Long-term Effects of a Perennial Forage Grass in a Peanut-Cotton Rotation 
on Soil Properties 
 
by 
 
Ronald Earl Prevatt, III 
 
 
 
 
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 
December 8, 2012 
 
 
 
 
Keywords: Bahiagrass, Cotton, Peanut, Organic Carbon, Grazing 
 
 
Copyright 2012 by Ronald Earl Prevatt, III 
 
 
Approved by 
 
Julie A. Howe, Chair, Assistant Professor of Agronomy and Soils 
Francisco J. Arriaga, Assistant Professor of Soil Science, University of Wisconsin-
Madison 
Joey N. Shaw, Alumni Professor of Agronomy and Soils 
 
 
 
 
 
 
ii 
 
 
 
 
 
 
Abstract 
 
 
Peanut (Arachis hypogeae) and cotton (Gossypium hirsutum) are traditionally 
rotated together in southern Georgia and Alabama, and in northern Florida.  Maintaining 
crop yields and long-term economic sustainability with this rotation is difficult. Inversion 
of peanuts for harvest and fallow soil in the winter causes fields to be prone to water and 
wind erosion.   This is exacerbated by the fact that neither cotton nor peanut contribute 
greatly to soil organic carbon (SOC), which is known to improve soil structure and 
drainage and reduce erosion.  Conservation practices such as reduced tillage aid in soil 
conservation, but may not be sufficient in these highly carbon-depleted soils.  The 
addition of bahiagrass (Paspalum notatum) to the traditional peanut-cotton rotation is a 
potential cropping strategy that may improve sustainability and profitability of traditional 
crops.  It has shown to lower the inputs of fertilizers, fuel, and pesticides; reduce pest and 
disease pressure; and increase productivity.  However, the effect of the perennial forage 
grass on soil organic carbon and soil quality has not been adequately quantified.  The 
objective of this research is to determine the effect of bahiagrass incorporated into the 
cotton-peanut rotation (i.e., sod-based rotation) on soil organic carbon and associated 
physical and chemical properties.   
Traditional and sod-based rotation systems that have been established for more 
than 8 years were evaluated at the Wiregrass Research and Extension Center (WREC) in 
Headland, AL, and the North Florida Research and Education Center (NFREC) in Quincy 
 iii 
and Marianna, FL. The WREC and NFREC (Marianna) sites have large-scale plots that 
are in all phases of the sod-based rotation (bahiagrass-bahiagrass-peanut-cotton) with 
cattle grazing on the 2nd year of bahiagrass and on winter oat/rye cover crops.  The 
WREC and NFREC (Quincy) sites have small-scale plots that have all phases of the sod-
based and traditional rotations without grazing.  For general comparisons of the rotations, 
all plots are irrigated under strip tillage, but additional treatments in the small plot 
experiments allow comparison of moldboard plow and strip tillage (WREC), as well as 
irrigation and non-irrigation (NFREC Quincy).  The large-scale plots have cattle 
exclusion cages (15x15 m) that allows for the comparison of grazed and non-grazed 
conditions.  Soil organic carbon (SOC) was assessed with depth, and the 13C/12C isotopic 
ratio of the SOC was assessed at 0-5 cm to assess the contribution of bahiagrass to the 
system.  The effects of bahiagrass on water relationships were assessed by examining the 
infiltration rate, bulk density, macroporosity, and the saturated hydraulic conductivity of 
the soil in the crop management systems.  In addition to carbon analysis, nutrient 
assessments included available Ca, Mg, K, P and Na, as well as nitrate-N and 
ammonium-N.   
Overall, there were few differences between the sod-based and conventional 
rotations.  Soil organic C was found to range from 1.20-19.00 g kg-1 and decrease with 
depth.  No difference was found between the cropping sequences or the rotation; 
however, SOC was typically higher following the bahiagrass sequences.  Secondary 
treatment, plow vs strip-tillage, in the small plot experiment at the WREC location was 
also found to differ by tillage treatment, with the strip-tilled plots usually having a higher 
amount of SOC than the plowed plots.  Using ?13C values, it was determined that 19.0 to 
 iv 
37.5% of the SOC was contributed by the bahiagrass.  Macroporosity ranged from 0 to 
1.1% and was generally highest after the peanut and cotton of the traditional rotation and 
after the cotton of the sod-based rotation.  Cropping sequence, secondary treatment, and 
rotation provided no difference in macroporosity.  Bulk density was not found to differ 
by cropping sequence or rotation at any location, but was generally higher in the 5-10 cm 
depth than in the 0-5 cm depth.  No difference in saturated hydraulic conductivity or 
infiltration was found between the cropping sequences or by rotation at any location.  
Calcium, K, Mg, Na, and P at all locations differed by depth, but there was no effect of 
cropping sequence, except with Mg (WREC small plot experiment) and P (WREC and 
NFREC large experiments), or secondary treatment in any of the experiments.  At both 
the small plot experiments, a difference in the amount of NO3-N and NH4-N was found 
between the different cropping sequences.  All benefits previously found were following 
the first few years of the sod-based rotation, while this study evaluated the system after 
10 years.  This suggests that over time the benefits of the sod-based rotation when 
compared to the traditional rotation, both using conservation practices, are lost.  This is 
likely due to the accumulation of organic C by cover crops.  However, when grazing was 
allowed on the 2nd year of bahiagrass, there was generally less organic C than in the non-
grazed portion.  More research is needed to complete the assessment of why the benefits 
of the sod-based rotation equal those of the traditional rotation when both in conservation 
systems. 
 
 
 
 
 
 
 v 
 
 
 
 
 
Acknowledgments 
 
 
 The author wishes to dedicate his thesis to his loving son, Dru.  The author also 
wishes to express his greatest appreciation to Dr. Julie A. Howe for her guidance, 
wisdom and council. Appreciation is also extended to the remaining members of the 
advisory committee, Dr. Francisco J. Arriaga and Dr. Joey N. Shaw, for their knowledge 
and insight on the procedures performed during this research. The author would also like 
to thank Ms. Cynthia Hunter, Mrs. Julie Arriaga, Mr. David Bailey, Mr. Robert Florence, 
Ms. Audrey Gamble and Mr. Jared Etress for their help in the laboratory and in the field, 
Ms. Kim Bryan for her help using the CT scanner, Mr. Donn Rodekohr for his help using 
GIS systems, and fellow graduate students for their friendship and support. Finally, the 
author wishes to offer his deepest appreciation to his parents, Mr. Ronald Prevatt Jr., Mrs. 
Janet Prevatt, and the rest of the Prevatt family and friends for their love and support 
through this and all aspects of his life. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 vi 
 
 
 
 
 
Table of Contents 
 
 
Abstract .......................................................................................................................... ii 
Acknowledgments ........................................................................................................... v  
List of Tables................................................................................................................ viii  
List of Figures ................................................................................................................. x  
I. Literature Review ......................................................................................................... 1 
Introduction ......................................................................................................... 1 
Peanut-cotton Producing Region of the Southeastern Coastal Plain ...................... 2 
Agronomic Practices ............................................................................................ 4 
Summary ........................................................................................................... 16 
References ......................................................................................................... 18 
II. Physical Effects on Coastal Plain Soils of Forage Grasses Included in a Peanut 
Cotton Rotation ....................................................................................................... 35 
Abstract ............................................................................................................. 35 
Introduction ....................................................................................................... 36 
Materials and Methods ....................................................................................... 39 
Results  .............................................................................................................. 47 
Discussion.......................................................................................................... 51 
Conclusion ......................................................................................................... 56 
References ......................................................................................................... 58 
 vii 
III. Effect of Perennial Grasses Added to a Peanut-Cotton Rotation on Soil Chemical 
Properties................................................................................................................. 74 
Abstract ............................................................................................................. 74 
Introduction ....................................................................................................... 75 
Materials and Methods ....................................................................................... 78 
Results  .............................................................................................................. 84 
Discussion.......................................................................................................... 88 
Conclusion ......................................................................................................... 91 
References ......................................................................................................... 93 
Appendix 1. Official series description of the Dothan soil series as described by the 
USDA-NRCS Soil Survey Division ......................................................................... 110 
Appendix 2. Official series description of the Orangeburg soil series as described by 
the USDA-NRCS Soil Survey Division ................................................................... 112  
 viii 
 
 
 
 
 
List of Tables 
 
 
Table 1.  Soil particle size distribution, texture, and mean pH for the small plot 
experiments at the Wiregrass Research and Extension Center (WREC) and 
the North Florida Research and Extension Center (NFREC).  The soil series 
at WREC was Dothan (Fine-loamy, kaolinitic, thermic Plinthic Kandiudult) 
and at NFREC was Orangeburg (Fine-loamy, kaolinitic, thermic Typic 
Kandiudult). . .................................................................................................. 65 
Table 2.  Soil organic carbon (SOC) by cropping sequence in the small plot and large 
experiments at the Wiregrass Research and Extension Center (WREC) and 
at the North Florida Research and Education Center (NFREC).  ...................... 66 
Table 3.  Soil organic carbon and bulk density in the 0-5 and 5-10 cm depth 
increments for each of the rotations in the small plot experiments at the 
Wiregrass Research and Extension Center (WREC) and the North Florida 
Research and Extension Center (NFREC).  ..................................................... 67 
Table 4.  Soil organic carbon (SOC) by secondary treatment and combined crop 
sequences in the small plot and large experiments conducted at the 
Wiregrass Research and Extension Center (WREC) and at the North Florida 
Research and Education Center (NFREC).  ..................................................... 68 
Table 5.  Calculated macroporosity (pore size ? 1.1 mm diameter) by area in 
calibration cores determined by gray-scale analysis of computerized 
tomographic scans of a loam, loam with 5% added peat, and 100% peat 
with three added macropores.  ......................................................................... 69 
Table 6.  Calculated macroporosity by area (pore size ? 1.1 mm diameter) in field 
cores by cropping sequence and depth in the small plot and large 
experiments at the Wiregrass Research and Extension Center (WREC) and 
the North Florida Research and Extension Center (NFREC) using 
computerized tomography (CT) scans.  Calibration of the CT scan method 
for determination of macroporosity indicated approximately 30% less 
macropores than actually present.  Data has not been corrected to reflect this 
loss. ................................................................................................................ 70 
Table 7.  Bulk density in the 0-5 and 5-10 cm depth increments for each of the crop 
sequence for the irrigated strip-tilled treatments in the small plot 
experiments at the Wiregrass Research and Extension Center (WREC) in 
Headland, AL, and the North Florida Research and Extension Center 
(NFREC) in Quincy, FL.  ................................................................................ 71 
 ix 
Table 8.  Soil textural class, mean pH, and cation exchange capacity (CEC) for 
Dothan soil series (Fine-loamy, kaolinitic, ,thermic Plinthic Kandiudult) at 
the Wiregrass Research and Extension Center (WREC) in Headland, AL, 
and for the Orangeburg soil series (Fine-loamy, kaolinitic, thermic Typic 
Kandiudult) at the North Florida Research and Extension Center (NFREC) 
in Quincy, FL.. .............................................................................................. 103 
Table 9.  Soil organic carbon (SOC) by cropping sequence in the small plot and large 
experiments at the Wiregrass Research and Extension Center (WREC) and 
the North Florida Research and Education Center (NFREC).  ....................... 104 
Table 10. Soil organic carbon (SOC) by secondary treatment (tillage, irrigation, 
grazing) in the small plot and large experiments conducted at the Wiregrass 
Research and Extension Center (WREC) and at the North Florida Research 
and Education Center (NFREC).  .................................................................. 105 
Table 11. Delta 13C values and contributions SOC by C3 and C4 plants in 0-5 cm 
depth increment in the small plot experiments at Wiregrass Research and 
Extension Center (WREC) and the North Florida Research and Extension 
Center (NFREC).  ........................................................................................ 106 
Table 12. Concentrations of Ca, K, Mg, Na, and P by depth at the small plot and large 
experiments at Wiregrass Research and Extension Center (WREC) and the 
North Florida Research and Extension Center (NFREC).  ............................ 107 
Table 13. Magnesium and P concentrations in soil by cropping sequence and depth in 
the small plot experiment at Wiregrass Research and Extension Center 
(WREC) and the large experiments at WREC and North Florida Research 
and Education Center (NFREC).  ................................................................. 108 
Table 14.  Nitrate-nitrogen (NO3--N) and ammonium-N (NH4+-N) concentrations at 
0-5 and 5-10 cm depths by cropping sequence in the small plot and large 
experiments at the Wiregrass Research and Extension Center (WREC) and 
the North Florida Research and Extension Center (NFREC).  ...................... 109 
 
 
 
 
x 
 
 
 
 
 
 
List of Figures 
 
 
Figure 1. Example grayscale computerized tomography (CT) scans of calibration 
cores constructed with A) loam soil, B) loam soil with 5% peat, and C) 
100% peat that were used to compare macroporosity calculated using CT 
analysis with actual macroposity. Arrows indicate constructed macropores 
with grayscale values < 72.  Macroporosity is defined as pore sizes ?1.1 mm 
in diameter.  .................................................................................................... 72 
Figure 2. Mean hydraulic conductivity of saturated soil (Ksat) at 15 cm below soil 
surface for each of the cropping sequences that were strip-tilled and irrigated 
in the small plot experiments at A) the Wiregrass Research and Extension 
Center (WREC) and B) the North Florida Research and Extension Center 
(NFREC).  Significance letters indicate differences by cropping sequence at 
?=0.05; SBR = sod-based rotation (bahia1-bahia2-peanut-cotton); TR = 
traditional rotation (peanut-cotton or peanut-cotton1-cotton2). Cotton2 data 
is not shown.  Black bars indicate crop sequences in the SBR and white bars 
indicate crop sequences in the TR. .................................................................. 73 
 
 
 
 
1 
 
 
 
 
 
 
I. Literature Review 
 
Introduction 
The current world population is 6.9 billion (U.S. Census Bureau, 2010), and it is 
expected to rise to approximately 10 billion by the year 2050 (Worldwatch Institute, 
2011).  As the world population increases, the demand for food and plant-based products 
will continue to rise.  Long-term, sustainable agricultural practices that are capable of 
maintaining high yield are necessary to keep pace with the rising demand.   
The traditional crop rotation in the southeastern U.S. is peanut (Arachis 
hypogaea) followed by one to two years of cotton (Gossypium hirsutum).  This rotation is 
consistently plagued with disease, pests, and weeds (Crookston, 1995; Tanaka et al., 
2002) that require high levels of management inputs.   Furthermore, the rotation is 
typically managed by conventional agronomic management practices involving inversion 
tillage and fallow periods during the winter months.  These practices decrease residues on 
the soil surface, which contributes to erosion and soil loss reducing long-term 
sustainability (Reeves, 1997; Reddy et al., 2004).  Because of these factors, conventional 
management of the traditional peanut-cotton rotation is difficult to sustain economically 
and environmentally. 
Conservation practices, such as reduced tillage and cover cropping, are an 
alternative to conventional management practices.  These practices improve 
environmental sustainability by reducing erosion and soil loss through preservation of 
2 
 
plant residues on the soil surface.  Reduced tillage has shown to increase crop production 
(Reeves, 1994), but long-term benefits to the soil from conservation practices can also 
improve sustainability due to changes in soil organic matter, nutrients, water retention, 
and soil structure (Reeves, 1994; Ess et al., 1998; Raper et al., 2000). 
In addition to conservation practices, adding a perennial grass to the traditional 
peanut-cotton rotation (i.e., sod-based rotation) improves profitability and environmental 
sustainability (Norden et al., 1977; Wiatrak et al., 2007).  Perennial grasses, such as 
bahiagrass (Paspalum notatum), have a large root biomass that contributes to soil organic 
carbon (SOC), which is known to provide numerous benefits to agronomic systems (e.g., 
infiltration, water and nutrient retention, and pH buffering).  Furthermore, sod-based 
rotations have demonstrated high yields with reduced fertilizer, pesticide, herbicide, and 
irrigation inputs (Norden et al., 1977; Wright et al., 2005; Wiatrak et al., 2007). 
The overall effects of sod-based rotation combined with conservation 
management on soil physical and chemical properties are poorly understood, especially in 
established systems (i.e., >8 years).   Understanding the impact of perennial grasses under 
hay and grazing management on soil properties may lead to improvements in 
management practices and sustainability for cotton and peanut producers in the 
southeastern U.S.   
Peanut-cotton Producing Region of the Southeastern Coastal Plain 
Geography 
 The peanut-cotton producing region of the southeastern Coastal Plain lies in the 
southern portion of Alabama and Georgia and the northern portion of Florida.  This 
region is located on the East Gulf Coastal Plain and the Atlantic Coastal Plain.  The 
3 
 
northern portion of the peanut-cotton producing region rests on sedimentary bedrock.  
Topography drastically changes from flat areas to steep slopes ranging from 40 to 180 m 
above sea level.  Steeper areas tend to be prone to runoff and erosion, while flatter areas 
accumulate water and are susceptible to leaching (USDA, 2012).  The southern portion of 
the peanut-cotton producing region is formed from beds of sandy and clayey marine 
sediments deposited by ocean currents and has a consistent elevation of 30-40 m.  The 
soils are formed from deltaic or shallow marine sediments with hills carved into the land 
by flowing water (USDA, 2012). 
Climate 
The climate of the southeastern U.S. peanut-cotton region is warm and relatively 
humid.  The air temperature typically follows a positive gradient from the north to the 
south, and there is a pronounced seasonal cycle (Mearns et al., 2003).  The temperature 
ranges from a daily average maximum of 33?C in the summer to a low of 3?C in the 
winter in southern Alabama and northern Florida (USDA, 2002).  
Average annual rainfall ranges from 1,040 to 1,525 mm in southern Alabama and 
northern Florida (USDA, 2002).  Short-term droughts lasting from 14 to 21 days are 
common during the peanut-cotton growing season (Simoes et al., 2009).  Minimum 
monthly rainfall is typically in October near peanut and cotton harvest times (Mearns et 
al., 2003). 
Soils 
The soils in the peanut-cotton producing region tend to be very similar.  They are 
typically coarse-textured, highly weathered, erodible, carbon-depleted, and have poor 
water and nutrient retention (Simoes et al., 2009).  Soils also tend to be weak structured, 
4 
 
