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The assessment of agricultural mechanization in Uganda: Perspective engineering options and strategies
Kibalama, Josephat Sentongo, Ph.D.
The Ohio State University, 1993
UMI 300 N. Zeeb Rd. Ann Arbor, MI 48106 THE ASSESSMENT OF AGRICULTURAL MECHANIZATION
IN UGANDA: PERSPECTIVE ENGINEERING OPTIONS
AND STRATEGIES
DISSERTATION
Presented in Partial Fulfillment of the Requirement for
the Degree Doctor of Philosophy in the Graduate
School of The Ohio State University
by
Josephat S. Kibalama, B.S., M.S.
* * * * *
The Ohio State University
1993
Dissertation Committee ppro
Thomas G. Carpenter, Ph.D
Robert J. Gustafson, Ph.D Advisor Department of David L. Zartman, Ph.D Agricultural Engineering To my dear father
Mr. Ernest Sentongo Kibalama ACKNOWLEDGEMENTS
I express sincere appreciation to Dr. Thomas G. Carpenter and Dr. Robert J.
Gustafson adviser and co-advisor respectively for their guidance and insight
throughout the research. Thanks go to Dr. David L. Zartman an advisory committee member for his suggestions and comments.
I am deeply indebted to Dr. Kenneth Hinchcliff of the Veterinary Clinic at
OSU for assistance rendered in traction animal instrumentation selection, and Mr.
Richard Roosenberg, the Director of Tillers International in Kalamazoo, Michigan where preliminary draft animal testing was done.
The technical assistance of Carl Cooper and Dennis Albery is gratefully acknowledged.
1 offer sincere thanks to my wife Proscovia for her willingness to endure without me. To our children, Evelyn, Jacqueline and Marjorie, I thank you for understanding my prolonged absence.
I thank the United States Agency for International Development (USAID) for funding the Manpower for Agricultural Development (MFAD) Project in
Uganda which sponsored my doctoral studies at The Ohio State University. VITA
April 5, 1952 Born - Kampala, Uganda
1977 B.S. (Eng.) Makerere University, Uganda
1977 - 1979 Special Assistant Agricultural Engineering Department, Makerere University
1981 M.S.(Agric. Eng.) University of Melbourne, Australia
1982 - Present Lecturer Department of Agricultural Engineering, Makerere University, Uganda
FIELDS OF STUDY
Major field; Agricultural Engineering
Studies in:
Agricultural Engineering: Dr. Thomas G. Carpenter, Dr. Robert J. Gustafson, Dr. Dennis P. Stombaugh
Mechanical Engineering: Dr. Gary L. Kinzel, Dr.Bernard J. Hamrock, Jack A. Collins, Rajendra Singh
Engineering Mathematics: Dr. Leroy F. Meyers, Dr. Ulrich H. Gerlach. John T. Scheick TABLE OF CONTENTS
DEDICATION ...... ii
ACKNOWLEDGEMENTS ...... iii
V ITA ...... iv
LIST OF TABLES...... x
LIST OF FIGURES...... xii
SYMBOLS ...... xvi
Chapter Page
I. INTRODUCTION ...... 1
1.1 Developing Countries ...... 1
1.2 Agricultural Mechanization...... 3
1.3 History and Progress of Mechanization...... 5
1.4 Objectives of the S tu dy...... 8
List of References...... 11
II. AGRICULTURAL MECHANIZATION IN UGANDA...... 12
2.1 Introduction ...... 12
2.2 Objectives ...... 13 2.3 Agricultural Production in Uganda...... 15
2.4 Mechanization Options...... 18
2.4.1 Human Power Mechanization ...... 21
2.4.2 Animal Powered Mechanization...... 23
2.4.3 Engine Powered Mechanization...... 25
2.4.3.1 Small Tractor Research ...... 26
2.4.3.2 Kabanyolo Small Tractor ...... 27
2.4.3.3 Mono Wheel Drive Tricycle Tractor...... 28
2.5 Mechanization Strategy...... 29
2.5.1 Tractor Power Requirement M o d el...... 30
2.5.1.1 Tractor Selection ...... 41
2.5.2 Labor and Draft Animal Requirement Model ...... 44
2.6 Conclusions ...... 50
List of References...... 52
III. ANIMAL POWERED MECHANIZATION...... 55
3.1 Introduction...... 55
3.2 Objectives ...... 56
3.3 Traction Dynamics of Draft Animals...... 57
3.3.1 Motion Mechanics of Draft Animals ...... 57
3.3.2 Traction Mechanics of Draft Animals...... 60
3.4 Traction Animal System...... 64
3.4.1 Traction Animal Instrumentation...... 65
vi 3.4.2 Traction Animal Research...... 67
3.5 Technical Problems of Animal Mechanization in Uganda ...... 70
3.6 Conclusions ...... 73
List of References...... 75
IV. DEVELOPMENT OF A TRACTION ANIMAL
DYNAMOMETER...... 77
4.1 Introduction...... 77
4.2 Objectives ...... 77
4.3 Performance Parameters...... 78
4.4 Tractive Loading D evices...... 79
4.5 Animal Physiological Parameters...... 81
4.6 Traction Animal Dynamometer D esign...... 84
4.6.1 Loading Cart Function, Features and Specifications . . . 85
4.6.2 Design Synthesis and Analysis...... 87
4.6.2.1 The Chassis ...... 88
4.6.2.2 The T ires ...... 88
4.6.2.3 Shaft D rives ...... 89
4.6.2.4 Transmission Chain ...... 90
4.6.2.5 Band Brake ...... 92
4.7 Fabrication and Assembly of the Dyno-cart...... 95
4.8 Instrumentation ...... 96
4.9 Loading Cart Calibration ...... 97
vii 4.10 Conclusions ...... 101
List of References...... 102
V. PRELIMINARY OXEN PERFORMANCE TEST...... 105
5.1 Introduction...... 105
5.2 Objectives ...... 105
5.3 Experimental Procedure...... 106
5.3.1 Traction Animals...... 106
5.3.2 Instrumentation...... 107
5.3.3 Procedure...... 107
5.4 Results and Discussion...... 109
5.4.1 The Dynamometer System...... 110
5.4.2 Traction Animal Characteristics ...... 112
5.5 Conclusions ...... 119
5.5.1 Traction Animal Dynamometer System...... 119
5.5.2 Traction Animal Testing ...... 121
List of References...... 123
VI. CONCLUSIONS AND RECOMMENDATIONS...... 124
6.1 Introduction...... 124
6.2 Conclusions ...... 124
6.3 Recommendations ...... 127
LIST OF REFERENCES...... 129
viii Appendices Page
A. THEORETICAL POWER REQUIREMENT MODELS...... 136
AJ Tractor Power Requirement M o d el...... 137
A.2 Labor and Draft Animal M odel...... 148
B. LOADING CART DESIGN ANALYSIS...... 163
B.1 Working Drawings ...... 164
B.2 Braked Wheel Traction Dynamics...... 176
B.3 Shaft D esign...... 178
B.4 Brake Band Analysis...... 180
C. INSTRUMENT SPECIFICATIONS...... 183
C.1 Force Transducer ...... 184
C.2 Chart Recorder...... 184
C.3 Veterinary Rectal Probe ...... 184
C.3.1 Digital Thermometer ...... 185
C.4 Heart Rate Monitor...... 185
D. EXPERIMENTAL DATA ...... 186
D.l Oxen Features...... 187
D.2 Oxen Yokes ...... 187
D.3 Experimental Data ...... 188
ix LIST OF TABLES
Comparative numbers of traction animals in millions (Woytinsky and
Woytinsky, 1953) ...... 8
Progression of total population, agricultural population, and active
agricultural population in Uganda ...... 13
Agricultural growth rates between 1880-1970 for USA and Japan . 19
Mechanization transition in Japan ...... 20
Mechanization transition in U S A ...... 20
Estimates of the number of ox-plows in Uganda between 1925-53 . 24
Kabanyolo Mark IV specifications ...... 27
Specifications of the Mono Wheel Tractor ...... 29
Output of the tractor optimization model based on primary tillage operation ...... 40
Percentage of tractor power ranges in the former Federal Republic of Germany ...... 43
Typical plot sizes and cropping sequence of a small holder ...... 48
Respiration, temperature and heart rate as indicators of work load in humans...... 83
x 4.2 Data for Goodyear super sure grip tires used on the loading cart. . . 89
4.3 Overall gear ratios between the transmission shaft and the brake
d r u m ...... 91
4.4 Properties of woven lining materials ...... 92
D.l Particulars of the oxen used in the experiments ...... 187
D. 1 Experiment No. 1...... 189
D.2 Experiment No. 2 ...... 190
D.3 Experiment No. 3 ...... 192
D.4 Experiment No. 4 ...... 194
D.5 Experiment No. 5 ...... 196
D.6 Experiment No. 6 ...... 197
D.7 Experiment No. 7 ...... 199
D.8 Experiment N o .8 ...... 200
D.9 Experiment No. 9 ...... 201
D.10 Experiment No. 10 ...... 202
xi LIST OF FIGURES
Figure Page
2.1 Average corn yield between 1980-1990 for selected countries, and
respective fertilizer utilization
(F.A.O, 1980-90A and F.A.O, 1980-90B) ...... 16
2.2 Cultivated area of selected crops in Uganda, in a period of 70 years
(Ministry of Agriculture & Forestry, Uganda ,1911-91) ...... 17
2.3 Relationship between the tractor weight (kN) and the PTO power
(kW). Data collated from
Tractor Test Reports (Nebraska, 1961-86) ...... 36
2.4 Relationship between Pull,P (kN) and speed v (kph), PTO power
PptL), (kW), and total tractor weight WT (kN). Data collated from
Nebraska Tractor Tests (1961-86) ...... 42
2.5 Number of hand laborers required throughout the season for the
cropping pattern shown in Table 2.9 ...... 49
2.6 Number of oxen pairs required throughout the season for the
cropping pattern shown in Table 2.9. (Note that in Jan., Jun.. and
Dec. hand labor is used because draft animals can not perform the
required farming operations) ...... 49
xii 2.7 Number of hand laborers supplemented with 2 pairs of draft
animals throughout the season for the cropping pattern shown in
Table 2.9...... 50
3.1 Top view of steady state stride cycles of an oxen as it walks, (the
arrow indicates a foot which is about to be lifted, the dotted lines
mark the stability triangle, and B is the stride length) ...... 58
3.2 Sketch of forces exerted on the ground in one stride by each leg of
a quadruped while walking ...... 59
3.3 Sketch of a quadruped about to generate tractive effort T. (rear left
hoof (4) is about to move) ...... 61
3.4 Variation of the optimum inclination of the line of pull with respect
to the indicated parameters. (x(/L is assumed to equal to 0.2) ...... 63
3.5 Schematic outline of traction animal system ...... 66
4.1 Some options of loading draft animals for the purpose of testing their
performance ...... 80
4.2 Relationship between the brake actuating force and the drawbar
pull...... 98
4.3 Experimental and theoretical gross traction ratio of the
dyno-eart ...... 99
5.1 Decline in animal heart rate immediately following three minute
work load for the first work-’cycle ...... Ill
xiii 5.2 Average travel speed of a pair of Shorthorn oxen for 3 consecutive
work-cycles. (average resting period between the work-cycles was 12
min. and the tractive effort was 2.1 kN) ...... 112
5.3 Effect of the drawbar pull on the travel speed and drawbar power
of a pair of oxen at the end of the first 91 meters ...... 114
5.4 Travel speed after 5 minutes and 10 minutes during consecutive
work-cycles. (tractive effort: 5 %; and average resting between each
work-cycle: 8.5 min.) ...... 115
5.5 Heart Rate at the end of work-cycle for different tractive efforts. . 116
5.6 Rate of change of the heart rate (HR) with respect to the tractive
effort based on the first work-cycle at each tractive effort ...... 116
5.7 Rate of change of the rectal temperature per unit work-cycle time
with respect to varying traction effort based on the end of the first
work-cycle for each tractive effort ...... 117
5.8 Average rate of change of the heart rate (HR) at the end of each
work-cycle for Louis while working individually and as a pair.
(Average resting: 10 minutes) ...... 118
5.9 The rate of change of the rectal temperature for Louis when
working as a pair and individually ...... 118
5.10 Body weight loss per minute of total work-cycle time with respect to
different drawbar pull ...... 119
B.l Layout of the lower part of the chassis ...... 164
xiv B.2 Layout of the upper part of thechassis ...... 165
B.3 The rear shaft...... 166
B.4 The rear shaft hub...... 167
B.5 The layout of the intermediate shaft...... 168
B.6 The layout of the final drive shaft ...... 169
B.7 Band and Brake lining layout ...... 170
B.8 The dyno-cart assembly ...... 171
B.9 Pivot bracket for the brake band ...... 172
B.10 The brake actuating power screw ...... 173
B. 11 The power screw collar ...... 174
B.12 Free body kinematics of a braked wheel ...... 176
B.13 Free body diagram of the band brake ...... 180
C. 1 The calibration curve of the force transducer excited
with 10 Volts...... 184
D. 1 An outline of the drop hitch neck yoke ...... 188
D.2 A Sketch of single neck yoke ...... 188
XV SYMBOLS
A field size, [ha]
A, area of farm field i, [ha] b implement width, [m]
tire section width, [m]
B stride length of a quadruped
Bj area of farm field i catered for by M animal pairs, [ha]
C, area of field i catered for by hand labor after M animal pairs have catered
for Bj, [ha]
Cn wheel numeric d overall tire diameter, [m]
F gross traction
Fc Froude number
G.i m total animal hours tor period m
Gt1 m total man hours for period m h tillage depth htl hip joint height of a quadruped
xvi H, theoretical field capacity, [ha/hr]
Ht. effective field capacity, [ha/hr]
Hcda effective field capacity, [days/ha]
Hr gross traction of a draft animal
HR heart rate [pulses/min] kdf Duty factor
Kh number of hand laborers required in addition to M pairs of draft animals
L draft animal hoof base m specified period eg month or weeks
M number of draft animal pairs available to the farmer.
MR Motion resistance
Na number of animals pairs required during period m
Nh number of hand laborers required during period m
N, number of tractors pa contact pressure between the brake drum and the band p, tensile stress in p,, specific soil draft, [N/m2]
PL. engine power, [kW]
P Pull
Ph average human power
P, average power of draft animal
P.„ average power per unit area
xvii Q, high tension in the brake band
o 2 low tension in the brake band
v. theoretical travel speed, [m/s]
va actual travel speed, [m/s]
Rr reaction on rear legs of a traction animal
Rt reaction on front legs of a traction animal
reliability of animals
h reliability of hand labor
rolling radius of a traction wheel
R radius of the brake band
RT rectal temperature [°C]
si wheel slip
s, step length of a quadruped
t brake lining thickness
tc critical time ( window), [days]
K number of working hours per day, [hrs/day]
T torque on the driving wheel
TE tractive efficiency
THY tractor hours per year
TO time [hrs] of operating on a particular operation
T, Tractive effort of a draft animal
animal work rates [hrs/ha] for crop j
xviii Th hand labor work rates [hrs/ha] for crop j
u tractor cost per operation
v walking speed of a draft animal
w brake lining width
xcg center of gravity of a traction animal
x(, location of harness pressure point on the traction animal
working hours per day for animals
Xh working hours per day for hand laborers
W vertical load on drive axle
Wa draft animal weight
wm working days for a specified period m (corresponds to required timeliness
of operation)
W., weight of traction animal
WT tractor weight, [kN]
Wd dynamic load on un-powered wheels
zcg center of gravity of a traction animal
zn location of harness pressure point on the traction animal
a, specific fuel consumption, [1/kW-hr]
a2 cost of fuel, [$/l]
a 3 oil consumption, [1/hr]
a4 cost of oil, [S/I] jSj ratio of annual fixed charges to initial tractor cost
xix 03 operator’s labor costs, [S/hr]
reliability of machinery
probability of a working day
Hr field efficiency n(m transmission efficiency
brake lining coefficient of friction
£ initial cost of tractor per rated power [$/kW]
X temperature and altitude factor
repair and maintenance cost percentage of initial costs e inclination of the tractive effort exerted by the draft animal
0 rap angle of the band brake
gear ratio between the rear and the brake shaft
XX CHAPTER I
INTRODUCTION
1.1 Developing Countries
There are two worlds whose difference is their comparative levels of wealth and poverty. Developing countries are in an impoverished category. There is need to transform the economic conditions and social attitudes of developing countries
in order to reduce poverty.
'Third World" is another terminology used to describe developing countries.
Wolf-Phillips (1979) indicated that this terminology was wrongly adopted.
Originally, it was meant to refer to third force, with a different political ideology.
In other words, the terminology applied to developing countries that remained outside the two power blocs. The North Atlantic community represents the first force, and Eastern Europe, China, and former Soviet Union, represent the second force. The "Third World" which consists of at least 120 countries (Kurian, 1987), is further subdivided into four groups: Organization of Petroleum Exporting
Countries (OPEC); advanced developing countries such as Brazil; middle developing countries such as Turkey; and least developed countries such as
Uganda. 2
Simpson (1987), examined 43 indices which are generally used in characterizing the differences between developing and developed countries. Some of the commonly used indices are gross national product per capita (GNP); daily calorie supply per capita (nutrition index); life expectancy; percentage population engaged in agriculture; infant mortality rate; illiteracy rate; rural population scatter; and population growth. The first three indices are lower and the last four are higher for the developing countries.
