to 
determine soil bulk density (Raper et al., 1999). In each experimental unit, three 
insertions of soil core sampler were obtained in the non-trafficked middle row where soil 
core samples were collected at ten different depths: 0 ? 0.05 , 0.05 ?  0.10, 0.10 ? 0.15, 
0.15 ? 0.20, 0.20 ? 0.25, 0.25 ? 0.30, 0.30 ? 0.35, 0.35 ? 0.40, 0.40 ? 0.45, 0.45 ? 0.50 m. 
The undisturbed soil core samples were oven dried at 55 ?C until constant weight.    
 
2.4.3. Cone Index (CI). 
Cone Index measurements were taken 1 week after plating, and 1 week after 
harvesting for both years, using a tractor-mounted, hydraulic-driven, soil cone 
penetrometer (Raper et al., 1999). In each experimental unit, three insertions of multi-
probe soil cone penetrometers were performed where five different positions were 
recorded per insertion:  1) in row; 2) untrafficked interrow ? 0.225 m away from row; 3) 
untrafficked interrow ? 0.45 m away from row; 4) wheel-trafficked row ? 0.225 cm away 
 
117 
 
from row; and 5) wheel-trafficked row ? 0.45 cm away from row. Cone index was 
determined using a soil cone penetrometer with 130 mm2 base area (ASAE Standards, 
2004a; ASAE Standards, 2004b) which were continuously (25 points per second) inserted 
in the soil to a depth of 50cm. Data were averaged for every 0.10 m depth range in order 
to perform statistical analysis and develop contour graphs using Surfer 8 software 
(Golden Software Inc., Golden, CO). Furthermore, soil samples were taken at 0 ? 0.15 m 
and 0.15 ? 0.30 m positions and oven dried at 105?C until constant weight to determine 
soil moisture during cone index readings. 
 
2.4.4. Soil water content (Wv). 
 A TRIME-T3 probe (Micromodultechnik GMBH, Germany) was used to measure 
soil water content based on Time Domain Reflectometry method. PVC access tubes 
having 0.06 m of diameter and 1 m long were installed in one of the two middle rows in 
each experimental unit. Soil water content was measured in row inserting the TRIME-T3 
probe in the access tubes, and readings were collected three times at four different depths: 
0.10, 0.20, 0.40, and 0.60 m. Measurements were stored in a TRIME Data Pilot 
(Micromodultechnik GMBH, Germany) which was connected to TRIME-T3 probe. Thus, 
readings were collected twice per week on mornings throughout the growing season. 
 
 
 
 
 
 
118 
 
3. RESULTS AND DISCUSSION 
 
3.1. Soil Organic Carbon 
  In 2008 before planting, no significant differences were found among samples 
collected in different positions in field for any depth (data not shown). Results suggested 
that the entire field was in similar condition before starting the experiment. Therefore, all 
SOC changes in 2009 after harvesting were related to treatments applied over those two 
years. 
Comparing soil organic carbon samples ? SOC (Mg ha-1) collected in  2008 
before planting with  samples collected in 2009 after harvesting, SOC significantly 
increased 11 and 17 % in the two top layers: 0 ? 0.05 and 0.05 ? 0.10 m, respectively, 
after two consecutive years of cropping. However, our measurements showed reduced 
SOC from 0.10 to 0.50, but those differences were only significant at 0.20 ? 0.25 and 
0.35 ? 0.50 m deep (table 2-1) which showed SOC reductions of 23 and 27 %, 
respectively. Furthermore, soil organic carbon ? SOC (Mg ha-1) tended to decrease with 
depth for both years. 
 In 2009, SOC was not significantly different for each crop at all evaluated depths, 
except for top soil layer (0 ? 0.05 m). At this depth, PS plots (6.9 Mg ha-1) had lower 
SOC than FS (7.5 Mg ha-1), corn (7.4 Mg ha-1), but had similar SOC as GS (6.9 Mg ha-1), 
P = 0.0551 (figure 2-1). SOC did not vary with irrigation treatment at any depth (figure 
2-2). Other studies found similar results when studying different irrigation regimes 
(Churchman and Tate, 1986; Sommerfeldt et al., 1988). Tillage treatments were 
significant different at 0.1 ? 0.15 m (P = 0.0351) and 0.4 ? 0.45 m depths (P = 0.0896). In 
 
119 
 
both layers, conservation tillage showed higher SOC than conventional tillage, 5.2 vs. 4.4 
Mg ha-1 and 2.3 vs. 2.0 Mg ha-1, respectively (figure 2-3). Several authors cited that 
conservation tillage resulted in higher SOC than conventional tillage particularly in layers 
shallower than 0.25 m (Potter et al., 1998; Motta et al., 2002; Zibilske et al, 2002). These 
SOC increases might be related to good amounts of  rye  biomass which was produced 
and not incorporated under the conservation tillage system in 2009. However, other 
authors pointed out that conservation tillage just redistributed SOC in soil, where their 
contents increased at top layers, but the reverse tendency was found in deep layers (Dick 
et al., 1991; Torbert et al., 1999).  
 
3.2. Total Nitrogen (TN) 
 In 2008 before planting, no significant differences were found among total 
nitrogen in soils - TN (Mg ha-1)  samples collected at different positions for any depth 
(data not shown). Results suggested that the entire field was in the same condition before 
starting the experiment. Therefore, all TN changes in 2009 after harvesting were related 
to treatments during those two years.  
Comparing TN (Mg ha-1) samples collected in 2008 before planting with samples 
collected in 2009 after harvesting, TN content increased drastically in all depths after two 
consecutive years of cropping (table 2-2). This N increment in soil might be related to 
high N application during both years in order to express the highest potential of all tested 
crops. Furthermore, TN (Mg ha-1) tended to decrease with depth before planting in 2008.  
A reverse trend was found in 2009 where TN showed higher values in deep layers after 
two years of experiment (2009 after harvest). Because, part of the N applied during both 
 
120 
 
years might not be uptaken by plants, it could percolate deep in the soil because Marvyn 
loamy sand is a well drained and moderately permeable soil which allows easy 
translocation of nutrients (Official Series Description, 2010).     
 In 2009 after harvest, TN was not significantly different among crops at all 
evaluated depths (figure 2-4). Irrigation treatments also showed no significant differences 
in any depth (figure 2-5).  Tillage treatments were significantly different at the 0.25 ? 
0.30 m depth, P = 0.0862 (figure 2-6). In this soil layer, conservation tillage showed 
higher TN than conventional tillage, 0.40 and 0.36 Mg ha-1, respectively. 
 
3.3. Bulk Density 
  Comparing  soil bulk density samples collected in 2008 before planting with  
samples collected in 2009 after harvest, Bd significantly increased at all layers, except at 
0.45 -0.50 m soil layer where Bd was not significantly different after two years of 
cropping.  In both years, Bd tended to increase drastically from near the surface to 0.3 m 
in depth and it tended to increase slightly in layers deeper than 0.30 m (table 2-3).  
 In 2009, crop affected soil bulk density significantly at three different soil layers: 
0.05 ? 0.10 m (P = 0.0471), 0.10-0.15m (P = 0.0102), and 0.15 ? 0.20 (P = 0.0295). In 
those 3 soil layers, PS always had the lowest Bd, respectively, 1.58, 1.63, and 1.68 Mg m-
3. Conversely corn always showed the greatest Bd values, 1.70, 1.72 and 1.78 Mg m-3 
respectively. A reasonable explanation for differences in PS and corn could be that higher 
PS population could increase root density from 0.05 to 0.20 m. High root density in PS 
fields may alleviate soil consolidation due to soil disruption. The other two crops showed 
intermediate Bd values at these same soil depths. GS had Bd values of 1.61, 1.68 and 
 
121 
 
1.74 Mg m-3, respectively and FS showed Bd values of 1.60, 1.71 and 1.76 Mg m-3, 
respectively (figure 2-7). Bulk density values for all crops were in the range proposed for 
a sandy loam soil (1.20 -1.80 Mg m-3), and Bd values from this study were below 2 Mg 
m-3 threshold value for soil compaction (Raper, 2005).  Therefore, we found that the 
sorghum varieties evaluated in the experiment had good development under these 
reasonable soil conditions which resulted in high cellulosic biomass production. 
 Irrigated plots were significantly higher in Bd than non-irrigated fields at 0.10 ? 
0.15 m (P = 0.0533) and 0.20 ? 0.25 m (P = 0.0539) depths in 2009 after harvest (figure 
2-8). In both soil positions, irrigated plots (1.71 and 1.78 Mg m-3, respectively) had 
higher Bd values than non-irrigated plots (1.66 and 1.74 Mg m-3, respectively). 
According to soil moisture measurements obtained during the growing seasons for both 
years, irrigated plots always showed higher soil moisture at 0.10 and 0.20 m depths. And, 
soils with high soil moisture were considered easy to compact due to reduced load 
support and increased deformation capacity, which resulted in higher Bd values (Hamza 
and Anderson, 2005). However, the higher Bd values found in irrigated treatments were 
still lower than 2 Mg ha-1 (threshold for restrictive soil layer) (Raper, 2005).Therefore 
irrigated plots could offer good soil conditions for plant growth, and ADM and grain 
yields would not be negatively affected.   
 Tillage treatments were significantly different at 0.10 ? 0.15 m (P = 0.0131), 
0.15-0.20 m (P = 0.0005), and 0.20 - 0.25 m (P = 0.0074) depths (figure 2-9). 
Conventional tillage (total disked area) always showed significant higher Bd values than 
conservation fields (in-row subsoiled). At these depths (0.10 ? 0.15, 0.15 ? 0.20, and 0.20 
? 0.25 m) Bd values in conventional tillage plots were 1.72, 1.78, and 1.79 Mg m-3, 
 
122 
 
respectively  And, Bd values in conservation tillage plots were 1.65 , 1.71, and 1.73 Mg 
m-3, respectively. Other researchers have found similar values with lower Bd values in 
conservation fields being caused by high biological soil activity due to large amounts of 
residue left on the soil (Lal et al. 1994), and high accumulation of organic matter 
(Edwards et al., 1992). In our fields, conservation plots also showed higher organic 
matter accumulation than conventional plots from 0.10 to 0.25 m depth in soil, but they 
were significantly higher only at depths of 0.10 to 0.15 m. 
 
