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dissertation entitled
SIMULATION OF
DAIRY MANURE MANAGEMENT
AND TILLAGE SYSTEMS
presented by

TIMOTHY MARK HARRIGAN

has been accepted towards fulﬁllment
of the requirements for

Ph.D. degreein Ag. Tech. & Syst. Mgmt.

 

 

Major professor

 

Date Apr11 7, 1995

 

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SIMULATION OF
DAIRY MANURE MANAGEMENT AND TILLAGE SYSTEMS

By

Timothy Mark Harrigan

A DISSERTATION

Submitted to
Michigan State University
in partial fulﬁllment of the requirements
for the degree of

DOCTOR OF PHILOSOPHY

Department of Agricultural Engineering

1995

ABSTRACT

SIMULATION OF
DAIRY MANURE MANAGEMENT AND TILLAGE SYSTEMS

By

Timothy Mark Harrigan

The dairy forage system model (DAFOSYM) was expanded to evaluate
tillage and manure management alternatives for Michigan dairy farms. Sub-
models were added to predict draft and power requirements for tillage, planting
and manure hauling. A soil moisture balance and daily time-step were added to
predict suitable days for major ﬁeld operations. Labor scheduling sub-models
were added to allow varying the length of workday and number of simultaneous
ﬁeld operations. Through simulation, the long-term performance, cost and net
return for three tillage and four manure handling systems were compared on 60,
150, 250, 400 and BOO-cow representative dairy farms. The analysis included all
factors of harvest, storage, feed and animal production including manure
production, storage and application, tillage, planting, crop growth and machinery
use. Mulch-till was the most economical tillage system and increased net return
from $15-$39/cow-yr compared to conventional tillage. Modiﬁed no-till

improved timeliness and reduced fuel and labor use by 50% compared to

conventional tillage, but those savings were offset by higher seed, chemical and
fertilizer costs. Manure irrigation increased net return $20-$30/cow-yr over
slurry injection on most farms. Slurry injection tended to delay tillage and
planting unless additional labor and equipment were available to allow
simultaneous manure hauling, tillage and planting. These delays reduced corn
grain and silage yields and increased feed costs as much as $24/cow-yr when
conventional tillage was used. The greatest net return related to manure handling
was associated with short-term storage and daily hauling if manure nutrient value
was included. Net return ranged from minus $342/cow-yr with slurry injection
and conventional tillage on the 60-cow farm to $558/cow-yr with daily hauling

and mulch-tillage on the 800-cow farm.

ACKNOWLEDGMENTS

I would like to express my gratitude and appreciation to Dr. William G.
Bickert, mentor, colleague and friend, for his guidance throughout this study and
my graduate program. I also owe a debt of gratitude to Dr. C. Alan Rotz,
USDA-ARS for many helpful suggestions and help in understanding and
programming the DAFOSYM model. I am also grateful to the other members
of my guidance committee, Dr. Howard Person, Agricultural Engineering
Department; Dr. Larry Hamm, Department of Agricultural Economics and Dr.
John Partridge, Food Science and Human Nutrition for their patience and
suggestions.

My greatest debt is to my wife Leslie and our children--Matthew, Lauren
and Alan--for their support, understanding and encouragement. I’d also like to
thank my parents, Bob and Roseanne Harrigan for the gift of patience and

determination.

iv

TABLE OF CONTENTS

Page

LIST OF TABLES ........................................ ix
1. INTRODUCTION .................................... l
1.1 OBJECTIVES .................................. 6

2. LITERATURE REVIEW ............................... 7
2.1 ECONOMICS OF MANURE MANAGEMENT SYSTEMS . . 7

2.2 MANURE STORAGE AND HANDLING SYSTEMS ...... 9

2.2.1 Manure Storage Systems ..................... 9

2.2.2 Solid Manure Systems ...................... 12

2.2.3 Semi-solid Manure Systems .................. 13

2.2.4 Slurry and Liquid Manure Systems ............. 14

2.3 ODOR NUISANCE ............................. 15

2.4 TILLAGE SYSTEMS DEFINED .................... 16

2.5 ECONOMICS OF TILLAGE SYSTEMS .............. 17

2.6 DRAFT OF TILLAGE AND PLANTING EQUIPMENT . . . 18

2.6.1 Subsoilers ............................... 19

2.6.2 Liquid Manure Injectors ..................... 21

2.6.3 Moldboard Plows .......................... 22

2.6.4 Chisel Plows ............................. 23

2.6.5 Disk Harrows ............................ 25

2.6.6 Disk Coulters ............................ 26

2.6.7 Field Cultivators .......................... 27

2.6.8 Row Crop Cultivators ...................... 27

2.6.9 Row Crop Planters ......................... 28

2.6.10 Grain Drills .............................. 29

2.7 SOIL EROSION AND SURFACE RUNOFF ........... 29

2.8 MANURE RUNOFF ............................. 31

2.9 PREDICTING CROP RESIDUE COVER .............. 33

2.10 TILLAGE EFFECTS ON CROP RESIDUE ............ 33

vi

Page

2.11 CROP RESIDUE EFFECT ON SOIL WATER
EVAPORATION ............................... 34
2.12 TILLAGE AND RESIDUE EFFECT ON CROP YIELD . . . 35
2.13 SOIL COMPACTION ............................ 36
2.14 EFFECT OF MANURE ON SOIL PHYSICAL PROPERTIES 38
2.15 SUITABLE DAYS FOR FIELDWORK ............... 38
2.15.1 Suitable Days ............................ 39
2.15.2 Prediction of Suitable Days .................. 40
MODEL DEVELOPMENT ............................. 43
3.1 DEVELOPMENT OF THE TILLAGE DRAFT MODEL . . . 43
3.1.1 General Draﬁ Model ....................... 44
3.1.2 Subsoilers ............................... 46
3.1.3 Liquid Manure Injectors ..................... 49
3.1.4 Moldboard Plows .......................... 49
3.1.5 Chisel Plows ............................. 50
3.1.6 Sweep Plows ............................. 51
3.1.7 Disk Harrows ............................ 52
3.1.8 Single Disk Gangs ......................... 53
3.1.9 Disk Coulters ............................ 54
3.1.10 Field Cultivators .......................... 55
3.1.11 Row Crop Cultivators ...................... 55
3.1.12 Rotary Hoes ............................. 56
3.1.13 Rod Weeders ............................. 57
3.1.14 Minor Tillage Tools ........................ 57
3.1.15 Row Crop Planters ......................... 58
3.1.16 Grain Drills .............................. 59
3.1.17 Hoe and Pneumatic Drills .................... 60

3.2 INTEGRATION OF TILLAGE DRAFT DATA
WITH DAFOSYM .............................. 60
3.3 DEVELOPMENT OF THE SUITABLE DAY MODEL . . . . 62
3.3.1 Soil Moisture Budget ....................... 63
3.3.2 Soil Moisture Criteria for a Suitable Day ......... 65
3.3.3 Veriﬁcation of the Suitable Day Model .......... 68
PROCEDURE ...................................... 72
4.1 HERD, CROP AND PRICE INFORMATION ........... 73
4.2 NUTRIENT AVAILABILTY AND LOSS ............. 80

4.3 CROP NUTRIENT REQUIREMENTS ................ 82

vii

Page
4.4 TILLAGE SYSTEMS ........................... 82
4.5 MANURE HANDLING SYSTEMS .................. 87
4.6 SELECTION OF TILLAGE AND MANURE
HANDLING EQUIPMENT ........................ 89
4.7 SIMULATION PROCEDURE ...................... 90
RESULTS AND DISCUSSION .......................... 91
5.1 COMPARISON OF MANURE HANDLING COST
AND RESOURCE USE .......................... 91
5.1.1 Nutrient Recovery ......................... 92
5.1.2 Manure Storage ........................... 92
5.1.3 Machinery ............................... 93
5.1.4 Fuel Use ................................ 94
5.1.5 Labor .................................. 96
5.2 COMPARISON OF TILLAGE COST AND RESOURCE USE 98
5.2.1 Machinery ............................... 98
5.2.2 Fuel Use ................................ 99
5.2.3 Labor ................................. 100
5.3 NET RETURN ................................ 100
5.4 EFFECT OF LABOR SCHEDULE ON SYSTEM
PERFORMANCE .............................. 102
5.4.1 60-Cow Farm: Tillage and Manure
Handling in Series ........................ 103
5.4.2 Effect of Hours Worked, 60-Cow
Farm ................................. 104
5.4.3 ISO-Cow Farm: Tillage and Manure
Handling in Series ........................ 107
5.4.4 250-Cow Farm: Tillage and Manure
Handling in Series ........................ 109
5.4.5 250- Cow Farm: Parallel Tillage and
Manure Handling ......................... 111
5.4.6 400- Cow Farm: Parallel Tillage and
Manure Handling ......................... 113
5.5 APPLICABILITY OF THE SIMULATION RESULTS . . . 115
CONCLUSIONS ................... j ................ 1 17
RECOMMENDATIONS .............................. 1 19

LIST OF REFERENCES ............................. 120

viii
APPENDICES

APPENDIX A Subroutine SUITDAY ................... 144

APPENDIX B Annual Feed and Manure
Production, System Costs and

Net Return ........................... 151

Table 3.1

Table 3.1

Table 3.2

Table 3.3

Table 3.4

Table 3.5

Table 4.1

Table 4.2

Table 4.3

LIST OF TABLES

Draﬁ parameters for major tillage and seeding
implements .................................. 47

(cont’d) ..................................... 48

Tillage, planting and seeding implement draft and

machine operation parameters used in
DAFOSYM .................................. 61

Allowable fraction of ﬁeld capacity (Ci’s) for
various soil layers and ﬁeld operations ............... 67

Comparison by data source: expected proportion of
days suitable for tillage per time period on a well
drained, clay loam soil .......................... 69

Predicted suitable days (80% probability) for
tillage, planting, manure spreading and harvest in
central Michigan with three soils and three levels
of crop residue ................................ 70

Major descriptive parameters of the representative
farms used to evaluate and compare tillage and
manure management systems ...................... 74

Economic parameters and prices assumed for
various system inputs and outputs in the
representative farm analysis ....................... 75

Major machines and structures used for crop

harvest and storage on the representative 60 and
150-cow farms ................................ 77

ix

Table 4.4

Table 4.5

Table 4.6

Table 4.7

Table 4.8

Table 4.9

Table 5.1

Table 5.2

Table 5.3

Table 5.4

Table 5.5

Table 5.6

Page
Major machines and structures used for crop
harvest and storage on the representative 250 and
400-cow farms ................................ 77

Major machines and structures used for crop
harvest and storage on the representative 800-cow
farm ....................................... 78

Major dairy costs ($/cow-yr) above the net return
over feed, manure and tillage costs calculated by
DAFOSYM .................................. 81

Major machines and structures used for tillage,
planting and manure storage on the representative
60 and ISO-cow farms .......................... 83

Major machines and structures used for tillage,

planting and manure storage on the representative
250 and 400-cow farms .......................... 84

Major machines and structures used for tillage,
planting and manure storage on the representative

800-cow farm ................................ 85

Annual ownership costs for three manure storage
systems ..................................... 93

Annual ownership costs for tractors, loaders and
manure handling equipment ....................... 94

Fuel use for manure loading, transport. and
spreading .................................... 95

Labor used for manure loading, transport and
spreading .................................... 97

Annual ownership costs for tractors, loaders and
tillage equipment .............................. 99

Fuel use for tillage and planting .................... 99

Table 5.7

Table 5.8

Table 5.9

Table 5.10

Table 5.11

Table 5.12

Table 5.13

Table 5.14

xi

Labor use for tillage and planting .................

Net return for three tillage and four manure
spreading systems .............................

Predicted dates (50% probability) to begin and end
major ﬁeld operations for a 60-cow dairy in
central Michigan: one implement working six
hours per'day, manure application and tillage in
series .....................................

Predicted dates (50% probability) to begin and end
major ﬁeld operations for a 60-cow dairy in
central Michigan: one implement working eight
hours per day, manure application and tillage in
series .....................................

Predicted dates (50% probability) to begin and end
major ﬁeld operations for a 150-cow dairy in
central Michigan: one implement working ten
hours per day, manure application and tillage in
series .....................................

Predicted dates (50% probability) to begin and end
major ﬁeld operations for a 250-cow dairy in
central Michigan: two implements working ten
hours per day, manure application and tillage in
series .....................................

Predicted dates (50% probability) to begin and end
major ﬁeld operations for a 250-cow dairy in
central Michigan: two implements working eight
hours per day, parallel manure application and
tillage .....................................

Predicted dates (50% probability) to begin and end
major ﬁeld operations for a 400-cow dairy in
central Michigan: three implements working ten
hours per day, parallel manure application and
tillage .....................................

101

112

115

Table 8.1

Table 8.2

Table B.3

Table 8.4

Table B.5

Table 8.6

Table B.7

Table 88

xii

Annual feed and manure production, system costs
and net return with conventional tillage and four
manure handling systems on a high producing, 60-

cow dairy farm ............................

Annual feed and manure production, system costs
and net return with mulch tillage and four manure
handling systems on a high producing, 60-cow

dairy farm ...............................

Annual feed and manure production, system costs
and net return with modiﬁed no-tillage and four
manure handling systems on a high producing, 60-

cow dairy farm ............................

Annual feed and manure production, system costs
and net retum with conventional tillage and four
manure handling systems on a high producing,

ISO-cow dairy farm ........................

Annual feed and manure production, system costs
and net return with mulch tillage and four manure
handling systems on a high producing, ISO-cow

dairy farm ...............................

Annual feed and manure production, system costs
and net return with modiﬁed no-tillage and four
manure handling systems on a high producing,

ISO-cow dairy farm ........................

Annual feed and manure production, system costs
and net return with conventional tillage and four
manure handling systems on a high producing,

250-cow dairy farm ........................

Annual feed and manure production, system costs
and net return with mulch tillage and four manure
handling systems on a high producing, 250-cow

dairy farm ...............................

Page

151

152

153

154

155

157

158

Table 8.9

Table B.10

Table B.11

Table B. 12

Table 8.13

xiii

Annual feed and manure production, system costs
and net return with modiﬁed no-tillage and four
manure handling systems on a high producing,

250-cow dairy farm ........................

Annual feed and manure production, system costs
and net return with conventional tillage and four
manure handling systems on a high producing,

400-cow dairy farm ........................

Annual feed and manure production, system costs
and net return with mulch tillage and four manure
handling systems on a high producing, 400-cow

dairy farm ...............................

Annual feed and manure production, system costs
and net return with modiﬁed no-tillage and four
manure handling systems on a high producing,

400-cow dairy farm ........................

Annual feed and manure production, system costs
and net return with modiﬁed no-till and four
manure handling systems on a high producing,

800-cow dairy farm ........................

Page

159

161

162

1. INTRODUCTION

Agriculture makes an important contribution to Michigan’s economy.
Cash receipts ﬁom crops, livestock and livestock products were nearly $3.24
billion in 1993 (MASS, 1994). Michigan ranked seventh nationally in milk
production with nearly 2.45 billion liters (5.4 billion lbs) worth more than $715
million produced on the state’s 5,000 dairy farms. Crop, dairy and livestock
production were concentrated in the southern half of the lower peninsula where
more than 80% of the cattle and calves, 98% of the hogs, pigs and poultry and
95% of all corn, wheat, soybeans and dry beans were produced.

Many changes in tillage and planting equipment have occured during the
past 15 years. Conservation tillage practices are replacing moldboard plowing
and conventional seedbed preparation on an increasing number of crop acres.
Tillage tool components that allow a range of control over the amount of crop
residue left on the soil surface and combination tillage tools that combine
multiple tillage operations are now commonly used. Tillage practices that leave
crop residue on the surface throughout the year reduce runoff and wind and water
erosion and also offer an opportunity to reduce costs and labor requirements.

However, concerns regarding soil compaction, odors and the inability to

2

incorporate manure have slowed the adoption of these production practices on
livestock farms.

A mature dairy cow creates about 54 kg (120 lb) of manure per day
(MWPS, 1985; ASAE, 1993g). Manure properly managed is a valuable source
of crop nutrients, but poorly managed manure is a potential source of water
pollution. Many farmers object to the problems associated with manure
application including soil compaction, uneven and slow application rate,
introduction of weed seeds and the need for additional tillage for incorporation.
Because of these problems, commercial fertilizers largely replaced manure as the
primary source of crop nutrients and in many cases manure is spread with little
regard to it’s nutrient value or impact on the environment.

In recent years, the introduction of larger farms and more intensive
livestock operations has brought crop production and manure management
practices under closer scrutiny. Major environmental concerns include manure
odors and the possibility of surface and groundwater contamination. State and
Federal legislation has been enacted to protect the environment from both point
and nonpoint pollution. At the Federal level, the National Pollutant Discharge
Elimination System (NPDES, Sec. 401) focuses on water pollution from large
livestock operations. The Coastal Zone Act Reauthorization Amendments of
1990 (CZARA) are being designed to protect surface water quality. The

Conservation Compliance provision of the Food Security Act (FSA) will be fully

3

implemented by 1995 and will deny farm program beneﬁts to farmers not
following approved conservation plans. More than a dozen State laws have been
enacted to protect surface water quality (MDNR, 1993). The Michigan Right to
Farm Act (PA. 1981, No. 93) was adopted and amended in 1987 (PA. 1987,
No. 240) to protect the environment and to protect crop and livestock producers
from nuisance suits if they follow recommended manure management practices
regarding soil testing and nutrient management, timing and method of
application, record keeping and containment of contaminated runoff (Michigan .
Agriculture Commission, 1992).

Protection of the environment and safe and efﬁcient manure utilization
involves changes in both farm structures and management practices. A
combination of short term storage (32 months) and frequent hauling is preferred
for most Michigan herds (Connor et al., 1989). This is a low cost system, but
it may not be the best system for all farms. Short-term storage with frequent
hauling requires ﬁelds available year around for spreading, a steady supply of
labor and frequent incorporation of spread manure to minimize runoff and
maximize manure nutrient use (Sweeten et al., 1983; Holmes and Klemme,
1989). The greatest nutrient losses in runoff water are expected where manure
is spread on melting snow or frozen soil covered with ice (Klausner et al., 1976;
Steenhuis et al., 1981) so some researchers recommend that manure be stored

rather than spread on frozen ground (Minshall et al., 1970; Phillips et al., 1981).

4

Long-term manure storage with subsurface injection effectively minimizes odors
and runoff and conserves nutrients but this system is expensive and concentrates
labor for manure handling in the already busy period in the spring prior to
planting and in the fall after harvest.

Tillage and manure storage and handling systems vary greatly in labor and
machinery requirements, cost, compatibility with the environment and other
aspects of the farming system. The challenge for dairy farmers is to manage
these systems in a cost effective and environmentally safe manner. Crop and
livestock production represents a set of interacting processes that must be
considered to establish systems that serve both economic and environmental
objectives. An analysis of the many interactions of manure management with
other operations and processes on the dairy farm requires a systems approach
(Schulte and Krocker, 1976).

Linear programming (Coote et al., 1976; Saﬂey et al., 1977) and mixed
integer programming (Amir and Ogilvie, 1977) have been used to evaluate dairy
waste management systems. These studies optimized systems based on annual
net cost. Burney et al. (1980a,b) used network analysis to analyze the annual
cost, labor and energy requirements of major components of dairy manure
management systems. In Michigan, Garsow et a1. (1992) integrated information
from various manure and farm ﬁnancial management programs in an analysis of

the economic impact of environmental control measures for dairy farms. Borton

5

et al. (1995) used simulation to compare the long-term performance of semi-
solid, slurry and liquid manure handling systems.

These studies revealed information regarding the costs and interactions of
major components of dairy waste management systems. The need exists,
however, for a more comprehensive analysis of tillage and manure handling
systems which includes all factors of harvest, storage, feeding, animal production,
and manure handling. Such an analysis requires a model which integrates the
effects of weather, machinery, labor and other relevant factors on tillage,'
planting, harvest, manure storage and handling, and feeding of the dairy herd.
A simulation model of the dairy forage system called DAFOSYM (Rotz et al.,
1989) provides a basis for such a model. The model was previously used to
evaluate a variety of dairy forage systems including the use of hay preservatives
on high-moisture hay (Rotz et al., 1992), the beneﬁts and costs of round bale hay
storage (Harrigan et al., 1994), and dairy manure handling systems (Borton et al.,

1995).

1.1 OBJECTIVES

A comprehensive analysis was conducted using the dairy forage system
model DAFOSYM to compare tillage and manure handling systems on
representative dairy farms. Speciﬁc objectives were to:

1. Develop parameters for implement draft, power
requirements, speed and depth of operation for conventional,
mulch-till and modiﬁed no-till tillage and planting
equipment.

2. Develop sub-models in DAFOSYM which integrate the
effects of weather, machinery, labor and other relevant
factors on manure application and conventional and
conservation tillage and planting of corn and alfalfa.

3. Analyze the costs and labor requirements of representative
tillage and manure handling systems which include all major
interactions from harvest through manure application, tillage
and planting.

4. Compare the economics and performance of representative
tillage, planting, manure storage, handling and land
application systems on representative 60, 150, 250, 400 and

800-cow Michigan dairy farms.

2. LITERATURE REVIEW
2.1 ECONOMICS OF MANURE MANAGEMENT SYSTEMS

The close proximity of non-farm, rural residents to livestock operations
has lead to frequent disputes between farm and non-farm residents. Complaints
of excessive odor and surface and ground water contamination have become
common (Ackerman and Taylor, 1985; Barth et al., 1982; Van Kleeck and
Bulley, 1985; Brynildson 1989; Thelen, 1992; Harvey and Lohr, 1992). In some
cases, public and private nuisance statutes have been brought to bear against
livestock producers (George et al., 1985; Harvey and Lohr, 1992). Livestock
producers have found that environmental concerns have created a more
restrictive, tightly regulated and costly operating environment (Barth et al., 1982;
Harvey and Lohr, 1992).

Animal waste management and pollution control costs have been shown
to be regressive; the highest per unit costs are imposed on the smallest producers
(Johnson et al., 1973; Van Arsdall and Smith, 1974; Garsow et al., 1992;
Leatham et al., 1991). Leatham et a1. (1991) examined the impact of compliance
with Texas water quality laws on dairy proﬁtability and estimated additional
costs for 300 and 720 cow dairies to be $81 and $60 per cow-yr, respectively.
Bennett et al. (1991) compared lagoon and above-ground tank storage systems
within the context of Missouri waste management regulations and Clean Water

Act provisions. Compared to short-term storage, the lagoon system increased

8
milk production costs $0.18 to $027th ($0.40 to $0.60/cwt) and an above-

ground liquid tank increased costs more than $0.45/hL ($1/cwt).

In Michigan, Good et al. (1973), Johnson et al. (1973) and later Garsow
et a1. (1992) examined the economic impact of environmental control measures
for dairy farms including mandatory control of surface runoff, prohibition of
winter spreading, subsurface injection of liquid slurry or immediate incorporation
of solid waste. Each reported that control measures increased costs but did not
increase revenue. Garsow et al. (1992) predicted a negative return on
investments in manure storage and injection equipment and estimated a drop in
net farm income of $118/cow-yr for a 60 cow herd and $37/cow-yr for a 250
cow herd compared to short-term storage with daily haul.

Equipment ownership and operating costs for several manure storage and
land application systems have been reported (Johnson et al., 1973; Good et al.,
1973; Moore and White, 1983; Maschhoff and Muehling, 1985; Burney et al.,
1980a, 1980b; Bennett et al., 1991; Garsow et al., 1992; Borton et al., 1995;
Bennett and Fulhage, 1994). The lowest costs were associated with short-term
storage and daily hauling and the greatest with long-term liquid storage. Manure
handling costs increase signiﬁcantly with distance hauled (Borton et al., 1995).
The use of a nurse tanker is economical for transport distances greater than 1 km
(Maschhoff and Muehling, 1985; Borton et al., 1995). The most rapid and

proﬁtable transport and application system when hauling 91/2 million L (21/2 million

9

gal) of liquid swine manure an average of 10 km (6.2 mi) was two nurse tankers
for transport and a single vacuum tanker for land application (Maschhoff and
Muehling, 1985).
2.2 MANURE STORAGE AND HANDLING SYSTEMS

The choice of manure handling system depends in part on the amount of
bedding used, length of storage and the amount of water added. When only a
small amount of bedding and little additional water is added, manure is about
12%-14% dry matter (DM, wet basis) and can be handled as a semi-solid. When
manure is stored for long periods, water from precipitation, lot runoff, parlor
wash water and other water sources increases the moisture content of the stored
manure. Water use with an automatic prep stall can be about 34 L/cow-day (9
gal/cow-day) with additional water needed for cleaning the bulk tank, parlor floor
and other areas (MWPS, 1985). The addition of about 60 L/cow-day (16
gal/cow-day) will dilute the manure from a semi-solid (12%-14% DM) to a slurry
(8%-10% DM) for tank wagon transport. The addition of 115 L/cow-day (3O
gal/cow-day) creates a dilute slurry (5%-7% DM) suitable for liquid irrigation.
2.2.1 Manure Storage Systems

Manure storage facilities range from ﬂat slabs for solid manure to above
ground glass-lined tanks for slurry and liquid storage. Above ground roofed
storage has been used successfully for comfort stall arrangements where large

amounts of bedding are mixed with the manure (Tenpas et al., 1972; London and

10

Bickert, 1983). Drained (picket dam) storage provides a means of removing rain
water from uncovered solid storage systems (Loudon and Bickert, 1983). Above
ground storage tanks may be preferred where earthen storage cannot be used
because of space constraints, high groundwater, unstable subsoil or for aesthetic
reasons (Loudon and Bickert, 1983) but earthen pits provide the most cost
effective long-term storage (Garsow, 1992). Long-term manure storage provides
for a ﬂexible spreading schedule, timely use of manure as fertilizer and efﬁcient
use of equipment and labor (Moore and White, 1983).

A ﬂoating crust of bedding and organic material on the surface of a stored
slurry helps minimize odor (MSU, 1990), but environmental hazards related to
manure storage remain a concern. Potential problems involve both surface and
groundwater contamination. Research has been conducted to evaluate sealing
mechanisms, inﬁltration rates and seepage from existing earthen storage ponds
(Davis et al., 1973; Chang et al., 1974; Clark, 1975; Collins et al., 1975; Ritter
et al., 1980; Dalen et al., 1983; Barrington et al., 1987a, 1987b). Soil sealing of
an earthen basin was the result of physical, chemical and biological processes
(Davis et al., 1973; Chang et al., 1974; Barrington et al. 1987a, 1987b). A small
amount of seepage was reported in some cases (Sewell et al., 1975; Clark, 1975;
Dalen et al., 1983), but after initial sealing there was usually little effect more
than a few meters from the edge of the basin (Sewell et al., 1975, Collins et al.,

1975; Ritter et al., 1980). There was little correlation between initial soil

ll

hydraulic conductivity and ﬁnal manure inﬁltration rates (Chang et al., 1974;
Barrington et al., 1987a).