single-grained or massive, low in soil organic carbon (SOC), and high in bulk density 
(Campbell et al., 1974).  These factors cause conditions in the soil that can physically 
impede root growth (Barley et al., 1965; Doty et al., 1975; Trouse and Reaves, 1980).   
With the weak soil structure in the peanut-cotton producing region, soils tend to be highly 
weathered and leached of plant available nutrients (USDA, 2012).  These factors also 
contribute to the inherently acidic soils of the peanut-cotton producing region (USDA, 
2012). 
Agronomic Practices 
Conventional Agronomic Management Practices 
Cultivation of cotton and peanut are common in the rural parts of southern 
Alabama and Georgia and in northern Florida in the Coastal Plain region of the 
Southeast.  The traditional agronomic practice in this region is to rotate one year of 
peanut with one to two years of cotton using conventional tillage practices involving 
plowing in the fall followed by a winter fallow and spring disking to break the surface 
prior to planting (Brown et al., 1985).  Short two-year rotations can become susceptible 
to classic problems, such as stagnant yields, soil degradation, and survival and adaptation 
of pests (e.g., nematodes) and disease (Tomato Spotted Wilt Virus; Cox and Sholar, 
1995; Crookston, 1995; Tanaka et al., 2002).   
Stagnate yields are likely linked to soil degradation.  Peanut and cotton provide 
little residue and do not contribute to organic carbon in the soil (Reeves, 1997; Reddy et 
al., 2004).  Furthermore, plowing and disking reduces surface residue and increases SOC 
degradation.  This leaves the system in a highly erodible condition during the fallow 
period (Brown et al., 1985).  The erosion and depletion of SOC under conventional 
5 
 
agronomic practices are primary processes that contribute to the degradation of the soil 
(Bruce et al., 1995).  In the sandy soils of the Southeast, SOC plays a major role in 
nutrient retention in soils (Wilson et al., 1982).  To maintain production yields, growers 
supplement soil with fertilizers for nutrients that are lost due to leaching and residue 
removal (Katsvario et al., 2007).  However, fertilization costs reduce profitability and can 
be a source of environmental pollution.   
Shallow rooting depth is also a problem with the traditional peanut-cotton 
rotation.  Cotton and peanut roots cannot penetrate the compaction zone that commonly 
exists in the region at the 15-cm soil depth (Kashirad et al., 1967; Campbell et al., 1974).  
This can cause crops to reach drought stress in as little as three days (Elkins et al., 1977).  
After decades of farming in this manner, yields have grown stagnant due to erosion, poor 
nutrient retention, and increased susceptibility to droughts, while the prices of fuel, 
fertilizer, seed, pesticides and herbicides have increased (USDA-Economic Research 
Service, 2011).  This limits profitability and leads to farm failure. 
Soil Physical Properties under Conventional Agronomic Practices 
 Management is known to directly affect soil physical properties including 
structure, bulk density, compaction, infiltration, saturated hydraulic conductivity, and 
porosity.  These properties influence productivity by limiting the amount of water crops 
are able to obtain (Benjamin et al., 2003).  Not only is water availability reduced in the 
soil, but there is a greater chance that rainfall and irrigation will runoff potentially taking 
soil with it. 
Soils under conventional agronomic management practices tend to be weak 
structured, single-grained or massive (Campbell et al., 1974).  Soil organic carbon is 
6 
 
known to be a natural binding agent for soil aggregation (Tisdall and Oades, 1982), but 
under conventional agronomic practices, decreases in SOC reduce the amount of water-
stable aggregates (Causarano et al., 2008).  The decrease in aggregation and overall soil 
structure increases soil bulk density due to loss of micro- and macropore space 
(Causarano et al., 2006). 
Bulk density is defined as the mass of dry soil per unit bulk volume (Soil Science 
Society of America, 2001).  Bulk densities associated with the conventional agronomic 
system, range from 1.5 to 1.6 g cm-3 (Benjamin et al., 2010).  High bulk densities such as 
these can be an indicator of soil compaction (Arshad et al., 1996), which is important 
when considering root growth and water movement through the soil.  Simoes et al. (2009) 
noted that a mixture of coarse particles (sand) from the surface and fine particles (clay) 
from the subsurface tends to fill most of the void spaces at the horizon interface.  This 
potentially creates a root restricting layer (Kashirad et al., 1967; Campbell et al., 1974) 
that prevents crops from reaching the nutrients and water beneath it.  High bulk density 
also contributes to water accumulation and runoff from the surface of the soil without 
infiltration resulting in sheet, rill, and gully erosion (Campbell et al., 1974).  Thus, 
maintaining or improving bulk density and reducing compaction can reduce losses in 
productivity and environmental pollution. 
Soils with lower bulk density typically have higher infiltration and less erosion 
(Paxton et al., 1993).  Soils under conventional agronomic management practices in the 
Southeast have been measured to have infiltration rates of 0.31 cm min-1 (Katsvairo et al. 
2007).  This is largely due to the low saturated hydraulic conductivity (e.g., 6?10-5 cm 
s-1) of soils with low organic matter and poor structure (Benjamin et al., 2010).  Low 
7 
 
infiltration and poor saturated hydraulic conductivity contribute to erosion as rainfall and 
irrigation practices are likely to exceed infiltration and downward movement of water. 
Macropores are the pathways for preferential flow of water, air, and nutrients in 
soils (Beven and Germann, 1982; Lin et al., 2005; Jarvis, 2007).  Soil type and land 
management are among the most important factors in determining macropore 
characteristics (Gantzer and Anderson, 2002; Mooney and Morris, 2008).  Macropores 
formed by roots are highly continuous and round, and decrease in size with depth (Luo et 
al., 2010).  Cropped management systems typically have few macropores (0.024 m3 m-3), 
which are smaller and less frequent near the compaction zone. 
Soil Chemical Properties under Traditional Management 
Chemical characteristics of the soil, such as pH, salinity, organic matter, nutrient 
content, and cation and anion exchange capacity, affect both sustainability and 
productivity of row crop production systems.  Production costs in the peanut-cotton 
producing region of the Southeast are increasing due to limitations caused by chemical 
properties associated with infertile soils (Marois et al., 2002).  Conventional management 
practices decrease the ability of the soil to recycle nutrients, lower its cation exchange 
capacity (CEC), and lower the pH of the soil.   
Cation exchange capacity indicates the capacity of a soil to hold cationic nutrients 
such as Ca, Mg, K, and Na.  In acid soils, this also includes proton and Al and its 
associated hydrolysis products (Essington, 2004b).  Cation exchange capacity is 
influenced by several factors including management practices (Hussain et al., 1999), 
amount of SOC (Fesha, 2004), and pH (Bohn et al., 1985).  Low CEC is associated with 
the conventional management practices due to their effect on reduction of SOC (Fesha, 
8 
 
2004) and pH (Katsvairo et al., 2007).  In general, about 45% of CEC is due to SOM with 
the remaining 55% attributed to clay (Foth and Ellis, 1997b).  Mahboubi et al. (1993) 
showed a significant increase in CEC in the 0 to15 cm depth range of a sandy clay loam 
layer when a no-till system was adopted that increased soil organic matter over 28 years. 
The pH of soil is an indicator as of nutrient availability to plants.  In addition, 
each crop requires a certain pH range to be able to grow.  Management practices have a 
tendency to change pH quickly in the surface horizon of the soil (Smith and Doran, 
1996).  Soils that have a pH lower than 4.0 to 4.5 or greater than 8.5 have usually been 
influenced by human activity (Essington, 2004a).  The pH of the soil affects the charge, 
both negative and positive, of mineral and organic particles, and thus the cation and anion 
exchange capacities of a soil (Foth and Ellis, 1997a).  The CEC of a soil will increase 
with increasing pH, thus a decreasing soil pH indicates reduced cation retention 
(Katsvairo et al., 2007).  Low pH is commonly corrected through the application lime, 
which increases pH and provides cations to the soil.  It will also help alleviate any 
aluminum toxicity associated with the soil.  Traditional management practices typically 
reduce soil organic matter, which is a natural buffer against changes in pH.  Thus, long-
term traditional management practices may result in more rapid pH decline than systems 
that promote higher SOC levels.  
Nutrients are highly influenced by their forms, concentrations, and ability to be 
retained by the soil and organic particles.  Loss of basic cationic nutrients, such as K, Ca, 
and Mg, under the traditional management practices is high, and it often outweighs the 
removal of crops, livestock and livestock products (Tivy, 1987).  The root-impeding 
compaction zone that is common in the Coastal Plain region prevents roots from reaching 
9 
 
nutrients found up to 170 cm beneath the soil surface (Long and Elkins, 1983).  
Potassium is typically unavailable and tends to be bound within rock or within specific 
clay minerals (Tivy, 1987).  
Nitrogen, which is crucial to plant growth, does not stay in the soil for long-
periods of time when applied as fertilizer.  Approximately 30-50% of applied nitrogen is 
taken up by crops (Tivy, 1987).  The remaining nitrogen is either immobilized by soil 
microorganisms or lost through leaching, volatilization, and denitrification (Cassman et 
al., 2002).  In particular, nitrate is susceptible to loss with drainage water due to repulsion 
of the anion by negatively charged soil colloids.  In areas with poor aeration and 
drainage, denitrification may occur (Tivy, 1987).  Denitrification is the bacterial 
reduction of nitrate to gaseous nitrogen (Tivy, 1987).  Ammonium compounds tend to 
volatilize when added near or on the soil surface (Smilde, 1972).  Under traditional 
agronomic practices, the majority of plant biomass is removed from the surface of the 
field taking with it organic N that could be mineralized and subsequently available to 
future crops.  Even when some residues remain, fields can lose up to 60% more N than if 
the field was under a winter cover crop (Wagger, 1989).   
Phosphorus is the most ?temperamental? of the nutrients (Tivy, 1987).  It has low 
mobility and low efficiency of use.  It is less susceptible to leaching than N or K, but is 
more easily fixed and rendered unavailable (Tivy, 1987).  The optimum pH range for P is 
much smaller than that of other macronutrients.  In acidic environments, such as the 
peanut-cotton producing region of the southeastern U.S., P is likely to form insoluble 
compounds with Fe, Al, and Mn (Tivy, 1987).  Conventional agronomic practices 
typically apply excess P to overcome immobilization issues (Wilson, 1982); however, 
10 
 
this can result in contamination of water due to loss of in runoff, leachate, and eroded 
particles. 
Conservation Management 
Conservation agronomic practices are becoming more prevalent in the Coastal 
Plain region.  By definition, it is any tillage or seeding system that maintains a minimum 
of 30% residue on the soil surface (ASABE Standards, 2005).  Reduced tillage, strip 
tillage, no tillage, and cover cropping are the most common techniques used alone or in 
combination; however, strip tillage is the most common technique used in this region 
(Wiatrak et al., 2007).  Strip tillage removes residue from the seeding area of the row 
allowing sunlight to reach the soil and warm it without disturbing most of the residue 
adjacent to the row (Johnson et al., 2001).  Unlike conventional agronomic systems, 
which may require multiple passes through a field to prepare a seedbed, only one pass 
through the field is needed saving time and fuel.   
In the peanut-cotton producing region of the Southeast, about 50% of the 2.9 
million ha of cotton and 55% of the 525,000 ha were in some type of conservation tillage 
system (CTIC, 2005).  Conservation systems in this region have demonstrated increased 
water retention and SOC levels, as well as improved soil structure (Reeves, 1994; Ess et 
al., 1998; Raper et al., 2000).  Because water retention increases, the number of days 
before a crop reaches drought stress increases reducing irrigation needs (Elkins et al., 
1977).  Furthermore, the increase in SOC reduces erosion by increasing aggregation and 
improving soil structure (Paxton et al., 1993).   
Another common conservation management practice in this region is planting a 
cover crop during the winter after row crops have been harvested.  The potential for 
11 
 
winter annual cover crops to conserve soil and water resources in conservation tillage 
production systems is well documented over diverse cropping environments (Blevins et 
al., 1971; Sojka et al., 1984).  Cover crops contribute to nutrient cycling and decrease the 
amount of erosion in comparison with a fallow field (Wagger, 1989).  In a study 
conducted by Wilson et al. (1982), cover cropping during the winter improved SOC 
content, total organic nitrogen, water retention and transmission properties, and decreased 
bulk density in the top 10 cm of soil. 
Sod-based Rotation  
The sod-based rotation adds two years of a perennial forage grass into the 
traditional peanut-cotton rotation, thus extending a two year peanut-cotton rotation into a 
four year sequence of peanut, cotton, perennial grass, and perennial grass (Katsvairo et 
al., 2007).  Numerous benefits of this rotation system have been identified including 
reducing of pressure from disease and pests by breaking their life cycles (Cox and Sholar, 
1995), improved water relationships (Benjamin et al., 2008), and enhanced nutrient 
retention (Wilson et al., 1982).   
Bahiagrass is a good perennial forage grass for the Southeastern Coastal Plain 
because it is suited for soils with low fertility (Magness et al., 1971).  It is traditionally 
grown in pastures in this region.  It is drought tolerant and able to grow in sandy soils 
(Field and Taylor, 2002).  The extensive root system exhibited by bahiagrass (Blue and 
Graetz, 1977; Impithuksa and Blue, 1978) increases porosity, which lowers bulk density 
allowing for greater water movement, and greater growth for subsequent crops (Simoes et 
al., 2009).  It has been shown that roots from crops following bahiagrass were able to 
reach below the compaction zone (Katsvairo et al., 2007).   Katsvario et al. (2007) found 
12 
 
that compared to cotton in the traditional rotation, cotton in sod-based rotation had larger 
root crown diameters, larger total root area, longer total root lengths, and a larger root 
biomass allowing the roots to explore a larger soil volume for nutrients and moisture.  
This could lead to a decrease in the amount of fertilizer and water needed for crops to be 
grown.  Elkins et al. (1977) noted that the sod-based rotation was able to resist water 
stress up to ten times longer than the peanut-cotton rotation under conventional 
agronomic management practices.  The perennial grass contributes to SOC through its 
remaining above-ground biomass and decay of below-ground biomass (Wright et al., 
2006).  Devane et al. (1952) reported greater soil N and SOC under bahiagrass than in the 
adjacent cultivated fields. 
A decrease in the amount of weeds (Wiatrak et al., 2007), diseases (Cox and 
Sholar, 1995; Jordan et al., 2002; Lamb et al., 1993), and pests (Cox and Sholar, 1995; 
Dickson and Hewlett, 1989; Jordan et al., 2002; Lamb et al., 1993; Wright et al., 2005) 
has also been observed in the sod-based rotation system.  This reduces the amount of 
herbicide and pesticide needed for maximum crop production and increases profitability 
of the crop by reducing the expense associated with maximum crop production.   
With these improved conditions, productivity would be expected to increase 
(Norden et al., 1977; Wiatrak et al., 2007).  Wiatrak et al. (2007) observed a decrease in 
the number of plants, but more cotton bolls per plant under strip-tillage.  Also, the yield 
and quality of peanuts were significantly better following bahiagrass sod than under the 
traditional peanut-cotton rotation (Norden et al., 1977). 
Grazing vs. Non-grazing of the Sod-based Rotation 
13 
 
 Bahiagrass in the sod-based rotation can be managed for hay or grazing.  By 
including livestock and allowing it to graze on the bahiagrass in the sod-based rotation, 
producers extend the period of productivity, improve economic returns, and reduce risk 
by diversification of their products available for sale.  Broadening the range of products 
for sale alleviates stress associated with fluctuations in climate and price by efficient 
utilization of resources (Tanaka et al., 2002; Zentner et al., 2002).   
   Grazing cattle return nutrients to the surface horizon of the soil (Sigua and 
Coleman, 2010).  Grazing also partially controls the amount and composition of SOC and 
distribution of N in the soil profile (Rosswall, 1976; Smoliak et al., 1972).  White et al. 
(2001) suggested that the longer durations of cattle grazing in one area increases 
defecation, and thus nutrient cycling.  Therefore, grazing pastures can help lower 
fertilizer input. 
 Soil Organic Carbon 
Following addition of a perennial grass to the peanut-cotton rotation, SOC 
increased (Wright et al., 2006).  This has also been demonstrated with the adoption of 
conservation tillage practices (Reeves, 1994).  Soil organic carbon influences the ability 
of the soil to aggregate, retain water, erode, sequester carbon, and cycle nutrients 
(Katsvairo et al., 2007).  Most short-term changes in SOC result from changes in 
management (Bowman et al., 1999; Mikha et al., 2006; McVay et al., 2006).  Carbon 
sequestration is the removal and storage of carbon from the atmosphere in carbon sinks 
(i.e., oceans, forests or soils) through physical or biological processes.  Agricultural soil 
is a potential sink for reducing the amount of carbon dioxide in the atmosphere (Sperow 
et al., 2003).  Sequestering carbon in the soil may decrease the amount of carbon dioxide 
14 
 
in the atmosphere, and thus impact global warming by decreasing greenhouse gases 
(Rosenzweig and Hillel, 2000; Izaurralde et al., 2001; Metting et al., 2001; Lal, 2004).  
Switching from annual crops to perennial crops and using of specialized management 
practices such as the use of improved grasses and rotated grazing (Conant et al., 2001) 
may improve soil carbon sequestration by increasing residues and plant roots and 
decreasing disturbances in the soil (Paustian et al., 1997).  
Influence of Soil Organic Carbon on Soil Physical Properties 
Soil organic carbon is known to be a natural binding agent for soil aggregation 
(Tisdall and Oades, 1982).  Under conservation tillage practices, increases in SOC have 
improved water stable macroaggregation in wheat/grass plots compared to wheat/fallow 
rotations (Causarano et al., 2008).  Macroaggregates are associated with the slowly 
decomposable or stabilized fraction of SOC (Cambardella and Elliot, 1992).   
Typically, increases in SOC result in decreases in soil bulk density (Wilson et al., 
1982).  Soil organic matter is a key in aggregation (Causarano et al., 2006) and combined 
with conservation management techniques improve soil structure, which decreases bulk 
density.  This is due to the lower bulk density of SOC itself, but also to the increased soil 
structure.  Reeves (1994) found that the average bulk density in fields under conservation 
tillage were lower than conventionally tilled fields.  Franzluebbers and Struedemann 
(2010) found a difference in bulk density in the top 6 cm of soil when grazing was 
allowed on the sod portion of the rotation (1.46 vs. 1.42 Mg m-3, grazed vs. ungrazed, 
respectively).  The improved structure and decreased bulk density can lessen the degree 
of erosion seen in southeastern fields (Causarano et al., 2006).  Also, with a decrease in 
15 
 