3.4. Cone Index 
 In all sampling periods, CI data were analyzed by separating in 3 different 
positions; non-traffic, in-row, and traffic. All positions were significantly different from 
each other when comparing between the four different periods of collection (P ? 0.0001). 
Therefore, the statistical analysis was conducted separated by period, position and depth 
(tables 2-4 to 2-8). Tillage was considered the most explanatory factor for CI in all data 
sets, and crop and irrigation treatments had minor effect in CI. 
 Conservation tillage showed lower CI values (27 %) than conventional tillage at 
in-row and non-traffic positions from 0 to 0.30 m soil depth in most sampling periods. 
However, different results were found in traffic positions from 0 to 0.30 m, where CI 
values were 26 and  29 % higher in conventional tillage than conservation tillage in 
spring 2008 and 2009, respectively, but conventional tillage tended to have lower CI 
values than conservation tillage in fall 2008 (14 %) and 2009 (37 %). At deep soil layers 
(0.30 ? 0.50 m), CI values were mostly not significantly different when comparing tillage 
treatments in all positions for spring 2009 and fall 2008 / 2009. Similar CI values 
 
123 
 
between conventional and conservation fields were expected at traffic and non-traffic 
positions, because the soil was not disrupted at deep layers (0.30 ? 0.50 m) for those 
positions. However, low CI values could be found for conservation tillage at in-row 
position, because narrow-shanked subsoiler disrupted the soil down to 0.45 m deep. 
Moreover, conservation tillage showed higher CI values than conventional treatment for 
all positions in spring 2008. Those unexpected results might be related to shallow in-row 
subsoiling (< 0.30m deep) in 2008 and/or different soil moisture between tillage plots at 
same period.  Contour graphs generating penetration isolines were plotted using CI 
means (figures 2-10 and 2-11). Gravimetric soil water content (GWC) was evaluated at 
all sampling periods (table 2-9), which showed small variation in depth and sampling 
period. Those small variations were attributed to different weather conditions among 
sampling periods. 
  In spring of both years, conservation tillage reduced soil resistance to penetration 
at in-row position at subsoiled layer (0 - 0.30m) to values lower than 1.0 MPa which 
offered good conditions for root growth (CI < 2.0 MPa). However, conventional plots 
showed a restrictive layer (CI > 2.0 MPa) at  0.10 ? 0.30 m soil layer in spring of 2009 
which could explain the significantly lower dry aboveground dry matter (ADM) 
production observed in conventional fields (12.2 Mg ha-1 ) than conservation plots (11.0 
Mg ha-1), P = 0.0028. Restrictive layers in Spring 2008 nor low ADM were found for 
conventional fields in 2008. 
 In both years, CI values were higher after harvest (fall) than after planting 
(spring). Note that CI values were particularly elevated (2 to 3 fold) in fall 2008 in both 
conventional and conservation treatments. However, better soil conditions for root 
 
124 
 
growth were always found at in-row position in conservation plots than conventional 
plots, therefore, in-row subsoiling must be recommended.  
 
3.5. Soil water content 
 Crops showed no significant volumetric water (Wv) differences at 0.10 m depth 
for both seasons, except for 82 and 89 days after planting (DAP) at a depth of 0.10 m in 
2009, where FS showed higher Wv values than corn. Generally, corn and GS showed 
lower Wv values than FS and PS at 0.20 m, 0.40 m and 0.60 m depths in both years. 
Those differences were significant for most days in 2009 season at 0.20 and 0.40 depths. 
A plausible explanation for those differences was that GS and corn required more water 
from soils due to the fact that they produced grains while FS and PS just produced 
biomass. Moreover, both FS and PS were cited as drought tolerant (Sorghum Partners, 
2008a; Sorghum Partners, 2008b), because forage sorghums were able to extract water in 
deeper soil layers: 0.45 ? 1.35 m (Farre and Faci, 2006). 
 Irrigated plots always had higher Wv values than non-irrigated fields in both 
years, but those differences were higher in 2008 than in 2009. High precipitation in 2009 
might have reduced the irrigation effect because the aboveground dry matter difference 
between irrigated and non-irrigated fields was greater in 2008 (4.13 Mg ha-1) than 2009 
(1.07 Mg ha-1). Volumetric water content (Wv) differences between irrigation treatments 
tended to decrease in depth for both seasons, where significant differences between 
irrigation regimes were not found at 0.60 m depth.  
 Conventional tillage plots showed higher volumetric water than conservation 
plots during most days at 0.10, 0.20 and 0.40 m depths for both years. But, no significant 
 
125 
 
differences were found at 0.60 m depth. In-row subsoiling 0.30 m deep applied on 
conservation tillage plots might have increased in-row water infiltration causing water to 
move to deep soil layers. Conversely, conventional plots (total disked area to a depth of 
0.15 m) might not result in good soil water drainage, causing water to be retained at soil 
layers above 0.40 m. Additionally, bulk density data were also higher in conventional 
plots than conservation at 0.1 - 0.35 m soil layers, resulting in lower soil porosity. 
Therefore, anaerobic conditions for plants could have occurred during 2009 season which 
contributed to lower aboveground dry matter yields than 2008 season. Figures 2.12 to 
2.35 illustrated Wv for all treatments and depths in both years.  
 
4. CONCLUSIONS 
 
 After 2 years of cropping, SOC increased at surface layers (0 ? 0.10 m), but it 
decreased from 0.10 to 0.50 m. Soil organic carbon losses in deep soil layers were 
numerically higher in conventional tillage than conservation tillage, but SOC significant 
differences between tillage system were only found at 0.10 ? 0.15 and 0.4 ? 0.45 m deep 
in soil.  Irrigation and crops showed no effect in SOC. 
 Nitrogen drastically increased in all soil depths (0 ? 0.50 m) after 2 years of 
cropping. This N increment in soil was probably related to high N application during both 
years in order to express the highest potential cellulosic biomass production of all tested 
crops. Furthermore, total N was higher in deep layers after two years of cropping, 
because part of applied N was not taken up by plants, and it percolated deep in soil which 
could result in environmental degradation. 
 
126 
 
 Soil consolidation was observed after two years of cropping. Bulk density (Bd) 
values increased in all depths during this period. However, all plots showed Bd values 
ranging between 1.58 to 1.79 Mg ha-1 which were below the threshold for soil 
compaction (2 Mg ha-1). Among all tested crops, PS had the lowest Bd values in 
superficial layers (0.05 ? 0.20 m) which was significantly lower than corn. Irrigated plots 
showed higher Bd values than non-irrigated at the 0 to 0.25 m soil layer, but those 
differences were only significantly higher at 0.05 ? 0.10 and 0.2 ? 0.25 m depths. 
 Additionally, conservation tillage (in-row subsoiling to a depth of 0.30 m) 
resulted in better soil conditions than conventional tillage (total disked area to a depth of 
0.15 m) in the depths disrupted by the practice of in-row subsoiling in conservation 
tillage (0.15 ? 0.30 m) because significantly lower values of Bd were found in those 
plots. Higher Bd values in conventional tillage might restrict soil water drainage which 
could explain its higher volumetric water content (Wv) at 0.10, 0.20 and 0.40 m soil 
depths on most days. Cone index (CI) values also showed better soil conditions at in-row 
position for conservation plots.  A restrictive layer at a depth of 0.15 m was found in 
conventional plots after one year of cropping (2008) which could restrict plant growth 
and cellulosic biomass production. 
 Therefore, conservation tillage should be used to grow PS which produced the 
highest biomass and is the recommended bioenergy crop.  Reduced nitrogen application 
should be investigated to decrease inputs and potentially prevent environmental 
degradation. 
 
 
 
127 
 
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131 
 
Table 2-1: Comparison of Marvyn loamy sand SOC (Mg ha -1) within depth between 
2008 and 2009. (Least Squares Means; LS means) 
 
* Significant at the 0.10 level of probability. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Depth (m) LS means  2008 2009 p-value 
 ----Soil organic carbon (Mg ha-1)----  
0 ? 0.05 6.47 7.25 0.0005* 
0.05 ? 0.10 6.08 7.27 0.0006* 
0.10 ? 0.15 5.06 4.78 0.2189 
0.15 ? 0.20 4.68 4.45 0.1454 
0.20 ? 0.25 4.26 3.29 0.0001* 
0.25 ? 0.30 3.59 3.29 0.2544 
0.30 ? 0.35 3.17 2.60 0.0005* 
0.35 ? 0.40 3.02 2.66 0.0550* 
0.40 ? 0.45 3.07 2.13 0.0001* 
0.45 ? 0.50 3.28 1.85 0.0002* 
 
 
132 
Table 2-2: Comparison of Marvyn loamy sand TN (Mg ha -1) within depth between 2008 and 2009. P-values denote significant 
differences between TN LS means. 
 
 
Depth (m) Total Nitrogen   2008 2009 p-value 
 ----LS means  (Mg ha -1)---- --C/N-- ----LS means  (Mg ha -1)---- --C/N--  
0 ? 0.05 0.28 23 0.40 18 0.0001* 
0.05 ? 0.10 0.25 24 0.41 18 0.0001* 
0.10 ? 0.15 0.14 35 0.37 20 0.0001* 
0.15 ? 0.20 0.10 48 0.38 12 0.0001* 
0.20 ? 0.25 0.08 50 0.37 9 0.0001* 
0.25 ? 0.30 0.05 66 0.38 9 0.0001* 
0.30 ? 0.35 0.06 52 0.46 6 0.0001* 
0.35 ? 0.40 0.08 40 0.49 5 0.0001* 
0.40 ? 0.45 0.08 37 0.49 4 0.0001* 
0.45 ? 0.50 ND** -- 0.47 4 -- 
 
* Significant at the 0.10 level of probability. 
** not detected. 
 