Although developing countries may be unable to feed their population securely and adequately, they are primarily agrarian societies with over half of the population living in rural areas and engaged in agricultural activities. Therefore agricultural productivity and related rural economy are very important in overall economic development processes and poverty reduction.
By the end of this century, it is estimated that the population of developing countries will be 4.9 billion (FAO, 1981). This will be approximately 78 percent of the world’s total population. Therefore, solution of the hunger problem in these highly populated developing countries will require tremendous increase in agricultural productivity based on productive technology. From the history of developed countries, increased agricultural productivity is linked directly to the transition in mechanization level. The scenario in developing countries is that mechanization transition stages which occurred elsewhere did not take place.
Increased agricultural productivity comes about by increasing output both from the land and the individual farm laborer. Technological advancement in 3 agriculture such as, high yielding varieties, soil management, plant and animal disease control, fertilizer and technological interventions do bring increased output from the land, but very little if any, increased output per worker. In order to increase output per worker, the meager human work output must be supplement ed by higher forms of energy and increased power input.
The level of food production for developing nations can not be sufficient when available power resources are inadequate. Furthermore the problem is compounded by lack of strategies for adopting the appropriate levels of mechanization. Consequently, together with a combination of other factors, there is poverty and stagnation in development. The Committee on Agriculture {Gifford,
1981) agree that mechanization is an indispensable input to rural development.
Furthermore, clearly defined strategies for agricultural mechanization are essential for increased agricultural production and efficiency.
1.2 Agricultural Mechanization
Humans can only exert limited muscle force, thus there is a need to supplement this force in order to carry out agricultural tasks with less drudgery and improved timeliness. The process by which human power is either supplement ed or replaced by other forms of power is mechanization. Typical mechanization stages can be categorized as: human; animal; and engine powered production.
Agricultural mechanization is defined as any means to increase efficiency and capacity of a farmer in performing agricultural tasks. Agricultural tasks as pointed out by Crossley and Kilgour (1983) include, field, farmstead and transport 4
operation efforts. Field tasks range from primary tillage to harvesting. Farmstead
tasks are centered around storage, processing and utilization of harvested crops.
Pingali et al. (1987) mentioned that field tasks, particularly land prepara
tion, are usually the most power-intensive. Furthermore the most power-intensive
operations are usually the first to be mechanized. Therefore initial mechanization
transitions from human power to higher forms of either animal or engine powered
mechanization should occur in land preparation.
The reasons for the need of mechanization transition are:
(i) Traditional human power is meager and insufficient for agricultural tasks.
Farming by human power alone is hard, monotonous work; consequently potential farm workers drift to urban areas for speculative and uncertain employment.
(ii) There is need to increase food production in order to feed the rapidly growing population.
(iii) Increased agricultural production could help to foster and further the develop ment of primary processing industries. The overall effect would be employment opportunities and improvement of social and economical conditions, i.e.. economic development and poverty reduction.
(iv) There is need to increase productivity and land under cultivation per person.
(v) There is a need to provide adequate power for timeliness of farming operations in order to improve crop yield. 5 1.3 History and Progress of Mechanization
The lessons learned and the historical perspective of mechanization progress in developed countries are important but direct transfer of such knowledge to developing countries often may lead to wrong solutions of critical problems. However, it is worth noting how, when, and why technological changes took place in the developed countries. Although, as pointed out by Gifford (1981), the historical pattern and pace in those countries should not be used as a formula, it can still help the developing countries in formulating appropriate strategies.
References to technological events for the era before the last three centuries are rare. Substantial records on inventions become commonplace after the onset of industrial revolution. Historical records however, show that as far back as 7500 B.C., man recognized the inability to carry out farming without use of tools. The tools then, were basically sticks and stones. Studies of paintings and drawings as far back as 6000 B.C. in ancient Egypt, show Y-sticks used in a manner similar to a hand hoe. These records indicate endeavors of early communities in mechanizing agriculture.
Anderson (1943), indicated that two thousand years later (4000 B.C), after the invention of the wheel, man began domesticating animals such as oxen and donkeys. This led to animals being used for transportation purposes. Utilization of animal power in this form led to harnessing of animal power for farm use. This was the beginning of animal power mechanization, and it was rapidly succeeded by invention of neck and horn yoke harnesses (Huntingford, 1934). 6
Between 500 B.C. and 1600 A.D., horses replaced oxen, and there were
harness modifications such as: throat and girth harness for horses and donkeys.
Later, breast strap and collar harnesses were introduced. Horse shoes were
invented for the purposes of improving endurance and reducing wear of hooves
(Green, 1966). Langdon (1986) indicated that these improvements and inventions in animal power mechanization benefitted horse traction, rather than oxen. There was no progress in oxen traction technology.
There were no rapid changes on the farm until the industrial revolution, in the middle of 19th century. After this revolution, there was a reduction in available farm labor due to creation of new and less strenuous jobs in other industries. At the same time the population growth rate was high due to medical breakthroughs in reducing infant mortality rates. Invention and development of the steam engine was quickly adopted for use as an off-the-road vehicle (a tractor). Use of these machines led to exploitation of land which before was not cultivated.
Up to this time, farmers had used their ingenuity and craftsmanship to develop and fabricate implements and machines used in mechanization. During the
19th century, off-the-farm manufacturing became a new dimension to mechaniza tion. Many manufacturing companies developed. At the beginning of this century
(1900’s), more adaptable tractors were developed. This coincided with the development of internal combustion engines. In subsequent decades, tractors suited for specific farming practices were developed, such as the row-crop tractor for inter-row crop cultivation. With the advent of rubber tires, tractors became lighter, faster, more productive and more comfortable. After the second world war,
the experiences gained from off-the-road vehicles were infused into the agricultural
sector. Thus the modern farm tractors, are the result of new technological
developments and needs of the market.
A review of the historic pace of mechanization in developed countries
reveals that population increase, reduction of rural farming population, and
technological development contribute to the type of transition in agricultural
mechanization.
The developing countries did not undergo this agricultural revolution.
Technological advances and the pressures, such as population growth and labor
scarcity due to urban migration, leading to mechanization transition were absent.
Invariably, most developing countries were colonies of countries such as Britain,
Spain, Germany, etc. Therefore, each developing country received different
mechanization stages by direct imposition. There was no internal mechanization momentum developed, as was the case in developed nations.
It is worth noting that animal power mechanization, which among other technological interventions, enhanced agricultural productivity in developed countries, was not developed with much vigor in developing countries. In Europe for example, Smith (1981) points out that many of the breeds classified as beef cattle were originally bred for traction purposes, and up to now, they are still used in some parts of Southern Europe. The developing region of Africa has very few traction animals as shown in Table 1.1 (Woytinsky and Woytinsky, 1953). When 8
the agricultural land for each region is incorporated, it can be seen that the
number of traction animals per unit area in Africa is quite small compared to other continents.
Table 1.1 Comparative numbers of traction animals in millions (Woytinsky and Woytinsky, 1953).
1928 1938 1950 North America (533)* 23.1 17.6 9.4 Asia (990) 34.6 18.8 13.7 Africa (766) 8.4 9.6 13.8 Europe (592) 29.8 26.2 20.4 South America (537) 31.8 37.6 37.6
( )* Approximate agricultural land in million hectares between 1920-1950.
1.4 Objectives of the Study
Development of Africa lies in improving the farming systems of small holders who produce the bulk of the agricultural output of the continent. The most important aspect which needs emphasis is promotion of appropriate agricultural mechanization. At present animal powered mechanization is the most suitable to the majority of the farmers. With time, animal powered mechanization will lead to transition to engine powered mechanization. The aims of this dissertation include documentation of the status of agricultural mechanization and associated technical animal mechanization problems which require research attention with specific reference to Uganda.
In this theses work, four objectives are presented as individual chapters.
Their specific aims are:
1. (i) Documentation of mechanization progress in Uganda.
(ii) Development of power requirement selection models for the two mechaniza tion levels: tractor and animal powered mechanization.
2. (i) Review the research on animal mechanization.
(ii) Establish critical engineering problems related to animal powered mechanization.
3. (i) Design and development of a mobile traction dynamometer (dyno-cart) for testing performance of traction animals.
4. Preliminary testing of traction animals using the prototype dynamometer developed.
The anticipated long term research framework will involve multi-disciplinary research programs conducted by engineers, social scientists, veterinary scientists and economists. Future work will likely include: breeding programs of animals whose endurance is commensurable with required farm tasks; nutritional and general maintenance requirements of traction animals; investigation of factors such as environmental conditions, effects of periods of work and rest upon the output of traction animals; harness designs for optimum animal performance; implement development and modification based on realistic knowledge of the draft ability of 10 traction animals; animal-operator ergonomics studies; and social and cultural educational programs. 11
List of References
Anderson A.L (1943) Introductory Animal Husbandry. MacMillan Co. NY.
Crossley, P; Kilgour.J (1983) Small Farm Mechanization for Developing Countries. John Wiley & Sons.
Gifford, R.C (1981) Agricultural Mechanization in Development: Guidelines for Strategy Formulation. Food and Agriculture Organization of United Nations, Rome, Italy.
Green C. (1966) The purpose of the early horseshoe. Antiquity, xi: 305-7.
Huntingford G.W.B (1934) Pre-historic ox-yoking. Antiquity, vii: 457.
F.A.O (1981) Agriculture: Toward 2000. Food and Agriculture Organization of United Nations, Rome, Italy.
Kurian G.T (1987) Encyclopedia of the Third World. 3 Ed. N.Y,N.Y.
Langdon J. (1986) Horses, Oxen, and Technological Innovation: The use of draft animals in english farming 1066-1500. Cambridge University Press.
Pingali,P.; Bigot,Y.; Binswanger,H.P. (1987) Agricultural Mechanization and the evolution of Farming Systems in Sub-Saharan Africa. World Bank Publication. Johns Hopkins University Press, Baltimore, MD
Simpson, E.S (1987) The Development World: An Introduction. Longmans Scientific & Technical, Wiley, NY.
Wolf-Phillips (1979) Why Third world?. Third World Quarterly I : 105-116.
Woytinsky,W.S; Woytinsky,E.S (1953) World Population and Production: Trends and Outlook. Twentieth Century Fund, Chapters 15 and 18. CHAPTER II
AGRICULTURAL MECHANIZATION IN UGANDA
2.1 Introduction
Uganda lies in the upper basin of the river Nile. With an equatorial climate, and two distinct wet seasons between March to May, and September to November, the country has immense agricultural potential. The average rainfall ranges from
635 mm in the semi arid northeast to 1650 mm in the tropical lake Victoria region.
The population estimate for Uganda in 1990 was 18.8 million (United
Nations, 1990). From Table 2.1 it can be observed that agricultural population1 is over 80 percent of the total population. Therefore research in the improvement of agricultural productivity must be targeted to this population. Simpson (1987) reported that the average annual population increase in Uganda is 2.6 percent and urban population growth rate is about 3.4 percent. Therefore, there is a need to increase food production for the growing population and for the increasing number
'Agricultural population is defined as all persons depending for their livelihood on agriculture. This comprises of those actively engaged in agriculture and their non-working dependents. Economically active population in agriculture includes all persons engaged or seeking employment in agriculture, including unpaid laborers on family farms.
12 13
of urban dwellers.
Table 2.1 Progression of total population, agricultural population, and active
agricultural population in Uganda.
Population YEAR (thousands) 1980 1985 1988 1990 Total population 13201 15477 17216 18794 Agricultural population 10678 12296 14110 15196 Active agricultural population 4380 5915 6306 6569
2.2 Objectives
Uganda, like many other African countries, derives over 50 percent of her gross domestic product (GDP) from agricultural production. The bulk of this
production is by small holders who use hand labor to perform the various farming
operations. Therefore, there is need to intensify research geared towards
improving agricultural production from these farmers.
The Committee on African Agricultural Research Capabilities (National
Academy of Sciences. 1974) noted that among the most important but least studied inputs to African agriculture is power. It then recommended that farm power, whether provided by human labor, draft animals or machines, should receive intensive investigation. Research should be undertaken in all the three 14
forms of power so that the drudgery of hand cultivation could be reduced through
development of appropriate implements that would overcome seasonal labor
bottlenecks, thus improving the timeliness of farm operations.
There are two aims accomplished in this chapter: documentation of
mechanization progress in Uganda, and development of power requirement
selection models for the tractor and animal powered mechanization levels.
The objectives will be accomplished in the following ways:
(i) Review of mechanization trends in the country using annual reports of the
Ministry of Agriculture and Forestry, annual reports of the Special
Development Section of the same Ministry, and oral interviews.
(ii) Collate data for various farm operations relevant for modelling power
requirements.
(iii) Use computer programming and optimization methods (for the tractor
powered mechanization) to model optimum power requirements.
There are three types of mechanization levels a farmer can expend: hand, animal, and engine powered mechanization. The degree of sophistication, the capacity to do work and the operating costs increase as one moves from hand to engine mechanization. The farmers’ choice is imposed by economic and social ingredients.
In Uganda, the contribution of engine powered mechanization is still small, and the adoption of anima) powered mechanization is very slow, leaving the majority of the agricultural operations to be carried out by hand power. 15 2.3 Agricultural Production in Uganda.
The country is bestowed with fertile land. This is exemplified in Figure 2.1 which shows fertilizer inputs and yield of corn for a few selected countries. Despite
low fertilizer inputs, the yield of corn in Uganda is akin to other countries which
utilize substantial fertilizer inputs. Unfortunately about 20 percent of this fertile
land is unutilized. Out of 20 million hectares of land area, an estimated 34 percent
is utilized for crop production; 28 percent is under forest and woodland; and 9 percent is used for livestock farming (F.A.O, 1990). Substantial arable fertile land is yet to be exploited.
As pointed out above, due to well distributed bi-modal annual rainfall and fertility the country has full potential for agricultural exploitation. The climate can adequately support two growing seasons. However it is imperative to use higher forms of mechanization to prepare the land in the shortest time available between harvesting and the next growing season.
There is stagnation in agricultural production as highlighted in Figure 2.2 which shows cropland size over the past seventy years for major crops. It can be seen that the size of all crops except for plantains has not increased considerably.
This probably occurs because plantain is not a power-intensive crop. Production of crops which require intensive power inputs has not increased because of a lack of adequate energy inputs other than hand labor.
Agricultural production is greatly hindered by lack of adequate power necessary for the various farming operations. Invariably hand labor is the most 16
2500 • 25
2000 -j - 20
'o'X 1 5 0 0 - ■■'5 a,
? 1000 - v
500 • 5
* * 0 Uganda Malawi Kenya Zimbabwe
Yield (kg/ha) Fertilizer (k g /h a )
Figure 2.1 Average corn yield between 1980-1990 for selected countries, and respective fertilizer utilization (F.A.O, 1980-90A and F.A.O, 1980- 90B). common power source as can be deduced from the fact that the average number of tractors in Uganda between 1980-1990 was 3,343 (F.A.O, 1980-90A) and the number of draft animals in the same period was below 600,000 (Starkey, 1988). By way of comparison in the same period Zimbabwe utilized 20,290 tractors and
800,000 draft animals.
Since independence in 1960, the main goal of the government policy in the agricultural sector has been to increase and diversify production. In three separate five year development plans, these goals have not been realized. In order for the 17
1600 t ------
o
0 Ar • T * ■ T ......
1920 1930 1940 1950 1960 1970 1980 1990 Year
Plantains H— Cotton Maize
f '■* Potatoes * Millet Cassava
Figure 2.2 Cultivated area of selected crops in Uganda, in a period of 70 years (Ministry of Agriculture & Forestry, Uganda ,1911-91).
Ugandan farmers to improve their output per unit land and output per family, they must be guaranteed the required inputs. Energy input is the most crucial and for a long time this has been assumed to be provided by tractor power through tractor hire service. Due to economic and managerial bottlenecks, this service never found widespread acceptance and it was eventually discontinued. Therefore there is a void as far as energy input is concerned. There is no explicit policy on the direction to be taken on energy inputs and the nature of that energy. As a result, the advancement of mechanization has been hampered by indecisive strategy of each type of mechanization. Animal powered mechanization was 18
gathering momentum in the early 50’s, when engine powered mechanization was
introduced. The latter has since been looked at as being substandard both by the
farmers and the researchers. The progress of either mechanization transition has
not been favorable. There is a need to readdress research efforts on mechaniza
tion strategies which will benefit the agricultural production sector.
The government is currently reinvigorating use of draft animals by small
holders. Therefore there is a need to establish mechanization needs of this target group so as to have relevant and significant extension service and education
rendered to them.