erosion, the amount of nutrients that are carried away with the soil is lessened (Paxton et 
al., 1993). 
Water retention in Southeast soils tends to be minimal due to the coarse soil 
textures and lack of SOC (USDA, 2007).  This causes crops to enter water stress quickly 
(Elkins et al., 1977) following several days without rain (Simoes et al., 2009).  Irrigation 
to supplement rainfall is costly to rural growers.  The sod-based rotation with bahiagrass 
and other conservation methods have demonstrated increased soil water retention due to 
increases in SOC compared to traditional rotation and management practices (Reeves, 
1994; Ess et al., 1998; Raper et al., 2000).  The increased SOC would increase the water 
holding capacity of the soil (Reeves, 1994; Ess et al., 1998; Raper et al., 2000) by 
absorbing the moisture and releasing it slowly.  Studies conducted in Texas show that 
using strip-tillage and cover cropping reduced the amount of evapotranspiration in soil 
and from the following cotton crop (Lascano et al., 1994).  This could reduce the need to 
supplement rainfall with irrigation (Lascano et al., 1994).   
Influence of Soil Organic Carbon on Soil Chemical Properties 
The increase in SOC increases the CEC of a soil (Fesha, 2004).  Wilson et al. 
(1982) showed that the increase in SOC after 2 years in bahiagrass increased the mean 
SOC by 0.35% (w/w), exchangeable Ca by 490 mg kg-1, and exchangeable Mg by 79 mg 
kg-1.  An increase in K status occurs because forage grasses, such as bahiagrass, are able 
to extract non-exchangeable K and recycle it from sub-surface horizons (Juo and Lal, 
1977).   
Nitrogen availability and quantity are important factors in cotton development and 
yield (Doss and Scarsbrook, 1969; Oosterhuis et al., 1983).  Numerous studies have 
16 
 
shown that legumes, such as peanuts, can immediately increase available N in soils, when 
left as residue, due to their rapid breakdown and release of N (McVay et al., 1989; 
Holderbaum et al., 1990; and Vyn et al., 2000).  Newman et al. (2006) found that soil 
organic N increased by 5.7% per year and SOC increased by 26% over six years by 
leaving residue in the field.  The use of crop rotation may reduce the potential of nitrogen 
to leach and degrade into groundwater (Touchton et al., 1995).  However, it is important 
to keep in mind that high C:N and C:P ratios can lead to immobilization of nutrients 
making them unavailable for plant uptake (Dubeux et al., 2007).   
Summary  
The traditional peanut-cotton rotation under conventional tillage management 
practices has limited sustainability environmentally and economically.  Both the rotation 
and the tillage management contribute to decreasing SOC (Katsvario et al., 2007), which 
affects soil structure and stability, nutrient and water retention, infiltration, and ultimately 
leads to erosion and soil loss (Paxton et al., 1993).  In addition, the peanut-cotton rotation 
does not sufficiently break disease and pest cycles.  Over time, inputs such as fertilizer, 
fungicides, pesticides, herbicides, and irrigation become more and more necessary as 
soils degrade, retain less nutrients and water, and disease and pest cycles are not 
interrupted.  Fuel required to apply agrochemicals and operate irrigation systems further 
decreases the profit margin for producers.  
Conservation management is becoming more widely adopted in the peanut-cotton 
producing region of the Southeast in place of conventional management (Johnson et al., 
2001).  These management practices have been proven to increase SOC and reduce 
erosion. Coupling sod-based rotation with conservation management has the potential to 
17 
 
further increase SOC and all of its associated benefits.  For the producer, this should 
equate to increased profitability and sustainability, as well as increased commodity 
diversity that will protect against unstable economic markets.  
Following implementation, the sod-based rotation has shown that it can improve 
physical and chemical aspects of the soil to further increase the yields of the crops 
following bahiagrass.  Bahiagrass returned organic residue to the soil, while 
simultaneously improving water- and nutrient-holding capacity, increasing crop rooting 
depth, improving soil structure, and reducing erosion (Reeves, 1994; Ess et al., 1998; 
Raper et al., 2000).  However, previous studies have not evaluated whether the sod-based 
rotation can improve SOC and its associated benefits to soil physical and chemical 
properties after more than a couple of years.  More research is needed to evaluate the 
potential benefits of the sod-based rotation in the long-term.
18 
 
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Peanut Sci. 36:196-203. 
  
35 
 
 
 
 
 
 
II. Soil Physical Effects of Perennial Grasses Included in a Peanut-Cotton 
Rotation on Coastal Plain Soils 
ABSTRACT 
Peanut and cotton crops have traditionally been grown under conventional tillage 
systems that decrease the already low amount of soil organic carbon (SOC) in the soil.  
Conservation tillage systems along with the addition of a forage crop, such as bahiagrass, 
into the peanut (Arachis hypogaea) -cotton (Gossypium hirsutum) rotation (bahia-bahia-
peanut-cotton or sod-based rotation) have been suggested to help increase SOC, which 
has been demonstrated to improve soil structure, reduce erosion, and improve water- and 
nutrient-holding capacities.  The objective of this study was to compare macroporosity, 
SOC, bulk density, saturated hydraulic conductivity of the soil, and infiltration rates in 
sod-based and traditional rotation systems that have been established for 8 to 10 years. 
Additional effects of tillage method, irrigation, and grazing were also investigated.  
Studies were conducted at the Wiregrass Research and Extension Center (WREC) in 
Headland, AL, and at the North Florida Research and Education Center (NFREC) in 
Quincy, FL, (small plot experiment) and Marianna, FL (large experiment).  Soil organic 
C ranged from 7.87 to 17.32 g kg-1.  Macroporosity, evaluated by computerized 
tomography from 0-60 cm and defined as pore sizes ? 1.1 mm in diameter, ranged from 
not detectable to 1.14% over all depths evaluated.  Bulk density ranged from 1.37 to 2.27 
g cm-3.  Infiltration rate ranged from 1.49x10-3 to 6.43x10-4 cm s-1.  Values for hydraulic 
conductivity of saturated soil had a similar range.  None of the parameters tested was 
36 
 
affected by rotation system, tillage, irrigation, or grazing treatment.  However, most were 
affected by depth, and macroporosity was affected by crop sequence in the NFREC small 
plot experiment where the peanut phase had the highest porosity.  Results indicate SOC 
and physical properties are not improved with the addition of bahiagrass to the peanut-
cotton rotation when conservation practices (e.g., strip-tillage and cover crops) are 
performed.  Lack of differences among treatments suggest that conservation practices, 
especially cover cropping which was used in all treatments, contribute significantly to the 
relatively high SOC levels and similar physical properties exhibited in these soils.   
Introduction 
Row-crop production in southern Alabama and Georgia and northern Florida is 
dominated by peanuts and cotton.  These crops are typically grown in rotation using 
conventional tillage practices.  Soils tend to be coarse-textured with weak structure, 
highly weathered, erodible, carbon-depleted, and have poor water retention (Simoes et 
al., 2009; Campbell et al., 1974).  In addition, soils in this region are commonly plagued 
with a root restricting layer near 15 cm depth (Barley et al., 1965; Doty et al., 1975; 
Trouse and Reaves, 1980) preventing crop roots from reaching water and nutrients in the 
sub-surface soil, making crops more susceptible to the effects of short-term droughts 
(Simoes et al., 2009).  The inherent soil properties in this region combined with 
conventional tillage practices (e.g., disking, soil inversion, winter fallow fields) have led 
to enhanced erosion and loss of water and nutrient-holding capacity over time resulting in 
a loss of economic and environmental sustainability.  In addition, repeated cropping of 
peanut and cotton have led to increased soil loss resulting in infertile fields and 
environmental contamination (Katsvairo et al., 2006).   
37 
 
In order to alleviate long-term soil degradation and high water demand from crops 
managed with conventional tillage, conservation management practices are becoming 
more common in this peanut-cotton growing region.  Common practices include reduced 
and no tillage practices and winter cover crops.  These practices can decrease the amount 
of evapotranspiration (Lascano et al., 1994), increase nutrient- and water-holding 
capacity (Reeves, 1994; Raper et al., 2000; Fesha, 2004), and reduce erosion through 
beneficial properties associated with increased soil organic carbon (SOC) (Causarano et 
al., 2006; Wright et al., 2006).  
 In addition to conservation practices to improve soil quality, the addition of a 
perennial forage grass into the peanut-cotton rotation (i.e., sod-based rotation) has 
improved yield, soil carbon, nutrient cycling, hydraulic properties, and reduced pests and 
diseases, irrigation, fuel consumption, use of fertilizers and chemicals (Dickson and 
Hewlett, 1989; Lamb et al., 1993; Jordan et al., 2002; Wright et al., 2005; Wiatrak et al., 
2007) in the short-term (one complete rotation).  To fully understand the benefits of a 
sod-based rotation in the Southeast, it is necessary to evaluate the system with at least 
two complete rotation cycles (i.e., 8 years).  
Conservation practices and the sod-based rotation are designed primarily to 
improve soil through increases in SOC.  Soil organic carbon contributes to the 
stabilization of soil aggregates (Benjamin et al., 2008).  Tisdall and Oades (1982) found 
that organic bonding agents were the main binding agent for aggregates > 250 ?m in 
diameter.  Maintaining adequate SOC is crucial to improving soil physical properties 
(Reeves, 1994).  Reduced tillage, strip tillage, no tillage, and cover cropping are the most 
common techniques used alone or in combination to improve SOC; however, strip-tillage 
38 
 
is the most common technique used in this region (Wiatrak et al., 2007).  Residue 
management systems that increase soil coverage by plants and reduce incorporation of 
residues have the greatest impact on SOC (Havlin et al., 1990; Wood et al., 1991; 
Edwards et al., 1992). 
Typically, increases in SOC result in decreases in soil bulk density (Wilson et al., 
1982). This is due to the lower bulk density of SOC itself, but also improved soil 
structure.  Reeves (1994) found that the average bulk density in fields under conservation 
tillage were lower than conventionally tilled fields.  While the sod-based rotation has the 
potential to improve SOC, grazing of perennial grasses may reduce the effectiveness of 
SOC to reduce bulk density.  Franzluebbers and Struedemann (2010) found that grazing 
increased bulk density (1.46 vs. 1.42 g cm-3, grazed vs. ungrazed, respectively) in the top 
6 cm of soil. 
With a natural lack of SOC, coarse-textured surface soils do not retain water, and 
water stress for crops is reached within a few days (Elkins et al., 1977).  Irrigation to 
supplement rainfall is costly to rural growers.  The sod-based rotation with bahiagrass 
and other conservation methods have demonstrated increased soil water retention due to 
increases in SOC compared to traditional rotation and management practices (Reeves, 
1994; Ess et al., 1998; Raper et al., 2000).  Sigua et al. (2009) noted that rainfall on SOC 
promoted plant growth.  Studies in Texas show that using strip tillage and cover cropping 
reduced the amount of evapotranspiration in soil from the following cotton crop reducing 
the need to supplement rainfall with irrigation (Lascano et al., 1994).  
 Increases in SOC can improve infiltration rates (Wright et al., 2006) due to the 
role of SOC in soil structure and aggregation (Causarano et al., 2006).  Practices that 
39 
 
increase SOC result in more stable aggregation, improved soil structure, and lower bulk 
density.  This structural benefit usually increases the porosity, especially macroporosity, 
of the soil resulting in greater infiltration (Causarano et al., 2006).  Macropores are 
important as preferential pathways of water, air, and chemicals in the soil (Beven and 
Germann, 1982; Lin et al., 2005; Jarvis, 2007).   Also, with a decrease in erosion, the 
amount of nutrients that are carried away with the soil is lessened (Paxton et al., 1993). 
The overall objective of this study was to determine the effect of the sod-based 
rotation on soil physical properties, including infiltration, saturated hydraulic 
conductivity, bulk density, and porosity on Coastal Plain soils after two complete rotation 
cycles.  In addition, factors such as tillage, irrigation, and grazing were also evaluated.   
Methods and Materials 
Site Description 
 The study was conducted using four separate established experiments.  Two 
experiments utilized small 0.1 to 0.25 ha plots in a randomized block design and two 
experiments were large 20.2 to 60.1 ha fields divided into sections representing each 
phase of the rotation.  One of each type was located at the Wiregrass Research and 
Extension Center (WREC) in Headland, AL, and at the North Florida Research and 
Education Center (NFREC) in Quincy, FL, (small plot experiment) and Marianna, FL 
(large experiment).  All experiments had been established for approximately 8-10 years.  
All experiments were managed using irrigation, strip tillage, winter oat/rye cover 
cropping, unless otherwise noted as an additional secondary treatment in small plot 
experiments. 
40 
 
The small plot experiment at WREC included all phases of the sod-based rotation 
(bahia1-bahia2-peanut-cotton) and the traditional rotation (peanut-cotton) under 
irrigation.  In addition to the various rotation treatments, a secondary treatment of strip 
tillage or moldboard plow was also included.  Each phase of the rotation with tillage 
treatment was replicated 5 times; however, 3 of the 5 replications were randomly selected 
for sampling.   
The small plot experiment at NFREC also included all phases of the sod-based 
rotation, but the traditional rotation included two years of cotton instead of one (peanut-
cotton1-cotton2) under strip tillage. In addition to the rotation treatments, a secondary 
treatment of irrigation or non-irrigation was also included.  Plots were arranged in a 
randomized complete block split plot design with irrigation treatment split in the plots.  
All plots were sampled, but the 2nd year of cotton (cotton 2) treatment was excluded from 
data analysis to simplify statistical analysis with experiments without this treatment.  
The large experiment at WREC was a 20.2 ha field divided into 5 sections with 
each phase of the sod-based rotation and one section that alternated peanut and cotton as 
a control representative of the traditional rotation.  Cattle were allowed to graze the 2nd 
year of bahiagrass during the summer, and they were rotated in all sections during the 
winter as forage was available.  Within each section there were three sampling locations 
identified using Global Positioning Systems (GPS; MiTAC Digital Corp., Santa Clara, 
CA).  At each sampling location, the site was split into a caged area to assess soil 
properties not affected by cattle grazing and an adjacent grazed area to assess soil 
properties affected by cattle grazing.  Cattle exclusion cages were approximately 15 ? 15 
m and the grazed sampling area was approximately the same dimensions located 3 m to 
41 
 
the side of the caged area.  All sampling locations were under the irrigation pivot.  Cattle 
density was maintained at approximately 5.0 head ha-1 between 2008 and 2011.  
The large experiment at NFREC was a 60.1 ha field divided into 4 quadrants 
representing each phase of the sod-based rotation.  Cattle were allowed to graze on the 
2nd year of bahiagrass during the summer, and were rotated during the winter as forage 
was available.  Within each section there were three sampling locations identified using 
GPS.  Similarly to the large experiment at WREC, at each sampling location, the site was 
split into a caged area to assess soil properties not affected by cattle grazing and an 
adjacent grazed area to assess the soil properties affected by cattle grazing.  Cages were 
approximately 15 ? 15 m and the grazed area was approximately the same dimensions 
and located 3 m to the side of the caged area. All locations were under the irrigation 
pivot.  Cattle density was maintained at approximately 3.7 head ha-1 between 2008 and 
present.   
Sampling 
 For determination of macroporosity, soil cores were collected in triplicate in April 
and May 2010 before planting from selected plots and sampling locations described 
above for all experiments to a 60-cm depth using a 7.5 cm diameter Giddings Probe? 
(Giddings Machine Company, Windsor, CO) equipped with plastic liners.  Specific 
sampling locations were recorded using GPS.  A general horizon description (master 
horizon, subordinate, depth to boundary) was determined for each horizon in every core.  
Following horizonation and macropore analysis, composite samples were made from the 
triplicate cores taken from each plot or sampling location.  Samples were air dried and 
sieved through a 2-mm mesh screen for analysis of the 0-5, 5-10, 10-15, 15-30, and 30-60 
42 
 
cm depth increments.  These composite samples were used for pH, and SOC analyses.  
Separate sampling was performed for bulk density and SOC, which is described below. 
General Soil Characteristics 
Two composite samples were randomly selected from the small plot experiment 
at the WREC location and one from the small plot experiment at NFREC (i.e., Quincy) 
for texture and cation exchange capacity (CEC) determination.  Texture was determined 
using particle size fractionation as outlined by the Soil Survey Investigation Staff (2004). 
Cation exchange capacity was determined using the ammonium acetate at pH 7 method 
(Soil Survey Investigation Staff, 2004).  Soil series were identified using CEC, texture, 
and horizonation of the selected soil profiles from the small plot experiments at WREC 
and NFREC.  Identified soil series were consistent with those reported in the USDA-
NRCS Soil Survey Division, Web Soil Survey (Soil Survey Division, 2012) for these 
sites.  The predominate soil series at WREC is a Dothan loamy-sand (Appendix 1), while 
the soil at NFREC is an Orangeburg loamy-sand (Appendix 2). 
The pH was evaluated on all composite samples from each depth increment using 
a 2:1 water:soil ratio as outlined by the Soil Survey Investigation Staff (2004).  Data was 
averaged by depth and experiment.  General soil characteristics are reported in Table 1.  
Macroporosity  
Computerized tomography (CT) was used to evaluate macroporosity in collected 
soil cores, but before application to field samples, calibration cores were prepared to 
determine the effectiveness of the methodology and establish the grayscale values 
representing macropores on an area basis.  Triplicate artificial soil cores were prepared 
using the same plastic liners as the soil cores (7.5 cm diameter) to 35 cm length and filled 
43 
 
with either loam, loam mixed with 5% (v/v) peat, and 100% peat.  Artificial macropores 
were made using drinking straws (5.33 mm inner diameter), coffee stirrers (3.34 mm 
inner diameter), laboratory tubing (2 mm inner diameter), and capillary tubing (~1 mm 
inner diameter) with the ends sealed to prevent clogging.  Actual artificial macropore 
space was approximately 28.23 m2 in each scan and calculated using only the tubing with 
>1 mm diameter as this was the pixel size and detection limit of the scan.  The actual 
macroporosity is defined as the percentage of macropore area in the area of the scan.      
Calculated macroporosity of calibration cores was determined using computerized 
tomography (CT).  The CT scan was performed on 10 cores simultaneously using a GE 
Highspeed CT/i (GE, Cincinnati, OH) using a contrast of 2500 ? -125 cd m-2 at 120 kV 
and 120 mA.  Each CT scan was composed of individual scans taken 10 mm apart in an 
axial program with scanning every 2 seconds with a 46 cm field of view.  Scans were 
cropped by individual core.  From the 35 individual scans per calibration core, 5 scans 
were selected per core that displayed clear artificial macropores that were not distorted 
due to angles.  This was done to improve correlation between actual macroporosity and 
calculated macroporosity.   
A 0 to 255 grayscale was used to evaluate scans for macropore space using 
ERDAS Imagine? (Intergraph Corp., Cobham, UK), which ranges from black to white, 
respectively.  In order to differentiate organic material from macropores, the 100% peat 
treatment was used to identify the grayscale range for organic matter and macropores.  
Artificial macropores appearing in the 100% peat samples had values < 72 (Figure 1).  
Thus, macropores were defined as pixels with values < 72 with a minimum size of 1.1 
mm diameter, which was based on pixel size.  Other studies have used similar size 
44 
 
