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EFFECTS OF TURNING FREQUENCY, PILE SIZE AND SEASON ON PHYSICAL, CHEMICAL AND BIOLOGICAL PROPERTIES DURING
COMPOSTING OF DAIRY MANURE/SAWDUST (DM+S)
M.S Thesis
Presented in Partial Fulfillment of the Requirements for the Degree Master in
Food, Agricultural, and Biological Engineering in the Graduate School of The
Ohio State University
By
Sandra M. Tirado, B.S.
****
The Ohio State University
2008
Dissertation Committee: Approved by
Dr. Frederick C. Michel, Jr, Adviser
Dr. Harold M. Keener Advisor
Dr. Brian McSpadden Gardener Food, Agricultural and Biological
Dr. Warren A. Dick Engineering Graduate Program
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ABSTRACT
Composting offers the potential to significantly reduce problems
associated with manure management including odors, pathogens, ground water
pollution, and utilization costs. Two variables that directly affect on-farm
composting costs are windrow size and windrow turning frequency. However the
size of a windrow is limited by the depth of penetration of oxygen and high
temperatures as well as available equipment. In this study three full scale
compost sets were set-up at the Ohio Agricultural Research and Developing
Center (OARDC) compost pad to evaluate the effects of turning frequency, pile
size and seasonal variability on physical (temperature, oxygen, bulk density,
moisture and weigh loss), chemical (volatile solid loss, pH, Carbon and Nitrogen
concentrations) and biological (plant growth bioassays and microbial community
structure) parameters during dairy manure/sawdust composting (DM+S). Based
on these data the operational costs for producing and transporting compost were
estimated and compared to those for liquid manure and fertilizer.
The three treatments consisted of a set of windrows (A) which were
turned using a self propelled and tractor drawn windrow turner every three days
for a total of 32 turns during 16 weeks, a second set (B) that was turned once
every ten days and a third set (C) consisting of much larger piles turned that was
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also turned every ten days with a loader. All three sets were composted in both
winter and summer for 120 days.
The hypotheses of the study was that: “turning frequency, pile size and
season do not significantly affect compost process parameters or the final
chemical, physical or biological properties of cured composts”
Results showed that neither physical chemical nor biological properties of
the final cured composts were significantly affected by turning frequency, season
or pile size (p> 0.05). During composting, he the surface area, oxygen
concentrations and Total nitrogen losses were significantly affected by pile size
(p < 0.05). Turning frequency affected (p < 0.05) mass losses, bulk density and
total nitrogen losses. The seasonal effects on composting during the process
were primarily related to moisture (p < 0.05), mostly due to ambient temperatures
which affects water holding capacity of air. Despite these process differences,
the final cured composts from all treatments and seasons had similar properties
(p > 0.5).
Plant growth bioassays showed a high emergence percentage (> 80%).
The fertilized cucumber plants grown in composts from the various treatments in
summer had higher shoot dry weights than peat controls ( ≥ 100%) except for
day 30 in pile C (89%). The unfertilized cucumbers plants showed an increase of
shoot dry weight at the end of the composting process (day 120) except for
windrow A in summer. However the bioassay tests were inconclusive.
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Microbial Community analysis, based on Terminal Restriction Fragment
Length Polymorphisms (T-RFLP), showed that management differences (turning
frequency, pile size and season) did not significantly affect (p > 0.05) microbial
community structure. Clustering, pairwise comparison, principal component
analysis (PCA) and Kruskal Wallis tests were used to determine the similarities
and differences between microbial communities in the different treatments. In
each treatment a different subset of TRFs were present suggesting that different
classes of organisms predominate during different stages of composting..
However, one terminal restriction fragment H371 contributed significantly (p< 0.1)
to the observed variation as a function of compost age
The Restriction Fragment (TRF) sizes obtained in the different treatments
were compared to fragment sizes predicted by in silico amplification and
digestion (RDP v.9.0) to characterize the microbial community in the composts.
TRFs fragments sizes were also compared to a clone library of 263 sequences
from composted dairy manure. Representative TRFs (61, 93, 99, 159, 167, 205,
215, 227, 365, 373, 437 and 481) in the compost samples were consistent with
the predicted TRFs of Proteobacteria, Firmicutes, Bacteroidetes and
Actinobacteria.
The main factor affecting total compost production operational cost was
the cost of the bulking agent. Operational costs for frequently turned windrow
were higher ($109/Mg) compared to the infrequently turned windrow ($95/Mg),
and the infrequently turned piles ($93/Mg). These differences are due to the time
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that is needed to turn and the equipment fuel costs. Thus, infrequent turning
(every ten days) with larger windrow sizes reduced the operating costs
associated with unseparated dairy manure composting compared to more
frequently turning windrows. It is recommended for the farmers to use a turning
frequency of ten days and piles with a surface to volume ratio of 0.9-1.2 m2/m3 to
minimize operational costs. If composting is performed in temperate climates
there is a need to consider the moisture content at the beginning of the process
to prevent moisture irregularities during the process.
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ACKNOWLEDGMENTS
I would like to express my deep appreciation to Harold M. Keener, Warren
A. Dick and Brian McSpadden Gardener, my academic committee, for all the
advice and support in every aspect of my graduate school experience; also for
encouraging me and showing me the right way for success. I would like to thank
Dr. Frederick C. Michel, my academic advisor, for showing me that
independence, patience and understanding are also essential to achieve any
goal.
I also would like to thank Dr. Jerome F. Rigot, Michael Klingman, Michael
J. Sciarini and the entire department in Wooster for the support, advice and help
during the study. A special thanks to Gerald L.Reid, Richard Franks and all the
crew of the Farm Operations at the OARDC; without them this study could not be
possible. Thanks also to Nathan Smith and my family in Colombia, for the
support and the concerned about my academic career and my life.
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VITA
August 12, 1980……………………………..Born in Manizales, Caldas, Colombia 2000 - 2005…………………………………. B.S., Pontificia Universidad Javeriana, Bogotá, Colombia 2005- 2006…………………………………..Researcher, Department of Food, Agricultural and
Biological Engineering The Ohio State University, Columbus,
Ohio
2006-Present………………………………..Graduate Research Associate- Student
Department of Food, Agricultural and Biological Engineering
The Ohio State University, Columbus, Ohio
PUBLICATIONS
Tirado, S. M., J. Rigot, Michel F.C. (2007). Analysis of bacterial community structure in dairy manure composts. Abstracts of the General Meeting of the
American Society for Microbiology. Washington, DC. p468-469.
Tirado, S.M., Michel F.C. (2008) Seasonal Effects on the composting of Dairy Manure/Sawdust (DMS)” Paper No 083671 Annual Meeting American Society of
Agricultural and Biological Engineers (ASABE)- Providence, R.I
FIELDS OF STUDY
Major Field: Food, Agricultural and Biological Engineering Studies in: Environmental Biology Environmental Microbiology
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TABLES OF CONTENTS
Page
ABSTRACT ...........................................................................................................ii ACKNOWLEDGMENTS .......................................................................................vi VITA….................................................................................................................vii LIST OF TABLES .................................................................................................xi LIST OF FIGURES............................................................................................. xiii LIST OF ABBREVIATIONS .................................................................................xv CHAPTERS 1.INTRODUCTION ............................................................................................... 1
1.1 Background.......................................................................................... 1
1.2 Objectives ............................................................................................ 6 2.LITERATURE REVIEW ..................................................................................... 8
2.1 Recycling organic wastes .................................................................... 8
2.2 Composting.......................................................................................... 9
2.3 Microbiology of composting ............................................................... 21
2.4 Current Research Interest on Composting......................................... 30
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3.EFFECTS ON TURNING FREQUENCY, PILE SIZE AND SEASON VARIABILITY ON THE COMPOSTING OF DAIRY MANURE SAWDUST (DMS) ................................................................................... 323.1 ABSTRACT........................................................................................ 32
3.2 Introduction ........................................................................................ 33
3.3. Materials and methods...................................................................... 35
3.4 Results and discussion ...................................................................... 44
3.6 Summary and conclusion................................................................... 77
4. BIOLOGICAL AND MOLECULAR PARAMETERS DURING
COMPOSTING OF DAIRY MANURE/SAWDUST (DMS) IN FREQUENT AND INFREQUENT TURNED WINDROWS....................... 78
4.1 Abstract.............................................................................................. 78
4.2 Introduction ........................................................................................ 80
4.3 Materials and methods....................................................................... 81
4.4 Results and discussion ...................................................................... 88 4.5 Summary and conclusions............................................................... 109
APPENDICES Appendix A. Physical, Chemical, Biological and Molecular parameters
analyzed during the composting process............................................... 110 Appendix B. Physical, Chemical, Biological and Molecular Parameters
Analyzed during the Composting Process in Summer........................... 114
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Appendix C. Operation Costs Equation in Dairy Manure Composting.............. 119 Appendix D. Potential Classes of Bacteria for samples I (Day 50), II (Day
155) and III (Day 330)-Clone Bank ........................................................ 122 REFERENCES................................................................................................. 124
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LIST OF TABLES
Table ..............................................................................................................Page 3.1 Summary of weather data for study period summer and winter 2007........... 37 3.2 Machinery used to build, turn and composite frequently turned windrows
(A), infrequently turned windrows (B) and piles (C) during this study and its respectively fuel efficiency (Grisso R.D., 2004)............................ 42
3.3 Initial and Final compost properties performed in this study, for
frequently turned windrows (A), infrequently turned windrows (B) and piles (C). .................................................................................................. 49
3.4 Effect of depth on temperature (°C), pH and oxygen concentrations (%)
for winter and summer on day 30. In frequently turned windrow (A-Every three days), infrequently turned windrow (B-Every 10 days) and infrequently turned pile (C-Every 10 days). ** Missing data .............. 55
3.5 Effects of Management practices (pile size, turning frequency and
season) during the composting process (from day zero through day 120) with p values (α= 0.05) and correlation coefficients......................... 65
3.6 Estimated costs per Mg of cured composts (produced in this study) in
US dollars for DM+S compost managed with different turning frequencies and pile sizes........................................................................ 68
3.7 Nutrient concentrations, values and costs where transportation costs
equal the nutrient value in miles for dairy manure (Heifer barn), composts (DM+S, produced in this study) and fertilizers (15:15:15)........ 71
4.18Biochemical changes of composite samples in frequently turned
windrows (A), infrequently turned windrows (B) and infrequently turned piles (C) for the full scale study..................................................... 91
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4.29Concentration of genomic DNA and conditions for the frequently turned windrows (A), infrequently turned windrows (B) and infrequently turned piles (C) compost treatments. ....................................................... 96
4.310Similarity coefficients between the TRFs from the middle of the pile (120cm) on day 30 of frequently turned windrows (A), infrequently turned windrows (B) and infrequently turned piles (C) compost.............. 98
4.41116S rDNA terminal restriction fragment with factor loadings |x|>0.60 on
the four principal components (PC) for each experimental treatment .... 103 4.512Predicted bacterial genera to generate a terminal restriction fragments
(TRFs) with factor loadings |x| ≥ 0.60 on the PCA for each experimental treatment .......................................................................... 107
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LIST OF FIGURES
Figure………………………………………………………………………………..Page
3.1 Experimental treatments and dimensions for winter (w) and summer (s). In frequently turned windrows (A), infrequently turned windrows (B) and infrequently turned piles (C). w= Winter, s= Summer........................ 38
3.2 Oxygen concentrations in frequently turned windrows (A), infrequently
turned windrows (B) and piles (C), before, immediately after and 2 hours after turning (120cm depth)............................................................ 51
3.3 Temperatures (°C) in frequently turned windrows (A), infrequently turned
windrows (B) and piles (C), before, immediately after and 2 hours after turning (120 cm depth)..................................................................... 52
3.4 Moisture Content and cumulative precipitations during winter (w) and
summer (s) for frequently turned widrows (A), infrequently turned windrows (B) and piles (C)....................................................................... 62
3.5 Day-by-day average daily temperatures during the composting process
(Wooster Experimental Station, OSU/OARDC). ...................................... 63 3.6 Revenues of compost in $/yd3 (produced in this study) when selling
compost in fertility-based (same product category such as soil amendments and fertilizer) and nonfertility-based (erosion control, disease suppression, bioremediation, storm water management) markets. ................................................................................................... 75
4.17Effects of compost age on Total N supplied by compost and shoot dry
weight of cucumber plants (C.sativus. L.cv) produced in the three different compost amended potting mixes treatments. Compost physical and chemical conditions are shown in previous results. ............ 92
4.28Dendogram-Relatedness of T-RFs profiles of HhaI-digested of 16S
rDNA from frequently turned windrows (A), infrequently turned
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windrows (B), infrequently turned piles (C) and clone compost samples (I, II, II). (The UPGMA, single linkage, was used to performed the cluster patterns and obtain the similarity dendogram) ...... 97
4.39Effects of composting age, turning frequency and pile size during winter
and summer in bacterial community structure for the frequently turned windrows (A), infrequently turned windrows (B), infrequently turned piles (C) and clone compost samples (I, II, II). Ordination plots from the first two principal components (PC) are shown with the corresponding standard error bars. The PCA was performed using the 16S rDNA terminal restriction fragment (HhaI) relative abundance data obtained from composts collected on day zero, 30, 60, 90 and 120 exposed to different management practices. ................ 101
4.410Effects of season variability, turning frequency, depth and pile size in
day 30 on bacterial community structure for the frequently turned windrows (A), infrequently turned windrows (B) and infrequently turned piles (C). ..................................................................................... 102
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LIST OF ABBREVIATIONS
AFLP………………………..Amplified Fragment Length Polymorphisms
ARISA………………………Automated Ribosomal Intergenic Spacer Analysis
ASAE...……………………..American Society Agricultural Engineers
ATCC……………………….The American Type Culture Collection
BC……………………………Bacterial Community
CA…………………………..Continuous Aeration
CLPP……………………….Community Level Physiological Profiles
DGGE………………………Denaturing Gradient Gel Electrophoresis
DM+S………………………...Dairy manure sawdust
DNA…………………………Deoxyribonucleic acid
EDTA………………………..Ethylene Diamine Tetraacetic Acid
FAME………………………..Fatty Acid Methyl Ester
FISH…………………………Fluorescent in situ hybridization
IA…………………………….Intermittent Aeration
ICP…………………………..Inductively Coupled Plasma
LB……………………………Luria-Bertani Enriched Bacterial Media
MSP…………………………Maximal Segment Pair Score
NCBI…………………………National Center for Biotechnology Information
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NOAA/NCDC……………….National Oceanic and Atmospheric
Administration/National Climate Data Center
OARDC……………………..Ohio Agricultural Research Development Center
PCA…………………………Principal Component Analysis
PCR…………………………Polymerase Chain Reaction
PLFA………………………..Phospholipid Fatty Acid
RDP…………………………Ribosomal Database Project
RFLP………………………..Restriction Fragment Length Polymorphisms
RNA…………………………Ribonucleic Acid
SCSU……………………….Sole Carbon Source Utilization
SSCP……………………….Single Strand Conformation Polymorphism
T-RFLP……………………..Terminal Restriction Fragment Length Polymorphism
TRFs………………………...Terminal Restriction Fragments
U.S. EPA……………………The United States Environmental Protection Agency
UPGMA……………………..Unweighted Pair Group Method with Arithmetic
averages
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CHAPTER 1
INTRODUCTION
1.1 BACKGROUND Composting and the use of compost offer the potential to significantly
reduce manure management problems such as odors, pathogens, ground water
pollution, and utilization costs (Rynk et al., 1992; Grewal et al., 2007; Keener et
al., 1996). Additionally, such composts can potentially be sold into high value off-
farm markets, thereby adding additional revenue for livestock producers. The
value of composts is a result of its ability to improve soil physical and biochemical
properties and to suppress common plant diseases (Hoitink et al., 1986).
Windrow composting is the most commonly used method to prepare
manure composts (Stentiford et al., 1996). It consists of placing a mixture of raw
materials in long narrow piles or windrows which are mechanically turned on a
regular basis. Two variables that directly affect on-farm composting costs are
windrow size and windrow turning frequency. The costs for on-farm composting
are strongly related to pile size (which affects pad size) equipment and labor
costs for windrow turning.
The size of a windrow is limited by the depth of penetration of oxygen and
high temperatures (Iannotti et al., 1994). Occasional turning is necessary to mix
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the compost to assure even decomposition and pathogen destruction (Alexander,
2007; Hoitink, 1993)
Previous authors have shown that turning frequency affects the rate of
composting, the time required to reach full maturation and elimination of
phytotoxicity (Stanford et al., 2006; Chikae et al., 2006; Tateda et al., 2005; Ibuki
et al., 1999; Tiquia et al., 1997; Illmer et al., 1997; Defoer et al., 2002; Parkinson
et al., 2004). Tiquia et al., (1997) studied the changes in physical (temperature),
chemical (pH and NH4+-N and HA) and biological (germination index) properties
showing that composting of spend pig litter with a 2 or 4-day turning frequency
had a faster composting rate than turning the spent pig litter pile with a 7-day
turning frequency. Frequency of turning has also been observed to influence
nitrogen and phosphorus losses from manure stacks (Parkinson et al., 2004).
Chikae et al., (2006) demonstrated that an efficient composting system is highly
correlated with the oxygen concentration regardless the turning frequency. The
efficient composting system was found to be a static aerated reactor system in
comparison with a turning pile.
Tateda et al., (2005) showed that turning by layers, which is different from
conventional turning that mixes compost pile entirely, was essential in terms of
hygienic aspects. Ibuki et al., (1999) composted dairy manure with an automatic
turning device and forced aeration device showing that economical and
managerial efficiency was improved with fewer turnings without affecting the
quality and microbial properties of the compost. However, Illmer et al., (1997)
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showed that the mixing action of the turning influenced significantly chemical and
biological parameters. The speed of degradation, as well as the quality of the end
product was significantly increased through supported mixing with a mechanical
stirrer, which reduced water content and improved aeration. In general, Illmer
showed that mechanical mixing led to better results regarding organic matter
decomposition and immobilization of nutrients, however manual mixing showed a
highest amount of microbial biomass compared with static composters.
Defoer et al., (2002) conducted a study in different composted materials to
determine the effects of turning frequency on odor emissions. Results
demonstrated that frequent turning resulted of less odor emissions but larger
costs; windrow turning frequency affected compost bulk density but did not
significantly affect temperature or oxygen concentration, the time to produce
stable compost or the characteristics of finish compost.
Michel et al., 1996 studying yard trimmings showed that turning
frequencies of once per month and seven times per month had similar
temperatures oxygen concentrations and final compost chemical properties. Only
bulk density and particle size were different in frequently and infrequently turned
windrows.
Turning exposes fresh material for microbial colonization and leads to the
release of NH3 that has accumulated in the internal void spaces. Thus enhanced
NH3 losses from turned composts may make an additional contribution to
deposition on sensitive ecosystems. Hence it may be environmentally beneficial
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to reduce turning frequencies or develop appropriate turning regimes that result
in high pathogen kill, yet retain N (Parkinson et al. 2004).
Different studies have been developed to determine the effects of pile size
on composting (Michel et al., 1996; Defoer et al., 2002; Criner et al., 1995;
Renkov et al., 1994; Criner et al., 1995; Weppen et al., 2002). Michel et al.,
(1996) showed that the effects of windrows and pile configurations (different
surface area to volume ratios) had dramatic effects on temperature and oxygen
concentrations.
Renkow et al., (1994) and Criner et al., (1995) showed that pile size and
pad size are directly associated with the costs of building and operating
composting facilities. Unpaved, minimal tech facilities are considerably cheaper
to build and operate than more sophisticated facilities; however, the lower quality
of the material produced by such facilities may significantly limit the amount of
that product that can be marketed (or even given away). Economies of scale
clearly favor more sophisticated systems at larger (≥ 100,000 tons per year)
annual volumes. At lower annual volumes (< 25,000 tons per year), composting
systems featuring specialized equipment like compost turners and shredders are
not likely to be cost effective.
To our knowledge, few studies have been conducted on the effects of
season on dairy manure composting. However, Nelson et al., (2006) composted
feedlot manure and showed that during hot dry weather conditions, windrows
lose moisture very rapidly causing the deceleration of the composting process
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when the moisture contents fall below 40%. With excessive rainfall composting
windrows absorb water, and that may result in levels of moisture content higher
than 60%. The large range of moisture, excessive rainfall to drought inflicted on
windrows by the environment can significantly affect the composting process.
Parkinson et al., (2004) investigated the effects of seasonal weather
conditions and the effects of turning regime on nitrogen and phosphorus losses
on the composting of cattle manure. They found that ammonia losses are greater
in wetter conditions compared to colder dry conditions. Larney et al., (2000)
examined active and passive composting of beef feedlot manure during winter
and summer demonstrating that water mass losses were higher in summer and
that high temperature composting is feasible in winter despite sub freezing
ambient air temperatures.
In this study the effects of turning frequency, season and pile size on
composting of dairy manure sawdust (DM+S) on physical, chemical and
molecular parameters were determined.
The hypotheses of the study were that:
• The turning frequency for dairy manure composting in windrows does not
significantly affect final chemical, physical or biological properties of cured
composts.
• Larger piles have lower oxygen concentrations and higher temperatures
than windrows during composting.
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• Composting in cold, wet conditions leads to high moisture contents and
cold compost temperatures that adversely impact the composting process
while composting in warm conditions leads to excess compost drying.