 
 
 
 
 
 
 
 
 
133 
 
Table 2-3: Comparison of Marvyn loamy sand bulk density (Mg m-3) within depth 
between 2008 and 2009. 
 
Depth (m) LS means  2008 2009 p-value 
 ---------Bulk density (Mg m-3)---------  
0 ? 0.05 1.18 1.43 ?0.0001* 
0.05 ? 0.10 1.38 1.62 ?0.0001* 
0.10 ? 0.15 1.50 1.69 ?0.0001* 
0.15 ? 0.20 1.61 1.74 ?0.0001* 
0.20 ? 0.25 1.67 1.76 ?0.0001* 
0.25 ? 0.30 1.73 1.79 ?0.0020* 
0.30 ? 0.35 1.74 1.80 ?0.0011* 
0.35 ? 0.40 1.72 1.76 ?0.0240* 
0.40 ? 0.45 1.69 1.73 ?0.0182* 
0.45 ? 0.50 1.65 1.62 ?0.1448 
 
* Significant at the 0.10 level of probability. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
134 
Table 2-4: Results of the type 3 test of treatments and effects from PROC MIXED for Cone index (MPa) for Marvyn loamy sandy at 
0 ? 0.1 m soil layer in all sampling periods of 2008 and 2009. Letters denote significant differences (L.S. means S.E.(0.10) within 
treatment and sampling period). 
 
0 - 0.1 m Cone Index Spring 2008 Fall 2008 Spring 2009 Fall 2009 
Non-traffic In row Traffic Non-traffic In row Traffic Non-traffic In row Traffic Non-traffic In row Traffic 
Effects -------------MPa------------- -------------MPa------------- -------------MPa------------- -------------MPa------------- 
Crops             
PS** 0.49 0.32c 0.30 1.04b 0.91b 1.73bc 0.70 0.39 1.23 0.74b 0.56 1.36a 
FS** 0.55 0.35bc 0.35 0.98b 0.84b 1.57c 0.70 0.35 1.18 0.70b 0.58 1.13b 
GS** 0.57 0.43a 0.40 1.14ab 0.88b 1.88b 0.71 0.33 1.29 0.83ab 0.56 1.37a 
Corn** 0.54 0.39ab 0.35 1.37a 1.07a 2.85a 0.69 0.37 1.39 0.96a 0.59 1.44a 
Irrigation             
irrigated 0.54 0.36 0.37 1.10 0.89 1.83 0.76 0.36 1.33 0.79 0.58 1.28b 
non-irrigated 0.53 0.38 0.33 1.16 0.96 1.83 0.64 0.35 1.22 0.82 0.57 1.36a 
Tillage             
conservation 0.35b 0.22b 0.18b 0.80b 0.83b 1.87 0.60b 0.20b 1.17b 0.68b 0.46b 1.38a 
conventional 0.73a 0.52a 0.52a 1.46a 1.02a 1.79 0.80a 0.52a 1.37a 0.94a 0.68a 1.27b 
 -------------p-value------------- -------------p-value------------- -------------p-value------------- -------------p-value------------- 
Source of Error           
crops (C) 0.4513 0.0358* 0.2416 0.0688* 0.0518* 0.0138* 0.9896 0.6906 0.2470 0.0262* 0.9425 0.0271* 
irrigation (I) 0.8090 0.2484 0.5179 0.6276 0.2758 0.9813 0.1448 0.8473 0.1626 0.7951 0.7270 0.0439* 
tillage (T) 0.0001* 0.0001* 0.0001* 0.0001* 0.0087* 0.3050 0.0001* 0.0001* 0.0189* 0.0006* 0.0001* 0.0396* 
CxI 0.1656 0.7335 0.1244 0.3091 0.2258 0.4533 0.1263 0.2725 0.4236 0.8950 0.4873 0.4496 
CxT 0.8179 0.6468 0.5897 0.0949* 0.4186 0.7473 0.7522 0.8496 0.8700 0.2376 0.3984 0.6492 
IxT 0.7743 0.3041 0.4629 0.7126 0.4891 0.5804 0.1752 0.6150 0.7828 0.5343 0.3809 0.6918 
CxIxT 0.2625 0.1234 0.4277 0.2309 0.4741 0.4503 0.5368 0.0281* 0.4075 0.7916 0.0354* 0.0986 
             
* Significant at the 0.10 level of probability. 
**PS: photoperiod sensitive sorghum (1990), FS: forage sorghum (SS506), GS: grain sorghum (NK300), Corn: Pioneer31G65.
 
 
135 
Table 2-5: Results of the type 3 test of treatments and effects from PROC MIXED for Cone index (MPa) for Marvyn loamy sandy at 
0.1? 0.2 m soil layer in all sampling periods of 2008 and 2009. Letters denote significant differences (L.S. means S.E.(0.10) within 
treatment and sampling period). 
* Significant at the 0.10 level of probability. 
**PS: photoperiod sensitive sorghum (1990), FS: forage sorghum (SS506), GS: grain sorghum (NK300), Corn: Pioneer31G65
0.1 - 0.2 m Cone Index Spring 2008 Fall 2008 Spring 2009 Fall 2009 
Non-traffic In row Traffic Non-traffic In row Traffic Non-traffic In row Traffic Non-traffic In row Traffic 
Effects -------------MPa------------- -------------MPa------------- -------------MPa------------- -------------MPa------------- 
Crops             
PS** 1.22b 0.68 1.63 2.17 1.70 3.19b 1.59 1.02 2.35 1.47c 0.85 2.33 
FS** 1.16b 0.64 1.65 1.25 1.73 3.02b 1.75 0.99 2.34 1.55bc 0.91 2.24 
GS** 1.55a 1.09 1.62 2.35 1.74 3.36b 1.84 0.85 2.41 1.56b 0.72 2.49 
Corn** 1.15b 0.67 1.65 2.67 2.04 4.06a 1.72 1.05 2.43 1.72a 0.75 2.52 
Irrigation             
irrigated 1.26 0.81 1.69 2.22 1.74 3.37 1.83 1.02 2.43 1.60 0.79 2.31 
non-irrigated 1.29 0.73 1.63 2.50 1.86 3.44 1.62 0.93 2.34 1.56 0.82 2.49 
Tillage             
conservation 0.98b 0.54b 1.53b 1.87b 1.09b 3.62a 1.29b 0.25b 2.21b 1.27b 0.65b 2.55a 
conventional 1.56a 1.00a 1.79a 2.85a 2.51a 3.19b 2.16a 1.70a 2.56a 1.88a 0.96a 2.25b 
 -------------p-value------------- -------------p-value------------- -------------p-value------------- -------------p-value------------- 
Source of Error           
crops (C) 0.0861* 0.1982 0.8890 0.2322 0.1532 0.0035* 0.5647 0.5017 0.9521 0.0014* 0.1168 0.2546 
irrigation (I) 0.9055 0.7190 0.6369 0.2796 0.5457 0.7039 0.2326 0.6066 0.5343 0.7920 0.6608 0.1117 
tillage (T) 0.0023* 0.0175* 0.0152* 0.0001* 0.0001* 0.0040* 0.0021* 0.0001 0.0001* 0.0001* 0.0002* 0.0004* 
CxI 0.9025 0.9415 0.6439 0.5984 0.6589 0.2514 0.9830 0.6373 0.4101 0.3255 0.2866 0.1660 
CxT 0.0427* 0.0789* 0.0803* 0.9131 0.5766 0.9274 0.1782 0.9226 0.8308 0.1002 0.5064 0.1536 
IxT 0.2422 0.2987 0.2382 0.8054 0.2234 0.9202 0.4142 0.9034 0.1991 0.2498 0.1122 0.7248 
CxIxT 0.0556 0.1397 0.0615* 0.3154 0.1567 0.6483 0.4446 0.1293 0.6423 0.5121 0.1246 0.7486 
             
 
 
136 
Table 2-6: Results of the type 3 test of treatments and effects from PROC MIXED for Cone index (MPa) for Marvyn loamy sandy at 
0 .2 ? 0.3 m soil layer in all sampling periods of 2008 and 2009. Letters denote significant differences (L.S. means S.E.(0.10) within 
treatment and sampling period). 
0.2 - 0.3 m Cone Index Spring 2008 Fall 2008 Spring 2009 Fall 2009 
Non-traffic In row Traffic Non-traffic In row Traffic Non-traffic In row Traffic Non-traffic In row Traffic 
Effects -------------MPa------------- -------------MPa------------- -------------MPa------------- -------------MPa------------- 
Crops             
PS** 1.86 1.07 2.05 2.85 1.93 3.12b 1.76 1.10 2.46 1.48 0.96 2.32 
FS** 1.48 0.64 1.90 2.62 2.13 3.19b 1.99 1.10 2.25 1.43 1.01 2.30 
GS** 2.01 1.20 2.18 3.18 2.03 3.89a 2.33 1.04 2.69 1.54 0.96 2.49 
Corn** 1.63 1.07 1.94 3.00 1.94 3.65a 1.92 1.06 2.51 1.47 0.99 2.29 
Irrigation             
irrigated 1.76 0.94 2.00 2.74 1.96 3.41 2.17 1.21 2.60 1.37b 0.91 2.23 
non-irrigated 1.73 1.02 2.03 3.08 2.05 3.51 1.83 0.94 2.36 1.58a 1.05 2.46 
Tillage             
conservation 1.70 0.96 1.95 2.80 0.95b 3.70a 1.81 0.96 2.33b 1.20b 1.28a 2.51a 
conventional 1.79 1.00 2.08 3.02 3.06a 3.23b 2.20 1.19 2.63a 1.75a 0.68b 2.19b 
 -------------p-value------------- -------------p-value------------- -------------p-value------------- -------------p-value------------- 
Source of Error           
crops (C) 0.3073 0.2128 0.4167 0.3865 0.8314 0.0076* 0.5308 0.9733 0.4493 0.9402 0.1280 0.3641 
irrigation (I) 0.9453 0.8464 0.9213 0.3034 0.5984 0.6069 0.1098 0.1200 0.2785 0.0766* 0.1896 0.1176 
tillage (T) 0.7013 0.8858 0.4301 0.4204 0.0001* 0.0171* 0.1139 0.5616 0.0859* 0.0001* 0.0001* 0.0305* 
CxI 0.9135 0.9652 0.8133 0.2899 0.7139 0.1939 0.8307 0.7464 0.6614 0.5773 0.8979 0.4441 
CxT 0.1556 0.1978 0.1767 0.9710 0.5575 0.7909 0.0886 0.3688 0.3022 0.2542 0.0969* 0.1985 
IxT 0.1569 0.1724 0.0635* 0.4128 0.1546 0.5209 0.1307 0.5725 0.0685 0.0857* 0.1732 0.7518 
CxIxT 0.0565* 0.2914 0.1050 0.3779 0.1683 0.6522 0.5704 0.8289 0.9417 0.8292 0.9857 0.1659 
 