parameters for macropores stating that the size for a macropore is > 1 mm in diameter 
(Kim et al., 2010).  Macroporosity was defined as the percentage of pixels attributable to 
macropores (i.e., < 72) from the total pixel count of the image.  Macroporosity from the 
five selected scans was averaged for the three replicate cores from each core media 
treatment (e.g., loam, loam + 5% peat, and 100% peat) for a final macroporosity per soil 
treatment and final correction factor in macropore determination.   
For field soil core analysis of macroporosity by volume, two of three cores were 
randomly selected from each plot in each experiment for CT analysis, excluding damaged 
cores.  Tomographic analysis was similar to that performed on calibration cores.  
Individual CT scans (~60 per field core) were analyzed digitally from the surface to 60 
cm and analyzed for grayscale values < 72.  Percent macroporosity was averaged for all 
scans within a depth increment (e.g., 0-5, 5-10, 10-15, 15-30, 30-60 cm).  
Bulk Density and Soil Organic Carbon 
Sampling for bulk density and SOC measurements was performed in August 2010 
in the small plot experiments at WREC and NFREC that were strip-tilled and irrigated.  
Two samples per plot were taken at 0-5 and 5-10 cm depth increments using 7.5 cm rings 
with a known volume.  Samples were weighed then dried at 105?C.  Soil dry weight was 
determined, and the sample was ground and passed through a 2-mm sieve to determine 
coarse fragment weight.  Bulk density was determined by dividing the air-dried mass 
minus the coarse fragment mass from the soil volume (Soil Survey Investigation Staff, 
2004).  Composite samples were prepared from replicate bulk density samples and 
analyzed for SOC using a LECO-TruSpec (LECO Corp., St. Joseph, MI).  Using the 
same methodology, SOC was determined at each depth interval for soil cores collected 
45 
 
for macropore analysis.  The 0-5 and 5-10 cm depth increments for SOC analysis from 
August 2011 was compared with the values found in the macropore cores from April and 
May 2010.  No difference was found in the SOC values; therefore, only SOC collected in 
April and May 2010 are reported. 
Saturated Hydraulic Conductivity and Infiltration  
 Hydraulic conductivity of saturated soil was determined in the field using a 
constant head procedure (Amoozegar and Wilson, 1999).  Briefly, this method 
determines saturated soil hydraulic conductivity by inserting a constant-head soil 
permeameter into a borehole at a test depth.  The borehole was dug to a depth of 15 cm 
using a bucket auger.  The 15 cm test depth was used because that is the average depth of 
the compaction zone in the soil (Barley et al., 1965; Doty et al., 1975; Trouse and 
Reaves, 1980).  This test evaluated the hydraulic conductivity of saturated soil at the 
compaction zone interface.  Water was added to a calibrated reservoir and allowed to 
flow freely into the borehole until an equilibrium level was reached.  Water flowing into 
the permeameter was throttled by an ?adjustable bubble tube?.  Hydraulic conductivity of 
saturated soil is determined mathematically using the equilibrium height of water, rate of 
water flow, and dimension of the borehole.  Determination of saturated hydraulic 
conductivity was done by multiplying the A-coefficient (Equation 1) 
Equation 1     A = sinh-1(H/r) ? (r/H2) + (r/H)/2?H2 
by the steady-state rate of water flow from the permeameter into the auger hole.  Where 
H is the change in water height and r is the radius of the borehole.  The A-coefficient is 
unique to the size of the bore hole and the depth at which saturated hydraulic 
conductivity is being evaluated. 
46 
 
Infiltration rates were determined in the field using a sprinkle infiltrometer 
(Cornell University, Ithaca, NY) from the irrigated and strip-tilled treatments of the small 
plot experiments at WREC and NFREC.  Infiltration rates were measured by simulating 
rainfall in a single, 24-cm inner diameter ring.  This allows for a wide range of 
predetermined rainfall rates to be assessed; for this project, 0.007 cm s-1 was used.  The 
volume of water that was released and the time required for water to accumulate on the 
surface of the soil were recorded.  The runoff was then collected over 3 minute intervals 
until measurements were equilibrated.  Measurements were taken in the row and 
conducted in duplicate in each selected plot.  Infiltration rate was determined by 
subtracting the runoff volume from the total amount of water released by the reservoir.  
Due to weather constraints, infiltration was only assessed in the small plot experiment at 
WREC. 
Data Analysis 
 Data was analyzed using the SAS? program (SAS Institute Inc., Cary, NC).  The 
data was processed through statistical analysis tests using the GLIMMIX procedure as 
outlined in SAS? for Mixed Models, Second Edition (2006).  These analyses allow for 
comparison of the strip-tilled and plowed plots, irrigated and dry land plots, grazed and 
non-grazed, as well as the sod-based and traditional rotations using the cotton cropping 
sequences for analysis.  Differences among treatment groups were evaluated at ? = 0.05 
level. 
 
 
 
47 
 
Results 
Soil Organic Carbon 
Soil organic carbon from all experiments ranged from 1.2 to 19.0 g kg-1 and 
decreased with increasing depth at all locations as expected (Table 2; P < 0.0001).  
Within the 0-5 cm depth increment, average SOC was 8.4, 15.6, 17.4, and 9.1 g kg-1 in 
the WREC small plot, NFREC small plot, WREC large, and NFREC large experiments, 
respectively.  There were no differences due to cropping sequence or rotation within any 
experiment at this depth.   However, within a specific depth increment, SOC following 
bahiagrass was generally greater than from other crop sequences at all depths although 
crop sequence was rarely significant.  This trend was most pronounced in the large 
experiments, where the greatest SOC occurred following bahiagrass and the least SOC 
occurred following peanuts and cotton.  However, results were significant only in the 
WREC (large) experiment in the 10-15 (P = 0.0010) and 15-30 (P = 0.0033) cm depth 
increments; and only at the 30-60 cm depth at the WREC (small) were differences among 
cropping sequence observed (P = 0.0067), where SOC following bahiagrass and peanuts 
were greater than SOC following cotton.   
When cotton and peanut were compared by rotation in the small plot experiments, 
there was no difference in SOC due to the rotation at any depth increment (Table 3).  
There was also no difference between the overall sod-based rotation and the overall 
traditional rotation in the small plot experiments.   
Tillage method affected SOC in the small plot experiment at WREC.  Strip tillage 
yielded 5.82 g kg-1 greater SOC at 0-5 cm depth than the moldboard plow treatment 
(Table 4).  While the treatments were similar at 5-10 cm, the moldboard plow treatments 
48 
 
were 0.5 and 0.75 g kg-1 greater in SOC than strip-tilled treatments at the 10-15 and 
15-30 cm depth increments, respectively.  No interaction was observed between the 
tillage treatment and the cropping sequence.   
The secondary treatments of irrigation (NFREC small plot experiment) and 
grazing (WREC and NFREC large experiments) were not significant.  However, it is 
interesting to note that the non-grazed treatments were slightly higher in SOC than the 
grazed treatments at all depths, except 30-60 cm, in both large experiments.     
Macroporosity 
 Percent macroporosity evaluated using CT scans of artificial soil cores with 
constructed macropores was 0.4 and 0.5% of the total scan area for the loam and loam 
with 5% peat cores, respectively (Table 5).  This is 64 and 72% of the actual 
macroporosity determined using combined area of the artificial macropores > 1 mm in 
diameter.  While the loam with 5% had slightly greater calculated macroporosity, it did 
not differ from the loam without peat.  The 100% peat soil reported nearly 100% 
macroporosity.  Calculated macroporosity was relatively consistent with coefficient of 
variations, ranging from 0.0 in the OM soil to 0.2 in the loam with 5% OM. 
Macroporosity in field cores ranged from none to 1.1% over all experiments and 
depths evaluated (Table 6).  In the small plot experiment at WREC, macro-porosity 
decreased with depth.  At the surface (0-5 cm) macro-porosity ranged from 0.6 to 0.1%, 
while the 30-60 cm depth ranged from 0.0 to 0.1%.  Although cropping sequence and 
secondary treatment were not significant within a depth, the peanut and cotton cropping 
sequences of the traditional rotation and the cotton cropping sequence of the sod-based 
rotation had generally higher macroporosity than other cropping sequences in the 0-30 
49 
 
cm depth increments.  No difference between sod-based and traditional rotation was 
found. 
 It the NFREC small plot experiment, macroporosity ranged from 0.02 to 1.14%, 
and there was an effect of the cropping sequence of the rotation at each depth increment.  
Macroporosity following peanuts in the sod-based rotation had the highest percentage of 
macropore space at each depth increment.  In particular, macroporosity was greater in 
peanut in the sod-based rotation than in the traditional rotation; however, there was no 
difference in the cotton cropping sequence of the different rotations.   
 In the large experiments at WREC and NFREC, macroporosity ranged from 0.0 to 
1.1% and 0.0 to 0.3%, respectively.  No difference in macroporosity was found due to 
depth, secondary treatment, or cropping sequence of the rotation (Table 5).   
Bulk Density 
Within the small plot experiment at the WREC, bulk density at the surface 0-5 cm 
depth ranged between 1.01 g cm-3 in the 2nd year of bahiagrass and 1.46 g cm-3 in the 1st 
year of bahiagrass (Table 7); however, there was no difference among the cropping 
sequences (P = 0.2195).  Bulk density in the 5-10 cm depth increment was greater than 
that at the surface (P < 0.0001).  Bulk density ranged from 1.65 g cm-3 in the peanut 
phase of the sod-based rotation to 1.76 g cm-3 in the peanut phase of the traditional 
rotation at this depth, but it did not differ by cropping sequence (P = 0.6018). 
In the small plot experiment at the NFREC, bulk density at the surface 0-5 cm 
depth ranged between 1.17 g cm-3 in the 1st year of bahiagrass to 1.50 g cm-3 in the peanut 
cropping sequence of the traditional rotation (Table 7).  Bulk density did not differ 
among cropping sequence (P = 0.9906).  Bulk density was generally greater in the 5-10 
50 
 
cm depth increment than in the 0-5 cm depth (P = 0.0002), but did not differ with depth.  
Within the 5-10 cm depth increment, bulk density did not differ among the cropping 
sequences (P = 0.4308). 
Comparing the overall rotation systems, bulk density did not differ among the 
rotations in the 0-5 or 5-10 cm depth increments at either location. 
Hydraulic Conductivity of Saturated Soil and Infiltration 
For the small plot experiment at WREC, the hydraulic conductivity of saturated 
soil at 15 cm below the soil surface ranged from 1.49x10-3 cm s-1 in the peanuts of the 
traditional rotation to 6.43x10-4 cm s-1 in the 2nd year of bahiagrass in the sod-based 
rotation, but differences among cropping sequence were not significant (P = 0.2722) 
(Figure 2A).  In the small plot experiment at NFREC, the highest saturated hydraulic 
conductivity was found in the cotton cropping sequence of the traditional rotation 
(9.19x10-4 cm s-1), and the lowest was found in the peanut cropping sequence of the sod-
based rotation (4.28x10-4 cm s-1) (Figure 2B).  Differences at this location were also not 
significant (P = 0.1609).  In addition, there was also no difference between the overall 
rotation schemes at either location (P = 0.2947 at WREC and P = 0.1808 at NFREC).   
Infiltration rates ranged from 7.27x10-3 cm s-1 in the cotton cropping sequence in 
the traditional rotation to 4.31x10-3 cm s-1 in the peanut cropping sequence for the sod-
based rotation in the small plot experiment at WREC (data not shown).  The phase of the 
rotation was not significant (P = 0.2225) nor was the overall rotational scheme (P = 
0.9810).   
 
 
51 
 
Discussion 
Soil Organic Carbon 
The average SOC from all experiments was 12.5 g kg-1 and 8.1 g kg-1 at the 0-5 
and 5-10 cm depths, respectively.  Values are slightly higher than those found under 
conservation management practices at these depths (Terra et al., 2005; Siri-Pierto et al., 
2007; Causarano et al., 2008); however, slightly larger depth increments (Causarano et 
al., 2008; Terra et al., 2005) could account for lower SOC.   Lower SOC due to intensive 
tillage practices at 0-5 cm is consistent with other studies in this region (Terra et al., 
2005; Siri-Pierto et al., 2007; Causarano et al., 2008).   
The lack of effect from the crop rotation system on SOC was also noted by 
Katsvairo et al. (2009), who reported data from the NFREC small plot experiment 4 years 
following its establishment.  They reported an average of 9.8 g C kg-1 (1.56% soil organic 
matter) in the 0-15 cm depth increment. Because this average is most similar to the 10-15 
cm depth increment in the current study, results suggest that SOC has increased over the 
last 6 years regardless of the rotation or irrigation treatments.    
 Intensive tillage with the moldboard plow reduced SOC by approximately 50% 
(11.32 to 5.5 g kg-1) in the 0-5 cm depth increment.  Causarano et al. (2008) also found 
reduced SOC due to intensive tillage practices.  They found that SOC increased from 6.0 
g kg-1 under conventional tillage to 8.0 g kg-1 using minimal tillage conservation 
practices.  Concentration of SOC was relatively similar to the current study although 
cropping systems in the Causarano et al. (2008) study did not include a perennial grass, 
whereas this study did, but their study did include corn, soybean, cotton, peanut, and 
tobacco that had been under the management practices for well over 10 years.  
52 
 
 Also, cover crops increase C inputs into agricultural systems (Reeves, 1997; Kuo 
et al., 1997).  They would have contributed small but significant amounts of organic C to 
the soil which will improve soil quality.  In a study conducted by Kuo et al. (1997), rye 
contributed approximately 1 g kg-1 organic C to the surface (0-15 cm) soil over 10 years.  
Rye was able to produce between 144 and 248 g kg-1 of above ground biomass (Dabney 
et al., 2001).  Combinations of increased carbon inputs together with reductions in tillage 
are needed to maximize increases in soil organic carbon (Roberson et al., 1991; Wright et 
al., 1999). 
Macroporosity 
 Macroporosity assessed using CT scans of the calibration cores of loam and loam 
with 5% peat was 64-72% of the actual macroporosity.  However, analysis of the 100% 
peat treatments greatly overestimated macroporosity.  Macroporosity in this sample was 
nearly 100% of the total scan area.  This indicates that the grayscale criterion for 
macropores was not effective at separating organic material from macropore space 
because the density of the organic material is not high enough to lighten the background 
color above the 72 grayscale value assigned to the macropores.  While addition of 5% 
peat to the loam sample slightly increased the macroporosity, it was not a significant 
difference.  Thus, even though organic materials can interfere with macroporosity 
analysis as performed, it was not a factor for soils with less than 5% organic matter, 
which is < 2% SOC assuming 60% C in soil organic matter (Edwards et al., 1999).  
Analysis of macroporosity using CT of the field soils in this study is acceptable due to the 
< 2% SOC found in these soils.  For the loam samples, macroporosity measured by CT 
was approximately 30% by area less than the actual macropore content.  This is likely 
53 
 
due to the pixels at the edge of the macropores that are not sufficiently dark to be 
classified as macropores.  However, this difference was consistent among analyses and 
should be used as a correction factor. 
In the field soils, macroporosity (pore size ? 1.1 mm diameter) ranged from 0.0 to 
1.1% by area over all experiments and depths evaluated.  The small plot experiment at 
NFREC was the only location where differences between the various cropping sequences 
were found.  In this study, macroporosity following peanut was greater throughout the 
soil profile than following other crop phases.  In a study conducted by Kim et al. (2010), 
macroporosity between treatments was most pronounced in the surface 10 cm of soil, and 
differences dissipated by 20 cm.  Using CT scans and grayscale analysis, Kim et al. 
(2007) found 0.03% macroporosity in the surface to 10 cm of soil, 0.01% in the 10-20 cm 
depth increment, and none in the 20-30 cm depth increment.  These findings include the 
range found in this study; however, maximum macroporosity observed was up to 30x 
greater in the current study.  Several factors could account for these differences.  
Differences in cropping system and soil type are likely to impact macroporosity.  In the 
study by Kim et al. (2007), corn was planted for two years prior to sampling on a silt 
loam soil in Missouri.  Given poor structure of the soils, coarse textured soils, such as 
those in Alabama and Florida, have a larger number of macropores compared to the 
smaller particles in a finer soil.  Unfortunately, courser textured soils are less likely to 
hold together during sampling and transportation of soil cores.  Although care was taken 
to minimize core damage, the irregularly high macroporosity may be an artifact from 
handling.  However, it could also be due to irregularly distributed zones of macropores 
created by biota (e.g., root zones, earthworm burrows).  
54 
 