Minnesota recently revised their standards for agricultural waste storage
ponds because of concerns regarding seepage from earthen structures (Brach et
al., 1992). Conditions were established whereby, with a credit for manure
sealing, compacted soil liners would limit inﬁltration rates to 10'7 cm/sec. It was
thought that seepage could occur through macropores, cracks caused by freezing
and drying of the liner or through earthworm casts. It was also thought that
excessive seepage could occur prior to sealing and seals that were broken when
the pond was emptied would have to re-form when the pond was reﬁlled. And,
if physical sealing of soil pores was the primary sealing mechanism, inadequate
sealing might occur when storing contaminated runoff of low solids content such
as milking parlor waste water.

Michigan recommendations for earthen basin seepage control are to use
liners that meet speciﬁcations and guidelines outlined in the USDA-SCS Field
Ofﬁce Technical Guides (MSU, 1990). Conditions were established whereby,
with a credit for manure sealing, compacted soil liners limit inﬁltration rates to
10'7 cm/sec. In most situations, unlined earthen pits are not suitable and
supplemental pit liners are suggested. Suitable liners included ﬂexible

membranes, bentonite, high swell clay materials or concrete.

12
2.2.2 Solid Manure Systems

In northern climates, most solid systems are associated with stanchion
barns (London and Bickert, 1983). Solid manure storage is used where manure
dries or enough bedding is added to make it a stackable solid (Loudon and
Bickert, 1983; MWPS, 1985; ASAE, l993h). Total solids of 20% or more are
required for a stacking system if organic bedding materials are used (Holmes,
1989). On most dairy farms calf pens, maternity pens and young stock housing
are bedded and that material is handled as a solid even though manure from the
milking herd is stored and handled as a slurry or semi-solid (Loudon and Bickert,
1983). The investment in specialized structures and equipment is low for solid
systems since the manure and spent bedding are handled with conventional
bucket loaders and end gate or ﬂail type Spreaders (Burney et al., 1980a, 1980b;
Moore and White, 1983; Holmes and Klemme, 1989; Garsow, 1992; Borton et
al., 1995). Waste water, including parlor wash water, lot runoff and manure
drainage must be handled apart from the solid fraction (Holmes, 1989).

The characteristics of stacked manure have been reported by Cramer et a1.
(1973) and Converse et al. (1975). Based on 454 kg (1000 lb) live weight,
average manure production including bedding (4 kg/d, 8.7 lb/d) was 0.05 m3/d
(1.8 ft3/d) with an average density of 3.77 kg/m3 (60.3 lb/ft’) and total solids of
16.9% (Converse et a1. 1975). The average in-place volume was about 22% less

than the volume of manure collected indicating shrinkage during storage due to

13

the separation of liquids and solids. The solids content when removed from
storage was about 21%.
2.2.3 Semi-solid Manure Systems

Most of the new dairy barns built in Michigan are of free stall design.
Manure from most free stall barns can be handled as a semi-solid unless
additional water is added. Semi-solid manure has excess liquids drained off and
some bedding added to increase solids content (MWPS, 1985; ASAE, l993h).
Manure with total solids of 10-15% is suitable for direct loading to a box or V-
tank spreader (Sweeten et al., 1983). Semi-solid and solid manure can generally
be handled out of the same facility and with the same set of equipment (London
and Bickert, 1983; MWPS, 1985). Box type Spreaders are used primarily for
solid and semi-solid manure and V-bottom Spreaders are used primarily for semi-
solid and slurry manure (ASAE, 1993j). Sand-laden manure with total solids of
40% or more can be handled as a semi-solid but considerable storage and
handling problems may develop (Wedel and Bickert, 1994).

Drained storage has proven suitable in northern climates for short-term
storage of free stall manure and longer-term storage of more heavily bedded free
stall manure (Loudon and Bickert, 1983). Drained storage such as picket dam
structures allows rain water to drain from uncovered storage thus maintaining the

handling characteristics. But drained storage does not reduce the moisture

14

content of manure in storage (Loudon and Bickert, 1983; MWPS, 1985) and
additional facilities are required to contain and handle contaminated runoff.

Phillips (1980) compared semi-solid manure hauling and land application
systems for a lSO-cow dairy in Ontario, Canada. Manure averaging 14.3% DM
was loaded with a front-end loader and hauled with a box spreader. The system
was then modiﬁed and manure at 12.9% DM was loaded ﬁom storage with a
liquid manure conveyor and hauled with a spreader tanker. The hauling rate was
faster for the tanker than the box spreader due to faster loading and unloading
rates.
2.2.4 Slurry and Liquid Manure Systems

Manure can be handled as a liquid if additional water is added. Common
sources of dilution water are precipitation, lot runoff and milking parlor waste
water. Dilution to 8-10% is recommended for tank or retention pond storage and
spreading with a slurry tanker (ASAE, l993h). Both slurry and thin slurries
(liquid) are agitated prior to removal from storage to create a homogeneous
material for land application (ASAE, 1993j). Slurry manure is typically hauled
from storage with closed tanker Spreaders and can be either surface applied or
injected below the soil surface (ASAE, 1993j). Disadvantages of long-term
storage with tanker spreading include the high initial cost of the storage structure
(Moore and White, 1983; Holmes and Klemme, 1989; Garsow, 1992; Borton et

al., 1995), soil compaction from large tractors and spreader tankers (Culley and

15

Patni, 1987) and odor emission (Sweeten et al., 1983; Holmes and Klemme,
1989)

Dilute slurries can be applied through irrigation systems. Several systems
for liquid manure irrigation have been described (MWPS, 1985; Brodie, 1989).
Semi-solid manure with 10-15% solids can be pumped through irrigation
equipment using special pumps and gun nozzles (MWPS, 1985; Brodie, 1989),
but for traveling gun irrigation, dilution to 4-7% solids is recommended (Sweeten
et.al, 1983; ASAE, 1993b). Liquid irrigation systems have higher throughput
capacity than tank wagons, require less labor (Melvin, 1979; Borton et al., 1995)
and ﬁeld access is not restricted when soils are too wet to support heavy tractor
and spreader loads. Liquid irrigation of manure reduced costs compared to slurry
spreading with long-term storage (Borton et al., 1995), but over-application, wind
drift and odor transport are potential problems. Irrigation of sand-laden manure
is not recommended since sand tends to separate and obstruct the lines (Wedel
and Bickert, 1994).
2.3 ODOR NUISANCE

Manure management practices have contributed to offensive odor
emissions from livestock production facilities. The most common source of
odors are storage, treatment and land application areas. The objective of odor
control efforts is to reduce the frequency, intensity, duration and offensiveness

of odors and to manage the operation in a way that creates a favorable perception

16

of the operation (MSU, 1990). Factors inﬂuencing odor are site selection, design
of the manure handling components and the operation and management of the
waste facility.

Proximity to neighbors is the most important factor determining which
odor control procedures are needed (MSU, 1990; ASAE, 1993 0. Consideration
of neighbors is recommended to minimize nuisance complaints. The most
remote locations require the least intensive management and least expensive
technology. Wind dissipates odors and carries odor away from nearby neighbors.
Manure should be injected or incorporated by tillage soon after spreading. Odors
are reduced by spreading fresh rather than decomposed manure. Facilities and
animals should be kept clean and storage and treatment systems should be
designed for the operation.

2.4 TILLAGE SYSTEMS DEFINED

A tillage system defines a sequence of operations that manipulate the soil
to enhance seed germination and crop growth. Typical operations in a crop
production system include tilling the soil, planting, harvesting, chopping or
shredding residue and applying pesticides and fertilizers (Dickey et al., 1992a).
Tillage systems can be deﬁned by objective or by the major tillage implements
used. In Michigan, a typical conventional tillage system includes chopping or
disking corn residue after harvest, applying fertilizer or manure, and then tilling

the soil with a moldboard plow. Spring tillage includes disking and ﬁeld

l7

cultivating to incorporate manure and prepare a seedbed. Conventional tillage
systems leave almost no crop residue on the soil surface after planting.

Conservation tillage deﬁnes by objective a wide range of tillage systems.
The primary objective of conservation tillage is to minimize wind and water
erosion. Tillage system strategies to reduce erosion include: 1) protecting the
soil with crop residue or growing plants, 2) increasing surface roughness, 3)
increasing soil permeability, and 4) a combination of the three (Dickey et al.,
1992a). Mulch-till includes all conservation tillage systems other than no-till.
A wide range of tillage operations can be used in a mulch-till system as long as
enough residue cover remains for erosion control. No-till is a conservation
tillage system which leaves residue from the previous crop undisturbed on the
soil surface throughout the year. The only tillage is a narrow seedbed cut by a
coulter on the planter. Strip-till or zone-till is similar to no-till except that rather
than using a single coulter on the planter, a gang of coulters (2 or 3) is used to
till a wider seedbed (15-30 cm, 6-12 in.).
2.5 ECONOMICS OF TILLAGE SYSTEMS

The major costs inﬂuenced by tillage system selection are related to
machinery and herbicides (Siemens and Doster, 1992). Both labor and
machinery costs decrease as the amount of tillage or the number of tillage
operations decrease. Estimated labor costs for a 405 ha (1,000 ac) com-soybean

farm in central Illinois were reduced by 30% and machinery costs by 25% with

18

a no-till system compared to chisel and moldboard plow based systems (Siemens
and Doster, 1992). No-till required less equipment, labor and horsepower than
more intensive tillage systems.

Herbicide costs increase as tillage is reduced (Siemens and Doster, 1992).
In Illinois, typical herbicide costs for corn production range from about $25-
$37/ha ($10-$lS/ac) with a moldboard-chisel system and $37-$62/ha ($15-$25/ac)
with a no-till system. In Michigan, no-till ﬁelds frequently require additional
herbicides for grass control in the ﬁrst year of a crop in the rotation (Kells,
1994). Slug damage may also increase insecticide costs or decrease yields in no-
till ﬁelds (Landis, 1994). Corn and alfalfa seeding rates are often increased 5%-
10% in no-till ﬁelds to compensate for insect loss or reduced emergence in no-till
conditions.
2.6 DRAFT OF TILLAGE AND PLANTING EQUIPMENT

Draft information is frequently used in machinery management to calculate
power requirements of tillage and seeding operations. Farm managers and
consultants use draft or power data to match tractors with implements and to
estimate fuel requirements. Farming system computer models often require draft
and power data to: 1) select farm machinery; 2) simulate the performance of
farming systems; and 3) evaluate the performance of alternative farming systems.

Accurate information on draft requirements is needed to create valid models.

19

Many changes in tillage and planting equipment have occured during the
past 15 years. Conservation tillage practices are replacing moldboard plowing
and seedbed tillage on an increasing number of crop acres. Tillage tool
components that allow a range of control over the amount of crop residue left on
the soil surface and combination tillage tools that combine multiple tillage
operations are now commonly used (Siemens et al., 1992). Where seedbed
tillage is reduced or eliminated, the planter or drill becomes the most important
piece of equipment used. Many planters are now designed to cut through surface
residue and in some cases to till a zone of soil for the seed ﬁrrrow. Drafts for
these new tillage and seeding implements are different from those published in
the current ASAE Standards (1993a). An update of the ASAE draft data is
required to more accurately represent current tillage and seeding practices.
2.6.1 Subsoilers

Deep tillage operations such as subsoiling are not annual tillage operations
on most farms. But soils that are naturally compact or that have been
compressed by heavy vehicle trafﬁc on wet soil may beneﬁt from deep tillage.
If the problem lies below the normal tillage zone (20 cm, 8 in.), subsoiling may
be helpful.

Subsoiler draft is affected by soil texture, strength and moisture, tillage
depth, operating speed and subsoiler geometry. Since subsoilers are designed to

penetrate and shatter dense, high strength soil layers, draft tends to be highly

20

variable. Draft in clay soils can be more than twice that in sandy soils (Nichols
and Reaves, 1958; Frisby and Summers, 1979; Trouse and Reaves, 1980;
Wildman et al., 1978). Curved (parabolic) or inclined subsoil shanks typically
create 10% to 20% lower draft than vertical shanks at the same depth (Nichols
and Reaves, 1958; Smith and Williford, 1988; Upadhyaya et al., 1984). Garner
et al. (1987) reported greater draft in soils with a shallow B-horizon. Subsoiler
draft is reported as a positive linear function of depth (ASAE, l993a; Garner and
Wolf, 1981; Upadhyaya et a1, 1984) and quadratic with respect to speed (Owen,
1989; Upadhyaya et al., 1984).

Tillage tines shatter soil at an angle from a point just above the tine tip to
the soil surface (crescent failure). The angle of crescent failure varies but

generally ranges from 20°to 45° from vertical (Cooper, 1971; Spoor and Godwin,

1978; Koohestani and Gregory, 1985; Gregory and M’Hedbhi, 1988). Below a
critical depth, soil only ﬂows forward and sideways (lateral failure) around the
point, compacting soil in the area of the point without increasing soil disturbance
(Spoor and Godwin, 1978). The critical depth is a function of subsoiler point
geometry. Tines of similar width and rake angle have about the same critical
depth. The critical depth with a narrow subsoiler point is typically about 30 cm
(12 in.; Cooper, 1971) but is likely deeper in clay than sandy loam soils (Owen,
1988) and, in a given soil, deeper in friable than in wet and plastic conditions

(Spoor and Godwin, 1978).

21

Winged attachments are often added to conventional, narrow subsoiler
points to increase soil shatter. Wings increase both the critical depth (Owen,
1988; Spoor and Godwin, 1978) and the amount of soil disturbed (Spoor and
Godwin, 1978; Ahmed and Godwin, 1983). Spoor and Godwin (1978) measured
draft and area disturbed with conventional and winged (30 cm, 12 in.) points at
different depths. When winged and narrow points were operated above the
critical depth, the winged attachments more than doubled the disturbed area with
only a 30% increase in draft. When operated below the critical depth of the
narrow point, soil disturbance with the winged point was more than three times
that of the narrow point with only a 10% increase in draft. Reeder et a1. (1992)
reported that 25 cm (10 in.) wings increased draft about 70% and 35 cm (14 in.)
wings more than doubled the draft of a 5 cm (2 in.) point in a silt loam soil.
2.6.2. Liquid Manure Injectors

Direct soil injection of liquid manure conserves nitrogen and greatly
reduces the odor associated with land application. Subsurface injection of liquid
slurry is possible with up to 12% solids (Sweeten et al., 1983). A winged
injector can inject almost twice the volume at a given depth as a narrow injector
(Godwin et al., 1985). Winged injectors also distribute the manure over a wider
area and decrease the potential for root inhibition and nitrogen losses (Schmitt

and Hoeft, 1986). Winged injector points reduce draft requirements by creating

22

more void space and permitting shallower injection than possible with narrow
points (Godwin et al., 1976; Negi et al., 1978).

Liquid manure injector draft data are not included in the current ASAE
data. Winged injector (30 cm, 12 in.) draft ranging from 1.5 kN in loose sand
to 6 kN in clay loam was reported by Negi et al. (1978; 10 to 15 cm, 4 to 6 in.)
depth. In a ﬁrm clay soil, draft of 5 to 6.2 kN at a depth of 20 cm (8 in.) was
reported by Lague' (1991). Godwin et al. (1985) reported a draft of 5.4 kN at a
depth of 13 cm (5 in.). Hann et a1. (1987) reported a higher draft (1.9 kN) in the
wheel track of a loaded tanker (800 gal., 3,028 L) than behind an empty tanker
(1.1 kN) or an umbilical injector (1 kN). Scarborough et al. (1978) cited
Horsﬁeld (1974) indicating that compared to surface spreading, slurry injection
at 20 cm (8 in.) with a narrow point required 13.4 kW (18 hp) per injector in
addition to tanker rolling resistance.

2.6.3 Moldboard Plows

Moldboard plow draft data (N/cm2 of the cross-section of tilled soil) are
published for several soil textural groups ranging from sand to clay loam (ASAE,
1993a). Draft is described as a positive linear function of depth and quadratic
with respect to speed. The Standard notes that soil moisture and speciﬁc gravity

affect plow draft but the relationship is not quantiﬁed.

23

A model to predict moldboard plow draft utilizing soil moisture and
strength was proposed (Eradat Oskoui and Witney, 1982) and tested (Eradat
Oskoui et al., 1982). Draft was calculated as a function of soil cone index, soil
moisture, soil speciﬁc weight, depth and width of tillage, plow speed and plow
tail angle. When related to local meteorological data, the proposed model
predicted draft better than previous models.

Bowers (1989) reported a wide range in draft both between and within soil
textural groups. Differences within a textural group were presumably due to
varying soil moisture and strength. Frisby and Summers (1979) found that
predicted draft based on the ASAE Standard was high but within 10% of
measured values for clay and loam soils. Summers et al. (1986) evaluated the
effects of speed and depth on moldboard plow draft in clay loam and silt loam
soils in Oklahoma and reported that measured data was closely estimated by the
ASAE Standard. The draft data reported by Summers et al. (1986) conﬁrmed the
linear increase of draft with depth and the quadratic relationship with speed
described by ASAE.

2.6.4 Chisel Plows

Compared to a moldboard plow, a chisel plow can cover a ﬁeld faster,

requires less power, creates no back or dead furrows and can be managed to

leave signiﬁcant amounts of crop residue on the soil surface. The rough surface

24

of a fall chisel plowed ﬁeld traps snow and moisture and helps protect the soil
from wind and water erosion.

Draft is generally found to be a linear function of both depth and speed
(Summers et al., 1986; Kydd et al., 1984; Gregory and M’Hedbhi, 1988) but
draft has also been reported to be a quadratic function of depth (ASAE, 1993a;
Grisso et al., 1994). The current ASAE data for chisel plows are not consistent
with other implement data reported across soil textural groups. Unlike the
moldboard plow and disk harrow, draft is higher for medium than ﬁne textured
soils.

Chisel plow point selection affects soil shatter, soil inversion, residue
cover after tillage (Dickey et al., 1992b) and draft (Gregory and M’Hedhbi,
1988). Straight, 5 cm (2 in.) points shatter less soil and bury less residue than
7.5 cm (3 in.) or 10 cm (4 in.) twisted shovels. Wide sweeps are sometimes
used to undercut weeds and loosen soil without burying surface residue. Gregory
and M’Hedhbi (1988) reported that chisel plow draft should vary with the cross-
sectional area of the furrow formed during tillage. The cross-sectional area
formed by a chisel point is trapezoidal (Willatt and Willis, 1965; Koohestani and
Gregory, 1985) with the bottom width approximated by the width of the chisel
point. Based on the cross-sectional area described by Koohestani and Gregory

(1985) and a 30° crescent failure, chisel draft with a 10 cm (4 in.) point will be

25

about 15% greater and a 5 cm (2 in.) point 15% less than with a 7.5 cm (3 in.)
point.
2.6.5 Disk Harrows

Disks harrows and combination tillage tools using disk gangs are among
the most commonly used tillage implements. Disk harrows are used for primary
tillage, seedbed preparation, weed control and incorporation of manure, fertilizers
and herbicides. In the past, tandem disks typically had less mass per unit width,
smaller diameter blades and a narrower blade spacing than offset disks. Tandem
disks were generally used for secondary or light primary tillage while offset disks
were used for heavy primary tillage. However, in recent years large tandem disk
harrows similar to offset disks in mass, blade size, blade spacing and primary
tillage capabilities have become common (Krishnan, 1988). The assumed
difference in draft between tandem and offset disk harrows used in the past is no
longer justiﬁed.

Many factors affect disk harrow draft including gang angle, mass per
blade, blade type and spacing, operating depth and travel speed (Gill et al., 1981;
Gill et al., 1982; Schafer et al., 1991; Sommer et al., 1983). Draft data for disk
harrows is reported by ASAE (ASAE, 1993a) with draft expressed as a function
of implement mass, independent of speed and working depth. Draft in a medium
textured soil is estimated to be about 80% and in a coarse textured soil, 53% of

draft in a ﬁne texture soil. Bowers (1989) reported that the ASAE Standard for

26

disk harrow draft tended to underestimate measured draft for tandem disk
harrows in the medium and coarse textured soils of North Carolina.

Disk harrow draft is described as a positive linear function of speed and
depth (Kydd et al., 1984; Summers et al., 1986) but primary tillage draft has also
been reported to be a quadratic function of speed (Krishnan et al., 1988) and
depth (Grisso et al., 1994).

2.6.6 Disk Coulters

Most no—till planters and drills and many tillage implements use disk
coulters to cut surface residue and in some cases to till a narrow band of soil.
Draft data for coulters are currently not reported by ASAE. Based on soil bin
tests in sandy loam and clay loam soils, coulter draft and vertical forces are
lowest for thin coulters with small wedge slopes (Tice and Hendrick, 1992).
Choi and Erbach (1986) noted that a 46 cm (18 in.) coulter has better residue
cutting characteristics than a 41 cm (16 in.) coulter but residue cutting was more
affected by soil strength than coulter shape. Draft and vertical forces are shown
to increase with coulter depth and diameter (Choi and Erbach, 1986; Kushwaha
et al., 1986), increase with soil strength (Choi and Erbach, 1986) and increase
with the presence of crop residue on the soil surface (Kushwaha et al., 1986).
Coulter shape had no effect on draft or vertical forces but forces tended to be
higher for ﬂuted than notched, ripple or smooth coulters (Choi and Erbach,

1986). Bowers (1985) cited work by Trouse and Reaves (1980) for various types

27

of coulters in clay loam, silt loam and sandy loam soils where smooth coulter
draft was lower (15% to 40%) than that for ﬂuted and bubble coulters.
2.6.7 Field Cultivators

Field cultivators and combination tillage tools based on ﬁeld cultivator
design are among the most commonly used seedbed tillage implements. Draft
data for ﬁeld cultivators are published by ASAE (1993a) to be the same as that
for a chisel plow. Field cultivator draft is described as linear with speed and
quadratic with depth (ASAE, 1993a; Grisso et al., 1994).
2.6.8 Row Crop Cultivators

Row crop cultivators are designed for a wide range of soil and residue
conditions. S-tine shanks stir and loosen soil over a wide area and are suitable
for tilled ﬁelds with light or moderate residue (Springman et al., 1989). C-
shanks slice and lift the soil, cutting weeds and pushing soil aside and thus are
more suitable for harder soil and heavier residue. Conservation tillage (no-till)
cultivators are heavy duty cultivators suitable for hard soils and heavy residue
(Springman et al., 1989; Grisso and Schuler, 1992). Most no-till cultivators use
a cutting coulter and a single 41 to 61 cm (16 to 24 in.) sweep to undercut weeds
in the inter-row area. Some use cut-away disks to remove weeds adjacent to the

POW.

28
2.6.9 Row Crop Planters

Planting conditions in a conservation tillage system are not as uniform as
in a conventionally tilled ﬁeld with a prepared seedbed, but the planting
objectives are the same: open a seed furrow, place the seed at the correct depth,
cover and ﬁrm the soil over the seed. Most no-till planters use coulters to cut
the residue and till a narrow band of soil. Removing or incorporating the residue
from the soil surface allows faster soil warm-up and easier placement of
fertilizer. When two or three coulters per row are run side-by—side, a zone of soil
15 to 30 cm (6 to 12 in.) wide is tilled, loosened and cleared of most surface
residue.

Row crop planter draft are published in the current ASAE standard
(l993a). The Standard assumes a prepared seedbed in a loam soil and includes
motion resistance. Based on data reported by Frisby and Summers (1979), there
appears to be little difference in draft across soil textural groups when planting
in a ﬁrm, prepared seedbed. Bowers (1989) reported draft for seeding units only
in a loamy sand to be similar to that reported by Stephens et al. (1981) in a silt
loam soil. When planting with seed, fertilizer and herbicide application, planter
draft tends to be higher and more variable. Chapin et al. (1988) noted a 75%
increase in draft on a loamy sand when a ﬂuted coulter was added to cut through
crop residue but others have found little difference in planter draft between tilled

and untilled soils (Stephens et al., 1981; Bowers, 1989). Apparently, added

29

coulter draft was offset by lower rolling resistance in some situations. Measured
drafts ranging from about 1200 to 1800 N/row are common with no consistent
trends across soil textural groups (Bowers, 1989; Matthews et al., 1981; Reid et
al., 1983; Stephens et a1, 1981) even though a lower draft (500 to 1000 N/row)
is reported for some soils (Bowers, 1989).
2.6.10 Grain Drills

Draft for conventional grain drills is reported in the current ASAE data
(1993a). Draft includes motion resistance and the draft is independent of seeding
depth and speed. Kydd et al. (1984) observed little difference in draft with
ﬁrrrow openers raised or lowered so draft was assumed to be largely a function
of transport and press wheel rolling resistance. Grain drill draft does not appear
to be affected by soil texture when seeding in a prepared seedbed (Frisby and
Summers, 1979). Mungai ( 1991) reported conservation tillage drill draft to be
about 80% of that in a conventionally tilled seedbed on loam soil and 75% of
that on a sandy loam, presumably due to lower rolling resistance on ﬁrmer soil.
2.7 SOIL EROSION AND SURFACE RUNOFF

The effectiveness of conservation tillage systems is inﬂuenced by the
amount of crop residue on the soil surface (Gilley et al., 1986). Even small
amounts of crop residue reduce soil erosion (Mannering and Meyer, 1963; Meyer
et al., 1970; Laﬂen et al., 1981; Dickey et al., 1984, 1985; Gilley et al., 1986).

Corn or soybean residue covering 20% of the soil surface reduced soil loss by

30

50% compared to a bare surface (Dickey et al., 1984, 1985). As residue cover
increased, runoff decreased (Gilley et al., 1986; Laﬂen et al., 1981), runoff
velocity decreased (Gilley et al., 1986, Meyer et a1, 1970) and sediment
concentration in the runoff decreased (Mannering and Meyer, 1963; Laﬂen et al.,
1981; Dickey et al., 1984; Gilley et al., 1986). Total soil loss (Laﬂen et a1,
1981; Gilley et al., 1986) and the rate of soil loss (Gilley et al., 1986) also
decreased as residue cover increased.

Soil erosion is also inﬂuenced by soil disturbance and ﬁeld slope. As
tillage and soil disturbance decrease, soil loss tends to decrease. For a given
tillage system, soil loss increases with ﬁeld slope (Dickey et al., 1985). Laﬂen
et al. (1981) reported that there was no critical slope length beyond which crop
residue was no longer effective in reducing erosion, and for a given slope, as
residue cover increased, runoff rate, runoff velocity, sediment concentration and
soil loss rate decreased (Gilley et al., 1987). No-till systems are associated with
the least erosion and the least cumulative runoff (Dickey et al., 1984).

Frozen soil is associated with increased runoff and erosion (Chanasyk and
Woytowich, 1986). Ice decreases inﬁltration by blocking soil pores. Severe
erosion occurs from saturated, unprotected soil when the surface is thawed while
deeper soil is still frozen (Flerchinger and Saxton, 1989a; Edwards and Burney,
1989). Long duration, low intensity rainfall on frozen soil leads to soil erosion

similar to a severe summer storm on dry soil (Rudra et al., 1986).