* Significant at the 0.10 level of probability. 
**PS: photoperiod sensitive sorghum (1990), FS: forage sorghum (SS506), GS: grain sorghum (NK300), Corn: Pioneer31G65.
 
 
137 
Table 2-7: Results of the type 3 test of treatments and effects from PROC MIXED for Cone index (MPa) for Marvyn loamy sandy at 
0.3 ? 0.4 m soil layer in all sampling periods of 2008 and 2009. Letters denote significant differences (L.S. means S.E.(0.10) within 
treatment and sampling period). 
0.3 - 0.4 m Cone Index Spring 2008 Fall 2008 Spring 2009 Fall 2009 
Non-traffic In row Traffic Non-traffic In row Traffic Non-traffic In row Traffic Non-traffic In row Traffic 
Effects -------------MPa------------- -------------MPa------------- -------------MPa------------- -------------MPa------------- 
Crops             
PS** 1.66 1.22 1.58 2.48 2.00 2.19b 1.32 0.94 1.55 1.72 1.55 1.56 
FS** 1.19 0.92 1.31 2.19 2.01 2.19b 1.37 0.95 1.36 1.12 1.94 1.41 
GS** 1.65 1.20 1.65 3.05 2.16 3.00a 1.80 1.02 1.70 1.22 1.61 1.64 
Corn** 1.48 0.97 1.36 2.38 1.92 2.17b 1.43 0.77 1.50 1.05 1.50 1.34 
Irrigation             
Irrigated 1.49 1.00 1.46 2.44 1.95b 2.44 1.56 0.97a 1.65 1.11b 1.89 1.45 
non-irrigated 1.50 1.15 1.49 2.61 2.09a 2.34 1.40 0.87b 1.41 1.22a 1.41 1.52 
Tillage             
conservation 1.73a 1.21a 1.59a 2.76a 1.53b 2.41 1.63a 0.99 1.59 1.09b 1.59 1.53 
conventional 1.26b 0.95b 1.36b 2.29b 2.51a 2.36 1.32b 0.85 1.46 1.25a 1.71 1.45 
 -------------p-value------------- -------------p-value------------- -------------p-value------------- -------------p-value------------- 
Source of Error           
crop (C) 0.2995 0.3335 0.3110 0.2694 0.8995 0.0007* 0.3368 0.1123 0.5786 0.4297 0.3002 0.2320 
irrigation (I) 0.9628 0.2595 0.7985 0.4148 0.0245* 0.4216 0.2791 0.0926* 0.2129 0.0001* 0.2026 0.4450 
tillage (T) 0.0047* 0.0171* 0.0091* 0.0364* 0.0001* 0.7348 0.0720* 0.2729 0.4276 0.0858* 0.1938 0.4774 
CxI 0.9124 0.9953 0.8216 0.2090 0.4198 0.5447 0.7175 0.9491 0.8835 0.3020 0.5037 0.8586 
CxT 0.4848 0.1309 0.1123 0.9563 0.2091 0.9721 0.2570 0.1310 0.6222 0.7138 0.4555 0.8329 
IxT 0.8202 0.2559 0.7252 0.6039 0.6977 0.5622 0.2884 0.9020 0.4802 0.1209 0.5638 0.8071 
CxIxT 0.1993 0.4434 0.3593 0.8219 0.1149 0.2783 0.4186 0.6310 0.1446 0.1734 0.5513 0.3214 
             
* Significant at the 0.10 level of probability. 
**PS: photoperiod sensitive sorghum (1990), FS: forage sorghum (SS506), GS: grain sorghum (NK300), Corn: Pioneer31G65
 
138 
 
138 
Table 2-8: Results of the type 3 test of treatments and effects from PROC MIXED for Cone index (MPa) for Marvyn loamy sandy at 
0 .4 ? 0.5 m soil layer in all sampling periods of 2008 and 2009. Letters denote significant differences (L.S. means S.E.(0.10) within 
treatment and sampling period). 
0.4 - 0.5 m Cone Index Spring 2008 Fall 2008 Spring 2009 Fall 2009 
Non-traffic In row Traffic Non-traffic In row Traffic Non-traffic In row Traffic Non-traffic In row Traffic 
Effects -------------MPa------------- -------------MPa------------- -------------MPa------------- -------------MPa------------- 
Crops             
PS** 1.20 1.45 1.20 1.85 2.32 1.96 1.00 0.85 1.16 1.07 1.47a 1.40 
FS** 1.06 1.27 1.07 1.82 2.06 1.79 1.02 0.86 1.24 1.10 1.36ab 1.41 
GS** 1.18 1.38 1.15 2.01 2.16 2.16 1.03 0.85 1.27 0.90 1.30bc 1.47 
Corn** 1.17 1.36 1.15 1.99 2.52 1.79 1.96 0.85 1.17 0.97 1.19c 1.40 
Irrigation             
irrigated 1.15 1.37 1.14 1.94 2.12 2.00a 1.04 0.88 1.22 1.02 1.21 1.39 
non-irrigated 1.15 1.35 1.15 1.89 2.41 1.86b 0.97 0.82 1.20 1.00 1.45 1.45 
Tillage             
conservation 1.22a 1.42a 1.19a 2.00a 2.28 1.94 1.08a 0.86 1.23 1.03 1.27 1.41 
conventional 1.08b 1.31b 1.09b 1.83b 2.25 1.92 1.93b 0.85 1.19 0.99 1.38 1.42 
 -------------p-value------------- -------------p-value------------- -------------p-value------------- -------------p-value------------- 
Source of Error           
crops (C) 0.3691 0.3285 0.2923 0.9164 0.6368 0.3910 0.8848 0.9984 0.6445 0.2119 0.0653* 0.9772 
irrigation (I) 0.8729 0.7509 0.8665 0.1062 0.1147 0.0920* 0.2507 0.3346 0.7533 0.7556 0.1597 0.3534 
tillage (T) 0.0126* 0.0604* 0.0330* 0.0619* 0.7141 0.7816 0.0040* 0.7802 0.1408 0.4347 0.2111 0.7817 
CxI 0.3912 0.2262 0.6239 0.1880 0.1308 0.8786 0.7128 0.6428 0.9377 0.8138 0.6080 0.1646 
CxT 0.5610 0.5734 0.1493 0.0328* 0.4997 0.0788* 0.2559 0.1213 0.0145* 0.0660* 0.8459 0.4812 
IxT 0.4839 0.8063 0.4530 0.3263 0.7292 0.5558 0.5682 0.8086 0.0665* 0.3202 0.6734 0.8197 
CxIxT 0.5817 0.5305 0.6954 0.6199 0.0312* 0.8937 0.3385 0.8005 0.7062 0.7649 0.4894 0.7060 
             
* Significant at the 0.10 level of probability. 
**PS: photoperiod sensitive sorghum (1990), FS: forage sorghum (SS506), GS: grain sorghum (NK300), Corn: Pioneer31G65. 
 
139 
 
Table 2-9: LS means of gravimetric water content (GWC) of a Marvyn loamy sand at the 
time of Cone Index measurements. 
 
Gravimetric Water Content 
 Spring 2008 Fall 2008 Spring 2009 Fall 2009 
 -------m3 m-3------- -------m3 m-3------- -------m3 m-3------- -------m3 m-3------- 
Depth     
0 ? 0.15 m 0.17a 0.11a 0.15a 0.14a 
0.15 ? 0.30 m 0.13b 0.10b 0.13b 0.12b 
     
 -----p-value---- -----p-value---- -----p-value---- -----p-value---- 
     
 0.0001* 0.0001* 0.0001* 0.0001* 
     
* Significant at the 0.10 level of probability. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
140 
 
Figure 2-1: Soil organic carbon (Mg ha-1) at non-trafficked middle row affected by crop 
treatments in 2009, and overall SOC before planting in 2008. Horizontal error bars 
indicate crop significant differences - Difference of L.S. Means S.E. (0.10). PS: 
photoperiod sensitive sorghum (1990), FS: forage sorghum (SS506), GS: grain sorghum 
(NK300), Corn: Pioneer31G65. 
 
 
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0.5
1.5 2.5 3.5 4.5 5.5 6.5 7.5 8.5
Dep
th 
(m
)
SOC yield (Mg ha-1)
2008 PS FS GS Corn
 
141 
 
Figure 2-2: Soil organic carbon (Mg ha-1) at non-trafficked middle row affected by 
irrigation treatments in 2009, and overall SOC before planting in 2008. Horizontal error 
bars indicate irrigation significant differences - Difference of L.S. Means S.E. (0.10).  
 