1.2 OBJECTIVES
The overall objective was to evaluate the effects of turning frequency, pile
size, and seasonal weather effects on dairy manure/sawdust (DM+S)
composting. The effects were measured by characterizing the composting
process and finished composts with a series of physical, chemical and molecular
parameters related to compost quality. These included volatile solids, bulk
density, moisture, temperature, nitrogen and carbon losses, oxygen
concentration, particle size, pH, carbon and nitrogen concentrations, plant growth
and microbial community structure. In addition to these analyses, the operating
costs for producing composts were determined. These costs were compared to
the nutrient value of the composts and to the transportation costs for composts,
liquid dairy manure and fertilizer.
Specific objectives were to:
Objective 1. Monitor the effects of turning frequency on temperature and
oxygen profile before and after turning to establish the time of
recovery and the effects of turning.
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Objective 2. Analyze and examine the effects of turning frequency and pile
size on physical parameters such as moisture content, bulk
density, and particle size distribution of DM+S during
composting.
Objective 3. Determine the effects of turning frequency, compost age and
pile size on chemical parameters such as, volatile solids loss,
total and available nutrient levels, pH and compost maturity of
DM+S as a function of compost age.
Objective 4. Calculate the costs, including production expenses and
energy use for on-farm composting of DM+S and suggest
ways to minimize these costs.
Objective 5. Determine the effects of turning frequency, season and pile
size on the microbial community structure in DM+S composts
using terminal restriction fragment length polymorphism (T-
RFLP) and 16S rRNA gene cloning and sequencing analysis.
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CHAPTER 2
LITERATURE REVIEW
2.1 RECYCLING ORGANIC WASTES
Many types of wastes are produced every year, some of which have
potential benefits in agriculture. These wastes are estimated to exceed 1 billion
Mg/yr in the United States alone (Tegtmeier et al., 2005; Karlen et al., 1995).
Increasing environmental awareness and the costs associated with the disposal
of effluents, organic wastes and biosolids has placed greater emphasis on their
beneficial reuse as feedstocks for agronomic purposes (Malcolm et al., 2000).
Although many materials have little potential for reuse due to elevated levels of
salts, heavy metals or toxic organic compounds, municipal wastewater, sewage
sludge, animal manures, byproduct gypsum, yard trimmings, food processing,
paper and pulp wastes have nutrients and organic matter that can be highly
beneficial to crop production as fertilizer substitutes if properly treated.
Composting has been shown to be one method of preparing these wastes for
reuse as a soil amendment (Defoer et al., 2002; Danso et al., 2006).
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2.2 COMPOSTING
2.2.1 Composting Principles and Methods
Recently, interest has increased in the land application of organic residues
that benefit nutrient recycling. Composting (i.e. the aerobic microbial
decomposition of organic materials) can be used to stabilize residues and
promote nutrient recycling (Ellert et al., 1995). Soil regularly amended with
compost is generally able to better hold air and water, drains more efficiently, and
contains a nutrient reserve that plants can draw on (Griffiths et al., 2001; Kostov
et al., 1995). Such soil also tends to produce plants with fewer insect and
disease problems (Steinberg et al., 2006; Iannotti et al., 1994; Hoitink et al.,
1986). The compost encourages a larger population of beneficial soil
microorganisms, which control harmful microorganisms (Gunapala et al., 1998;
Hoitink et al., 1986). It also fosters healthy plant growth, and healthy plants are
better able to resist pests. Other benefits of on-farm composting include having a
saleable product, improved manure handling, improved land application, lowered
risk of pollution and nuisance complaints, the ability to recycle compost as a
bedding substitute, and the ability to charge processing or tipping fees for
producing composts.
Dick and McCoy (1993) reviewed some of the information related to the
effect of compost application on crop production and yield. The paper described
how composts alter specific soil physical, chemical and biological properties.
Crop growth studies demonstrated that the addition of compost improves soil
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fertility resulting in increased production of food and fiber (Suzuki et al., 1990).
Nutrient uptake may be increased by compost additions due strictly to increased
nutrient concentrations in the soil (Suzuki et al., 1990). Changes in soil properties
resulting from compost addition include a decrease in soil bulk density (Tester et
al., 1990; Tester et al., 1989) increased total porosity (Pagliai et al., 1981),
improvements in soil aggregate stability in water (Pagliai et al., 1981), increased
soil organic matter concentrations (Mays et al., 1973), greater water retention
(Tester et al., 1990), higher cation exchange capacity (Dick et al., 1993) and a
decrease in heavy metal concentrations (Dick et al., 1993).
The microbial community is considered the most active fraction of soil
organic matter. It decreases the impact of soilborne plant pathogens (Hoitink et
al., 1986; Dick et al. 1993) is a significant source of plant available nutrient
(Hoitink, et al. 1986), increases soil enzyme activity (Dick et al., 1993; Giusquiani
et al., 1995) and decreases soil redox potential (Epstein et al., 1976).
Composting begins when suitable organic materials are mixed to achieve
a C:N ratio, moisture content and pore space that assures appropriate conditions
for degradation (Illmer et al. 2007; Michel et al., 2004; Tiquia et al., 2002;
Giusquiani et al., 1995; Horwath et al., 1995). The ingredients for composting are
organic by-products or waste materials. On farms such materials may include
animal manure, bedding, crop residues and some processing wastes (Rynk et
al., 1992). The majority of the time; the primary material used is a troublesome
waste needing treatment and/or disposal. The most common materials available
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for farmers include livestock manure (cattle manure, poultry manure, horse
manure, swine manure) (Wilkinson et al., 2005; Ibuki et al., 1999; Kashmanian
et al., 1993; Michel et al., 1996; Rynk, 1994; Tiquia et al., 1997), crop residues
(hay and silage, straw, sawdust, leaves, wood chips, grass clippings) and almost
any organic matter consisting of plant and animal material that is in the process
of decomposing, (Criner et al., 1995; Danso et al., 2006; Giusquiani et al., 1995;
Michel et al., 1996; Michel et al., 1993; Saebo et al., 2006). These manures and
other organic wastes contain naturally occurring microorganisms which catalyze
the breakdown of organic matter and are imperative for rapid composting (Chikae
et al., 2006; Tateda et al., 2005; Defoer, et al 2002; Ibuki et al., 1999; Illmer et al.,
1997; Horwath et al., 1995; Keener, et al 2005; Hogland et al., 2003;
Kashmanian et al., 1993).
Four general groups of composting methods are used on farms: passive
composting, windrows, aerated piles, and a group of methods commonly known
as in-vessel composting. Passive composting simply consists in stacking
feedstocks and leaving them to compost over a long period of time (Larney et al.,
2000). Windrow composting is the production of compost by piling organic matter
or biodegradable waste, like animal manure and crop residues, in long rows
(windrows). Windrow composting is the most commonly used of farm scale
composting methods (Avnimelech et al., 2004).
Aerated pile composting uses a blower to supply air to the composting
material. The blower provides direct control of the process and allows larger piles
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(Larney et al., 2000). In-vessel composting is an industrial form of composting
biodegradable waste that occurs in enclosed reactors. These generally consist of
metal tanks or concrete bunkers in which air flow and temperature can be
controlled.
Passively aerated windrows eliminate the need for turning by supplying
air to the composting material through perforated embedded pipe. However
regular mixing is required. The aerated static pile method takes the piped
aeration system a step further and uses a blower to supply air to the composting
materials (Alexander, 2007; Ibuki et al., 1999; Larney et al., 2000; Rynk et al.,
1992). Larney et al (2000) examined the effects of two composting methods
(active and passive aeration) on physical changes of beef feedlot manure during
winter and summer. This study was carried out during May and October with
passive and active treatments. During the thermophilic phase in winter, the active
treatment showed significantly greater losses in volume and mass than passive
treatment. For the summer study, total mass losses and water losses were
significantly higher with active than with passive composting. In both studies,
higher volume reduction in the active compared to the passive treatment became
apparent in the first 30 days. These results demonstrated that year-round
composting is an option for beef cattle feedlots interested in reducing the volume
of raw manure and producing a product that has lower haulage requirements.
Brodie et al., (2000) studied static and turned windrow technologies at a
commercial site. Their results showed the major difference between the static
12
pile and turned windrow is the amount of energy and labor required. Good quality
compost can be produced for field nursery and landscape use with static piles
and /or machine turned windrows at a cost that can be marginally covered by the
sale of the compost (Operational cost was driven by the cost of compost
ingredients and accounted for 60-70% of the cost in the pilot study).
Hong et al., (1998) and Elwell et al., (2002) evaluated the effects of
continuous aeration (CA) and intermittent aeration (IA) during composting of hog
manure amended with sawdust. They concluded that there is no significant
difference in C:N ratio but IA compared to CA may be a practical way to reduce
nitrogen loss and ammonia emissions during composting. Ammonia emissions
were positively related to air flow rate in these studies, lowering air flow,
particularly during periods of thermophilic activity, offers an option for reducing
ammonia emissions.
In vessel composting studies refers to a group of methods which confine
the composting materials within a building, container or vessel. There are a
variety of in-vessel methods with different combinations of vessels, aeration
devices and turning mechanisms.
In terms of costs, management and process speed, the windrow,
passively aerated windrow, and aerated static pile systems are similar (Rynk et
al., 1994). Windrow composting is more labor-intensive than aerated piles, but
allows a greater choice of amendments, produces more uniform compost and
reduces the need for secondary operations. A major disadvantage is that
13
windrow composting is at the mercy of the weather. Rain, snow, and mud are
more likely to cause problems with windrows and pile systems as compared to in
vessel systems (Rynk et al., 1994)
2.2.2 Factors affecting the composting process
2.2.2.1 Oxygen and Temperature
Composting begins almost immediately as soon as appropriate materials
are piled together. The decomposition of organic matter generates heat and
carbon dioxide and consumes oxygen. As the supply of oxygen decreases,
aerobic decomposition slows and may eventually stop if the oxygen is not
replenished. Thus aeration is continually required to recharge the oxygen supply.
A minimum oxygen concentration of 5% within the pore spaces of the
composting pile is recommended to maintain predominantly aerobic conditions
during composting (Ibuki et al., 1999; Tiquia et al., 1997; Keener et al., 2005;
Hogland et al., 2003).
Keener et al., (2005) used a set of energy and mass balance equations
relating biological and physical factors and compost temperature, moisture,
oxygen level and decomposition rates for aerobic composting. The study focused
on the effects of intermittent aeration on the composting operation. A multi-
parameter kinetic model in conjunction with heat and mass balance equations
was used to predict and optimize the performance of composting (Compost
14
performance is the ability of the final product to stimulate beneficial
characteristics either in soil or plant growth) systems.
Michel et al., (2004) studied the effects of straw and sawdust amendments
on dairy manure composting. Straw amended composts had low initial bulk
densities with high free air space values of 75-93%. This led to lower
temperatures and near ambient interstitial oxygen concentrations during
composting. Sawdust-amended composts, on the other hand, had higher bulk
densities, lower porosities and self-heated to temperatures > 55°C within 10 days
maintaining these levels for more than 60 days. Therefore taking into account the
type of amendment type will help farmers optimize and potentially reduce costs
associated with composting.
Temperature, which hastens reactions if raised, is a strong driving force in
the succession of microbial communities during composting; and since the
release of heat is directly related to the microbial activity (Waksman et al., 1939;
Nelson et al., 2006; Keener et at. 2005; Hogland et al., 2003; Weppen et al.,
2002) temperature is a good process indicator. Composting essentially takes
place within two ranges known as mesophilic (10-40°C) and thermophilic (above
40°C). Most composting takes place at temperatures between 45°C and 65°C.
The thermophilic temperatures result in more rapid decomposition and pathogen
weed seed and fly larvae destruction (Hoitink et al., 1986; Dick et al., 1993; Inbar
et al., 1993; Alexander, 2007; Tateda et al., 2005; Hogland et al., 2003).
15
2.2.2.2 Nutrients, pH and moisture
Carbon (C), nitrogen (N), phosphorus (P) and potassium (K) are the
primary nutrients required by microorganisms involved in composting, as well as
the primary nutrients for plants, influencing the value of compost (Dick et al.,
1993; Wilkinson et al., 2005; Saebo et al., 2006). Almost all organic materials
used for composting contain all of these nutrients at various levels which
microorganisms use for energy and growth. An insufficient or excessive supply of
nutrients may result in low quality compost. Barker et al., (2006) showed that the
beneficial effects of the composts on plant growth were associated with
increased supply of nutrients for the plants. However, excessive supply
decreased shoot plant weight.
C:N ratio has been shown to affect composting rate and the amount of
nitrogen lost during composting. (Illmer et al., 2007; Tiquia et al., 2002; Horwath
et al., 1995; Michel et al., 2004; Ekinci et al., 2000). Michel et al., (2004)
composted freestall dairy manure (83% moisture) with either hardwood sawdust
or straw and composted it for 110-155 days in turned windrows in four replicated
trials that began on different dates. Initial C:N ratios of the windrows ranged from
25:1 to 50:1. Their results showed that at C;N ratios of less than 40:1, large
amounts of N are volatilized, suggesting that an initial C:N ratio of greater than
40 is recommended to minimize nitrogen loss during dairy manure composting
with sawdust or straw amendments.
16
Particle size, nitrogen content, cellulose and lignin content, electrical
conductivity (soluble salts), pH, and inhibitors released by compost are known to
affect incidence of diseases caused by soilborne plant pathogens (Hoitink et al.,
1986). Hoitink and Fahy (1986) reviewed a series of studies that showed that
composting can destroys soilborne plant pathogens. One of these studies
showed that Bacteria and nematodes are more sensitive to heat than most fungal
pathogens. However, the majority of fungal pathogens do not survive the
maturing process after peak heating. Factors other than heat, such as
antagonism, apparently kill fungal pathogens in low- temperature parts of
windrows during curing. While small-scale compost piles may not achieve
adequate temperature-time exposure, commercial scale operations should
achieve effective pathogen kill, if adequate precautions are taken.
Studies to determine the effects of nutrient concentration on the
composting process, such as those performed by Tiquia et al., (2002) who
studied composted swine manure from a hoop house (a mixture of partially
decomposed pig manure and cornstalks from swine fed in hoop structures) are
commonly observed in the literature. Tiquia et al., (2002) investigated C, nutrient,
and mass loss during the composting process. Feeding cycle mass balance
results indicated that N losses from the bedded pack ranged from 24 to 36%.
Results showed that the initial C:N was the most critical factor affecting the N
loss in this composting process. Similarly, Michel et al., (2004) showed that the
17
initial total manure N lost during composting varies according to the amendment
used and initial C:N ratio of the compost.
The composting process is relatively insensitive to pH, within the range
commonly found in mixtures of organic materials, largely because of the broad
spectrum of microorganisms involved. The preferred pH is in the range of 5.5-9.0
(Rynk R et al., 1992; Carnes et al., 1970). pH does become important with raw
materials that have a high percentage of N (Illmer et al., 2007; Tiquia et al., 2002;
Tiquia et al., 1997). A high pH, above 8.5, encourages the conversion of N
compounds to ammonia which further adds to the alkalinity and leads to N losses
due to volatilization (Rynk et al., 1992).
Moisture is necessary to support the metabolic processes of the microbes.
The large range of moisture contents that can occur in outdoor windrows due to
excessive rainfall or drought can significantly affect the composting process
(Nelson et al., 2006). During hot dry weather conditions, composting windrows
lose moisture very rapidly due to evaporation, causing the decceleration of the
composting process when the moisture contents fall below 40% (Michel et al.,
2004). With excessive rainfall, composting windrows absorb water, and that may
result in levels of moisture content greater than 60%. Various studies have been
conducted to investigate the effects of moisture content on the composting
process specifically the compost temperature and energy required to turn the
windrows of different moisture contents (Nelson et al., 2006; Keener et al., 2005).
These studies showed that moisture is an essential parameter to be controlled
18
during composting. Nelson et al., (2006) evaluated the composting of feedlot
manure using three compost windrows which were maintained at each of four
moisture contents (40, 50, 60 and 70% wet basis) to determine the relationships
between moisture content, composting temperatures and the energy required to
turn the windrows. Windrows maintained at 60 and 70% moisture content did not
reach or sustain temperature levels of 55° C. The windrows maintained at 40 and
50% moisture content satisfied the compost process constraints with regard to
temperature as defined by the Canadian Council of Ministers of the Environment.
Windrows maintained at 50% moisture required the least amount of energy to
turn them and achieved the best temperature profile. However the temperature
and energy data suggest a possible threshold, when achieving ideal
temperatures, between 50 and 60% moisture content. Keener et al., (2005)
depict that the moisture content is associated with the ash content. For materials
with high levels of inerts, such paper sludge, the optimum water content should
be based on the non-inert fraction.
2.2.2.3 Porosity, Structure, Texture, Bulk density and Particle Size
Porosity, structure, and particle size affect the composting process by their
influence on aeration. They can be adjusted by the selection of raw materials and
by grinding or mixing (Michel et al., 2004).
Porosity is a measure of the air space within the composting mass and
determines the resistance to airflow. Structure refers to the rigidity of the
19
particles. Good structure prevents the loss of porosity in the moist environment of
the compost pile (Giusquiani et al., 1995).
Most of the aerobic decomposition of composting occurs on the surface of
particles, because oxygen moves readily as a gas through pore spaces but much
slower through the liquid and solid portions of the particles (Rynk et al., 1992).
Smaller particles reduce the effective porosity. Good quality compost is usually
obtained when the particle sizes range from 1/8-2 inch average diameter.
(Hoitink et al., 1986; Michel et al., 1996; ASAE, 2007; Saebo et al., 2006).
2.2.3 Compost quality - maturity and stability
Compost maturity is a critical issue for the use of compost because
immature compost can be detrimental to plant growth and the soil environment
(Wu et al., 2000). Well prepared compost can increase soil quality by decreasing
soil bulk density, increasing soil porosity, water retention and soil organic matter
during the establishment and management phases of plants (Saebo and Ferrini
2006). Descriptions of the quality of the composts must be comprehensive
enough to be able to predict the effect of composts on the growth and
development of plants at the point of use. These include stability, the absence of
unpleasant smell, a low or medium salt content, and absence of polluting
substances or particles inhibiting germination and growth. The specific quality
demands on composts have to be related to nutrient content and particle size in
order to achieve optimal conditions for plant growth (Saebo et al., 2006).
20
Compost stability is assessed by measuring the oxygen uptake rate of
compost under standard moisture and temperature conditions. (Hue et al., 1995).
Iannotti et al., (1994) correlated the oxygen uptake rates of composts prepared
from municipal solid waste (MSW) at a full-scale composting plant to chemical
(pH and total Kjeldahl N), physical (dry solid content), and biological assays
(rygrass growth). Their results showed that respiration bioassays used to
determine stability (O2 and CO2 respirometry) were sensitive to process control
problems, and among all the tests, oxygen respirometry best predicted the
potential for ryegrass growth.
Wu et al., (2000) showed that stability and maturity can be correlated (e.g
more stable compost tends to be more mature). However, due to variations in
compost feedstock and composting processes, some stable compost may have
phytotoxic substances, and some mature compost may have relatively high
respiration rates and be unstable. As a result, both parameters are needed to
assure high quality compost.
2.3 MICROBIOLOGY OF COMPOSTING
Microorganisms are the foundation of the Earth’s biosphere, and play
integral and unique roles in ecosystem function and biogeochemical cycling of
carbon, nitrogen, sulfur and various metals. Because microorganisms play a
central role in decomposing organic matter, the release of mineral nutrients, and
21
in nutrient cycling, they affect soil nutrient contents, chemical-physical properties,
and consequently plant productivity (Liu et al., 2006).
Understanding the complex diversity of the microbial community in the
environment is a challenging task. This is not only because of methodological
limitations, but also because of a lack of taxonomic knowledge (Gunapala et al.,
1998; Steinberg et al., 2006; Liu et al., 2006).
Microbial analyses of compost can serve to confirm pathogen removal
during the composting process (Grewal et al., 2007) and help identify microbial
communities consistent with compost maturity (Annabi et al., 2007; Weppen et
al., 2002). Surveys of microbial communities in mature composts can also be
used to better understand plant-growth promoting bacteria or disease
suppressive microbial populations (Gunapala et al., 1998; Green et al., 2004;
Steinberg et al., 2006).
2.3.1 Microbial community structure
Composting occurs through the efforts of diverse microorganisms. No one
species or organism dominates because the materials and conditions vary from
one pile to the next, over time within a given pile and at different sections of the
pile creating many different localized environments, each populated by a mixed
group of microorganisms (Gunapala et al., 1998; Steinberg et al., 2006).
The types and number of species within a community (species richness)
and the sizes of species populations within a community (species evenness) are
22
the essential parameters for defining community structure and diversity (Liu et
al., 1997; Van Elsas et al., 2000).
Different microbial communities predominate during composting phases,
each of which is adapted to a particular environment (Ryckeboer et al., 2003).
The composition of a microbial community during composting is determined by
many factors. Under aerobic conditions, temperature is the major selective factor
for populations and determines the rate of metabolic activities. While some
authors state that the total number of microorganisms does not significantly
change during composting (Atkinson et al., 1996), other authors report higher
numbers during the mesophilic stage (Ryckeboer et al., 2003; Steinberg et al.,
2006).