2.4 Mechanization Options
Historical perspectives in other countries indicate that use of improved methods and adoption of appropriate mechanization result in increased output both from the land and the worker. Table 2.2, from Binswanger (1984), is used to elucidate this point. In both cases there exists high and comparable agricultural output growth rates. However, the means taken to achieve the growth rates are different. 19
Table 2.2 Agricultural growth rates between 1880-1970 for USA and Japan
Japan USA Agricultural output index Year: 1880 100 100 1970 428 403 Growth rate 1.63 1.56 Agricultural output per worker (wheat units) Year 1880 1.89 13.0 1970 15.77 157.4 Growth rate % 2.38 2.81 Agricultural output Der hectare (wheat units) Year 1880 2.86 0.513 1970 10.03 0.981 Growth rate % 1.4 0.72 Agricultural land per worker fhal Year 1880 0.659 25.4 1970 1.573 160.5 Growth rate % 0.97 2.07
(Binswanger, 1984)
Agricultural land in Japan is small as exhibited in the figures for agricultural land per worker. The emphasis has been directed toward increased output from the land combined with appropriate mechanization levels. In Japan the emphasis of mechanization transition was from animal powered to walking tractors and then to conventional tractors as shown in Table 2.3. 20
Table 2.3 Mechanization transition in Japan.
Year Number of units in thousands Animal power* Walking tractors Conventional Trac tors
1880 2778 --
1900 2746 - -
1920 2724 -- 1939 2935 3 - 1951 1112 16 -
1960 618 514 - 1966 396 2725 39 1976 3183 721 ------
* Animal power figures include oxen and horses (Binswanger, 1984).
Table 2.4 Mechanization transition in USA.
Year Number of units in thousands Animal power* Steam engine Conventional tractors Tractors
1870 9589 --
1890 18635 40 - 1910 10833 72 10 1930 17612 1131 920 1950 7415 3394 1970 Insignificant Insignificant 4619 1989 4670
* Animal power figures include horses and mules (Binswanger, 1984). 21
In the USA, where there is abundant land, and yet there is labor scarcity,
engine mechanization level was used, as shown in Table 2.4.
Therefore land and labor dictate the type of mechanization transition.
Taking into account the size of Uganda and population growth rate, it is prudent
to take a mechanization transition from human to: animal powered; small tractors;
and conventional tractors in that order.
2.4.1 Human Power Mechanization
Human power is the most common power source in Uganda with nearly
80% of farmers relying on it. An adult may generate about 0,26 kW for very short
durations, but this power drops rapidly as time increases. Campbell (1990) gives
a function with respect to time, of human power as:
Power (kW) = 0.139 - 0.069 log10t (2.1)
Where
t = time in hours.
For a time period exceeding three hours, the human power output drops below
0.1 kW. The above estimation is based on daily food intake which is equivalent to about 12500 kJ per day (Grandjean,1988). This is hardly achievable in developing countries, because the average food energy supply per person per day is 8300 kJ,
(F.A.O., 1981). Tropical climatic conditions coupled with poor nutrition, significantly decrease the above projected human power. Other limitations of hand 22
power include:
(i)Timeliness of various farming operations is necessary for optimum yield. Hand
labor can not meet this criterion.
(ii) Hand hoeing may not satisfactorily control weeds and several weedings may
be required thereby losing vital time.
(iii) Due to acute labor shortages farmers tend to wastefully broadcast crops such as sorghum.
(iv) Hand labor is inadequate, monotonous and limits the farmer to small farms,
(v) Hand powered farming operations such as hoeing are less than 10% efficient.
Power per unit area cultivated is a good indicator of the degree of mechanization. An estimate of this index is:
P.H + P M + P T P = h a a c (2.2) av a where
Ph = average human power
H = number of people involved in agriculture
P., = average power of traction animals
Ma = number of traction animals
Pt, = average tractor power
N, = number of tractors
A = area cultivated
P.)V = Average power per unit area 23
Giles (1975) found a correlation between power input and crop yield of some
major crops. The data showed that in order to have optimum yields without
substantial fertilizer inputs it is necessary to have power input of at least 0.4 kW
/ha. By using equation 2.1 and the estimates of other characteristics provided
earlier, current Pa for Uganda is below 0.2 kW/ha. However, if the number of
traction animals is increased by a factor of five over a period of five years, Pa
would be equal to 0.4 kW/ha. On the other hand if the number of tractors were
increased to 10000 over the same period, Pa would be equal to only 0.27 kW/ha.
The former is quite achievable, because it is based on available animal resources.
The latter, however, is expensive and it does not raise the power input substantial
ly. Therefore animal power can greatly improve power per unit area.
2.4.2 Animal Powered Mechanization
Draft animals commonly used for agricultural production are oxen, water
buffalos, horses and mules. In Uganda only oxen are used. Animal powered
mechanization was introduced in Eastern Uganda in the early 1900’s (Ministry of
Agriculture and Forestry, 1911-1991). This area contains about 60 percent of the
Ugandan cattle population. The people in this region are willing to adopt animal
traction technology. In addition the soil and land configuration are well suited for animal power. During the second quarter of this century animal powered
mechanization grew rapidly as reflected in the number of ox-plows shown in Table
2.5. 24
Table 2.5 Estimates of the number of ox-plows in Uganda between 1925-53.
Year 1925 1925 1930 1937 1953
No. of plows 287 1840 6430 23638 44593
(Ministry of Agriculture, Uganda, Annual reports)
By the end of 1940, animal powered mechanization had spread in Eastern
Uganda in the following areas: Kumi, Serere, Soroti, Usuku, Pallisa, Amuria in
Teso District; Kaberamaido, Kumam in Lango District; Budama, Bugwere in
Torero District; Bugisu in Mbale District; Paranga, Lamogi in Gulu District; and
in a few isolated areas of the Busoga District.
In 1924, two animal plowing schools were opened in the central region, one in Masaka and another in Bulemezi, however animal powered mechanization was not adopted. There are three possible reasons for not adopting powered mechanization in this area: The people were unfamiliar with cattle handling and management. Secondly the main staple food, plantain (matooke), is a perennial crop which requires less labor intensity than annual crops. Hence, there were no conflicts in terms of power demand to cultivate land. The third reason was an abundance of available hired hand labor at that time. In southwestern Uganda, animal powered mechanization was hampered by popular belief that an ox trained 25 for plowing is useless for dowry purposes.
Today there is desire to revive the use of traction animals partly due to the following reasons: eradication of animal diseases; changes in ethnological attitudes about animal usage; shortage of farm labor; changes in cropping patterns to more labor intensive annual crops in areas which previously grew perennial crops; and tractor powered mechanization alternative involves prohibitive capital investment.
Additionally, as Starkey (1986) pointed out, animal power is appropriate and sustainable for intensifying agriculture and raising the living standards of small holders. For these reasons animal powered mechanization offers the best solution to mechanization transition, in terms of social, cultural and economic conditions.
However there are several technical constraints limiting the full exploitation of animal power. These constraints are outlined in the next chapter.
2.4.3 Engine Powered Mechanization
Engine powered mechanization was introduced in Uganda in the late 1940’s through tractor hire services. In 1963, the Government infused 100 tractors into the service, and by 1965 there were 489 tractors. In subsequent years, the service was abandoned partly due to the heavy financial burden on the Government as a result of subsidizing this service. Furthermore, timeliness of agricultural operations was difficult to perform because of timing conflicts among the users of the service.
In 1990, there were a total of 3,021 tractors (Ministry of Agriculture and Forestry,
1991), most privately owned by individuals and the others by groups of farmers. 26
Due to social and economical problems, most of the tractors are owned by very few farmers (.05 percent of the farming population), who are financially capable of meeting the high capital outlay associated with tractors. Engine powered mechanization is affordable where a farming system provides sufficient income to pay for tractor purchase, operator, maintenance, repair and depreciation. In addition to farm size and layout, inadequate technical skills and lack of well defined infrastructure creates bottlenecks such as after-sale services, generally limit the wide adoption of engine mechanization. Therefore engine mechanization at present can not be afforded by the majority of farmers.
2.4.3.1 Small Tractor Research
Pothecray (1969) defined a small tractor as any tractor with less than 15 kW, designed to carry out a range of basic farm operations which may include transportation. In addition, the tractor design features should suit skills and requirements of the targeted society. As higher powered tractors were introduced to the market, the definition which is based on power, has shifted upwards with time. Holtkamp (1990), for example describes small tractors as those smaller than
26 kW. In general, small tractors should be of simple design, intended to be used where conventional, higher powered types are not favored due to either social or economic reasons. Currently, tractors can be assorted in terms of power as low
(less than 26 kW); medium (between 27 and 75 kW); and high (above 76 kW).
Herein, small tractors will refer to those in the low power range. 27 2.4.3.2 Kabanyolo Small Tractor
Engine powered mechanization has been the subject of much experimenta tion in Uganda with very little success. In search of an appropriate tractor, Boshoff
(1972) initiated development of a small tractor which would be suitable for
Ugandan conditions. The rational was based on the fact that big powered tractors have high annual operating costs when used on small holdings (Chancellor, 1968).
The purpose was to develop and manufacture locally a tractor suitable for a Ugandan farmer in terms of capital outlay and farm size. Four successive prototype models were designed. The design was a universal type tractor powered by a 10 kW engine. Specifications and performance parameters are shown in Table
2.6. A combination of poor transmission efficiency, low engine power and light weight/poor traction contributed to insufficient performance.
Table 2.6 Kabanyolo Mark IV specifications.
P Wt. T.W W.B Tire speed Gears DB (kw) (kg) (mm) (mm) (kph) CkN) 10 680 1232 1435 8 x 24 1-14.3 6/2 3.1 & 5x16
P - Power; Wt. - weight; T.W - tread width; W.B - wheel base: DB - maximum drawbar pull. 28
Considering that Uganda lies at an altitude of over 1500 m, and has high
temperatures in many areas, power reductions in the range of 15 to 20 percent are
normal (SAE, 1983). Therefore, a 10 kW engine would produce approximately 8.5
kW due to altitude loss.
Maximum drawbar pull on a concrete surface was 3.1 kN. From the
maximum drawbar pull on concrete, expected maximum drawbar pull in the field would be approximately 2.3 kN. Heavy soils of central Uganda have an estimated specific draft of 8 N/cm, therefore for a working depth of 20 cm , the matching
plow size would have to be less than 15 cm. This would translate into a field capacity of some 18 hrs/ha which can be achieved by two pairs of traction animals.
2.4.3.3 Mono Wheel Drive Tricycle Tractor
Howson (1965), outlined the early stages of a mono wheel drive tractor for a developing country. The concept was to reduce operator fatigue by providing a ride-on configuration, on a powered tiller. The configuration out of these considerations was a tricycle tractor of single wheel drive with two forward speeds and one reverse. The specifications of this tractor are shown in Table 2.8. In addition to inadequate drawbar pull, this tractor has stability and maneuverability limitations. The lateral stability envelop is very limited and furthermore the distribution of the tractor weight between the front wheels is not even. The inability of the operator to reverse without dismounting the tractor greatly reduces the field efficiency. Both the Kabanyolo and Mono wheel tractor have not 29
developed beyond a prototype stage.
Table 2.7 Specifications of the Mono Wheel Tractor.
P Wt. T.W W.B Tire speed Gears DB (kw) (kg) (mm) (mm) (kph) (kN) 9 572 1600 1651 8 x 24 3-14 2/1 2.5 & 5x16
P - Power; Wt. - weight; T.W - tread width; W.B - wheel base; DB - maximum drawbar pull.
2.5 Mechanization Strategy
There are four options: human; animal; and engine power and a combina
tion of any of these.The choice of the type of mechanization a farmer can use
depends mainly on economics. Agricultural development in Africa has evolved
from subsistence and a shifting agricultural system to a market economy-fixed
cultivation system. Theses changes require careful planning so as to effectively
utilize the available resources at optimum cost. Best production is achieved by carrying out farming operations on a timely basis. Whether hand, animal or engine
power is used, the farmer needs to have a projection of labor or power demand throughout the season so as to plan for availability of needed labor or power. In developing countries managerial practices, selection and costing of engine power are well advanced. However in developing countries such are missing. Agricultural 30
mechanization based on engine power drains national foreign exchange unless the
crops produced are in turn exported. Therefore there is a need to estimate
optimum tractor power sizes which match the farming practices and farm sizes.
There is a need for expedient projection of labor demand so that farmers through
extension services can receive advice and rely upon advanced planning.
Consideration of the above points has prompted the formulation of two
models: TAPOR (Tractor Power Requirement) and LADAR (Labor and Draft
Animal Requirement) models. TAPOR model selects optimum tractor size by
minimizing the cost of operation while taking into account pertinent constraints.
LADAR model estimates number of laborers and/or the combination of animal
pairs which are needed to accomplish the required farming operations in a
specified period. The accuracy of these models depend upon the precision of the
input data. Therefore it is essential that reliable data be documented for accurate
predictions.
2.5.1 Tractor Power Requirement Model
One of the challenges of utilizing engine power in the agricultural sector
is the development of guidelines for the power size of tractors which should be
imported into the country. A selection of the suitable optimum tractor is dictated
by peak power requirements of a given operational task. While making the
decision, there are other variables which should be taken into account: farm size, working days, investment and operating costs. Typical conventional tillage 31
operations on engine mechanized farms in Uganda include:
(i) First and second plowing, in case a previous crop was corn, the stalks are
slashed first.
(ii) Disk harrowing once or twice, depending on the crop to be planted.
(iii) Planting
(iv) Cultivation at least two times. Hand labor is used in harvesting. Each of the
above mentioned tasks must be performed within a certain specific time.
The Tractor Power Requirement (TAPOR) model estimates the required
optimum tractor power and matching implement size. This theoretical model can
be used as a guideline in selecting a suitable tractor. It is based on deriving
theoretical expression for power required for a particular farm operation and work
rate. Theses expressions are constrained by the engine power and the critical
timeliness of farm operation, respectively. A cost function is then optimized in
order to obtain the theoretical optimum power. In conventional tillage practice,
primary tillage is the most energy demanding and therefore it is used as the basis for formulating the theoretical constraints.
Field Capacity
Timeliness for completion of agricultural tasks can not be over emphasized, and therefore it will be a pivotal parameter in sizing the appropriate mechanical power unit. In order to utilize optimization techniques, an objective function minimizing the cost of tractor operation for land preparation must be formulated.
The design variables are: engine power (Pe), tool width (b), and travel speed v;i. 32
In addition, there are several parameters which depend on location of the region.
In developing a theoretical model lef us define the following design variables:
(i) implement width, b [m]
(ii) theoretical travel speed, vt [m/s]
(iii) actual travel speed, va [m/s]
(iv) wheel slip, si
(v) Field efficiency, rjf
(vi) Tractive efficiency, TE
(vii) Transmission efficiency, rjtm
(viii) Field size, A [ha]
(ix) Critical time ( window), te [days]
(x) Number of working hours per day, t^, [hrs/day]
(xi) Theoretical field capacity, H, [ha/hr]
(xii) Effective field capacity, He [ha/hr]
(xiii) Effective field capacity, Heda [days/ha]
(xiv) p4 (N/m2) specific soil draft.
(xv) Pc (kW) engine power
(xvi) W, tractor weight (kN)
(xviii)ji = dynamic traction ratio
(xix) x = climatic and geographic factor
(xx) — probability of a working day
(xxi) P = drawbar pull (kN) 33
(xxii) Wd= dynamic load on the wheel (kN)
From the definition of slip
va=(l-sl)vt (2.3) and hence the theoretical field capacity is,
H( = 0.36bva (2.4)
Incorporating field efficiency and substituting for va:
He = 0.36 rjf b v, {1 —si) (2.5)
Utilizing t*,, the farm working hours we get:
1 = - r ^ r - (2-6)
Taking in consideration the constraint of critical land preparation for afield size of A hectares:
AHeda < tc/t„ps (2.7)
Rearranging we have:
•3 6 tctw0 sb,7 fvt(, "sl) - A
Critical time. tr
The number of working days in any period is a function of climatic condition, soil type, drainage characteristics, equipment being used, operations to be performed, and tractive devices. A probability of working days (U5) has to be incorporated to 34 get the effective time.
Field efficiency
Crossley and Kilgour (1983) point out that field efficiency is low on small farms because maneuverability and accessibility are poor due to awkwardly shaped fields.
Tillage Power
Primary tillage is the most energy demanding of all agricultural tasks, therefore it will be used as a basis for developing a mathematical model. Silt clay of Texas is similar to a typical Ugandan soil. The Agricultural Machinery Management and
Data (ASAE, 1992) specifies the specific draft ps for silt clay as:
ps - 104(7 + 0.635 va2) (2.9)
Taking into consideration the implement width and depth of tillage, the expression for drawbar pull becomes:
P - 10(7 +.635va)bh ( 2 . 10)
In addition to the soil resistance on the tillage implement, the tractor has to generate traction to overcome motion resistance of the unpowered wheels.
Liljedahl et al. (1989) give the expression for motion resistance as:
(2. 11) MR - — + 0.04 Wd where 35
Wd = the dynamic load on the unpowered wheels
Cn = the wheel numeric which is defined as
C l b d C = ____— (2.12) W,d
where
Cl = cone index
bw = tire section
d = rolling radius of the tire
The dynamic loading includes the static load on the wheel and load change due to "weight transfer". Typically for rear driven tractors the drawbar pull reduces the load on the front wheels by about 15 percent of the drawbar pull.