 
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0.5
1.5 2.5 3.5 4.5 5.5 6.5 7.5 8.5
De
pth 
(m
)
SOC yield (Mg ha-1)
2008 Irrigaton Non-irrigated
 
142 
 
Figure 2-3: Soil organic carbon (Mg ha-1) at non-trafficked middle row affected by 
tillage treatments in 2009, and overall SOC before planting in 2008. Horizontal error bars 
indicate tillage significant differences - Difference of L.S. Means S.E. (0.10).  
 
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0.5
1.5 2.5 3.5 4.5 5.5 6.5 7.5 8.5
De
pth 
(m
)
SOC yield (Mg ha-1)
2008 Conservation Conventional
 
143 
 
Figure 2-4: Total nitrogen (Mg ha-1)  at non-trafficked middle row affected by crop 
treatments in 2009 and overall TN before planting in 2008. Horizontal error bars indicate 
crop significant differences - Difference of L.S. Means S.E. (0.10). PS: photoperiod 
sensitive sorghum (1990), FS: forage sorghum (SS506), GS: grain sorghum (NK300), 
Corn: Pioneer31G65. 
 
 
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0.5
0 0.1 0.2 0.3 0.4 0.5 0.6
De
pth 
(m
)
Total nitrogen (Mg ha-1)
2008 PS FS GS Corn
 
144 
 
Figure 2-5: Total nitrogen (Mg ha-1) at non-trafficked middle row affected by irrigation 
treatments in 2009 and overall TN before planting in 2008. Horizontal error bars indicate 
irrigation significant differences - Difference of L.S. Means S.E. (0.10).  
 
 
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0.5
0 0.1 0.2 0.3 0.4 0.5 0.6
De
pth 
(m
)
Total Nitrogen (Mg ha-1)
2008 Irrigaton Non-irrigated
 
145 
 
Figure 2-6: Total nitrogen (Mg ha-1)  at non-trafficked middle row affected by tillage 
treatments in 2009, and overall TN before planting in 2008. Horizontal error bars indicate 
tillage significant differences - Difference of L.S. Means S.E. (0.10).  
 
 
 
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0.5
0 0.1 0.2 0.3 0.4 0.5 0.6
De
pth 
(m
)
Total Nitrogen (Mg ha-1)
2008 Conservation Conventional
 
146 
 
Figure 2-7: Bulk density (Mg m-3) at non-trafficked middle row affected by crop 
treatments in 2009 and overall Bulk density before planting in 2008. Horizontal error bars 
indicate crop significant differences - Difference of L.S. Means S.E. (0.10). PS: 
photoperiod sensitive sorghum (1990), FS: forage sorghum (SS506), GS: grain sorghum 
(NK300), Corn: Pioneer31G65. 
 
 
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0.5
1 1.2 1.4 1.6 1.8 2
De
pth 
(m
)
Bulk density (Mg m-3)
2008 PS FS GS Corn
 
147 
 
Figure 2-8: Bulk density (Mg m-3) at non-trafficked middle row affected by irrigation 
treatments in 2009 and overall Bulk density before planting in 2008. Horizontal error bars 
indicate irrigation significant differences - Difference of L.S. Means S.E. (0.10).  
 
 
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0.5
1 1.2 1.4 1.6 1.8 2
De
pth 
(m
)
Bulk density (Mg m-3)
2008 Irrigaton Non-irrigated
 
148 
 
Figure 2-9: Bulk density (Mg m-3) at non-trafficked middle row affected by tillage 
treatments in 2009, and overall Bulk density before planting in 2008. Horizontal error 
bars indicate tillage significant differences - Difference of L.S. Means S.E. (0.10).  
 
 
 
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0.5
1 1.2 1.4 1.6 1.8 2
De
pth 
(m
)
Bulk density (Mg m-3)
2008 Conservation Conventional
 
149 
 
Figure 2-10:.Contour graphs of penetration isolines using Cone Index ? CI (MPa) values 
for Marvyn loamy sand at tillage treatments in all sampling periods of 2008. Spring CI 
values were collected 1 week after planting. Fall CI values were collected 1 week after 
harvesting. 
 
 
 
 
 
 
 
 
 
150 
 
Figure 2-11: Contour graphs of penetration isolines using Cone Index ? CI (MPa) values 
for Marvyn loamy sand at tillage treatments in all sampling periods of 2009. Spring CI 
values were collected 1 week after planting. Fall CI values were collected 1 week after 
harvesting. 
 
 
 
 
 
 
 
 
 
 
151 
Figure 2-12: In row soil water content at 0.10 m deep affected by crop treatments for Marvyn loamy sand in 2008. Vertical error bars 
denote significant differences ? Difference of L.S. means S.E.(0.10). WAP: weeks after planting, PS: photoperiod sensitive sorghum 
(1990), FS: forage sorghum (SS506), GS: grain sorghum (NK300), Corn: Pioneer31G65. 
 
 
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
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Soil
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ten
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m-
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Pr
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 (m
m)
Days after planting (DAP)
Crops, season: 2008, depth: 0.10 m  
Rainfall Irrigation PS FS GS Corn
(5 WAP) (10 WAP) (15 WAP)
 
 
152 
Figure 2-13: In row soil water content at 0.20 m deep affected by crop treatments for Marvyn loamy sand in 2008. Vertical error bars 
denote significant differences ? Difference of L.S. means S.E.(0.10). WAP: weeks after planting, PS: photoperiod sensitive sorghum 
(1990), FS: forage sorghum (SS506), GS: grain sorghum (NK300), Corn: Pioneer31G65. 
 
 
0
0.05
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0.3
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m-
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Pr
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 (m
m)
Days after planting (DAP)
Crops, season: 2008, depth: 0.20 m  
Rainfall Irrigation PS FS GS Corn
`
(5 WAP) (10 WAP) (15 WAP)
 
 
153 
Figure 2-14: In row soil water content at 0.40 m deep affected by crop treatments for Marvyn loamy sand in 2008. Vertical error bars 
denote significant differences ? Difference of L.S. means S.E.(0.10). WAP: weeks after planting, PS: photoperiod sensitive sorghum 
(1990), FS: forage sorghum (SS506), GS: grain sorghum (NK300), Corn: Pioneer31G65. 
 
 
 
 
 
 
 
 
 
 
 
 
0
0.05
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35 45 55 65 75 85 95 105 115
Soil
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t (
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m-
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Pr
ecip
ita
tion
 (m
m)
Days after planting (DAP)
Crops, season: 2008, depth: 0.40 m  
Rainfall Irrigation PS FS GS Corn
`
(5 WAP) (10 WAP) (15 WAP)
 
 
154 
Figure 2-15: In row soil water content at 0.60 m deep affected by crop treatments for Marvyn loamy sand in 2008. Vertical error bars 
denote significant differences ? Difference of L.S. means S.E.(0.10).  WAP: weeks after planting, PS: photoperiod sensitive sorghum 
(1990), FS: forage sorghum (SS506), GS: grain sorghum (NK300), Corn: Pioneer31G65. 
 
 
0
0.05
0.1
0.15
0.2
0.25
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35 45 55 65 75 85 95 105 115
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m3
m-
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Pr
ecip
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 (m
m)
Days after planting (DAP)
Crops, season: 2008, depth: 0.60 m  
Rainfall Irrigation PS FS GS Corn
`
(5 WAP) (10 WAP) (15 WAP)
 
 
155 
Figure 2-16: In row soil water content at 0.10 m deep affected by irrigation treatments for Marvym loamy sand in 2008. Vertical error 
bars denote significant differences ? Difference of L.S. means S.E.(0.10). WAP: weeks after planting. 
 
 
  
 
-0.1
-0.05
0
0.05
0.1
0.15
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m-
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Pr
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 (m
m)
Days after planting (DAP)
Irrigation, Season: 2008, depth: 0.10 m  
Rainfall Irrigation Irrigated Non-irrigated
`
(5 WAP) (10 WAP) (15 WAP)
 
 
156 
Figure 2-17: In row soil water content at 0.20 m deep affected by irrigation treatments for Marvyn loamy sand in 2008. Vertical error 
bars denote significant differences ? Difference of L.S. means S.E.(0.10). WAP:  Weeks after planting. 
 
 
0
0.05
0.1
0.15
0.2
0.25
0.3
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35 45 55 65 75 85 95 105 115
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m-
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Pr
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 (m
m)
Days after planting (DAP)
Irrigation, season: 2008, depth: 0.20 m  
Rainfall Irrigation Irrigatied Non-irrigated
`
(5 WAP) (10 WAP) (15 WAP)
 
 
157 
Figure 2-18: In row soil water content at 0.40 m deep affected by irrigation treatments for Marvyn loamy sand in 2008. Vertical error 
bars denote significant differences ? Difference of L.S. means S.E.(0.10). WAP:  Weeks after planting. 
 
 
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0
10
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30
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50
60
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80
90
100
35 45 55 65 75 85 95 105 115
Soil
 w
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ten
t (
m3
m-
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Pr
ecip
itat
ion
 (m
m)
Days after planting (DAP)
Irrigation, season: 2008, depth: 0.40 m  
Rainfall Irrigation Irrigated Non-irrigated
`
(5 WAP) (10 WAP) (15 WAP)
 
 
158 
Figure 2-19: In row soil water content at 0.60 m deep affected by irrigation treatments for Marvyn loamy sand in 2008. Vertical error 
bars denote significant differences ? Difference of L.S. means S.E.(0.10). WAP:  Weeks after planting. 
  