Green et al., (2004) analyzed bacterial communities in two cow manure
composts derived from the same feed and composted in the same location, but
composted with different carbon amendments (wheat straw, hardwood sawdust
and wood shavings). The bacterial communities were analyzed with denaturing
gradient gel electrophoresis (DGGE). Results indicate that the effects of the initial
carbon amendment on the mature compost bacterial communities were minor,
while factors such as the manure, composting location, temperature and
moisture may have been more influential on the communities.
Ryckeboer et al., (2003) showed that aerobic decomposition by
microorganisms occurs at a wide moisture range of from 30% to 65%. If moisture
decreases below 30% and temperature rises above 30°C, the substrates become
23
more alkaline and Actinomycetes, and Streptomycetes thrive. Actinomycetes
play an important role in composting by degrading natural polymers and
colonizing organic material left after the other bacteria and fungi have consumed
easily degradable fractions (Peters et al., 2000). When temperature increases
above 55°C, thermal inactivation of pathogens start which is required to obtain
safe products, both in terms of phytohygiene and human diseases (Peters et al.,
2000; Ryckeboer et al., 2003).
2.3.2 Methods for studying microbial community structure
The present level of understanding of microbial community dynamics in
composting processes is largely based on studies made with traditional, culture
based methods. Biochemical based techniques such as plate counts, community
level physiological profiles (CLPP), sole carbon source utilization (SCSU), fatty
acid methyl ester (FAME), phospholipid fatty acid analyses (PLFA) (Klamer et al.,
1998) are traditional methods that are used to study diversity and metabolic
activity (Liu et al., 2006) in some populations. For example, Riddech et al.,
(2002) tested CLPPs with Biolog microplates in a sequence of mature composts
from organic waste and prunings. Their results showed distinctly different
patterns of carbon source utilization identifying five substrates (α-cyclodextrin,
tween 40, D-glucosaminic acid, L-threonine and 4-hydroxybenzoic) that
significantly contributed to difference in CLPPs.
24
However, many microorganisms cannot be cultivated under laboratory
conditions (Green et al., 2004; Gunapala et al., 1998; Liu et al., 1997;
Stackebrandt et al., 1991; Van Elsas et al., 2000). Therefore, in the late
1980s/early 1990s, molecular tools such as nucleic acid hybridization,
polymerase chain reaction (PCR) and DNA cloning and sequencing, were
developed to improve the analysis of microbial communities in environmental
samples (Liu et al., 1997; Van Elsas et al., 2000).
DNA analysis can provide information about the structural diversity of
organisms in environmental samples and the presence or absence of functional
genes. A large and diverse suite of protocols has been published on nucleic acid
extraction from environmental matrices. Van Elsas et al., (2000) discussed one
approach based on direct in situ lysis of microbial cells in the presence of the
environmental matrix followed by separation of the nucleic acids from matrix
components and cell debris. This is by far the most frequently utilized method.
However, directly extracted DNA often contains considerable amounts of co-
extracted substances such as humic acids that interfere with subsequent
molecular analysis (Howeler et al., 2003; Stackebrandt et al., 1991; LaMontagne
et al., 2002).
In another method, microbial cells are separated from the environmental
matrix prior to cell lysis and subsequent DNA extraction and purification. This
method is commonly called ex situ DNA extraction (Stackebrandt, 1991).
25
After the DNA is extracted, molecular-based techniques are applied, such
as nucleic acid hybridization, fluorescent in situ hybridization (FISH), denaturing
gradient gel electrophoresis (DGGE), amplified fragment length polymorphisms
(AFLP), restriction fragment length polymorphism analyses (RFLP and TRFLP),
automated ribosomal intergenic spacer analysis (ARISA) and/or single strand
conformation polymorphism (SSCP) (Kelly, 2003; Liu et al., 2006).
Green et al., (2004) evaluated the bacterial communities in cow manure
composted with different carbon amendments (wheat straw, hardwood sawdust
and wood shavings). Bacterial communities were characterized by PCR-DGGE
(DGGE is based on the melting or denaturation of two complementary DNA
strands, when this happens the electrophoretic mobility of the DNA drops
considerably and a band is formed). Their results demonstrated that bacterial
community profiles of individual composts were highly similar. The microbial
population was minimally affected by different carbon amendments.
Wang et al., (2007) and Halet et al., (2006) investigated the microbial
dynamics of microbial communities during the composting process with DGGE
and plating. Their results showed that the great majority of microorganisms were
bacteria followed by fungi. Hansgate et al., (2005) studied the network of bacteria
and fungi demonstrating that, while the fungal species richness was relatively low
at any time point, the community structure was dynamic and paralleled changes
in bacteria community structure.
26
Klammer et al., (1998) investigated the microbial biomass and community
structure of swine manure/straw composts in reactors and open boxes using
phospholipid fatty acid (PLFA) analysis. Their results showed different PLFA
patterns indicating rapid changes in the microbial community. Gram-positive
bacteria increased rapidly with increasing temperature and decreased with
decreasing temperature. Gram-negative bacteria increased rapidly with
increasing temperature up to 50°C, but decreased during the high temperature
phase. The development of the microbial community was similar during the initial
thermophilic phase, but the communities after 3 months differed. In contrast,
Cooper et al., (2002) studied the resilience of microbial communities to
temperature changes during composting and showed that decomposition
(organic matter breakdown) by thermophilic communities appeared to be less
resilient than that by mesophilic communities. The resilience of compost systems
to perturbation is usually attributed to the highly active and diverse microbial
population. Composting is characterized by distinct temperature changes that are
associated with a succession of microbial communities adapted to the prevailing
temperature (Cooper et al., 2002).
Single strand conformation polymorphism, another technique used for
microbial community analysis, distinguishes DNA molecules of the same size but
of different nucleotide sequences using electrophoresis in a non-denaturing
polycrylamide gel. Peters et al., (2000) directly extracted DNA from compost
samples and used primers targeting 16S rRNA genes (bacteria) and 18S rRNA
27
genes (fungi). Homologous PCR products were converted to single-stranded
DNA molecules by exonuclease digestion and were subsequently
electrophoretically separated by their single-strand-conformation polymorphism
(SSCP). Genetic profiles obtained by this technique showed a succession and
increasing diversity of microbial populations with time using all primers. This
study indicates that community SSCP profiles can be highly useful for the
monitoring of bacterial diversity and community successions in composting.
Terminal Restriction Fragment Length Polymorphism (T-RFLP) is a
molecular biology technique for profiling of microbial communities based on the
position of a restriction site closest to a labeled end of an amplified gene. The
method is based on digesting a mixture of PCR amplified variants of a single
gene using one or more restriction enzymes and detecting the size of each of the
individual resulting terminal fragments using a DNA sequencer. The result is a
graph image where the X axis represents the sizes of the fragments and the Y
axis represents their fluorescence intensity (Liu et al., 1997). It has been used to
describe communities in many different environments including soils (Benitez et
al., 2007), lakes (Kent et al., 2003), activated sludge, groundwater interface, gut
of termites (Liu et al., 1997) and composts (LaMontagne et al., 2002) among
many others. Community analysis by this technique requires DNA isolation, PCR
amplification and digestion to obtain the restriction fragment length, which is
determined by the sequence of the fragment to be digested. Terminal restriction
fragment (T-RF) lengths can be predicted from known sequences; thus, the T-
28
RFLP method can potentially identify specific organisms in a community based
on their T-RF length (Kent et al., 2003). Few studies have been published that
use this technique on compost samples. Michel et al., (2002) studied the
bacterial community structure during yard trimmings composting using TRFLP.
They isolated community DNA from different composting days; the DNA was
PCR –amplified using fluorescent label primers. The products were digested with
HhaI, MspI, and RsaI to give fingerprints of the bacterial communities. Their
results showed that the greatest diversity of bacteria was observed in day 64 and
day 136, showing a diverse group of potentially beneficial plant disease
biocontrol agents in mature composts (day 136). Similarly Tiquia et al., (2002b)
studied the phylogenetic diversity of bacterial communities in livestock manure
composts (in-vessel and windrow composts) using terminal restriction fragment
length polymorphisms. Their results showed an increase in diversity in in-vessel
compost after 21 days of composting, while a decrease in diversity was observed
in the windrow composts after 109 days. Another compost study using T-RFLP
was performed by Tiquia et al., (2002a). T-RFLP analysis of PCR amplified
bacterial 16S rRNA genes from triplicate root tips grown in different treatments
and digested with HhaI, MspI, and RsaI revealed that the T-RFLP pattern of
rhizosphere communities from the bare soil treatment were more similar (54-
82%) to plots mulched with ground wood than to plots mulched with compost.
This data showed that mulching with compost strongly influenced the structure of
the microbial rhizophere community. Liu et al., (1997) discussed the possibility
29
that T-RFLP analysis may permit at least semiquantitative analysis of the relative
proportions of dominant members/genotypes within a microbial community, while
cautioning that T-RFLP analysis is subject to all the biases inherent in any PCR
amplification approach (Kanagawa, 2003).
2.4 CURRENT RESEARCH INTEREST ON COMPOSTING
Composting and marketing of composted materials is one of the options
currently being used by livestock farms to better manage manure and other
wastes. Most composters practice composting for several reasons including
improving manure for on-farm use, easing manure handling problems and
providing additional revenue from compost sales and tipping fees. Farmers take
advantage of composting in different ways, depending on their objective and farm
situation. Most perform their own composting on farm but, several large farms
rely on others to produce and/or sell the compost (Rynk, 1994). Windrow
composting is the predominant method. Manure generated on the farm, plus
bedding materials, are the basic composting materials.
Rynk (1994) performed a survey of dairy farms and found that several
farmers observed improvements in crop yield or quality due to the use of
compost instead of raw manure and/or fertilizer. Many researchers have found
these benefits by studying the process (Inbar et al., 1993; Chikaee et al., 2006;
Jeong et al., 2001; Horwath et al., 1995; Hogland et al., 2003; Weppen et al.,
2003; Alexander, 2004; Halet et al; 2006; Hoitink et al., 1993; Illmer et al; 2007;
30
Keener et al., 2005; Kashmanian et al., 1993). Composting is a microbiological
process which adds a great amount of value to the soil improving crop quality
(Inbar et al., 1993; Chikae et al., 2006; Horwath et al., 1995; Hogland et al.,
2003; Weppen et al., 2002).
Typically, composters base their decisions on experience and
accommodate material mixes according to their situation. Amendments are
either scarce, costly, or avoided because they add to the materials handling
costs and labor. Generally, the on-farm composters have not invested a great
deal of time in optimizing the process. Research in composting is essentially
performed to optimize the process and minimize the costs of production. The
results of this study can be used to minimize costs and optimize the process.
31
CHAPTER 3
EFFECTS ON TURNING FREQUENCY, PILE SIZE AND SEASON ON THE
COMPOSTING OF DAIRY MANURE SAWDUST (DM+S)
3.1 ABSTRACT
Composting offers the potential to significantly reduce problems
associated with manure management including odors, pathogens, ground water
pollution, and utilization costs. Two variables that directly affect on-farm
composting costs are windrow size and windrow turning frequency. However the
size of a windrow is limited by the depth of penetration of oxygen and high
temperatures as well as available equipment. In this study the effects of two pile
sizes and two turning frequencies in two different seasons, winter and summer
2007, on weight loss, volatile solids loss, moisture content, oxygen and
temperature gradients, bulk density, particle size and the costs associated with
the composting of unseparated dairy manure with hardwood sawdust (DM+S)
were examined. Windrows were divided into three replicates for winter and one
replicate for summer. Turning frequency had a significant effect (r > 0.7) on bulk
density, moisture and weight loss but not on volatile solid loss, particle size,
32
oxygen and temperature gradients. There was no significant effect of turning
frequency, pile size or season on the physical and chemical characteristics of the
final cured composts. The bulking agent was the main factor affecting total
operational costs while windrow size and turning frequency had minor effects on
costs. Estimated operational costs for frequently turned windrows were
$20.60/yd3, for infrequently turned windrows $17.89/yd3 and $17.74/yd3 for
infrequently turned piles. The seasonal effects on composting were primarily
related to moisture content, mostly due to ambient temperatures which affect
water holding capacity by air. Results of this study indicate that while variations in
moisture content, temperature and bulk density occurred during the composting
process, final compost properties were very similar regardless of turning
frequency, season or pile size. It can be established that larger and infrequent
turned piles are cost beneficial and are recommended for efficient dairy manure
compost production.
3.2 INTRODUCTION
Composting is a dynamic and complex ecological process in which
temperature; oxygen, pH, moisture content, organic matter and nutrient
availability are in constant flux. Composting is accomplished using a variety of
different systems, which include turned windrows, static piles with forced aeration
and in-vessel systems (Alexander, 2007; Rynk et al., 1992). The process of
composting in any of these is governed by the fundamental principles of heat and
33
mass transfer and by biological constraints on living microorganisms (Keener et
al., 2005; Tirado et al., 2008).
Many physical, chemical, biological and molecular methods have been
developed to monitor the composting process and assess compost quality
(Alexander 2007; Beaffi et al., 2007; Illmer et al 1997; Giusquiani et al., 1995;
Iannoti et al., 1994; Michel et al., 1993). Relatively few studies have focused on
the effects of turning frequency, pile size or season on compost quality or on
mass losses, bulk density, volume and moisture content. Changes in these
properties may affect compost quality (Saebo et al., 2006) and are important
from a transportation or haulage standpoint (Larney et al., 2000).
Windrow size and windrow turning frequency directly affect on-farm
composting costs due to the type of machinery used and the area needed to
construct them. However the size of a windrow is limited by the equipment, the
depth of penetration of oxygen and by high temperatures that develop in the
center of the pile that can inhibit microbial activity (Guo et al., 2007; Halet et al.,
2006; Cooper et al., 2002; Jeong et al., 2001). Turning temporarily mitigates high
temperatures and low oxygen concentrations and is occasionally necessary to
mix the compost to assure even decomposition and pathogen destruction
(Alexander et al., 2007; Nelson et al., 2006; Tateda et al., 2005; Michel et al.,
1996).
In order for composting to be an effective management practice for
manure, it must be a year-round operation. In addition, the cured compost must
34
be uniform with an added value in the market and costs must be optimized to
cover (at least) the operating costs of a compost site.
There is a perceived constraint to winter composting in temperate
climates, where low ambient temperatures may drop below freezing and
composting temperatures, optimal moisture contents and rates may be harder to
maintain.
In this study the effects of two pile sizes, two turning frequencies and two
seasons on volatile solids loss, moisture content, bulk density, oxygen and
temperature gradients as well as the operational costs of producing and the
dollar value of DM+S composts compared to manure and fertilizer were
determined.
3.3. MATERIALS AND METHODS
3.3.1 Experimental treatments
Two full scale compost sets were set-up at the Ohio Agricultural Research
and Developing Center (OARDC) compost pad during winter and summer 2007.
The composts were made from similar initial mixtures (3:1 wet basis) of dairy
manure (OARDC- Heifer Barn-Wooster, Oh) (straw was used as bedding) and
hardwood sawdust (Dalton Wood Products, Inc) similar in properties to those
described previously by Michel et al., (2004). One set of windrows (A) were
turned every three days using a tractor drawn windrow turner for a total of 30
turns during 16 weeks. A second set (B) was turned once every 10 days. A third
35
set (C) consisted of much larger piles turned every 10 days. Windrows were
divided into three replicates in winter and one for each treatment in summer
(Figure 3.1). The approximate dimensions of the windrows were 7.6m long, 1-
1.2m high and 3m wide with an estimated cross-sectional area of 10.7m2. One
pile treatment set per season was also built, with approximate dimensions of 1.5-
2 m high and a base circumference of 22-27m.
Samples (100g) were collected on days zero, 30, 60, 90 and 120.
Samples consisted of mixed composites collected immediately after turning. For
depth studies, 0.03 m3 were also collected from three different depths (5 cm, 60
cm and 120 cm) before turning (Table 3.3).
3.3.2 Weather conditions
Precipitation and daily temperatures were recorded at the Wooster
Experimental Station –Wayne County Lat 40 47 Long 81 55W Elevation 1020ft
(OH ST UNIV-OARDC). Monthly averages are summarized in Table 3.1. Winter
treatments were built starting January 8th 2007; thereafter one replicate for each
treatment was built every week for three weeks to give three replicates (January
22nd). For the summer treatment, all replicates were built during the same week
(August 8th 2007).
36
** Precipitation Temperature total (cm) mean (°C) January,2007 6.73 -2.3 February, 2007 4.11 -8.0 March, 2007 11.18 5.2 April, 2007 8.10 7.6 May, 2007 8.26 16.9 June, 2007 * 7.80 20.5 July, 2007 * 16.64 20.3 August, 2007 14.45 22.2 September, 2007 6.45 18.1 October, 2007 11.81 14.5 November, 2007 8.81 4.4 December, 2007 8.70 0.05
*Experiments were not conducted during these months, ** Data from NOAA/NCDC Table 3.1 Summary of weather data for study period summer and winter 2007
37
1-1.2m Aw Aw Aw
7.6m
BsAs
Bw Bw Bw
7.6m
Cw
CwCw
Cs
1.5-2m
1-1.2m
1.5-2m 1.5-2m
1-1.2m 1-1.2m
1-1.2m 1-1.2m
1-1.2m 1-1.2m 1.5-2m
7.6m
22-27m
22-27m
22-27m22-27m
3m 3m 3m
3m 3m 3m
3m 3m
Figure 3.1 Experimental treatments and dimensions for winter (w) and summer (s). In frequently turned windrows (A), infrequently turned windrows (B) and infrequently turned piles (C). w= Winter, s= Summer
38
3.3.3 Physical Parameters
3.3.3.1 Dimensions- Surface area and volume determinations
The length, height, width and circumference (Figure 3.1) of each windrow
and pile was measured and recorded every time composting materials were
turned to determine differences in volume with turning and age. Cross sectional
area and volumes were calculated by integrating formulas of cones that best
represented windrows and piles.
3.3.3.2 Temperature and oxygen profiles
Pile and windrow temperature profiles were measured manually at three
depths (5cm, 60cm, and 120cm), using a series of portable K-thermocouples
(Omega ®). Oxygen concentrations were determined using a galvanic oxygen
sensor, Model 320A (Teledyne Analytical Instruments) at three depths (5cm,
60cm and 120cm). Oxygen and temperature profiles were measured before and
after turning at 0, 30, 60 and 90 minutes to determine the duration of the effect of
turning.
3.3.3.3 Bulk Density and Moisture Content
The bulk density was determined as described by the US Composting
Council (Thompson et al., 2003). The weight per unit volume of compost was
calculated and reported on a dry weight basis.
39
Moisture content was determined as described by Michel et al., (1993).
Approximately 250g per sample was dried at 70 ± 5°C for 24h to a constant
weight. The percent moisture was calculated as the mass loss due to
evaporation (g/g) divided by the wet weight.
3.3.3.4 Particle size
Particle size was determined using dried compost samples. The method
was performed as described in ASAE Standards S424.1. A set of seven square-
hole sieves were used consisting of numbers 3.5, 6, 10, 14, 20, 35 and 60, with
screen openings of 5.66, 3.36, 2, 1.41, 0.85, 0.5 and 0.246mm, respectively.
3.3.4 Chemical Parameters
3.3.4.1 Volatile solids (Organic matter) and pH
The organic matter was determined according to the US Composting
Council (Thompson et al., 2003) and measured as the fraction of the dry weight
lost when the compost is combusted at 550°C in the presence of excess air (%
g g-1). Compost pH was determined as described by Carnes and Lossin (1970).
Ten grams of compost was added to 100ml of deionized water and pH
determined using a pH electrode and an Orion pH meter.
40
3.3.4.2 Total Carbon, Nitrogen and major elements
Approximately 100 g of wet composite compost samples were sent to the
Service Testing and Research Laboratory (STAR Lab
http://oardc.osu.edu/starlab/ ) at the OARDC Wooster campus for analysis of
total N (Dumas Method), total C (Combustion with CO2 detector) and mineral
analysis (Microwave-Assisted Nitric Acid Digestion, US EPA 3051, plus
Inductively coupled mass spectrometry-ICP analysis). Test methods for the
examination of composting were performed according to the US Composting
council (Thompson et al., 2003) (Table 3.3).
3.3.5 Energy Inputs and Farm Composting Economics
Production costs and fuel use for cured compost were estimated based on
amendment costs, the machinery used (Table 3.4), turning frequency, labor and
transportation costs. Operational costs for frequently and infrequently turned
composts were calculated according to the time of turning, the labor needed and
the machinery used (Table 3.4). According to Grisso et al., 2004 the operating
costs for the agricultural machines depend on the type of fuel, the amount of time
the machine is used and the amount of work accomplished relative to the cost
incurred in getting the work done. Grisso et al., reports the fuel efficiency of
different types of engines and the optimum travel speed for a given operation;
Table 3.4 shows the values for each machine used in this study. Hauling costs
41
were estimated assuming 30 mph travel speed, hauled material with 40%
moisture, average diesel price ($4.15/gal), and a rate of labor of $15.00/hour.
Compost, fertilizer (15:15:15) and manure values were calculated based
on the N:P:K contents of the compost, using STARLab results. Hauling costs
were estimated assuming 80% moisture content for manure (Michel et al., 2004),
40% for compost and 10% for fertilizer.