 The lack of difference in macroporosity between cropping sequence, rotation, and 
secondary treatment was unexpected.  Peanuts must be inverted at harvest and may have 
increased the amount of porosity at the surface of the soil at the time of sampling.  
However, much of the added porosity could have dissipated during the 6-7 months 
between peanut harvest and sample collection.  Differences between strip tillage and 
moldboard plow and grazed and non-grazed were expected.  The lack of difference 
among treatments could be explained by the consistent use of winter cover cropping.  
After 10 years in rotation, the SOC levels had few differences among the treatments, 
except for tillage.  Because SOC is likely the main factor driving differences in 
macroporosity, it is then not surprising that differences were not observed.  However, 
SOC under strip tillage was greater than moldboard plow treatments at the 0-5 depth and 
less at 10-15 and 15-10 cm depths.  Differences in macroporosity would be expected, but 
were not observed.  However, differences in SOC were rather small and may not be 
sufficient to see differences in macroporosity.    
Bulk Density 
 Bulk density in both small plot experiments differed by depth, but was not 
affected by phase of the rotation or overall rotation scheme.  Bulk density averaged 1.19 
and 1.33 g cm-3 in the 0-5 cm depth of the sod-based rotation at WREC and NFREC, 
respectively.  These values are below the 1.6 g cm-3 bulk density where root penetration, 
depending on the plant species and soil type, begins to be impacted (C.A.R.E.S., 2012).  
These values are lower, even considering the differences in depth increments, than those 
reported by Wilson et al. (1982), who found that bulk density for the 0-10 cm depth was 
1.49 g cm-3 when bahiagrass was used as a cover crop.  Bulk density in the traditional 
55 
 
rotation (1.24 and 1.44 g cm-3 in the 0-5 cm depth at WREC and NFREC, respectively) 
was the less than the 1.65 g cm-3 reported by Siri-Prieto et al. (2007) under a no-till 
peanut-cotton cropping system.  Franzluebbers and Stuedemann (2010) found the bulk 
density for the top 20 cm of a soil in Georgia to be 1.44 g cm-3 under pasture 
management, which is lower than that of the sod-based rotation.  This is not surprising as 
traffic from row crop production would be expected to increase bulk density.  
Saturated Hydraulic Conductivity and Infiltration 
 Saturated hydraulic conductivities were not found to differ in the small plot 
experiments at WREC and NFREC.  Benjamin et al. (2003) showed that the soil physical 
environment can influence crop productivity in a semiarid environment by influencing 
hydraulic properties of the soil.  He found saturated hydraulic conductivities of 3.00x10-4 
cm s-1 for conservation systems.  These values are similar to the values that were found in 
the strip-tilled plots at both small plot experiments at WREC and NFREC.  While the 
data from this study is consistent with Benjamin et al. (2003), the expected difference 
between sod-based and traditional rotations or the cropping sequences within the 
rotations was not found.  However, the lack of difference in hydraulic properties is 
supported by the lack of difference in SOC, macroporosity, and bulk density.  Each of 
these parameters has a strong influence on saturated hydraulic conductivity (Benjamin et 
al., 2008). 
In this study, cropping sequence and rotation were all expected to differ in 
infiltration, and neither did.  Katsvairo et al. (2007) measured the infiltration rate at 
3.05x10-2 cm s-1 in the sod-based rotation, while the traditional rotation had an infiltration 
of 5.17x10-3 cm s-1.  The data from the small plot experiment at WREC is consistent with 
56 
 
the traditional rotation measurements found by Katsvairo et al. (2007), but are much 
lower than the values they found for the sod-based rotation.  Differences in infiltration 
rates for sod-based and traditional rotations in the small plot experiment at WREC and 
those found by Katsvairo et al. (2007) were likely due to the amount of time the crops 
have been in rotation.  At the WREC small plots have been in rotation for approximately 
10 years, while those studied by Katsvairo et al. (2007) were within the first 4 years of 
the rotation.  The lack of difference in infiltration rates between the cropping sequences 
could be due to lack of differences in SOC.  Typically infiltration rates increase when 
SOC increases; this is to be expected through increased aggregation and improved soil 
structure (Benjamin et al., 2008).   
Conclusion 
 Initial studies in the sod-based rotation suggested that it may have the potential to 
increase SOC and its associated soil benefits beyond what traditional and conservation 
practices can achieve.  After 10 years in the sod-based rotation, SOC, macroporosity, 
bulk density, saturated hydraulic conductivity, and infiltration were evaluated and 
compared to the traditional peanut-cotton rotation managed with conservation practices.  
However, few differences were found.  The use of conservation management practices in 
both the traditional and sod-based rotations may have, over time, equalized with respect 
to SOC accumulation.  Because it is a key factor in forming aggregates and improving 
soil structure, it is not surprising that soil physical properties do not differ when SOC 
concentrations are similar among rotation systems studied.   While there are numerous 
benefits to the sod-based rotation, including disruption of disease and pest cycles and 
economic diversity, the benefits to SOC and its associated role in the physical properties 
57 
 
of soil were not evident when both systems were managed using strip tillage and cover 
cropping.   
58 
 
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Wright, S.F., J.L. Starr, and I.C. Paltineanu. 1999. Changes in aggregate stability and 
concentration of glomalin during tillage management transition. Soil Sci. Soc. 
Am. J. 63:1825-1829. 
Wright, D., J. Marois, T. Katsvairo, P. Wiatrak, and D. Hartzog. 2006. Perennial Grasses 
? A Key to Improving Conservation Tillage. p.p. 79-84. In: Proc. Southern 
Conservation Systems Conf. Amarillo, TX. June 26-28, 2006.  
  
65 
 
Table 1. Soil particle size distribution, texture, and mean pH for the small plot 
experiments at the Wiregrass Research and Extension Center (WREC) and the North 
Florida Research and Extension Center (NFREC).  The soil series at WREC was Dothan 
(Fine-loamy, kaolinitic, thermic Plinthic Kandiudult) and at NFREC was Orangeburg 
(Fine-loamy, kaolinitic, thermic Typic Kandiudult). 
?Sand, Silt and Clay = 0.5-2.0, 0.002-0.5, <0.002 mm particle size separates, respectively
Location Depth  Sand? Silt Clay Texture pH 
 
cm ????????????? % ????????????? 
  WREC 0 ? 5 83.15 11.48 5.37 Loamy Sand 5.3 
 
5 ? 10 83.58 8.96 7.46 Loamy Sand 5.2 
 
10 ? 15 83.32 11.31 5.37 Loamy Sand 5.1 
 
15 ? 30 77.12 11.25 11.64 Sandy Loam 5.3 
  30 ? 60 66.06 11.83 22.12 Sandy Loam 5.2 
       
Location Depth  Sand Silt + Clay Texture pH 
 cm ????????????? % ?????????????   
NFREC 0 ? 5 91.29 8.71 Loamy Sand 5.7 
 
5 ? 10 91.99 8.01 Loamy Sand 5.8 
 
10 ? 15 90.16 9.84 Loamy Sand 5.8 
 
15 ? 30 75.74 24.26 Sandy Clay Loam 5.6 
 
30 ? 60 63.43 36.57 Sandy Clay Loam 5.5 
66 
 
Table 2.  Soil organic carbon (SOC) by cropping sequence in the small plot and large experiments at the Wiregrass Research and 
Extension Center (WREC) and at the North Florida Research and Education Center (NFREC). 
Location Depth 
Bahia 1 
SBR? 
Bahia 2 
SBR 
Peanut 
SBR 
Cotton 
SBR 
Peanut 
TR 
Cotton 
TR? P-value 
 cm ??????????????????? g SOC kg-1 ???????????????????  
         
WREC (small) 0-5 9.23 9.02 7.61 7.90 8.59 8.13 0.3428 
 5-10 4.68 4.95 5.33 4.80 5.04 4.90 0.5441 
 10-15 4.86 4.83 4.49 4.46 4.12 4.46 0.4713 
 15-30 3.79 3.73 4.10 3.53 3.73 3.37 0.5933 
 30-60 1.50 ab? 1.81 a 1.80 a 1.30 b 1.80 a 1.43 b 0.0067 
NFREC (small) 0-5 17.43 13.98 16.14 16.03 14.93 14.99 0.5781 
 5-10 12.14 11.05 11.48 11.34 11.00 10.83 0.7153 
 10-15 9.46 8.67 8.90 9.53 9.23 9.40 0.9306 
 15-30 6.57 5.47 5.32 5.53 5.29 5.72 0.2368 
 30-60 2.11 2.15 1.78 2.00 2.05 1.74 0.5630 
NFREC (large) 0-5 10.24 12.61 5.10 8.64 - - 0.0791 
 5-10 9.41 12.92 4.91 6.71 - - 0.0633 
 10-15 8.01 9.55 3.96 4.33 - - 0.1227 
 15-30 6.69 7.83 2.85 3.29 - - 0.0580 
 30-60 1.20 2.73 1.23 0.88 - - 0.2447 
WREC (large) 0-5 19.00 18.76 16.66 15.18 - - 0.1592 
 5-10 11.15 9.43 9.32 8.55 - - 0.1659 
 10-15 7.47 b 9.50 a 6.10 c 6.14 bc - - 0.0010 
 15-30 5.47 a 6.11 a 5.11 a 3.60 b - - 0.0033 
 30-60 2.58 2.29 2.43 1.60 - - 0.2522 
? All crop sequence labels are for the 2009 growing season with sample collection prior to 2010 growing season; SBR = sod-based 
rotation (bahia1-bahia2-peanut-cotton), TR = traditional rotation (peanut-cotton, except in small plot experiment at NFREC which as 
peanut-cotton1-cotton2) 
? Letters denote significance at the ? = 0.05 level; significance calculated across crop sequence, each depth increment analyzed 
individually 
? The second year of cotton in the traditional rotation was omitted at the NFREC for statistical analysis
65
 
67 
 
Table 3. Soil organic carbon and bulk density in the 0-5 and 5-10 cm depth increments 
for each of the rotations in the small plot experiments at the Wiregrass Research and 
Extension Center (WREC) and the North Florida Research and Extension Center 
(NFREC). 
Location Depth Rotation SOC 
Bulk 
Density 
 
cm 
 
g kg-1 g cm-3 
WREC 0-5 SBR? 10.81 1.18 
 
0-5 TR 12.35 1.23 
 P-value  0.6822 0.9500 
 
5-10 SBR 6.50 1.68 
 
5-10 TR 5.74 1.74 
  P-value   0.6822 0.9471 
     NFREC 0-5 SBR 15.56 1.27 
 
0-5 TR 14.35 1.45 
 P-value  0.7315 0.6094 
 
5-10 SBR 12.25 1.64 
 
5-10 TR 11.10 1.66 
  P-value   0.7530 0.9894 
? SBR = sod-based rotation (bahia1-bahia2-peanut-cotton); TR = traditional rotation 
(peanut-cotton or peanut-cotton1-cotton2).  Cotton2 was omitted from NFREC data.
68 
 
Table 4.  Soil organic carbon (SOC) by secondary treatment and combined crop sequences in the small plot and large experiments 
conducted at the Wiregrass Research and Extension Center (WREC) and at the North Florida Research and Education Center 
(NFREC). 
Location Depth 
Moldboard 
Plow 
Strip 
Tillage Irrigated 
Non-
Irrigated Grazed 
Non-
grazed P-value 
 
cm ??????????????????????????? g SOC kg-1 ????????????????????????????  
        
 
WREC (Small) 0-5 5.50 b? 11.32 a - - - - <0.0001 
 
5-10 4.94 4.97 - - - - 0.8206 
 
10-15 4.91 a 4.16 b - - - - 0.0028 
 
15-30 3.96 a 3.45 b - - - - 0.0434 
 
30-60 1.60 1.62 - - - - 0.6003 
NFREC (Small) 0-5 - - 14.84 16.32 - - 0.1990 
 
5-10 - - 11.28 11.33 - - 0.9006 
 
10-15 - - 9.21 9.18 - - 0.9439 
 
15-30 - - 5.53 5.77 - - 0.4577 
 
30-60 - - 1.83 2.07 - - 0.3459 
NFREC (Large) 0-5 - - - - 8.10 10.20 0.2784 
 
5-10 - - - - 7.86 9.12 0.5300 
 
10-15 - - - - 5.35 7.58 0.2365 
 
15-30 - - - - 4.49 5.84 0.3392 
 
30-60 - - - - 1.54 1.48 0.9242 
WREC (Large) 0-5 - - - - 16.60 18.20 0.2423 
 
5-10 - - - - 8.96 10.26 0.1381 
 
10-15 - - - - 7.00 7.60 0.2288 
 
15-30 - - - - 4.97 5.18 0.6079 
 
30-60 - - - - 2.19 2.26 0.8475 
? Letters denote significance at the ? = 0.05 level; significance calculated across secondary treatments, each depth increment analyzed 
individually, and all crop sequences were combined.
67
 
69 
 
Table 5. Calculated macroporosity (pore size ? 1.1 mm diameter) by area in calibration 
cores determined by gray-scale analysis of computerized tomographic scans of a loam, 
loam with 5% added peat, and 100% peat with three added macropores.  
Soil Type Macro- Macroporosity Accuracy? 
 pores Calculated Actual Mean 
 
No. pixels % CV?  % 
Loam 24.2 0.44 ? 0.05 b? 0.11 0.69 64.2 ? 6.7 b 
Loam+5% peat 27.2 0.52 ? 0.11 b 0.21 0.69 75.8 ? 14.2 b 
100% peat 5333.8 98.74 ? 1.39 a 0.01 0.69 14309 ? 685 a 
? Accuracy is defined as the ratio of calculated to actual macroporosity x 100.   
? CV is the coefficient of variation, which is the ratio of the standard deviation to the 
mean. 
? Values are mean ? standard deviation.   Dissimilar letters within a column indicated 
significant differences at the ? = 0.05 level. 
 
70 
 
 Table 6. Calculated macroporosity by area (pore size ? 1.1 mm diameter) in field cores 
by cropping sequence and depth in the small plot and large experiments at the Wiregrass 
Research and Extension Center (WREC) and the North Florida Research and Extension 
Center (NFREC) using computerized tomography (CT) scans.  Calibration of the CT scan 
method for determination of macroporosity indicated approximately 30% less 
macropores than actually present.  Data has not been corrected to reflect this loss. 
Location Depth  
Bahia 1 
SBR? 
Bahia 2 
SBR 
Peanut 
SBR 
Cotton 
SBR 
Peanut   
TR 
Cotton    
TR? P-value 
 
cm ????????????????? % ????????????????? 
 WREC 
(small) 0-5 0.50? 0.09 0.21 0.56 0.43 0.58 0.5404 
 
5-10 0.10 0.05 0.33 0.37 0.44 0.38 0.7550 
 
10-15 0.02 0.00 0.10 0.07 0.30 0.25 0.5920 
 
15-30 0.01 0.01 0.06 0.01 0.09 0.09 0.5818 
 
30-60 0.11 0.01 0.07 0.04 0.04 0.03 0.5235 
NFREC 
(small) 0-5 0.14 b? 0.02 b 0.89 a 0.02 b 0.12 b 0.06 b 0.0201 
 
5-10 0.16 b 0.02 b 0.88 a 0.02 b 0.12 b 0.05 b 0.0141 
 
10-15 0.17 b 0.02 b 0.84 a 0.02 b 0.07 b 0.05 b 0.0226 
 
15-30 0.11 b 0.04 b 1.01 a 0.04 b 0.39 b 0.03 b 0.0060 
 
30-60 0.08 b 0.05 b 1.14 a 0.12 b 0.45 b 0.05 b 0.0019 
WREC 
(large) 0-5 0.03 0.15 0.03 0.37 - - 0.2940 
 
5-10 0.32 0.17 0.01 0.54 - - 0.3419 
 
10-15 0.06 0.10 0.00 0.50 - - 0.2125 
 
15-30 0.04 0.09 0.01 0.59 - - 0.1619 
 
30-60 0.16 0.03 0.00 0.26 - - 0.0780 
NFREC 
(large) 0-5 0.00 0.05 0.26 0.06 - - 0.5404 
 
5-10 0.04 0.00 0.09 0.03 - - 0.7576 
 
10-15 0.07 0.00 0.04 0.05 - - 0.8001 
 
15-30 0.07 0.00 0.00 0.04 - - 0.1095 
 
30-60 0.17 0.07 0.00 0.05 - - 0.4613 
? All crop sequence labels are for the 2009 growing season; SBR = sod-based rotation 
(bahia1-bahia2-peanut-cotton), TR = traditional rotation (peanut-cotton, except in small 
plot experiment at NFREC which as peanut-cotton1-cotton2) 
? Values are a mean of macropore area through the depth increment 
? Letters denote significance at the ? = 0.05 level; significance calculated across crop 
sequence, each depth increment analyzed individually 
?The second year of cotton in the traditional rotation was omitted at the NFREC for 
statistical analysis
71 
 
Table 7. Bulk density in the 0-5 and 5-10 cm depth increments for each of the crop 
sequence for the irrigated strip-tilled treatments in the small plot experiments at the 
Wiregrass Research and Extension Center (WREC) in Headland, AL, and the North 
Florida Research and Extension Center (NFREC) in Quincy, FL. 
Location 
Crop in 
2010 Rotation Depth Bulk Density 
   
cm g cm-3 
WREC Bahia 1? SBR? 0-5 1.46 
 
Bahia 2 SBR 0-5 1.01 
 
Peanut SBR 0-5 1.12 
 
Cotton SBR 0-5 1.13 
 
Peanut TR 0-5 1.17 
 
Cotton TR 0-5 1.30 
P-value   0.9737 
 
Bahia 1 SBR 5-10 1.69 
 
Bahia 2 SBR 5-10 1.69 
 
Peanut SBR 5-10 1.65 
 
Cotton SBR 5-10 1.69 
 
Peanut TR 5-10 1.76 
 
Cotton TR 5-10 1.72 
 P-value     0.3138 
     NFREC Bahia 1 SBR 0-5 1.17 
 
Bahia 2 SBR 0-5 1.21 
 
Peanut SBR 0-5 1.26 
 
Cotton SBR 0-5 1.46 
 
Peanut TR 0-5 1.49 
 
Cotton TR 0-5 1.39 
P-value   0.7807 
 
Bahia 1 SBR 5-10 1.67 
 
Bahia 2 SBR 5-10 1.66 
 
Peanut SBR 5-10 1.71 
 
Cotton SBR 5-10 1.51 
 
Peanut TR 5-10 1.62 
 
Cotton TR 5-10 1.70 
 P-value     0.6158 
? Bahia 1 is the 1st year of bahiagrass in the crop rotation and Bahia 2 is the 2nd year of 
bahiagrass in the rotation 
? SBR = sod-based rotation (bahia1-bahia2-peanut-cotton); TR = traditional rotation 
(peanut-cotton or peanut-cotton1-cotton2).  Cotton2 data was omitted.
72 
 
Figure 1. Example grayscale computerized tomography (CT) scans of calibration cores 
constructed with A) loam soil, B) loam soil with 5% peat, and C) 100% peat that were 
used to compare macroporosity calculated using CT analysis with actual macroposity. 
Arrows indicate constructed macropores with grayscale values < 72.  Macroporosity is 
defined as pore sizes ?1.1 mm in diameter. 
 