Therefore,
Wd = \V - 0.15P (2.13)
W here
Ws = static weight on the unpowered wheel (typically «: 0.25W,)
W, = total tractor weight
Data collated from 60 random tractor reports (Nebraska, 1961-86) showed that for tractors below 100 kW the relationship between the total weight and the power 36
from PTO is linear. Figure 2.5 shows the plot of this data, and a linear regression2
gives the following expression:
WT = °-92 Pe f " 14)
90 t
80 ■
70 ■
60
ct) 50 01 O o 3 0 :
1 o o 0 10 20 50 40 50 60 70 80 PTO power (kW)
Figure 2.3 Relationship between the tractor weight (kN) and the PTO power (kW), Data collated from Tractor Test Reports (Nebraska, 1961-86).
1 The statistical information on the regression is: No. of observations = 60 x coefficient = 0.92 it 0.04 y intercept = 2.41 37
There is a reduction of power due to high altitude and ambient tempera
tures. Let x be a factor taking into account those two aspects. Uganda is on a
plateau of about 1524 m and ambient temperatures of about 35°C during the dry
season. Hence from SAE (1983) % can be approximated to 0.802. Taking into
consideration the above equations the required engine power is:
10(7 + .635 (v, (1 - si))2) bh +( — +.04).25W, v ,(l-sl) (2.15) P. > T E r?tmX
Cost of operation
In order to utilize the above mentioned constraints, an objective function must be formulated and minimized, subject to those constraints.
The economics of owning and operating a tractor requires minimization of the operating costs. Hunt (1983) divides these costs into two categories: fixed and variable costs. Chancellor(1968) separated the variable costs into energy and time costs. Energy costs include fuel, lubricants, repair and maintenance, and deprecia tion component due to wear of the parts while in use. The depreciation costs are directly proportional to the time the tractor is in operation. Fixed costs, which are proportional to the power size of the tractor, are associated with ownership and include depreciation associated with obsolescence, interest, taxes, insurance, and shelter. Time cost is proportional to the time the tractor is in operation and includes the operator charges. 38
By considering the above mentioned different costs, and the Agricultural
Machinery Management Data (ASAE, 1992), equation 2.16 was developed.
(2.16) THY where,
u = tractor cost per operation
/?! = ratio of annual fixed charges to initial tractor cost
£ = initial cost of tractor per rated power [$/kW]
a, = specific fuel consumption (1/kW-hr)
a2 = cost of fuel ($/])
a 3 = oil consumption (1/hr)
a4 = cost of oil ($/l)
i|ri = repair and maintenance cost percentage of initial costs
= operator’s labor costs [$/hr]
THY = tractor hours per year
TO = time (hrs) of operating a particular operation
From Standard D230.4 (ASAE, 1992),a, and a3 are given as:
a , =2.64RT + 3.91 - 0.203 ^(738 RT + 173) (2.17) where RT is the ratio of equivalent PTO power required by an operation to the maximum from the PTO, and PTO equivalent is defined in equation 2.18 where DBP is the drawbar power and TE is traction efficiency which is expressed 39
DBP (2.18) 0.96TE in equation 2.19.
1 2 — +0,04 Cn (2.19) 1 - 0.75(1 - e - 3Cns,)J and a3 is given as:
( . ) a,5 = 0.00059 P e +0.00657 2 2 0
Selection of Optimum Engine size
A standard presentation of optimization problem (Reklaits et al, , 1983) is as follows.
Minimize:
P . 5 u = + a j a 2 + i|fj i) Pe + a 3 a 4 + (2.21) THY .36 b v( rj{ (1 - si)
Subject to:
-•36tt,twj040 5bvf J7 r(J - si) + AiO ( 2.22)
- P . T E , j .( 10(7..635 v,2( 1 -sl)2)bh+( i 3 +0.4).25W>,(l -slJiO (2.23) n 40
By use of work developed by Vanderplaats (1984), a program was written to minimize the above standardized problem. The coding is shown in Appendix
A.I. Table 2.8 summarizes results obtained for several farm sizes. This is based on primary tillage operation in Ugandan conditions. For optimum sizing, all operations have to be investigated and the highest power determines the tractor size and corresponding relevant implement size.
The model gives an average optimum for the cost of primary tillage per hectare as US $ 41 and seventy percent is due to fuel cost. The fuel cost is the major prohibitive factor of using engine power, unless the farmers who use engine mechanization receive government subsidy on fuel.
Table 2.8 Output of the tractor optimization model based on primary tillage operation.
Area (ha) 5 10 15 20 Power(kW) 9.3 9.9 13.3 22.0 Travel speed 2.2 - 1.2 2.4 - 1.3 3.- 1.5 4.5- 2.5 (km /hr) No. of 46 cm plows 1 - 3 1 - 3 1 -3 1 - 3
The above analytical work provides an insight on the level of optimum engine power required for farming operations. Accuracy of the model depends on the validity of the various primary parameters used. Therefore there is a need to 41
accumulate sufficient primary data outlined in Appendix A. 1, without which
reliable modelling of power demands can not be developed.
The TAPOR model estimates optimum tractor size which matches farm size
and the most energy demanding farm operation. Once the theoretical optimum
engine power is obtained, the next task is to choose a tractor which has the
matching power. The choice of tractors which are to be imported into the country
can be facilitated if the standard tests of those tractors are available. In absence
of a comprehensive test data, Figure 2.4 can be used to decide whether a
particular tractor is capable of providing required drawbar pull for given values of
PTO power, tractor speed and total tractor weight. The data plotted in this Figure
was obtained from the Nebraska Tractor Test Reports (Nebraska Tractor Tests,
1961-1986) which are based on tractive performence on concrete. Drawbar pull
predictions for other tractive surface conditions should incorporate approrite
tractive thoery and knowledge.
2.5.1.1 Tractor Selection
As mentioned in section 2.4, engine mechanization progression should move from small tractors to conventional tractors. Small tractors were used in this type
of transition by countries such as the former Federal Republic of Germany
(Holtkamp, 1990). In the 50’s, about 80 percent of the tractors used in the former
Federal Republic of Germany had rated power of less than 18kW. Later 18-25 kW »/2 P = 1.17 P W 10 pto j 2 v i r ~ 0.98 o t 0 10 20 AQ _ 40 50 60 lPplo Y ~ »
Figure 2.4 Relationship between Pull,P (kN) and speed v (kph), PTO power Pp^, (kW), and total tractor weight W, (kN). Data collated from Nebraska Tractor Tests (1961-86).
tractors took over with subsequent power transitions as shown in Table 2.9.
Uganda should not be an exception in this type of trend. Due to the farm sizes of farmers in Uganda, and the country’s social structure, engine mechanization should be invested in small tractors.
Data compiled by Holtkamp (1990), can help us to generalize levels of success in research and developmental work of small tractors.
1) Most successful small tractors are universal type, which means that this type of configuration is superior to all others forms. Next to this form is the platform type. 43
It is appealing to developing countries because of versatility as a transport vehicle.
Table 2.9 Percentage of tractor power ranges in the former Federal Republic of Germany.
No. of tractors in thousands Year Power ranges (kW) <18 19-25 26-29 30-37 38-59 60-74 75-89 > 1951 79 19 2 1956 83 13 4 1961 40 40 20 1966 10 34 56 1971 5 13 20 62 1976 3 3 18 17 49 5 3 2 1981 4 2 10 10 54 13 3 4 1986 5 1 5 10 48 28 3 5
(Holtkamp, 1990)
2) Special designed tractors intended to suite local conditions never succeeded.
Thus developing countries need to look at small tractors already in production, to decide whether they are capable of handling the work.
3) Tricycle tractors with a single driving wheel have intrinsic instability and lack sufficient traction from a single tractive device.
From these trends there are two options open for any future acquisition and/or development of small tractors by developing countries:
(i) Select appropriate small tractor, to suite the country’s need, from those which
are already being manufactured. 44
(ii) If any undertaking to manufacture a local small tractor still exists, initiative
should come from that developing country, and for success, component
manufacture and assembly should all be in that country. From past success,
it should either be universal design or platform type.
2.5.2 Labor and Draft Animal Requirement Model
Each farm operation requires different work rates which also depend on the mechanization technology being employed. As farmers make agricultural mechanization transition from hand to animal or engine mechanization, they are likely to use all three energy resources. Therefore there is a need to have labor demand projections throughout the season. A knowledge of peak demands can help the farmer in planning the size to be cultivated based on available energy resources.
Modelling labor demand requires data which are specific to the agro-zone.
F.A.O.( 1990B) defined agro-zone as an area of land within which the climates, natural resources and farming systems are similar. Three broad categories of data which need to be collated are: ecological, economic and technical. Ecological data include climatic factors, soil types and cropping pattern of the area. Economic data include cost factors and technical data include information which depends on the mechanization level being utilized. Example of such data is the draft requirement of various implements. 45
Ferguson et al. (1971) indicated there are six broad agricultural farming systems in Uganda. The range of operations typically carried out within each agricultural zone is uniform. Typically there are seven farm operations: land clearing (this is particularly so, for areas where a fallow or resting crop such as cassava in the Teso farming system, is left on the field for up to two years; first plowing; second plowing; planting; first weeding; second weeding; and harvesting.
Each of these tasks as mentioned for engine mechanization, has to be accom plished in a specified time. Typically in one season a small holder grows several crops on small plots. This model is developed along that type of farming system.
It is also assumed that each crop is in a single stand.
The following parameters are used in developing the Labor and Draft
Animal Requirement (LADAR) model:
Ai - area of farm field i (ha)
M - number of draft animal pairs available to the farmer.
B, - area of farm field i catered for by M animal pairs (ha)
C, - area of field i catered for by hand labor after M animal pairs have catered for Bj
Kh - number of hand laborers required in addition to M pairs of draft animals m - specified period eg month or weeks
T - animal work rates (hrs/ha) for crop j
ThJ - hand labor work rates (hrs/ha) for crop j
Gajn - total animal hours for period m Ghj - total man hours for period m
Na - number of animals pairs required during period m
Nh - number of hand laborers required during period m
Xa - working hours per day for animals
Xh - working hours per day for hand laborers wm - working days for a specified period m (corresponds to required timeliness of operation) ra - reliability of animals rh - reliability of hand labor
Therefore,
n G (2.24)
n (2.25)
Therefore
(2.26) N a similarly 47
Assumptions:
(i) Each field has a single crop stand.
(it) Time of operation is achieved within the specified period m. If it is to be completed over several periods> then it is assumed to be equally distributed.
Invariably a small holder has limited resources available, for example the number of draft animals which are owned or hired. In this case it is necessary to find the number of laborers who could supplement available animal power. It is assumed that equal portions of each field will be covered by M pairs of available draft animals.
Therefore,
B = ‘*‘r‘ (2.28) ' MET,.
Therefore area catered for by hand laborers is:
C1 ; = A. I - B, (2.29)
Provided C > 0 then,
£ T C K.h,m = h-— I (2.30) X h W m r h
The coding based on the above outlined modelling is presented in Appendix
A.2. An example of how this model is used is shown in Figures 2.6 through to 2.8 which display labor demand throughout the year. The example is based on an 48 assumption that a small holder has four fields cropped as shown in Table 2.9.
It can be seen that even with small plot sizes, hand labor alone requires large numbers of laborers. Approximately one pair of oxen can do a job of six adults.
Therefore there is justification in utilizing animal power for farming use.
Table 2.10 Typical plot sizes and cropping sequence of a small holder.
CROPS GROWN FIELD FARM SIZE 1ST RAINS 2ND RAINS (ha) 2.1 COTTON NOT FEASIBLE 2 1.9 MILLET SO R G H U M 3 0.8 PEANUTS COW PEAS 4 1.2 CORN SWEET POTATOES J FMAHJ jasond MONne
Figure 2.5 Number of hand laborers required throughout the season for the cropping pattern shown in Table 2.9.
J f M A M J J A S 0 N I) MONTTt
Figure 2.6 Number of oxen pairs required throughout the season for the cropping pattern shown in Table 2.9. (Note that in Jan., Jun., and Dec. hand labor is used because draft animals can not perform the required farming operations). g 5 3 HAND LABORERS 5 5 2 OXEN PAIRS
Figure 2.7 Number of hand laborers supplemented with 2 pairs of draft animals throughout the season for the cropping pattern shown in Table 2.9.
2.6 Conclusions
1. Hand powered mechanization is predominant among Ugandan farmers.
2. Hand power alone is unproductive, outdated, menial and uninteresting. It should be used as a supplementary power source to either animal or engine powered mechanization in order to exploit the rich agricultural resources of the country.
3. Experimentation with engine mechanization has to date not been successful.
Economics of either owning or hiring tractors is not feasible among small holders.
The TAPOR model shows that the cost of using an optimum tractor for primary tillage is US $ 41 per hectare. Fuel cost alone contributes over 70 percent of the total cost.
4. Where there is justification and the means of utilizing engine power, the optimum sized tractor should be used. In this way the land area of the farm size 51 is automatically taken into consideration. There is always a general and justified fear that engine mechanization, if not controlled, deprives or eliminates the opportunity for rural community employment in agricultural productions.
5. The Tractor Power Requirement model needs refinement particularly in provision of accurate parameters. This package is useful to government planners.
6. Animal mechanization should be used as a bridging gap between inadequate hand labor and expensive engine mechanization.
7. Work study of human-animal farming systems needs to be undertaken in order to update generalized parameters which were used in the Labor and Draft Animal
Model. This package when used by extension personnel can be useful to farmers for advanced labor requirement planning . Therefore primary data should be collated for each agricultural zone. Once the primary data are collated, the
LADAR model can be improved by incorporating cost analysis.
8. There is a need to incorporate engineering into animal mechanization and develop improved and more efficient methods and systems. To a large extent research results of engine mechanization are directly transferable from one region to another. However, animal mechanization is derived from a biological system and a direct transfer may not be possible. Nonetheless, in order to embark on research in this area, it is necessary to establish state of the art methods and systems utilized in other countries. 52
List of References
ASAE (1992) ASAE Standards: Standards, Engineering Practices and Data adopted by the American Society of Agricultural Engineers. 33rd Edition, ASAE, St. Joseph, Michigan.
Binswanger, H.P. (1984) Agricultural Mechanization: A Comparative Historical Perspective. World Bank Staff Working Paper No. 673.
Boshoff, W.H (1972) Development of the Ugandan Small Tractor. World Crops, 24, (5),: 238-240.
Campbell, J.K (1990) Dibble Sticks,Donkeys, and Diesels: Machines in Crop Production. International Rice Research Institute, Manila, Philippines.
Chancellor, W.J (1968) Selecting Optimum-sized Tractors for Developmental Agricultural Mechanization. Trans. ASAE (11),4, pp: 508-514.
Crossley P and Kilgour J. (1983) Small Farm Mechanization for Developing Countries. John Wiley and Sons.
F.A.O (1980-90A) FAO Yearbook: Production. F.A.O. Statistics Series, Food and Agriculture Organization of the United Nations, Rome Italy.
F.A.O (1980-90B) FAO Yearbook: Fertilizer. F.A.O. Statistics Series, Food and Agriculture Organization of the United Nations, Rome Italy.
F.A.O (1981) Agriculture: Toward 2000. F.A.O, N.Y, N.Y, (Abbreviated version of a first provisional report to thee 1979 conference of FAO).
F.A.O. (1990A) FAO Yearbook: Production. F.A.O. Statistics Series, Food and Agriculture Organization of the United Nations, Rome Italy.
F.A.O. (1990B) Agricultural Engineering in Development: Selection of Mechaniza tion Inputs. F.A.O. Agricultural Service Bulletin 84, Food and Agriculture Organization of the United Nations, Rome, Italy.
Ferguson,L.C.; Baver,L.D.; Scott,E.G.; Way,W.A. (1971) Agricultural Research in Uganda: A Survey. Evaluation, and Recommendations. USAID Report (Contact AID/afr 785). 53
Giles, G.W (1975) The reorientation of Agricultural Mechanization for the Development Countries. FAO/OCED Report of Expert panel (FAO,- Rome).
Grandjean, E (1988) Fitting Task to the Man. 4 th Ed., Taylor & Francis Ltd. London.
Holtkamp, R. (1990) Small Four Wheel tractors for tropics and subtropics: their role in agriculture and industrial development. GTZ.
Howson, D.F (1965) Evaluation of Basic Tractor for Developing Countries. World Crops, 17,(1): 81-87.
Hunt D. (1983) Farm Power and Machinery Management. 8 th Edition, Ames, Iowa State University Press.
Liljedahl,J.B; Turnquist, P.K; Smith,D.W; Hoki,M. (1989) Tractors and Their Power Units
Ministry of Agriculture & Forestry, Uganda (1911-91) Annual Agriculture reports. Ministry Headquarters, Entebbe, Uganda.
Ministry of Agriculture & Forestry, Uganda (1991) Tractor Census.