Type* of
machinery Capacity Gal/tank
Engine Power
(Gross-hp) Max
Mile/h Fuel type
gal/h **
$/gal *** $/h
I 140 250 45 diesel 13.91 4.15 57.7II 18 80 20 diesel 4.96 4.15 20.6III 20 51 6 diesel 4.19 4.15 17.4IV 18 80 20 diesel 4.96 4.15 20.6
* I Medium Duty Dump truck Class 1-3 GVW, II Aereomaster MidWest PT120+Truck Hydrostatic drive Farmall 1026, III CASE 1840 Wheel Skid Steer Loader, IV Butler 3340 ensilmixer+Truck Hydrostatic drive Farmall 1026 *** Average price of gas (May, 2008) Table 3.2 Machinery used to build, turn and composite frequently turned windrows (A), infrequently turned windrows (B) and piles (C) during this study and its respectively fuel efficiency (Grisso R.D., 2004) 3.3.6 Statistical Analysis
All statistical analyses were performed using MINITAB (ver 15.1) from
MINITAB, Inc. Plots were made using SIGMAPLOT (ver. 10.0) from TE Sub
Systems Inc. Standard one way analysis of variance was used to determine
differences in treatments, while mean comparisons among treatments and
42
seasons were performed using Fisher’s protected least significance difference
test (5% level). Correlation analysis between random variables was performed
using Pearson product moment and Spearman R for categorical variables.
Discrete (turning frequency), continuous (compost temperature, pH, bulk density,
volatile solids, moisture content and particle size) and categorical (season and
pile size) variables were used to make the comparisons.
43
3.4 RESULTS AND DISCUSSION
3.4.1 Effects of turning frequency
Dairy manure sawdust was composted for 120 days. To determine the
effects of turning, windrows turned frequently and infrequently were compared.
Total Mass and volume reductions
At the beginning of the composting process, the total volume varied from
40-25 m3 in the frequently and infrequently turned windrows, with an initial
surface area to volume ratio of 1.55 ± 0.4 m2/m3 for winter and 1.74 ± 0.9 m2/m3
in summer.
Cumulative volume reductions appear to be greater during winter than
summer (Table 3.3). A cumulative volume reduction of 63% for the frequently
turned windrow (A) during winter was the highest followed by the infrequently
turned windrow in summer (B) (47%). Although cumulative volume reduction was
higher for the frequently turned windrows, the rate of volume reduction for each
treatment in both seasons did not differ significantly after the composting process
(p > 0.150).
There was a highly significant relationship (r >0.95) between the number
of turnings and volume reduction for frequently turned windrow (A) in both
seasons during composting (Table 3.5). This relationship showed that windrow
turning had a greater negative impact on volume reduction than infrequently
turned windrows. This result is similar to the observations reported by Michel et
44
al., (1996) who observed that the effects of turning regime are transient and
present similar trends in different windrow and pile configurations.
Composting significantly reduced compost mass weight. Wet mass losses
during the composting process reached 67% (winter) for frequently turned
windrows, and for the infrequently turned composts mass losses ranged from 44
to 62% (Table 3.3).
The numbers of turnings directly affected mass losses. The frequently
turned windrows appeared to have greater losses (r > -0.98) compared to the
infrequently turned windrows (r > -0.68). There was a significant difference in
overall mass loss (p < 0.05) between frequently and infrequently turned
windrows. This difference was not an effect of moisture content since dry mass
losses were also greater than wet mass losses in the frequently turned windrows
(Table 3.3, Table 3.5).
Surface area
The surface area of the windrows, during winter was slightly higher (50-
70m2) than those windrows built in summer (35-50 m2). The greatest effect in the
percentage of cumulative surface area loss was observed in frequently turned
windrows (r > 0.95). The surface area during composting showed no significant
difference between treatments (p > 0.06); but, between seasons there was
significant difference (p < 0.005; α= 0.05) (Table 3.5).
45
Temperature and Oxygen gradients
Compost heat is produced as a by-product of the microbial breakdown of
organic material. The heat production depends on the size of the pile, its
moisture content, aeration, and C/N ratio. Additionally, ambient temperature
affects compost temperatures. According to Keener et al (2005) consistent
performance of composting systems to generate high quality compost requires
controlled process conditions, such as temperature (ranges vary from 35 to
60°C), oxygen (> 5%) and mixing. The optimal compost temperatures from the
standpoint of pathogen destruction and organic matter decomposition are 55-
60°C (Hoitink et al., 1986; Dick et al., 1993; Inbar et al., 1993; Alexander, 2007;
Tateda et al., 2005; Michel et al 2004; Hogland et al., 2003; Grewal et al., 2007).
According to these parameters, windrows and piles in this study were
grouped into six different temperature ranges (from -1 to 15°C, 15.1 to 31.1°C,
31.2 to 47.2°C, 47.3 to 63.3°C, 63.4 to 79.3°C, 79.4 to 95.4°C) and groups with
oxygen concentrations greater than 5%. Optimal composting conditions were
considered to be temperatures of 35°C to 60°C and oxygen concentrations
greater than 5%. These, to determine the frequency of dates that had optimal
composting conditions. Optimal temperatures were reached in the majority (>
70%) of the composting periods in all treatments for both seasons.
Turning frequency had little effect on windrow temperature and oxygen
gradients. Compost temperatures at the center of the windrows (120 cm) rose to
greater than 55°C after 10 days in both treatments (Figure 3.2). At depths closer
46
to the surface (5 and 60 cm) temperatures were lower and appeared to be
influenced by turning frequency. Temperatures at these levels were higher in the
infrequently turned windrows.
There was a significant relationship (r > 0.80) between oxygen
concentration at the center of the windrows and the number of turnings during
summer (Table 3.5). However, overall, turning had only a transitory effect on
compost oxygen concentrations; two hours after turning oxygen concentrations
were similar to levels before turning (Figure 3.3). Overall, the different turning
frequencies used in this study did not appear to have a great impact on compost
temperatures or oxygen concentrations during the process (p > 0.05).
Bulk Density
Initial bulk density varied between 117-142 kg/m3 and rose during
composting to 143 to 182 kg/m3. There was a small difference in final bulk
densities between frequently turned windrows as compared to the infrequently
turned (Table 3.3); this difference can be attributed to the chopping and mixing
action of the windrow turner which may have accelerated the breakdown of straw
fragments, hence reducing air space and increasing bulk density. Our values are
similar to those reported by Larney et al., (2000) who reported final bulk density
values ranging from 170 to 290 kg/m3 for the composting of similar feedstocks.
47
A higher correlation between bulk density in windrows (A and B) and
turning frequency was observed during winter (r > 0.85) than between windrows
in summer (r < - 0.75) (Table 3.5).
Moisture Contents
Initial moisture contents were 62-68% (Table 3.3). Final moisture contents
for the frequently turned windrows (≤ 70%) where higher than those observed for
the infrequently turned windrows (≥ 59%). However these differences did not
appear to be significant (p > 0.5) (Table 3.5).
Particle Size
Particle sizes during composting (day zero thorough day 120) were 2.15 ±
0.82 mm in the frequently turned windrows and 2.25 ± 0.81 mm for the
infrequently turned windrows. The particle size in the frequently turned windrows
showed lower values during the composting process (day zero thorough day
120) than those observed in the infrequently turned windrows (Table 3.3).
No correlation was observed between particle size and turning frequency
with an r= 0.19 for frequently turned windrows and r= -0.12 for infrequently turned
windrows (Table 3.5).
48
A* Frequently turned
windrow
B* Infrequently turned
windrow
C* Infrequently turned
pile Winter Summer Winter Summer Winter Summer Surface Initial 69.3±5.5 48 51.6±14.2 51 42.7±0.7 34.4 Area (m2) Final 33.6 43 46.9 38 30.6 29.3 Reduction 51% 10% 19% 25% 28% 15% Volume Initial 38.8±2.8 24.40 37.5±7.2 23.70 43±1.2 31.20 (m3) Final 14.3±0.9 15.40 21.80±0.5 12.50 25.50±0.5 24.50 Reduction 63% 37% 21% 47% 41% 21% Surface Area Initial 1.78 1.96 1.87 2.15 0.99 1.1 to volume Ratio Final 2.35 2.79 2.15 3.02 1.2 1.2 Wet Mass Initial 6145±522 3992 6152±501 3919 6424±29 3909 (kg) Final 2026±200 2531 2331±527 1923 3115±141 2195 Loss 67% 37% 62% 51% 52% 44% Dry Mass Initial 2129±181 1709 1951±159 1697 2177±10 1732 (kg) Final 643±63 734 691±156 785 1013±46 676 Loss 70% 57% 65% 54% 53% 61% Bulk Density a,b Initial 125 127 122 135 117 143 (kg/m3) Final 176 146 170 151 143 182 Moisture Initial 65.4±2.2 61.9 68.3±4.4 60.3 66.1±2.0 58.2 (%) Final 68.8±4.4 71.0 70.4±5.9 59.2 67.5±7.8 69.2 pH Initial 8.25±1.07 7.85 8.59±0.01 8.1 8.35±0.29 8.2 Final 8.62±0.17 7.24 8.17±1.00 7.2 7.94±0.09 7.4 Carbon b, c Initial 52.75±3.33 50.56±2.60 52.75±3.33 50.56±2.60 52.75±3.33 50.56±2.60(%) Final 41.35 44.50 45.01 43.09 44.71 44.16 loss 76% 62% 70% 61% 61% 66% C:N Initial 37.61 37.31 37.61 37.31 37.61 37.31 Final 15.1 24.4 17.6 21.4 17.4 21.7 Nitrogen b, c Initial 1.40±0.18 1.35±0.10 1.40±0.18 1.35±0.10 1.40±0.18 1.35±0.10 % g/g dw Final 2.74 1.82 2.55 2.01 2.57 2.03 Loss 41% 42% 35% 31% 15% 41% Volatile Initial 94.2±1.5 93.10 92.8±2.8 93.80 93.8±0.4 93.5 Solids a Final 76.5±3.4 80.10 76.2±10 72.20 69.1±22.5 76.2 (g/ginitial) Loss 75% 63% 71% 64% 66% 68% Particle size Initial 2.4±1.0 1.7 3.2±1.5 1.6 1.7±0.2 0.9 (mm) Final 2.6±0.7 1.9±0.2 1.9±0.6 2.0±0.3 1.9±1.7 2.9±0.9
a Dry weight basis b Composite samples c Analysis performed in StarLab * A frequently turned windrow (Every three days), B infrequently turned windrow (every 10 days), C infrequently turned piled (every ten days Table 3.3 Initial and Final compost properties performed in this study, for frequently turned windrows (A), infrequently turned windrows (B) and piles (C).
49
Volatile Solid Loss, Nitrogen Loss and pH
The volatile solid losses, calculated assuming constant ash, reached 25%
loss on day 30 (for frequently and infrequently turned) and increased to 63-75%
in the final cured compost for both windrows, regardless of turning frequency (p >
0.4) .
Frequently turned windrows had higher N losses (40%) than those
windrows turned infrequently (30%) (Table 3.3). Turning exposes fresh material
to microbial colonization and leads to the release of NH3 that has accumulated in
the internal void spaces of the compost (Parkinson et al., 2004; Ogunwande et
al., 2008).
According to Wu et al., (2000), Inbar et al., (1993), Alexander et al., (2007)
and Michel et al., (1996), compost pH varies between 7.0 to 9.2. There was no
significant pH difference among turning frequencies (p > 0.5) (Table 3.3 and 3.4).
For the frequently turned windrows, pH during composting was 8.2 ± 0.4 and for
infrequently turned 8.1 ± 0.5. The alkaline values obtained in this study may
contribute to nitrogen losses and ammonia odors during composting because
above pH 8.2, ammonia nitrogen becomes volatile (Michel et al., 1996).
However Ekinci et al., (2000) showed a 75% reduction in ammonia loss by
lowering initial pH from 8.3 to 6.6; verifying that lowering initial pH with additives
can be an important factor for ammonia control.
50
Winter
0
50
0 20 40 60 80 100 120
As Bs Cs Aw Bw Cw
2 ho
urs A
fter
Tur
ning
Im
med
iate
ly A
fter
Bef
ore
Tur
ning
Im
med
iate
ly A
fter
Bef
ore
Tur
ning
O
xyge
n C
once
ntra
tion
(%)
Oxy
gen
Con
cent
ratio
n (%
)
-5
0
5
10
15
20
0 30 60 90 12
Figure 3.2 Oxygen concentrations in frequently turned windrows (A), infrequently turned windrows (B) and piles (C), before, immediately after and 2 hours after turning (120cm depth).
Figure 3.2 Oxygen concentrations in frequently turned windrows (A), infrequently turned windrows (B) and piles (C), before, immediately after and 2 hours after turning (120cm depth).
Time (days)
0-5
0
5
10
15
20
0 30 60 90 12
Winter Summer
0
-5
0
5
10
15
20
0 30 60 90 120
-5
0
5
10
15
20
0 30 60 90 120
-5
0
5
10
15
20
0 30 60 90 120-5
0
5
10
15
20
0 30 60 90 120
Frequently turned windrow (Every three days), Infrequently turned windrow (every 10 days), Infrequently turned pile (every 10 days). w=winter, s=summer
51
2 ho
urs A
fter
Tur
ning
Im
med
iate
ly A
fter
Bef
ore
Tur
ning
T
empe
ratu
re °C
Winter
0
50
0 20 40 60 80 100 120
As Bs Cs Aw Bw Cw
Figure 3.3 Temperatures (°C) in frequently turned windrows (A), infrequently turned windrows (B) and piles (C), before, immediately after and 2 hours after turning (120 cm depth).
0
10
20
30
40
50
60
70
80
0 30 60 90 120
0
10
20
30
40
50
60
70
80
Winter Summer
0 30 60 90 120
0
10
20
30
40
50
60
70
80
0 30 60 90 120
0
10
20
30
40
50
60
70
80
0 30 60 90 120
0
10
20
30
40
50
60
70
80
0 30 60 90 12
0
10
20
30
40
50
60
70
80
0 30 60 90 1200
Time (days)
Frequently turned windrow (Every three days), Infrequently turned windrow (every 10 days), Infrequently turned pile (every 10 days). w=winter, s=summer
52
3.4.2 Effects of pile size in composting To determine the effects of pile size, infrequently turned windrows were
compared to larger infrequently turned piles.
Total Mass The primary differences between windrows and piles used in this study
were the surface area to volume ratios. The surface area to volume ratios for
windrows ranged from 1.7 to 2.0 m2/m3, while for piles the surface to volume
ratios was 0.99 to 1.1 m2/m3 (Table 3.3). The windrows and piles were built with
a mix ratio of 3:1 (DM+S) on a wet basis. Dry mass losses for piles were ≥ 53%
and for windrows ≥ 54%, suggesting similar losses for windrows and piles.
Temperature and Oxygen gradients
The temperature and oxygen concentrations in the pile were significantly
different (p < 0.05) than those effects observed in the windrows (p > 0.1). In the
piles (C), the temperatures rose from 2.49°C ± 2.36 to 43.6°C ± 9.63 from day
zero to day 30, and remained above 40°C through day 120 (Figure 3.2). Piles
maintained lower oxygen concentration (range from 5 to 12% of oxygen) than the
windrows (>10%) (Figure 3.3) in both summer and winter replicates.
There was a significant relationship (r > 0.80) between oxygen
concentrations and windrow size during summer. The windrows during winter
showed a small negative correlation between size and oxygen (r < -0.15), which
53
might be the result of higher moisture content (Figure 3.4). For the piles the
relationship was less (r < 0.60) which may suggest a difference in oxygen
concentrations with pile size, but not turning frequency (Table 3.3, Table 3.5).
Bulk Density
The bulk density in the piles during the composting process rose from
117-143 kg/m3 to 143-182 kg/m3 on day 120. For the windrows initial bulk density
was 122-135 kg/m3 and increased to 170-151 kg/m3 (Table 3.3, Table 3.5). This
finding is similar to those observed by Michel et al., 1996, who observed gradual
increase in compost bulk density as a function of turning frequency to a similar
level as those observed in piles and windrows in this study.
Moisture Contents
Moisture contents were not significantly different between windrows and
piles (p > 0.5) (Figure 3.3). Pile moisture contents during composting showed
slightly higher values (64.6 ± 7%) than those observed in the windrows (63.7 ±
10%). During winter and summer, windrows (60-75%) and piles (58-72%)
presented similar values (Table 3.3).
54
A* Frequently turned
windrow
B* Infrequently turned
windrow
C* Infrequently turned
pile Depth Winter Summer Winter Summer Winter Summer
5cm 8.2 8.6 9.09 8.4 8.3 7.9 pH 60cm 7.9 8.6 8.6 8.4 8.8 7.9
120cm 8.9 8.7 8.85 8.3 8.3 8.4 5cm 44.1 52.3 18.5 50.2 41.3 48.2
Temperature 60cm 43.8 48.3 34.8 46.7 49.9 46.3 (°C) 120cm 46.5 54.2 35.1 46.1 41.7 24.5
5cm 16.0 17.0 17.0 18.0 13.7 17.0 Oxygen 60cm 15.0 17.0 ** 18.0 0.75 16.5
% 120cm 8.0 17.0 14.5 17.0 0.0 18.5 5cm 71.6 48.8 74.5 48.3 72.9 49.6
Moisture 60cm 66.7 54.4 67.7 49.4 62.6 63.1 % 120cm 66.9 54.4 67.8 52.6 65.6 67.9
Table 3.4 Effect of depth on temperature (°C), pH and oxygen concentrations (%) for winter and summer on day 30. In frequently turned windrow (A-Every three days), infrequently turned windrow (B-Every 10 days) and infrequently turned pile (C-Every 10 days). ** Missing data Particle Size
During composting (day zero thorough day 120), windrows had similar
particle sizes (2.2 ± 0.8mm) as piles (2.0 ± 0.7mm) (Table 3.3), There was no
significant difference between pile size and particle size (p > 0.150) in the final
cured composts. However there was a greater range of particle sizes (higher
heterogeneity) in the piles as compared to the windrows (Table 3.3, Table 3.5).
55
Volatile Solid Loss, Nitrogen Loss and pH
Volatile solid loss did not vary significantly between windrows (60-75%)
and piles (66-68%) during the composting process. The volatile solids content
loss from the composting material during the composting process reflects the
amount of organic material converted to CO2 during composting.
Nitrogen losses during both seasons for windrows varied from 31-35%, for
piles it was significantly different between seasons with 41% and 15% in
summer and winter respectively; these differences suggest an effect of season
but not pile size (Table 3.3, Table 3.5).
In the thermophilic phase of composting (day 30), pH varied (8.43 ± 0.34)
between depths 5cm, 60cm and 120 cm (Table 3.3). However these variations
were not significant (p > 0.05) (Table 3.5)
3.4.3 Seasonal Effects
The effects of season variability during composting was determined by
comparing compost characteristics in winter and summer in frequently turned (A)
infrequently turned (B) windrows and piles (C).
Total Mass
In summer, the greatest dry mass loss was in the infrequently turned pile (61%);
followed by frequently turned windrow (57%) and the infrequently turned windrow
56
(54%). During winter, the greatest dry mass loss was observed for the frequently
turned windrow (70%). Dry and wet weigh losses are shown in Table 3.3.
The greater dry mass loss observed in the summer pile compared to the
pile in winter may be due to the effect that in summer the piles were wetter than
the windrows in summer, allowing more extensive degradation (Table 3.3, Table
3.5). In winter, the piles and windrows all had similar higher moisture contents
(Figure 3.4). The piles also had lower oxygen concentrations (Figure 3.3) during
winter which may have limited decomposition.
Temperature and Oxygen gradients
On day zero of the winter season the average daily ambient temperature
was -0.6°C; during composting in the winter season daily average temperatures
varied from -23.4 (day 38) to 25°C (day 86) with an average relative humidity of
65%. Temperatures below freezing were present during days 10-60 (winter-
spring, January through March); after day 60 (until day 90) daily ambient
temperatures rose to levels similar than those in summer-autumn (Figure 3.5);
from day 90 (March-April) until day 120 (May) daily ambient temperatures in
winter-spring treatment were higher than those in summer-autumn treatments.
For the summer study initial ambient temperature was 26°C and varied from
34°C (day 1) to -7.8°C (day 119) with an average relative humidity of 75%. On
day 60 (August) until day 90 (October), summer-autumn ambient temperatures
decreased to temperatures similar to those in winter (10-0°C).
57
Compost temperatures rose to greater than 50°C after 30 days in both
winter and summer treatments. Final temperatures in summer (15 ± 11°C) were
somewhat lower than in winter (32 ± 17°C). Even though average daily
temperatures varied between seasons, windrow and pile temperatures during
winter and summer rose to levels higher than 30˚C after day 5, increasing
thereafter (52 ± 10˚C) until day 90 in winter and day 110 in summer. Final
temperature (day 120) in the frequently turned windrows in winter-spring
(05/10/07) was 13˚C and in summer-autumn 5.2˚C (12/19/07). The piles seemed
to maintain higher temperatures at the end with 47˚C and 31˚C for winter and
summer respectively.
For the summer-autumn study there was a significant difference in
compost temperatures (p < 0.05), whereas there was no difference between
treatments for the winter-spring study (p > 0.3) (Table 3.5).
Bulk Density
For the winter study, bulk density on day zero varied from 117 kg/m3 to
122 kg/m3. It was necessary to construct compost piles at different times during
the winter treatment and the bulk density variation can be explained by the
amount of straw bedding that was included during construction. Average bulk
density during winter composting varied from 119 kg/m3 in the pile to 131 kg/m3
in the windrows. By the end of the curing phase, bulk density had increased to
greater than 160 kg/m3 in all treatments.