31
2.8 MANURE RUNOFF

Manure runoff is a potential source of pollution. Runoff can occur from
animal holding, manure storage or land areas where manure is spread. The high
biological oxygen demand created by animal wastes is detrimental to ﬁsh (Long
and Painter, 1991), excess nutrients promote eutrophication of aquatic plants and
pathogens contaminate ﬁsh and drinking water. Pollution can be minimized by
using conservation tillage practices or buffer strips to prevent contaminated
runoff from reaching surface waters. Doyle et al. (1975) reported that a 7.6 m
(25 ft) forest buffer strip was effective in preventing stream pollution from
animal wastes. Vegetative ﬁlter strips were found to reduce nutrients, solids and
oxygen demanding materials by more than 80% on a concentration basis and
more than 95% on a weight basis (Dickey and Vanderholm, 1980). A terraced
pasture effectively removed nutrients and solids from dairy feedlot runoff in
South Carolina (Livingston and Hegg, 1980).

Some researchers have recommended that manure not be spread on frozen
ground (Minshall et al., 1970; Phillips et al., 1981). Late fall and winter
spreading of manure on frozen ground has led to pollution of surface water.
Nutrient loss from runoff increases in proportion to the length of time spread
manure remains on frozen, tilled soil (Hensler et al., 1970) but the greatest losses
follow heavy rain near the time of manure application (Hensler et al., 1970;

Minshall et al., 1970). Freezing, thawing and raindrop impact contribute to fecal

32

nitrogen loss (Steenhuis, 1975). Winter applications are thought to pose a greater
pollution risk due to decreased inﬁltration rates and longer survival of fecal
bacteria during the cool, damp winter months (Doyle et al., 1975).

The fate of the ﬁrst meltwater after winter spreading greatly affects
nutrient loss. When water inﬁltrates, losses are low but when the water runs off,
losses are high (Steenhuis et al., 1981). The greatest nutrient losses in runoff
water are expected where manure is spread on melting snow or frozen soil
covered with ice (Steenhuis, 1981; Klausner et al., 1976). Surface applications
of liquid manure on frozen soil led to greater nitrogen (N), phosphorus (P) and
potassium (K) concentrations in runoff water than incorporated spring, fall or
split spring-fall applications in Ontario, Canada (Phillips et al., 1981). Nutrient
concentration in the runoff increased in proportion to the manure application rate.
As much as 20% of N, 12% of P and 14% of K were lost from manure applied
to tilled, frozen soil (Hensler et al., 1970; Minshall et al., 1970).

Michigan recommendations are to avoid manure application on frozen or
snow covered soils if possible (MSU, 1990), but if winter applications are made,
solid manure should only be applied on slopes of 6% or less and liquid manures
on slopes of 3% or less. Erosion and runoff control measures such as
conservation tillage and vegetative buffer strips should separate manure treated

areas from surface water.

33
2.9 PREDICTING CROP RESIDUE COVER

Crop residue cover (%) increases with residue mass and residue mass is
correlated with grain yield at harvest. Corn, winter wheat and oats produce about
1 kg (2.2 lb), 1.7 kg (3.7 lb) and 2 kg (4.4 lb), respectively, of crop residue per
kg of grain produced (Robertson and Mokma, 1978; USDA-SCS, 1992). Residue
cover increases with crop yield and regression data based on these relationships
have been published (Gregory, 1982; Dickey et al., 1984; Gilley et al., 1986;
Smith et al., 1987). Greb (1967) estimated that 3,600 kg/ha (3,200 lb/ac) of ﬂat,
uniformly distributed wheat residue was needed for 100% soil cover but more
was needed under ﬁeld conditions. More than 3,600 kg/ha (8,000 lbs/ac) of corn
residue was needed for 100% cover (Gregory, 1982; Dickey et al., 1984; Smith
et al., 1987). High-yielding corn typically left 90%-95% cover and small grains
and lower yielding corn left 70%-85% cover (Shelton et al., 1992b).

Crop residue decays and is lost over time. The rate of residue
decomposition is a function of time, temperature, moisture and the initial
carbonznitrogen ratio (Ghidey et al., 1985). Smith et al. (1987) reported corn
residue lost over winter in Nebraska in the range of 10-15%.' Ghidey et al.
(1985) reported a 71% loss of corn residue over 10 months in Missouri.

2.10 TILLAGE EFFECTS ON CROP RESIDUE
There is an interaction of residue and tillage implement on the amount of

residue cover left after tillage. Soybean and dry bean residue are fragile and

34

much more likely to shatter and be buried during tillage than non-fragile residue
such as corn, wheat, oats or hay (Shelton et al., 1992b). A single pass of a chisel
plow with twisted points will leave 40-70% of non-fragile residue on the soil
surface but only 10-30% of a fragile residue. Colvin et al. (1986) reported
residue changes during tillage ranging from 80% disappearance of soybean
residue following a single pass of a chisel plow to an increase due to uncovering
of buried residue by a no-till planter. Shelton et al. (1992b) listed expected
reductions in residue cover for each pass of several tillage implements.
2.11 CROP RESIDUE EFFECT ON SOIL WATER EVAPORATION

Water is removed from the soil proﬁle through drainage, plant use and
evaporation. Early in the spring and after harvest when a crop is not growing,
evaporation is required to remove soil moisture to a level below ﬁeld capacity
and suitable for tillage. Evaporation is largely inﬂuenced by solar radiation,
temperature, wind and the interaction of temperature and wind (Brun et al.,
1986). Since crop residue reﬂects solar radiation and reduces both wind velocity
and temperature at the soil surface, the rate of soil water evaporation is reduced
by residue cover (Bond and Willis, 1969; 1970; Smika, 1983; Brun et al., 1986;
Aase and Tanaka, 1987).

Evaporation occurs in three stages (Bond and Willis, 1969; 1970). During
the ﬁrst stage, the rate of water loss is high, similar to a free water surface and

controlled primarily by external conditions. Much of the total water loss occurs

35

during the ﬁrst (constant rate) stage. The second stage begins when dry soil
appears. The hydraulic properties of the soil begin to regulate drying so the
drying rate decreases rapidly. During the third stage, evaporation is almost
entirely by vapor diffusion; the drying rate is slow and relatively constant. Crop
residue cover has the greatest effect during Stage 1 when the soil surface is wet
(Bond and Willis, 1969). Bond and Willis (1969) measured a nearly linear
reduction in Stage 1 drying as residue cover approached 100%.

Cumulative evaporation has been shown to be related to both precipitation
frequency and amount. When rains were infrequent and light and evaporation
continued for an extended time, there was little difference in cumulative
evaporation between bare or residue covered surfaces (Bond and Willis, 1969;
Brun et al., 1986; Aase and Tanaka, 1987). But as rainfall increased in
frequency and amount, there was less cumulative evaporation from a stubble
covered than a bare soil (Brun et al., 1986).

2.12 TILLAGE AND RESIDUE EFFECT ON CROP YIELD

Corn grown in a no-till system may yield less than corn grown in more
conventional tillage systems (Grifﬁth et al., 1973; Erbach, 1982; Griffith et al.,
1992). No-till corn grain yields tend to be lower on ﬁne textured, poorly drained
soils than on medium or coarse textured soils (Grifﬁth et al., 1992). The lower

yields are attributed to low soil temperatures early in the growing season due to

36

crop residue cover (Allmaras et al., 1964; Kaspar et al., 1987; Kaspar et al.,
1990; Swan et al., 1987; Al-Darby and Lowery, 1987).

Crop residue may also have allelopathic effects when com follows corn
in a rotation. Aqueous extracts of corn residue were shown to reduce corn
seedling growth under laboratory conditions (Yakle and Cruse, 1983; 1984).
Deep or primary tillage did not seem to affect corn emergence as much as the
amount of surface residue (Erbach et al., 1992; Erbach and Kaspar, 1993).
Shinners and Wang (1992) reported that a 20-30 cm (8-12 in) residue free band
appeared optimal with respect to early season soil warm-up and crop emergence.
2.13 SOIL COMPACTION

Badger (1972) noted that producers valued manure as a soil amendment
but noted several drawbacks from using manure including soil compaction. Soil
compaction is the reduction of pore space from the compression of the soil. An
ideal soil has about 50% of its total volume as pore space (Robertson and
Erickson, 1980). Compact soil layers have inadequate pore space for drainage,
aeration and root growth. Soil compaction can delay emergence of corn plants,
reduce plant height and grain yields and increase grain moisture at harvest
(Erbach et al., 1988; Voorhees et al., 1989). In the short-term, soil compaction
can be alleviated by tillage (Cooper, 1971). In the long-term, natural phenomena
such as wetting and drying and freezing and thawing also reduce soil compaction

(Larson and Allmaras, 1971). Deep soil compaction can persist for at least four

37

years despite annual freezing and thawing (Voorhees et al., 1986; Lowery and
Schuler, 1991).

Some Michigan soils have naturally compact soil layers (Johnson et al.,
1986) but most soil compaction is caused by heavy vehicle trafﬁc. Tillage or
vehicle induced soil compaction was greater in wet than dry soils (Voorhees et
al., 1986; Voorhees et al., 1989; Robertson and Erickson, 1980). Most tire
sinkage (70-90%) occurs on the ﬁrst wheel pass (Guo and Schuler, 1992; Taylor
et al., 1982) as does the greatest increase in soil density (70%; Taylor et al.,
1982). Repetitive trafﬁc leads to excessive deep compaction under both
moderate (3.8 t; Petelkau and Dannowski, 1990) and heavy (13.8 t; Wood et al.,
1993) axle loads. Finer textured (clay) soils are more susceptible to soil
compaction than medium textured (loam) soils (Gameda et al., 1985; Lowery and
Schuler, 1991).

There appears to be an interaction of weather and deep compaction on
grain yield. A small amount of compaction tends to increase yield in years when
soil moisture is short and decrease in years when the soil is wet (Wolf et al.,
1981; Gameda et al., 1985; Voorhees et al., 1989; Voorhees, 1990; Johnson et
al., 1990; Bicki and Siemens, 1990). Soil compaction has a greater impact on
poorly drained than well drained soils (Voorhees et al., 1986). Gruber and
Tebrt'igge (1990) reported that the danger of subsoil compaction is less with

reduced tillage systems. Less tilled soils are reported to be more resistant to

38

vehicle trafﬁc and exhibit less tire sinkage and pore volume change as well as
lower measured soil stress beneath the wheel load. Robertson et al. (1979)
reported improved crop yields when compact soil layers below the plow layer
were broken, but only if the soil was relatively dry at the time of tillage.
2.14 EFFECT OF MANURE ON SOIL PHYSICAL PROPERTIES

Several researchers have reported beneﬁcial effects of manure on soil
physical properties. Manure application can improve aggregate stability (Elson;
1941, 1943), increase soil water holding capacity and decrease soil water
evaporation (Unger and Stewart, 1974). Manure is reported to increase soil
organic matter, decrease soil bulk density (Mathers and Stewart, 1980;
Sommerfeldt and Chang, 1985) and increase hydraulic conductivity (Mathers and
Stewart, 1980). The addition of organic matter from manure can improve water
inﬁltration (Mazurak et al., 1955; Minshall, 1969; Swader and Stewart, 1972;
Converse et al., 1976; Mathers et al., 1977) and increase soil moisture in the
plow layer (Wilkins and Rasmussen, 1993). Lower tillage tool draft requirements
are reported in manure applied soils (Sommerfeldt and Chang, 1985; Wilkins and
Rasmussen, 1993).
2.15 SUITABLE DAYS FOR FIELDWORK

Machinery selection for ﬁeld work is inﬂuenced by many factors. Labor
hours available, number of operations carried out and crop acreage are among the

most important (Edwards and Boehlje, 1980). Soil type and crop and weather

39

parameters are also important (Rotz and Black, 1985). Important crop parameters
include penalties (costs) for crop loss due to untimely ﬁeld operations. These
timeliness penalties are generally the result of adverse weather limiting the
number of days suitable for ﬁeldwork or, under more normal conditions,
selecting a machinery set too small to complete the ﬁeldwork in a timely fashion.
A machinery complement capable of completing the required operations within
a speciﬁed time in 8 years out of 10 generally provides the best basis for
selection (Elliott et al., 1977; Rotz et al., 1983; Rotz and Black, 1985).
2.15.1 Suitable Days

Suitable working days are the days available in a scheduled period during
which ﬁeld operations can be performed (Von Bargen et al., 1986). The number
of suitable days in a time period is inﬂuenced by climatic region, soil slope and
texture, drainage, operation to be performed and traction and ﬂotation devices
(ASAE, l993a). Field operations that delay the timely planting of corn increase
the risk of economic loss for both crop and livestock producers. Early planting
of corn is important whether harvested for silage or grain. In southern Michigan
there was an average grain loss of 63 kg/ha (l bu/ac) for each day of delay past
the recommended May 1-10 planting period (Erdmann and Hildebrand, 1977).
Early planted corn produced higher yielding, higher quality corn silage.

Compared to corn planted May 9, total silage yield decreased 7% and 9% for

40

com planted May 22 and June 2, respectively. Silage quality declined as the
grain content fell from 54% to 43% with the late planting.

A common strategy for manure land application is to spread stored manure
and till the soil in the spring prior to planting and in the fall after corn harvest.
Since timeliness penalties for corn planting begin to accumulate in early May and
soil conditions for tillage and spreading deteriorate rapidly in the fall, selecting
machinery capable of completing ﬁeld operations within the time available is
particularly important.

2.15.2 Prediction of Suitable Days

Estimates of suitable days for ﬁeldwork have been derived from historic
records of crop and ﬁeld conditions (Fulton et a1, 1976). This data is useful in
the geographic area where collected but it is not transferable to other areas and
new data is difﬁcult to acquire. Records over several years are needed to
estimate the probability of suitable conditions over a period of days (Selerio and
Brown, 1972). An alternative method to predict suitable days is computer
simulation. Models have been developed that impose soil trafﬁcability criteria
on a soil moisture balance. Models that included precipitation, runoff,
evapotranspiration and drainage showed good results when compared to
validation sources (Selerio and Brown, 1972; Dyer and Baier, 1979; Acharya et
al., 1983). Crop residue effects were added to some models (Elliott et al., 1977;

Von Bargen et al., 1986) while others included the possibility of snow cover or

41
frozen soil (Rutledge and McHardy, 1968; Baier, 1973; Tulu et al., 1974;

Rosenberg et al., 1982; McGechan and Cooper, 1994) or rainfall on the day of
scheduled ﬁeld operations (Elliott et al., 1977; Rosenberg et al., 1982; Acharya
et al., 1983).

Soil texture and drainage affect water holding capacity and water
movement through the soil and are important factors inﬂuencing the number of
days available for ﬁeld operations (Elliott et al, 1977; Rosenberg et a1, 1982). p
In southern Michigan, sandy soils were estimated to provide about 15% more
suitable days than clay soils (Rosenberg et al., 1982). In Indiana, coarse textured
soils allowed about 10% more and ﬁne textured soils about 15% less suitable
days than a medium textured soil (Parsons and Doster, 1980). In southern
Ontario, about 15% more time was expected on sandy than clay loam soils
(ASAE, l993b).

Since crop residue reﬂects solar radiation and reduces both wind velocity
and temperature at the soil surface, the rate of soil water evaporation is reduced
by residue cover (Bond and Willis, 1969, 1970; Smika, 1983; Brun et al., 1986;
Aase and Tanaka, 1987). This shading of the soil reduces the number of days
suitable for ﬁeldwork. Residue cover has the greatest effect during Stage 1
evaporation when the soil surface is wet (Bond and Willis, 1969). Bond and
Willis (1969) measured a nearly linear reduction in Stage 1 drying with

increasing residue cover until the soil was completely covered. Increasing

42

residue beyond 100% cover continued to reduce drying but at a diminished rate.
Cumulative evaporation from soil cores fully shaded by wheat residue was about
40% of that from a bare soil surface during the ﬁrst 3 to 4 days of Stage 1
drying (Bond and Willis, 1969). The straw was clean, bright and uniformly
distributed and probably reﬂected solar radiation more effectively than could be
expected of weathered residue. The evaporation potential of shaded columns
ranged ﬁ‘om about 40% to 60% of unshaded soil columns (Bond and Willis,
1970) and Stage 1 evaporation of soil covered with 4,600 kg/ha (4,100 lb/ac) of
wheat residue was about 63% of that from bare soil (Aase and Tanaka, 1987).
A less pronounced reduction in Stage 1 drying (80% of a bare surface) was

reported by Brun et al. (1986) for a ﬁeld covered with wheat residue.

3. MODEL DEVELOPMENT

DAFOSYM is a comprehensive computer model that simulates alfalfa and
corn growth, harvest, storage, feeding, and use on a dairy farm (Rotz et al.,
1989). Recently, submodels were added for manure production, collection,
storage and application (Borton et al., 1995). To enable the simulation and
evaluation of the interaction of manure storage, land application and tillage
systems, submodels were added to predict suitable days under a range of soil and
crop residue conditions, draft of a wide range of tillage and seeding implements
and scheduling of tillage, planting and manure application.
3.1 DEVELOPMENT OF THE TILLAGE DRAFT MODEL

The draft force required to pull a tillage or seeding implement is primarily
a function of the width of the implement and the speed at which it is pulled.
Tillage draft is inﬂuenced by site speciﬁc conditions including soil type,
moisture, density and residue cover (Michel et al., 1985). Draft also depends
upon operating depth (Summers etal., 1986; Khalilian et al., 1988; Grisso et al.,
1994) and geometry of the tillage tool (Upadyaya et al., 1984). Wide variations
in draft are common both within and between soil textural groups (Bowers et al.,
1989). Equations have been developed for speciﬁc implements such as the
moldboard plow (Oskoui and Witney, 1982; Oskoui et al., 1982) which relates
draft to site speciﬁc conditions, but valid results require detailed information

about soil conditions. Dafosym requires a general model which provides

43

44

reasonable values for most conditions without knowledge of speciﬁc soil
conditions.

Available information on draft requirements for tillage and seeding
equipment was reviewed. Draft was deﬁned as the force required to propel an
implement in the direction of travel (ASAE, l993e). Unless noted otherwise,
draft required to overcome rolling resistance of the implement was included. The
two major phases of this work were: 1) to develop a model with machine-speciﬁc
parameters that predicts typical draft requirements for major tillage, planting and
seeding implements and 2) to integrate this model in DAFOSYM for predicting
tillage and planting power requirements.

3.1.1 General Draft Model

A simple function was used to model tillage draft under general conditions
where draft is a function of soil texture, implement width, depth and speed of
operation:

D=Fi* [A+B(S)+C(S)2] * W*TD
where

D is implement draft, kN (lbf).

F is a soil texture adjustment factor.

i is l for ﬁne, 2 for medium and 3 for coarse textured soils.

A, B and C are machine speciﬁc parameters.

S is speed, km/h (mph).

45

W is machine width (m, ft), number of rows or tools.

TD is tillage depth (cm, in.) for major tillage tools, 1 (unitless) for minor

tillage tools and seeding implements.

Although the same equation was used for all machines, only one or two of the
parameters were used to describe the draft of any given machine.

A form of this model was previously used by Summers et al. (1986) for
reporting moldboard plow, chisel plow, sweep plow and disk harrow draft.
Compared to using several different equations, this simple equation with machine
speciﬁc parameters has the advantage of being easily understood and convenient
to use. Draft data can be estimated per unit of depth of operation for most major
tillage tools. A description of tillage tools and components has been provided
by Siemens et al. (1992) and can be found in the ASAE Standards (19930, d, e).

Rather than using traditional soil textural classiﬁcations such as clay or
loam, the proposed data categorize soil groups as ﬁne, medium or coarse. Fine
textured soils can be described as predominantly clay, medium textured are
loamy soils and coarse textured are sandy soils. This method of grouping soils
has been used by Rotz and Black (1985) and to a limited extent by others (Hunt,
1977; White, 1977). This form of classiﬁcation is currently being used by some
tillage implement and herbicide application equipment manufacturers.

A major part of the model development was to determine the machine

speciﬁc parameters A, B and C. Each term is a function of tillage tool geometry.

46

In addition, the constant term A is a function of soil strength while the
coefﬁcient of speed terms (B or C) are related to soil bulk density. Soil strength
was assumed to decline and bulk density to increase from ﬁne to coarse textured
soils.

The primary source for new draft data was published research. In some
cases, the machine parameters were published for speciﬁc conditions and, based
on a comparison of reported data across soil textural groups, extrapolated to a
wider range of conditions. If parameter estimates were not previously published,
the draft/speed relationship was estimated from published data of similar tools
and the ratio of the coefﬁcient of speed (B or C) to the constant (A) was
maintained. Data selected were not necessarily means of available data but
values which seemed most reasonable for typical conditions.

3.1.2 Subsoilers

Reported draft for a conventional subsoiler shank varies widely, ranging
from 90 N/t/cm (51 lb/t/in., Wolf et al., 1981) to 675 N/t/cm (385 lb/t/in.,
Wildman et al., 1978). Based on a comparison of reported draft across soil
textural groups, subsoiler draft in medium and coarse textured soils is estimated
as 70% and 45%, respectively of that for ﬁne textured soils (Bowers, 1989;
Cooper, 1971; Godwin et al., 1985; Khalilian et al., 1988; Mielke et al., 1992;
Reeder et al., 1992; Shinners, 1989; Smith and Williford, 1988; Smith, 1989;

Spoor and Godwin, 1978; Trouse and Reaves, 1980; Wildman et al., 1978;

 

 

 

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49
Williams et al., 1979; Wolf et al., 1981). Draft is linearly related to depth and

quadratic with respect to speed (Table 3.1). At 6.4 km/h (4 mph), the proposed
draﬁ ranges from about 135 to 300 N/t/cm, similar to current ASAE data which
ranges from about 150 to 315 N/t/cm. Draft for a subsoiler with 30 cm (12 in.)
winged points is estimated as that for a narrow point increased by 30% (Spoor
and Godwin, 1985).
3.1.3 Liquid Manure Injectors

The proposed liquid manure injector draft data do not include tanker
rolling resistance. Similar to subsoiler draﬁ, the proposed data (Table 3.1) are
a positive linear function of depth and quadratic with speed. Draﬁ in medium
and coarse textured soils is estimated as 70% and 45%, respectively, of that for
ﬁne textured soils. The proposed data for injector draft in a ﬁne textured soil are
similar to that reported by Godwin et al. (1985) and Negi et al. (1978) for
winged injectors in clay loam and Lagué' (1991) in ﬁrm clay soils. Based on the
proposed data, injector draﬁ ranges from 200 N/t/cm in a coarse textured soil to
450 N/t/cm in a ﬁne textured soil (Table 3.1).
3.1.4 Moldboard Plows

Since most reported plow draﬁ data are in reasonable agreement with the
current ASAE data (Bowers, 1985; Bowers, 1989; Chaplin et al., 1986; Frisby
and Summers, 1979; Nichols et al., 1958; Reaves and Schafer, 1975; Reid, 1978;

Reid, 1983; Self et al., 1983; Stephens et al., 1981; Summers et al., 1986;

50

Wilkins and Rasmussen, 1993; Williams et al., 1979; Zwilling and Hummel,
1988), the proposed parameters (Table 3.1) are based on the ASAE data. Draft
is linear with respect to depth, quadratic with speed (ASAE, 1993a; Summers et
al., 1986) and adjusted for soil texture. Draft for medium and coarse textured
soils is estimated as 70% and 45%, respectively, of that for ﬁne textured soils.
Bowers (1989) reported that moldboard plow draft in the sandy loam soils of
North Carolina tended to be underestimated by the ASAE Standard. With the
proposed model, predicted draft for coarse textured soils is somewhat higher than
that reported by ASAE for sand and sandy loam soils.
3.1.5 Chisel Plows

The proposed parameters for chisel plow draft (Table 3.1) are based on a
comparison of reported values across soil textural groups (Bowers, 1989; Frisby
and Summers, 1979; Hendrick, 1980; Hunt, 1983; Reid, 1978; Reid, 1983; Self
et al., 1983; Stephens et al., 1981; Summers et al., 1986; Zwilling and Hummel,
1988; Grisso et al., 1994). Draft is generally found to be a linear function of
both depth and speed (Summers et al., 1986; Kydd et al., 1984; Gregory and
M’Hedhbi, 1988) but draft has also been reported to be a quadratic ﬁinction of
depth (Grisso et al., 1994). Draft factors A and B for medium textured soil are
based on data reported by Summers et al. (1986) for silt loam soil. Draft in
medium and coarse textured soils is estimated as 85% and 65%, respectively, of

the draft in ﬁne textured soil. Bowers (1989) reported that the ASAE Standard

51

data tended to over-estimate draft for chisel plows in the medium and coarse
textured soils of North Carolina. Chisel plow draft based on the proposed
parameters tends to be lower than that reported in the current ASAE Standard.
3.1.6. Sweep Plows

Sweep plows are used to loosen soil and undercut weeds while leaving the
soil surface undisturbed. The current ASAE Standard does not include draft data
for sweep plows, but sweep plows and similar tillage tools will likely come into
wider use as conservation tillage systems gain wider acceptance.

Summers et al. (1986) measured speed-draft relationships of sweep plows
in clay loam and silt loam soils in Oklahoma. Kydd et al. (1984) reported draft
data for sweep plows (blade cultivators) in both primary and secondary tillage
conditions. Draft was reported to be linear with respect to speed and depth
(Summers et al., 1986; Kydd et al., 1984). Comparisons of sweep plow draft
across soil textural groups were not found. The proposed sweep plow parameters
are based upon a composite of reported data (Summers et al., 1986; Kydd et al.,
1984). Similar to chisel plows, ﬁeld cultivators and other chisel-type tools, draft
in medium and coarse textured soils is estimated to be 85% and 65%,
respectively, of that in a ﬁne textured soil (Table 3.1). Based on sweep plow
draft data reported by Kydd et al. ( 1984), draft during secondary tillage is

estimated as 70% of that required for primary tillage.

52
3.1.7 Disk Harrows

Summers et al. (1986) reported greater draft for an offset compared to a
tandem disk, but direct comparisons were difﬁcult due to greatly different soil
conditions. Bowers (1989) reported tandem disk draft about 69% and 89%,
respectively, of that for an offset disk on ﬁne sandy loam and sandy loam soils.
A composite of values reported for silt loam soils (Bowers, 1989; Frisby and
Summers, 1979; Self et al., 1983) indicates tandem disk draft to be about 90%
of that for an offset disk. In the proposed parameters, draft of a tandem disk is
estimated to be 85% of that required for an offset disk at the same depth.

Disk draft is typically greater during primary than secondary tillage.
However, farmers generally perceive greater draft during secondary tillage due
to increased operating depth and reduced tractive efﬁciency in tilled soil. Draft
for a tandem disk during secondary tillage was about 38% of primary tillage in
a loamy ﬁne sand (Self et al., 1983), 73% in a loamy sand, 73% in a ﬁne sandy
loam, 76% in a sandy loam and 56% in a loam (Bowers, 1989). Offset disk
draft for secondary tillage was about 63% of primary tillage draft in a clay loam
(Reid, 1978), 58% in a sandy clay loam and 93% in a sandy loam (Reid et al.,
1983). In the proposed parameters, draft during secondary tillage is assumed to
be 70% of that required for primary tillage.