 
0
0.1
0.2
0.3
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0.5
0
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35 45 55 65 75 85 95 105 115
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m3
m-
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Pr
ecip
itat
ion
 (m
m)
Days after planting (DAP)
Irrigation, season: 2008, depth: 0.60 m  
Rainfall Irrigation Irrigated Non-irrigated
`
(5 WAP) (10 WAP) (15 WAP)
 
 
159 
Figure 2-20: In row soil water content at 0.10 m deep affected by tillage treatments for Marvyn loamy sand in 2008. Vertical error 
bars denote significant differences ? Difference of L.S. means S.E.(0.10). WAP:  Weeks after planting 
 
 
 
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0
10
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50
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35 45 55 65 75 85 95 105 115
Soil
 w
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ten
t (
m3
m-
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Pr
ecip
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ion
 (m
m)
Days after planting (DAP)
Tillage, season: 2008, depth: 0.10 m  
Rainfall Irrigation Conservation Conventional
`
(5 WAP) (10 WAP) (15 WAP)
 
 
160 
Figure 2-21: In row soil water content at 0.20 m deep affected by tillage treatments for Marvyn loamy sand in 2008. Vertical error 
bars denote significant differences ? Difference of L.S. means S.E.(0.10). WAP:  Weeks after planting. 
 
 
  
 
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0
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35 45 55 65 75 85 95 105 115
Soi
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ate
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onte
nt (
m3
m-
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Pr
ecip
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ion
 (m
m)
Days after planting (DAP)
Tillage, season: 2008, depth: 0.20 m  
Rainfall Irrigation Conservation Conventional
`
(5 WAP) (10 WAP) (15 WAP)
 
 
161 
Figure 2-22: In row soil water content at 0.40 m deep affected by tillage treatments for Marvyn loamy sand in 2008. Vertical error 
bars denote significant differences ? Difference of L.S. means S.E.(0.10). WAP:  Weeks after planting. 
 
 
 
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
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35 45 55 65 75 85 95 105 115
Soil
 w
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ten
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m-
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Pr
ecip
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ion
 (m
m)
Days after planting (DAP)
Tillage, season: 2008, depth: 0.40 m  
Rainfall Irrigation Conservation Conventional
`
(5 WAP) (10 WAP) (15 WAP)
 
 
162 
Figure 2-23: In row soil water content at 0.60 m deep affected by tillage treatments for Marvym loamy sand in 2008. Vertical error 
bars denote significant differences ? Difference of L.S. means S.E.(0.10). WAP:  Weeks after planting. 
 
 
 
  
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0.5
0
10
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90
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35 45 55 65 75 85 95 105 115
Soil 
water 
content 
(m
3 m
-3 )
Precipitation 
(m
m)
Days after planting (DAP)
Tillage, season: 2008, depth: 0.60 m  
Rainfall Irrigation Conservation Conventional
`
(5 WAP) (10 WAP) (15 WAP)
 
 
163 
Figure 2-24: In row soil water content at 0.10 m deep affected by crop treatments for Marvyn loamy sand in 2009. Vertical error bars 
denote significant differences ? Difference of L.S. means S.E.(0.10). WAP:  Weeks after planting, PS: photoperiod sensitive sorghum 
(1990), FS: forage sorghum (SS506), GS: grain sorghum (NK300), Corn: Pioneer31G65. 
 
 
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
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30 40 50 60 70 80 90 100
Soil
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ten
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m3
m-
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Pr
ecip
itat
ion
 (m
m)
Days after planting (DAP)
Crops, season: 2009, depth: 0.10 m  
Rainfall Irrigation PS FS GS Corn
`
(5 WAP) (10 WAP) (15 WAP)
 
 
164 
Figure 2-25: In row soil water content at 0.20 m deep affected by crop treatments for Marvyn loamy sand in 2009. Vertical error bars 
denote significant differences ? Difference of L.S. means S.E.(0.10). WAP:  Weeks after planting, PS: photoperiod sensitive sorghum 
(1990), FS: forage sorghum (SS506), GS: grain sorghum (NK300), Corn: Pioneer31G65. 
 
 
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0
10
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100
30 40 50 60 70 80 90 100
Soil
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ten
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m3
m-
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Pr
ecip
itat
ion
 (m
m)
Days after planting (DAP)
Crops, season: 2009, depth: 0.20 m  
Rainfall Irrigation PS FS GS Corn
`
(5 WAP) (10 WAP) (15 WAP)
 
 
165 
Figure 2-26: In row soil water content at 0.40 m deep affected by crop treatments for Marvyn loamy sand in 2009. Vertical error bars 
denote significant differences ? Difference of L.S. means S.E.(0.10). WAP:  Weeks after planting, PS: photoperiod sensitive sorghum 
(1990), FS: forage sorghum (SS506), GS: grain sorghum (NK300), Corn: Pioneer31G65. 
 
 
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0.5
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30 40 50 60 70 80 90 100
Soil
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ten
t (
m3
m-
3 )
Pr
ecip
itat
ion
 (m
m)
Days after planting (DAP)
Crops, season: 2009, depth: 0.40 m  
Rainfall Irrigation PS FS GS Corn
`
(5 WAP) (10 WAP) (15 WAP)
 
 
166 
Figure 2-27: In row soil water content at 0.60 m deep affected by crop treatments for Marvyn loamy sand in 2009. Vertical error bars 
denote significant differences ? Difference of L.S. means S.E.(0.10). WAP:  Weeks after planting, PS: photoperiod sensitive sorghum 
(1990), FS: forage sorghum (SS506), GS: grain sorghum (NK300), Corn: Pioneer31G65. 
 
 
 
0
0.1
0.2
0.3
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30 40 50 60 70 80 90 100
Soi
l w
ater
 con
ten
t (m
3 m
-3 )
Pr
ecip
itat
ion
 (m
m)
Days after planting (DAP)
Crops, season: 2009, depth: 0.60 m  
Rainfall Irrigation PS FS GS Corn
`
(5 WAP) (10 WAP) (15 WAP)
 
 
167 
Figure 2-28: In row soil water content at 0.10 m deep affected by irrigation treatments for Marvyn loamy sand in 2009. Vertical error 
bars denote significant differences ? Difference of L.S. means S.E.(0.10). WAP:  Weeks after planting. 
 
 
0
0.05
0.1
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30 40 50 60 70 80 90 100
Soil
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ten
t (
m3
m-
3 )
Pr
ecip
itat
ion
 (m
m)
Days after planting (DAP)
Irrigation, season: 2009, depth: 0.10 m  
Rainfall Irrigation Irrigated Non-irrigated
`
(5 WAP) (10 WAP) (15 WAP)
 
 
168 
Figure2-29: In row soil water content at 0.20 m deep affected by irrigation treatments for Marvyn loamy sand in 2009. Vertical error 
bars denote significant differences ? Difference of L.S. means S.E.(0.10). WAP:  Weeks after planting. 
 
 
0
0.05
0.1
0.15
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30 40 50 60 70 80 90 100
Soil
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ten
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m3
m-
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Pr
ecip
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ion
 (m
m)
Days after planting (DAP)
Irrigation, season: 2009, depth: 0.20 m  
Rainfall Irrigation Irrigated Non-irrigated
`
(5 WAP) (10 WAP) (15 WAP)
 
 
169 
Figure 2-30: In row soil water content at 0.40 m deep affected by irrigation treatments for Marvyn loamy sand in 2009. Vertical error 
bars denote significant differences ? Difference of L.S. means S.E.(0.10). WAP:  Weeks after planting. 
 
 
 
0
0.05
0.1
0.15
0.2
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30 40 50 60 70 80 90 100
Soil
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ten
t (
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m-
3 )
Pr
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ion
 (m
m)
Days after planting (DAP)
Irrigation, season: 2009, depth: 0.40 m  
Rainfall Irrigation Irrigated Non-irrigated
`
(5 WAP) (10 WAP) (15 WAP)
 
 
170 
Figure 2-31: In row soil water content at 0.60 m deep affected by irrigation treatments for Marvyn loamy sand in 2009. Vertical error 
bars denote significant differences ? Difference of L.S. means S.E.(0.10). WAP:  Weeks after planting. 
 
  
 
0
0.05
0.1
0.15
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0.25
0.3
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30 40 50 60 70 80 90 100
Soil
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ten
t (
m3
m-
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Pr
ecip
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ion
 (m
m)
Days after planting (DAP)
Irrigation, season: 2009, depth: 0.60 m  
Rainfall Irrigation Irrigated Non-irrigated
`
(5 WAP) (10 WAP) (15 WAP)
 
 
171 
Figure 2-32: In row soil water content at 0.10 m deep affected by tillage treatments for Marvyn loamy sand in 2009. Vertical error 
bars denote significant differences ? Difference of L.S. means S.E.(0.10). WAP:  Weeks after planting. 
 
 
 
0
0.05
0.1
0.15
0.2
0.25
0.3
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0
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120
30 40 50 60 70 80 90 100
Soil
 w
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ten
t (
m3
m-
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Pr
ecip
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ion
 (m
m)
Days after planting (DAP)
Tillage, season: 2009, depth: 0.10 m  
Rainfall Irrigation Conservation Conventional
`
(5 WAP) (10 WAP) (15 WAP)
 
 
172 
Figure 2-33: In row soil water content at 0.20 m deep affected by tillage treatments for Marvyn loamy sand in 2009. Vertical error 
bars denote significant differences ? Difference of L.S. means S.E.(0.10). WAP:  Weeks after planting. 
 
 
 
0
0.05
0.1
0.15
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0
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30 40 50 60 70 80 90 100
Soil
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m-
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Pr
ecip
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ion
 (m
m)
Days after planting (DAP)
Tillage, season: 2009, depth: 0.20 m  
Rainfall Irrigation Conservation Conventional
`
(5 WAP) (10 WAP) (15 WAP)
 
 
173 
Figure 2-34: In row soil water content at 0.40 m deep affected by tillage treatments for Marvyn loamy sand in 2009. Vertical error 
bars denote significant differences ? Difference of L.S. means S.E.(0.10). WAP:  Weeks after planting. 
 