 
A) 
B) 
C) 
73 
 
Figure 2. Mean hydraulic conductivity of saturated soil (Ksat) at 15 cm below soil 
surface for each of the cropping sequences that were strip-tilled and irrigated in the small 
plot experiments at A) the Wiregrass Research and Extension Center (WREC) and B) the 
North Florida Research and Extension Center (NFREC).  Significance letters indicate 
differences by cropping sequence at ?=0.05; SBR = sod-based rotation (bahia1-bahia2-
peanut-cotton); TR = traditional rotation (peanut-cotton or peanut-cotton1-cotton2). 
Cotton2 data is not shown.  Black bars indicate crop sequences in the SBR and white bars 
indicate crop sequences in the TR.  
0.00 
0.20 
0.40 
0.60 
0.80 
1.00 
1.20 
1.40 
1.60 
M
ean
 K
sat
 (c
m 
s-1
 x 
1000)
 
0.00 
0.20 
0.40 
0.60 
0.80 
1.00 
1.20 
1.40 
1.60 
M
ean
 K
sat
 (c
m 
s-1
  x
 1000)
 
(A) 
(B) 
Bahia 1 
SBR 
Bahia 2 
SBR 
Peanut 
SBR 
Cotton 
SBR 
Peanut 
TR 
Cotton 
TR 
74 
 
 
 
 
 
 
III. Effects of Perennial Grasses Added to a Peanut-Cotton Rotation on Soil 
Chemical Properties 
ABSTRACT 
The conventional tillage systems that have been traditionally applied to the 
commonly used peanut-cotton rotation have degraded the soil organic carbon (SOC) 
contents leaving the soils with a low cation exchange capacity (CEC) and thus a low 
concentration of nutrients being retained in the soil.  To help alleviate these problems 
associated with the traditional rotation and conventional tillage systems, along with 
conservation tillage methods, implementing a forage grass, such as bahiagrass, into the 
rotation (sod-based rotation) has been suggested.  The objective of this study was to 
evaluate the effect of the sod-based rotation on SOC and nutrient concentrations as 
compared with the traditional rotation under multiple different treatments.  Long-term 
(~10 years) sod-based rotations were sampled to a depth of 60 cm and divided into 5 
depth increments for analysis.  Analysis was performed to compare effects of 
management systems, irrigation, grazing, and the sod-based vs traditional rotations at the 
Wiregrass Research and Extension Center (WREC) in Headland, AL (small plot and 
large plot experiments), and the North Florida Research and Education Center (NFREC) 
in Quincy, FL (small plot experiment) and Marianna, FL (large plot experiment).  Soil 
organic C ranged from 0.88 to 19.00 g kg-1 in all samples.  Soil organic C decreased with 
increasing depth at all locations and differed by cropping sequence at the 30-60 cm depth 
at the small plot experiment at the WREC location with the 2nd year of bahiagrass having 
75 
 
the highest amount of SOC.  At the WREC small plot experiment, SOC in the 0-5 cm 
depth was greater in conservation tillage systems than the conventional tillage systems 
regardless of the whether the rotation was sod-based or traditional.  Carbon isotopic 
analysis showed two years of bahiagrass contributed 36.5% of the SOC, but after a year 
of peanut and a year of cotton the contribution of bahiagrass dropped to 16.5% indicating 
that this pool of carbon was relatively labile.  Nutrients were largely unaffected by 
rotation and tillage management, except for phosphorus and nitrogen which differed 
among the crop phases due to fertilization of cotton and cover crops.  Consistency in 
SOC between the sod-based rotation and traditional rotation under conservation practices 
after ~10 years suggests that perennial grasses do not increase the carbon sequestration 
potential in Coastal Plain soils beyond the ability of conservation practices after 10 years. 
Introduction 
The agriculture in southern Alabama and Georgia and northern Florida is 
dominated by peanut and cotton production.  These crops are traditionally rotated year-
to-year.  The soils in this area tend to be coarse-textured, weakly structured, highly 
weathered, erodible, and carbon-depleted with poor water retention (Simoes et al., 2009; 
Campbell et al., 1974).  In addition, the soils typically have a root restricting zone at the 
15 cm depth (Barley et al., 1965; Doty et al., 1975; Trouse and Reaves, 1980).  While the 
soil structure is ideal for peanut production, the conventional tillage methods typically 
used in these sandy soils contribute to erosion (Reeves, 1994) and decrease nutrient 
cycling (Tivy, 1987), cation exchange capacity (CEC) (Fesha, 2004), and soil pH 
(Katsvairo et al., 2007) resulting in a loss of economic and environmental sustainability. 
76 
 
 Much of the decline in soil quality is due to the loss of soil organic matter from 
the intensive cotton-peanut production systems.  Soil organic carbon (SOC) has high 
nutrient- and water-holding capacities and reduces erosion by improving aggregation and 
soil structure (Reeves, 1997).  Conservation tillage practices, such as cover cropping, no 
tillage, and strip tillage, are designed to increase organic residues at the surface and 
organic carbon in the soil.  In this region, conventional tillage methods are slowly being 
replaced by conservation practices in order to capitalize on the benefits of added carbon 
(Johnson et al., 2001).  Currently, more than 50% of the cotton and peanut production in 
this region utilize one or more conservation tillage practice (CTIC, 2005), primarily cover 
cropping and strip-tillage (Wiatrak et al., 2007).  However, conservation practices may 
not be sufficient to maximize SOC to levels that provide the greatest benefit to 
production and environmental sustainability.   
 Incorporating perennial grasses into the traditional peanut-cotton rotation has 
been suggested as another mechanism to improve SOC and thus the economic and 
environmental sustainability of peanut and cotton production.  Many perennial grasses 
are well known for their ability to contribute to SOC due to their high above- and below-
ground biomass that increases surface residue, reduces soil disturbance, and improves 
SOC (Paustian et al., 1997).  Specialized management practices such as rotated grazing 
(Conant et al., 2001) have also shown to improve SOC (Paustian et al., 1997).   
In the southeastern Coastal Plain, bahiagrass is a perennial forage grass that is 
suited for soils with low fertility (Magness et al., 1971).  Addition of two years of 
bahiagrass into the peanut-cotton rotation has shown to increase SOC (Wright et al., 
2006), especially with the use of conservation practices (Reeves, 1994).  This rotation is 
77 
 
sometimes called the sod-based rotation (Katsvairo et al., 2007).  The extensive root 
system of bahiagrass (Blue and Graetz, 1977; Impithuksa and Blue, 1978) has been 
shown to reach below the compaction zone allowing the roots of subsequent crops to 
explore a larger soil volume for nutrients and moisture (Katsvairo et al., 2007).  Wilson et 
al. (1982) showed that 2 years in bahiagrass increased residue at the surface and 
increased mean SOC by 0.35% (w/w).   
Soil organic carbon influences chemical properties associated with the soil.  Due 
to the numerous functional groups found in organic matter, increases in SOC increase 
CEC of a soil (Fesha, 2004).  The increase in SOC after 2 years in bahiagrass resulted in 
increased exchangeable Ca by 490 mg kg-1 and exchangeable Mg by 79 mg kg-1 within 
two years (Wilson et al., 1982).  Potassium status following perennial grass production 
has also been seen to improve (Wilson et al., 1982) because many grasses are able to 
extract K from sub-surface horizons and recycle it to the surface (Juo and Lal, 1977) thus 
improving nutrient cycling in excess of fallow fields (Wagger, 1989). 
Nitrogen is also influenced by SOC.  Numerous studies have shown that legumes, 
such as clover, can immediately increase available N in soils when left as residue, due to 
their rapid breakdown and release of N (McVay et al., 1989; Holderbaum et al., 1990; 
and Vyn et al., 2000).  Allen et al. (2006) found that soil organic N increased by 5.7% per 
year and SOC increased by 26% over six years due to legume residue left in the field.  
However, a study conducted by Meso et al. (2010) showed that there was not a 
significant increase in N when peanut residue was left in the field. 
Stable C isotopic ratios have been used in SOC studies to trace the source of 
vegetative components in SOC (Flessa et al., 2000; Bronson et al., 2005; Haile et al., 
78 
 
2010).  Carbon from plants using the C4 carbon fixation mechanism can be distinguished 
from carbon from plants using the C3 carbon fixation mechanism due to the greater 
discrimination against 13C by C3 plants.  The delta 13C (?13C) values typically range from 
-9 to -19? for C 4 plants and from -20 to -35? for C 3 plants (Haile et al., 2010).  In a 37-
year rye-maize rotation system, maize, which is a C4 plant, contributed to SOC up to 20 
cm depth and accounted for 15% of the SOC in the Ap horizon (Flessa et al., 2000).   
Bronson et al. (2005) found that the contribution of carbon from C4 species in particulate 
organic matter (0-30 cm depth) was 59% in native grasslands and conservation reserve 
program lands (predominantly C4 species) compared to 35% in cropland soils dominated 
by cotton, rye, and wheat (predominantly C3 species).   
The sod-based rotation, coupled with conservation management practices, has the 
potential to improve carbon sequestration, which can improve SOC; however, the effects 
of the rotation more than a few years following establishment are not demonstrated.  The 
objective of this study was to evaluate the long-term effect (> 10 years) of the sod-based 
rotation on SOC and nutrient distributions in the soil profile.  Management effects of 
irrigation, grazing, and tillage (i.e., strip-tillage vs conventional moldboard plowing) 
were also evaluated.     
Materials and Methods 
Site Description 
 The study was conducted using four separate established experiments.  Two 
experiments utilized small 0.1 to 0.25 ha plots in a randomized block design and two 
were large experiments of 20.2 and 60.1 ha that are divided into sections representing 
each phase of the rotation.  Both small plot and large experiments were located at the 
79 
 
Wiregrass Research and Extension Center (WREC) in Headland, AL, and at the North 
Florida Research and Education Center (NFREC) in Quincy, FL, (small plot experiment) 
and Marianna, FL (large experiment).  All experiments had been established for 8-10 
years.  All experiments were managed using irrigation and strip tillage with a winter 
oat/rye cover crop, unless otherwise noted as an additional secondary treatment. 
The small plot experiment at WREC included all phases of the sod-based rotation 
(bahia1-bahia2-peanut-cotton) and the traditional rotation (peanut-cotton) under 
irrigation.  In addition to the various rotation treatments, a secondary treatment of strip 
tillage or moldboard plow was also included.  Each phase of the rotation with tillage 
treatment was replicated 5 times; however, only 3 of the 5 replications were randomly 
selected for sampling.  
The small plot experiment at NFREC also included all phases of the sod-based 
rotation, but the traditional rotation included two years of cotton instead of one (peanut-
cotton1-cotton2) under strip tillage. In addition to the rotation treatments, a secondary 
treatment of irrigation or non-irrigation was also included.  Each phase of the rotations 
were arranged in a randomized complete block split plot design with irrigation treatment 
split in the plots.  All plots were sampled, but the 2nd year cotton treatment was excluded 
from data analysis to make statistical analysis similar.   
The 20.2 ha large experiment at WREC was divided into 5 sections with each 
phase of the sod-based rotation and one section that represented the traditional rotation, 
which alternated peanut and cotton.  Cattle were allowed to graze the 2nd year of 
bahiagrass during the summer, and they were rotated in all sections during the winter as 
forage was available.  Within each section there were three sampling locations identified 
80 
 
using Global Positioning Systems (GPS; MiTAC Digital Corp., Santa Clara, CA).  At 
each sampling location, the site was divided into grazed and non-grazed sampling 
locations.  Cattle exclusion cages were approximately 15 ? 15 m and located within 3 m 
of the adjacent grazed sampling area (15 ? 15 m).  All sampling locations were under the 
irrigation pivot.  Cattle density was maintained at approximately 5.0 head ha-1 between 
2008 and 2010.  
The 60.1 ha large experiment at NFREC was divided into 4 quadrants 
representing each phase of the sod-based rotation.  Cattle were allowed to graze on the 
2nd year of bahiagrass during the summer and were rotated during the winter in all 
quadrants as forage was available.  Similar to the large experiment at WREC, there were 
three sampling locations per quadrant identified using GPS.  Unlike WREC, one 
sampling location per quadrant was located outside the irrigation pivot.  This sampling 
location was omitted due to possible confounding effect of irrigation practice.  To 
supplement the two sampling locations per quadrant, an additional grazed sampling 
location was selected inside the irrigation pivot.  The corners and sampling locations 
within this 15 x 15 m area were recorded to ensure reproducibility.  Thus, there were 
three grazed sampling locations per quadrant and two non-grazed sampling locations. 
Cattle density was maintained at approximately 3.7 head ha-1 from 2008 to the present.   
Sampling 
 Soil cores were collected in triplicate during April and May 2010 before planting 
from selected plots and sampling locations described above for all experiments to a 60-
cm depth using a 7.5 cm diameter Giddings Probe? (Giddings Machine Company, 
Windsor, CO) equipped with plastic liners.  Specific sampling locations were recorded 
81 
 
using GPS.  Following horizonation, composite samples were prepared by combining the 
triplicate cores taken from each plot or sampling location at 0-5, 5-10, 10-15, 15-30, and 
30-60 cm depth increments.  Samples were air dried and sieved through a 2-mm mesh 
screen for analysis.   
General Soil Characteristics 
A general horizon description (master horizon, subordinate, depth to boundary) 
was determined for each horizon in every core.  Two sets of composite samples, all depth 
increments for selected samples, were randomly selected from the small plot experiment 
at the WREC location and one from the small plot experiment at NFREC (i.e., Quincy) to 
have texture and CEC determined.  Texture was determined using established procedures 
as outlined by the Soil Survey Investigation Staff (2004).  Cation exchange capacity was 
determined using the ammonium acetate at pH 7 method (Soil Survey Investigation Staff, 
2004).  Predominate soil series were determined using CEC, texture, horizonation, and 
the USDA-NRCS Soil Survey Division, Official Soil Series Descriptions (USDA-NRCS 
Soil Survey Division, 2011) for the WREC and NFREC locations and were in agreement 
with the findings of the USDA-NRCS Web Soil Survey (Soil Survey Staff, 2012).  The 
predominate soil series at WREC is a Dothan loamy-sand (Appendix 1) and the 
predominate soil series at NFREC is an Orangeburg loamy-sand (Appendix 2).  The pH 
was evaluated on all composite samples from each depth increment using a 2:1 water:soil 
ratio as outlined by the Soil Survey Investigation Staff (2004).  Data was averaged by 
depth and experiment.  General soil characteristics are reported in Table 8.  
 
 
82 
 
Soil Organic Carbon and Carbon Isotopic Analysis 
 Soil organic carbon (SOC) analysis of composite samples from each depth 
increment was determined using a LECO-TruSpec? (LECO Corp., St. Joseph, MI).  
Analysis of ?13C of samples from the WREC and NFREC small plot experiments at the 
0-5 cm depth (only strip-tilled and irrigated plots) was performed by the Stable Isotope 
Facility at the University of California at Davis using a PDZ Europa ANCA-GSL 
elemental analyzer interfaced with a PDZ Europa 20-20 isotope ratio mass spectrometer 
(Sercon Ltd., Cheshire, UK). 
 The ?13C value represents the isotopic signature and is reported as the parts per 
thousand (per mil, ?).  It reflects the difference between the ratio of 13C/12C of the 
sample of interest and an internationally accepted standard (Equation 1).   
Equation 1      000
t an
12
13
12
13
13 1 0 0 01
dards
s a m p l e
C
C
C
C
C  
The standard for ?13C is Pee Dee Belemnite (or PDB), which is a carbonite fossil from 
South Carolina.  The ?13C value is higher for C4 plants compared to C3 plants due to the 
difference in carbon assimilation pathways.  Plants with the C3 pathway (e.g., cotton, 
peanut, oat, and rye) discriminate against 13C more than C4 plants (e.g., bahiagrass).  The 
?13C value can then be used to calculate the contribution of carbon by C4 and C3 plants 
(Equation 2 and 3).  Reference ?13C values of -25.8? for peanut (Hubick et al., 1986; 
1988), -26.4? for cotton (Tsialtas et al., 2008), and -27.2? for rye (Nii -Annang et al., 
2009) were averaged to represent the C3 plants yielding -26.5? for ? 13C3.  The reference 
?13C value for bahiagrass was -13.1? for ? 13C4 (Haile et al., 2010).   
83 
 
Equation 2      %1 0 0%
313413
313134 CC CCC s a m p l e 
Equation 3      43 %%100% CC  
Nutrient Analysis 
Calcium, K, Mg, Na, and P were extracted from each composite sample using the 
Mehlich-I or double acid extract, which is a mixture of 0.05 N hydrochloric acid and 
0.025 N sulfuric acid (Mehlich, 1953).  Extracted nutrients were quantified using 
inductively coupled plasma (ICP) spectroscopy (Spectro Ciros ICP, SPECTRO 
Analytical Instruments, Kleve, Deutschland). 
NO3-N and NH4-N Analysis 
 Nitrogen from nitrate (NO3-) and ammonium (NH4+) was determined in composite 
samples from 0-5 and 5-10 cm depths using the method of Sims et al. (1995).  In this 
procedure, the sample is prepared by shaking 5 g of soil and 25 mL of 2 M KCl for 30 
min followed by filtering through Whatman #42 filter paper.  Filtrate is then placed into a 
microplate, and a mixture of citrate (5 g L-1 of trisodium citrate with 2 g L-1 of sodium 
hydroxide), salicylate-nitroprusside (7.813 g L-1 of sodium salicylate and 0.126 g L-1 of 
sodium nitroprusside), hypochlorite (1 g L-1 of sodium (tribasic) phosphate, 2 mL of 2 M 
sodium hydroxide, and 10 mL of commercial bleach), and 2 M KCl is added and allowed 
to develop for 30 min.  The NH4+-N is analyzed using a spectrophotometer equipped with 
a microplate reader (Bio Tek FLx800, Bio Tek Instruments Inc., Winooski, VT) at 695 
nm.  The NO3- is then converted to NH4+ in the microplate with Devarda?s alloy and 
reanalyzed for total organic nitrogen (TON) (i.e., NO3--N plus NH4+-N).  The NO3-N 
concentration was determined by difference.     
84 
 
Data Analysis 
 Data was analyzed using SAS? (SAS Institute Inc., Cary, NC).  The data was 
processed using the GLIMMIX procedure in reference to Littell et al. (2006).  Analyses 
allowed for comparison of the strip tilled and plowed, irrigated and non-irrigated, grazed 
and non-grazed, and the sod-based and traditional rotation treatments with the cropping 
sequence.  Differences among treatment groups were evaluated at ? = 0.05 level. 
Results 
Soil Organic Carbon and Carbon Isotopic Analysis 
 Soil organic carbon from all experiments ranged from 1.20 to 19.00 g kg-1 and 
decreased with increasing depth at all locations as expected (P < 0.0001).  Within the 0-5 
cm depth increment, average SOC was 8.4, 15.6, 17.4, and 9.1 g kg-1 in the WREC small 
plot, NFREC small plot, WREC large, and NFREC large experiments, respectively.  
There were no differences due to cropping sequence or rotation within any experiment at 
this depth.   However, within a specific depth increment, SOC following bahiagrass was 
generally greater than from other crop sequences at all depths although crop sequence 
was rarely significant (Table 9).  This trend was most pronounced in the large 
experiments, where the greatest SOC occurred following bahiagrass and the least SOC 
occurred following peanuts and cotton.  However, results were significant only in the 
WREC (large) experiment in the 10-15 (P = 0.0010) and 15-30 (P = 0.0033) cm depth 
increments; and only at the 30-60 cm depth at the WREC (small) were differences among 
cropping sequence observed (P = 0.0067), where SOC following bahiagrass and peanuts 
were greater than SOC following cotton.   
85 
 