Since most newer tandem and offset disks can limit depth of tillage with

transport wheels, draft data based on depth of tillage are preferred to draft

53

estimates based on mass alone. The proposed data for primary tillage with a
tandem disk harrow in ﬁne textured soils are based on data presented by
Summers et al. (1986) and a comparison of reported draft across soil textural
groups (Bowers, 1989; Frisby and Summers, 1979; Kydd et al., 1984; Reid,
1978; Reid et al., 1983; Self et al., 1983; Stephens et al., 1981; Williams et al.,
1979; Zwilling and Hummel, 1988; Grisso et al., 1994). Draft (N/cmz) for
medium and coarse textured soils is estimated as 88% and 78%, respectively, of
draft for a ﬁne textured soil.

Since ASAE disk harrow draft data do not consider depth, a direct
comparison with the proposed data is difﬁcult. The proposed data predict a
narrower range of draft at a given depth than the current Standard. However, in
a medium textured soil the proposed data are similar to ASAE data (55 kg/blade)
for a silt loam soil at depths of 14 cm (5.5 in.) and 20 cm (8 in.), respectively,
for primary and secondary tillage with a tandem disk harrow at 8.9 km/h (5.5
mph). The proposed draft for an offset disk is similar to ASAE data (105
kg/blade) at a depth of 18 cm (7 in.) during primary tillage and 23 cm (9 in.)
during secondary tillage. V
3.1.8 Single Disk Gangs

Single disk gangs are frequently used on combination tillage tools for both
primary and secondary tillage. Draft data for single disk gangs are currently not

reported by ASAE. Hunt (1977) reported typical draft for a single disk gang as

54

about 50% of that for a light tandem disk. But the gang angle is typically less

for a single disk gang (8° to 12°) than a tandem disk harrow (18° to 22°) and

reducing the gang angle tends to reduce both depth of operation and draft
(Sommer et al., 1983). Based on draft-gang angle relationships described by

Sommer et al. (1983), reducing the gang angle from 20° to 10° will reduce draft
by 25 to 30%. In the proposed parameters, draft for a single disk gang at a 10°

gang angle is estimated as 40% of that for a tandem disk under similar conditions
(Table 3.1).
3.1.9 Disk Coulters

Coulter draft in the range of 45 to 50 N/cm of depth for a 46 cm (18 in.)
rippled coulter was reported by Choi and Erbach (1986) based on soil bin tests
in a silty-clay-loam and comstalk residue. In soil bin tests in a clay loam soil
and straw residue, Kushwaha et a1. (1986) measured draft in the range of 35 to
40 N/cm of depth for a smooth coulter, 46 cm (18 in.) in diameter. In general,
draft reported by Trouse and Reaves (1980) tended to be higher than that
reported by Choi and Erbach (1986) or Kushwaha et al. (1986), ranging from
about 60 N/cm for a smooth coulter in a sandy loam to 125 N/cm for a bubble
coulter in clay loam soil.

The proposed draft parameters for smooth and ripple coulters (Table 3.1)
were established from a composite of reported data (Choi and Erbach, 1986;
Kushwaha et al., 1986; Trouse and Reaves, 1980). Coulter draft is assumed to

be a linear function of both depth and speed with a 20% increase for ﬂuted and

55

bubble coulters. Similar to disk harrows, draft in medium and coarse textured
soils is 88% and 78%, respectively, of the draft in ﬁne textured soils.
3.1.10 Field Cultivators

The proposed parameters for ﬁeld cultivator draft (Table 3.1) are based on
a summary of reported draft data (Dumas and Renoll, 1982; Frisby and Summers,
1979; Stephens et al., 1981; Kydd et al., 1984; Zwilling and Hummel, 1988;
Grisso et al., 1994). Few data are available comparing draft across soil textural
groups so similar to chisel plows, draft for medium and coarse textured soils was
estimated as 85% and 65%, respectively, of the draft in a ﬁne textured soil.
Based on the draft data reported by Kydd et al. (1984), draft during secondary
tillage was estimated as 70% of that required for primary tillage. Field cultivator
draft (N/t/cm) based on the proposed parameters tends to be lower during
secondary tillage (30—50 N/t/cm) and higher during primary tillage (45-70 N/t/cm)
than that based on the current ASAE Standard data (45-55 N/t/cm).
3.1.11 Row Crop Cultivators

Row crop cultivator draft (N/m of width) is reported as linear with respect
to depth (ASAE, l993a). Hunt (1977) reported a range of values Similar to that
reported by ASAE. Frisby and Summers (1979) reported cultivator draft in clay,
loam and sand soils. Stephens et al. (1981) reported draft for row cultivators
with 3 to 5 sweeps or 5 S-tine shanks per row in a sandy-loam soil. No draft

data for conservation tillage cultivators were found.

56

The proposed parameters for S-tine and C-shank cultivators (Table 3.1) are
based on reported draft data (ASAE, l993a; Hunt, 1977; Frisby and Summers,
1979; Stephens et al., 1981). The data (N/cm/row) for no-till cultivators (Table
3.1) are estimated from proposed sweep plow data (assuming a 22 in., 56 cm
sweep) plus added draft for three coulters to approximate the draft of one cutting
coulter and two cut-away disks per row. Draft was assumed to be a linear
function of both speed and depth. Similar to a chisel plow, ﬁeld cultivator and
sweep plow draft, draft in medium and coarse textured soils is assumed as 85%
and 65%, respectively, of draft in a ﬁne textured soil. Based on the proposed
data, draft for the S-tine cultivator is at the low end and the C-shank cultivator
with sweeps at the high end of the range currently reported by ASAE.

3.1.12 Rotary Hoes

Rotary hoes were designed to dislodge small weeds and loosen crusted soil
early in the growing season (Springman et al., 1989). Rotary hoes work best at
relatively high speeds in tilled ﬁelds with light to moderate residue cover.
Rotary hoe draft is reported to be linear with respect to speed (ASAE, l993a).
A range of expected draft (N/m of width) was reported by Hunt (1977). Rotary
hoe draft reported by Stephens et al. (1981) was lower than that predicted by the
current ASAE data. Based on Stephens et al. (1981), the proposed data for

rotary hoe draft are 500 N/m, independent of travel speed. A single value with

57

an expected range or variation is consistent with data reported for other minor
tillage tools (Table 3.1).
3.1.13 Rod Weeders

Rod weeders use a rotating round or square rod running below the soil
surface to undercut weeds and leave them lying on the soil surface. A range of
expected draft was reported by ASAE (ASAE, 1993a) and a similar range was
reported by Hunt (1977). Kydd et al. (1984) reported draft data for rod weeders
under typical Canadian prairie conditions and indicated draft to be linear with
respect to speed. The proposed parameters for rod weeder draft in medium
textured soil are based on Kydd et a1. (1984). Draft is adjusted for soil texture
similar to other cultivation tools with medium and coarse textured soils causing
85% and 65%, respectively, of the draft in ﬁne textured soils (Table 3.1).
3.1.14 Minor Tillage Tools

ASAE spike harrow data (440-730 N/m) are similar to that reported by
PAMI (PAMI, 1986); therefore a single value (590 N/m) with an expected range
of variation is provided. A similar modiﬁcation was made for roller-packer (660
N/m), land plane (8,000 N/m) and spring tooth harrow (1,800 N/m) data. The
proposed roller-harrow parameter (2,700 N/m) is a composite of the current
ASAE roller packer data and the proposed ﬁeld cultivator parameters. Proposed

coil-tine harrow data (250 N/m) were derived from harrow-packer draft data

58
(PAMI, 1988). Disk-bedder draft (N/r/cm) are based on Reid (1978) and

adjusted for soil texture similar to disk harrows.
3.1.15 Row Crop Planters

Row crop planter draft (N/row) is published in the current ASAE standard
(ASAE, 1993a). The Standard data assumes a prepared seedbed in a loam soil
and includes rolling resistance. Based on data reported by Frisby and Summers
(1979), there appears to be little difference in draft across soil textural groups
when planting in a ﬁrm, prepared seedbed. Bowers (1989) reported draft for
seeding units only in a loamy sand to be similar to that reported by Stephens et
al.(1981) in a silt loam soil. When planting with seed, fertilizer and herbicide
application, planter draft tends to be higher and more variable. Measured drafts
ranging from about 1,200 to 1,800 N/row are common with no consistent trends
across soil textural groups (Bowers, 1989; Matthews et al., 1981; Reid et al.,
1983; Stephens et al., 1981) even though a lower draft (500 to 1,000 N/row) is
reported for some soils (Bowers, 1989).

Rolling resistance of transport and press wheels is a large portion of row
planter draft. Row planter draft only increased about 10% when planting at 7.5
cm (3 in.) compared to 2.5 cm (1 in.) in a prepared seedbed of silt loam soil
(Stephens et al., 1981) indicating little contribution to draft from the seeding

units. Bowers (1989) indicated 15 to 20% lower draft in an untilled ﬁne sandy

59

loam soil compared to the same planter in a prepared seedbed, possibly due to
lower rolling resistance on ﬁrm soil.

Since planter draft in a prepared seedbed does not appear to be greatly
affected by soil texture or planting depth, row planter draft is estimated as 500
N/row for a mounted planter with seed units only (Table 3.1), 900 N/row for a
drawn planter running only seeding units and 1,550 N/row when running seed,
fertilizer and herbicide units in a prepared seedbed. Motion resistance was
assumed to be less with no-till planters. No-till planter draft was estimated as
1,325 N/row with seed, fertilizer, herbicide units plus the estimated draft of one
ﬂuted coulter (320 to 470 N/row). Draft for zone-till planters was estimated as
row unit draft (1,325 N/row) plus the draft of three ﬂuted coulters per row (1,440
to 2,100 N/row).

The proposed row planter draft parameter (N/row) for a mounted planter
with seed units only is at the lower end of the range listed in the current ASAE
data (Table 3.1). Draft for a drawn planter with seed units only is somewhat
higher than the upper end of the range listed by ASAE. The proposed data for
row planters applying seed, fertilizer and herbicide are in the mid-range of that
listed by ASAE.

3.1.16 Grain Drills
Since grain drill draft is not greatly affected by soil texture or seeding

depth, but is greatly affected by rolling resistance, a range of draft (N/row)

60

values based on drill width is proposed. Based on a synopses of reported data
(Frisby and Summers, 1979; Mungai, 1991; Stephens et al., 1981; Kydd et al.,
1984) draft data for a conventional disk drill in a tilled, ﬁrm seedbed range from
200 N/row for a wide drill (>3.66 m, 12 ft) to 400 N/row for a narrow (<2.44 m,
8 ft) drill. Since rolling resistance is not as dominant in ﬁrm, no-till conditions,
draft for no-till drills was estimated as 250 N/row plus the coulter draft (320-470
N/row). The proposed drill draft parameters are within the range currently
reported by ASAE.
3.1.17 Hoe and Pneumatic Drills

Proposed draft parameters for hoe drills (2,200 to 3,400 N/m of width) and
pneumatic drills (2,600 to 4,350 N/m) are based on Kydd et al. (1984). These
values are adjusted for soil texture similar to other chisel-type tools. The
proposed hoe drill data are in general agreement with the deep furrow grain drill
data currently listed by ASAE (1993a).
3.2 INTEGRATION OF TILLAGE DRAFT DATA WITH DAFOSYM

The proposed draft and power data were integrated with DAFOSYM to
predict draft, power and fuel consumption for a range of tillage and planting
implements as a function of soil texture, tillage depth and speed of operation.
Total power required to operate implements was greater than that required to
overcome draft. Rotary power, power to overcome rolling resistance and draft

power components were calculated separately. Rotary power for implements

61

Table 3.2. Tillage, planting and seeding implement draft and machine
operation parameters used in DAFOSYM.

 

 

Speed Depth Field S1 Parameters, S1

Implement km/h cm efﬁciency units A B C
Moldboard Plow 7.2 20 .75 n/cm2 4.20 --- 0.037
Coulter-Chisel Plow

7.5 cm twisted shovel 8.9 20 .85 Mom” 2.90 0.17 ---
Tandem Disk Harrow

secondary tillage 8.9 10 .85 n/cm2 1.90 0.10 «-
Field Cultivator

w/coil tine harrow 9.7 7.5 .85 n/cm2 2.32 0.11 «-
Seedbed Conditioner

secondary tillage 9.7 7.5 .85 n/cm2 2.57 0.14 «-
Manure Injectorl 7.2 12 .90 --- --- --- ---
Rotary Hoe 14.5 --- .85 n/m 500 --- ---
Aerator 9.7 --- .85 n/m 4,500 --- ---
Corn Planter

conventional 8.8 --- .65 Mn 1 ,500 --- ---

conservation 8.8 --- .65 n/m 1,500 --- ---

zone-till 8.8 --- .65 n/m 3,700 —-- ---
Grain Drill

conventional 8 8 --- .70 n/m 1,100 --- ---

no-till 8 8 --- .70 n/m 2,900 --- ---

 

with signiﬁcant rotary power requirements such as manure Spreaders was based
on published data (Saﬂey and Nye, 1982) and determined by standard procedures
(Rotz and Muhtar, 1992). For manure Spreaders, row crop planters and seed
drills that required considerable power to overcome rolling resistance, implement
mass and typical values for soil cone index were used to calculate rolling
resistance (ASAE, l993a). Draft to overcome rolling resistance was included in
the draft parameters (Table 3.1) for tillage, planting and seeding implements.

Total draft for slurry injector tankers was obtained by ﬁrst calculating rolling

 

' 11.9 kW (16 hp) per injector shank was added to draft needed to overcome tanker rolling
resistance.

62
resistance and then adding 11.9 kW (16 hp) per injector as indicated by the draft

data in Table 3.1.

Major tillage tool draft data were converted to common units (n/cmz) based
on implement conﬁguration for use in DAFOSYM. Minor tillage tool, planting
and seeding implement draft were determined per unit width (n/m). The
standardized draft parameters used in DAFOSYM are listed in Table 3.2. Total
power required for the operation of implements is the sum of implement power
components converted to equivalent pto power (ASAE, l993b). Total engine
power required was set greater than total implement power required. Variations
in soil and moisture conditions, topography and safety requirements make it
necessary to hold some power in reserve to overcome ﬂuctuating load conditions.
Twenty percent of the maximum potential power available at the drawbar was
held in reserve. Field speeds were limited by machine draft where power
requirements were greater than available with the speciﬁed power unit. Fuel
consumption was modeled using standard procedures (ASAE, 1993a). Fuel use
was a function of the ratio of the equivalent pto power required by an operation
to the maximum available from the pto.

3.3 DEVELOPMENT OF THE SUITABLE DAY MODEL

A common approach for manure land application is to spread stored

manure in the spring prior to planting and in the fall after com harvest. Since

timeliness penalties for corn planting begin to accumulate in early May and soil

63

conditions for tillage and spreading deteriorate rapidly in the fall, an accurate
estimate of suitable days is important for livestock producers. Suitable working
days are the days available in a scheduled period during which ﬁeld operations
can be performed (Von Bargen et al., 1986). A good estimate of the number of
days suitable for ﬁeld operations helps farm managers select the machinery
capable of completing ﬁeld operations within the time available. The number of
suitable days in a time period is inﬂuenced by climatic region, soil slope and
texture, drainage, operation performed and the use of traction and ﬂotation
devices (ASAE, 1993a).
3.3.1 Soil Moisture Budget

A soil moisture budget was developed based on the method of Kiniry and
Jones (1986) and was used to predict suitable days for ﬁeld work. Similar to
models developed by other researchers (Rutledge and McHardy, 1968; Selerio
and Brown, 1972; Baier, 1973; Tulu et al., 1974; Elliott et al., 1977; Dyer and
Baier, 1979; Acharya et al., 1983; von Bargen et al., 1986), soil moisture was
calculated for multiple soil layers. Daily temperature, precipitation and solar
radiation together with soil characteristics inﬂuenced water inﬁltration, drainage
and evaporation. Submodels were added to estimate the date of soil thaw in the
spring and the effect of crop residue cover on the rate of soil moisture

evaporation.

64

Soil moisture was tracked in four soil layers: surface to 3 cm (surface to
1.2 in), 3 to 7.6 cm (1.2 to 3 in), 7.6 to 15.2 cm (3 to 6 in) and 15.2 to 100 cm
(6 to 39.4 in). Soil moisture in the upper three layers determined suitable days
for ﬁeld work. Since suitable day determinations were not needed from the time
corn was planted until corn silage harvest began in the fall, soil moisture
extraction from crop grth was not modeled. However, a full season soil
moisture balance was maintained by assuming 0.3 cm/d (0.12 in; Shayya and
Bralts, 1994) soil moisture was removed by plant grth from June 1 through
September 30.

Freezing and thawing of soil are not considered in the soil moisture
balance of Kiniry and Jones. Since manure spreading and tillage begin in the
spring as soon as soil is trafﬁcable, an estimate of the date of soil thaw based on
annual climatic data is needed. A simple model was developed to predict spring
soil thaw and initial soil moisture. Soil was considered thawed and at ﬁeld
capacity after the accumulation of fourteen degree days (celsius; Tulu, 1973).
A degree day was calculated as the average of the daily maximum and minimum

temperatures. If the maximum daily temperature was greater than 7° C (45° F),

degree days were accumulated (Selerio and Brown, 1972). If the maximum daily

temperature was less than 7° C but greater than 0° C, degree days were
accumulated at a reduced rate. If the average daily temperature was less than 0°
C (32° F) the soil was assumed to re-freeze and the total accumulation reset to

zero but soil was always assumed thawed by April 20.

65

Water is removed from the soil through inﬁltration. plant use and
evaporation. Early in the spring and late in the fall when a crop is not growing,
evaporation is required to draw soil moisture to a level below ﬁeld capacity.
Evaporation is largely inﬂuenced by solar radiation, temperature, wind and the
interaction of temperature and wind (Brun et al., 1986). Residue cover delays
the rate of evaporation. A simple model was developed to describe the effect of
crop residue on the rate of moisture evaporation. The rate of Stage 1 evaporation
was reduced as a positive linear function of residue cover ranging from no effect
at 0% cover to a 50% reduction at 100% residue cover. This rate reduction is
a composite of both ﬁeld and soil core measurements (Bond and Willis, 1969;
1970; Smika, 1983; Brun et al., 1986; Aase and Tanaka, 1987). '

3.3.2 Soil Moisture Criteria for a Suitable Day

The main factor determining a suitable day was the trafﬁcability of the soil
surface. Trafﬁcable soil could be worked without serious structural damage or
excessive compaction (Flores et al., 1990). Soil moisture criteria were compared
to the soil moisture level to determine suitable days. A day was determined
suitable for ﬁeld operations if the soil moisture was within acceptable limits.
Soil is not generally considered suitable for tillage until the soil to the depth of
tillage is below ﬁeld capacity (Rutledge and McHardy, 1968; Selerio and Brown,
1972; Baier, 1973; Tulu et al., 1974; Elliott et al., 1977; Dyer and Baier, 1979;

Acharya et al., 1983; von Bargen et al., 1986), but higher moisture levels are

66

are considered suitable for some non-tillage operations. Soil moisture at ﬁeld
capacity near the surface was considered suitable for harvest operations (Tulu et
al., 1974; Rosenberg et al., 1982) and moisture above ﬁeld capacity was
considered suitable for land application of manure (Witney et al., 1982;
McGechan and Cooper, 1994). In the current model, a day was considered
suitable if:

SM,SC,fori= 1,2,3
where:

SMi = available moisture of the ith soil layer as a fraction of ﬁeld

capacity.

C = upper limit of moisture allowable as a fraction of ﬁeld capacity.

i = 1, 2, 3 refers to the 0-5 cm, 5-10 cm and 10-15 cm soil layers,

respectively.

The upper soil moisture limit as a fraction of ﬁeld capacity (C values) used
to deﬁne suitable days are listed in Table 3.3. The C values were speciﬁc to soil
texture and ﬁeld operation. Since coarse textured (sandy) soils tend to be less
susceptible to soil compaction than ﬁne textured soils (loams and clay loams),
greater moisture was allowed in the coarser textured soils.

Higher soil moisture was allowed when there where opportunities to
alleviate soil compaction prior to spring planting. Remedial activities included:

1) fall tillage under drier soil conditions, 2) freezing and thawing and 3) spring

67

Table 3.3 Allowable fraction of ﬁeld capacity (Ci’s) for various soil layers
and ﬁeld Operations.

 

 

Soil Layer, i Clay Loam Loam Sandy Loam
Operation

Spring Tillage, Planting

and Manure Injection 1 0.95 0.97 0.99
2 0.95 0.97 0.99
3 0.97 0.985 1.00

Spring Manure Spreading, Fall

Tillage and Manure Injection 1 0.98 0.99 1.00
2 0.98 0.99 1.00
3 0.99 1.00 1.01

Corn Harvest and Fall Manure

Spreading 1 1.02 l .04 1.06
2 1.02 1.04 1.06
3 1.00 1.02 1.04

 

seedbed tillage. Spring tillage and planting are the ﬁnal operations prior to crop
establishment. If the soil is worked when too wet, soil compaction and cloddy
seedbeds may result with no suitable opportunities for remedial action.
Therefore, the driest soil was required for spring tillage, spring manure injection
and planting (Table 3.3). Higher moisture was allowed for fall tillage, fall
manure injection and spring surface spreading of manure since soil compaction
could be alleviated by either spring tillage or winter freeze-thaw cycles. The
greatest soil moisture was allowed in the fall for corn harvest and manure
spreading. This higher allowable moisture recognizes the ability of crop residue
and root mass to aid trafﬁcability and the opportunity for fall tillage, freezing and
thawing and spring tillage to alleviate soil compaction and create a suitable

seedbed prior to planting.

68
3.3.3 Veriﬁcation of the Suitable Day Model

A comparison of suitable days on a well-drained clay loam soil in
Michigan and southern Ontario is listed in Table 3.4. The number of available
days predicted by the suitable day model for spring operations was somewhat
less than reported by Rosenberg et a1. (1982) but greater than that reported by
ASAE (1993a) and similar to that reported by McCorquodale et al., (1988).
Similarly, the suitable day model predicted somewhat less time available for fall
operations than reported by Rosenberg et al. (1982) or McCorquodale et a1.
(1988) but more days than reported by ASAE (1993a). Since predicted days are
inﬂuenced by assumptions regarding inﬁltration rate, organic matter, sand, silt
and clay content and other soil parameters, some deviation from other published
data is expected.

Soil texture inﬂuenced suitable days. More time was available on a coarse
textured sandy loam than on a ﬁne textured clay loam. Fine textured soils have
greater water holding capacity and tend to drain more slowly than coarse textured
soils so more time is needed for inﬁltration and evaporation to create soil
conditions suitable for ﬁeld work. The greatest difference was late in the fall
when cool temperatures and reduced solar radiation reduced evaporation. In the
spring there were two to three more days available for tillage on a sandy loam
than a clay loam soil. There were four to eight more days available for tillage

from October through December on the coarse textured soil. These differences

69

Table 3.4 Comparison by data source: expected proportion of days suitable
for tillage per time period on a well drained, clay loam soil.

 

 

 

Central Central Southeast Southern
Michigan Michigan' Michigan2 Ontario3
(proposed)
Probability, % 80 80 50 90 67 75
April 11-20 .25 -- -- -- -- --
April 21-30 .29 .34 .20 -- .36 .23
May 1-10 .51 .66 -- -- .61 .49
May 11-20 .37 .62 -- -- .51 .37
May 21-31 .60 .71 .61 .32 -- --
June 1-15 -- .66 -- -- .60 .50
June 16-30 -- .72 .69 .42 .53 .41
July 1-15 -- .80 -- -- -- --
July 16-31 -- .79 .75 .52 -- --
August 1-15 -- .65 .74 .53 -- ~-
August 16-31 -- .71 -- -- -- --
September 1-15 .65 .75 .70 .35 -- --
September 16-30 .45 .68 -- -- .80 .70
October 1-15 .50 .64 .59 .26 .74 .64
October 16-31 .48 .58 -- -- .70 .60
November HS .26 .42 .42 .06 .59 .48
November 16-30 .05 .11 .07 .00 .48 .43

 

are similar to those reported by other researchers for Michigan and nearby states
(Tulu et al., 1974; Parsons and Doster, 1980; Rosenberg et al., 1982; ASAE,
l993b).

Crop residue reduced the number of suitable days for ﬁeld work (Table
3.5). The greatest effect was early in the spring and late in the fall when
temperatures and solar radiation were relatively low. On a clay loam soil, eighty
percent residue cover reduced suitable days for tillage in April and May by about

three. This difference is similar to that reported by Elliott et al. (1977). The

 

' Rosenberg et al., 1982.
2 ASAE, 199321.
3 McCorquodale et al., 1988.

70

Table 3.5 Predicted suitable days (80% probability) for tillage, planting,
manure spreading and harvest in central Michigan with three 'soils
and three levels of crop residue.

April May June July Aug Sept Oct Nov Dec

CONVENTIONAL TILLAGE '
Till, Plant, Inject

 

Clay loam 7.8 18.0 18.4 22.3 19.3 17.7 16.4 5.8 0.0
Loam 9.0 19.3 19.2 23.5 21.0 19.2 18.0 7.0 0.0
Sandy loam 9.7 21.1 19.8 23.8 21.8 20.3 19.9 12.4 8.3
Harvest, Spreading

Clay loam 9.0 19.9 20.1 25.8 23.2 21.3 21.2 12.0 6.6
Loam 9.9 21.1 21.2 26.2 23.8 21.7 21.8 14.4 11.1
Sandy loam 11.0 21.8 20.9 24.9 22.8 20.8 21.7 15.4 13.4

MULCH TILLAGE 2
Till, Plant, Inject

Clay loam 5.7 16.5 17.0 20.5 18.1 16.4 14.7 4.5 0.0
Loam 7.8 18.5 18.2 22.6 19.6 18.6 16.4 5.5 0.0
Sandy loam 8.6 20.3 18.9 23.5 20.9 19.4 18.9 11.0 7.0
Harvest, Spreading

Clay loam 7.9 18.5 18.4 24.6 22.3 20.0 19.8 9.9 5.2
Loam 8.6 20.5 19.8 25.4 22.8 21.0 21.3 13.1 9.9
Sandy loam 10.1 21.1 20.2 24.3 22.1 20.4 20.8 14.0 12.8
NO-TILL ’

Till, Plant

Clay loam 4.6 15.2 15.4 19.5 16.9 15.0 12.6 2.7 0.0
Loam 7.0 16.8 16.5 21.0 18.9 17.2 14.1 3.8 0.0
Sandy loam 8.0 19.0 17.8 22.2 20.2 18.7 18.0 9.9 6.0
Harvest, Spreading

Clay loam 5.5 16.9 17.4 23.2 21.3 19.3 17.9 8.8 3.7
Loam 7.9 18.7 18.4 23.9 22.1 19.9 19.8 1 1.0 8.6
Sandy loam 9.4 19.9 19.1 23.2 21.0 19.5 19.7 12.9 12.0

 

reduction in suitable days was not as great on the coarse textured sandy loam due
to the lower moisture holding capacity of that soil. Eighty percent cover reduced

available time by about two days in April and May. Since harvest, tillage and

 

' 10% residue cover in the fall, 0% cover in the spring.

2 50% residue cover in the fall, 40% cover in the spring.
3 90% residue cover in the fall, 80% cover in the spring.

71

manure spreading occured on untilled corn residue, no reduction in suitable days

from residue cover was predicted between tillage systems for fall operations.