 
 
0
0.05
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0.15
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 w
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m-
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Pr
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 (m
m)
Days after planting (DAP)
Tillage, season: 2009, depth: 0.40 m  
Rainfall Irrigation Conservation Conventional
`
(5 WAP) (10 WAP) (15 WAP)
 
 
174 
Figure 2-35: In row soil water content at 0.40 m deep affected by tillage treatments for Marvyn loamy sand in 2009. Vertical error 
bars denote significant differences ? Difference of L.S. means S.E.(0.10). WAP:  Weeks after planting. 
 
 
 
0
0.05
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 w
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m-
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Pr
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 (m
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Days after planting (DAP)
Tillage, season: 2009, depth: 0.60 m  
Rainfall Irrigation Conservation Conventional
`
(5 WAP) (10 WAP) (15 WAP)
 
175 
 
III. RAPIDLY DRYING SOGHUM BIOMASS FOR POTENTIAL BIOFUEL 
PRODUCTION 
 
ABSTRACT 
The Southern U.S. has an ideal climate that may aid in growing large amounts of biomass 
potentially suitable for biofuel; however, short-term droughts during the growing season 
may reduce yields.  Sorghum (Sorghum bicolor L.) may have great potential as an energy 
crop, because it is capable of high biomass yields and is drought tolerant. Sorghum could 
be integrated into a conservation system as part of a crop rotation. However, sorghum 
biomass has relatively high moisture content and should be conditioned and dried before 
transported to reduce costs.  Sorghum-sudan hybrid was harvested with two different 
headers on a self-propelled windrower:  a Massey Ferguson 9145 (sickle) and a Massey 
Ferguson 9185 (disc).  The disc header was comprised of two pairs (rear / front) of metal 
conditioner rollers which compressed the biomass, thus improving the drying process. 
The roller pairs were used with three different pressures (0, 3500 and 7000 kPa), and with 
different gaps (0 and 0.02 m). Sorghum biomass samples were collected after harvest and 
moisture content (%) evaluated daily until they remained constant. Results revealed that 
the higher pressures and smaller gaps resulted in faster drying of biomass. Thus, the best 
settings for the disc header were ?7000 kPa ? 0 m? or ?7000 kPa ? 0.02 m? which 
showed, respectively, moisture content levels of 13.6 % and 16.8 % after 14 days. 
However, when the disc header was set to ?0 kPa - 0.02 m?, the moisture content was 
 
176 
 
significantly higher (43.2%).  These results indicate sorghum was adequately dried for 
bailing in Southeastern U.S. condition, when using MF 9185 set with both ?0 m gap front 
and rear, 7000 kPa? and ?0.02 gap front / 0 m gap rear, 7000 kPa?. 
 Keywords: moisture, conditioning, bailing, windrowers, settings. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
177 
 
1. INTRODUCTION 
 
Growing domestic biomass for bioenergy may help to reduce the amount of oil 
imported by the United States.  The Southeastern U.S. has an ideal climate that may aid 
in growing large amounts of biomass; however, short-term droughts during the growing 
season over the last several years have dramatically reduced production. For these 
reasons, sorghum may be a reasonable alternative as an energy crop in this region, 
because it is considered drought resistant (Habyarimana et al., 2004). Sorghum can 
extract water from deep soil layers with most coming from depths of 0.45 - 1.35 m (Farre 
and Faci, 2006).  
 Additionally, sorghum has been considered a potential bioenergy crop, mostly 
from a cellulosic standpoint, providing a total maximum dry matter yield of 30.15 tons 
ha-1 in a short time (120 days) and with a maximum mean daily growth rate of 22 g day-1 
(Loomis and Williams, 1963). 
 Therefore, sorghum could be integrated into a conservation system as part of a 
crop rotation with typical cash crops where part of its biomass would be used as a soil 
cover and any additional amount of biomass would be harvested for potential biofuel 
production. While much emphasis has been placed on perennials for biofuel production, 
annual crops, such as sorghum would provide a major source of biomass for cellulosic 
ethanol production. These annual crops for bioenergy production have largely been 
ignored in the Southeastern U.S. 
 However, sorghum biomass has relatively high moisture content and should be 
dried before transported to reduce costs. Cundiff and Worley (1992) found that freshly 
 
178 
 
harvested sorghum stalks had 48 to 76% of fresh weight and contained 42?75 % of 
whole-plant nonstructural carbohydrate. Thus, sorghum biomass needs to be dried to a 
moisture content of 15?20 % for storage. Moisture content higher than 20 % results in 
molds and bacteria growth that decreases biomass quantity and quality. On the other 
hand, moisture content lower than 15 % results in leaf loss decreasing biomass quantity 
(Wilcke et al., 1998). 
 Therefore, the objective of this study was: 1) Compare the drying of sorghum 
biomass under two different headers on a self-propelled windrower, 2) determine the best 
setting of the disc header including setting the pressures and gaps, 3) evaluate if adequate 
drying could be obtained for baling sorghum within a relatively short time period in 
southeastern U S. conditions. 
 
2. MATERIAL AND METHODS 
 
 In order to compare the drying of sorghum biomass, an experiment was conducted 
at the E.V. Smith Research Station, Shorter, AL (85?:53?50? W, 32?:25?22? N) in April, 
2008. The soil at the experimental field was classified as Lynchburg loamy sand (fine-
loamy, siliceous, semiactive, thermic Aeric Paleaquults). The total field was previously 
used for with corn (Zea Mays L.) silage before planting sorghum. 
 
2.1. Crop 
 The sorghum evaluated in this experiment was the Sweet Graze BMR (Brown 
Midrib Sorghum Sudangrass). It is described as tolerant to drought (500 mm rainfall 
 
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requirement during growing season), high sugar content, high forage quality, low lignin 
content, and with little cold tolerance (Pogue Agri Partners Inc., 2010). 
 Conventional tillage was applied to the entire experimental area. Seeding rate of 
28 kg ha-1 and N rate of 65 kg ha-1 was applied during planting. Other applications, such 
as nutrients and herbicides were obtained by following the Auburn University Extension 
recommendations. Only natural rainfall was used.   
 
 2.2. Self-propelled Windrowers   
 Two different headers on a self-propelled windrower were compared:  a Massey 
Ferguson 9145 and a Massey Ferguson 9185 (AGCO Company, Duluth, GA), which are 
a sickle and a disc header, respectively. Figure 3-1 illustrates both windrowers.  
 The disc header was comprised of two pairs (rear / front) of metal conditioner 
rollers which compressed the biomass, thus improving the drying process. The roller 
pairs were used with three different pressures (0, 3500 and 7000 kPa), and with different 
gaps (0 and 0.02 m) combined in 7 different configurations. However, the sickle header 
was also comprised of 2 pairs (rear/front) of conditioners, the front pair being metal and 
the rear pair being rubber. Table 3-1 showed all settings applied to both windrowers.  
 
2.3. Field description 
 The total number of experimental plots was 32 which were composed of 8 
different treatments and 4 replications. The treatments were: the 7 different gap/pressure 
settings of Massey Ferguson 9185 (disc), and the standard setting of Massey Ferguson 
9145 (sickle) which were represented in Table 3-1.  
 
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 All plots and borders were 5 m wide and 30 m long in which 4 rows were spaced 
apart by 0.9 m. Each block was separated by borders. 
 
2.4. Biomass samples 
  The total dry aboveground matter produce by the evaluated sorghum was 
approximately 6.3 Mg ha-1 and was established by collecting 0.25 m2 samples from the 
all plots before harvesting. Sorghum was harvested on October 16, 2008. Biomass 
samples were collected after harvest and moisture content (%) was evaluated until it 
remained constant. Samples were collected daily in early afternoon, except for rainy days 
and subsequent wet days. However, biomass samples were collected 8 times from 
October, 16th to October 30th, where the collection days were: October 16th, 20th, 21th, 
22th, 23th, 28th, 29th, and 30th.  All plots were disturbed using a Frontier TD10E hay 
Tedder (Deere & Company, Moline, IL) on October 28th in order to achieve faster 
biomass drying. 
 Three handfuls of biomass subsamples were taken randomly from each plot, and 
placed in bags where the wet biomass weight was recorded. Biomass samples were dried 
at 55? C until constant weight was achieved.  Wet-basis moisture content -Mwb(%) was 
calculated using the following formula: 
 
100( % ) 2 2 xmm mM dmOH OHwb  
Where:  
Mwb (%)= wet-basis moisture content, mH2O = mass of moisture in kg, and  mdm = mass of 
dry matter in kg. 
 
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2.5. Statistical Analysis 
 Statistical analyses were performed in a randomized complete block design 
(RCB) with eight different treatments as shown in Table 3-1. The predetermined 
significance level was P ? 0.10 and Fisher?s least-significant-difference test (LSD) was 
performed for means comparisons. The data were analyzed with GLM procedure using 
software SAS 9.1 (SAS Inst. Inc., Cary, NC) 
  
 3. RESULT AND DISCUSSIONS 
 
3.1. Effect of different MF 9185?s roller pressures on sorghum moisture content. 
 Results showed that higher pressures applied on rollers tended to speed the 
biomass drying process dry sorghum biomass faster than lower pressures (Figure 3-2). 
For all sampled days, rollers set to 7000 kPa were significantly more effective in drying 
biomass than rollers set to 0 kPa. This difference in pressure treatments was highest on 
October 30 (29.8 % vs. 15. 2 %, P = 0.0025).  
 Different results were found when comparing 3500 and 7000 kPa pressures. No 
significant differences were found between those applied pressures on October 22, 23, 28 
and 29. Controversially, October 21 and 30 showed significant differences between 
different applied pressures. And, the last sampled day (October 30) had the highest 
difference between 3500 and 7000 kPa (24.2 % vs 15.2 %, P = 0.0460). 
 