When cotton and peanut were compared by rotation in the small plot experiments, 
there was no difference in SOC due to the rotation at any depth increment.  There was 
also no difference between the overall sod-based rotation and the overall traditional 
rotation in the small plot experiments.   
Tillage method affected SOC in the small plot experiment at WREC.  Strip tillage 
yielded 2x greater SOC at 0-5 cm depth than the moldboard plow treatment (Table 10).  
While the treatments were similar at 5-10 cm, the moldboard plow treatments were 
greater in SOC than strip-tilled treatments at the 10-15 and 15-30 cm depth increments, 
but overall differences were < 20%.  No interaction was observed between the tillage 
treatment and the cropping sequence.   
The secondary treatments of irrigation (NFREC small plot experiment) and 
grazing (WREC and NFREC large experiments) were not significant.  However, it is 
interesting to note that the non-grazed treatments were slightly higher in SOC than the 
grazed treatments at all depths, except 30-60 cm, in both large experiments.   
 Delta 13C values differed by cropping sequence in the 0-5 cm depth (P < 0.0001) 
(Table 11).  The ?13C for cotton and peanuts in the traditional rotation were 2.6 to 5.3? 
lower than all sequences of the sod-based rotation.  Cotton in both rotation systems had 
the lowest ?13C values in their respective rotations.  The C4 bahiagrass in the sod-based 
rotation contributed 19.0-37.5% of the SOC found in the soil, which was maximized 
following the 2nd year of bahiagrass and minimized following cotton. 
Nutrient Analysis   
Calcium, K, Mg, Na, and P at all locations differed by depth, but there was no 
effect of cropping sequence, except with Mg (WREC small plot experiment) and P 
86 
 
(WREC and NFREC large experiments), or secondary treatment in any of the 
experiments.  Typically, concentrations of Ca, K, Mg, and P were highest at the surface 
decreasing with depth, while Na appeared to be slightly irregular at 10-15 cm depth 
(Table 12).   
Magnesium in the small plot experiment at the WREC location differed by 
cropping sequence at the 30-60 cm depth increment (Table 13).  The cotton grown in the 
traditional rotation was higher in Mg than all other cropping sequences except cotton 
grown in the sod-based rotation at this depth.  Magnesium concentrations also differed by 
the secondary tillage treatment at this location.  The strip-tilled treatment had higher Mg 
concentrations (43.60 mg kg-1) than the moldboard plowed treatment (36.26 mg kg-1).  
There was also an interaction of depth with the tillage secondary treatment and depth 
with cropping sequence. 
At both large plot experiments, P differed by cropping sequence within the sod-
based rotation (Table 13).  The highest concentration of Mehlich-I extractable soil P in 
the NFREC large experiment was following cotton with 67.55 mg kg-1 at the 0-5 cm 
depth.  Significantly greater P in cotton was also measured in the 15-30 cm depth 
increment.  While cropping sequence did not differ significantly in the other depth 
increments, P concentrations following cotton were slightly higher than following other 
crops.  At the WREC large plot experiment, a similar trend was observed.  Cropping 
sequence affected P concentration in all depths, except the 30-60 cm depth increment.  
Phosphorus concentrations following cotton were generally higher than other crops at the 
top three surface depths.  The P concentrations following the 1st year of bahiagrass were 
87 
 
lower than cotton in all depth increments to 30 cm, and they were lower than all other 
cropping sequences except at the 5-10 cm depth increment.   
Nitrate-N and Ammonium-N Analysis 
Both NO3-N and NH4-N differed by cropping sequence and by depth.  In the 
small plot experiment at the WREC location, the highest concentration of NO3-N and 
NH4-N was in the 0-5 cm depth increment from the cotton phase of the traditional 
rotation (Table 14).  At this depth, the 1st year of bahiagrass had generally the lowest 
NO3-N and NH4-N, although they did not differ significantly from other cropping 
sequences, except cotton from the traditional rotation.      
In the small plot experiment at NFREC, the highest concentration of NO3-N was 
in the 2nd year of bahiagrass in the sod-based rotation at 0-5 and 5-10 cm depths (Table 
14).  The lowest concentrations of NO3-N were in the peanut and cotton phases of the 
traditional rotation.  These values were 4 to 9 times lower than those following the 2nd 
year of bahiagrass.  Concentrations of NH4-N did not differ by cropping sequence at 
either depth.  
In both large experiments, there was no difference in NO3-N concentration among 
the bahiagrass and peanut phases of the sod-based rotation at 0-5 and 5-10 cm depths 
(Table 14).  However, at the 0-5 cm depth, the NO3-N concentration was greater 
following the cotton phase than all other phases at NFREC and following the 1st year of 
bahiagrass at WREC.  At NFREC, the same differences among cropping sequence were 
also seen at the 5-10 cm depth.   There was no difference in NH4-N due to cropping 
sequence in either experiment.   
88 
 
 In all experiments, NO3-N and NH4-N differed by depth.  Both NO3-N and NH4-
N concentrations were, typically, higher in the 0-5 cm depth than in the 5-10 cm depth.  
The WREC large plot experiment had the highest NO3-N concentration at 72.59 mg kg-1 
in the 0-5cm depth and 27.34 mg kg-1 in the 5-10 cm depth.   
Discussion 
Soil Organic Carbon and Carbon Isotopic Analysis 
 The average SOC from all experiments was 12.5 and 8.1 g kg-1 at the 0-5 and 5-
10 cm depths, respectively.  Values are slightly higher than those found under 
conservation management practices at these depths (Terra et al., 2005; Siri-Pierto et al., 
2007; Causarano et al., 2008); however, slightly larger depth increments (Causarano et 
al., 2008; Terra et al., 2005) could account for lower SOC.   Lower SOC due to intensive 
tillage practices at 0-5 cm is consistent with other studies in this region (Terra et al., 
2005; Siri-Pierto et al., 2007; Causarano et al., 2008).   
The lack of effect from the crop rotation system on SOC was also noted by 
Katsvairo et al. (2009), who reported data from the NFREC small plot experiment 4 years 
following its establishment.  They reported an average of 9.8 g C kg-1 (1.56% soil organic 
matter) in the 0-15 cm depth increment. Because this average is most similar to the 10-15 
cm depth increment in the current study, results suggest that SOC has increased over the 
last 6 years regardless of the rotation or irrigation treatments.    
 Intensive tillage with the moldboard plow reduced SOC by approximately 50% 
(11.32 to 5.5 g kg-1) in the 0-5 cm depth increment as compared to the strip-tilled 
treatment.  Causarano et al. (2008) also found reduced SOC due to intensive tillage 
practices.  They found that SOC increased from 6.0 g kg-1 under conventional tillage to 
89 
 
8.0 g kg-1 using minimal tillage conservation practices.  Concentration of SOC was 
relatively similar to the current study although cropping systems in the Causarano et al. 
(2008) study did not include a perennial grass, but did include corn, soybean, cotton, 
peanut, and tobacco that had been under the management practices for well over 10 years.  
Bahiagrass was able to contribute up to 37.5% of the SOC after two years; 
however, in subsequent years under peanut and cotton its contribution declined.  After the 
cotton phase, or 2 years following bahiagrass, only 19% of SOC was attributable to 
bahiagrass.  Haile et al. (2010) was also able to distinguish carbon attributed to 
bahiagrass from that supplied by trees in a silvopasture system.  The contribution of SOC 
contributed by C4 plants in the silvopasture system was found to be between 25 and 32% 
(Haile et al., 2010).  This value is slightly lower than the percentage found in this study; 
however, most silvopasture systems include both C3 and C4 plants simultaneously, which 
may reduce the impact of the C4 contribution.  Studies conducted by Puget et al. (1995), 
Flessa et al. (2000), and Christensen et al. (2011) evaluated the percent carbon due to 
maize under long-term cultivation.  The contribution of maize to SOC was 11 and 44% 
after 6 and 23 years in a silty soil (Puget et al., 1995), while it was only 15% after 37 
years in a very sandy soil (Flessa et al., 2000) and 14-16 years in a clayey soil 
(Christensen et al., 2011).  However, inputs of maize-derived carbon were likely much 
lower than that attributable by perennial bahiagrass due to shorter growth cycle and 
harvesting of maize in these studies.  In addition, maize stubble was plowed to a 25 cm 
depth each year (Flessa et al., 2000; Christensen et al., 2011), which would likely 
encourage SOC decomposition.   
90 
 
Also, cover crops increase C inputs into agricultural systems (Reeves, 1997; Kuo 
et al., 1997).  They would have contributed small but significant amounts of organic C to 
the soil which will improve soil quality.  In a study conducted by Kuo et al. (1997), rye 
contributed approximately 1 g kg-1 organic C to the surface (0-15 cm) soil over 10 years.  
Rye was able to produce between 144 and 248 g kg-1 of above ground biomass (Dabney 
et al., 2001).  Combinations of increased carbon inputs together with reductions in tillage 
are needed to maximize increases in soil organic carbon (Roberson et al., 1991; Wright et 
al., 1999). 
The 18.5% decrease in the contribution of C4-carbon to the pool of SOC between 
the 2nd year of bahiagrass and the cotton phases of the rotation indicates that this portion 
of C4-carbon has been mineralized.  Because SOC concentrations did not differ 
significantly, additional SOC was supplied by subsequent C3 crops (i.e., peanut, cotton, 
oat, rye).  Loss of nearly 20% C4 carbon from maize decomposition is consistent with 
measured CO2 fluxes of 25% attributable to maize residue that was measured in the fall 
in a no-till study in Canada (Drewitt et al., 2009).   
Overall the lack of difference in SOC among the crop phases and between 
rotations suggests that the conservation practices are responsible for the relatively high 
carbon levels in these Southeast Ultisols.  While the bahiagrass does contribute to SOC 
pools, half of this carbon is rapidly mineralized within the next couple of years.  
Nutrient Analysis 
 Soil organic carbon plays an important role in nutrient retention, especially in 
sandy soils.  Neither the rotation system nor the crop phase had a large impact on Ca, K, 
Mg, and Na.  Because changes in SOC were not observed due to rotation, crop sequence, 
91 
 
grazing, tillage, and irrigation, it is not unexpected that there were few changes in 
nutrient cycling.  The highest amount of P at the WREC and NFREC large plot 
experiments was found in the cotton cropping sequence of the sod-based rotation and 
were likely due to fertilization, which was applied to both cotton and cover crops each 
year.   
Nitrogen from nitrate and ammonium were higher in the surface 0-5 cm than in 
the 5-10 cm depth.  Total organic N in this study ranged between 0.053 and 0.034 g kg-1 
in the 0-5 cm depth.  In similar soils, total organic N (NO3 and NH4) ranged between 0.3 
and 0.4 g kg-1 in the surface soil (Hubbard et al., 2008), which is 10x higher.  However, 
total organic nitrogen is slightly higher than the 0.01 to 0.02 g kg-1 measured by Allen et 
al. (2006) in an experiment conducted in Minnesota.  Fertilization practices and reduced 
tillage practices that maintain residue at the surface are likely responsible for higher 
nitrogen at the surface.  Nitrate-N was higher than NH4-N in both depths at all locations.  
This is as expected as nitrate fertilizers were typically used.  Cotton sequences, typically, 
had the highest concentration of NO3-N due to fertilization.  Lack of differences among 
the rotations indicates that the contribution of nitrogen from peanut is not affected by 
addition of perennial grasses into peanut-cotton rotation when conservation practices are 
used. 
Conclusion 
 The peanut-cotton rotation in southern Alabama and Georgia and in northern 
Florida has been troubled with low sustainability and productivity due to conventional 
management practices.  Conservation management practices seek to improve 
sustainability and productivity through improving SOC.  In order to further improve 
92 
 
SOC, addition of a perennial grass to the traditional peanut-cotton rotation has been 
suggested.  Together and over time, the conservation management system and forage 
grass were expected to increase the amounts of SOC, increase nutrients, and increase the 
amounts of organic N in the soil.   
 Initial studies of the sod-based rotation expected to find increases in SOC, but 
now after 10 years in the system few differences are found.  However, the long-term use 
of conservation practices in both the traditional and sod-based rotation may account for 
this lack of difference.  Relatively high levels of SOC were found in these soils, which 
may indicate that build-up of SOC through conservation practices has matched what the 
sod-based rotation achieved earlier.  The contribution of bahiagrass to overall SOC 
through each phase of the sod-based rotation supports this concept as SOC contributed by 
bahiagrass is fairly rapidly mineralized over the peanut and cotton phases of the rotation.  
Differences in SOC due to intensive tillage were still observed, even though the 
conservation practice of cover cropping was practiced.  Due to lack of differences in 
SOC, differences in nutrient cycling would not be expected and were not found.  
Differences in nutrient distributions that were observed were largely attributable to 
fertilization practices for individual crop phases.  
This research shows that after 10 years, there is little difference between the sod-
based rotation and the traditional rotation when conservation practices such as strip 
tillage and cover cropping are used.  However, SOC levels were relatively high for the 
region and evidence supports that conservation practices, as well as the sod-based 
rotation, have the ability to improve SOC, which should lead to reduced erosion, 
improved water management, and improved nutrient cycling.     
93 
 
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103 
 
Table 8. Soil textural class, mean pH, and cation exchange capacity (CEC) for Dothan 
soil series (Fine-loamy, kaolinitic, ,thermic Plinthic Kandiudult) at the Wiregrass 
Research and Extension Center (WREC) in Headland, AL, and for the Orangeburg soil 
series (Fine-loamy, kaolinitic, thermic Typic Kandiudult) at the North Florida Research 
and Extension Center (NFREC) in Quincy, FL. 
Location Depth Texture Soil Series pH CEC 
 
cm 
   
cmolc kg-1 
WREC (small) 0-5 Loamy Sand Dothan 5.3 3.51 
 
5-10 Loamy Sand 
 
5.2 2.21 
 
10-15 Loamy Sand 
 
5.1 2.03 
 
15-30 Loamy Sand 
 
5.3 2.86 
 
30-60 Sandy Loam 
 
5.2 2.91 
      NFREC (small) 0-5 Loamy Sand Orangeburg 5.7 3.64 
 
5-10 Loamy Sand 
 
5.8 4.36 
 
10-15 Loamy Sand 
 
5.8 4.36 
 
15-30 Sandy Loam 
 
5.6 3.49 
  30-60 Sandy Loam   5.5 3.41 
 
104 
 
Table 9.  Soil organic carbon (SOC) by cropping sequence in the small plot and large experiments at the Wiregrass Research 
and Extension Center (WREC) and the North Florida Research and Education Center (NFREC). 
Location Depth 
Bahia 1 
SBR? 
Bahia 2 
SBR 
Peanut 
SBR 
Cotton 
SBR 
Peanut 
TR 
Cotton 
TR? P-value 
 cm ??????????????????? g SOC kg-1 ???????????????????  
         
WREC (small) 0-5 9.23 9.02 7.61 7.90 8.59 8.13 0.3428 
 5-10 4.68 4.95 5.33 4.80 5.04 4.90 0.5441 
 10-15 4.86 4.83 4.49 4.46 4.12 4.46 0.4713 
 15-30 3.79 3.73 4.10 3.53 3.73 3.37 0.5933 
 30-60 1.50 ab? 1.81 a 1.80 a 1.30 b 1.80 a 1.43 b 0.0067 
NFREC (small) 0-5 17.43 13.98 16.14 16.03 14.93 14.99 0.5781 
 5-10 12.14 11.05 11.48 11.34 11.00 10.83 0.7153 
 10-15 9.46 8.67 8.90 9.53 9.23 9.40 0.9306 
 15-30 6.57 5.47 5.32 5.53 5.29 5.72 0.2368 
 30-60 2.11 2.15 1.78 2.00 2.05 1.74 0.5630 
NFREC (large) 0-5 10.24 12.61 5.10 8.64 - - 0.0791 
 5-10 9.41 12.92 4.91 6.71 - - 0.0633 
 10-15 8.01 9.55 3.96 4.33 - - 0.1227 
 15-30 6.69 7.83 2.85 3.29 - - 0.0580 
 30-60 1.20 2.73 1.23 0.88 - - 0.2447 
WREC (large) 0-5 19.00 18.76 16.66 15.18 - - 0.1592 
 5-10 11.15 9.43 9.32 8.55 - - 0.1659 
 10-15 7.47 b 9.50 a 6.10 c 6.14 bc - - 0.0010 
 15-30 5.47 a 6.11 a 5.11 a 3.60 b - - 0.0033 
 30-60 2.58 2.29 2.43 1.60 - - 0.2522 
? All crop sequence labels are for the 2009 growing season with sample collection prior to 2010 growing season; SBR = sod-
based rotation (bahia1-bahia2-peanut-cotton), TR = traditional rotation (peanut-cotton, except in small plot experiment at 
NFREC which as peanut-cotton1-cotton2) 
? Letters denote significance at the ? = 0.05 level; significance calculated across crop sequence, each depth increment analyzed 
individually 
? The second year of cotton in the traditional rotation from NFREC (small) and the traditional rotation from WREC (large) 
was omitted  
104
 
105 
 
Table 10.  Soil organic carbon (SOC) by secondary treatment (tillage, irrigation, grazing) in the small plot and large 
experiments conducted at the Wiregrass Research and Extension Center (WREC) and at the North Florida Research and 
Education Center (NFREC). 
Location Depth 
Moldboard 
Plow 
Strip 
Tillage Irrigated 
Non-
Irrigated Grazed 
Non-
grazed P-value 
 
cm ??????????????????????????? g SOC kg-1 ????????????????????????????  
        