4. PROCEDURE

Many of the questions that farmers have at the systems engineering level
relate to the capacity, cost, labor requirements and compatibility of alternative
tillage and manure handling subsystems. One of the objectives in the
development of the suitable day, tillage and manure handling submodels of
DAFOSYM was to create a ﬂexible model that could be used to describe,
evaluate and compare a wide range of tillage, planting, manure storage, transport
and application methods. Tillage and planting systems compared include
conventional, mulch-till and modiﬁed no-till. Land application methods included
liquid irrigation, surface spreading or injection with slurry tankers and daily
hauling with a V-tank spreader. Other parameters that could be varied included
land area, crop rotation, number of animals, feeding strategy, length of workday
and number of simultaneous ﬁeld operations. This range of options provides a
ﬂexible model that can generate data suitable for a speciﬁc farm or can be used
in a more generalized way to evaluate and compare alternative farming systems.

To illustrate the ability of the model to describe, evaluate and compare a
wide range of tillage and manure handling options, four manure handling and
three tillage systems were modeled and compared on ﬁve synthesized,
representative dairy farms. The farms included dairies milking 60, 150, 250, 400
and 800 cows. The analysis was performed over 26 years of East Lansing,

Michigan weather conditions to obtain a long-term evaluation of systems.

72

73
4.1 HERD, CROP AND PRICE INFORMATION

The dairy herds included Holstein cows and replacement stock. Cows in
their ﬁrst lactation formed 35% and dry cows 15% of the milking herd. The
number of young stock on each farm was selected to provide all replacements
(Table 4.1). Potential annual milk production was set at 10,000 kg/cow (22,000
lb/cow). This yield level could only be attained with the addition of fat to the
diet and fat was not fed so forage quality was the primary constraint to milk
production. Higher forage quality increased milk production. Corn and alfalfa
were the two crops grown on all farms with approximately half of the farm land
area in each. No crop land was set aside for the purpose of manure disposal
during the growing season. The soil was a medium loam with a total water
holding capacity of 200 mm (7.9 in). Crop areas and predicted average post-
harvest yields for each representation are listed in Table 4.1.

Herbicide costs for ﬁrst year alfalfa following corn and ﬁrst year corn
following alfalfa were increased to allow a bum-down treatment for grass
control. Seeding rates were increased by 5% with the no-till system for both
corn and alfalfa to compensate for decreased emergence or insect damage.
Annual costs for seed, chemicals and fertilizer are listed in Table 4.2.

Alfalfa and corn silage harvest procedures were similar for all farms. A
four cutting system was used for alfalfa and harvests were begun at a bud stage

of development for ﬁrst and second cuttings and an early ﬂower stage for third

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Table 4.2 Economic parameters and prices assumed for various system inputs
and outputs in the representative farm analysis.

 

 

Parameter Value

Labor wage rate $9.35/h

Diesel fuel price $0.28/liter ($1.06/gallon)
Electricity price $0.08/kW-h

Corn drying cost
Corn grain elevation and storage cost
Land rental rate
Milk price
Fertilizer prices
-Nitrogen
-Phosphorous
-Potassium
Annual cost of seed and chemicals:
conventional and mulch tillage
-Estab1ishment year alfalfa
-Estab1ished alfalfa
-Com following alfalfa
-Corn following corn
modified no-till
-Establishment year alfalfa
-Established alfalfa
-Com following alfalfa
-Com following corn
Selling price of feeds
-Corn grain
-High-moisture corn
-Alfalfa hay
-Corn silage
Buying price of feeds and bedding
-Soybean meal
-Corn grain
-A|falfa hay
-Chopped straw bedding
Custom operation rates

-Corn grain harvest, transport and unload

Economic life
-Storage structures
-Machinery

Salvage value
-Storage structures
-Machinery

Real interest rate

81 .1 8/pt./t ($1.07/pt./ton)
$9.40/t DM ($8.54/ton DM)
$125/ha ($50/acre)
$0.28/1iter ($12.5/cwt)

$0.31/kg ($0.14/1b)
$0.42/kg ($0.19/1b)
$0.24/kg ($0.11/1b)

$203/ha ($82/acre)
315/ha ($6/acre)

$116/ha ($47/acre)
$156/ha ($63/acre)

$235/ha ($95/acre)
SIS/ha ($6/acre)

$133/ha ($54/acre)
$156/ha ($63/acre)

$113/t ($103/ton) DM
SlOZ/t ($93/ton) DM
$90/t ($82/ton) DM
$66/t ($60/ton) DM

$260/t ($236/ton) DM
$118/t ($107/ton) DM
$100/t ($91/ton) DM
$60/t (SSS/ton)

$65/ha ($26/acre)

20 yr
10 yr

0%
l 0%
6%/yr

 

76

and fourth. Harvest dates for the ﬁrst three cuttings were within ﬁve days of
May 30, July 6, and August 23. Weather permitting, fourth cutting was begun
on October 15. Alfalfa harvest days were not available for tillage or manure
spreading. First, third and fourth cuttings of alfalfa were harvested as silage with
only second cutting baled as hay. Chopping was begun when the crop had dried
to 65% moisture. Hay was harvested at less than 20% moisture in round bales
and stored in a shed.

Weather permitting, corn silage harvest was begun on September 12 with
silage preserved at 65 to 70% moisture (dough to glaze stage of maturity). High-
moisture corn harvest was begun on October 1 and stored at 25 to 30% moisture.
Harvest of dried shelled corn was begun October 10 with grain dried to 151/5%
moisture. Corn grain harvest was custom hired and did not interfere with tillage
or manure spreading. Alfalfa silage, corn silage and high-moisture shelled corn
were stored in bunker or concrete-stave silos (Tables 4.3, 4.4 and 4.5). Other
corn grain was dried, elevated and stored off the farms. Silage and concentrates
were fed as a total mixed ration (TMR) using a mobile feed mixer and a skid-
steer loader. Hay was fed ﬁ'om a self-feeding rack. Feeds not used during the
year following harvest were sold as excess feed.

Tillage and manure spreading on the land harvested as corn silage was

begun upon completion of corn silage harvest. Manure spreading and tillage of

77

 

 

 

 

Table 4.3 Major machines and structures used for crop harvest and storage on
the representative 60 and 150-cow farms.

Machine or 67 ha (165 acreL 60-Cow Farm 145 ha (358 agre) ISO-Cow Fm
storage type Size No. Price($) Size No. Price($)
FEED HARVEST AND STORAGE

Mower-conditioner 2.7 m (9 1t) 1 10,800 3.7 m (12 ft) 1 15,200
Tandem rake 5.4 m (18 ft) 1 8,500 5.4 m (18 ft) 1 8,500
Round baler small (4X4) 1 10,000 medium (5X4) 1 15,200
Bale loader/grabber large 1 6,300 large 1 6,300
Round bale wagon 3.3 t (3.6 ton) 1 4,000 4.9 t (5.4 ton) 1 4,000
Forage harvester 12 t (13.2 ton) DM/h 1 20,100 12 t ( 13.2 ton) DM/h 1 20,100
Forage blower 10 t (11 ton) DM/h 1 3,800 10 t (11 ton) DM/h 1 3,800
Forage wagons 6 t (6.6 ton) 2 8,650 6 t (6.6 ton) 2 8,650
Feed mixer 4.5 t (5 ton) DM/h 1 12,600 12 t (13.2 ton) DM/h 1 22,500
Hay storage shed 99 t (110 ton) DM 1 11,800 200 t (220 ton) DM 1 20,125
Alfalfa bunker --- - -- 490 t (540 ton) DM 1 24,950
Alfalfa silo 180 t (198 ton) DM 1 23,000 -- - «-
Corn silage bunker -- - -- 490 t (540 ton) DM 1 24,950
Corn silage silo 159 t (144 ton) DM 1 19,350 -- - --
High-moist. corn silo m - ..- 262 t(289 ton) DM 1 14,800

 

 

 

 

 

Table 4.4 Major machines and structures used for crop harvest and storage on
the 250 and 400-cow representative farms.

Machine or 250 ha @16 acre) 250-Cow Fa_rm 400 ha (988)3cre) 400 Cow 11am
2 storage type Size No. Price($) Size No. Price($)
FEED HARVEST AND STORAGE

Mower-conditioner self-prop. 4.3 m (14 ft) 1 34,200 3.7 m (12 ft) 2 34,200
Tandem rake 5.4 m (18 ft) 1 8,500 5.4 m (18 ft) 2 8,500
Round baler large (6X4) 1 17,700 large (6X4) 2 17,700
Bale loader/grabber large 1 6,300 large 2 6,300
Round bale wagon 4.9 t (5.4 ton) 1 4,000 4.9 t (5.4 ton) 2 4,000
Forage harvester 18 t (19.8 ton) DM/h 2 30,450 18 t (19.8 ton) DM/h 2 30,450
Forage blower 10 t (11 ton) DM/h 1 3,800 10 t (11 ton) DM/h 1 3,800
Forage wagons 6 t (6.6 ton) 4 8,650 6 t (6.6 ton) 4 8,650
Feed mixer 12 t (13.2 ton) DM/h 1 22,500 12 t (13.2 ton) DM/h 2 22,500
Hay storage shed 334 t (367 ton) DM 1 31,900 500 t (550 ton) DM 1 95,000
Alfalfa bunker 385 t (424 ton) DM 2 21,275 1150 t (1265 ton) DM 1 48,050
Corn silage bunker 645 t (711 ton) DM 1 30,375 1150 t (1265 ton) DM 1 48,050
High-moist. corn silo 323 t (356 ton) DM 1 19,350 403 t (444 ton) DM 1 34,050

 

78

Table 4.5 Major machines and structures for crop harvest and storage on the
representative 800-cow farm.

 

Machine or 800 h_a (1.975 acre) 800-Cow Farm
storage type Size No. Price($)

 

FEED HARVEST AND STORAGE

Mower-conditioner self-prop. 4.3 m (14 ft) 3 34,200
Tandem rake 5.4 m (18 ft) 3 8,500
Round baler large (6X4) 3 17,700
Bale loader/grabber large 3 6,300
Round bale wagon 4.9 t (5.4 ton) 3 4,000
Forage harvester 18 t (20 ton) DM/h 3 30,450
Forage blower 10 t (11 ton) DM/h 1 3,800
Forage wagons 6 t (6.6 ton) 6 8,650
Feed mixer 12 t (13.2 ton) DM/h 3 22,500
Hay storage shed 1100 t (1211 ton) DM 1 95,000
Alfalfa bunker 1435 t (1579 ton) DM 1 48,050

1150 t (1265 ton) DM 1 48,050
Corn silage bunker 1150 t (1265 ton) DM 2 48,050
High-moist. corn silo 692 t (763 ton) DM 1 34,050

 

land harvested for high-moisture or dried corn began as land became available
following harvest.

Feed rations for each of six animal groups (three lactation groups, dry
cows, older heifers and younger heifers) were determined by a linear program
embedded in DAFOSYM. The linear program maximizes forage intake while
minimizing the cost of purchased feeds to establish rations (Rotz et al., 1989).
The total digestible nutrient (TDN) contents of farm-grown alfalfa and corn were
predicted by the growth, harvest and storage submodels of DAFOSYM. Average
values were assumed for purchased feeds.

The manure production and utilization model used in DAFOSYM has been
described by Borton et. a1 (1995). Manure production was modeled as feed dry

matter (DM) consumed minus the digestible DM used by the animals plus urine

79

DM. Manure DM was increased by 3% of the feed DM intake to account for
feed losses and further increased to account for the bedding dry matter used. To
determine the quantity of manure handled, moisture contents of 87%, 91% and
94% were assumed for semi-solid, slurry and liquid irrigation systems,
respectively.

The manure nutrient value was determined through a mass balance of all
the animal groups with manure nutrients equal to the nutrient intake minus
nutrients contained in milk and body growth. Nitrogen intake was determined
from the crude protein content of the feed consumed. Typical values of
phosphorus (P) and potassium (K) in feeds as published by the National Research
Council (1988) were used together with nutrients in feed supplements to predict
P and K in manure (Borton et al., 1995).

Prices were set to reﬂect the long-term relative values for the various farm
inputs and outputs in 1994 dollars. Prices for milk, excess feed and various farm
inputs are listed in Table 4.2 and those for machinery and storage structures are
listed in Tables 4.3, 4.4 and 4.5. Machinery repair and maintenance costs were
determined as a ﬁinction of price and accumulated use (ASAE, 1993a). Diesel
fuel was priced at $0.28/liter ($1.06/gal) and the labor wage rate was $9.35/h.
A real interest rate (approximately nominal rate minus inﬂation) of 6% annually
was used for investments. Machines and structures were depreciated over 10 and

20 years to salvage values of 10% and 0% of their initial value, respectively.

80

DAFOSYM follows a partial budget format and accounts for all costs
associated with manure storage and land application, tillage, planting, growing,
harvesting and storing of feed and feeding the milking herd and young stock. A
net return over tillage, feed and manure costs is calculated as the difference
between the income from milk sales and the net cost of producing the feed,
feeding the animals and handling the manure. Additional costs for operations not
modeled in DAFOSYM including animal housing, milking center, livestock
expenses, utilities and herd health were estimated (Table 4.6) from Nott and
Carter (1993), Bickert (1994) and Bickert and Stowell (1994) to determine a net
return (Table 5.8).

4.2 NUTRIENT AVAILABILITY AND LOSS

Nitrogen losses during collection, storage and application were modeled
in DAFOSYM by Borton et al. (1995). Volatile N was assumed to be 35% of
the total N after collection and loss of volatile N during storage was a function
of loading method, rate of loading, wind speed and ambient temperature. Loss
of volatile N from manure applied to crop land was a function of time between
spreading and incorporation. All volatile N applied to alfalfa land was assumed
lost. Of the organic N entering the soil, 30% was considered available to the
crop during the ﬁrst year with one-half of the remaining amount becoming
available in each succeeding year. Losses of P and K were assumed to be 5%

of that contained in fresh manure.

81

Table 4.6 Major dairy costs ($lcow-yr)l above the net return over feed, manure
and tillage costs calculated by DAFOSYM.

 

60-cow ISO-cow 250-cow 400-cow 800-cow

 

Animal housing2 123 123 123 123 123
Milking centelJ 271 108 98 81 81
Misc. eqp’t. & structures4 55 26 23 21 16
Livestock expenses’ 455 474 500 500 500
Utilities° 74 61 61 61 61
Herd labor’ 468 464 449 411 365
TOTAL 1,446 1,260 1,254 1,197 1,146

 

The nutrient value of the manure produced by a 636 kg (1,400 lb) dairy
cow is about $82/yr (Jacobs, 1991). System losses and inefﬁcient use of the
nitrogen contained in manure spread on alfalfa land reduced the value of the
manure on the representative farms. About forty-ﬁve percent of the manure
produced was spread on alfalfa land. Although nutrient carry-over provided

some value for corn production, most of this nitrogen was lost.

 

‘ Cash ﬂow basis, before tax costs. Animal housing depreciated over 20 years and milking center
over 12 years to 0% salvage value. Six percent real interest rate (nominal minus inﬂation). Annual
taxes, insurance and repair and maintenance estimated as 2.25% of purchase price. Labor @ $9.35/h.

2 Source: Bickert, 1994. Free stall and dry cow housing purchase price @ $800/cow, animal care
facility @ $50/cow, replacement housing @ $350/cow and commodity shed @ $70/cow.

3 Source: Bickert, 1994. Includes holding pen, crowd gate, parlor, milking equipment and bulk
tanks @ $15,000 per milking unit. Double four (D-4) herringbone parlors were used on the 60 and 150-
cow farms and D6, D-8 and D-16 parlors were used on the 250, 400 and 800-cow farms, respectively.

4 Includes water wells, back-up electrical, computers and software.

5 Source: Nott and Carter, 1994. Includes breeding and herd health, trucking, livestock supplies,
DHIA, registration and related expenses.

6 Source: Nott and Carter, 1994.

7 Calculated as herd labor per cow (Nott and Carter, 1994) minus labor for feeding and alley
scraping calculated in DAFOSYM.

82
4.3 CROP NUTRIENT REQUIREMENTS

Crop nutrient requirements as modeled in DAFOSYM were based on
nutrients removed as a function of yield (Borton et al., 1995). Crop nutrient
requirements were met ﬁrst by crop rotation carryover effects, then by manure
nutrients and ﬁnally by purchased fertilizer. Manure was applied on each crop
until the most limiting of N, P or K was met with a small over-application of
nutrients allowed. Rotated alfalfa land was ﬁrst used for corn silage production
and then for corn grain production. The N requirement was reduced by 112
kg/ha (100 lb/ac) on this land following alfalfa and yields were increased by 15%
as a rotation effect. Manure was allocated ﬁrst to corn silage land, next to corn
grain land, then to new alfalfa seedings with the remainder spread on existing
alfalfa ﬁelds. Crop nutrient requirements not met by manure were applied as
commercial fertilizer during the planting operation.

4.4 TILLAGE SYSTEMS

Three tillage systems offering a range in tillage and planting practices
were modeled. Conventional tillage included fall tillage with moldboard plowing
of all land to be planted in the spring. In the spring, corn ground was disked
once and ﬁeld cultivated once before planting. Alfalfa ground was disked twice
and ﬁeld cultivated twice before seeding. A list of tillage and planting

equipment used on each farm is included in Tables 4.7, 4.8 and 4.9.

83

Table 4.7 Major machines and structures used for planting and manure storage
on the 60 and ISO-cow representative farms.

 

 

 

 

Machine or 67 113(1654a_cre) 60-Cow Farm 145 ha (358 acre) ISO-Cow Farm
storage type Size No. Price($) Size No. Price($)
TRACTORS AND LOADERS
Conventional and mulch-tillage
Tractors 35 kW (47 hp). used 1 4,000 35 kW (47 hp). used 2 4,000
50 kW (67 hp) 1 27,150 65 kW (87 hp) 2 37,200
65 kW (87 hp) ' 1 37,200 80 kW (108 hp) 1 45,750
Skid-steer loader small 1 10,350 large 1 18,450
TILLAGE AND PLANTING
Conventional tillage
Moldboard plow 1.4 m (4.5 ft) 1 7,300 1.6 m (5.3 ft) 1 8,100
Tandem disk 2.7 m (9.0 ft) 1 3,950 4.9 m (16 ft) 1 9,750
Field cultivator 3.7 m (12.0 ft) 1 7,550 5.5 m (18 it) 1 11,250
Grain drill 2.4 m (8.0 ft) 1 5,750 2.4 m (8 ft) 1 5,750
Conventional planter 3.0 m (10.0 ft) 1 12,000 3.0 m (10 ft) 1 12,000
Mulch-tillage
Coulter-chisel plow 2.0 m (6.6 ft) 1 3,825 2.0 m (6.6 ft) 1 3,825
Seedbed conditioner 4.0 m (13 ft) 1 8,820 4.0 m (13 ft) 1 8,820
Grain drill 2.4 m (8.0 ft) 1 5,750 2.4 m (8 ft) 1 5,750
Conservation planter 3.0 m (10.0 ft) 1 13,000 3.0 m (10 ft) 1 13,000
Modiﬁed no-till
Aerator 2.4 m (8 ft) 1 5,725 3.7 m (12 ft) 1 7,800
Rotary hoe 4.5 m (15 ft) 1 3,500 4.6 m (15 ft) 1 3,500
Nootill drill (used) 2.4 m (8.0 ft) 1 5,750 2.4 m (8 ft) 1 5,750
Zone-till planter 3.0 m (10 ft) 1 17,400 3.0 m (10 ft) 1 17,400
MANURE HANDLING AND STORAGE
Semi-solid, 3 day storage
Slab/buckwall 60 m2 (645 112) 1 1,600 150 m2 (1610 1121 1 3.900
V-tank spreader 7.9 t (2100 gal) 1 15,850 9.8 t (2600 gal) 1 19,100
Slurry, 7 month storage
Clay-lined storage pit 2140 mJ (566,000 gal) 1 30,000 5237 m3 (1.4 mil. gal) 1 47,500
Slurry pump/agitator 340 t/h (1500 gpm) 1 7,200 450 W (2000 gpm) 1 9,000
Slurry spreader 8.3 t (2200 gal) 1 8,750 10.2 t (2700 gal) 1 10,350
or
Slurry injection 8.3 t(2200 gal) 1 11.400 10.2 t (2700 gal) 1 13,950
Liquid, 7 month storage
Clay-lined storage pit 2840 m3 (752,000 gal) 1 34,000 6980 m’ (1.86 mil. gal) 1 57,500
Slurry pump/agitator 340 t/h (1500 gpm) 1 7,200 450 t/h (2000 gpm) 1 9,000
Chopper pump (used) -- 1 1,950 -- 1 1,950
Pressure pump 136 t/h (600 gpm) 1 4,500 136 t/h (600 gpm) 1 4,500
Pipe (used) 500 m (1640 ft) - 3,000 750 m (2460 ft) - 4.550
Traveler w/hose (used) --- 1 5,700 m 1 5,700

 

 

An 80 kW (108 hp) tractor was used if manure was injected.

84

Table 4.8 Major machines and structures used for planting and manure storage
on the 250 and 400-cow representative farms.

 

Machine or 25011;! (616 _a_cre) 250-Cow Farm 400 h_a (988 acre) 400-Cow Farm
storage type Size No. Price($) Size No. Price($)

 

TRACTORS AND LOADERS

Tractors 35 kW (47 hp), used 3 4,000 35 kW (47 hp). used 3 4,000
65 kW (87 hp) 2 37,200 65 kW (87 hp) 2 37,200
100 kW (134 hp) 2 56,850 80 kW (108 hp) 2 45,750
-- - -- 120 kW (161 hp) 2 68,400
Skid-steer loader large 2 18,450 large 2 18,450
TILLAGE AND PLANTING
Conventional tillage
Moldboard plow 2.3 m (7.5 ft) 1 10,500 2.8 m (9 ft) 1 12,500
Tandem disk 5.5 m (18 ft) 1 12,050 7.3 m (24 ft) 1 16,750
Field cultivator 6.4 m (21 ft) 1 13,350 8.5 m (28 ft) 1 17,600
Grain drill 3.7 m (12 ft) 1 8,650 3.7 m (12 It) 1 8,650
Conventional planter 4.6 m (15 ft) 1 16,500 6.1 m (20 ft) 1 20,500
Mulch-tillage
Coulter-chisel plow 2.7 m (9 ft) 1 5,350 3.4 m (11 ft) 1 6,900
Seedbed conditioner 5.8 m (19 ft) 1 14,850 7.6 m (25 ft) 1 17,900
Grain drill 3.7 m (12 ft) 1 8,650 3.7 m ( 12 ft) 1 8,650
Conservation planter 4.6 m (15 ft) 1 18,000 6.1 m (20 ft) 1 22,250
Modified no-till
Aerator 4.9 m (16 ft) 1 9,800 6.1 m (20 ft) 1 12,800
Rotary hoe 6.1 m (20 It) 1 4,800 6.1 m (20 ft) 1 4,800
No—till drill (used) 2.4 m (8 ft) 1 5,750 4.6 m (15 ft) 1 10,000
Zone-till planter 4.6 m (15 ft) 1 24,500 6.1 m (20 ft) 1 31,000
MANURE HANDLING AND STORAGE
Semi-solid, 3 day storage
Slab/buckwall 240 1n2 (2580 ft’) 1 6,500 387 m2 (4160 ftz) 1 20,800
V-tank spreader 10.9 t (2900 gal) 1 21,000 10.9 t (2900 gal) 1 21,000
Slurry, 7 month storage
Clay-lined storage pit 8835 m3 (2.27 mil. gal) 1 67,250 14040 m3 (3.7 mil. gal) 1 96,500
Slurry pump/agitator 450 t/h (2000 gpm) 1 9,000 450 t/h (2000 gpm) 1 9,000
Slurry spreader 12.5 t(3300 gal) 2 12,300 15.1 t(4000 gal) 2 14,500
or
Slurry injection 12.5 t(3300 gal) 2 15,850 15.1 t(4000 gal) 2 18,100
Liquid, 7 month storage
Clay-lined storage pit 11730 m3 (3.1 mil. gal) 1 83,700 18700 1n3 (5 mil. gal) 1 122,700
Slurry agitator 450 t/h (2000 gpm) 1 9,000 450 t/h (2000 gpm) 1 9,000
Chopper pump (used) -- 1 1,950 -- ' I 1,950
Pressure pump 136 t/h (600 gpm) 1 4,500 136 t/h (600 gpm) 1 4,500
Auxiliary pump «- - - 136 t/h (600 gpm) 1 4,500
Pipe (used) 1000 m (3280 ft) - 6,000 2000 m (6560 ft) - 12,150
Traveler w/hose (used) --- 1 5,700 «- 1 5,700

 

85

 

 

 

Table 4.9 Major machines and structures used for tillage, planting and manure
storage on the 800-cow representative farm.
Machine or 800 hajlﬁ‘Mre) 800-Cow Farm
storage type Size No. Price($)
TRACTORS AND LOADERS
Tractors 35 kW (47 hp), 6 4,000
65 kW (87 hp) 3 37,200
80 kW (108 hp) 3 45,750
120 kW (161 hp) 4 68,400
Skid-steer loader large 3 18,450
TILLAGE AND PLANTING
Mulch-tillage
Coulter-chisel plow 3.4 m (11 ft) 2 6,900
Seedbed conditioner 7.6 m (25 It) 2 17,900
Grain drill 4.9 m (16 ft) 1 11,500
Conservation planter 9.1 m (30 ft) 1 31,500
MANURE HANDLING AND STORAGE
Semi-solid, 3 day storage
Slab/buckwall 773 m2 (8320 11’) 1 20,800
V-tank spreader 10.9 t (2900 gal) 2 21,000
Slurry, 7 month storage
Clay-lined storage pit 28000 m3 (7.4 mil. gal) 1 157,400
Slurry pump/agitator 450 t/h (2000 gpm) 1 9,000
Slurry spreader 15.1 t (4000 gal) 4 14,500
or
Slurry injection 15.1 t(4000 gal) 18,100
Liquid, 7 month storage
Clay-lined storage pit 37400 rnJ (9.9 mil. gal) 1 210,000
Slurry agitator large 1 9,000
Chopper pump, used --- 2 1,950
Pressure pump 136 t/h (600 gpm) 2 4,500
Auxiliary pump 136 t/h (600 gpm) 2 4,500
Pipe, used 5000 m (16,400 ft) - 30,350
Traveler w/hose, used -- 2 5,700

 

Mulch-tillage included primary tillage with a coulter-chisel plow in the fall
and spring seedbed tillage with a combination disk/ﬁeld cultivator/coil-tine
harrow. Land to be planted to corn required one pass for manure incorporation
and seedbed preparation in the spring while alfalfa land was worked twice prior

to seeding.

86

A modiﬁed no-till system was used which included fall tillage with a
rolling tine aerator. The aerator buried very little residue yet loosened the soil,
improved water inﬁltration and helped alleviate shallow soil compaction. When
manure was irrigated a rotary hoe was used in the spring to speed drying of the
soil surface. Specialized no-till drills using coulters mounted in front of the
furrow openers to cut through surface residue and till a narrow band of soil were
used. Zone-till planters using a gang of three ﬂuted coulters to till a band of soil
15-30 cm (6-12 in.) wide for each seed furrow were used.