58
For the summer study, initial bulk densities in all treatments were similar
(135 ± 8 kg/m3). Average bulk density during summer composting varied from
100 to 190 kg/m3 (Table 3.3). Final values ranged between 140 and 180 kg/m3.
Moisture Contents
The initial moisture contents of the compost treatments were 60-70% in
both seasons which are optimal for composting (Rynk, 1992). At the end of the
composting period, of both seasons, moisture reached values of 67.6 ± 4.32 %.
A winter storm (Table 3.1) on day 20-30 increased compost moisture to 70%. A
small amount of sawdust (Approximately 130kg per treatment) was added to the
windrows on day 28 which reduced the moisture content from 70% to 69%.
Due to high precipitations during winter (recorded precipitation of the
weather conditions showed an increase during dates 60-65), moisture content
rose similarly in all three treatments to approximately 75% after 60 days (Figure
3.4).
Geotextile (Midwest Biosystems) covers were used after the winter storm
to reduce water infiltration from precipitation. This material is permeable to air
and gas, but water-repellent. Covers were left on the compost the rest of the
cycle, being removed only for turning operations. Moisture content during the
summer replicate decreased to levels below 45% indicating a need for addition of
water in all treatments. On day 64 water addition of 130, 95 and 62 gal were
added to A, B and C respectively to maintain adequate moisture (60%) (Keener
59
et al., 2005). The amount of water was added according to a mass balance
(Figure 3.4).
A medium linear relationship (r > 0.5) between the number of turnings and
moisture was observed indicating an effect of turning on moisture content.
Moisture content was highly correlated with windrow temperature during winter (r
> 0.7). During the curing phase, approximately on day 90, moisture contents in
both seasons dropped from 70% to 55%. Even though different moisture
contents were observed during the composting period, cured compost of more
than 120 days for all treatments showed similar values (45 ± 4.5%) (p > 0.6)
(Data not shown).
The average pile moistures during winter were slightly lower (68.57% ±
2.6) for piles compared to the windrows (70.3 ± 3.0%) but not significantly
different (p > 0.5) (Figure 3.4, Table 3.5). During summer the variation was
opposite. Piles maintained a higher moisture content (60.6 ± 7.8%) than
windrows (57.0 ± 9%). These variations may be correlated to weather conditions
and surface to volume area ratios (Table 3.3, Figure 3.4).
The total cumulative precipitation during winter was 33.81cm (Table 3.1).
The highest recorded precipitation occurred in March (11cm) followed by January
(9.8cm). During the summer treatment the total cumulative precipitation reached
45.69 cm with a highest precipitation of 14.4 cm during August and a lowest
precipitation of 6.4 cm in September (Figure 3.4). Although precipitation during
60
the summer study was higher (50cm) moisture contents were lower due to higher
evaporation rates.
The temperature at any point during composting depends on how much
heat is being produced by microorganisms, balanced by how much is being lost
through conduction, convection, and radiation (Richard et al., 1996). Conduction
occurs at the bottom of the compost pile into the concrete pad. Convection refers
to transfer of heat by movement of a fluid such as air or water. When compost
gets hot, warm air rises within the system, and the resulting convective currents
cause a steady but slow movement of heated moist air upwards through the
compost and out the top. In addition to this natural convection, turning adds a
forced convection (Richard et al., 1996).
In winter moisture in the air leaving the compost will condense as it leaves
the windrow. In summer high ambient temperatures allow much greater amounts
of water vapor to escape by convection. However according to Richard et al.,
(1996) the heat removal due to water evaporation (about 70%) is the largest heat
removal source, radiation (about 20%) is the second, and convection (about
10%).
61
0
10
20
30
40
50
60
70
80
0 30 60 90 120
Time (days)
% M
oistu
re
0
5
10
15
20
25
30
35
40
45
50
Dai
ly P
reci
pita
tion
(cm
Day 30 Sawdust addition (A, B)
Day 64 Water addition (A, B, C)
0
1 0
2 0
3 0
4 0
5 0
6 0
7 0
8 0
0 3 0 6 0 9 0 1 2 0Time (d a ys)
0
1 0
2 0
3 0
4 0
5 0Aw BwCw AsBs CsCumulative precipitation (cm)-Summer Cumulative precipitation (cm)-Winter
Frequently turned windrow (Every three days), Infrequently turned windrow (every 10 days), Infrequently turned pile (every 10 days). w=winter, s=summer
Figure 3.4 Moisture Content and cumulative precipitations during winter (w) and summer (s) for frequently turned widrows (A), infrequently turned windrows (B) and piles (C).
62
-20
-15
-10
-5
0
5
10
15
20
25
30
0 30 60 90 120
Time (days)
Tem
pera
ture
( C
)
Summer Winter
Winter Day zero =Julian day 008, day 120= Julian date 125; Summer day zero = Julian date 220, day 120 = Julian date 340 (2007)
Figure 3.5 Day-by-day average daily temperatures during the composting process (Wooster Experimental Station, OSU/OARDC).
Particle Size
There was a significant difference between season and particle size (p <
0.05) during the composting process. These differences can be attributed to the
amount of straw fragments incorporated in the initial mixture. Initial particle size
for winter (2.4 ± 0.7mm) was higher than summer (1.4 ± 0.3 mm). Average final
particle sizes varied from 2.62 ± 0.74 mm in winter and 1.67 ± 0.46 mm in
summer.
63
Volatile Solid Loss, Nitrogen Loss and pH
Volatile solids did not appear to be influence by season (p = 0.9). Volatile
solid losses at the end of the composting process were 60 ± 7% in winter and
summer.
Infrequently turned windrows, during winter, had higher nitrogen losses
(35%) compared to those in summer (31%). For the frequently turned windrows
and the piles nitrogen losses were higher in summer compared to those in winter
which may be correlated to the exposure of the piles to direct sunlight which may
have accelerated the decomposition and loss of valuable nutrients (Ogunwande
et al., 2008).
Initial pH values were similar between winter (8.39 ± 0.17) and summer
(8.04 ± 0.11) treatments, but final pH values were significantly (p < 0.05) higher
in winter (8.2 ± 0.34) than in summer (7.28 ± 0.12). These differences can be
attributed to ambient and compost temperatures (Barron and Geary 2008) as
discussed previously (pile size effects). According to Barron and Geary (2008),
pH is a measure of the hydrogen ion concentration, and a change in the
temperature will be reflected by a subsequent change in pH. In this study there
was no significant correlation between pH and compost temperature of windrows
and piles during winter (r < 0.40). However, there was a slight correlation of pH
and temperatures in piles and windrows during summer (r > 0.50) (Table 3.5).
64
Pile Size* Turning Frequency* Season*
P
value CorrelationP
value Correlation P
value Correlation
Properties α = 0.05 ( r )
α = 0.05 ( r )
α = 0.05 ( r )
Volume 0.8 < -0.97 > 0.15 > 0.95 0.04 > 0.95
Area < 0.05 < -0.99 > 0.06 > 0.90 0.005 > 0.93 Mass > 0.05 > 0.7 < 0.05 > -0.7 0.05 > 0.8, > 0.7
Temperature > 0.05 > 0.8 > 0.05 0.73, -0.46 >0.3,
< 0.05 > 0.7, < -0.4
Oxygen < 0.05 > 0.80 > 0.05 > 0.80 0 Wi= <-0.12 (w),
>0.76 (s);
Pile= >0.7(w);
>0.28(s)
Bulk Density < 0.05 > 0.30 < 0.05 >0.85, <-
0.75 0 > 0.60(w), < 0.3
(s) Moisture > 0.5 > 0.50 > 0.5 < 0.20 0 < -0.683
Particle Size > 0.15 < -0.39 > 0.5 < 0.19 0.05 < -0.62 Volatile Solids > 0.05 -- > 0.4 < -0.54 0.9 --
pH > 0.05 -- > 0.5 < -0.18 0.005 < 0.4, > 0.5 Total Nitrogen 0.05 -- < 0.05 > 0.58 < 0.05 > 0.20
Dry Weight > 0.15 -- > 0.15 -- 0.03, 0.43 --
Microbial Community > 0.1 -- > 0.1 -- 0.1 --
*Values during the composting process, final cured compost significance are different (p > 0.05). Table 3.5 Effects of Management practices (pile size, turning frequency and season) during the composting process (from day zero through day 120) with p values (α= 0.05) and correlation coefficients.
The management practices did not appear to significantly affect final cured
compost properties (p > 0.05).
65
3.4.4 Energy Inputs and Farm Composting Economics
The costs of producing compost can be offset by the value of composts in
the marketplace. This value is due not only to nutrients but the ability of compost
to reduce plant diseases and improve soil physical properties (Michel, 2002;
Hoitink et al., 1993).
In this study the size and the turning frequency of the composting
treatment affected total operating costs. Capital costs would add to total compost
costs but were not considered in this study.
Approximately $ 99.29 ± 8.57 per Mg (value depends on turning
frequency) U.S dollars were spent on operational costs to produce final cured
compost (Table 3.6).
The costs of transporting and application of solid or semi-solid manure
and composts vary greatly within the different states and between countries.
Custom haulers usually charge by load regardless of tonnage. A common
practice is to charge by load up to one or two miles radius and from there charge
on a per-mile bases. When custom haulers or farm owners haul compost their
major limiting factor is volume. So haulers usually charge by cubic yard of
compost regardless of tonnage. In this study operational cost calculations were
made according to the costs of amendments (sawdust/manure 3:1), rental of
agricultural machinery, size and load per machine, type of machinery, fuel
efficiency (Table 3.2), average local fuel prices, travel speed, distance hauled,
time of turning, and labor; assuming an initial compost moisture of 60% a final
66
moisture of 40% and mass weight loss of 70%. An average hauling cost on a per
mile basis was determined (Table 3.7).
When hauling solid stockpiled manure or semi-solid manure the moisture
content will vary according to the manure handling system, bedding material
used, meteorological conditions, storage type, how long that manure has been
stored, etc. In most cases trucks will be hauling a considerable amount of water.
Liquid manure, because of its high water content, cannot be transported as far
but low cost irrigation systems can be used to distribute it relatively
inexpensively.
An additional analysis of the real value of transporting and spreading
manure, compost and fertilizer was based on the nutrient value (Table 3.7). The
nutrient concentration was expressed as Total N- P2O5-K2O5, which are the
primary forms in the market. Even though there is variation between
concentrations, primary nutrients (Total N- P2O5 - K2O5) in this study were
unaffected (p > 0.05) by pile size, turning frequency and season. The average
percentage of total N in the final cured compost (regardless of season- final
cured composts were composite piles) was 2.25 ± 0.63%, 2.30 ± 0.42% and 2.30
± 0.41% for the frequently turned windrow (A), infrequently turned windrow (B)
and the infrequently turned pile (C), respectively. Phosphoric acid (P2O5)
concentrations were 0.60%, 0.59% and 0.58% for A, B and C respectively. Cured
composts had 2.66% (A), 2.76% (B) and 2.39% (C) of potash (K2O5). Table 3.7
67
shows total N: P: K per Mg of cured compost (regardless of turning frequency,
pile size or season) produced in this study (Assumes 40% moisture).
Compost *Amendment Machinery used-Costs ($/Mg) b Labor Total ** $/y3
Treatment Costs $U.S I II III IV Costs c ($/Mg)
$ U.S Mg
A a 88.47 0.02 10.2 8.62 0.01 1.8 109.13 20.6
B a 88.47 0.02 3.4 2.87 0.01 0.6 95.38 17.89
C a 88.47 0.02 0 4.33 0.01 0.54 93.37 17.74 * Prices include hauling to site (Sawdust: Dalton Wood Products Inc, Orville, OH (January, 2007), Manure from OARDC Heifer Barn (No cost) ** Total costs does not consider transportation or application costs (for final hauling, refer Table 3.7). All values were divided by the total mass produced in this study (15 Mg) a A frequently turned windrow (Every three days), B infrequently turned windrow (every 10 days), C infrequently turned piled (every ten days). b I Medium Duty Dump truck Class 1-3 GVW, II Aeromaster MidWest PT120+Truck Hydrostatic drive Farmall 1026, III CASE 1840 Wheel Skid Steer Loader, IV Butler 3340 ensilmixer+Truck Hydrostatic drive Farmall 1026 c Labor costs were calculated with a rate of $15/h; 5 people on the day of construction (3h) and 2 people for each turning (approximately 1minute/windrow and 3.5minute/pile)
Table 3.6 Estimated costs per Mg of cured composts (produced in this study) in US dollars for DM+S compost managed with different turning frequencies and pile sizes.
Tables 3.5 show the costs of making and transporting frequently and
infrequently turn windrows and piles. Results show that turning frequency and
size are major compost production expenses. Operational costs for frequently
turned windrows were higher ($109/Mg) compared to the infrequently turned
windrows ($95/Mg). The lowest cost was observed for the infrequently turned pile
($93/Mg). These differences are due to the time that is needed to turn and the
68
equipment necessary (Table 3.6). Operational costs are affected greatly by the
type of amendment used.
Table 3.7 describe the costs and nutrient values per Mg of manure,
fertilizer (15:15:15) and composts (produced in this study) and shows the
distance where the transportation costs equal the nutrient value of each
amendment. Hauling costs were calculated assuming a labor rate of $15.00/hour,
a travel speed of 30mph, a rate of rent of $60.00/h plus additional mileage
($0.50/mile) and gas ($1.92/mile for a medium dump truck according to Grisso et
al., (2004)) for a total hauling costs of $4.90/mile per load in a medium duty truck
for materials with a moisture content of 40%. The total costs were divided by the
amount of material a medium duty dump truck class 1-3 carries (from 4.5 to 9.0
Mg per load); in this study 7.0 Mg was assumed per load.
The total nutrient values per kilogram of the composts generated in this
study were compared to the nutrient value of commonly used fertilizer (Total N,
Phosphoric acid and potash 15-15-15) and manure (Alexander, 2004; James et
al., 2006) (Town & Country Co-Op, Ashland, OH –April 21, 2007) (Table 3.7).
Results showed that fertilizer had the greatest nutrient value per kg followed by
compost and manure. However to take into account the potential sale of compost
in the market, the value should be considered as the potential to suppress
pathogens, the slow release of nutrients and organic matter, the potential to
69
reduce erosion and increase water holding capacity, and other properties that
can off set the expense of creating compost in addition to the amount of nutrient
present.
70
Costs $ U.S/Mg,Nutrient Values (kg/Mg) and Transportation (miles)
kg/Mg $/Mg
Distance where transportation costs = value (miles)
Fertilizer a N 150 216 309 P2O5 150 252 360 K2O 150 159 227 Total 627 896 N 18.20 26.2 37.44 P2O5 5.77 9.7 13.85 Compost b K2O 26.03 27.6 39.42 Total 63.5 90.70 N 3.55 5.1 7.30 P2O5 1.10 1.8 2.64 Manure c K2O 3.37 3.6 5.10 Total 10.5 15.05
a= Source Town & Country Co-Op, Ashland, OH (April 21, 2007). Price is at the point of sale and does not consider application costs. b= Assume 70% wet mass loss, and moisture content 40%, Average operational cost $99/Mg, Results from this study c= Source Ohio Livestock Management guide. Table 3.7 Nutrient concentrations, values and costs where transportation costs equal the nutrient value in miles for dairy manure (Heifer barn), composts (DM+S, produced in this study) and fertilizers (15:15:15).
71
Fecal N is approximately 40% available (NH4, nitrate, nitrite) and only 50%
reacts (bacteria, sloughed digestive tract cells) generating a product potentially
available to plants. Significant amounts of N can be lost by volatilization of
ammonia, nitrous oxides and N2 (N2, N2O, NH3) (Martins and Dewes, 1992).
Fresh manure can harm plants due to elevated ammonia levels (Walker et al.,
2001). Composting can address this problem as composting accumulates N. N
that is not lost to the environment is assimilated in the microbial biomass and
incorporated into the organic compounds to give immobilized organic N, and a
highly stable end-product (Keeling and Cook, 1998). According to Keeling and
Cook (1998) during composting, ammonia gas is lost from the manure.
Therefore, nitrogen levels may be lower in composted manure than in raw
manure (Different from our results). On the other hand, the phosphorus and
potassium concentrations will be higher in composted manure. Salt levels also
will be higher in composted manure than in raw manure (Jeong et al., 2001).
Chemical fertilizers have been the principal source of N in conventional
agricultural systems, but the prices are increasing and the demand for
biofertilizers in the form of compost and manure has increased rapidly (Garnier et
al., 2003). New organic standards (Fed Reg. No 49) require the use of compost
or manure for Organic agricultural systems. Excess animal wastes have become
an endemic problem at large scale animal production facilities (Inbar et al.,
72
1993). Composting can address these problems by reducing the weight or
manure by up to 70% (found in this study), enabling sales in value-added off-
farm markets and by sequestering manure N (Michel et al., 2004).
From the agricultural point of view, the challenge persists on how to
produce nutrient-rich compost at the lowest cost, which can justify a price high
enough to cover (at least) the operating costs of a compost station and the
transportation costs for fertility sources. Operational costs are highly affected by
the bulking material used; however these costs can be offset when the compost
is sold off farm.
When assessing exactly how to price a high quality compost there is a
need to recognize two distinct markets: 1) Fertility based, same product category
such as soil amendments and fertilizers; and 2) Non-fertility based such as
erosion control, disease suppression, bioremediation, storm water management
(Alexander et al., 2004). Typically, there is little price elasticity between products
in fertility based markets, even when the benefits that compost adds are factored
in.
Non fertility based markets, on the other hand, are outside of the soil
amendment and fertilizer category. Therefore the price point is fixed by the most
competitive products in that category (i.e., fertility based products for that industry
or service sector such as mulches).
Composts can be priced based on the nutrients it contains, or based on
the typical selling price of composts in a market area. A typical price for compost
73
is in the range of $25-50 yd3 (Alexander et al., 2004). Figure 3.5 shows the
revenues of compost (produced in this study) when selling compost for nutrient
value or assessing its costs for its complete benefits.
Results showed that infrequently turned piles may produce higher
revenues (selling composts for nutrient value) than frequently turned windrows.
74
Selling Compost for Nutrient Value
$(1,000.00)
$(500.00)
$-
$500.00
$1,000.00
$1,500.00
$2,000.00
0 20 40 60 80 100 120
`
Fertility Based- Markets
C
ompo
st V
alue
-Cos
t of P
rodu
ctio
n ($
)
Non-fertility Based- Markets
Selling Compost for $50/yd3
$(1,000.00)
$(500.00)
$-
$500.00
$1,000.00
$1,500.00
$2,000.00
0 20 40 60 80 100 120
`
Selling Compost for $25/yd3
$(1,000.00)
$(500.00)
$-
$500.00
$1,000.00
$1,500.00
$2,000.00
0 20 40 60 80 100 1
20
`
Winter
0
50
0 20 40 60 0 100 1208
Cost of Amendment ($/Mg)
As Bs Cs Aw Bw Cw
Frequently turned windrow (Every three days), Infrequently turned windrow (every 10 days), Infrequently turned pile (every 10 days). w=winter, s=summer
Figure 3.6 Revenues of compost in $/yd3 (produced in this study) when selling compost in fertility-based (same product category such as soil amendments and fertilizer) and nonfertility-based (erosion control, disease suppression, bioremediation, storm water management) markets.
75
3.5 RECOMMENDATIONS FOR FUTURE RESEARCH AND APPLIED
AGRICULTURE
As more farmers adopt composting to reduce the environmental impacts
of manure management, a wider spectrum and greater quantity of organic
materials are composted, and different management practices are developed,
the need to optimize and suggest ways to minimize compost production costs,
will become critical to the future growth of composting.
The results of this study indicate that even though different management
practices are employed, final properties of composts did not vary considerably.
However operational costs can differ. It is recommended for farmers not to use
frequent turning, a frequency of ten days rather than many times a week can
reduce operational costs. If composting is performed in temperate climates there
is a need to take into account the moisture content at the beginning of the
process. Composting in winter (January) can start with lower moisture contents
(45 - 50%) and if summer (July-August) composting is performed, additional
water addition may be necessary to maintain adequate moisture contents of 50-
60%.
Future research in composting is recommended in order to establish the
effects of amendment types on these management practices (e.g straw, leaves,
paper, woodchips, etc; and different manures pig, poultry). It is also
recommended that other environmental and seasonal variables such as wind
76
velocity and trajectory be measured in order to estimate their effects on compost
mass losses, oxygen profiles, temperatures and particle size.
3.6 SUMMARY AND CONCLUSION
The different turning frequencies and pile sizes used in this study did not
appear to have a great impact on compost properties, temperatures or oxygen
concentrations during composting (p > 0.05). Neither moisture content, bulk
density nor volatile solids losses were significantly affected by turning frequency
or pile size (p> 0.05). Similar oxygen concentrations and temperatures were
observed in all windrow treatments and although oxygen concentrations rose
transiently after turning, they returned to preturn levels after two hours indicating
that this is not an important mechanism of aeration. The seasonal effects on
composting were primarily related to moisture content mostly due to ambient
temperatures which affect water holding capacity by air. pH was also affected by
composting season possibly as a result of ammonia volatilization during summer
and condensation during winter. The bulking agent was the main factor affecting
total operational costs. But when amendment costs are low, windrow size and
turning frequency can also considerably affect those costs. Results of this study
indicate that composting is possible in any season and infrequent turning (every
10 days) with larger windrow sizes could potentially be used to reduce the
operating costs associated with unseparated dairy manure composting.