 
 
 
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3.2. Effect of different MF 9185?s roller gaps on sorghum moisture content. 
 Sorghum biomass tended to dry faster when rollers were contacting each other 
(Fig. 3 -3). Comparing two different gap sets: ?O m gap front/rear? vs. ?0.02 m gap front 
/ 0 m gap rear?, all sampled days showed numerically low moisture content values for ?0 
m gap front and rear? treatments. But, they were significant different on October 23, 28 
and 30. Additionally, the last sampled day (October 30) showed averages of 19.8 % and 
26.4 %, respectively for ?0 m gap front/rear? and ?0.02 m gap front / 0 m gap rear? 
treatments (P = 0.0712).  
 
3.3. Interaction of different MF 9185?s roller gaps and pressures on sorghum 
moisture content. 
3.3.1. Day: 10/16/2008 
 Different moisture contents among treatments were observed 5 hours after harvest 
on October 16. Treatment 8 showed minimum moisture content (63.5 % ?0.02) followed 
by treatments 3 (63.8 % ?0.03), 2 (64.8 % ? 0.02), 5 (66.2 % ?0.03) and 6 (66.1 % ? 
0.04), which showed no significant differences among each other. Treatment 1 (67 % ? 
0.02) was considered not significantly different from treatments 2, 3, 5, and 6. Treatments 
4 (69.8 % ?0.16) and 7 (70.7 % ?0.02) showed highest moisture content (Figure 3-4). 
The average temperature during October 16th was 20.5 ?C (AWIS Weather Services, 
Inc., 2010).  
 MF 9185 showed similar biomass moisture content to MF 9145 when set at 3500 
or 7000 kPa; but MF 9185 had higher moisture content when set to 0 kPa. Therefore, 
 
183 
 
higher pressures exposed more plant tissues to the atmosphere than low pressures which 
resulted in faster biomass drying over a short period of time.     
 
3.3.2. Day: 10/23/2008 
 Seven days after harvest, treatment 3 (27.7 % ?0.053) and 2 (28.5 % ?0.062) 
showed reduced values of moisture content followed by treatments 8 (30.9 % ?0.065), 6 
(31.6 % ?0.068) and 1 (33.4 % ?0.045), which showed no significant differences among 
each other. Treatment 5 (34.4 % ?0.075) was considered not significantly different from 
1, 6 and 8. Thus, treatments 4 (43.8 % ?0.07) and 7 (56.5 % ?0.03) showed the highest 
moisture content, but they were not statistically different from each other (Fig. 3-5). All 
previous sampling days including October 20, 21 and 22 showed the same trend as 
October 23. Thus, the average temperature was 17.0 ?C during those 7 days, and 8 mm of 
precipitation was recorded on October 18th (AWIS Weather Services, Inc., 2010). 
  However, MF 9185 showed similar biomass moisture content to MF 9145 when 
rollers set to any pressure with 0 m gap, and when rollers submitted on 7000 kPa with 
0.02 m gap in front roller. Additionally, moisture content was higher in MF 9185 plots 
than MF 9145 ones when rollers set with 0 and 3500 kPa or had at least a 0.02 m gap.  
 On October 28, the biomass moisture content had an average increment of 0.07% 
in all experimental plots due to 57 mm of precipitation on October 24 (AWIS Weather 
Services, Inc., 2010). Consequently, the sorghum biomass in all experimental plots was 
fluffed with the tedder to improve biomass drying. 
 
 
 
184 
 
3.3.3. Day: 10/30/2008 
 Fourteen days after harvest, biomass from treatment 3 (13.6 % ?0.037) and 6 
(16.8 % ?0.054) showed minimum moisture content followed by treatments 2 (21.8 % 
?0.044), 1 (24.0 % ?0.058), 8 (24.1 % ?0.039) and 5 (26.6 % ?0.042), which were not 
significantly different among each other. Treatment 4 (35.6 % ?0.048) was considered 
not significantly different from 5. Thus, treatments 7 (43.2 % ?0.021) showed the highest 
moisture content. (Figure 3-6).  The sampled previous day (October 29) showed the same 
trend as October 30. Thus, the average temperature from October 24 to 30 was 11.7 ?C 
(AWIS Weather Services, Inc., 2010). 
 However, biomass harvested from plots where the MF 9185 was used for 
harvesting showed 13.6 % and 16.8 % of moisture content for treatments 3 and 6, 
respectively. It has been recommended that moisture content of biomass samples fall 
between 15.0 ? 20.0 % of moisture content (Wilcke et al., 1998). Therefore, MF 9185 
was able to dry sorghum biomass when rollers were set on 7000 kPa with ?0 m gap 
front/rear? and ?0.02 m gap front / 0 m gap rear?. Additionally, MF 9145 exceeded the 
recommended values by still containing 24.1 % moisture after 14 days.   
  
4. CONCLUSION 
 
 1. MF 9185 windrower dried sorghum biomass faster when higher pressures were 
applied on conditioner rollers. Therefore, pressures of 7000 kPa caused reduced moisture 
content values as compared to 0 and 3500 kPa after 15 days of harvest. 
 
185 
 
 2. No gap between the rollers on the MF 9185 conditioner dried sorghum biomass 
faster than 0.02 m gap.  
 3. MF 9185 windrower was considered more efficient in drying sorghum biomass 
than MF 9145 when conditioner rollers were set with ?0 gap front/rear, 7000 kPa?.  The 
settings ?0 m gap front and rear, 7000 kPa? and ?0.02 gap front / 0 m gap rear, 7000 kPa? 
reduced moisture content to values lower than 20%, which was considered the maximum 
moisture content value for storing biomass.  
 Therefore, high biomass crops such as sorghum were successfully dried for baling 
in southeastern U.S. condition, when using MF 9185 set with both ?0 m gap front and 
rear, 7000 kPa? and ?0.02 gap front / 0 m gap rear, 7000 kPa?.  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
186 
 
5. REFERENCES 
 
AWIS Weather Services Inc., 2010. Weather information for EV Smith AL: 2008 /2009, 
pp. Retrieved May 1 2010, from http://www.awis.com/cgi-bin/ncgi/ 
awondasta.uncgi. 
Cundiff, J.S., Worley, J.W., 1992. Chopping parameters for separation of sweet sorghum 
pith and rind-leaf. Bioresource Technology 39, 263-269. 
Farr?, I., Faci, J.M., 2006. Comparative response of maize (Zea mays L.) and sorghum 
(Sorghum bicolor L. Moench) to deficit irrigation in a Mediterranean 
environment. Agricultural Water Management 83, 135-143. 
Habyarimana, E., Bonardi, P., Laureti, D., Di Bari, V., Cosentino, S., Lorenzoni, C., 
2004a. Multilocational evaluation of biomass sorghum hybrids under two stand 
densities and variable water supply in Italy. Industrial Crops and Products 20, 3-9. 
Loomis, R.S., Williams, W.A., 1963. Maximum crop productivity: an estimate. Crop Sci 
3, 67-72. 
Pogue Agri Partners Inc., 2010. Brown midrib sorghum sudangrass: product description, 
pp. Retrieved May 1 2010, from: http://www.pogueagri.com/ 
Sweet_Graze_Bmr.aspx  
Wilcke, B., Cuomo, G., Fox, C., 1998. Preserving the value of dry stored hay, Univ. 
Minn. Manuscript FO-7404-GO. 
 
 
 
 
187 
 
Table 3-1: Settings applied in both self-propelled windrowers. Massey Ferguson 9185 
(disc header) and Massey Ferguson 9145 (sickle header). 
 
 
Self ?propelled 
  Windrowers 
Treatment 
Number      
Pressure 
(KPa) 
Gap (m) 
front          rear 
Massey Ferguson 9185 ? disc header    
 1 0   0                0 
 2 3500   0                0 
 3 7000   0                0 
 4 0 0.02             0 
 5 3500 0.02             0 
 6 7000 0.02             0 
 7 0 0.02           0.02 
Massey Ferguson 9145 ? sickle header    
 8 standard standard 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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Table 3-2: Daily average temperature and precipitation during drying period  
(AWIS Weather Services, Inc., 2010). 
 
Dates Average Temperature 
(?C) 
Precipitation 
(mm) 
10/16/2008 20.5 0 
10/17/2008 22.7 0 
10/18/2008 17.2 8 
10/19/2008 14.4 0 
10/20/2008 12.7 0 
10/21/2008 13.3 0 
10/22/2008 16.6 0 
10/23/2008 18.3 0 
10/24/2008 15.5 57 
10/25/2008 13.8 0 
10/26/2008 13.8 0 
10/27/2008 16.1 0 
 10/28/2008* 8.3 0 
10/29/2008 6.1 0 
10/30/2008 8.3 0 
10/31/2008 12.2 0 
 
 
* Plots disturbed using a Frontier TD10E hay Tedder. 
 
 
 
 
 
 
 
 
 
 
189 
 
Figure 3-1: Massey Ferguson 9185 ? disc header (A); and Massey Ferguson 9145 ? 
sickle header (B). 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
A 
B 
 
190 
 
Figure 3-2: Sorghum moisture content (wet basis, %) for different disc header pressures 
for all sampled days. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
191 
 
Figure 3-3: Sorghum moisture content (wet basis, %) for different disc header gaps in all 
sampled days. 
 
 
 
 
 
 
 
 
 
 
 
 
 
192 
 
Figure 3-4: Sorghum moisture content (wet basis, %) for all treatments on October 16, 
2008. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
193 
 
Figure 3-5: Sorghum moisture content (wet basis, %) for all treatments on October 23, 
2008.  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
194 
 
Figure 3-6: Sorghum moisture content (wet basis, %) for all treatments on October 30, 
2008.