Residue cover on corn ground following grain harvest was assumed to be
65%, consistent with the long-term average grain yield of 7,300 kg/ha (116
bu/ac). The rolling-tine aerator reduced residue cover to 60%, chisel plowing
reduced cover to 35% and all residue was buried by moldboard plowing.
Residue cover was assumed to decrease by 5 percentage units over winter leaving
0%, 30% and 55% cover in the spring for conventional, mulch-till and modiﬁed
no-till systems, respectively.

Manure spreading was begun in the spring as soon as the soil was thawed
and soil moisture was suitable. Weather permitting, spring disking was allowed
to begin April 10 and ﬁeld cultivating April 20. Seedbed tillage with mulch-till
and rotary hoeing with modiﬁed no-till was allowed to begin April 20. Alfalfa

seeding could begin April 20 and corn planting May 1 with each tillage system.

87

Fall manure spreading and tillage began after corn silage harvest and continued
as land became available following harvest of high-moisture corn or corn grain.
4.5 MANURE HANDLING SYSTEMS

Four manure storage and handling systems typical of Michigan farms using
free-stall housing were modeled: a system of short-term (3 day) storage with
frequent hauling and three systems using long-term storage: 1) slurry tanker
spreading 2) slurry tanker injection and 3) liquid irrigation. Manure handling
rates were a composite of rates reported in the literature or measured by the
author on the farms of experienced dairy producers. A description of the storage
structures and equipment used is listed in Tables 4.7, 4.8 and 4.9.

Short-term storage with daily hauling is among the most common of
manure handling systems in Michigan. A V-bottom tanker was used for daily
hauling of semi-solid (13% DM) manure. Manure was removed from the barn
with a tractor mounted scraper and the spreader was loaded directly from a push-
off ramp. A three day storage capacity was provided using a concrete slab with
a buckwall. A full spreader was always hauled to the ﬁeld. A suitable day was
not required for spreading with this system.

Manure was removed from long-term storage by irrigation (6% DM) or
hauling with top loaded slurry tankers (9% DM). One-half of the annual manure
production was spread in the spring with the remainder spread in the fall, but

seven months storage capacity in a clay-lined pit was provided. The excess

88

storage capacity increased annual storage costs about 12%, but it helped prevent
the need to spread on wet soil and provided ﬂexibility in the tillage and
spreading schedule. Pit agitation and tanker loading were with a tractor powered
pump/agitator. Pit agitation was begun two hours prior to the start of spreading
and then continued only during tanker loading. Agitation was continuous during
irrigation.

The average hauling distance for manure spreading on the 60-cow (0.5 km,
0.3 mi), 150-cow (0.8 km, 0.5 mi) and 250-cow (1 km, 0.6 mi) herds was based
on an average travel distance with contiguous crop acreage and centrally located
storage structures. The larger farms were not assumed to have a contiguous land
base. The average hauling distance for the 400-cow farm was 2 km (1.25 mi)
and 3 km (1.9 mi) for the 800-cow farm. When manure was irrigated, a pressure
pump capable of pumping up to 1 km (0.61 mi) was located at the storage pit.
One auxiliary pump was added to pump manure up to 2 km (1.25 mi) on the
400-cow farm and two auxiliary pumps were added for the 3 km (1.9 mi)
pumping distance covered on the 800-cow farm. Each manure handling option
was compatible with conventional and mulch-tillage. However, slurry injection
was not an option with modiﬁed no-till since slurry injectors were disruptive of
the soil surface and additional tillage was required to level the surface and
prepare a seedbed. Tanker spreading, irrigation and daily hauling with a V-tank

spreader were compared in the modiﬁed no-till systems.

89

Manure hauled daily and all manure under no-till management was
assumed to be left on the surface more than 15 days. Injected slurry was
incorporated immediately. Surface spread slurries and irrigated liquid were
incorporated within three days of spreading. Phosphorus and potassium were
considered stable and available for crop grth regardless of placement or time
between spreading and incorporation. Nitrogen, however, was subject to
volatilization losses in the barn, during storage and after spreading (Borton et al.,
1995). A longer delay in incorporation led to greater loss of volatile N.

4.6 SELECTION OF TILLAGE, PLANTING AND MANURE
HANDLING EQUIPMENT

Tractor power, spreader and tillage equipment capacity were chosen by
ﬁrst selecting the tractor power and forage harvester capacity needed for the most
economical return to the forage harvesting operation. Tillage equipment was
then chosen as the largest implement possible at the designated depth and speed
of operation based on the tractor power available (Table 3.1) but implement
width was reduced if net return could be increased without creating delays in
subsequent tillage and planting operations.

Safety in transport is a major concern when hauling large tankers and
Spreaders. Tanker and spreader capacities were chosen based on both mass and
power requirements. Tankers and Spreaders were selected such that the mass of
the loaded implement was not greater than two times the tractor mass. Tractor

mass was estimated as 80 kg/pto-kW (130 lb/pto-hp). When additional power

90

was needed to accommodate injector draft, tractor power was increased without
increasing tanker capacity.
4.7 SIMULATION PROCEDURE

Farmers strive to ﬁnish fall tillage by mid-November since in most years
few days are suitable after that time. In the spring, timely planting is important
since corn grain and silage yields and corn silage quality declines rapidly if
planting is delayed beyond May 10. Simulation of 60, 150, 250, 400 and 800-
cow representative farms was used to compare the costs and performance of
conventional, mulch-till and modiﬁed no-till planting systems and their
interaction with various manure handling systems. Manure application
alternatives included V-tank transport of semi-solids, tanker spreading or tanker
injection of manure slurry and liquid irrigation. To demonstrate the effect of the
scheduled ﬁeld operations and length of work day on timeliness of major ﬁeld
operations, the number of simultaneous operations and length of workday were

varied.

5. RESULTS AND DISCUSSION

The expanded DAFOSYM model provides a ﬂexible and useful tool for
comparing the long-term performance and economics of tillage and manure
handling systems and their interaction with feed production on dairy farms.
Although DAFOSYM offers a wide range of system options, many assumptions
were made to simplify the analysis. Labor, interest and depreciation rates were
the same for all farms. Animal housing and feeding systems and the level of
management were similar for all farms. Unless speciﬁed, machinery and
equipment was purchased new, depreciated over ten years and replaced. Soils
were uniform, well drained loams and the choice of the tillage and manure
handling system was not limited by site-speciﬁc or environmental constraints.
Corn grain was custom harvested and did not affect the progress of other ﬁeld
operations but a four cutting alfalfa harvest system was used which diverted labor
from tillage and manure handling in mid-October. Government cost-sharing and
tax effects were not considered.

5.1 COMPARISON OF MANURE HANDLING COST AND RESOURCE
USE

Manure handling systems on Michigan dairy farms range from short-term
storage with frequent hauling to long-term storage with irrigation or nurse tanker
transport to ﬁelds located far from the herd. Frequent hauling is preferred by
many producers because the direct costs are low, little specialized equipment is

required and there are no concentrated labor demands. Long-term storage can

91

92

allow for timely application, improve nutrient use and reduce runoff, but direct
costs for specialized equipment and storage are high and labor needed for
spreading may conﬂict with other ﬁeld operations.

Manure moisture content greatly affected the amount of manure handled
and had an impact on machinery selection and machinery, fuel, labor and total
costs. Dilution of semi-solid manure at 13% DM to 9% DM for tanker transport
increased the amount of material handled by 63% (Tables B.1-B.13) and more
than doubled the mass of material handled when diluted to 6% DM for irrigation.
5.1.1 Nutrient Recovery

The slurry systems improved recovery of manurial nitrogen and led to a
small reduction in commercial fertilizer purchased. The nutrient value of injected
slurry was about $72/yr per cow plus replacements (Tables B.1-B.13). When
incorporation was delayed, nitrogen losses continued for up to 15 days until all
volatile N was lost. Volatile N losses reduced the nutrient value by about
$3/cow-yr if the manure was delayed more than 15 days and $1.50/cow-yr with
a three day delay in incorporation.

5.1.2 Manure Storage

Manure storage was the single greatest cost incurred in the change from
short-term storage with daily hauling to long-term storage with slurry spreading.
The lowest costs were for the slab/buckwall used with daily hauling. The annual

ownership cost with this system was $3/cow-yr on each farm. Costs increased

93
greatly with long-term slurry storage. When a dilute slurry (5%-7% DM) was

irrigated, the required storage capacity increased about 33% and annual costs

about 20%.

Table 5.1 Annual ownership costs for three manure storage systems.

 

Ownership costs, $/cow-yr
60-cow 150-cow 250—cow 400-cow 800-cow

 

Manure Storage

slab/buckwall 3 3 3 3 3
clay-lined pit, slurry 51 32 28 25 20
clay-lined pit, liquid 58 39 34 31 27

 

5.1.3 Machinery

Machinery costs include implement ownership and repair and maintenance
based on accumulated use. Tractor selection was based on power needed for
economical forage harvest and feeding of the milking herd. Tractor and loader
costs were based on proportional use but total costs changed little with use.
Tractor ownership plus repair and maintenance costs were about $0.16/kW-hr
($0.12/hp-hr) and annual costs for tractors and loaders ranged from $210/cow-yr
on the 60-cow farm to $120 on the 800-cow farm (Table 5.2). Annual costs
increased to $233/cow-yr for the 60-cow farm when manure injection was used
since a larger tractor was needed.

The V-tank spreader used for daily hauling was loaded directly from a
push—off ramp so a special pump or loader was not required. Slurry hauling
required a pit agitator/pump and slurry tankers for transport and spreading.

When slurry injection was required, slurry injectors were added at an additional

94

cost. The irrigation system required a pit agitator, a chopper pump to deliver a
uniform material for pumping, a pressure pump, a traveling gun and 15 cm (6
in.) aluminum pipe for transport. When the pumping distance was greater than
1 km (0.62 mi) and auxiliary pump was used to provide sufﬁcient pressure at the

gun nozzle.

Table 5.2 Annual ownership costs for tractors, loaders and manure handling

 

 

 

equipment.
Owners_hip costs, §/coWﬂ
60-cow 1 50-cow 250-cow 400-cow 800-cow

Tractors and Loaders 210 156 152 141 120
Manure Handling Equipment

spreader tanker, injection 74 37 39 27 24

spreader tanker, slurry 64 31 32 23 20

irrigation, liquid 89 41 26 23 22

V-tank, daily haul 63 31 20 13 13

 

The lowest cost for manure handling equipment was generally associated
with daily hauling and the greatest with tanker injection. However, machinery
costs for irrigation equipment varied greatly among farm sizes. Pumping
capacity was ﬁxed and this provided excess capacity and high costs on the 60
and 150-cow farms. Costs decreased on the larger farms where the pump
capacity was better matched to the amount of material handled.

5.1.4 Fuel Use

Fuel use for manure handling varied with hauling method and pit agitation

time. The most fuel was used for slurry injection and the least with V-tank

spreading or slurry irrigation (Table 5.3). When the V-tank spreader was loaded

95

directly from a push-off ramp, fuel use for hauling and spreading ranged from
18 L/cow-yr on the 60-cow farm to 41 L/cow-yr on the 800-cow farm. Bucket
loading (front-end loader) increased fuel use about 7 L/cow-yr (2 gal/cow-yr).
The slurry systems required tractors for both transport and agitation/pumping.
Fuel use for pit agitation was about 10 L/cow-yr (2.6 gal/cow-yr) when the pit
was agitated only during tanker ﬁlling and increased to about 12 L/cow-yr (3.2
gal/cow-yr) with continuous agitation during irrigation.

Fuel use for hauling and spreading with a V-tank spreader increased with
herd size. Fuel use ranged from 18 to 21 L/cow-yr for herds of 60 to 250-cows
as spreader capacity increased from 7,950 L (2,100 gal) to 10,975 L (2,900 gal).
Larger tractors were used on the 400 and 800-cow farms but the spreader
capacity remained the same as on the 250-cow farm since larger spreaders were
not available. This increased fuel use. Hauling and spreading required 33
L/cow-yr (8.8 gal/cow-yr) on the 400-cow farm and 41 L/cow-yr (11.1 gal/cow-
yr) on the 800-cow farm.

Table 5.3 Fuel use for manure loading, transport and spreading.

 

Fuel use, L/cow-Lr
60-cow ISO-cow 250-cow 400-cow 800-cow

 

injector tanker 48 43 48 61 73
spreader tanker 37 36 41 54 65
irrigation 22 25 27 43 48
V-tank w/push-off ramp 18 17 21 33 41

V-tank w/bucket loading 25 , 24 28 40 48

 

96

Manure irrigation was the most fuel efﬁcient slurry spreading method.
Fuel use nearly doubled on the 400 and 800-cow farms compared to the smaller
farms since auxiliary pumps and tractors were added. Fuel use for irrigation
' ranged ﬁ'om 22 L/cow-yr (5.8 gal/cow-yr) for the 60-cow farm to 48 L/cow-yr
(12.7 gal/cow-yr) for the 800-cow farm.
5.1.5 Labor

Labor for transport and spreading was inﬂuenced by spreading method and
tanker loading and unloading rate. Tanker loading and unloading rates were
inﬂuenced by the power available at the pump or spreader. Loading a V-tank
spreader from a push-off ramp created no additional labor beyond that required
for alley scraping. Transport and spreading in this manner required 1.4 h/cow-yr
for the 60-cow herd and 1 h/cow-yr for the 150 and 250-cow herds where larger
spreaders were used (Table 5.4). Labor for transport and spreading increased on
the 400 (1.3 h/cow-yr) and 800-cow (1.6 h/cow-yr) farms since the hauling
distance increased but the spreader capacity remained the same. Bucket (front-
end loader) loading increased labor for manure handling about 0.75 h/cow-yr on
each farm.

Even though the hauling distance was greater for the larger herds, labor
efﬁciency (L hauled/min) for slurry hauling increased with the use of larger
tankers and transfer pumps. The tanker loading rates ranged from 3,200 lein

(850 gpm) on the 60-cow farm to 4,150 L/min (1,100 gpm) on the 150 and 250-

97
cow farms and 5,100 L/min (1,350 gpm) on the 400 and 800-cow farms.

Unloading rates ranged from 2,550 L/min (675 gpm) for the small tankers on the
60-cow farm to 3,400 L/min (900 gpm) on the larger farms. The tanker
unloading rate was the same for both the tanker spreader and the tanker injector,
but more time was needed for maintenance of the injector tankers. Tanker
injection required about 10% more labor than tanker spreading. The unloading
rate of the V-tank spreader was 2,840 L/min (750 gpm).

Tanker injection required the most labor of the manure handling methods.
Labor decreased from 2.1 h/cow-yr for the 60-cow herd to 1.7 h/cow-yr for the
250-cow herd as tanker size increased from 8,325 L (2,200 gal) to 12,500 L
(3,300 gal). Labor increased a small amount for the 400-cow (1.9 h/cow-yr) and
800-cow (2/h-cow-yr) farms as hauling distance increased but the use of larger
tankers (15,150 L, 4,000 gal) helped reduce travel time. About 10% less labor
was needed for tanker spreading than tanker injection since less time was needed
for maintenance and repairs.

Table 5.4 Labor used for manure loading, transport and spreading.

 

Labor, h/cow-yr
60-cow 150-cow 250-cow 400-cow 800-cow

 

Hauling distance, km 0.5 0.75 1.0 2.0 3.0
injector tanker 2.1 1.9 1.7 1.8 2.2
spreader tanker 1.9 1.6 1.5 1.6 2.0
irrigation 1.2 1.1 1.0 1.4 1.9
V-tank w/push-off ramp 1.4 1.0 1.0 1.3 1.3

V-tank w/bucket loading 2.2 1.8 1.8 2.1 2.1

 

98

Manure irrigation required less labor than the other slurry systems.
Irrigation required about 1.2 h/cow-yr on the 60-cow farm. An auxiliary pump
was added on the larger farms if manure was pumped further than 1 km (0.62
mi). Labor increased to 1.4 h/cow-yr on the 400-cow farm since two people
were required to tend the pump, auxiliary pump and traveler. Three people were
needed to tend the two pressure pumps and two auxiliary pumps used on the
800-cow farm and labor needs increased to 1.9 h/cow-yr.

5.2 COMPARISON OF TILLAGE COST AND RESOURCE USE

Conventional tillage is favored on many livestock farms because of the
ease with which both crop residue and manure can be incorporated and managed.
Mulch-tillage is used on an increasing number of farms since machinery, fuel and
labor costs can be reduced yet all manure handling options are available.
Modiﬁed no-till can reduce fuel and labor costs and protect the soil from erosion
but manure injection is not possible and nutrient loss to the environment may be
greater.

5.2.1 Machinery

The highest ownership cost for tillage equipment was associated with
conventional tillage and the lowest with mulch-till. Modiﬁed no-till equipment
was slightly higher than mulch-till equipment (Table 5.5). The only tillage

equipment used with the modiﬁed no-till system was a soil aerator and, if

99

manure was irrigated, a rotary hoe. Lower costs for tillage equipment were
largely offset by higher costs for planting equipment.

Table 5.5 Annual ownership costs for tractors, loaders and tillage equipment.

 

Ownership costs, $/cow-yr
60-cow ISO-cow 250-cow 400-cow 800-cow

 

Tractors and Loaders 210 156 152 141 120
Tillage/Planting Equipment
conventional 1 03 56 42 32 «-
mulch-till 88 38 32 23 21
modiﬁed no-till 91 42 31 25 «-

 

5.2.2 Fuel Use

The greatest fuel use for tillage and planting was associated with
conventional tillage (Table 5.6). Fuel use ranged from 27 L/cow-yr (7.1 gal/cow-
yr) on the 60-cow farm to 23 L/cow-yr (6.1 gal/cow-yr) on the 400-cow farm
(Table 5.6). Mulch-tillage reduced ﬁJel use about 30% compared to conventional
tillage. Fuel use for mulch tillage ranged from 19 L (5 gal)/cow-yr on the 150-
cow farm to 15 L (4 gal)/cow-yr on the 800-cow farm. The most fuel efﬁcient
system was modiﬁed no-till where fuel use dropped about 50% compared to
conventional tillage. Fuel use for tillage and planting was about 13 L/cow-yr
(3.7 gal/cow-yr) on most farms.

Table 5.6 Fuel use for tillage and planting.

 

Fuel use, L/COWﬂ
60-cow 150-cow 250-cow 400-cow 800-cow

 

conventional 27 25 25 23 ---
mulch—till 18 19 16 16 15
modiﬁed no-till 13 13 12 13 m

 

100
5.2.3 Labor

Labor decreased as tillage intensity decreased or larger tillage and planting
equipment were used. The most labor was associated with conventional tillage
on the small farms. Conventional tillage required about 2.0 h/cow-yr on the 60-
cow farm but less than 1.0 h/cow-yr on the 400-cow farm (Table 5.7). Mulch-
tillage reduced the labor needed for tillage and planting by about 35% compared
to conventional tillage. Labor for mulch-tillage ranged from 1.2 h/cow on the
60-cow farm and 0.5 h/cow-yr on the 800-cow farm. Modiﬁed no-till generally
required less than one-half of the labor needed for conventional tillage.

Table 5.7 Labor used for tillage and planting.

 

Ebor. h/cow-yr
60-cow ISO-cow 250-cow 400-cow 800-cow

 

conventional 2.0 1 .6 1 .2 0.9 «-
mulch-till 1.2 1.1 0.8 0.6 0.5
modiﬁed no—till 0.9 0.7 0.6 0.5 ---

 

5.3 NET RETURN

The net return was calculated as the difference between the income from
milk sales and the net cost of handling the manure, producing and harvesting the
crops and feeding, milking and caring for the milking herd and young stock. The
net return increased with herd size from 60 to 800 cows (Table 5.8). When
mulch-tillage was used, 69% of the increase in net return gained by increasing

herd size from 60 to 800 cows was obtained by increasing herd size from 60 to

101

150-cows. Increasing herd size to 250-cows provided 81% and 400 cows
provided 90% of the net return available to the 800-cow herd.

Table 5.8 Net return for three tillage and four manure spreading systems.

 

Net Return /cow- r

 

Tank Tank
Injector Spreader Irrigation V-Tank

60-cow

conventional -342 -3 13 -3 16 -246

mulch-till -303 -278 -281 -213

modiﬁed no—till --- -298 -301 -220
ISO-cow

conventional 225 245 253 303

mulch-till 25 1 269 278 327

modiﬁed no-till --- 264 265 321
250-cow

conventional 334 346 355 389

mulch-till 354 364 374 410

modiﬁed no-till m 357 363 406
400-cow

conventional 408 42 1 437 462

mulch-till 425 438 453 477

modiﬁed no-till --- 428 440 470
800-cow

mulch-till 502 518 539 558

 

Mulch-till provided the greatest return among tillage systems. The annual
cost of tillage equipment for modiﬁed no-till was similar to mulch-till (Table
5.5), but fuel (Table 5.6) and labor (Table 5.7) costs were lower for modiﬁed no-
till. However, these savings were offset by higher costs for seed, fertilizer,
herbicides and insecticides (Table 4.2). Seed and chemical costs were $32/ha
($l3/ac) higher for establishment year alfalfa and $17/ha ($7/ac) for corn
following alfalfa in the modiﬁed no-till system. Fertilizer costs about $3.00/cow-

yr higher with the no-till system where manure was not incorporated. Mulch-till

102

till increased net return about $l9/cow-yr compared to modiﬁed no-till for the
60-cow herd but the advantage was only about $10/cow-yr for the 400-cow herd.

Across tillage systems the highest net return was associated with short-
terrn manure storage and frequent hauling and the lowest with long-term storage
and tanker injection. Compared to slurry injection, slurry spreading increased net
return about $10/cow-yr for farms of 150 cows or more and increased net return
even more ($25/cow-yr) for the 60-cow farm. Compared to slurry injection,
irrigation improved net returns $18/cow-yr on the 60-cow farm and $37/cow-yr
on the 800-cow farm.

The greatest net return among manure hauling systems was associated with
short-term storage and frequent hauling with a V-tank spreader if the manure
nutrient value is included. The advantage for daily hauling over slurry injection
ranged from $96/cow-yr on the 60-cow farm with conventional tillage to
$56/cow-yr with mulch-tillage on the 800-cow farm. Most of the difference in
net return between long-term and short-term storage systems was due to the high
cost of manure storage (Table 5.1). If the nutrient value ($72/cow-yr) of the
manure was not included there was little difference in net return between daily
hauling and slurry systems with long-term storage.

5.4 EFFECT OF LABOR SCHEDULE ON SYSTEM PERFORMANCE

The timeliness of tillage and planting is inﬂuenced by the number of

simultaneous operations and the type of tillage and manure handling used. On

103

small farms, one person may have responsibility for all ﬁeld work plus
management and care of the livestock. On larger farms, one or more workers
may devote all their attention to ﬁeld work or their time may be divided between
ﬁeld and livestock duties. More labor and power is usually available on larger
farms so manure hauling and tillage may be able to progress simultaneously.
The expected completion dates (50% probability) for major ﬁeld operations for
representative farms with varying labor schedules are listed in Tables 5.9-5.14.

5.4.1 60-Cow Farm: One Operation, Tillage and Manure Handling in
Series.

One person was available six hours per day for all ﬁeld operations on the
60-cow farm. Fall tillage and spreading began after corn silage was harvested
in late September but was delayed by alfalfa harvest in mid-October. Corn grain
was custom harvested and did not require on-farm labor. Spreading from long-
term storage delayed both the start and ﬁnish of fall tillage. Conventional tillage
was complete by November 2 when manure was hauled daily but was not
ﬁnished until about nine days later with tanker injection (Table 5 9)

The longest delays in spring tillage and manure spreading were associated
with conventional tillage and tanker injection. Spring spreading began April 9
with conventional and mulch-tillage on the 60-cow farm and a day later with
modiﬁed no-till. Manure irrigation was ﬁnished within a few days but tanker
injection required more than two weeks. Spring tillage was ﬁnished by the end

of the ﬁrst week in May in most years on the 60-cow farm.

104
Corn planting began May 1 and was ﬁnished by May 5 with each tillage

system if manure was hauled daily. Slurry injection delayed planting ﬁve to
eight days. The latest corn planting was associated with conventional tillage but
neither tillage nor manure hauling had a strong adverse effect on timeliness.
Tanker injection caused the greatest variability in corn planting on the 60-cow
farm. Planting with conventional tillage was ﬁnished after May 20 four times
following tanker injection and three times following tanker spreading but was
always ﬁnished by May 20 with daily hauling or irrigation. Delaying planting
with tanker injection increased feed costs about $4/cow-yr compared to daily
hauling of manure.

5.4.2 Effect of Hours Worked on System Performance, 60-cow Farm

The effect of hours worked on system performance was demonstrated by
comparing timeliness with both six and eight hour days spent on ﬁeld operations.
Increasing the length of the workday improved the ability to complete ﬁeld
operations in a timely fashion.

Since the equipment used on the 60-cow farm had sufﬁcient capacity to
allow ﬁeld work to be completed with little delay with all tillage and manure
hauling methods, there was little economic beneﬁt in increasing the length of the
workday. Increasing the length of work day to eight hours had the greatest
impact with tanker injection in a conventional tillage system. Compared to the

six hour day, fall spreading by tanker injection was completed three days sooner

105

Table 5.9 Predicted dates (50% probability) to begin and end major ﬁeld
operations for a 60-cow dairy in central Michigan: one implement
working six hours per day, ﬁeld operations in series.

 

 

 

Fall Fall Spring Spring Corn
Spreading Tillage Spreading Tillage Planting
Begin End Begin End Begin End Begin End Begin End
Conventional
Slurry injection 9/23 10/20 9/28 11/11 4/9 4/24 4/25 5/7 5/8 5/12
(3.7) ' (9.7) (4.1) (21.8) (6.8) (9.1) (9.3) (9.9) (8.7) (8.9)
[3] 2 [4]
Slurry tankers 9/22 10/ 17 9/26 11/8 4/9 4/21 4/23 5/4 5/6 5/11
(3.5) (7.1) (3.8) (19.7) (7.0) (8.8) (8.5) (8.8) (7.2) (8.2)
[3] [3]
Liquid irrigation 9/22 10/12 9/24 11/4 4/9 4/12 4/15 4/29 5/2 5/6
(3.5) (4.9) (3.4) (20.4) (7.0) (7.3) (6.0) (5.5) (3.4) (4.6)
[31 [01
Semi-solid, -- -- 9/23 1 1/2 -- -- 4/13 4/27 5/ 1 5/5
daily haul (3.7) (17.7) (3.3) (3.9) (1.9) (3.5)
[3] [0]
Mulch-till
Slurry injection 9/23 10/19 10/1 11/3 4/9 4/25 4/28 5/3 5/5 5/10
(3.6) (9.9) (6.8) (20.6) (6.9) (9.4) (7.5) (7.7) (5.7) (7.6)
[3] [31
Slurry tankers 9/23 10/16 9/28 11/1 4/9 4/22 4/26 5/1 5/3 5/9
(3.5) (6.9) (4.1) (17.9) (7.0) (8.7) (6.5) (6.3) (4.2) (7.3)
[2] [3]
Liquid irrigation 9/23 10/11 9/24 10/22 4/9 4/13 4/22 4/28 5/1 5/5
(3.5) (4.8) (3.5) (10.3) (7 .0) (7.3) (3.3) (4.0) (1.9) (2.8)
[0] [0]
Daily haul -- -- 9/24 10/19 -- -- 4/21 4/27 5/1 5/5
(3.4) (9.4) (2.0) (3.9) (1.5) (2.6)
[0] [0]
Modiﬁed no-till
Slurry tankers 9/22 10/17 9/26 10/31 4/ 10 4/23 -- -- 5/3 5/7
(3.5) (7.1) (3.8) (17.9) (7.0) (8.9) (3.3) (5.3)
[2] [2]
Liquid irrigation 9/22 10/11 9/24 10/ 19 4/10 4/13 4/19 4/22 5/2 5/5
(3.5) (4.9) (3.4) (9.6) (7.0) (7.5) (4.8) (6.3) (4.0) (4.2)
[0] ' [1]
Daily haul -- -- 9/23 10/17 -- -- -- -- 5/2 5/5
(3.7) (9.7) (3.9) (4.1)
[0] [1]

 

with the longer workday (Table 5.10). Moldboard plowing was ﬁnished about

a week earlier and chisel plowing two to three days earlier than with a six hour

 

' ( ) indicates standard deviation from the mean.