77
CHAPTER 4
BIOLOGICAL AND MOLECULAR PARAMETERS DURING COMPOSTING OF
DAIRY MANURE/SAWDUST (DM+S) IN FREQUENT AND INFREQUENT
TURNED WINDROWS
4.1 ABSTRACT
Composting is a biological process which contains diverse microbial communities
due to the wide range of conditions prevalent during the process. These
microbial communities mediate some of the most valuable properties of
composts including plant disease suppression and nutrient availability. However
the effects of dairy manure compost production practices on community structure
an on compost maturity have not yet been previously studied. The objectives of
this study were to determine the effects of turning frequency (frequently-every 3
days, infrequently-every 10 days), size (windrow and pile) and season (winter
and summer) on the microbial community structure in DM+S composts of
different ages and their impacts on compost maturity determined by plant growth
bioassays. A mixture of dairy manure and sawdust (3:1 w/w) was composted in
windrows/piles and samples were collected on days 0, 30, 60, 90, and 120.
78
Bacterial populations were characterized using T-RFLP analysis of amplified 16S
rDNA sequences. PCR products were digested with HhaI and the Terminal
Restriction Fragment (TRF) sizes were compared to fragment sizes predicted by
in silico amplification and digestion (RDP v.9.0). TRF fragments sizes were also
compared to a clone library of 263 sequences from composted dairy manure.
Clustering, pairwise comparison, principal component analysis (PCA) and kruskal
Wallis tests were used to determine the similarities and differences between
microbial communities in the different treatments. Plant growth bioassays
showed a high emergence percentage (≥ 80%) and shoot dry weight for all
compost treatments that were correlated with carbon and nitrogen content of the
compost and to fertilizer application. Pairwise comparision on day 30, showed
that piles of different sizes and turning frequencies have very similar microbial
communities (>60%) but that composts of different seasons and ages were less
similar (~30%). Principal component analysis revealed variations in the
communities in response to age, size and season. In each treatment a different
subset of TRFs contributed considerably to the variation along the first three
principal components. Representative TRFs (61, 93, 99, 159, 167, 205, 215, 227,
365, 373, 437 and 481) in the compost samples were consisted with the
predicted TRFs of Proteobacteria, Firmicutes, Bacteroidetes and Actinobacteria .
A single terminal restriction fragment, H371, contributed significantly (p < 0.1) to
the observed variation in compost age. According to the clone database
Cytophaga sp, E.coli, Ewingella, Rothia and/or Bifidobacterium cuniculi ATCC
79
27916 could have given rise to H371. Overall, management differences (turning
frequency, pile size and season) did not appear to affect significantly (p > 0.05)
microbial communities, but different classes of organisms predominated during
different stages of composting (p < 0.1).
4.2 INTRODUCTION
Composting is a treatment method used for municipal and agricultural
solid wastes that substantially reduces mass, volume and water content.
Although several reports are available concerning the composition and dynamics
of the microflora during composting (Gunapala et al.,1998; Klamer et al., 1998;
Hansgate et al., 2005; Halet et al., 2006; Wang et al., 2007; Michel et al., 2004),
little is know about the effects of management differences on microbial
communities during composting. For example the effects of windrow turning or
pile size which may affect the moisture, oxygen or temperature gradients during
composting.
The effect of these process parameters on compost maturity, or the
potential for the development of beneficial effects upon utilization, is also not
known (Hoitink, et al., 1986; Tiquia et al., 1997; Iannotti et al., 1994). Immature or
nonstabilized compost can be phototoxic due to the occurrence of insufficiently
degraded organic compounds (Illmer et al., 1997). Beneficial effects of compost
on plant health (disease suppression) and soil physical properties are frequently
correlated with the microflora and the organic matter decomposition (Iannotti et
80
al., 1994; Kostov et al., 1995; Zubillaga et al., 2006). Since the production of
composts requires energy for turning and mixing, understanding all the impacts
of these practices on final compost properties is important to optimize the
process.
In this study the effects of turning frequency, pile size and season during
DM+S composting on biological (bioassay) and molecular parameters (microbial
communities) were determined.
4.3 MATERIALS AND METHODS
4.3.1 Composts
Compost samples (0.03 m3) of different ages (0, 30, 60, 90,120 days),
made from initial mixtures (3:1 w/w) of unseparated dairy manure (Heifers are fed
with silage, corn silage, grain mix and dry-baled) and hardwood sawdust (Dalton
Wood Products, Inc) were collected during a full scale compost study at the
OARDC compost pad during winter and summer 2007. Three treatments were
evaluated during each season; frequently turned windrow (A- every three days),
infrequently turned windrow (B-every ten days) and infrequently turned piles (C-
every ten days). Windrows were turned with an Aeromaster turning machine and
piles with a skid steer loader. The dimensions of the piles and other properties
are described in chapter 3.
81
4.3.2 Biological Parameters
Prior to bioassay compost samples were stored at -20°C until each
season replicate was concluded. Bioassays for winter and summer were
performed separately
The effects of each treatment on seedling emergence and plant growth
were determined with a cucumber bioassay according to Iannotti et al., (1994) at
the end of each season. Bioassays were performed in 20% v/v compost
amended (Wilkinson et al., 2005) potting medium (ProMix 360) with 12.5g/L slow
release fertilizer (Osmocote 14-14-14, Grace-Sierra Chemical Co) and without
fertilizer. Two (with and without fertilizer) 500 ml pots with 450 ml potting mix and
compost were used per experimental set. Eight cucumber (Cucumis sativus L.cv.
Straight Eight, 99% germination) seeds were planted 1.0cm deep in composite
samples for each treatment in both seasons. Plants were grown in a greenhouse
at 22-27°C with 14 hours per day of supplemental illumination (225μEm-2 s-1).
Pots were irrigated as needed and incubated for 21 days. On day 7, the mean
emergence was determined and the number of seedlings thinned to four per pot.
On day 21, the aerial portion of each plant was harvested and weighed and then
air-dried (70°C) to a constant weight from which plant dry weight per pot was
determined. The response of cucumber plants to differences in compost
treatments and age was expressed as the percent of plants grown in compost
mixes compared to the peat control.
82
4.3.3 Bacterial Community Analysis
DNA was extracted from the composts (5 to 10 g used) on day 0, 30, 60,
90, 120 and from 120cm depth of day 30 (highest temperature in compost piles,
according to previous results). DNA was extracted using the Ultraclean soil DNA
isolation kit (MoBio Laboratories). The genomic DNA was quantified using
PicoGreen ® dsDNA Quantitation reagent (Molecular probes). DNA
concentration was adjusted to 2 ng/μl so that equivalent amounts of DNA were
used as templates in PCR reactions. PCR was performed using the eubacterial
16S gene targeted primers 11F (3’ GTT TGA TCM TGG CTC AG 5’) and 907R
(3’ CCG TCA ATT CMT TTR ATG TT 5’) (Peters et al., 2000). The 11F primer
was labeled with the fluorescent phosphoramidite dye (Sigma, Proligo) for
visualization of terminal restriction fragments (TRF). Amplifications were carried
out in 50μl reactions containing 0.45 μg/ml of BSA, 0.2 mM dNTPs, 1 mM MgCl2,
3% DMSO, 0.5 μM of each primer and 0.025 U/μl of Taq polymerase (StartTaq,
Qiagen). PCR cycling was done in a T-gradient Biometra thermocycler, using an
initial activation step of 5 min at 95˚C, 30 cycles of 30 sec at 95˚C, 45 sec at
52.5˚C, 2 min at 72˚C with a final extension at 72˚C for 10 min. Amplified rDNA
was purified with Microcon-PCR mini-columns (Millipore). Products were
separated on a 2% agarose gels in 50% Tris-borate-EDTA buffer and visualized
by ethidium bromide staining.
Restriction digestion of PCR products were performed in 25μl reactions
containing 0.5μl HhaI enzyme (20U/ml) (Promega), 5μl of 10x BSA, 5μl buffer
83
Neb#4 and varied volumes of PCR product according to concentration
(300ng/50μl). Samples were incubated for 12h at 37°C followed by 20 min at
75°C for enzyme inactivation. 10μl were cleaned with Wizard S.V Gel-Clean DNA
Kit (Promega) and sent to the Research Technology Support facility of Michigan
State University. There, samples were mixed with 100mM ROX standard size
(Bioventures). The lengths of fluorescent labeled terminal restriction fragments
(TRFs) were determined with the use of Perkin Elmer’s ABI GeneScan Analysis
System. Bionumerics software v3.5 (Appllied Maths) was used to evaluate the
results. Matrixes containing incidence as well as peak height data of individual
TRFs were generated for all samples. The following criteria were used to limit,
evaluate and define TRFs used in this assay: fragment size ≥ 50bp, ≥ 0.1 for
normalized area of each peak, ±1bp for TRFs < 100, ±2bp for TRFs between 100
and 200bp, and ±5bp for TRFs > 200. Because of the natural variation in
bacterial population between replicates of the same treatments, comparisons
between treatments were performed only when TRFs appear in a minimum of 4
out of 31 samples. TRF identity was predicted by a computer-simulated
amplification and digestion of complete 16S gene sequences obtained from the
Ribosomal Database using TAP TRFLP software (RDP v9.0) and by comparison
to a clone library of 16S sequences of DM+S composts.
The clone library was obtained from DNA DM+S composts (day 50, 155
and 330) that were amplified with the same set of primers (11F and 907R)
labeled at the 5’ end with the phosphoramidite dye Hex and digested with HhaI,
84
MspI or RsaI restriction. The cloning of PCR products Ligations were obtained
using the pGEM®-T and pGEM®-T easy vectors and the 2x rapid ligation buffer
(Promega Corporation). The ligated reactions were transformed (uncut plasmid)
and the transformation efficiency cfu/mg DNA was calculated (Promega).
Transformation efficiencies higher than 1 x 108 cfu/mg DNA were cultured in LB
media overnight. Identification of the colonies containing the recombinant
plasmid was performed using a multiplexed miniprep for rapid screening
(Berghammer and Auer, 1993). Individual screening was performed if pools
produced the same pattern of bands by utilizing a colony-lysis miniprep (Hultner
and Cleaver, 1994). Approximately 100 different clones were selected for each
compost sample for sequencing.
DNA sequences were pairwise aligned (Maximal Segment Pair) and
submitted to the NCBI Genbank BLAST search to determine the nearest relative.
Sequences were also phylogenetically classified using the I Bayesian rRNA
Classifier of the ribosomal database project (RDP). Final TRFs from each of the
treatments were compared to the phylogenetically classified clone sequences
that presented the same fragment size (fragment size ≥ 50bp, ≥ 0.1 for
normalized area of each peak, ±1bp for TRFs < 100, ±2bp for TRFs between 100
and 200bp, and ±5bp for TRFs > 200).
85
4.3.4 Statistical Analysis
All statistical analyses for the Bioassay were performed using MINITAB
(ver 15.1) from MINITAB, Inc. Plots were generated using SIGMAPLOT (ver.
10.0) from TE Sub Systems Inc. Standard one way analysis of variance was
used to determine differences in treatments, while mean comparisons among
treatments and seasons were performed using Fisher’s protected least
significance difference test (5% level). Correlation analysis between variables
was performed using Pearson product moment and Spearman R for ranked
variables.
The similarity of microbial communities in each treatment was estimated
by clustering, pairwise comparison, principal component analysis (PCA) and
kruskal wallis (Benitez et al., 2007). Pairwise comparisons were carried out to
valuate the similarity of microbial communities between seasons, age and turning
frequency. Normalization and analysis of fragment sizes were done with
BioNumerics software v3.5 (Applied Maths). The normalized banding patters
were used to generate dendograms by calculating the Pearson product moment
correlation coefficient and by UPGMA (unweighted pair group method with
arithmetic averages) clustering. This approach compares profiles based on both
band position and intensity. Principal component analysis (PCA) on covariance
matrices of T-RFLP was employed to generate hypothesis and group or separate
samples based on the presence or absence of TRFs from each TRFLP pattern.
Data from each experiment treatment (Compost age, season variability, turning
86
frequency and size) was analyzed separately using MINITAB (ver 15.1) statistical
software package. Ordination plots were created with SigmaPlot (v 10.0 Systat
Software Inc) from the mean principal component scores of each treatment.
Loading factors were used to determine the relative influence of each TRF on the
variation among treatments. TRFs with loading factor values of ≥ 0.6 present in
the first 4 principal components were selected for further analysis. MINITAB
(v.15.1.1 Minitab Inc) was used to perform the rank-based Kruskal-Wallis test
used to determine treatment differences in relation to the relative abundance of
the selective TRFs.
87
4.4 RESULTS AND DISCUSSION
4.4.1 Plant Growth Bioassay
The evaluation of the maturity of composting process has been widely
evaluated with plant growth bioassays (Illmer et al., 2007; Chikae et al., 2006;
Hogland et al.,, 2003; Tiquia et al., 2002; Wang et al., 2004). Immature compost
can cause a decrease of the O2-concentration around the root system (Chikae et
al., 2006). Additionally, compost can inhibit plant growth by the production of
phytotoxic substances, including ammonia, ethylene oxide, and organic acids
(Iannotti et al., 1994; Tiquia et al., 2002).
Cucumber cultivation has been performed by various authors showing a
rapid and significant response to compost treatments (Iannotti et al., 1994;
Kostov et al., 1995; Tiquia et al., 2002). In this study, trends in compost pH,
moisture content, percent volatile solids, organic C and total N were analyzed
simultaneously with the bioassay (Table 4.1) to facilitate interpretation of the
plant growth response.
Plant growth bioassays indicated that the seedling emergences were
higher than 80% in all potting media amended with compost that contain fertilizer
and more than 90% in the potting media without fertilizer. Day 60 of windrow B of
the winter replicate was the only sample with less than 80% emergence (74%);
however there was no significant (p > 0.3) inhibition of germination by any of the
composts. These results are similar to the ones reported by Kostov et al., (2002)
88
who showed a higher increase of cucumber emergence on compost treatments
mixed with fertilizers.
The response of cucumber plants to differences in compost age and
treatment in fertilized and unfertilized treatments was expressed as the percent
shoot dry weight of plants grown for 21 days in compost mixes as compared to a
peat control (Table 4.1). In the fertilized treatments, the shoot dry weight of
cucumbers in the summer compost amended mixes surpassed the peat control
(≥ 100%) for all treatments and days except for day 30 in pile C (89%). In winter
only pots containing compost for pile C on day 120 surpassed the peat control
(102%). In the unfertilized treatments infrequently turned piles (Cs) showed the
highest response of plants (highest shoot dry weight related to the peat control)
(80 ± 13%) compared to the frequently (65 ± 8%) and infrequently turned
windrows (61 ± 10%).
Total N incorporated as compost into the potting mix showed an increase
with compost age over the entire test period (120 days) for all treatments and
seasons (Figure 4.1). However these differences were not significant (p > 0.05)
and there was no correlation between total nitrogen and shoot dry weight (r <
0.5). Similar results were obtained by Wang et al., (2004) suggesting that total N
supplied by the compost does not relate well to shoot N or dry weight.
Initial mixtures contained 3 parts wet basis of sawdust (0.40% N) and one
part manure. Manure of Heifers, expressed as a percent in a dry basis contained
4.25% total nitrogen. The percentage of initial nitrogen for winter treatments was
89
1.40 ± 0.18%, for summer treatments 1.35 ± 0.10%; final cured compost in all
treatments and seasons varied from 1.80 to 2.70% (Table 4.1).
Volatile solid loss, moisture and pH did not affect significantly (r2 < 0.5)
plant growth. However there was variation between pH and pile size in winter for
the cured composts, for the windrows 8.62 ± 0.17 and the piles 7.94 ± 0.09.
According to our results pH, affected shoot dry weigh, which was higher for the
windrows (Table 4.1). These can be also explained with the nitrogen
concentration; according to Beegle (2007) with low nitrogen concentrations plant
yield increase as soil pH increases
Although the dairy manure sawdust compost supported growth of
cucumber without added fertilizer, the fertilized pots had higher shoot plant
weight. It is recommended to conduct some studies to optimize the concentration
of the controlled release fertilizer and compost which could reduce nutrient
leaching and improve plant quality.
90
**
A * Frequently turned
windrows
B * Infrequently turned
windrows
C * Infrequently turned
piles Properties Day Winter Summer Winter Summer Winter Summer
% 0 1.4±0.2 1.3±0.1 1.4±0.2 1.3±0.1 1.40±0.2 1.3±0.1 Nitrogen a 30 1.5 1.5 1.5 1.5 1.4 1.5
60 1.9 1.9 1.9 1.8 1.9 1.9 90 1.8 1.8 1.8 1.8 1.7 1.8 120 2.7 1.8 2.6 2.0 2.6 2.0
% 0 52.7±3.3 50.3±2.6 52.7±3.3 50.3±2.6 52.7±3.3 50.3±2.6 Carbon a 30 47.8 47.6 47.5 47.3 47.6 47.4
60 43.9 42.1 45.0 43.2 47.5 45.7 90 46.7 49.2 46.3 45.1 46.4 43.7 120 41.7 44.5 45.0 43.1 44.7 44.2
pH 0 8.2±1.0 7.8 8.6±0.01 8.0 8.3±0.3 8.2 30 8.4±0.7 8.4 8.8±0.3 8.4 8.3±0.1 8.0 60 8.6±0.3 8.4 8.7±0.5 7.9 8.4±0.05 8.0 90 8.6±0.1 7.6 8.3±0.5 7.3 8.2±0.3 7.4 120 8.6±0.2 7.2 8.2±1.00 7.2 7.9±0.1 7.4
% 0 65.4±2.3 61.9 68.3±4.4 60.33 66.11±2.03 58.21 Moisture 30 67.7±0.9 52.9 69.3±6.1 50.11 66.65±3.12 60.24
60 74.0±2.2 42.5 72.0±6.8 45.90 72.44±1.67 49.01 90 73.7±0.1 59.1 74.2±4.3 66.99 70.20±1.13 66.36 120 68.8±4.5 71.0 70.4±5.9 59.20 67.46±7.84 69.19
% Volatile 0 94.17±1.51 93.09 92.8±2.8 93.8 93.8±0.4 93.5 solids 30 89.44±1.89 91.25 88.9±6.1 91.7 94.8±0.8 90.7
g/g initial 60 85.32±5.85 73.21 83.8±2.8 76.3 79.4±2.2 74.7 90 69.90±9.76 87.61 78.2±3.2 87.8 85.9±0.9 85.4 120 76.53±3.44 81.00 76.2±10.8 72.2 69.1±0.2 76.2
Shoot Dryb 0 95% 59% 123% 71% 122% 71% Weight (%) 30 78% 68% 66% 65% 86% 76% N-Fertilizer 60 81% 78% 85% 65% 75% 70% 90 47% 62% 51% 44% 51% 83% 120 100% 57% 90% 60% 90% 102% Shoot Dryb 0 131% 134% 129% 127% 144% 101% Weight (%) 30 102% 100% 127% 122% 119% 89% Fertilizer 60 112% 100% 120% 126% 121% 155% 90 98% 116% 107% 136% 126% 158% 120 98% 161% 76% 127% 112% 162%
* A (Every three days), B (every 10 days), C (every ten days) ** Winter Day zero =Julian day 008, day 120= Julian date 125; Summer day zero = Julian date 220, day 120 = Julian date 340 (2007) a Analysis of total C and N were performed in the StarLab at the OARDC Wooster campus. b Percentage compared to the shoot dry weigh of plants grown in a peat control. N- means without fertilizer Table 4.18Biochemical changes of composite samples in frequently turned windrows (A), infrequently turned windrows (B) and infrequently turned piles (C) for the full scale study
91
Unfertilized
00.40.81.21.6
22.42.83.23.6
44.4.
48
5.25.6
66.46.8
0 30 60 90 120
Sh
oot D
ry W
eigh
t (g/
pot)
Compost Age (days)
Fertilized
0.00.40.81.21.62.02.42.83.23.64.04.44.85.25.66.06.46.8
0 30 60 90 120
Compost Age (days)
0 30 60 90 120
Aw As
Bw Bs
Cw Cs
N concentration (Compost-Winter) N concentration (Compost-Summer)
Frequently turned windrow (Every three days), Infrequently turned windrow (every 10 days), Infrequently turned pile (every 10 days). w=winter, s=summer
Figure 4.17Effects of compost age on Total N supplied by compost and shoot dry weight of cucumber plants (C.sativus. L.cv) produced in the three different compost amended potting mixes treatments. Compost physical and chemical conditions are shown in previous results.
92
4.4.2 Quantitative Assessment of Microbial Community
The amount of extractable DNA is strongly correlated with the total
microbial biomass and reflects the size of genetic material pools of
microorganisms (Kelly, 2003; Howeler et al., 2003; Yang et al., 2007). However,
the DNA content does not reflect the ability of these microorganisms to be
activated physiologically and metabolically. Blagodatskaya et al., (2003)
characterized microbial communities by the amounts of extractable DNA
quantified by PicoGreen. He found a strong correlation between microbial
biomass and DNA contents in environmental samples of different types (r = 0.8);
thus, the DNA content of the compost samples analyzed in this study can be
used to characterize the compost microbial community (Blagodatskaya et al.,
2003; Yang et al., 2007).