 
WREC (Small) 0-5 5.50 b? 11.32 a - - - - <0.0001 
 
5-10 4.94 4.97 - - - - 0.8206 
 
10-15 4.91 a 4.16 b - - - - 0.0028 
 
15-30 3.96 a 3.45 b - - - - 0.0434 
 
30-60 1.60 1.62 - - - - 0.6003 
NFREC (Small) 0-5 - - 14.84 16.32 - - 0.1990 
 
5-10 - - 11.28 11.33 - - 0.9006 
 
10-15 - - 9.21 9.18 - - 0.9439 
 
15-30 - - 5.53 5.77 - - 0.4577 
 
30-60 - - 1.83 2.07 - - 0.3459 
NFREC (Large) 0-5 - - - - 8.10 10.20 0.2784 
 
5-10 - - - - 7.86 9.12 0.5300 
 
10-15 - - - - 5.35 7.58 0.2365 
 
15-30 - - - - 4.49 5.84 0.3392 
 
30-60 - - - - 1.54 1.48 0.9242 
WREC (Large) 0-5 - - - - 16.60 18.20 0.2423 
 
5-10 - - - - 8.96 10.26 0.1381 
 
10-15 - - - - 7.00 7.60 0.2288 
 
15-30 - - - - 4.97 5.18 0.6079 
 
30-60 - - - - 2.19 2.26 0.8475 
? Letters denote significance at the ? = 0.05 level; significance calculated across secondary treatments, each depth increment 
analyzed individually all crop sequences were combined
105
 
 
106 
  
 
Table 11.  Delta 13C values and contributions SOC by C3 and C4 plants in 0-5 cm 
depth increment in the small plot experiments at Wiregrass Research and 
Extension Center (WREC) and the North Florida Research and Extension Center 
(NFREC). 
 
? All crop sequence labels are for the 2009 growing season; SBR = sod-based rotation 
(bahia1-bahia2-peanut-cotton), TR = traditional rotation (peanut-cotton, except in small 
plot experiment at NFREC which as peanut-cotton1-cotton2) 
? Letters denote significance at the ? = 0.05 level.  Because there was no 
difference between locations, data were combined. 
? The second year of cotton in the traditional rotation was omitted at the NFREC 
for statistical analysis  
? ND = Not Detectable 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
Crop Sequence ?13C Values C4-Carbon C3-Carbon 
 ?  ?????? % SOC ?????? 
Bahia1 SBR? -22.55 c? 29.5 70.5 
Bahia2 SBR -21.48 d 37.5 62.5 
Peanut SBR -22.40 c 30.6 69.4 
Cotton SBR -24.12 b 19.0 81.0 
Peanut TR -26.74 a   ND? 100 
Cotton TR? -27.13 a ND 100 
P-value <0.0001   
 
 
107 
  
Table 12. Concentrations of Ca, K, Mg, Na, and P by depth at the small plot and large 
experiments at Wiregrass Research and Extension Center (WREC) and the North Florida 
Research and Extension Center (NFREC). 
 
 
? Letters denote significance at the ? = 0.05 level by depth increment for each nutrient in 
each experiment; all crop sequences were combined. 
 
 
 
Location Depth  Ca K Mg Na P 
 
cm ???????????????????? mg/kg ???????????????????? 
       WREC 
(Small) 0-5 529.34 a? 61.20 a 38.90 b 41.25 ab 10.31 a 
 
5-10 307.54 b 40.64 c 23.54 c 40.54 b 7.46 b 
 
10-15 273.06 b 41.43 c 23.60 c 39.21 b 7.45 b 
 
15-30 307.74 b 46.92 b 39.02 b 42.54 ab 5.81 c 
 
30-60 305.47 b 30.71 d 79.58 a 44.99 a 0.93 d 
P-value   <0.0001 <0.0001 <0.0001 0.0435 <0.0001 
       NFREC 
(Small) 0-5 891.85 a 147.72 a 135.14 a 41.67 b 57.52 a 
 
5-10 745.55 b 96.19 b 118.14 b 40.81 b 39.62 b 
 
10-15 618.65 c 90.51 b 105.87 c 39.58 b 27.56 c 
 
15-30 397.83 d 87.68 b 115.59 b 42.75 ab 7.22 d 
 
30-60 315.39 e 42.92 c 109.84 bc 44.94 a 0.70 e 
P-value   <0.0001 <0.0001 <0.0001 0.0129 <0.0001 
       NFREC 
(Large) 0-5 611.33 a 113.66 a 60.06 a 32.91 50.84 a 
 
5-10 628.07 a 63.96 b 52.69 b 31.29 46.42 ab 
 
10-15 558.48 a 58.72 bc 46.21 c 31.76 42.51 b 
 
15-30 410.82 b 52.76 bc 37.73 d 32.00 28.60 c 
 
30-60 249.82 c 42.17 c 30.73 e 31.83 4.66 d 
P-value   <0.0001 <0.0001 <0.0001 0.5792 <0.0001 
       WREC 
(Large) 0-5 789.44 a 112.62 a 205.27 a 38.01 ab 25.17 a 
 
5-10 571.90 b 52.28 b 151.43 b 36.73 bc 11.26 b 
 
10-15 487.40 c 41.14 bc 133.64 bc 35.02 c 6.79 c 
 
15-30 445.14 c 30.14 cd 131.18 c 37.80 ab 3.61 d 
 
30-60 343.16 d 20.17 d 120.07 bc 40.13 a 0.26 e 
P-value   <0.0001 <0.0001 <0.0001 0.0102 <0.0001 
 
108 
  
Table 13. Magnesium and P concentrations in soil by cropping sequence and depth in the small plot experiment at Wiregrass 
Research and Extension Center (WREC) and the large experiments at WREC and North Florida Research and Education 
Center (NFREC). 
 
? All crop sequence labels are for the 2009 growing season; SBR = sod-based rotation (bahia1-bahia2-peanut-cotton), TR = 
traditional rotation (peanut-cotton) 
? Letters denote significance at the ? = 0.05 level when compared within a depth increment across crop sequence 
  
 
Location Nutrient Depth 
Bahia 1 
SBR? 
Bahia 2 
SBR 
Peanut 
SBR 
Cotton 
SBR 
Peanut 
TR 
Cotton  
TR P-value 
  
cm ??????????????????????? mg/kg ????????????????????? 
 WREC (Small) Mg 0 ? 5 43.30 49.44 47.11 42.98 28.72 36.20 0.7419 
  5 ? 10 27.64 25.26 24.03 29.69 16.75 24.70 0.3488 
  
10 ? 15 26.98 24.85 28.64 22.56 15.22 28.51 0.1395 
  15 ? 30 41.22 33.94 30.12 45.08 27.05 54.21 0.0737 
  
30 ? 60 76.80 bc? 66.14 bc 75.74 bc 91.77 ab 53.07 c 107.89 a 0.0500 
          
NFREC (Large) P 0 ? 5 38.75 b 55.14 ab 41.60 b 67.55 a - - 0.0381 
  5 ? 10 36.14 51.07 38.93 57.17 - - 0.1102 
  10 ? 15 33.93 47.21 29.45 54.82 - - 0.1121 
  15 ? 30 26.53 b 19.89 b 26.77 b 42.02 a - - 0.0308 
  30 ? 60 3.39 1.87 3.69 10.90 - - 0.1588 
          
WREC (Large) P 0 ? 5 10.39 b 30.06 a 26.67 a 33.27 a - - 0.0024 
  5 ? 10 3.87 b 11.26 ab 11.67 ab 18.51 a - - 0.0082 
  10 ? 15 2.18 b 7.56 a 8.53 a 8.92 a - - 0.0013 
  15 ? 30 1.06 b 4.55 a 6.09 a 4.35 a - - 0.0022 
  30 ? 60 0.47 0.71 0.59 0.89 - - 0.1077 
108
 
 
 
 109 
Table 14. Nitrate-nitrogen (NO3--N) and ammonium-N (NH4+-N) concentrations at 0-5 and 5-10 cm depths by cropping 
sequence in the small plot and large experiments at the Wiregrass Research and Extension Center (WREC) and the North 
Florida Research and Extension Center (NFREC). 
 
? All crop sequence labels are for the 2009 growing season; SBR = sod-based rotation (bahia1-bahia2-peanut-cotton), TR = 
traditional rotation (peanut-cotton, except in small plot experiment at NFREC which was peanut-cotton1-cotton2) 
? Letters denote significance at the ? = 0.05 level when compared within a depth increment across crop sequence.   
? The second year of cotton in the traditional rotation was omitted at the NFREC for statistical analysis  
 
Location N Form Depth 
Bahia 1 
SBR? 
Bahia 2 
SBR 
Peanut 
SBR 
Cotton 
SBR 
Peanut 
TR 
Cotton  
TR? P-value 
  
 ??????????????????????? mg N/kg ????????????????????? 
 WREC (Small) NO3--N 0 ? 5 15.32 b 18.09 b 19.08 b 15.82 b 25.42 b 47.99 a 0.0002 
 
NH4+-N  6.76 b 8.07 ab 17.51 ab 7.83 ab 8.57 ab 17.51 a 0.0382 
 NO3--N 5 ? 10 7.56 6.68 9.95 7.75 10.79 13.89 0.1039 
 
NH4+-N  5.63 5.00 5.90 5.37 5.96 6.15 0.9508 
NFREC (Small) NO3--N 0 ? 5 17.31 bc 39.47 a 11.66 bc 30.30 ab 4.30 c 9.10 c 0.0148 
 
NH4+-N  16.52 18.23 9.90 17.84 10.92 16.04 0.7233 
 NO3--N 5 ? 10 5.63 bc 18.25 a 8.78 bc 14.27 ab 2.99 c 4.93 c 0.0124 
 
NH4+-N  8.66 7.87 6.76 11.50 7.38 8.14 0.4902 
NFREC (Large) NO3--N 0 ? 5 32.37 b 31.28 b 24.56 b 64.89 a - - 0.0087 
 NH4+-N  5.75 10.90 10.09 15.31 - - 0.2429 
 
NO3--N 5 ? 10 23.48 b 17.82 b 14.84 b 36.32 a - - 0.0057 
 
    NH4+-N  4.99 5.39 8.14 8.42 - - 0.1114 
WREC (Large) NO3--N 0 ? 5 16.58 b 32.70 ab 33.23 ab 72.59 a - - 0.0003 
 NH4+-N  26.84 17.61 16.30 15.74 - - 0.6915 
  NO3--N 5 ? 10 11.73 14.38 27.34 19.46 - - 0.2912 
 NH4+-N  11.64 8.14 7.70 8.40 - - 0.3466 
109
 
 
110 
 
 
Appendix 1. Official series description of the Dothan soil series as described by the 
USDA-NRCS Soil Survey Division. 
DOTHAN SERIES 
The Dothan series consists of very deep, well drained, moderately slowly to slowly 
permeable soils on broad uplands. They formed in thick beds of unconsolidated, medium 
to fine-textured marine sediments of the Coastal Plain. Slopes range from 0 to 12 percent. 
Near the type location, the average annual precipitation is about 53 inches and the 
average annual air temperature is about 65 degrees F. 
TAXONOMIC CLASS: Fine-loamy, kaolinitic, thermic Plinthic Kandiudults 
TYPICAL PEDON: Dothan sandy loam--cultivated field. (Colors are for moist soil.) 
Ap--0 to 13 inches; brown (10YR 4/3) sandy loam; weak fine granular structure; very 
friable; about 2 percent, by volume, ironstone; many fine roots; strongly acid; abrupt 
smooth boundary. (6 to 12 inches thick) 
Bt1--13 to 22 inches; yellowish brown (10YR 5/8) sandy clay loam; weak medium 
subangular blocky structure; friable; about 2 percent, by volume, ironstone; many fine 
roots; common faint clay films on ped faces; strongly acid; diffuse smooth boundary. 
Bt2--22 to 36 inches; yellowish brown (10YR 5/8) sandy clay loam; weak medium 
subangular blocky structure; friable; common fine roots; common faint clay films on ped 
faces; about 1 percent, by volume, plinthite nodules; common medium distinct strong 
brown (7.5YR 5/8) masses of iron accumulation; strongly acid; clear wavy boundary. 
(Combined thickness of the Bt horizons ranges from 15 to 36 inches.) 
Btv1--36 to 52 inches; yellowish brown (10YR 5/8) sandy clay loam; weak medium 
subangular blocky structure; friable; common fine roots; common faint clay films on ped 
faces; about 10 percent by volume, plinthite nodules; common medium distinct strong 
brown (7.5YR 5/8), red (2.5YR 4/8), yellow (10YR 7/8) masses of iron accumulation and 
common medium distinct light brownish gray (10YR 6/2) areas of iron depletions; very 
strongly acid. 
Btv2--52 to 80 inches; 20 percent yellowish brown (10YR 5/8), 20 percent strong brown 
(7.5YR 5/8), 20 percent red (2.5YR 4/8), 20 percent yellow (10YR 7/8) and 20 percent 
very pale brown (10YR 8/2) sandy clay loam in a variegated pattern; weak medium 
subangular blocky structure; firm; compact in place; many fine roots; common faint clay 
films on ped faces; about 20 percent by volume, plinthite nodules; the areas of yellowish 
brown, strong brown, red, and yellow are iron accumulations; the areas of very pale 
brown are iron depletions; very strongly acid. 
 
111 
 
TYPE LOCATION: Henry County, Alabama; Wiregrass Agricultural Experiment 
Station; south side of Alabama Highway 134; NE 1/4, NW 1/4, Section 3, R. 27 E., T. 4 
N.; latitude 31 degrees, 21 minutes, 17.2 seconds N; longitude 85 degrees, 19 minutes, 
30.4 seconds W. 
RANGE IN CHARACTERISTICS: Solum thickness ranges from 60 to more than 80 
inches. Depth to horizons that contain 5 percent or more plinthite ranges from 24 to 60 
inches. Content of ironstone pebbles range from 0 to 5 percent, by volume in the A 
horizon and upper part of the B horizon. Content of quartzite pebbles range from 0 to 5 
percent throughout the profile. Soil reaction ranges from very strongly acid to moderately 
acid throughout except where the surface has been limed. 
The A or Ap horizon has hue of 10YR or 2.5Y, value of 3 to 7, and chroma of 2 to 4. 
Texture is sand, loamy fine sand, loamy sand, fine sandy loam, or sandy loam. 
The E horizon, where present, has hue of 10YR or 2.5Y, value of 5 to 7, and chroma of 3 
to 6. Textures are the same as the Ap horizon. 
The BE or BA horizon, where present, has hue of 10YR or 2.5Y, value of 5 or 6, and 
chroma of 3 to 8. Texture is fine sandy loam or sandy loam. 
The Bt horizon has hue of 7.5YR to 2.5Y, value of 5 to 8, and chroma of 4 to 8. The 
upper 20 inches of the Bt horizon contains 18 to 35 percent clay and less than 20 percent 
silt. Redoximorphic features in shades of brown or red range from none to common. 
Content of nodular plinthite ranges from 0 to 3 percent, by volume. Texture is fine sandy 
loam, sandy loam, or sandy clay loam. 
The Btc horizon, where present, has the same colors and textures as the Bt horizon. 
The Btv horizon has hue of 10YR or 2.5Y, value of 3 to 8, and chroma of 4 to 8; or it has 
no dominant matrix color and is variegated in shades of red, yellow, brown, and gray. A 
matrix hue of 2.5YR, 5YR, or 7.5YR is allowed below a depth of 40 inches. Content of 
nodular or platy plinthite ranges from 5 to 35 percent, by volume. Texture is commonly 
sandy clay loam or sandy clay but includes clay loam. 
  
 
112 
 
Appendix 2. Official series description of the Orangeburg soil series as described by the 
USDA-NRCS Soil Survey Division. 
ORANGEBURG SERIES 
The Orangeburg series consists of very deep, well drained, moderately permeable soils 
that formed in loamy and clayey sediments of the Coastal Plain. Slopes range from 0 to 
25 percent. 
TAXONOMIC CLASS: Fine-loamy, kaolinitic, thermic Typic Kandiudults 
TYPICAL PEDON: Orangeburg loamy sand--cultivated. (Colors are for moist soil 
unless otherwise stated.) 
Ap--0 to 7 inches; dark grayish brown (10YR 4/2) loamy sand; weak fine granular 
structure; very friable; many fine and medium roots; strongly acid; clear smooth 
boundary. (3 to 10 inches thick) 
BA--7 to 12 inches; strong brown (7.5YR 5/6) sandy loam; weak fine subangular blocky 
structure; very friable; many fine roots; sand grains bridged and coated with clay; very 
strongly acid; clear smooth boundary. (0 to 12 inches thick) 
Bt1--12 to 54 inches; yellowish red (5YR 4/6) sandy clay loam; moderate medium 
subangular blocky structure; friable; many fine roots; many fine pores; common distinct 
clay films on faces of peds; very strongly acid; gradual smooth boundary. 
Bt2--54 to 72 inches; yellowish red (5YR 5/8) sandy clay loam; moderate medium 
subangular blocky structure; friable; few fine roots; few faint clay films on faces of peds; 
few fine distinct yellowish brown (10YR 5/6) masses of relic iron accumulation; very 
strongly acid. (Combined thickness of the Bt horizons is 52 to 70 inches or more) 
TYPE LOCATION: Dougherty County, Georgia; 0.6 mile west on Antioch Road from 
intersection with Gravel Hill Road; 660 yards north in cultivated field. (USGS 
Quadrangle, Putney, GA. (1974); lat. 31 degrees 29 minutes 07 seconds N., long. 84 
degrees 04 minutes 20 seconds W.) 
RANGE IN CHARACTERISTICS: Solum thickness typically is 72 to 96 inches and 
ranges from 70 to 120 inches. Ironstone nodules range from 0 to 10 percent throughout 
the solum. Reaction of the A and Bt1 horizons is very strongly acid to moderately acid, 
and the Bt2 and underlying horizons are very strongly acid or strongly acid. 
The A or Ap horizon has hue of 5YR, 7.5YR, or 10YR, value of 3 through 5, and chroma 
of 2 through 6. Texture is sand, loamy sand, loamy fine sand, sandy loam, fine sandy 
loam, or sandy clay loam. 
 
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The E horizon, where present, has hue of 7.5YR or 10YR, value of 5 or 6, and chroma of 
3 through 6. It is loamy sand or sand. 
The BA or BE horizon, where present, has hue of 2.5YR, 5YR, 7.5YR, or 10YR, value of 
4 through 6 and chroma of 4 through 8. Texture is sandy loam or fine sandy loam. 
The Bt horizon has hue of 5YR or 2.5YR, value of 4 or 5, and chroma of 6 or 8, however, 
hues of 7.5YR are allowed within the upper 10 inches, and 10R hues are allowed in the 
lower Bt. The upper part of the Bt horizon is sandy clay loam and the lower part is sandy 
clay loam or sandy clay with less than 45 percent clay. 
The lower Bt horizon has none to common brownish masses of iron accumulation which 
are relic redoximorphic features. Clay content of the upper 20 inches of the Bt horizon 
ranges from 20 to 35 percent and silt content is less than 20 percent.