2 [ ] indicates number of years in 26 when fall tillage was delayed beyond November 30 or corn
planting beyond May 20.

106

Table 5.10. Predicted dates (50% probability) to begin and end major ﬁeld
operations for a 60-cow dairy in central Michigan: one implement
working eight hours per day, ﬁeld operations in series.

Fall Fall Spring Spring Corn
Spreading Tillage Spreading Tillage Planting

Begin End Begin End Begin End Begin End Begin End

 

Conventional

Slurry injection 9/23 10/18 9/29 11/5 4/9 4/21 4/22 5/1 5/4 5/8
(3.7) ' (9.9) (4.1) (20.3) (6.8) (9.0) (8.3) (7.8) (5.2) (6.8)

[3] 2 [2]

Slurry tankers 9/22 10/15 9/25 11/3 4/9 4/18 4/20 4/30 5/3 5/6
(3.5) (6.9) (3.5) (17.7) (7.0) (8.7) (7.7) (7.0) (4.4) (5.0)

[3] [1]

Liquid irrigation 9/22 10/ 12 9/24 10/24 4/9 4/10 4/14 4/27 5/1 5/4
(3.5) (4.9) (3.4) (9.9) (7.0) (7.0) (5.0) (4.7) (2.2) (3.4)

[1] [01
Semi-solid, -- -- 9/23 10/24 -- -- 4/13 4/26 5/1 5/4
daily haul (3.7) (9.6) (3.3) (4.0) (1.6) (2.8)
[01 [0]
Mulch-till

Injection 9/23 10/ 17 9/28 11/2 ' 4/9 4/22 4/26 4/29 5/3 5/6
(3.7) (9.9) (4.1) (10.6) (6.9) (9.1) (6.0) (6.5) (3.7) (4.6)
[1] [01
Tankers 9/23 10/14 9/27 10/23 4/9 4/19 4/24 4/28 5/2 5/4
(3.5) (6.6) (4.0) (10.0) (7.0) (9.1) (5.1) (5.4) (2.6) (3.5)
[0] [0]
Irrigation 9/23 10/1 1 9/24 10/18 4/9 4/1 1 4/21 4/26 5/1 5/4
(3.5) (4.8) (3.5) (9.7) (7.0) (7.1) (2.0) (4.0) (1.6) (2.0)
[0] [0]
Daily haul -- -- 9/24 10/17 -- -- 4/21 4/25 5/1 5/3
(3.6) (9.7) (2.0) (3.3) (1.4) (1.8)
101 101

Modiﬁed no-till
Tankers 9/22 10/15 9/26 10/22 4/10 4/20 -- -- 5/1 5/5
(3.5) (6.9) (3.9) (10.2) (7.0) (8.8) (4.1) (4.7)
[0] [1]
Irrigation 9/22 10/1 1 9/24 10/18 4/10 4/12 4/18 4/20 5/2 5/4
(3.5) (4.9) (3.4) (9.9) (7 .0) (7.5) (3.4) (6.0) (1 .4) (4.2)
101 . 111
Daily haul -- -- 9/24 10/18 -- -- -- -- 5/1 5/4
(3 .4) (9.6) (1.4) (3.9)
[01 [1]

 

day. When manure was hauled daily, fall tillage was rarely delayed beyond the

end of November regardless of the tillage system used.

 

‘ ( ) indicates standard deviation from the mean.
2 [ ] indicates number of years in 26 when fall tillage was delayed beyond November 30 or corn
planting beyond May 20.

107

Spring tillage and planting were not greatly affected little by the longer
work day if manure was hauled daily, but corn was planted about four days
sooner when slurry injection was used. Compared to a six hour work day, feed
costs were reduced about $2/cow-yr with an eight hour day with conventional
tillage and slurry injection.

5.4.3 150-Cow Farm: One Operation, Tillage and Manure Handling in
Series.

One person was available ten hours per day for tillage, planting and
manure handling on the 150-cow farm. Manure handling, tillage and planting
progressed in series. Slurry injection and tanker spreading delayed planting and
led to high timeliness costs.

Fall tillage and spreading began in late September after corn silage harvest
(Table 5.11). Manure irrigation was ﬁnished in early October but slurry injection
was not ﬁnished until the end of October. Fall tillage began in late September
and moldboard plowing was ﬁnished by the end of October when manure was
hauled daily. When slurry injection was used tillage began in early November
and was not ﬁnished until early December. Chisel plowing was ﬁnished about
two weeks sooner than moldboard plowing.

The longest delays in spring tillage and spreading were associated with
conventional tillage and tanker injection. Spring spreading began about April 10
and manure irrigation was ﬁnished about a week later. Slurry injection was not

ﬁnished until the ﬁrst week of May. Spring tillage was ﬁnished by the end of

108

 

 

 

Table 5.11 Predicted dates (50% probability) to begin and end major ﬁeld
operations for a 150-cow dairy in central Michigan: one implement
working ten hours per day, ﬁeld operations in series.

Fall Fall Spring Spring Corn
Spreading Tillage Spreading Tillage Planting
Begin End Begin End Begin End Begin End Begin End
Conventional
Slun'y injection 9/28 10/28 1 1/3 12/5 4/9 5/6 5/7 5/16 5/16 5/24
(3.8)' (19.5) (26.5) (26.0) (6.8) (11.2) (11.1) (10.7) (10.2) (10.2)
[12] 2 [15]
Slurry tankers 9/27 10/16 10/20 1 1/26 4/9 4/29 5/1 5/12 5/13 5/19
(3.6) (11.3) (17.2) (26.9) (7.0) (9.4) (10.4) (10.1) (9.4) (9.6)
[9] [13]
Liquid irrigation 9/27 10/7 10/7 11/7 4/9 4/17 4/19 5/3 5/4 5/12
(3.6) (6.3) (9.5) (24.4) (7.0) (8.5) (7.2) (7.0) (5.5) (7.7)
[4] [4]
Semi-solid, -- -- 9/23 10/30 -- -- 4/13 4/29 5/1 5/9
daily haul (3.8) (25.2) (3.3) (3.8) (2.1) (4.5)
[3] [1]
Mulch-till
Injection 9/28 10/28 1 1/3 1 1/22 4/9 5/7 5/8 5/15 5/15 5/23
(3.8) (19.5) (26.5) (27.9) (6.9) (11.6) (11.3) (11.0) (10.5) (10.4)
[9] [151
Tankers 9/27 10/16 10/20 1 1/9 4/9 5/1 5/3 5/1 1 5/1 1 5/18
(3.6) (11.3) (17.2) (23.3) (7.0) (10.1) (9.3) (10.0) (9.6) (9.3)
14] [10]
irrigation 9/27 10/7 10/7 10/22 4/9 4/18 4/24 5/2 5/4 5/12
(3.6) (6.3) (9.5) (18.6) (7.0) (9.0) (4.8) (5.5) (4.2) (7.2)
[21 [3]
Daily haul -- -- 9/28 10/17 -- -- 4/21 4/29 5/2 5/10
(3.8) (17.4) (2.0) (3.8) (2.1) (4.9)
[11 [0]
Modiﬁed no-till
Tankers 9/27 10/16 10/20 11/1 4/10 5/2 -- -- 5/9 5/15
(3.6) (1 1.3) (17.2) (23.6) (7.0) (10.7) (9.1) (9.3)
[41 [7]
Irrigation 9/27 10/7 10/7 1 m 6 4/ 10 4/19 4/24 4/30 5/3 5/1 1
(3.6) (6.3) (9.6) (17.7) (7.0) (9.0) (4.9) (5.5) (4.5) (7.1)
[11 [4]
Daily haul -- -- 9/28 10/9 -- -- -- -- 5/2 5/8
(3.8) (9.1) (3.7) (4.6)
101 [1]

 

 

' ( ) indicates standard deviation from the mean.
2 [ ] indicates number of years in 26 when fall tillage was delayed beyond November 30 or corn
planting beyond May 20.

109

April when manure was hauled daily but was delayed until the middle of May
by slurry injection. Corn was planted by May 10 when manure was hauled daily
but was not planted until late May with manure injectioﬂ‘anker injection caused
the greatest variability in corn planting on the ISO-cow farm. Delayed planting
decreased the amount of grain produced and the quality of feeds fed, increased
feed costs and decreased net return (Tables B.4-B.6). Planting delays with
conventional tillage increased feed costs $24/cow-yr with slurry injection and
$15/cow-yr with tanker spreading.

5.4.4 250-Cow Farm: Two Operations, Tillage and Manure Handling in
Series.

Two manure tankers were used for slurry hauling on the 250-cow farm.
Two workers were available ten hours per day and manure hauling and tillage
were in series; manure storage was emptied before fall tillage began. 1f manure
was hauled daily, tillage began as soon as corn silage was harvested.

Delaying fall tillage ﬁve to eight days in late September delayed the ﬁnish
as much as two weeks since suitable days drop off rapidly after the end of
October (Table 5.13). If manure was hauled daily moldboard plowing was
ﬁnished by early November but slurry injection delayed plowing as much as
three weeks. Chisel plowing was ﬁnished one or two weeks sooner and soil
aeration two or three weeks sooner than moldboard plowing. The longest delay

with each tillage system was associated with tanker injection.

110

Table 5.12 Predicted dates (50% probability) to begin and end major ﬁeld
operations for a 250-cow dairy in central Michigan: two implement
working ten hours per day, manure application and tillage in series.

 

 

 

Fall Fall Spring Spring Corn
Spreading Tillage Spreading Tillage Planting
Begin End Begin End Begin End Begin End Begin End
Conventional
Slurry injection 9/23 10/17 10/2 11/20 4/9 4/25 4/26 5/12 5/12 5/18
(3.7)3 (17.9) (8.8) (28.1) (6.8) (9.5) (9.5) (10.0) (9.5) (9.8)
[31‘ [10]
Slurry tankers 9/22 10/11 9/28 11/13 4/9 4/21 4/24 5/10 5/10 5/15
(3.5) (10.5) (3.7) (27.2) (7.0) (8.8) (9.0) (9.6) (9.2) (9.2)
[6] [8]

Liquid irrigation 9/22 10/11 9/27 11/9 4/9 4/20 4/23 5/9 5/9 5/14
(3.5) (9.9) (4.0) (24.2) (7.0) (8.7) (8.5) (9.6) (9.1) (9.0)

[4] [6]
Semi-solid, -- -- 9/23 10/29 -- -- 4/13 5/1 5/3 5/9
daily haul (3.7) (20.9) (3.3) (4.7) (3.4) (5.6)
[2] [2]

Mulch-till
Slurry injection 9/23 10/ 17 10/2 11/5 4/9 4/27 4/29 5/8 5/9 5/15
(3.7) (17.8) (8.8) (23.2) (6.9) (9.7) (7.6) (9.9) (9.1) (9.5)
[31 [71
Slurry tankers 9/22 10/11 9/28 10/27 4/9 4/22 4/27 5/6 5/7 5/13
(3.5) (10.5) (4.7) (17.4) (7.0) (8.7) (6.8) (9.0) (8.2) (8.5)
[2] [5]

Liquid irrigation 9/22 10/11 9/27 10/27 4/9 4/20 4/26 5/5 5/6 5/13
(3.5) (10.0) (4.0) (17.1) (7.0) (8.7) (6.5) (8.3) (7.3) (8.2)

[2] [5]
Daily haul -- -- 9/23 10/20 -- -- 4/21 5/1 5/2 5/8
(3.7) (18.3) (2.0) (3.8) (2.5) (4.3)
[21 [0]

Modiﬁed no-till
Sluny tankers 9/22 10/11 9/28 10/22 4/10 4/23 -- -- 5/5 5/11
(3.5) (10.5) (4.7) (17.5) (7.0) (9.0) (5.3) (7.6)
[11 [4]

Liquid irrigation 9/22 10/11 9/27 10/22 4/10 4/21 4/27 5/3 5/6 5/12
(3.5) (10.0) (4.0) (17.5) (7.0) (8.7) (6.4) (6.9) '(6.0) (7.9)

[l] [4]

Daily haul -- -- 9/23 10/16 -- -- -- -- 5/2 5/7
(3.7) (17.6) (3.9) (4.7)

[I] [1]

 

 

3 ( ) indicates standard deviation from the mean.
‘ [ ] indicates number of years in 26 when fall tillage was delayed beyond November 30 or corn
planting beyond May 20.

111

The longest delay in spring tillage was associated with conventional tillage
and within tillage systems, with tanker injection. Spring spreading began by
April 10. Slurry irrigation was ﬁnished by April 20 and tanker injection a few
days later. Conventional spring tillage began about two weeks sooner with daily
manure hauling than with tanker injection. Spring tillage was ﬁnished by early
May with daily hauling but was delayed as much as twelve days by slurry
injection.

Corn was usually planted by May 10 (50% probability) with daily hauling
but slurry injection delayed planting a week or more. Manure irrigation caused
a small delay in planting but on most farms, the irrigation system would have
been operated more hours per day and on days when the soil was dry enough to
prevent runoff but too wet for tanker trafﬁc. Under such management irrigation
would rarely delay planting. Compared to daily hauling, feed costs increased $11
to $l3/cow-yr with conventional tillage, $8 to $12/cow-yr with mulch-tillage and
$3 to $5/cow-yr with modiﬁed no-till (Tables B.9-B.11).

5.4.5 250-Cow Farm: Three Operations, Parallel Tillage and Manure
Handling.

An alternative labor schedule using three workers eight hours per day was
used on the 250-cow farm. This allowed tillage to begin at the same time as
slurry spreading. Other than a small advantage with the longer workday, there
was little difference in fall spreading with the two labor schedules since the same

equipment was used (Table 5.13). However, since fall tillage began at the same

112

Table 5.13 Predicted dates (50% probability) to begin and end major ﬁeld
operations for a 250-cow dairy in central Michigan: three
implements working eight hours per day, parallel manure
application and tillage.

 

 

 

Fall Fall Spring Spring Corn
Spreading Tillage Spreading Tillage Planting
Begin End Begin End Begin End Begin End Begin End
Conventional
Slurry injection 9/23 10/20 9/23 11/4 4/9 4/28 4/13 5/3 5/4 5/ 12
(3.7) ' (18.5) (3.7) (19.5) (6.8) (9.6) (3.3) (6.9) (5.2) (7.4)
[2] 2 [41
Slurry tankers 9/22 10/ 14 9/23 “M 4/9 4/25 4/ 13 5/1 5/3 5/ 10
(3.5) (12.0) (3.7) (19.4) (7.0) (9.4) (3.3) (6.4) (3.9) (6.4)
[2] [3]

Liquid irrigation 9/22 10/13 9/23 1 1/4 4/9 4/23 4/13 4/29 5/1 5/8
(3.5) (11.5) (3.7) (19.4) (7.0) (9.0) (3.3) (4.4) (2.1) (4.6)

[2] [3]
Semi-solid, -- -- 9/23 1 1/4 -- -- 4/1 3 4/27 5/1 5/8
daily haul (3.7) (19.4) (3.3) (3.7) (1.3) (4.0)
[21 [ll
Mulch-till

Injection 9/23 10/19 9/23 10/25 4/9 4/30 4/21 5/1 5/2 5/1 1
(3.7) (18.7) (3.7) (21.2) (6.9) (10.4) (2.0) (4.4) (2.9) (6.0)
[21 [31
Tankers 9/22 10/14 9/23 10/25 4/9 4/27 4/21 5/1 5/2 5/10
(3.5) (12.0) (3.7) (21.1) (7.0) (9.5) (2.0) (4.6) (2.8) (6.0)
' [2] [21
Irrigation 9/22 10/14 9/23 10/25 4/9 4/23 4/21 4/29 5/1 5/9
(3.5) (11.5) (3.7) (21.1) (7.0) (9.2) (2.0) (4.2) (1.7) (4.3)
[2] [0]
Daily haul -- -- 9/23 10/25 -- -- 4/21 4/27 5/1 5/8
(3.7) (21.1) (2.0) (3.9) (1.3) (3.9)
12] [0]

Modiﬁed no—till
Tankers 9/22 10/14 9/23 10/18 4/10 4/27 -- -- 5/1 5/8
(3.5) (12.0) (3.7) (17.6) (7.0) (9.4) (3.9) (4.7)
[11 [1]
Irrigation 9/22 10/13 9/23 10/21 4/10 4/24 4/21 4/26 5/2 5/8
(3.5) (11.5) (3.7) (17.6) (7.0) (9.2) (2.0) (4.3) (3.9) (4.7)
[1] [1]
Daily haul -- -- 9/23 10/ 18 -- -- -- -- 5/2 5/8
(3.7) (17.6) (3.9) (4.7)
[1] [1]

 

 

' ( ) indicates standard deviation from the mean.
2 [ ] indicates number of years in 26 when fall tillage was delayed beyond November 30 or corn
planting beyond May 20.

113

time as slurry hauling, there was little difference in the completion of fall tillage
whether manure was hauled daily (November 5) or injected (November 8).
Chisel plowing was ﬁnished about one week and aeration two weeks sooner than
moldboard plowing.

Spring slurry injection was ﬁnished ﬁve to seven days later than slurry
irrigation. Spring tillage was ﬁnished by the end of April when manure was
hauled daily and four to six days later with tanker injection. Delaying spring
tillage with tanker injection delayed corn planting. Corn was planted by May 8
when manure was hauled daily. Tanker injection delayed corn planting three to
four days.

5.4.6 400-Cow Farm: Three Operations, Parallel Tillage and Manure
Handling.

Three workers were available ten hours per day on the 400-cow farm.
This allowed parallel tillage and manure hauling. Compared to the 250-cow farm
a longer workday, larger slurry tankers and tillage equipment were used (Table
4.8). When using mulch-tillage, fall tillage was ﬁnished about two weeks
sooner if manure was hauled daily (October 22) than if injected (Table 5.14).
Slurry injection delayed spring tillage more than one week. Corn was usually
planted by May 10 with daily hauling but was delayed about six days with tanker
injection. Compared to daily manure hauling on the 400-cow farm, feed related
costs increased $4/cow-yr with tanker spreading, $6/cow-yr with irrigation and

$9/cow-yr with tanker injection (Table 8.11).

114

Table 5.14 Predicted dates (50% probability) to begin and end major ﬁeld
operations for a 400-cow dairy in central Michigan: three
implements working ten hours per day, parallel manure application

 

and tillage.
Fall Fall Spring Spring Corn
Spreading Tillage Spreading Tillage Planting

 

Begin End Begin End Begin End Begin End Begin End
Conventional

Slurry injection 9/26 10/27 9/26 11/15 4/9 5/7 4/13 5/1 5/3 5/11
(3.8)3 (18.3) (3.8) (23.6) (6.8) (11.1) (3.3) (4.7) (3.4) (6.6)

[51‘ [4]2

Slurry tankers 9/26 10/19 9/26 11/15 4/9 5/2 4/13 5/2 5/3 5/11
(3.5) (12.5) (3.8) (23.6) (7.0) (10.4) (3.3) (5.2) (3.8) (6.7)

[51 [4]

Liquid irrigation 9/26 10/15 9/26 11/ 15 4/9 4/27 4/13 4/28 5/1 5/8
(3.5) (11.6) (3.8) (23.6) (7.0) (9.3) (3.3) (3.9) (1.9) (4.5)

[5] [1]
Semi-solid, -- -- 9/26 1 1/15 -- -- 4/13 4/27 5/1 5/8
daily haul (3.8) (23.6) (3.3) (3.6) (1.3) (3.9)
121 [1]
Mulch-till

Injection 9/26 10/27 9/26 10/31 4/9 5/8 4/21 5/2 5/3 5/1 1
(3.8) (18.3) (3.8) (18.6) (6.9) (11.6) (2.0) (4.1) (3.0) (5.2)
[2] [0]
Tankers 9/26 10/19 9/26 1 1/4 4/9 5/4 4/21 5/1 5/3 5/10
(3.5) (12.5) (3.8) (21.1) (7.0) (10.6) (2.0) (4.1) (3.0) (5.1)
12] [0]
Irrigation 9/26 10/15 9/26 10/31 4/9 4/28 4/21 4/29 5/1 5/8
(3.5) (11.6) (3.8) (18.6) (7.0) (9.3) (2.0) (3.9) (1.5) (3.9)
[21 [0]
Daily haul -- -- 9/26 10/31 -- -- 4/21 4/27 5/1 5/8
(3.8) (18.6) (2.0) (3.9) (1.3) (3.9)
12 [0]

Modiﬁed no-till
Tankers 9/26 10/19 9/26 10/20 4/10 5/5 -- -- 5/2 5/9
(3.5) (12.5) (3.8) (12.3) (7.0) (11.4) . (3.8) (4.8)
[0] [1]
Irrigation 9/26 10/15 9/26 10/20 4/10 4/29 4/21 4/28 5/2 5/9
(3.5) (11.6) (3.8) (12.3) (7.0) (9.5) (2.0) (4.0) (3.8) (4.8)
[01 [1]
Daily haul -- -- 9/26 10/20 -- -- -- -- 5/2 5/8
(3.8) (12.3) (3.7) (4.6)
[0] [1]

 

 

’ ( ) indicates standard deviation from the mean.

‘ [ ] indicates number of years in 26 when fall tillage was delayed beyond November 30 or corn
planting beyond May 20.

115
5.5 APPLICABILITY OF THE SIMULATION RESULTS

Farmers considering expansion or seeking to improve their farming system
should evaluate both tillage and manure handling systems. Compared to
conventional tillage, mulch-tillage can reduce machinery costs, fuel use and labor
and improve the timeliness of ﬁeld operations. Modiﬁed no-till can further
decrease fuel and labor costs but those savings may be offset by higher costs for
seed, herbicides, insecticides and fertilizer. Slurry injection and tanker spreading
may delay tillage and planting. When using these systems, adequate labor,
power and equipment should be available to allow parallel tillage and manure
spreading operations. Daily hauling can improve timeliness and simplify labor
scheduling on most farms.

The proﬁtability of manure handling systems depends upon the ability to
recycle manure nutrient for crop production and reduce commercial fertilizer
costs. Accounting for these nutrients is easier when spreading stored manure
than when spreading daily. When manure is hauled daily, nutrient concentration
and uniformity of distribution is highly variable both within and between ﬁelds.
Fields close to the barn often receive heavier applications than more remote
locations. Coarse textured soils receive manure when the soil is wet, ﬁne texture
soils when the soil is dry. And during the growing season, some ﬁelds are left

uncropped for the purpose of manure disposal. 1f the value of the spread manure

116

($72/cow-yr) is reduced to allow for inefﬁcient use, the net return with daily
hauling is be similar to slurry systems.

Cost and labor requirements are important but environmental constraints,
together with governmental regulations, will strongly inﬂuence the selection of
tillage and manure handling systems in the future. Environmental risks are farm
and ﬁeld speciﬁc. Manure spread on frozen or snow covered, sloping ﬁelds
adjacent to surface waters may threaten water quality. But the risk is not great
if ﬁelds are nearly level and conservation tillage is combined with vegetative
buffer strips or other erosion control structures to prevent runoff. Manure
injection may be the best way to minimize odor and runoff, but it may not be the
best choice for coarse textured soil with a high water tables since deep placement
may facilitate leaching of nitrogen to groundwater. Manure irrigation is cost
effective and labor efﬁcient but over-application, runoff, wind drift and odor
transport are potential problems. Irrigation is best suited to level or gently

sloping ﬁelds in sparsely populated areas.

6. CONCLUSIONS

The expanded DAFOSYM model provides a flexible and useful tool for

comparing the long-term performance and economics of tillage and manure

handling systems on dairy farms.

1.

The highest machinery, fuel, labor and timeliness costs for manure hauling
were associated with slurry injection and the lowest with daily V-tank
hauling if the spreader was loaded from a push-off ramp during alley
scraping. If bucket loading of the spreader was used, costs were similar
to the slurry hauling systems.

The lowest fuel, labor and timeliness costs for slurry manure systems
were associated with irrigation.

The greatest net return among manure hauling systems was associated
with short-term storage and daily hauling if manure nutrients were
recovered for crop growth. Irrigation provided the greatest return and
slurry injection the lowest return among slurry systems. If manure
nutrients were not recovered and used for crop growth, the net return with
daily hauling was similar to the slurry hauling systems.

The highest machinery, fuel, labor and timeliness costs for tillage and
planting were associated with moldboard plowing and conventional
seedbed preparation. Compared to conventional tillage, mulch-tillage

reduced machinery, fuel and labor costs about 30%. Machinery costs for

117

118

the modiﬁed no-till system were similar to mulch-tillage, but fuel and
labor costs were further reduced to about 50% of that needed for
conventional tillage.

The greatest net return among tillage systems was associated with mulch-
tillage. Modiﬁed no-till provided a higher return than conventional
tillage, but compared to mulch-tillage, savings in fuel and labor were
offset by higher costs for seed, fertilizer, herbicides and insecticides.
Net return increased with herd size from 60 to 800 cows with all
tillage/manure systems. Most of the increase in net return (69%) was
gained as herd size increased from 60 to 150 cows. Increasing herd size
to 250 cows provided 81% and 400 cows, 90% of the net return earned
by the 800-cow farm.

The number of simultaneous ﬁeld operations and length of workday
inﬂuenced system cost and performance. The highest timeliness costs
were associated with tanker injection and conventional tillage. The lowest
timeliness costs were associated manure irrigation or daily manure

hauling.

7. RECOMMENDATIONS
The following recommendation is made with respect to the need for future
research.
1. Simulation models such as DAFOSYM must be further
reﬁned and expanded to allow additional crops such as
wheat and soybeans in the crop mix. These crops provide
ﬂexibility in timing of manure application and efﬁciency of
nutrient utilization and may help determine the best

machinery and management alternatives for individual farms.