The genomic DNA for the composite compost samples of every treatment
after turning was quantified using PicoGreen ® dsDNA Quantitation reagent
(Molecular probes). Initial DNA concentrations were 0.36 μg DNA/g of compost
and 4.57 μg DNA/g of compost for winter and summer respectively. The
concentration of genomic DNA at the end of the composting phase did not vary
greatly (p > 0.05) between seasons and treatments (10.36 ± 2.54 μg DNA/g wet
compost) (Table 4.2). According to Howeler et al., (2003) an average extraction
and purification of wet compost is 18.2 ± 3.8 μg DNA/g; the amount of DNA
recovered with the kit used in this study depends greatly on the sample; on the
other hand the binding capacity of the spin filter is 20 μg of DNA. Even though
93
DNA concentrations were not as high as those values reported in the literature
(Howeler et al., 2003; Yang et al., 2007), results showed similar patterns in the
concentration of genomic DNA in all composts.
During the first 30 days, DNA concentration for the infrequently turned
piles for both seasons, showed the highest increase. There was a high
correlation of the concentration of genomic DNA with turning frequency and pile
size (r > 0.7). A high positive correlation with temperature (r > 0.6), in all
treatments and seasons, and oxygen (r > 0.6) in the summer replicates was
observed (Figure 3.3), verifying that the microbial community is highly dependent
on its surroundings (i.e. temperature, oxygen, moisture).
The DNA purification methods produced DNA sufficiently pure to allow
restriction enzymes and DNA polymerase enzymes to function; and although
PCR amplification is extremely sensitive to humic acid contamination (Howeler et
al., 2003; LaMontagne et al., 2002), humic acid concentration was reduced
sufficiently and the PCR products of the expected size were present in the
majority of the samples (25/30). Molecular analyses were limited to those
samples that had sufficient digestion product for T-RFLP analysis. Samples from
day 90 (frequently turned windrow, Aw), day 120 (infrequently turned windrow
Bw) of the winter study; and samples from day 90 and 120 of the infrequently
turned windrow and day 90 of the infrequently turn pile of the summer study (Bs,
Cs) were not considered due to poor DNA recovery.
94
4.4.3 Analysis of bacterial community structure
Terminal Restriction Fragment Length polymorphism was used to asses
the microbial community structure. The profiles of the samples were evaluated,
using UPGMA clustering based on pearson correlation coefficients. The resulting
dendogram generated four large clusters, assigned 1 to 4 (Figure 4.2). Cluster 1
contained samples from day zero (fresh dairy manure sawdust compost from a
composite mix of winter and summer replicate) and showed low similarity with
the rest of the treatment samples (r = 1.75%). The great majority of the young
samples (day 30 and 60) for winter and summer grouped in the same cluster (4)
with ≥ 41.49% similarity in almost all the treatments. Older samples (> 60 days)
also clustered together (3), but similarity among these samples was less (>
13.61%). There was no clustering of samples based on season, turning
frequency or pile size.
TRF profiles from the clone sequences, representing active (50 days-
compost I), stable (155 days- compost II) and mature (330-days-compost III)
composts clustered (3 and 4) with separately from the other samples (Figure
4.2), Clustering results from T-RFLP profiles of samples I, II and III are shown in
Figure 4.2.
95
A Frequently turned
windrows
B Infrequently turned
windrows
C Frequently turned
piles Properties Day Winter Summer Winter Summer Winter Summer
Temperature 0 3.2±3.8 36.5±5.2 4.6±3.4 40.3±0.6 2.5±2.4 37.6±1.6 (°C) * 30 38.4±5.4 51.6±3.0 28.5±18.6 47.7±2.2 43.6±9.6 39.7±13.2
60 48.5±5.1 43.4±1.1 51.4±19.2 25.4±5.5 43.4±4.8 41.8±9.2 90 37.2±7.5 46.3±3.7 44.6±5.6 47.3±1.6 48.9±6.5 37.2±11.5 120 42.1±6.2 22.8±2.9 42.9±5.7 7.3±0.5 41.5±17 34.9±3.7
Oxygen 0 11.0±7.7 7.0±3.0 11.1±2.7 17.0±3.1 11.9±6.7 17.5±8.0 (%) * 30 13.7±7.6 19.6 8.3±1.73 19.5±0.6 15.9±7.1 4.67±1.04
60 15.0±6.3 17.6 11.4±5.6 19.5 13.3±6.5 19.5±0.9 90 15.9±6.1 19.5±0.3 8.9±7.5 7.8 5.3±5.1 17.3±0.3 120 9.7±8.2 17.3 12.0±3.7 18.8 12.4±8.9 11.5±10.6
μg DNA/ 0 0.36 4.57 0.36 4.57 0.36 4.57 g Wet 30 16.35 19.48 23.84 7.18 37.75 21.69
Compost ** 60 19.03 25.61 18.47 24.49 18.07 11.44 90 8.47 16.74 24.20 17.04 21.57 15.70 120 8.73 8.91 10.30 9.87 15.43 9.05
A frequently turned windrow (Every three days), B infrequently turned windrow (every 10 days), C infrequently turned piled (every ten days) * Temperature and oxygen gradients are averages of all depths, before and after turning **Composite samples. DNA concentration was based on Picogreen results The number in parenthesis is the age of compost
Table 4.29Concentration of genomic DNA and conditions for the frequently turned windrows (A), infrequently turned windrows (B) and infrequently turned piles (C) compost treatments.
96
100
95908580757065605550454035302520151050
As(90)
Aw(60)
Cs2(30)
Cw(60)
Aw(120)
Cw(90)
AS(60)
As(120)
Bw(90)
Cw(120)
I(50)
III(330)
II(155)
Cs(120)
Aw2(30)
Bs(30)
Bw(60)
Cs(30)
Bw(30)
Cw(30)
Cw2(30)
As(30)
As2(30)
Bs2(30)
Bw2(30)
Aw(30)
Bs(60)
Cs(60)
Zero
3
4
2
1
A frequently turned windrow (Every three days), B infrequently turned windrow (every 10 days), C infrequently turned piled (every ten days)*. w=winter, s=summer. I(50) The number in parenthesis is the age of compost. Samples day 30, Samples day 60
Samples day 90, Samples day 120 . Figure 4.28Dendogram-Relatedness of T-RFs profiles of HhaI-digested of 16S rDNA from frequently turned windrows (A), infrequently turned windrows (B), infrequently turned piles (C) and clone compost samples (I, II, II). (The UPGMA, single linkage, was used to performed the cluster patterns and obtain the similarity dendogram)
97
Pairwise comparisons of the TRFLP profiles between the seasons for the
frequently turned windrow (A) showed a similarity from 30 to 70% during the
composting process (day 30-120). In winter, a high similarity (70%) between
infrequently turned (B-C) composts made in piles of different sizes suggested no
effect of pile size on the microbial community. In Table 4.3 similarities between
the middle depths in day 30 of compost for all seasons, pile size and turning
frequency are shown; a low similarity between summer pile compost and the
other treatments was observed.
Aw Bw Cw As Bs Cs Aw X 61% 59% 45% 61% 22% Bw X X 43% 61% 64% 0% Cw X X X 30% 40% 0% As X X X X 85% 6% Bs X X X X X 0% Cs X X X X X X
A frequently turned windrow (Every three days), B infrequently turned windrow (every 10 days), C infrequently turned piled (every ten days)*. W=winter, S=summer. * Pairwise comparisions were performed using Bionumerics (Apllied Math v.3.5) Table 4.310Similarity coefficients between the TRFs from the middle of the pile (120cm) on day 30 of frequently turned windrows (A), infrequently turned windrows (B) and infrequently turned piles (C) compost
During composting (day zero through day 120) there was low similarity
between various treatments, therefore further statistical analyses were performed
to determine where the variation occurred. Principal component analyses were
98
performed to determine the overall effect of each treatment (turning frequency,
pile size, age and season) on the observed populations of 16S rDNA TRFs. For
this part of the study each TRF was considered as a different variable.
Samples from different seasons, turning frequencies, pile sizes and ages
were analyzed separately to identify were variation. Ordination plots, generated
from the mean principal components scores, were used to interpret the observed
treatment separations. Variation explained by the first two principal components
ranged from 40% to 95% among season and age. There was an apparent effect
of season on bacterial community structure (Figure 4.3). The variation between
winter and summer explained by the first two principal components ranged from
46% to 70% among all turning frequencies and sizes samples (data not shown).
T-RFLP profiles from day 30 and 60 appeared to be influenced by turning
frequency and pile size (Fig. 4.4).. For day 30 in the summer replicate,
separation between winter treatments was observed in the infrequently turned
pile and windrow, but not the frequently turned ones, suggesting no significant
effect of turning in the microbial communities but some effect of season. Overall
winter replicates separated from the summer replicate along the second principal
component (17%) and only the infrequently turned pile (C) for winter and summer
was separated along the first component (45%) (Figure 4.3).
The observed TRFs from the clone sequence (I,II,II) were compared
according to age, (samples were collected from the compost pad and did not
have any treatment- turning frequency or pile size). These TRFs showed high
99
similarity with the rest of the samples but separated from the other treatments
along the second PC (17%) with day 30 of the infrequently turned windrow
(summer).
A response to pile size was also observed in the PCAs of the T-RFLP
profiles in both seasons for each date evaluated. During day 30, after turning, the
frequently turned windrow in summer (As) showed 10% of variation along the
second PC between the replicate from winter (Aw). The communities also depict
differences in day 30 among windrow/pile size. The windrow (As) is separated
from the pile (Cs) along the second PC (10%). For 120cm depth on day 30,
before turning, the pile in summer (Cs) was separated from the rest of the
replicates along the first component (44%). However the pile in winter (Cw) did
not separate from the other treatments (Figure 4.4).
For day 60 the highest variation among communities was observed for the
infrequently turned windrow during winter but not for summer (PC2 10%). For
day 90 and 120 the frequently turned windrow (A) is separated from the
infrequently turned pile (C) along the second PC suggesting an effect of pile size.
The pair wise comparison and the cluster analysis showed differences and
effects in the microbial communities with compost age but not season, pile size
or turning frequency.
100
Aw(30)
As(30) Bw(30) Bs(30)
Cs(30)Bw(60) AS(60) Aw(120) As(120) Cw(120) Cs(120) Cw(90)
Zero As(90) Cw(60) Cs(60) Aw(60) Bs(60)
Bw(90) I(50) II(155) III(330)
II(155)
Aw(30)
As(30)
Bw(30)
Bs(30)
Cs(30)Bw(60)
Cw(90)Zero As(90)Cw(60)Aw(60)
-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
-0.3 -0.2 -0.1 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7PC1 (45%)
PC2
(17%
)
A frequently turned windrow (Every three days), B infrequently turned windrow (every 10 days), C infrequently turned piled (every ten days)*. w=winter, s=summer. The number in parenthesis is the age of compost. Figure 4.39Effects of composting age, turning frequency and pile size during winter and summer in bacterial community structure for the frequently turned windrows (A), infrequently turned windrows (B), infrequently turned piles (C) and clone compost samples (I, II, II). Ordination plots from the first two principal components (PC) are shown with the corresponding standard error bars. The PCA was performed using the 16S rDNA terminal restriction fragment (HhaI) relative abundance data obtained from composts collected on day zero, 30, 60, 90 and 120 exposed to different management practices.
101
Day 30
Aw(30)
Bw(30)
Cw(30)
As(30)
Bs(30)
Cs(30)
-1.5
-1
-0.5
0
0.5
1
1.5
-0.4 -0.2 0 0.2 0.4 0.6 0.8 1 1.2PC 1 (75%)
PC 2
(10%
)
120 cm Depth -Day 30
Aw2(30)
Bw2(30)
Cw2(30)
As2(30)
Bs2(30)
Cs2(30)
-1.2
-1
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
-0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6PC 1 (44%)
PC 2
(34%
)
-1
-0.5
0
0.5
Aw(30) Bw(30) Cw(30) As(30) Bs(30) Cs(30)
Plots show the mean principal component (PC) scores for each treatment with the corresponding error bars. The PC analyses of TRf’s were performed using 16S rDNA terminal restriction from Hha. A frequently turned windrow (Every three days), B infrequently turned windrow (every 10 days), C infrequently turned piled (every ten days)*. w=winter, s=summer. The number in parenthesis is the age of compost. Figure 4.410Effects of season variability, turning frequency, depth and pile size in day 30 on bacterial community structure for the frequently turned windrows (A), infrequently turned windrows (B) and infrequently turned piles (C).
102
Principal Component PC1 PC2 PC3 PC4 Age** 0 93 30 215 371 437 60 371 61,99 90 205 120 215 159, 167 Season Winter 371 Summer 215 371 93 481 Turning
& A 481,371 373 Size B 371 215 481, 365
C 93 227 371 * TRFsize was predicted by a computer-simulated amplification and digestion of complete 16S gene sequences obtained from the Ribosomal Database using TAP TRFLP software (RDP v9.0) A frequently turned windrow (Every three days), B infrequently turned windrow (every 10 days), C infrequently turned piled (every ten days)*. W=winter, S=summer. ** Winter Day zero =Julian day 008, day 120= Julian date 125; Summer day zero = Julian date 220, day 120 = Julian date 340 (2007) Table 4.41116S rDNA terminal restriction fragment with factor loadings |x|>0.60 on the four principal components (PC) for each experimental treatment
103
Only a small subset of TRFs contributed strongly to the variation observed
in the PCA. TRFs with a factor loading |x| ≥0.60 for each of the first four principal
components are summarized in Table 4.4. The first four principal components
explained from 40% to 96% of the variation among the different experimental
treatments. In all treatments, A TRF with a size of 371 bp (H371) contributed
more than 40% of the variation. H371 had factor loading values of |x| ≥ 0.8 in all
treatments except in the older composts (day 90-120). Other TRFs that largely
contributed to the variation to the first four principal components in more than one
scenario were H93, H215 and H481. TRFs with high factor loadings in day 30
from 120cm depth for summer did not show any similarities with those found in
winter, in addition the factor loading for M379 did not meet (x≤0.4) our selection
criteria.
In order to determine if the relative abundance of individual TRFs was
influenced by treatment and if there was a significant difference in bacterial
community structure, the nonparametric Kruskall-Wallis test was also used. Even
though uncommon TRFs were found in the different treatments (season, age,
turning frequency and depth); p (α =0.1) values revealed that differences in
abundance of TRFs were directly affected by age but not season, turning
frequency or pile/windrow size. Only TRF M371 was directly associated with age
(p < 0.1). Nevertheless the loading factor for H371 for summer (0.673) was more
highly associated to the variation than in winter (0.605).
104
The clone library of active (I), stable (II) and mature (III) composts
generated a total of 87, 85 and 91 16S rRNA gene clones respectively that were
sequenced. Phylogenetic analysis of the sequences using RDP Naïve Bayesian
classification indicated that 9, 11 and 12 different Phyla were found in composts
I, II and III, respectively (data not shown). In all three composts, Proteobacteria
ribotypes predominated. Many sequences from the phyla Actinobacteria,
Bacteroidetes, Firmicutes, and Chloroflexi were also found (Table 4.5). The
numbers of different Classes of bacteria observed among the cloned sequences
from the three composts was 14, 18 and 17 for composts I, II and III,
respectively. The class Gamma Proteobacteria predominated in composts I and
II while Actinobacter was the most prevalent class in compost III. Clostridia,
Chloroflexi and Sphingobacteria were observed in all three composts. The
BLAST nearest relatives of the clones from all three composts did not include
any pathogenic bacteria (data not shown). Sequences related to classes of
bacteria not previously described in composts, such as Chlorofexi, Anaerolineae,
Thermomicrobia, Gemmatimonadetes and Acidobacteria, were found.
Conversely, entire phyla such as the Acidobacteria or the Chloroflexi are poorly
represented among the sequence databases but are widely abundant in natural
environments (Mering C.von., 2007). Only two sequences corresponding to
Bacillus, the predominant culturable genus found in composts (Strom, 1985),
were observed.
105
Phylogenetic identity of the terminal restriction fragments (± 2bp) for each
experimental treatment with factor loadings |x| ≥ 0.60 on the PCA (Table 4.4)
were performed using TAP TRFLP software (RDP v9.0) and by comparisons to
the clone database (Table 4.5). Phylogenetic assignments for H371 ± 5bp with
the clone database suggested the presence of Cytophaga sp (Bacterioidetes),
E.coli and Ewingella (Gammaproteobacteria), Rothia and/or Bifidobacterium
cuniculi ATCC 27916 (Actinobacteria) in young compost samples.
Comparisons of the representative TRFs in the PCA for each treatment
(Table 4.4) with the clone database was consistent with the presence of 4
different Phyla. Among these TRFs, Proteobacteria ribotypes were the most
prevalent, followed by Firmicutes, Bacterioidetes and Actinobacteria (Table 4.5).
The number of different Classes of bacteria consistent with the TRFs from
all the treatments was 14. The class Gamma proteobacteria was consistent with
the largest number of TRFs (H61, H205, H215, H371) while Actinobacteria and
Alpha proteobacteria were consistent with TRFs in all the samples regardless of
turning frequency, pile size, season or age.
In this study the TRFs found indicated that the microbial community varies
with time during composting and that there is a succession of bacterial lineages
during composting. Microbial communities are very diverse within dairy manure
composts (Wang et al., 2007; Bolta et al., 2003; Morales et al 2005; Guo et al.,
2007) throughout the composting process but do not differ significantly with
compost turning frequency, pile size or season.
106
TRF Phyla Classes 61 Proteobacteria AlphaProteobacteria
Firmicutes Bacilli Proteobacteria Gammaproteobacteria Firmicutes Clostridia
93 Bacterioidetes Flavobacteria Firmicutes Bacillales Bacterioidetes Bacteroidetes Bacterioidetes Sphingobacteria
99 Proteobacteria Epsilonproteobacteria Bacterioidetes Bacteroidetes
159 Proteobacteria Alphaproteobacteria Firmicutes Mollicutes
167 Actinobacteria Actinobacteria
Proteobacteria Proteobacteria
Betaproteobacteria AlphaProteobacteria
205 Proteobacteria Acidobacteria
Proteobacteria Acidobacteriales
Proteobacteria Gammaproteobacteria
215 Proteobacteria Proteobacteria
Gammaproteobacteria AlphaProteobacteria
Firmicutes Actinobacteria
Lactobacillales Actinobacteria
Firmicutes Bacillales Bacterioidetes Sphingobacteria
227 Firmicutes Clostridia Firmicutes Mollicutes Proteobacteria Alphaproteobacteria Proteobacteria Gammaproteobacteria
365
Proteobacteria Proteobacteria Firmicutes
Alphaproteobacteria Gammaproteobacteria Bacilli
Actinobacteria Actinobacteria 371 Bacterioidetes unclassified
ProteobacteriaFirmicutes
Gammaproteobacteria Bacillales
437 Actinobacteria Actinobacteridae 483 Uncultured Clone TBS19
* TRFsize and identity was predicted by a computer-simulated amplification and digestion of complete 16S rDNA gene sequences obtained from the Ribosomal Database using TAP TRFLP software (RDP v9.0) and comparing fragment sizes to a clone sequence database (HhaI disgested) matching (fragment size ≥ 50bp, ±1bp for TRFs < 100, ±2bp for TRFs between 100 and 200bp, and ±5bp for TRFs > 200). Table 4.512Predicted bacterial genera to generate a terminal restriction fragments (TRFs) with factor loadings |x| ≥ 0.60 on the PCA for each experimental treatment
107
4.5 RECOMMENDATIONS FOR FUTURE RESEARCH AND APPLIED
AGRICULTURE
Even though several studies have described the composition and
dynamics of microbial communities during composting (Wang et al., 2007), none
have examined the impacts of turning frequency, season or pile size on microbial
community structure on dairy manure composts or the effect of these process
parameters on compost maturity.
This study is the first, to our knowledge, to determine these effects.
Although the dairy manure sawdust compost supported growth of cucumber
without added fertilizer, the fertilized pots had higher shoot plant weight. It is
recommended to conduct some further studies to control, quantify and optimize
the concentration of nutrients in potting media to reduce nutrient leaching and,
therefore, improve the sensitivity of this test to compost maturity.
This work can be used as the first step of a step-wise approach for
identifying and confirming the predominant bacterial populations in composts. It
is also recommended to evaluate different microbial communities based on
different ribosomal subunits (i.e, 18S rDNA T-RFLP profiles) with different
restriction enzymes (i.e, RsaI, MspI, TaqI, Mbo, etc), and to use functional genes
to identify, if possible, the metabolic activities of the microorganisms present .
108
4.5 SUMMARY AND CONCLUSIONS
The different turning frequencies and pile sizes did not appear to have a
great impact on plant growth (dry and wet weight) and bacterial community
structure (p > 0.05). Cluster analysis on TRFLP profiles of the different
treatments revealed low similarities between composts of different age and
season but high similarities between composts of different turning frequencies
and pile sizes. Ppairwise comparison showed low similarities between small
windrows and larger piles (≤ 6%), but high similarities between microbial
communities from composts of different seasons and ages (≥ 70%). Principal
Component Analysis revealed changes in the bacterial communities in response
to age, size and season. In each treatment (turning frequency, pile size and age)
a different subset of TRFs contributed considerably to the variation along the first
three principal components. However, terminal restriction fragment M371
contributed significantly (p<0.1) to the observed variation with compost age.
According to RDP and a clone database, , fragment M371 is consistent with
Cytophaga sp, E.coli, Ewingella, Rothia and Bifidobacterium cuniculi. The effects
of management differences (turning frequency, pile size and season) did not
appear to affect significantly (p > 0.05) microbial communities; but different
classes of organisms predominated during different stages of composting.