National Academy of Sciences (1974) African Agricultural Research Capabilities. National Academy of Sciences, Washington.
Nebraska Tractor Tests (1961-86) Tractor Test Reports. University of Nebraska Agricultural Experimental Station.
Pothecray, B. P (1969) The Small Tractor in Developing Countries. World Crops, 21,(3): 225-226.
Reklaits,G.V;Ravindran,A;Ragsdell,K.M (1983) Engineering Optimization: Methods and Application. John Wiley and Sons.
SAE (1983) Engine Power Test Code, SAEJ1349. Society of Automotive Engineers.
Serunjogi,L.K. (1987) Breeding for Subsistence Agriculture. University of Cambridge, Darwin College. 54
Simpson, E.S (1987) The Development World. An introduction. Longmans Scientific & Technical.
Starkey,P. (1986) Draft Animal Power in Africa: Priorities for development, research and liaison. Networking paper (14) :l-40, Farming Systems Support Project, University of Florida, Gainesville.
Starkey,P. (1988) Animal Traction Directory: Africa. GTZ publication.
United Nations (1990) Demographic Yearbook. United Nations, N.Y.
Vanderplaats, G.N (1984) ADS-A FORTRAN Program for Automated Design Synthesis. NASA, N85-10684. CHAPTER III
ANIMAL POWERED MECHANIZATION
3.1 Introduction
The data by Kemp (1987) pertaining to total agricultural draft animal and tractor power usage in developing countries indicated there is an equal relative contribution from both sources. This situation is unlikely to change appreciably due to constraints associated with motorized mechanization. Therefore animal powered mechanization will continue to be utilized and intensified in areas where such technology has not been fully adopted. The importance of draft animals in developing countries is extensively discussed by Muzinger (1982). There are four major reasons advanced for their promotion: (i) acute shortage of capital on individual farms and within the national economy, (ii) fairly small farm holdings,
(iii) low technical skills among the farmers, and (iv) lack of infrastructure essential for motorized mechanization.
A substantial portion of GNP for most developing countries, particularly in
Africa, is derived from agricultural production. Draft animal power would be a catalyst in increasing agricultural productivity. Unfortunately draft animal
55 56 technology is new to most African countries.
3.2 Objectives
The knowledge of draft animals has been subjective and regarded to be
inferior by technocrats. However, if significant use is to be made of this form of
mechanization to enhance agricultural development, there is a need to study and
understand draft animal systems. Four uajor disciplines are relatively important
for draft animal research: economics, engineering, agronomy and veterinary
medicine
There appears to be inadequate engineering research pertaining to draft animals. It should be pointed out that unlike motorized mechanization, where research findings can be generalized, animal research is rather site oriented.
Therefore there is a need to initiate and intensify research on draft animals locally.
A thorough understanding of the characteristic performance of draft animals will lead to more efficient use.
The objectives of this chapter are twofold: First, to review the extent of animal mechanization research. (This will be done by reviewing research in the area of draft animal technology). Secondly to establish critical engineering problems. It is necessary to establish engineering problems associated with draft animal technology that prohibit wide spread adoption of draft animal technology in U ganda. 57 3.3 Traction Dynamics of Draft Animals
There have been enormous advances in the knowledge of traction
mechanics of tractors. In return this has led to improved and more efficient tractor
designs. Unfortunately advanced knowledge and understanding of the traction
dynamics of draft animals is very limited. It is imperative to explore the manner
in which draft animals propel themselves and generate traction in order to
understand the whole traction animal picture.
3.3.1 Motion Mechanics of Draft Animals
In order to explore traction dynamics of draft animals, the following terminology adapted from Alexander and Goldspink (1977) should be defined:
(i) Stride, a complete cycle of leg movements.
(ii) Stride length (B), distance traveled in a stride.
(iii)Step length (SJ, distance moved by the center of mass of the animal while a particular hoof is on the ground.
(iii)Duty factor (k^), fraction of the cycle time for which a particular hoof is on the ground. (The ratio of step to stride length is approximately equal to the duty factor).
Muybridge (1957) documented different patterns of leg movements of various quadrupeds. From this work Alexander and Goldspink (1977) concluded that the sequence of leg movement associated with stability is as shown in Figure
3.1. 58
Quadruped animals possess four distinct patterns of leg movement or gaits.
These patterns depend on whether the animal is walking, trotting, cantering or
galloping. At low travel speeds quadruped animals maintain perpetual equilibrium
as they walk by moving one leg at a time. Thus at least three legs are on the
ground at any one time. This gait ensures that the center of gravity of the animal
always falls within the stability triangle which is illustrated in Figure 3.1.
= \ S A \ 1 N .1 ✓ Kl ; \ \J y B •' i. I II III IV I
Figure 3.1 Top view of steady state stride cycles of an oxen as it walks, (the arrow indicates a foot which is about to be lifted, the dotted lines mark the stability triangle, and B is the stride length).
Draft animals employ all four feet for the purpose of maintaining stability
and generating adequate traction to handle propulsion and harness loads. The hind
legs are responsible for generating traction. From Figure 3.1 it can be concluded, by considering traction dynamics and stability of the animal, maximum traction will be generated when both hind legs are on the ground and one of them is about to 59 move. In other words, referring to Figure 3.1, traction will be generated in the second and fourth cycle of Figure 3.1. As pointed out previously traction in draft animals is invariably provided by the hind legs. Therefore when the oxen is hitched to an implement, it will start motion by either left or right rear leg, depending on its current stance. Using Figure 3.1 as an illustration, it can be seen that half a stride is moved in two cycles and during this interval gross traction H,. is generated.
Therefore tractive effort generated by animals is intermittent and the time delay between the next thrust depends on the duty factor.
Alexander (1983) measured forces exerted by animals while walking. A sketch of these forces on each of the four legs is shown in Figure 3.2. As the animal generates traction, the legs experience alternating force magnitude.
Force Front left kg
Front right leg ..J
Hear left kg I
Kan right kg
Stride cyck*
Figure 3.2 Sketch of forces exerted on the ground in one stride by each leg of a quadruped while walking. 60
Alexander and Goldspink (1977) by use of dimensional analysis developed an empirical formula (equation 3.1) for travel speed of animals.
(3.1) where ho is the hip height and Fe the Froude number is defined as:
With a knowledge of animal dimension I\, and Fc associated with stability, the theoretical speed can be obtained. From the work of Alexander and Goldspink
(1977), minimum duty factor (Sl/B) which ensures stability while quadrupeds are walking is 0.75. Assuming that the step length (SjJ is approximately equal to hip joint height (ho), the following can be deduced from the definition of duty factor.
v < 0.4^(gho) (3.3)
Equation 3.3 gives the maximum travel speed of a walking animal.
3.3.2 Traction Mechanics of Draft Animals
At the time when the rear left leg is about to leave the ground, it can be deduced from Figure 3.2 that the left front leg and the rear right legs will carry most of the reaction while the right front leg provides instant stability. Assuming neck yoking, let Te be the tractive effort and let R,. and Rf be the reactions on the 61
right posterior and left anterior legs respectively at the instant of generating
traction. Let the coordinates of the center of gravity and harnessing point,
respectively, be
animal, L the hoof base.
Top Virw
4 1
Zo
Xo L Figure 3.3 Sketch of a quadruped about to generate tractive effort Te. (rear left hoof (4) is about to move).
Resolving forces vertically and horizontally and taking moments we have:
Rr = + -^?Tec o s 0 - ^?Te s i n 0 (3-4)
Rf = ( 1 rXca) Wa --f? Tceos8 + ( Tesin6 (3.5) L L L
Te c o s 0 = fxgt Rr (3 .6 ) where jigt is the gross traction ratio. 62
Substituting equation 3.4 into 3.6 the expression for Te becomes:
T „ (3-7) * (L-zD*Jgt)c°s8 ♦ Mjt'tosine
Equation 3.7 gives a theoretical tractive effort. It should be noted that the tractive
effort exerted by an animal over a prolonged duration is much smaller. As far as
the animal is concerned, it would prefer to exert minimum pull. For a given type
of draft animal and tractive surface, the only parameter which would vary in
equation 3.7 is 0. Equation 3.8 gives an expression for the theoretical inclination
of the line of pull which would correspond to theoretical optimum pull as far as
the animal is concerned.
0o = arctan (3.8)
'"•I
With the knowledge of the characteristics of the hoof-soil surface and animal dimensions, the optimum angle can be obtained. Ramiah et al. (1956) and
Kebede and Pathak (1987) suggested this angle to be between 15° and 20°.
Figure 3.4 shows the effect of the parameters of equation 3.8 on the magnitude of the optimum inclination. When the hitch point on the animal is less than the hoof base, 0O is small. This is not practical in most cases because it would 63 require the implement hitch point to be quite far away from the rear hooves, thus restraining maneuverability in small fields. When is higher than L, 0O is high which is desirable for two reasons:
(i) the implement can be hitched quite close to the rear of the animal, (ii)the scapula bone (shown dotted in Figure 3.3) of the thoracic limb slants at an angle greater than 10P. It would be desirable to have the line of pull perpendicular to this bone. However it should be noted that a large 0 translates into a high vertical load on the neck of the animal which accelerates fatigue.
50 7 45 -j
"a 5 \
Zo/L
Gross Traction ratio ■ .25 — .50 .6 5 -B - .75
Figure 3.4 Variation of the optimum inclination of the line of pull with respect to the indicated parameters. (xJL is assumed to equal to 0.2). 64 3.4 Traction Animal System
In order for animal mechanization to be effective and useful to the farmer, research and education on the technical problems related to this technology should be strengthened.
Before the technology of using traction animals can be taken to the farmers, there is a need for a technical data bank. Technical information required includes the following: endurable tractive effort exhibited by the types of animals used; specific draft requirement of soils for various tillage operations (both of these are particularly important in designing or modifying implements which match the ability of the animals); field capacities for different tillage operations; and effects of different types of harnesses and implement hitching on the performance characteristics of traction animals under varying tractive efforts.
In most developing countries where draft animal technology is not fully adopted, there is a lack of a full range of traction animal implements. Therefore, there is a need to review present and past animal traction implements used elsewhere for adaptive design or modification to suit local conditions.
Key areas which need engineering research can be identified through careful analysis of the draft animal system. There are five broad factors which affect the performance of the draft animals, namely: B.M.E (bio-data, maintenance and environment), some of the aspects included in bio-data are animal species, age, size and training; maintenance includes nutrition, work-cycle, health care etc.; and environment includes vectors, ambient temperatures etc. 65 The other four factors are, operator, farm task, implement, and harness
(including hitching). In addition some of these factors interact within one another as shown by the dotted line Figure 3.5. For any system, it is always desirable to operate it efficiently. This is done by identifying and minimizing losses.
Each of these factors and their interactions need to be investigated in search for designs and management procedures which render optimum draft animal system efficiency. Magnitude of sustainable tractive effort exerted and stress sustained by the draft animal is dependant on the harness type. It is desirable also to convert in-so-far as possible all the tractive effort into drawbar pull. This is affected by the hitching methods.
3.4.1 Traction Animal Instrumentation
In order to study the above outlined factors which influence characteristic performance of the draft animal, there is need to have instruments and equipment which can be used to measure the various independent variables.
Unlike internal combustion engines, which generally provide steady state power that is independent of time, animal power is inversely proportional to time, similar to human power. Therefore it is necessary to indicate the time elapsed at which a certain power level is expended. Beyond a certain time, the power level becomes rather constant, and at this stage the animal is starting to show signs of exhaustion. It would be better not to load animals beyond this point. Humans can expend power even when exhausted only due to some psychological desires such 66
B.M.E Soil A, Task Operation
ANIMAL HARNESS IMPLEMENT
Biological loti Tractir* loti Figure 3.5 Schematic outline of traction animal system
as the need to finish or the desire exhibited by long distance athletes. For animals, there are no such psychological desires and once they are overloaded they just stop working.
Various mechanical and physiological variables need to be measured in order to assess and compare the performance of draft animals. Some of those variables are: tractive effort, travel speed, power, heart and respiration rate, and body temperature. Macmillan (1985) outlined some of the mechanical variables, and Kemp (1985) discussed relevant physiological variables, including possible methods of monitoring them. Any loading system used to test or document traction animal performance should provide variable load in order to fully explore animal performance. 67
3.4.2 Traction Animal Research
The purpose of the following cited work is to indicate the extent of research
on draft animals and to reflect on the reasons why such work was carried out. In
doing so, it will help in identifying the general research work. Most research work
has pertained to draft animal performance characteristics and harnessing
efficiency. Devadattam and Maurya (1978) investigated the characteristic
performance of the Indian Hariana bullocks widely used in northern India. A pair of bullocks was tested by allowing them to pull a loading cart with varying tractive effort. Variables which were measured included: travel speed, tractive effort, time, heart rate, and body temperature. The investigation was prompted by a wide range of tractive effort values quoted by previous researchers. The significance of this work is that it indicates the necessity to test the endurance performance of each type of draft animal. Generalization of the characteristic performance is not acceptable.
Endurance performance experiments on the Indian Hallikar bullocks were carried out at the International Crop Research Institute for Semi* Arid Tropics
(ICR IS AT, 1980). Sustainable tractive effort was measured for neck yoke paired animals. Travel speed was also measured. Four different weights were put on a sled, and the animals were allowed to pull each load for six hours or until they were tired. The variables measured were: time, tractive effort and power. The 6 8 quest for this work was to obtain knowledge required for designing draft animal equipment and implements.
Mathews (1987) investigated power output characteristics of female Filipino
Carabaos buffalo crossbreeds. Tractive effort exerted by the animals while pulling a loaded sled for a specified length of time was monitored at equal intervals. The loaded sled was used to simulate plowing and harrowing. This research work is an example of multi-disciplinary research program on draft animals. Theses animals were initially bred for the purpose of producing meat and milk. However due to the tradition of the farmers using the local Carabaos as draft animals, there was a need to investigate endurance performance of the new breed while they are used as draft animals.
Kebede and Pathak (1987) studied performance characteristics of Ethiopian draft oxen while they were exerting tractive effort varying up to 25 percent of their body weight. An oxen pair pulled a loading cart while speed, power and tractive effort were being measured. The work was prompted by the general concept that draft animals sustain drawbar pull of 10 percent of their body weight. However it was discovered that the draft requirement of the local draft animal plow exceeded this popular belief. Hence work was initiated to establish the performance characteristics over a wide spectrum of tractive effort.
Vaugh (1945) reported work which was carried out in India, on different types of harnesses (historically as Starkey (1989) points out, harnesses for bovines are referred to as yokes and for equines as collars). Double and single neck yokes 69
of different designs were tested. The animals were allowed to exert the maximum
tractive effort by operating a stationary dynamometer. The work was part of a
broad breeding program of draft animals in India. The effect of body conformation and harness designs on the sustainable pull the animals could endure was
undertaken.
Varshney et al. (1982) evaluated the effect of different harness designs on the performance of draft animals of northern India. Variable loads were applied through the resistance offered by a stationary dynamometer. A pair of bullocks with a particular harness was allowed to pull a particular load. Variables measured included tractive effort, temperature, pulse, respiration rate and travel speed.
Efficient harness design was the main objective of carrying out this work. Similar work was done by Barton (1985) who investigated effect of collar versus yoke harnesses on the performance of Ankole bullocks in Burundi. Several pairs were tested while plowing.
Kivikko and Roosenberg (1987) compared the effectiveness of different types of harnesses in efficiently harnessing power from draft animals. Three variables measured were: harness surface contact area, tractive effort and animal comfort (chafing, willingness to pull, and indication of awkward gait). Loading was via a sled, loaded differently for each run. They concluded there was not much difference in performance, when using either type of harness. Similar work was reported by Kivikko (1987) who investigated the effect of harness surface area on traction effort and animal comfort while pulling a sledge. 70
Hussain et al. (1980) carried out similar work to that of Varshney et al.
(1982), but in Bangladesh. Three types of harnesses were developed, tested and then compared with two traditional harnesses. The experimental work was carried out using an implement hitched to a pair of oxen. Variables measured were time, tractive effort and power.
A general pattern evolves from this reported research. Engineering research on draft animals is prompted by lack of adequate knowledge on the performance of the draft animal power unit. Furthermore optimum equipment and implement design for draft animals can only be achieved through a thorough knowledge of the characteristics of the animals. Various research work reported from other regions can be used in identifying the general research areas which are then integrated into local Ugandan concerns so that they can be prioritized.
3.5 Technical Problems of Animal Mechanization in Uganda
The Government of Uganda has formed a national research body, NARO
(National Agricultural Research Organization), which is to be responsible for developing, implementing, and coordinating a research and extension plan in support of all agricultural production. There will be several research institutions including one for agricultural mechanization. Therefore the future of agricultural engineering research is promising. Research needs of animal mechanization in particular range from collating basic data on draft animals to adaptive design of ox-implements to suit local breeds and needs. 71
In order to educate, demonstrate and provide extension services to farmers
concerning animal powered mechanization, there is a need to collate data
concerning performance characteristics of traction animals. Information required
includes endurable tractive effort of the animals used; field capacities for different
tillage operations; optimum harness/implement hitching design; and optimum
implement design.