119

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APPENDICES

APPENDIX A

Subroutine SUITDAY

C*********************************************************************

SUBROUTINE SUITDAY

C*********************************************************************

OOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO

O

DETERMINES IF A GIVEN DAY IS SUITABLE FOR FIELD WORK. BASED
ON CERES-MAIZE BY JONES AND KINRY, 1986

SOIL(S,3)=unitless, bare soil albedo
SOIL(S,4)=mm/d, upper limit of stage 1 soil evap.
SOIL(S,5)=g/cc, soil bulk density

SOIL(S,6)=%, organic carbon

SOIL(S,7)=constant

SOIL(S,8)=%, silt content

SOIL(S,9)=%, clay content

SOIL(S,10)=%, sand content

SOIL(S,11)=SCS runoff curve number
SOIL(S,12)=whole proﬁle drainage rate coefﬁcient
LL=lower limit of plant extractable water, cm/cm
DUL=ﬁeld capacity extractable water, cm/cm
SAT=saturated soil water, cm/cm

PO=%, soil porosity

XZ=density correction factor

BDM=g/cc, maximum bulk density

DLAYR=cm, depth of soil layers
NLAYR=number of soil layers to simulate
ES=actual soil evap., mm/d

EOS=potential soil evaporation, mm/d
ESW=crn/cm, extractable soil water

RC=residue cover, %

SWRqelative plant ext. soil water in layer
FLUX=saturated moisture ﬂow between layers
DRAIN=cm/d, drainage rate from a layer
WINF=cm, precip that inﬁltrates

THET1=soil water above LL for upper layer, cm/cm
THET2=soil water above LL for lower layer, cm/cm
DBAR=avg soil water diffusivity

FLOW=unsat. ﬂow, cm

INTEGER S,ND(12)
+,IWGT5(45)

144

C

145

REAL LL,DLAYR(4),SW(4)
+,SDP(26,18),SDPMS(3,18),PROB(18)
INCLUDE ’GENERALBLK’
INCLUDE ’TILL.BLK’

INCLUDE ’MANUREBLK’
INCLUDE ’OPER.BLK’

DATA DLAYR /3.,4.6,7.6,100./,NLAYR /4/
DATA ND /31,28,3l,30,31,30,3l,31,30,3l,30,31/

C DETERMINE SOIL WATER HOLDING CAPACITY

C

S=ISOIL
PO=1-SOIL(S,5)/2.65
XZ=SOIL(S,6)*0.0172
BDM=(1-XZ)/(l/SOIL(S,5)-XZ/O.224)
IF(SOIL(S,10).GT.75) THEN
W1=O.19-0.0017*SOIL(S,10)
W2=0.429-0.00388*SOIL(S,10)
ELSEIF(SOIL(S,8).GT.70) THEN
W1=0.16
W2=0.1079+0.000504*SOIL(S,8)
ELSE
W1=0.0542+0.00409*SOIL(S,9)
W2=0.1079+0.000504*SOIL(S,8)
ENDIF
LL=W1*(1.-XZ)*(1.+BDM-SOIL(S,5))+0.23*XZ
DUL=LL+W2*(1.-XZ)-(BDM-SOIL(S,5))*0.2+0.55*XZ
SAT=SOIL(S,7)*(PO-DUL)+DUL
DO J==1,NLAYR
SW(J)=SAT
ENDDo
SWEF=0.9-0.00038*(DLAYR(1)-30.)**2

C DETERMINE SPRING THAW DATE

DD=O.

TMAX=O.

DO 1=60,110
TAV=AMAX1(0.,(WTHR(I,3)+WTHR(1,4))/2.)
IF(TAV.LE.0) DD=0.
TMAX=AMAX1(TMAX,TAV)
IF(TMAX.GT.7) THEN

DD=DD+TAV
ELSE

DD=DD+TAV/6.
ENDIF

146

IF(DD.LT.14) lTHAW=1
STDAY(I,1)=0.0
STDAY(I,2)=0.0
STDAY(I,3)=0.0

ENDDo
C
C DAILY TIME LOOP
Do I=ITHAw,365

SOLRAD=WTHR(I,2)
TEMPMX=WTHR(I,3)
TEMPMN=WTHR(I,4)
PRECIP=WTHR(I,5)

C RESIDUE COVER
IF(I.LT.180.AND.ICRNPL.LE.4) THEN

RC=0.30
ELSE
RC=0.65

ENDIF
SWR=AMIN1(1.,(SW(1)-LL)/(DUL-LL))
IF(SWR.LT.O.9) THEN

SUMESI=SOIL(S,4)

SUMESZ=25.-27.8*SWR
=(SUMES2/3.5)**2

ELSE

SUMESl=lOO.-SWR*100.

SUMES2=0.

T=0.

ENDIF
WINF=PRECIP
FLUX=O.1*PRECIP
C
C CALCULATE INFILTRATION, DRAINAGE AND SATURATED FLOW
Do L=1,NLAYR
HOLD=(SAT-SW(L))*DLAYR(L)
IF ((FLUX.EQ.0.0) .OR. (FLUX.LE.HOLD)) THEN
SW(L)=SW(L)+FLUX/DLAYR(L)
IF(SW(L).GT.DUL+0.003) THEN
DRAIN=(SW(L)-DUL)*SOIL(S,12)*DLAYR(L)
SW(L)=SW(L)-DRAIN/DLAYR(L)
FLUX=DRAIN

ELSE
FLUX=0.

ENDIF

ELSE
DRAIN=(SAT-DUL)*SOIL(S,12)*DLAYR(L)

C

147

SW(L)=SAT-DRAIN/DLAYR(L)
FLUX=FLUX-HOLD+DRAIN
ENDIF
ENDDO

C CALCULATE SOIL EVAPORATION

C

POTENTIAL EVAPORATION
TD=0.6*TEMPMX+0.4*TEMPMN
EEQ=SOLRAD*(1.-0.5*RC)*(0.00488-0.00437*SOIL(S,3))*(TD+29.)
EOS=EEQ*1.1
IF(TEMPMX.GT.35) EOS=EEQ*((TEMPMX-35.)*0.05+1.1)
IF(TEMPMX.LT.5) EOS=EEQ*0.01*EXP(0.18*(TEMPMX+20.))

ACTUAL SOIL EVAPORATION
IF(SUMESI.oE.SOIL(S,4).AND.WINE.OE.SUMEsz) THEN
WINF=W1NF-SUMES2
SUMES1=SOIL(S,4)-WINF
T=0
IF(WINF.GT.SOIL(S,4)) SUMESI=0.0
SUMESI=SUMESI+EOS
IF(SUMES1.GT.SOIL(S,4)) THEN
ES=EOS-O.4*(SUMES1-SOIL(S,4))
SUME32=0.6*(SUMESI-SOIL(S,4))
T=(SUMESZ/3.5)**2
ELSE
ES=EOS
ENDIF
ELSEIE(SUMESI.GE.SOIL(S,4).AND.WINF.LT.SUMEsz) THEN
T=T+1.
ES=3.5*T**0.5-SUMES2
IF(WINF.GT.0) THEN
ESX=O.8*WINF
IF(ESX.LE.ES) ESX=ES+WINF
ES=AMIN1(EOS,ESX)
ELSEIF(ES.GT.EOS) THEN
ES=EOS
ENDIF
SUMES2=SUMEsz+Es-WINE
T=(SUMESZ/3.5)**2
ELSEIF(WINF.GE.SUMES1) THEN
SUMESI=EOS
1F(SUMES1.GT.SOIL(S,4)) THEN
ES=EOS-0.4*(SUMESI-SOIL(S,4))
SUMESZ=0.6*(SUMES1-SOIL(S,4))
=(SUMESZ/3.5)**2

148

ELSE
ES=EOS
ENDIF
ELSE
SUMESI=SUMES1-WINF+EOS
IF(SUMESI.GT.SOIL(S,4)) THEN
ES=EOS-0.4*(SUMES1-SOIL(S,4))
SUMES2=0.6*(SUMES1-SOIL(S,4))
T=(SUMES2/3.5)**2
ELSE
ES=EOS
ENDIF
ENDIF
SW(1)=AMAX1(LL*SWEF,SW(1)-ES*0.l/DLAYR(1))
C
C ESTIMATE PLANT EXTRACTED MOISTURE (0.3 CM/DAY FROM LOWER
LAYER)
IF(I.GT.150.AND.I.LT.270) THEN
SW(4)=AMAX1(LL,SW(4)-0.3/DLAYR(4))
ENDIF
C
C CALCULATE UNSATURATED FLOW BELOW FIELD CAPACITY
DO J=1,NLAYR-1
=J+1
THET1=AMAX1(0.,SW(J)-LL)
THET2=AMAX1(0.,SW(M)-LL)
DBAR=AMIN1(100.,0.88*EXP(35.4*(THET1+THET2)*0.5))
FLOW=DBAR*(THET2-THET1)/((DLAYR(J)+DLAYR(M))*0.5)
IF(FLOW.LT.O) THEN
FLOW=AMAX1(FLOW,(SW(M)-SW(J))*DLAYR(J))
ELSE
FLOW=AMIN1(FLOW,(DUL-SW(J))*DLAYR(J))
ENDIF
SW(J)=SW(J)+FLOW/DLAYR(J)
SW(M)=SW(M)-FLOW/DLAYR(M)
ENDDO
C
C DETERMINE IF DAY IS SUITABLE FOR FIELD WORK
IF(I.LT.180) THEN
IF(SW(1).LE.SOIL(S,13)*DUL.AND.SW(2).LE.
+ SOIL(S,l3)*DUL.AND.SW(3).LE.SOIL(S,l4)*DUL) THEN
C DAY IS SUITABLE FOR TILLAGE AND PLANTING
STDAY(I,1)=1
ELSE
STDAY(I,1)=0

149

ENDIF
ELSE
IF(SW(1).LE.SOIL(S,15)*DUL.AND.SW(2).LE.
+ SOIL(S,15)*DUL.AND.SW(3).LE.SOIL(S,16)*DUL) THEN
C DAY IS SUITABLE FOR TILLAGE AND PLANTING
STDAY(I,1)=1
ELSE
STDAY(I,1)=0
ENDIF
ENDIF
IF(I.LT.180) THEN
IF(SW(1).LT.SOIL(S,15)*DUL.AND.SW(2).LE.SOIL(S,15)*DUL.AND.
+ SW(3).LE.SOIL(S,16)*DUL) THEN
C DAY IS SUITABLE FOR SURFACE SPREADING (SPRING)
STDAY(I,2)=1
ELSE
STDAY(I,2)=0
ENDIF
ELSE
IF(SW(1).LT.SOIL(S,17)*DUL.AND.SW(2).LE.SOIL(S,17)*DUL.AND.
+ SW(3).LE.SOIL(S,18)*DUL) THEN
C DAY SUITABLE FOR SURFACE SPREADING OR CORN HARVEST
(FALL)
STDAY(I,2)=1
ELSE
STDAY(I,2)=0
ENDIF
ENDIF
STDAY(I,3)=STDAY(I,2)
IF(ISPD.GE.l3.AND.ISPD.LE.16) THEN

C MANURE INJECTION, SAME SUITABLE DAYS AS TILLAGE
STDAY(I,2)=STDAY(I,1)
ENDIF
ENDDO
C
C SUMMARIZE DATA FOR DETAILED OUTPUT
Do I=1,12

SDP1(NTHYR,I)=0.0
SDP2(NTHYR,I)=0.0
ENDDO

L=0
DO M=1,12
Do I=1,ND(M)
L=L+1

150

SDP l (N THYR.M)=SDP l (N THYR,M)+STDAY(L, 1 )
SDP2(NTHYR,M)=SDP2(NTHYR,M)+STDAY(L,3)
ENDDO
ENDDO

APPENDIX B

Annual Feed and Manure Production, System Costs and Net Return

 

 

Table B.1 Annual feed and manure production, system costs and net return
with conventional tillage and four manure handling systems on a
high producIng, 60-cow dalry farm.

Slurry Slurry Liquid Semi-
injection spreader irrigation solid

Production or cost parameter Unit tankers tankers V-tanker

CONVENTIONAL TILLAGE

Feed production and utilization

Preharvest alfalfa production t DM 348 348 348 348

High quality alf. hay production t DM 64 67 67 67

Low quality alf. hay production t DM 21 17 17 17

Alfalfa silage production t DM 198 199 199 I99

Corn silage production t DM 128 129 129 129

High-moisture corn production t DM --- --- --- ---

Corn grain production t DM 124 125 125 125

Corn grain purchased (sold) t DM (27) (29) (29) (29)

Alfalfa purchased (sold) t DM 31 30 30 30

Soybean meal purchased tDM 25 25 25 25

Average milk production L/cow 9,297 9,308 9,312 9,315

Manure production and utilization

Manure, bedding and waste handled t WM 3,671 3,669 4,890 2,256

Manure applied to alfalfa land t WM 1,487 1,491 1,990 919

Manure applied to corn grain t WM 1,474 1,469 1,956 902

Manure applied to corn silage t WM 711 710 944 435

Manure nitrogen to cropland t 8 7 7 6

Manure phosphorus to cropland t 3 3 3 3

Manure potassium to cropland t 10 10 10 10

Manure fertilizer value credit 3 4,515 4,461 4,463 4,321

System costs and returns

System machinery cost $ 34,363 33,138 33,660 32,847

System fuel and electric cost 5 3,934 3,690 3,576 3,414

System feed and manure storage cost $ 9,412 9,421 9,828 6,516

System labor cost $ 12,168 12,210 11,684 11,726

Seed, fertilizer and chemical cost 5 7,281 7,335 7,333 7,475

Corn grain drying cost S 2,494 2,469 2,447 2,444

Land charge S 8,000 8,000 8,000 8,000

Feed and bedding purchased $ 9,543 9,330 9,310 9,326

Income from milk sales $/cow 2,557 2.560 2,561 2,562

Total feed and manure cost $/cow 1,453 1,427 1,431 1,362

Other major costs $/cow 1,446 1,446 1,446 1,446

Net return $/cow -342 -313 -316 -246

 

151

Table B.2

Annual feed and manure production, system costs and net return

with mulch tillage and four manure handling systems on a high
producing, 60-cow dairy farm.

 

 

Slun'y Slurry Liquid Semi-

injection spreader irrigation solid
Production or cost parameter Unit tankers tankers V-tanker
MULCH-TILLAGE
Feed production and utilization
Preharvest alfalfa production t DM 348 348 348 348
High quality alf. hay production t DM 64 67 67 67
Low quality alf. hay production t DM 21 18 18 18
Alfalfa silage production t DM 196 197 197 197
Corn silage production t DM I44 144 144 144
High-moisture corn production t DM -- --- -- «-
Corn grain production t DM 119 119 118 118
Corn grain purchased (sold) t DM (24) (24) (24) (24)
Alfalfa purchased (sold) t DM 17 16 16 16
Soybean meal purchased t DM 27 27 27 27
Average milk production Ucow 9,359 9,365 9,369 9,369
Manure production and utilization
Manure, bedding and waste handled t WM 3,658 3,657 4,876 2,250
Manure applied to alfalfa land t WM 1,482 1,474 1,973 912
Manure applied to corn grain t WM 1,382 1,388 1,843 850
Manure applied to corn silage t WM 794 796 1,060 489
Manure nitrogen to cropland t 8 7 7 6
Manure phosphorus to cropland t 3 3 3 3
Manure potassium to cropland t 9 9 9 9
Manure fertilizer value credit S 4,500 4,435 4,439 4,298
System costs and returns
System machinery cost S 33,714 32,535 33,006 32,206
System fuel and electric cost S 3,829 3,598 3,479 3,311
System feed and manure storage cost S 9,495 9,496 9,902 6,591
System labor cost S 12,001 12,011 11,471 11,492
Seed, fertilizer and chemical cost S 7,378 7,443 7,439 7,580
Corn grain drying cost S 2,357 2,347 2,332 2,330
Land charge S 8,000 8,000 8,000 8,000
Feed and bedding purchased S 9,080 8,980 9,044 9,055
Income from milk sales S/cow 2,574 2,575 2,576 2,576
Total feed and manure cost S/cow 1,431 1,407 1,411 1,343
Other major costs S/cow 1,446 1,446 1,446 1,446
Net return S/cow -303 -278 -281 -213

 

152

Table B.3

Annual feed and manure production, system costs and net return

with modiﬁed no-till and four manure handling systems on a high
producing, 60-cow dairy farm.

 

 

Slurry Slurry Liquid Semi-

injection spreader irrigation solid
Production or cost parameter Unit tankers tankers V-tanker
MODIFIED NO-TILL
Feed production and utilization
Preharvest alfalfa production t DM --- 348 348 348
High quality alf. hay production t DM --- 67 67 67
Low quality alf. hay production t DM --- 17 17 17
Alfalfa silage production t DM --- 199 199 199
Corn silage production t DM --- 129 129 129
High-moisture corn production t DM --- --- m «-
Corn grain production t DM --- 126 125 125
Corn grain purchased (sold) t DM --- (29) (29) (29)
Alfalfa purchased (sold) t DM --- 30 30 30
Soybean meal purchased t DM m 25 25 25
Average milk production L/cow --- 9,312 9,315 9,315
Manure production and utilization
Manure, bedding and waste handled t WM --- 3,667 4,889 2,256
Manure applied to alfalfa land t WM --- 1,488 1,986 917
Manure applied to corn grain t WM --- 1,471 1,958 904
Manure applied to corn silage t WM --- 709 944 436
Manure nitrogen to cropland t --- 6 6 6
Manure phosphorus to cropland t --- 3 3 3
Manure potassium to cropland t m 10 10 10
Manure fertilizer value credit S m 4,314 4,315 4,318
System costs and returns
System machinery cost S --- 32,110 32,573 31,294
System fuel and electric cost S --- 3,468 3,349 3,165
System feed and manure storage cost S --- 9,420 9,827 6,516
System labor cost S --- 11,678 11,135 11,091
Seed, fertilizer and chemical cost S --- 8,330 8,329 8,326
Corn grain drying cost S --- 2,477 2,468 2,466
Land charge S --- 8,000 8,000 8,000
Feed and bedding purchased S --- 9,268 9,312 9,325
Income from milk sales S/cow --- 2,561 2,562 2,562
Total feed and manure cost S/cow --- 1,413 1,417 1,336
Other major costs S/cow --- 1,446 1,446 1,446
Net return S/cow --- -298 -301 -220

 

153

Table B.4 Annual feed and manure production, system costs and net return
with conventional tillage and four manure handling systems on a

high producing, 150-cow dairy farm.

 

 

Slurry Sluny Liquid Semi-

injection spreader irrigation solid
Production or cost parameter Unit tankers tankers V-tanker
CONVENTIONAL TILLAGE
Feed production and utilization
Preharvest alfalfa production t DM 751 753 753 753
High quality alf. hay production t DM 130 129 129 129
Low quality alf. hay production t DM 48 56 56 56
Alfalfa silage production t DM 447 443 443 443
Corn silage production t DM 446 446 446 446
High-moisture corn production t DM 198 220 220 220
Corn grain production t DM 2 8 8 9
Corn grain purchased (sold) t DM 19 9 (7) (14)
Alfalfa purchased (sold) t DM 17 17 17 17
Soybean meal purchased I DM 103 102 103 103
Average milk production L/cow 9,507 9,509 9,498 9,498
Manure production and utilization
Manure, bedding and waste handled t WM 9,061 9,052 12,061 5,565
Manure applied to alfalfa land t WM 3.985 3,910 5,191 2,391
Manure applied to corn grain t WM 2,492 2,543 3,454 1,610
Manure applied to corn silage t WM 2,583 2,598 3,416 1,564
Manure nitrogen to cropland t 20 18 18 16
Manure phosphorus to cropland t 7 7 7 7
Manure potassium to cropland t 23 23 23 23
Manure fertilizer value credit S 10,764 10,535 10,567 10,308
System costs and returns
System machinery cost S 52,185 51,019 51,184 50,028
System fuel and electric cost S 8,190 7,903 7,634 7,214
System feed and manure storage cost S 13,722 13,729 14,756 9,279
System labor cost S 21,413 21,052 20,015 20,025
Seed, fertilizer and chemical cost S 16,896 17,125 17,093 17,352
Corn grain drying cost S 34 57 139 163
Land charge S 18,125 18,125 18,125 18,125
Feed and bedding purchased S 38,810 37,478 35,952 35,214
Income from milk sales S/cow 2,614 2,615 2,612 2,612
Total feed and manure cost S/cow 1,129 1,110 1,099 1,049
Other major costs S/cow 1,260 1,260 1,260 1,260
Net return S/cow 225 245 253 303

 

154

Table B.9 Annual feed and manure production, system costs and net return
with modiﬁed no—till and four manure handling systems on a high
producing, 250-cow dairy farm.

 

 

Slurry Slurry Liquid Semi-

injection spreader irrigation solid
Production or cost parameter Unit tankers tankers V-tanker
MODIFIED NO-TILL
Feed production and utilization
Preharvest alfalfa production t DM --- 1,390 1,390 1,390
High quality alf. hay production t DM --- 210 210 210
Low quality alf. hay production t DM m 139 139 139
Alfalfa silage production t DM --- 817 817 817
Corn silage production t DM --- 593 593 593
High-moisture corn production t DM --- 304 304 304
Corn grain production t DM --- 121 121 120
Corn grain purchased (sold) t DM --- (65) (65) (64)
Alfalfa purchased (sold) t DM --- 56 56 56
Soybean meal purchased t DM --- 165 165 165
Average milk production Ucow -- 9,520 9,520 9,520
Manure production and utilization
Manure, bedding and waste handled t WM --- 15,025 20,033 9,246
Manure applied to alfalfa land t WM --- 7,005 9,324 4,311
Manure applied to corn grain t WM --- 4,843 6,473 2,980
Manure applied to corn silage t WM --- 3,177 4,237 1,955
Manure nitrogen to cropland t --- 28 28 28
Manure phosphorus to cropland t --- 12 12 12
Manure potassium to cropland t --- 39 39 39
Manure fertilizer value credit S --- 17,617 17,611 17,634
System costs and returns
System machinery cost S --- 71,908 70,417 68,778
System fuel and electric cost S --- 12,241 11,737 10,966
System feed and manure storage cost S --- 20,437 22,119 14,229
System labor cost S --- 27,403 26,134 25,786
Seed, fertilizer and chemical cost S --- 31,643 31,649 31,626
Corn grain drying cost S --- 2,301 2,315 2,263
Land charge S --- 31,250 31,250 31,250
Feed and bedding purchased S --- 54,504 54,592 54,573
Income from milk sales S/cow --- 2,618 2,618 2,618
Total feed and manure cost S/cow --- 1,007 1,001 958
Other major costs S/cow --- 1,254 1,254 1,254
Net return S/cow --- 357 363 406

 

159

Table B.10 Annual feed and manure production, system costs and net return
with conventional tillage and four manure handling systems on a
high producing, 400-cow dairy farm.

 

 

Slurry Slurry Liquid Semi-

injection spreader irrigation solid
Production or cost parameter Unit tankers tankers V-tanker
CONVENTIONAL TILLAGE
Feed production and utilization
Preharvest alfalfa production t DM 2,219 2,219 2,219 2,219
High quality alf. hay production t DM 344 344 343 344
Low quality alf. hay production t DM 201 201 201 201
Alfalfa silage production t DM 1,298 1,298 1,299 1,298
Corn silage production t DM 1,068 1,068 1,068 1,068
High-moisture corn production t DM 380 380 380 380
Corn grain production t DM 232 231 238 237
Corn grain purchased (sold) t DM (59) (59) (65) (65)
Alfalfa purchased (sold) t DM 13 13 13 13
Soybean meal purchased t DM 268 268 268 269
Average milk production L/cow 9,588 9,588 9,586 9,586
Manure production and utilization
Manure, bedding and waste handled t WM 23,916 23,916 31,887 14,717
Manure applied to alfalfa land t WM 11,310 11,272 15,030 6,937
Manure applied to corn grain t WM 6,917 6,915 9,270 4,281
Manure applied to corn silage t WM 5,689 5,729 7,587 3,499
Manure nitrogen to cropland t 53 49 49 43
Manure phosphorus to cropland t 19 19 19 19
Manure potassium to cropland t 62 62 62 62
Manure fertilizer value credit S 29,211 28,711 28,715 28,041
System costs and returns
System machinery cost S 125,230 120,845 116,155 116,888
System fuel and electric cost S 24,387 23,672 22,150 21,596
System feed and manure storage cost S 28,657 28,656 31,360 19,882
System labor cost S 48,925 48,423 45,870 46,660
Seed, fertilizer and chemical cost S 44,635 45,145 45,131 45,805
Corn grain drying cost S 4,569 4,542 4,525 4,499
Land charge S 50,000 50,000 50,000 50,000
Feed and bedding purchased S 86,317 86,365 85,633 85,699
Income from milk sales S/cow 2,637 2,637 2,636 2,636
Total feed and manure cost S/cow 1,032 1,019 1,002 978
Other major costs S/cow 1,197 1,197 1,197 1,197
Net return S/cow 408 421 437 462

 

160

Table B.13 Annual feed and manure production, system costs and net return
with mulch tillage and four manure handling systems on a high
producing, 800-cow dairy farm.

 

 

Slurry Slurry Liquid Semi-

injection spreader irrigation solid
Production or cost parameter Unit tankers tankers V-tanker
MULCH-TILLAGE
Feed production and utilization
Preharvest alfalfa production t DM 4,210 4,210 4,209 4,209
High quality alf. hay production t DM 619 619 622 622
Low quality alf. hay production t DM 444 444 442 442
Alfalfa silage production t DM 2,563 2,563 2,561 2,561
Corn silage production t DM 2,161 2,161 2,161 2,161
High-moisture corn production t DM 652 652 652 652
Corn grain production t DM 521 533 580 582
Corn grain purchased (sold) t DM (60) (72) (121) (123)
Alfalfa purchased (sold) t DM 67 67 71 71
Soybean meal purchased tDM 528 528 528 528
Average milk production L/cow 9,636 9,636 9,634 9,634
Manure production and utilization
Manure, bedding and waste handled t WM 47,735 47,735 63,645 29,374
Manure applied to alfalfa land t WM 22,464 22,409 29,884 13,794
Manure applied to corn grain t WM 13,687 13,715 18,391 8,517
Manure applied to corn silage t WM 11,585 11,612 15,369 7,063
Manure nitrogen to cropland t 105 96 96 85
Manure phosphorus to cropland t 37 37 37 37
Manure potassium to cropland t 124 124 124 124
Manure fertilizer value credit S 57,362 56,328 56,421 55,134
System costs and returns
System machinery cost S 220,187 213,721 202,635 204,362
System fuel and electric cost S 54,889 51,729 50,310 48,609
System feed and manure storage cost S 53,415 53,462 59,104 39,755
System labor cost S 95,746 93,088 87,694 90,551
Seed, fertilizer and chemical cost S 87,297 88,331 88,238 89,525
Corn grain drying cost S 10,873 10,911 11,328 11,137
Land charge S 97,500 97,500 97,500 97,500
Feed and bedding purchased S 181,422 180,103 174,541 174,431
Income from milk sales S/cow 2,650 2,650 2,649 2,649
Total feed and manure cost S/cow 1,002 986 964 945
Other major costs S/cow 1,146 1,146 1,146 1,146
Net return S/cow 502 518 539 558

 

163