109
APPENDIX A
PHYSICAL. CHEMICAL, BIOLOGICAL AND MOLECULAR PARAMETERS
ANALYZED DURING THE COMPOSTING PROCESS
WINTER
110
Physical. chemical, biological and molecular parameters analyzed during the composting process---WINTER
A Frequently
turned windrow
B Infrequently
turned windrow
C Infrequently turned pile
Properties Day Winter % Nitrogen 0 1.40 ± 0.18 1.40 ± 0.18 1.40 ± 0.18 30 1.50 1.50 1.40 60 1.88 1.90 1.94 90 1.80 1.80 1.70 120 2.70 2.60 2.60 % Carbon 0 52.75 ± 3.33 52.75 ± 3.33 52.75 ± 3.33 30 47.80 47.50 47.61 60 43.90 45.03 47.49 90 46.70 46.30 46.45 120 41.36 45.02 44.71 pH 0 8.25 ± 1.07 8.59 ± 0.01 8.35 ± 0.29 30 8.44 ± 0.71 8.85 ± 0.35 8.33 ± 0.06 60 8.57 ± 0.33 8.72 ± 0.46 8.39 ± 0.05 90 8.60 ± 0.11 8.31 ± 0.54 8.23 ± 0.29 120 8.62 ± 0.17 8.17 ± 1.00 7.94 ± 0.09%Moisture 0 65.36 ± 2.28 68.29 ± 4.44 66.11 ± 2.03 30 67.66 ± 0.96 69.27 ± 6.06 66.65 ± 3.12 60 74.05 ± 2.18 72.03 ± 6.85 72.44 ± 1.67 90 73.72 ± 0.11 74.17 ± 4.34 70.20 ± 1.13 120 68.78 ± 4.48 70.37 ± 5.88 67.46 ± 7.84Cumulative 0 0.17 ± 0.29 0.17 ± 0.29 0.00 ± 0.00Daily 30 1.48 ± 2.57 1.48 ± 2.57 1.48 ± 2.57Precipitation 60 7.92 ± 10.25 7.92 ± 10.25 0.00 ± 0.00(cm) 90 0.03 ± 0.04 0.03 ± 0.04 0.03 ± 0.04 120 0.01 ± 0.01 0.01 ± 0.01 0.01 ± 0.01Atmospheric 0 81.00 ± 3.61 81.00 ± 3.61 92.00 ± 6.93Humidity 30 70.00 ± 4.24 70.00 ± 4.24 83.00 ± 0.01% 60 40.33 ± 11.24 40.33 ± 11.24 58.00 ± 6.93 90 59.67 ± 6.35 58.00 ± 8.19 56.00 ± 0.01 120 64.00 ± 0.01 64.00 ± 0.01 64.00 ± 0.01% Volatile 0 94.17 ± 1.51 92.84 ± 2.85 93.82 ± 0.42solids 30 89.44 ± 1.89 88.96 ± 6.14 94.76 ± 0.82 g/g initial 60 85.32 ± 5.85 83.82 ± 2.79 79.45 ± 2.17 90 69.90 ± 9.76 78.22 ± 3.21 85.98 ± 0.86 120 76.53 ± 3.44 76.20 ± 10.86 69.06 ± 0.23Temperature 0 3.19 ± 3.80 4.56 ± 3.45 2.49 ± 2.36(°C) 30 38.41 ± 5.44 28.55 ± 18.56 43.61 ± 9.63Compost 60 48.51 ± 5.12 51.39 ± 19.18 43.38 ± 4.84 90 37.18 ± 7.51 44.56 ± 5.62 48.99 ± 6.50 120 42.10 ± 6.19 42.88 ± 5.66 41.56 ± 17 Temperature 0 -3.43 -3.43 -3.90 (°C) 30 -8.87 -8.87 0.33 Ambient 60 6.20 6.20 17.17 90 8.47 10.30 10.07 120 20.60 20.60 20.60
111
Physical. chemical, biological and molecular parameters analyzed during the composting process---WINTER
A Frequently turned
windrow
B Infrequently
turned windrow
C Infrequently turned pile
Properties Day Winter Oxygen 0 11.00 ± 7.75 11.14 ± 2.72 11.88 ± 6.70(%) 30 13.71 ± 7.65 8.29 ± 1.73 15.88 ± 7.15 60 15.00 ± 6.34 11.42 ± 5.62 13.30 ± 6.48 90 15.96 ± 6.07 8.90 ± 7.51 5.31 ± 5.09 120 9.75 ± 8.17 12.00 ± 3.70 12.38 ± 8.90μg DNA/g 0 0.36 0.36 0.36 Wet 30 16.35 23.84 37.75 Compost 60 19.03 18.47 18.07 90 8.47 24.20 21.57 120 8.73 10.30 15.43 Dry 0 125.13 126.42 117.61 Bulk 30 98.20 118.96 122.53 Density 60 117.31 105.34 110.44 Kg/m3 90 147.69 127.66 101.19 120 176.04 170.19 143.13 0 38.84 ± 2.85 27.52 ± 13.27 43.00 ± 1.21 30 31.50 ± 12.67 35.60 ± 5.39 39.93 ± 1.21Volume 60 26.14 ± 10.12 23.03 ± 0.79 36.84 ± 5.67 m3 90 14.41 ± 0.53 18.25 ± 6.57 20.48 ± 4.11 120 14.34 ± 0.91 21.78 ± 0.50 25.50 ± 0.50 0 0% 0% 0% Cumulative 30 19% -29% 7% volume 60 33% 16% 14% reduction 90 63% 34% 52% (%) 120 63% 21% 41% 0 69.31 ± 5.56 51.57 ± 17.24 42.75 ± 0.78 30 61.91 ± 15.72 67.53 ± 9.40 40.69 ± 0.87Area 60 55.06 ± 9.79 51.70 ± 1.56 38.61 ± 4.12 m2 90 40.75 ± 4.76 41.75 ± 10.23 26.36 ± 3.45 120 33.64 ± 0.07 46.94 30.64 Cumulative 0 0% 0% 0% area 30 11% -31% 5% reduction 60 21% 0% 10% (%) 90 41% 19% 38% 120 51% 9% 28% Surface 0 1.78 1.87 0.99 Area to 30 1.97 1.90 1.02 Volume 60 2.11 2.24 1.05 Ratio 90 2.83 2.29 1.29 120 2.35 2.15 1.20 0 2.37 ± 1.00 3.25 ± 1.46 1.75 ± 0.16Particle 30 2.43 ± 1.51 2.73 ± 1.35 1.06 ± 0.93size 60 3.90 ± 2.29 3.59 ± 2.37 3.12 ± 1.30(mm) 90 2.70 ± 3.05 2.98 ± 1.40 3.05 ± 0.63 120 2.59 ± 0.73 1.88 ± 0.62 1.97 ± 1.71
112
Physical. chemical, biological and molecular parameters analyzed during the composting process---WINTER
A Frequently turned
windrow
B Infrequently
turned windrow
C Infrequently turned pile
Properties Day Winter 0 100% ± 0.01 100% ± 0.01 96% ± 7.22 30 100% ± 0.01 100% ± 7.22 96% ± 0.01Germination 60 100% ± 0.01 100% ± 0.01 96% ± 0.01No-Fertilizer 90 100% ± 0.01 100% ± 0.01 96% ± 0.01(%) 120 100% ± 0.01 100% ± 0.01 96% ± 0.01 0 6.11 ± 0.75 8.37 ± 1.95 8.23 ± 4.00Wet Weight 30 5.06 ± 1.00 4.05 ± 0.60 5.24 ± 1.01No Fertilizer 60 4.95 ± 1.59 5.35 ± 1.01 4.75 ± 1.56(g) 90 6.33 ± 1.35 6.30 ± 2.57 5.95 ± 1.93 120 6.76 ± 0.67 5.58 ± 1.31 5.87 ± 1.61 0 0.93 ± 0.10 1.21 ± 0.17 1.20 ± 0.52Dry Weight 30 0.77 ± 0.17 0.65 ± 0.08 0.84 ± 0.19No Fertilizer 60 0.80 ± 0.25 0.84 ± 0.15 0.74 ± 0.26(g) 90 0.46 ± 0.04 0.50 ± 0.18 0.50 ± 0.14 120 0.98 ± 0.11 0.88 ± 0.05 0.89 ± 0.26Germination 0 100% ± 0.01 96% ± 7.22 100% ± 0.01Fertilizer 30 100% ± 7.22 96% ± 7.22 100% ± 7.22(%) 60 100% ± 0.01 96% ± 7.22 100% ± 7.22 90 100% ± 0.01 96% ± 0.01 100% ± 7.22 120 100% ± 0.01 96% ± 7.22 100% ± 7.22 0 13.09 ± 1.23 13.48 ± 1.70 14.90 ± 2.35Wet Weight 30 11.39 ± 0.75 13.68 ± 1.27 12.84 ± 0.81Fertilizer 60 12.38 ± 1.68 12.76 ± 1.56 12.79 ± 1.16(g) 90 10.53 ± 2.24 11.07 ± 2.87 12.86 ± 0.95 120 9.71 ± 1.61 7.49 ± 3.05 10.43 ± 0.23 0 0.97 ± 12.00 0.96 ± 0.14 1.07 ± 0.19Dry Weight 30 0.76 ± 0.04 0.94 ± 0.06 0.88 ± 0.04Fertilizer 60 0.83 ± 0.10 0.89 ± 0.07 0.89 ± 0.10(g) 90 0.72 ± 0.18 0.79 ± 0.16 0.93 ± 0.06 120 0.72 ± 0.11 0.56 ± 0.20 0.83 ± 0.02 0 81.00 ± 44.31 78.67 ± 42.33 367.00 ± 51 Time 30 104.67 ± 25.89 122.33 ± 78.65 300.01 ± 49 turning 60 75.67 ± 19.09 88.33 ± 27.15 453.33 ± 70 (sec) 90 50.33 ± 12.50 60.00 ± 26.87 422.00 120 piled Wet Mass 0 6144.6 ± 521.6 6152 ± 500.9 6424 ± 29 (kg) 120 2026 ± 200.1 2331 ± 527.3 3115 ± 141 Loss 67% 62% 52%
113
APPENDIX B
PHYSICAL, CHEMICAL, BIOLOGICAL AND MOLECULAR PARAMETERS
ANALYZED DURING THE COMPOSTING PROCESS
SUMMER
114
Physical. chemical, biological and molecular parameters analyzed during the composting process---SUMMER
A B C
Frequently
turned windrow Infrequently
turned windrow Infrequently turned pile
Properties Day Summer % Nitrogen 0 1.35 ± 0.1 1.35 ± 0.1 1.35 ± 0.1 30 1.53 1.5 1.5 60 1.88 1.85 1.9 90 1.78 1.85 1.78 120 1.8 2 2 % Carbon 0 50.56 2.6 50.6 ± 2.6 50.56 ± 2.6 30 47.6 47.3 47.41 60 42.1 43.2 45.69 90 49.2 45.1 43.75 120 44.5 43.1 44.17 pH 0 7.85 8.05 8.23 30 8.45 8.37 8.05 60 8.42 7.96 8 90 7.58 7.33 7.4 120 7.24 7.19 7.42 %Moisture 0 61.87 60.3 58.21 30 52.99 50.1 60.24 60 42.48 45.9 49.01 90 59.06 67 66.36 120 71.01 59.2 69.19 0 0 0 0 Cumulative 30 0 0 0 Daily 60 0 0 0 Precipitation 90 0 0 0 (cm) 120 0 0 0 Atmospheric 0 77 77 77 Humidity 30 68 68 68 (%) 60 79 79 79 90 72 72 72 120 75 75 75 % Volatile 0 93.09 93.8 93.46 solids 30 91.25 91.8 90.36 g/g initial 60 73.21 76.3 74.73 90 87.61 87.8 85.42 120 81 72.2 76.17 Temperature 0 36.35 ± 5.16 40.3 ± 0.6 37.63 ± 1.6(°C) 30 51.6 ± 3.01 47.7 ± 2.2 39.67 ± 13Compost 60 43.4 ± 1.05 25.4 ± 5.5 41.83 ± 9.2 90 46.33 ± 3.67 47.3 ± 1.6 37.22 ± 12 120 22.82 ± 2.88 7.28 ± 0.5 34.95 ± 3.8
115
Physical. chemical, biological and molecular parameters analyzed during the composting process---SUMMER
A B C
Frequently
turned windrow Infrequently
turned windrow Infrequently turned pile
Properties Day Summer Temperature 0 28 28 28 ( °C) 30 24.7 24.7 24.7 Ambient 60 22.9 22.9 22.9 90 3 3 3 120 -8.1 -8.1 -8.1 0 7 ± 3 17 ± 3.1 17.5 ± 8Oxygen 30 19.67 ± 0.01 19.5 ± 0.6 4.67 ± 1(%) 60 17.67 ± 0.01 19.5 ± 0 19.5 ± 0.9 90 19.5 ± 0.29 7.83 ± 0 17.33 ± 0.3 120 17.27 ± 0.01 18.8 ± 0 11.5 ± 11μg DNA/g 0 4.57 4.57 4.57 compost 30 19.48 7.18 21.69 (Wet) 60 25.61 24.5 11.44 90 16.74 17 15.7 120 8.91 9.87 9.05 0 127.05 135 143 Bulk Density 30 158.64 113 92.16 Kg/m3 60 191.87 162 168.5 90 135.7 78.1 114.6 120 145.58 151 182.3 0 24.45 23.7 31.23 30 22.1 21.2 27.63 Volume 60 18.93 18.9 26.02 m3 90 11.98 9.75 13.48 120 15.39 12.5 24.54 0 0% 0% 0% Cumulative 30 10% 11% 12% volume 60 23% 20% 17% reduction 90 51% 59% 57% (%) 120 0.37 47% 21% 0 48 51.1 34.45 30 47.1 50.3 32.13 Area 60 42.73 44.8 30.54 m2 90 30.84 28.1 19.67 120 42.87 37.8 29.35 Cumulative 0 0% 0% 0% area 30 2% 2% 7% reduction 60 11% 12% 11% (%) 90 36% 45% 43% 120 11% 26% 15%
116
Physical. chemical, biological and molecular parameters analyzed during the composting process---SUMMER
A Frequently turned
windrow
B Infrequently
turned windrow
C Infrequently turned
pile Properties Day Summer
0 100% 100% 100% 30 100% 100% 100% Germination 60 100% 100% 100% No-Fertilizer 90 100% 100% 100% (%) 120 100% 100% 100% 0 4.63 5.35 4.76 Wet Weight 30 4.91 4.64 5.39 No Fertilizer 60 5.98 5.15 4.77 (g) 90 4.20 3.92 6.29 120 4.11 4.63 8.03 0 0.37 0.45 0.45 Dry Weight 30 0.43 0.41 0.48 No Fertilizer 60 0.49 0.41 0.44 (g) 90 0.39 0.28 0.52 120 0.36 0.38 0.64 Germination 0 100% 100% 100% Fertilizer 30 100% 100% 100% (%) 60 100% 100% 100% 90 100% 100% 100% 120 100% 100% 100% 0 13.39 12.24 10.39 Wet Weight 30 9.68 11.91 8.84 Fertilizer 60 10.26 13.12 15.27 (g) 90 11.44 14.18 17.13 120 16.35 13.55 17.20 0 0.99 0.94 0.75 Dry Weight 30 0.74 0.90 0.66 Fertilizer 60 0.74 0.93 1.15 (g) 90 0.86 1.01 1.17 120 1.19 0.94 1.20 0 1.10 1.00 4.10 Time 30 1.12 3.19 6.14 turning 60 1.05 1.06 7.10 (sec) 90 1.21 1.15 7.06 120 PILED Wet Mass 0 3991.6 3919 3910 (kg) 120 2531 1923 2195 Loss 37% 51% 44%
117
Physical. chemical, biological and molecular parameters analyzed during the composting process---SUMMER
A B C
Frequently turned
windrow Infrequently turned
windrow Infrequently turned pile
Properties Day Summer Surface 0 1.96 2.15 1.1 Area to 30 2.13 2.38 1.16 Volume 60 2.26 2.37 1.17 Ratio 90 2.57 2.88 1.46 120 2.79 3.02 1.2 0 1.75 ± 0.01 1.57 ± 1.6 0.98 ± 1Particle 30 1.28 ± 0.11 1.47 ± 0.1 1.89 ± 0.6size 60 1.25 ± 0.05 1.32 ± 0 1.7 ± 0.1(mm) 90 1.31 ± 0.35 1.69 ± 0.2 1.86 ± 0.5 120 1.92 ± 0.21 2.03 ± 0.4 2.96 ± 1
118
119
APPENDIX C
OPERATION COSTS EQUATION
120
( ) ( ) ( ) ( )[ ]{ }MiSFeAmSRtSLrHc ÷÷++÷+÷=
( ) ( )[ ]{ } ( ) ( )[ ]{ }( ) ( ) ( )[ ]( )
( ) ( ) ( ) ( )[ ]{ }
( )[ ] ( )[ ]{ } ( ){ }LrHcMlturnLrPSmixLrP
MlturnMgivMlturnMgiiiMlturnMgiiMlturnMgi
MlmixMgiv
MlmixMgiiiMlmixMgiiMlmixMgiSDhHcCsIrSDhHcCmC Mg
++÷Θ×+÷Θ×
+÷Θ×+÷Θ×+÷Θ×+÷Θ×
+⎪⎭
⎪⎬⎫
⎪⎩
⎪⎨⎧
÷Θ×+
÷Θ×+÷Θ×+÷Θ×+÷+++÷×+=
∑
∑/$
Variables: - Hc Hauling cost ($/mile/Mg) - Lr rate of labor ($/h) - S speed (mph) - Rt Rent truck ($/h) - Am Additional mileage ($/mile) - Fe fuel efficiency ($/h) - Ml machine-truck load - Cm Cost of manure ($/Mg) - Cs Cost of sawdust ($/Mg) - Dh Distance hauled (miles) - Ir Initial bulking ratio - Mtype:I, ii, iii, iv Machinery type used (fuel efficiency) ($/h) - Ө Time (minutes) - P personnel
Assumptions:
- No costs of manure - Cost of Sawdust $35.00/Mg (Dalton Wood Products) - Initial ratio 3:1 (hardwood sawdust/manure) - Initial Moisture content 60% (This study) - Final Moisture content 40% (Market moisture) - Weight wet losses 70% (This study) - Constant speed 30mph - Medium Dump truck load: 7Mg - Fuel efficiency of Medium Dump Truck: 13.91 gal/h (Grisso et al., 2007) - Average fuel price $4.15/gal - Labor Rate: $ 15.00/h - Rent costs $60/h plus additional mileage $0.50/mile
121
122
APPENDIX D
POTENTIAL CLASSES OF BACTERIA FOR SAMPLES I (DAY 50), II (DAY 155)
AND III (DAY 330)-CLONE BANK.
Assesion Compost Pile Blast match AY921982.1 I,III Uncultured Chloroflexi bacterium clone AKYG1747 16S ribosomal RNA gene, partial sequence AY309119.1 I,II Uncultured bacterium clone WIM-Mc-53 16S ribosomal RNA gene, partial sequence AY921689.1 I,II,III Uncultured Chloroflexi bacterium clone AKYH1447 16S ribosomal RNA gene, partial sequence AB109432.1 II, III Uncultured Chloroflexi bacterium gene for 16S rRNA, partial sequence, clone:STG-2 AJ421905.1 II, III UBA421905 uncultured bacterium partial 16S rRNA gene, clone Alt9-K79 AY599186.1 I,II,III Uncultured gamma proteobacterium clone FH1-54 16S ribosomal RNA gene, partial sequence AB185000.1 I, II Uncultured bacterium gene for 16S rRNA, partial sequence, clone:TH-143 AF445671.1 I,III Uncultured gamma proteobacterium clone SM1D02 16S ribosomal RNA gene, partial sequence AY493939.1 I,II Uncultured soil bacterium clone 455 small subunit ribosomal RNA gene, partial sequence AY592559.1 II, III Uncultured bacterium clone Napoli-1B-02 16S ribosomal RNA gene, partial sequence AY922114.1 I,II Uncultured gamma proteobacterium clone AKYH1464 16S ribosomal RNA gene, partial sequence AY921889.1 I,III Uncultured delta proteobacterium clone AKYH682 16S ribosomal RNA gene, partial sequence AB041226.1 I, II Roseiflexus castenholzii gene for 16S rRNA, partial sequence AF392758.1 I, II Uncultured bacterium clone LBB1 16S ribosomal RNA gene, partial sequence AF452103.1 II, III Pseudomonas cellulosa 16S ribosomal RNA gene, partial sequence AJ292582.1 I,III UEU292582 uncultured eubacterium WD254 partial 16S rRNA gene, clone WD254 AY548937.1 I,II Uncultured bacterium clone 1-13 16S ribosomal RNA gene, partial sequence AY921711.1 I,III Uncultured Chloroflexi bacterium clone AKYG535 16S ribosomal RNA gene, partial sequence AY921831.1 I,III Uncultured Actinobacteria bacterium clone AKYG619 16S ribosomal RNA gene, partial sequence AY921918.1 II, III Uncultured Gemmatimonadetes bacterium clone AKYG1585 16S ribosomal RNA gene, partial sequence DQ088788.1 I,II Uncultured bacterium clone MP104-SW-b25 16S ribosomal RNA gene, partial sequence
123
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