Draft animal technology lacks engineering expertise, because it has not
been a "glamorous" field of study to merit time and effort of engineers trained in
modern technologies. There is a need for engineers to get involved in this
appropriate technology.
There is lack of a complete range of traction animal implements. Thus there is need to review antique implements of developed countries for adaptive design or modification to suit local conditions. Examples of operations for which implements are needed are: primary and secondary tillage; land forming; planting, weeding and harvesting. Figure 3.5 can be used in identifying major areas which need research attention.
Characteristic performance of draft animals
Human ergonomics studies have enhanced performance of athletes, and it is quite possible that similar studies on draft animals can lead to full exploitation of animal power for agricultural production. The purpose of draft animal performance studies would be to ascertain optimum working conditions. The following need to be investigated: 72
(i) Standard methodology of evaluating performance of animals.
(ii) Development of equipment for testing animals.
(iii)Optimum work-rest -cycle performance studies.
(iv) Effect of the environment on draft animal performance.
(v) Effect of continuous loading on the health of the animals.
(vi) Field work studies to collate information such as field capacity for different task operations.
(vii)Nutritional requirement for optimum performance. The issue of animal nutrition is significant since the land area of Uganda is small compared to potential agricultural population.
Implement and adaptive design of harnesses and hitches
There is a need to survey existing harness types used by different localities and assess their performance. There are harness types for oxen which were used successfully elsewhere particularly in North America and Europe. Design concepts from these harnesses could be incorporated in local types for adaptive design. The purpose of this type of research would be investigation of local harnesses on the performance of draft animals and their improvement for enhancing animal performance within the economic feasibility of the farmers.
Use of draft animals will lead to larger farm fields than normally managed by hand labor, therefore there will be a need to mechanize operations other than plowing. Inevitably in some operations this might require more than two animals.
Thus there is a need to investigate tandem hitching of animals for optimum 73
performance.
Improved and adaptive design of ox-implements and equipment
Implements as well as harnesses ought to be adapted to match local animal breeds and farming systems. Surveys similar to those outlined for harnesses need be carried out. In addition close attention must be paid to farming systems of the region so that the adapted implements suit the needs of the farmers of the region.
There are at least seven categories of on-farm implements and equipment which need adaptation, namely: plows, cultivators, harrows, land forming (levelling) equipment, seeding and planting equipment, and selected harvesting equipment.
Proper matching of implements to the power source, be it a tractor or animal, requires knowledge of the resistance of the soil for different task operations. Therefore investigation of specific draft of various ox-implements should be undertaken.
Ergonomic studies of draft animals and operator
Work studies should be carried out to find suitable arrangement and conditions for various task operations. Findings of these studies would help to improve the efficiency of operation of both the operator and the animals.
3.6 Conclusions
A review of problems of animal mechanization outlined in section 3.5 reveal that all research work which is being suggested for investigation requires animal 74 testing. Research on most of the above mentioned major areas requires long term study. Due to time limitations the contribution of the work presented here will be directed towards the development of equipment for testing animals. Literature of draft animal research outlined earlier indicated that there is great variability and considerable inconsistencies for testing the animals.
In order to validate and make fair comparisons of research findings in
Uganda, there is a need to have standard equipment and procedures for testing animals. Therefore there is a need to develop a dynamometer which can be used in testing traction animals. 75
List of References
Alexander R., McN. (1983) Animal Mechanics. Blackwell Scientific Publishers, Oxford.
Alexander R., McN. and Goldspink, G. (1977) Mechanics and Energetics of Animal Locomotion. John Wiley & Sons.
Barton, D. (1985) Yokes or collars? Harnessing techniques for draft cattle. Draft Animal News, Center for Tropical Veterinary Medicine, Edinburgh, (4): 1-5.
Devadattam, D.S.K. and Maurya,N.L. (1978) Draftability of Hariana Bullocks. Indian Journal of Dairy Science, 31, (2): 120-127.
Hussain,A.,M.,M.; Hossain,Md.,M,; Hussain,Md,,D. (1980) Design and Develop ment of Neck Harness for Cattle in Bangladesh. Agricultural Mechanization in Asia, Africa and Latin America, U., (l):85-89.
ICRISAT (1980) Annual Report. International Crops Research Institute for the Semi-Arid Tropics, India, pp 192-194.
Kebede, A. and Pathak, B.S. (1987) Draft characteristics of Ethiopian oxen. Draft Animal News, Center for Tropical Veterinary Medicine, Edinburgh, (8): 12- 13.
Kemp, D.C. (1985) Performance measurement for ox and implement combina tion. Proceedings Silver Jubilee Convention, Indian Society of Agricultural Engineers, 29-31 October, 1:16-21.
Kemp,D.C. (1987) Draft Animal Power: Some Recent and Current Development. World Animal Review 63, : 7-14.
Kivikko, R. (1987) Preliminary Tests for single animal harness systems. Tillers report news letter, Tillers International, Kalamazoo, 7, (1 ):8-9.
Kivikko, R. and Roosenberg, R.(1987) Designing Ox Yokes for More Effective Power. Tillers Report, 7, (1): 5*7.
Macmillan, R.H. (1985) Engineering problems in the measurement of draft animal performance. Proceeding, Australian Center for International Agricultural 76
Research, 10-16 July, 1985, pp 149-155.
Mathews, M.D.P. (1987) Measuring draft animal power of carabaos crossed with exotic buffaloes. World Animal Review, 63:15-19.
Muybridge, E. (1957) Animals in Motion. Dover Publication Inc., NY.
Muzinger,P. (1982) Animal Traction in Africa. GTZ Publication, Eschborn, Germany.
Ramiah,R.V.; Chartterjee,G.D.; Mukheijee,T.S. (1956) Hitch your moldboard plow right. Indian Farming 6, (4): 28-30.
Starkey, P. (1989) Harnessing and Implements for Animal Traction. GTZ Publication, Veiweg, Germany.
Varshney, B.P.; Kumar, A.; Mishra, T.N.; Singh, R.P. (1982) Performance of Harness used for draft animals. Agricultural Mechanization in Asia, 3,(13):15-19.
Vaugh, M. (1945) Report on a detailed study of methods of yoking bullocks for agricultural work. Indian Journal of Veterinary Science 15, (3): 186-198. CHAPTER IV
DEVELOPMENT OF A TRACTION ANIMAL DYNAMOMETER
4.1 Introduction
If draft animal power is to be harnessed and efficiently utilized in agricultural production in Uganda, it is important to document characteristic performance of draft animals over a wide range of operating conditions. Therefore it is necessary to test different types of animals used by different communities. One of the purposes of testing the animals is to gain knowledge of the performance of the animals with respect to the loads imposed on them and the effect of the environment. Secondly the knowledge acquired from the tests will facilitate design of implements and equipment which match the power of the draft animals.
Subsequent follow up research includes priorities outlined in section 1.4.
4.2 Objectives
In order to test the draft animals it is necessary to develop a dynamometer.
The specific aim of the current objectives is to design and develop a mobile traction dynamometer system for testing performance of traction animals.
77 78
The system will consist of: a loading cart (dyno-cart) which will simulate a
wide range of drawbar pull, and instruments for measuring mechanical and
physiological parameters. The simple, low-tech system will be used to promote and
enhance additional research and development toward the long term goal.
Furthermore it will serve as a basis for educational and research programs in the
Agricultural Engineering Department at Makerere University.
4.3 Performance Parameters
Macmillan (1985) pointed out that a traction animal dynamometer should simulate the draft arising from common agricultural operations. Furthermore it should provide variable load in order to explore a wide range of animal performance spectrum.
Performance characteristics of agricultural tractors are well known, and standard tests are well established and outlined in ASAE (1992). However, performance characteristics of traction animals are to a large extent subjective and intuitive. There are two broad aspects of traction animal tests which should be considered. They are physiological and tractive power tests.
In physiological response tests, the animal should be loaded to different sustained tractive efforts while measuring physiological response. These responses which include breathing rate; heart rate; and body temperature rise, are indicators of stress which the animal experiences while exerting tractive effort. 79
Tractive power tests should evaluate performance of the draft animal while
it exerts varying tractive effort (pull exerted by the animal) over given speeds over
extended periods of time. The purpose of varying tractive effort tests would be to
investigate the response of the draft animals to sustained exertion. It is widely
indicated, though not substantiated with evidence (Hopfen (1969), Goe and
McDowell (1980), Smith (1981), FAO (1990), FAO (1972)), that traction animals
can exert sustained tractive effort of over 10 but below 25 percent of their body
weight. The characteristics associated with this spectrum of tractive efforts are not well documented. Therefore it is necessary to investigate the performance
characteristics of draft animals over this spectrum.
Knowledge of physiological responses and mechanical outputs such as
power, speed, and work rate at different tractive efforts can be used to predict optimum performance of traction animals and provide insight into the most suitable managerial procedures.
4.4 Tractive Loading Devices
Figure 4.1 shows an outline of three broad categories of tractive loading: natural walking and working; active treadmills; and passive treadmills. In natural walking and working the animal is allowed to work in a manner corresponding, or similar, to field work. Most common types are where the animal walks in a straight line. The simplest way is to let the animal pull a field implement or piece of tillage equipment in the field while parameters are being measured. Barton (1985), 80
Hussain et al. (1980), and Kemp (1987), Sims and Ramirez (1989) are some of the researchers who have used this method. Tractive effort by this method is quite variable and it is neither held constant nor reproduced.
Natural Walking Natural Walking Simulated Walking CATEGORY: A Working A Simalatmi Working A Working
OPTIONS: I Straight Line Circular Path _j_ ___ _ ; | LOADING Loading‘ TilSled Wihth Tillage J Dead DEVICE Cart i Im plem ent „ . D ea d I | I "“w" W right I I_____J I 1
PRINCIPLE Anti-TractNe . Gravitational Resistance OF LOADING:
Figure 4.1 Some options of loading draft animals for the purpose of testing their performance.
Mukherjee et al. (1961), ICRISAT (1979-80), Mathews (1987), and Kivikko
(1987) loaded the animals by use of a sledge. Tractive effort was varied by use of different weights on the sledge. Tractive effort requirements for pulling the sledge varied with soil to sledge contact friction. In addition to having similar disadvantages as those mentioned above the system requires a substantial number of dead weights (ballast) in order to simulate a wide range of tractive loading.
A stationary winch and drum was used by Vaugh (1945) and Varshney et al. (1982). Variation of tractive effort is accomplished by a frictional brake drum.
In addition to being immobile, this method is limited to short distances and short 81
duration tests.
Devadattam (1977) and Kebede et al. (1987) used loading cart systems. The
former varied tractive effort by throttling a hydraulic pump which was driven by
the ground wheels of the cart. The latter used hydraulic activated brakes to vary
tractive effort.
The other two categories of tractive loading are passive and active
treadmills. With passive treadmills, like one used by Brody (1945), the animal
walks naturally on either artificial or natural surface, while working under
simulated tractive effort. The active treadmills are driven by external power sources and they simulate both the working and walking functions of the animal.
The loading cart appears to offer the most acceptable approach for controlling the load and providing systematic testing of animal performance in a natural environment. It is considered to be most desirable because it can test multiple animal hitching systems; the animals walk, work and are loaded naturally; the system is self powered and simple to fabricate; and it is possible to control and attain a wide load range.
4.5 Animal Physiological Parameters
Although some of the work reported in this section refers to horses and humans, some similarities can be drawn for oxen.
Engelhart (1977) indicated that heart rate in horses may be as low as 30 beats per minute and during heavy work the rate may be as high as 240. Thus 82
heart rate can be used to assess how hard the animals are working. Engelhart
(1977) further pointed out that breathing rate is proportional to heart rate.
Therefore either heart rate or breathing rate can be used to measure physiological
performance in animals.
Under work load, muscles generate a considerable amount of heat which
causes the body temperature to rise. Wyndham et al. (1965) stated that in man,
work should be considered to be easy when the rectal temperature is 38°C and
excessive when the rectal temperature exceeds 39.2°C, Between these two limits,
the work is graded as increasingly difficult. Table 4.1 shows work rating based on
theses physiological responses in humans (Grandjean, 1988). Engelhart (1977)
reported results of an experiment on horses where the temperature rose by 2°C
from 37.9°C while the horses were running. Therefore heart rate and body
temperature are physiological responses which are good indicators of work stress
in animals. It is imperative that equivalent responses in oxen be investigated.
There are three cited methods of determining the heart rate of animals:
hand method, stethoscope, and electrocardiogram. Devadattam et al. (1978)
determined heart rate of oxen by palpation of the artery on the under part of the
animal tail. Cardinet et al. (1963) estimated heart heat of horses by use of stethoscope to auscultate the thorax before and after the task, while Mukherjee et al. (1961) used a similar method for oxen. Holmes et al. (1966) described a method of monitoring the heart beat of a horse. Essentially the same method can be used in bovines. 83
Table 4.1 Respiration, temperature and heart rate as indicators of work load in humans.
Work load Oxygen Rectal temp. H eart rate rating Consumption TO (Pulses/m in.) (1/min) Very low .25 * 0.3 37.5 6 0 - 70 Low 0.5 - 1.0 37.5 75 - 100 M oderate 1.0 - 1.5 37.5 - 38.0 100 - 125 High 1.5 - 2.0 38.0 - 38.5 125 - 150 Very High 2.0 - 2.5 38.5 - 39.0 150 - 175 Extremely high 2.4 - 4.0 over 39.0 over 175
(Grandjean, 1988)
This method of sensing the heart beat is based on the electric field created
by the heart. Potential difference of the field is measured, which requires at least
two different sensing locations on the animal. Banister et al. (1968) reported use
of a radiotelemetry system for detecting heart beat of horses while they were
running. The system consisted of two electrodes securely adhered to the skin of the animal in the desired position, a transmitter, antenna, receiver, and a chart
recorder. Hinchcliff and McKeever (1990) measured heart rate of horses on a treadmill using electrocardiography, which is similar to the telemetry method used by Banister et al. (1968) except that the signal is channeled to the output device without need of a transmitter and receiver configuration. Kuhlmann et al. (1985) studied physiological, stresses in calves by using an electrocardiogram to determine the heart rate. Two electrodes were held in place on the animal in two locations. 84
Kemp (1985) on the other hand used infra-red light source to sense blood flow
through the ear. A method which measures the heart rate on a continuous basis
is most desirable.
Invariably rectal temperature is used to indicate body temperature.
Devadattam et al. (1978), Varshney et al. (1982) and Mukherjee et al. (1961)
measured temperature by insertion of a clinical thermometer into the rectum.; Pan
et al. (1983) used a rectal temperature probe. However, Kemp (1985) measured
body temperature by sensing heat radiated from the ear drum area.
4.6 Traction Animal Dynamometer Design
The procedure used in accomplishing the objectives is as indicated below.
1st Stage:(a) Preliminary design of the loading cart. This consisted of the following: identification of its functions; specifying technical requirements of the cart; identification of possible mechanisms; force analysis of the shapes selected.
(b) Identification of functions of the measuring equipment. Specification of the ranges of variables to be measured and identification of possible equipment to measure and record these variables.
2nd_Stage:(a) Detailed design of the cart which included: component design analysis, final specifications, and preparation of working drawings.
(b) Final specification of the measuring equipment. 85
3rdJ5tage:(a) Workshop fabrication and assembly of the dyno-cart and equipment
installation on to the cart.
(b) Calibration of the dyno-cart.
4.6.1 Loading Cart Function, Features and Specifications
Devadattam (1977) described a loading cart developed for applying varying
loads to the traction animals. The loading cart was constructed from a horse drawn
mower. It consisted of two metallic wheels driving a power take-off via a gearbox.
When the animals pulled the cart, the power take-off powered a positive
displacement hydraulic pump. By adjusting the oil outlet of the pump, varying oil
pressures were obtained. The pressure created a resistive torque on the driving
wheels, which the animals had to overcome by exerting tractive effort. A similar
type of loading cart is described by Dinsmore et al. (1923). The discharge valve
was controlled by suspended variable weights which the animal had to maintain in
suspension. Since key parts (pump, cart, transmission) were modified from specific obsolete parts, it would be impossible to replicate the same cart for research elsewhere. Furthermore even if off the shelf parts were to be used, the cost would be very prohibitive.
Lawrence (1987) described the loading cart with two tires fitted on to a vehicle axle. Loading was achieved by operating the internal expanding brakes of the wheel. This is the simplest and cheapest loading cart. The main set back however is that internal expanding brakes were used. These brakes are used on 86 vehicles for the purpose of bringing the vehicle to a complete stop with no drag effect. Therefore there is very little room for adjusting the range of pull. In addition a high actuating brake force is required when the brake is located on the driving wheels. This would necessitate provision of some system to provide a high mechanical advantage, most likely a hydraulic system.
Functions and features of the loading cart to be designed will include the following:
(i) Vary and control drawbar puli to be exerted by the traction animal. The drawbar pull should vary from 5 to 20 percent of a range of animal body weights.
(ii) Have space for the instruments, operator and/or ballast. Appropriate ballast is necessary in order to generate required drawbar pull with minimal slippage. It can be deduced from equation B.6 in Appendix B, that the loading on the tractive device should match the generated torque so as to keep the wheel slippage low. Failure to do so would result in excessive slippage and wear of the tires.
(iii) Should be portable and easily maneuverable.
(v) Should have hitch points from which the tractive effort exerted by the oxen can be attached.
There are two local types of cattle used in Uganda. They are Ankole (the
East African long horned Zebu) and Bukedi (East African short horned Zebu).
FAO (1972); FAO (1990); and Goe (1983) indicated that these two species have body weight ranging from 300 to 450 kg. Personal observation from visits at some 87
of the research stations and a few farmers indicated that although the above range
may be true for animals at the research stations, those belonging to farmers are
much lighter, ranging from 150 to 250 kg. Therefore the range of weight for
traction animals in Uganda will be assumed to range from 150 to 450 kg.
Assuming the following: inclination angle of the tractive effort to be 15°;
maximum sustainable tractive effort to be 20 percent of the body weight; nominal
weight of traction animals in Uganda varies from 150 to 450 kg, then the
maximum drawbar pull exerted by the largest pair of animals is 1705 N. The
loading cart should be capable of varying and controlling drawbar pull up to 1705
N. Assuming further that the traction effort is to be varied from 5 to 20 percent of the body weight of any tested pair of traction animals, the loading cart should be designed so that it can generate drawbar pull ranging from 142 to 1705 newtons.
4.6.2 Design Synthesis and Analysis
The principle of the loading device designed is anti-tractive resistance and its advantages were discussed in section 4.4. The resistive torque is generated by a band brake system. Band brakes are simpler and less expensive than other braking devices. Because of their simplicity, they can be produced easily in shops with moderate equipment. 88 4.6.2.1 The Chassis
The choice of the chassis for the loading cart was based on stability, the weight required to create anti-tractive resistance, and the space for equipment.
The cart was designed such that its weight would vary. In other words weights would be added whenever higher anti-tractive resistance is required. Other considerations were the lateral stability and space for the transmission elements.
Figures B. 1 and B.2 in Appendix B show the chassis layout.
4.6.2.2 The Tires
As pointed out earlier the principle of this dynamometer is based on anti tractive resistance. Therefore traction tires were used. Using equation B.6 in
Appendix B (assuming Cn= 30 and slip is less than 10 percent) the minimum load on the axle is 3 kN. Based on the traction requirement and the load carrying capacity, two Goodyear garden super sure grip tires were used. Design features of the tires are shown in Table 4.2. It was assumed that approximately 30 percent of the total weight will be carried by the front wheel. In order to facilitate maneuverability of the cart and to ensure that the front wheel does not sink or dig in soft ground, a pneumatic swivel caster was used. The caster wheel was 254 mm diameter by 104 mm width with overall height of 330 mm and its load capacity was
2.4 kN. 89
Table 4.2 Data for Goodyear super sure grip tires used on the loading cart.
Size Ply Rim Overall Rolling Maximum rating width dia. (mm) radius load (kN) (mm) 7 x 16 2 140 800 346 2.6
Loaded tire Section height (mm) Section width (mm) deflection (mm) 42 185 191
4.6.2.3 Shaft Drives
There are three shafts on the dyno-cart: rear shaft, intermediate shaft and the final drive shaft. Transmission is from the rear shaft to the final drive shaft where the brake drum is located. The chain drive associated with the transmission is discussed in section 4,6,2.4. Two simple pillow block bearings supported each of these shafts. The layout of the rear shaft is shown in Figure B.3.
The hub on each end of the rear shaft is shown in Figure B.4. in Appendix B. The primary loading imposed on the shaft is due to: the static and dynamic loading, resistive torque, tensile load in the transmission chain, and the weight of the chain sprocket, tires, and the shaft.
Figure B.4 shows the layout of the intermediate shaft. The primary loading on this shaft consists of the tension in both transmission chains and the weight of the sprocket and the shaft. 90
The final drive shaft layout is shown in Figure B.5. The loading on the shaft consists of weight of the brake drum, tension of the transmission chain and brake band tension. The outline of the design analysis for the shafts is shown in
Appendix B.3.
4.6.2.4 Transmission Chain
When the brake is actuated by force Q2 (see Figure B.7 in Appendix B) the drawbar pull P which the animal has to exert (provided appropriate loading on the rear axle exists) is given in equation 4.1.
P - Q2 R — (4.1) r 0
W here
Q2 = activating force
R = radius of the brake band
rn = rolling radius of the tires
H = coefficient of friction between the brake limning and the brake drum
n, = gear ratio between the rear and the final drive shafts
Derivation of this equation is shown in Appendix B.4. As pointed out one of the functions of the loading cart is to vary P. It can be varied by changing any of the six parameters of equation 4.1. However only two can be varied without 91 complicating the design , namely Qj and r^. In order to vary a simple multi speed bicycle chain was chosen since it is cheap, readily available and easily maintained. However the power rating (Oberg (1984) for roller chain number 41 used on bicycles is such that it can not transmit more than 0.8 kW unless the speed of the smallest sprocket is above 400 rpm. Taking into account the size of the tire, and the average travel speed of Zebu oxen as 2.4 kph (F.A.O., 1990), the transmission shaft would run at about 22 rpm. In order to use a bicycle chain between the transmission shaft and the counter-shaft a sprocket 18 times the size of the smallest size would have to be used on the transmission shaft! Yet the recommended single speed ratio in chain drives is 7 (Mott, 1985). Thus an intermediate chain RC 60 was used to transmit motion from a 56 teeth sprocket to an 11 teeth sprocket located on the intermediate shaft. The sizes of the two bicycle chain sprockets on the intermediate shaft are 48 and 52 tooth. The overall gear ratios for the loading cart are shown in Table 4.3.
Table 4.3 Overall gear ratios between the transmission shaft and the brake drum
G ear G ear G ear G ear N um ber (i) R atio (fij N um ber (i) R atio (rij) 1 18.9 7 12.6 2 17.5 8 11.6 3 16.6 9 11.0 4 15.3 10 10.2 5 14.7 11 9.5 6 13.6 12 8.5 92 4.6.2.S Band Brake
The brake was placed on the fastest shaft because less actuating force is required. Hagenbook (1945) pointed out two conditions which dictate the size of the brake. The first condition is the requirement of the brake to create a desired braking torque. The second condition is the amount of heat that is to be dissipated.
The torque which has to be resisted by the brake is given by equation 4.2
(derived from equation B.14 and B.15 in Appendix B).
e ^ - 1 ) T = Q2 R (4.2)
Where the symbols are defined for equation 4.1
The sheave used as a brake drum was 184 mm pitch diameter which meets the criterion of equation 4.5. The thickness of the lining is 4.8 mm and the width is
25.4 mm which conforms with the suggested approach by Hagenbook (1945).
Table 4.4 Properties of woven lining materials.
Tensile strength 17 - 21 MPa Maximum temperature 200 - 26(T C Maximum speed 38 m/s Maximum pressure 340 - 690 kPa Coefficient of friction .45
(Shigley and Mischke, 1989) 93
Woven fabric lining was used and its characteristics are shown in Table 4.4. The width of the lining is dictated by the contact pressure which the lining can withstand. Considering contact pressure,
(4.3) w here
pa = contact pressure between the drum and the band
w = width of the lining
Taking into account the size of the drum and that of the lining, pa ( equation 4.3) is equal to 186 kPa which is below the strength of the lining (Table 4.5). The tensile strength of the lining p, (equation 4.4), calculated using equation 4.3 is 3.6
MPa which is below the strength of the lining given in Table 4.5.
(4.4) where
t = lining thickness (4.8 mm)
pt = tensile stress
Typical brake linings maintain their required characteristics when the temperature is below 400 °F (Orthwein, 1986). The maximum temperature rise is estimated by use of equation 4.5 (Shigley and Mischke, 1989). w h ere
Pb = average power dissipated as heat
nib = mass of the brake drum (kg)
Since there is a continuous drag, the heat dissipated by the brake is equal to the power being generated by the animals. Once the size of the brake drum is obtained, the minimum criterion of equation 4.5 has to be checked (Hagenbook,
1945).
I (4.6) D > 110 Pb3 where,
D — brake drum diameter (184 mm)
The lining was riveted on to a 3 m metallic strip. In order to reduce heat build up, the lining was riveted in segments on the metallic strip as shown in Figure B.5 in
Appendix B.6. A simple provision was made to allow water to drip slowly on the inner side of the brake drum. It is important to ensure that water does not get between the mating surfaces of the lining and the brake drum. 95 4.7 Fabrication and Assembly of the Dyno-cart
Figure B.7 in Appendix B shows the assembled layout of the loading cart.
The construction was done in the workshop of the Agricultural Engineering
Department at The Ohio State University. The lower and upper parts of the chassis frame were made of 45 millimeter mild steel tubing.
The three shafts were made out of SAE 1045 cold drawn steel. The ends of the rear shaft were bolted on the tire rims via hubs made of SAE 1045.
A 56 tooth sprocket of roller chain number 60 was centrally keyed onto the rear shaft. Another sprocket of similar roller chain, but with 11 teeth, was keyed onto the intermediate shaft. A twin bicycle sprocket with 48 and 52 teeth was fastened at the end of the intermediate shaft via a flange adapter (collar) which was in turn keyed on the intermediate shaft.
A bicycle multi-sprocket was fastened onto the final drive shaft via a male threaded collar.
A two groove cast iron V-belt sheave was used as a brake drum. The middle part of the groove was milled out to provide a 25 mm wide flat groove surface for the brake band. The sheave was fastened on the final drive shaft by a split taper bushing. The band brake was made of 16 gage (15.2 mm) mild steel sheet. A synthetic fabric brake lining of 4.5 mm thickness was rivetted onto the band using 3 x 8 mm counter sunk head rivets. One end (high tension) of the band was pivoted on a mounting bracket (Figure B.8), This bracket was located on a cross chassis member ahead of the sheave. The low tension end was connected to 96
a spring scale and in turn the spring scale was connected to a power screw via a
collar, Figures B.9 and B.10 (an ordinary 16 mm fine thread screw was used) .
A platform constructed out of 19 mm ply wood was fastened on three angle
iron steel struts. The struts were bolted onto the lower part of the chassis frame.
A seat was provided for the dyno-cart operator.
4.8 Instrumentation
The instruments associated with the dynamometer system include: a rotary revolution counter, a force transducer, veterinary rectal probes complete with a digital temperature meter, and a telemetry heart rate monitor. The specifications of these instruments are shown in Appendix C.
One end of a flexible shaft drive was attached to the shaft of a rotaty counter and the other end was attached to the intermediate shaft. The purpose of the rotary counter is to measure the distance travelled by the animal. This method is used with prior knowledge of slip characteristics of the tractive surface with respect to the tractive device of the dyno-cart.
A strain gage load cell of 8.9 kN capacity was used to measure the tractive effort exerted by the draft animal. The output of the load cell was channeled to a chart recorder. Furthermore a 12 Volt Gel cell provided the necessary electrical energy to the load cell and the chart recorder. A spring scale was used to measure the brake actuating force. 97
The veterinary thermocouple probes measured the rectal temperature of
the animals with an output to a dual channel digital thermometer.
A bi-polar heart rate monitor measured the heart rate based on sensing the
electrical field created by the pumping action of the heart which creates an electric
field. The bi-polar electro-cardio sensors placed in appropriate locations on the
animal’s body monitor the electrical wave pattern of the heart. The electric
potential detected is converted into a transmission signal which is picked up by a
receiver.
4.9 Loading Cart Calibration
The purpose of calibrating the dyno-cart was to establish its characteristic
performance with respect to the relationship between the brake activating force
(Q2) and the drawbar pull (P). The procedure consisted of setting the brake
actuating force to a particular level while pulling the dyno-cart with a small tractor.
The drawbar pull was measured by the load cell and the slippage was calculated from measured revolutions of the wheel over a fixed distance. Several levels of
brake actuating force were investigated and three test replicates were made at each level.
The tractive characteristic of the dyno-cart when ballasted to a total rear axle load of 3.67 kN is shown in Figure 4.2. This tractive relationship indicates the capacity of the dyno-cart to generate high drawbar pull without excessive ballasting. Perez et al. (1992) used a sledge where 29.4 kN of ballast was required 98 to generate 2.5 kN drawbar pull.
--1
15 10
0 5
! [) -I- - -4 £) 70 40 60 ao 100 170 MO 160 180 ?0C Acludting Tore* (W)
Figure 4.2 Relationship between the brake actuating force and the drawbar pull of the dyno-cart rear axle is ballasted to 3.7 kN.
When conventional tires are used it is necessary to reduce wear by keeping the wheel slippage low. This can be done by providing appropriate axle load through the use of ballast which minimizes slippage. Figure 4.3 shows the theoretical and experimental values of traction ratio (pull/load). Experimental values of the traction ratio are superimposed on the theoretical curve which was calculated from the Wismer and Luth (1974) equation for traction as given in
ASAE Standard D 497, Section 3.2.2 (ASAE, 1992). Equation 4.7 for slip of a driving wheel for a ground driven implement is given in Section 5.2 of this
Standard.
0.75 s i - In 3 C„ 1.2 (4.7) + 0.079 r 0 W 99
where,
Cn — wheel numeric which is a function of soil strength, vertical loading, wheel
diameter and width. Cn increases with soil cone index rating of the traction
surface.
T — torque due to the brake resistance acting on the drive wheel
r0 = rolling radius of the drive wheel
W = dynamic axle load
si = slip
0.9
0.8
0.7 S 0 6 % 0.5
5 0.4 a . 0,3
0 2
F T iperl i e i «T 0.0 0 10 20 30 40 50 60 70 80 90 100
Wh««l Slip (pereenti)
Figure 4.3 Experimental and theoretical traction ratio of the dyno-cart.
Attempts to use equation 4.7 indicated that it is erroneous. Therefore, it was necessary to derive the theoretical relationship from the original Wismer/Luth equation. The traction mechanics of the dyno-cart falls in the category of a braked 100 wheel.
Therefore,
P = F + MR (4.8) where,
F = gross traction
MR = motion resistance
Thus,
E = I + (4.9) WWW
From the work of Wismer/Luth equation we have:
Ew = 0.75 (1 - e '3 ^ = Ell + 0.04 (4.11) W Cn Substituting equations 4.10 and 4.11 into 4.9 we have: E = 0.75 (1 - e"*3 Solving this equation for slip yields the following relationship: Equation 4.13 was used to calculate the theoretical plot shown in Figure 4.3, assuming Cn to be 50 for the asphalt surface on which the experimental data were obtained. This Cn value corresponds to a hard soil. In order to minimize motion resistance of the dyno-cart without excessive wheel slip, values of Pull/Axle Load should be in the range of 0.4 to 0.6 depending upon traction surface conditions. Soft or tilled soils may require lower values of Pull/Axle Load to avoid excessive slip. 4.10 Conclusions The objective of designing and constructing a traction animal dynamometer system has been accomplished. Although the dyno-cart has been fabricated from mild steel stock, the entire chassis can be constructed from wood. This is particularly essential if the dyno-cart is to be relatively inexpensive in Uganda. The pneumatic rubber wheels may be replaced with metallic or wooden wheels padded with old tire lining, if relatively high traction and steady low rolling resistance are maintained. 102 List of References ASAE (1992) Standards 1992. American Society of Agricultural Engineers. St. Joseph, Michigan. Banister, E.W.; Purvis, A.D. (1968) Exercise electrocardiography in the horse by radiotelemetry. Journal of the American Veterinary Medical Association, 152 (7): 1004-1008. Barton, D. (1985) Yokes or collars? Harnessing techniques for draft cattle. Draft Animal News, Center for Tropical Veterinary Medicine, Edinburgh, (4): 1-5. Brody, S. (1945) Bioenergetics and growth. Reinhold Co, NY. Cardinet III , G. H.; Fowler, M. E.; Tyler, W. S. (1963) Heart rates and respiratory rates for evaluating performance in horses during endurance trail ride competition. Journal of the American Veterinary Medical Association, December 15, 1963: 1303-1309. Devadattam, D.S.K. (1977) Development of a loading car for draft animals. Journal of Agricultural Engineering Research, 14, (l):49-50. Devadattam, D.S.K.; Maurya, N.L. (1978) Draftability of Hariana bullocks. Journal of Dairy Science, 31 (2): 120-127. Dinsmore,E.V.; Collins,E.V.; Caine,A.B. (1923) Testing the power of horses. Report, Committee on animal motors. Transactions, ASAE xvii: 210-217. Engelhart, W.V. (1977) Cardiovascular effects of exercise and training in horses. Advances in Veterinary Science and Comparative Medicine, 21: 173-205. F.A.O. (1972) Manual on Employment of draft Animals in Agriculture. Food and Agriculture Organization of the United Nations, Rome, Italy. F.A.O. (1990) Agricultural Engineering in Development: Selection of Mechanization Inputs. F.A.O. Agricultural Service Bulletin 84, Food and Agriculture Organization of the United Nations, Rome, Italy. Goe, M.R.; McDowell, R.E. (1980) Animal traction: Guidelines for utilization. International Development Agriculture Mimeo 81, Cornell University, Ithaca, New York. 103 Grandjean, E (1988) Fitting Task to the Man. 4 th Ed., Taylor & Francis Ltd. London. Hagenbook, L.D. (1945) Design of Brakes and Clutches of the Wrapping Band Type. Product Engineering, May 1945: 321 - 325. Hinchcliff,K.W.; McKeever,K.H. (1990) Renal systemic hemodynamic responses to sustained sub-maximal exertion in horses. American Journal of Physiology 258: 1177-1183. Holmes, J.R.; Alps, B.J.; Darke, P.G.G.; (1966) A method of radiotelemetry in equine electrocardiography. Veterinary Record, 70 (4): 90-94. Hussain, A.A.M.; Hussain,D.; Hossain,M. (1980) Design and development of neck harness for cattle in Bangladesh. Agricultural Mechanization in Asia, Africa and Latin America II (1): 85-89. ICRISAT (1980) Annual Report. International Crops Research Institute for the Semi-Arid Tropics, India, pp 192-194. Kebede, A.; Pathak, B.S. (1987) Draft characteristics of Ethiopian oxen. Draft Animal News, Center for Tropical Veterinary Medicine, Edinburgh, (8): 12- 13. Kemp, D.C. (1985) Performance measurement for ox and implement combination. Proceedings Silver Jubilee Convention, Indian Society of Agricultural Engineers, 29-31 October, 1:16-21. Kemp, D.C. (1987) Draft animal power: some recent and current work. World Animal Review, 63:7-14 Kivikko, R. (1987) Preliminary tests for single animal harness systems. Tillers report news letter, Tillers International, Kalamazoo, 7, (l):8-9. Kuhlmann W.D; Hodgson, D.S.; Fedde, M.R. (1985) Respiratory, cardiovascular, and metabolic adjustments to exercise in the Hereford calf. Journal of Applied Physiology, 58(4): 1273-1280. Lawrence, P.R. (1987) Implements and instrumentation: Loading devices for experiments with oxen. Draft Animal News, 8: 19 & 21. Liljedahl,J.B.; Turnquist,P.K.; Smith,D.W.; Hoki,M. (1989) Tractors and Their Power Units. 4th edition, AVI. 104 Macmillan, R.H. (1985) Engineering problems in the measurement of draft animal performance. Proceeding, Australian Center for Internationa] Agricultural Research, 10-16 July, 1985, pp 149-155. Mathews, M.D.P. (1987) Measuring draft animal power of carabaos crossed with exotic buffaloes. World Animal Review, 63:15-19. Mukherjee, D.P.; Dutta, S.; Bhattacharya, P. (1961) Studies on the draft capacity of Hariana bullocks. Indian Journal of Veterinary Science and Animal Husbandry, 31,(1): 39-50. Mott, R.L. (1985) Machine Elements in Mechanical Design. Charles E. Merill Publishing Co., London. Pan,L.G.; Forster, V.; Bisgard, G.E.; Kaminski, R.P.; Dorsey, S.M.; Busch, M.A. (1983) Hyperventilation in ponies at the onset of and during steady state exercises. Journal of Applied Physiology, 54 (5): 1394-1402. Perez,R; Recabarren,S.E; Mora,g.; Jara,C.; Quijada,G.; Hetz,E. (1992) Cardiorespiratory Parameters in Draft horses before and after short term draft work pulling loads. Journal of Veterinary Medicine, 39: 215-222. Sims, B.G.; Ramirez, A.A. (1989) Draft oxen energy expenditure: A Mexican case study. Agricultural Mechanization in Asia, Africa and Latin America, 20,(2): 9-14. Smith, A.J. (1981) Draft animal research: A neglected subject. World Animal Review (FAO), 40: 43-48. Varshney, B.P.; Kumar, A.; Mishra, T.N.; Singh, R.P. (1982) Performance of harness used for draft animals. Agricultural Mechanization in Asia, 3,(13): 15-19. Vaugh, M. (1945) Report on a detailed study of methods of yoking bullocks for agricultural work. Indian Journal of Veterinary Science 15, (3): 186-198. Wismer,R.D.; Luth,H.J. (1974) Off-road Traction Prediction for wheeled vehicles. Trans. ASAE 17, (1): 8-10,14. Wyndham,C.H.; Strydom,N.B.; Morrison, J.F.; Williams, C.G; Bredell, G.A.G; Maritz, J.S; Munro, A. (1965) Criteria for physiological limits for work in heat. Journal of Applied Physiology, 20 (1): 30-45. 222 CHAPTER V PRELIMINARY OXEN PERFORMANCE TEST 5.1 Introduction On completion of the development of a traction animal dynamometer system, the next stage was to evaluate the prototype with a preliminary test of the performance of a team of oxen. 5.2 Objectives Theere were two objectives of this work. The first one was assessing the suitability of the dynamometer system developed for the purpose of testing and evaluating traction animals. Evaluation of the system’s performance would lead to its modifications where necessary. This was accomplished by observing characteristic performance of the system: tractive resistance of the dyno-cart, maneuverability, and equipment performance. The second objective was to carry out preliminary endurance tests. The work was preliminary in nature since the animals tested are quite different from the local Ugandan oxen and secondly the ambient conditions during the tests were very much different from Ugandan 105 106 conditions. Nonetheless, the results of the work provide a guideline for future similar work in Uganda. 5.3 Experimental Procedure 5.3.1 Traction Animals Testing of the draft animals was carried out at Tillers International, Kalamazoo, Michigan. One pair of Shorthorn (Durham) oxen was used throughout the experiments. Particulars of these animals are shown in Appendix D. Two patches were shaved on the animals’ skin in order to place the electrodes for measuring the heart rate. One patch was located just behind the scapula cartilage and the other was located near the point of shoulder. The choice of the latter was not the most suitable as far as signal strength is concerned but was dictated by the fact that this was a place where the animals were not irritated by the electrodes. Before and after each experiment the weight of each animal was determined using a platform scale of 22.3 kN capacity complete with a digital readout. A drop hitch double neck yoke of 200 mm size was used when the animals worked as a pair. When they were working individually, a single neck yoke (Appendix D) was used. It should be noted that the size refers to the bow width of the yoke, which in turn depends on the size of the neck of the animal. 107 5.3.2 Instrumentation A loading cart (dyno-cart) developed as outlined in chapter 4 was used. The maximum axle loading was 323 kg. It was achieved by use of ballast placed near the rear axle. By setting the brake actuating force to different levels, appropriate resistive torques on the driving wheels were generated. In turn the oxen generated tractive effort to overcome the tractive resistance of the dyno-cart. The details of the instrumentation of the dynamometer system are outlined in Section 4.8. 5.3.3 Procedure Every morning before each experiment it was necessary to re-shave the patches on the animals’ skin where the electrodes were placed. The endurance test was carried out on the team by requiring the animals to exert a known tractive effort for a specified work-cycle1. The animals were allowed to rest at the end of the work-cycle and during that period their heart rates and their rectal temperatures were monitored. At the end of the rest period the animals started exerting the same effort. The routine was repeated until two hours elapsed. The heart rate was measured by bi-polar heart rate monitors for humans (Appendix C). In order to adapt them for animal use, the adhesive electrodes with leads were connected to the transmitter. The rectal temperature 1 Work-cycle is defined in here as the period during which the animal is working. It consists of multiple laps along the working path and included time for turning at the ends of the test track which averaged 10 seconds at each end. At the end of each work-cycle the animals rested. 108 was measured by veterinary rectal probes (Appendix C) and the output was displayed on a digital thermometer. The procedure for loading was based on consideration of the general way in which the animals were being used at the Tillers’ farm. The test track length was dictated by available level space. However as it turned out, the length closely matched the typical length the animals work on the farm. An asphalt surface was used. The test track was divided into five equal segments of 18.3 m and each of those points were flagged. The test track ran east-west, and to facilitate identification of each flag they were numbered 1 through 6 in one direction and 7 through 12 in opposite direction. After setting the brake actuating force to the required level, the oxen pulled the dyno-cart until the set work time cycle duration was completed. Meanwhile the time to traverse each flagged track segment was observed and recorded. Immediately after the completion of the work-cycle, the rectal temperature and the heart rate were monitored. The data of the experiments conducted is shown in Appendix D. During the work-cycle the following aspects were observed: frothing, step coordination, tongue protrusion, and concentration to work. The experiments were carried out in early spring season as evidenced by the ambient temperature in Appendix D. 109 5.4 Results and Discussion As pointed out in section 5.2 there were two aspects of the preliminary draft animal testing. The results are presented on that basis, (i) To evaluate the suitability of the dynamometer system with particular reference to the ability of the dyno-cart to simulate a range of tractive efforts and the suitability of the instrumentation, and (ii) To carry out a preliminary characteristic performance of oxen. The study investigated the following: (a) Effect of work-cycle duration on the heart rate, investigation of the trends of heart rate with respect to work-cycles and the change in heart rate with respect to tractive effort. Endurance capabilities can be deduced from these characteristics. Furthermore these characteristics can give an insight into good oxen management as far as working oxen in the field is concerned. (b) Effect of work-cycle duration on the speed. This involved investigation of travel speed with respect to work-cycles. Knowledge of these characteristic can be used in deducing drawbar power and field capacity performances. (c) Effect of tractive effort on speed for specified work-cycles. Similar performances as in (b) can be obtained. (d) Effect of tractive effort on the rectal temperature. Similar knowledge as in (a) can be obtained. (e) Effect of work-cycle on the rectal temperature. Similar to (d). 1 10 5.4.1 The Dynamometer System In order to evaluate the ability of the dyno-cart to simulate traction loads, a dynamometer was fixed between the harness chain and a tillage implement. Two implements were used: a moldboard plow and a wood-bar harrow (Roosenberg, 1992). The loading pattern which developed as the animals exerted the required tractive effort was similar to the dyno-cart. Results indicated that the dyno-cart does simulate field loading patterns. The dyno-cart can be maneuvered by the animals. However, care must be exercised when turning to ensure that the harness chain or rope does not rub excessively over the skin of the animal. This can be avoided by bringing the animals to a complete stop and then making a 90 degree turn. The bi-polar heart rate monitors are adequate as long as care is taken to ensure there are no strong electromagnetic sources near the test track. Interference from these signals can lead to erroneous heart rate measurement. Furthermore, precaution should be taken in minimizing signal interference of one transmitter to the adjacent receiver when both paired animals are monitored. Opposite ends of the animals should be instrumented. There is a rapid heart rate drop at the end of the work-cycle as seen in Figure 5.1 derived from data shown in Table D.6 in Appendix D. Therefore heart rate monitoring should be initiated immediately at the end of the work period. Furthermore, the electrodes should be thoroughly moistened before sticking them onto the shaved areas. In order to hold the electrodes on the skin, small droplets Ill 120.0 100,0 90.0 BOO t 7 0 .0 ------ 60.0 J- 0 100 150 Time (Sec.) Figure 5.1 Decline in animal heart rate immediately following three minute work load for the first work-cycle. of surgical glue should be applied on the periphery of the electrodes. It is not possible to monitor the rectal temperature on a continuous basis because the animals keep ejecting the probes. Therefore rectal temperature can only be monitored when the animals have stopped. Unlike the heart rate, the rectal temperature does not immediately decline. Therefore if there is a limitation in the number of helping hands, heart rate should be measured first. The rectal temperature should be measured soon afterwards. The response time (at least 90 %) of the temperature measuring instruments should be known so that the temperature is monitored for the length of time equal to at least the response time. Failure to do so would result in low rectal temperature indication. 112 5.4.2 Traction Animal Characteristics Figure 5.2 shows the average travel speed for a pair of traction animals exerting tractive effort on a hard surface. The speed of the shorthorns is much higher than other oxen such as Brahmans. Lawrence and Stibbards (1990) obtained an average speed of 0.8 m/s for a pair of Brahman oxen while exerting tractive effort equal to 10 % of their weight. The Ethiopian oxen pair travel 0.55 m/s while exerting tractive effort equivalent to 10 percent of their weight (Kebede and Pathak, 1987). 1.50 T r 1.45 \- ~ n ii iork-ey( le Z nd 1.10 i 1 1.05 - !- - - 4 - 1.00-t- . 4------2.0 3.0 5.0 6.0 7.0 ».() 9.0 10.0 Work -cycle time (min.) Figure 5.2 Average travel speed of a pair of Shorthorn oxen for 3 consecutive work-cycles. (average resting period between the work-cycles was 12 min. and the tractive effort was 2.1 kN). 113 The track was east-west in direction and the barn for the oxen was westward. The travel speed measured on westbound was irregular because the animals tended to speed up as they were heading for home. A logical explanation for the high speed of the Shorthorns is their size. As pointed out in section 3.3.1 the theoretical maximum walking speed of oxen is given by equation 3.3. The average hip height of our Shorthorn pair (Louis and Clark) was 1.4 m. Hence the maximum walking speed for these animals is 1.5 m/s. It can be deduced from Figure 5.2 that the travel speed drops off with time. The trend suggests that the highest achievable speed for each successive work- cycle is lower than the previous one. Since tractive effort was fairly constant, it is apparent that the power of the pair was very similar to speed with respect to time. Figure 5.3 shows the trend of the speed with different drawbar pull (horizontal component of the tractive effort). Only one lap (91 m) of the track length was used in developing this trend because comparison could be made only at the end of one lap. At higher tractive efforts the animals were rested at the end of the lap. In the same figure drawbar power is plotted. For a particular tractive effort, the speed trend obtained for a pair is shown in Figure 5.4. This signifies the fact that travel speed is not constant within work- cycles. The speed after 10 minutes in cycle I is lower than for subsequent work- cycles. This could be due to the fact that the animals had to walk to the test track while pulling a loaded cart and had not fully recovered at the start of the experimental runs. Knowledge of animal speed characteristics is particularly 114 t 4.00 1.58 1.54 ■ 3.50 1.50 j-3.00 5 1-46 H x£ 1 1 -4 2 r2.50 ■g 138 Power ■2.00 £ W8, 1.34 - 1.30 a! speed r 1.50 £ > i d 1.26 ^ X t/Z Z < 1.00 C i.i8 r -0.50 1.14 i 1 . 1 0 * — 0.00 0.5 1.0 1.5 2.0 2.5 3.0 Drawbar Pull (kN) Figure 5.3 Effect of the drawbar pull on the travel speed and drawbar power of a pair of oxen at the end of the first 91 meters. important when designing ground driven draft animal equipment such as grass cutters, fertilizer spreaders and sprayer dusters. When the animals exert tractive effort equal to fifteen percent of their body weight the heart rate is elevated. Figure 5.5 shows the trend of the heart rate for consecutive work-cycles. An average of 12 minutes of rest was allowed in between each work-cycle. The heart rate tends to rise as the work-cycle increases. The heart rate trends for five percent tractive effort are also shown in Figure 5.5. The work-cycle duration for fifteen and five percent is 3 and 11.5 minutes, respectively. Since the heart rate levels are comparable but the work-cycle durations are different, it can be deduced that the animals can work for longer periods while 115 II ffl IV Work-Cyole No. hi-iy after 5 minutes after 10 minutes Figure 5.4 Travel speed after 5 minutes and 10 minutes during consecutive w ork-cycies. (tractive effort: 5 %; and average resting between each work-cycle: 8.5 min.). exerting a low tractive effort. Figure 5.6 shows the change in the heart rate per unit time of the work-cycle. The trend suggests rapid rate of change as the tractive effort increases. Similar characteristics are exhibited for rectal temperature changes in Figure 5.7. With the knowledge of acceptable cardiovascular levels for well conditioned oxen and in conjunction with characteristics of Figures 5.5 through 5.7, work-cycle duration and tractive effort which can be tolerated by the oxen can be extrapolated. Endurance capabilities and proper managerial practices can be learned from these characteristics. 116 140 Tractive Effort fg&a 5 % pggj 10 % II ID IV V VII D ork Cycle No. Figure 5.5 Heart Rate at the end of work-cycle for different tractive efforts. 7 0 \ 6 0 - c E \ 5 0 + ■ t , I 4(J -f 5 ! t 30 1 ...... — I * o 1 . -. E« 10 I1 [■■■ ...... _. +■ ‘ ! K i '' X o - 4 ■ - ■ - 4 ...... - • 0 ,5 1.0 1.5 2 .0 2 5 :i.n Drawbar Pull (kN) Figure 5.6 Rate of change of the heart rate (HR) with respect to the tractive effort based on the first work-cycle at each tractive effort. 117 0.24 t— 0.22 ^ 0.10 -j------ a> 0.08 o 0.06 -i- 0.04 — 0.02 0.00 0.5 1.0 1.5 2.0 2.5 3.0 D raw bar Pull {kN) Figure 5.7 Rate of change of the rectal temperature per unit work-cycle time with respect to varying traction effort based on the end of the first work-cycle for each tractive effort. Figure 5.8 shows a comparison of the average rate of change of the heart rate of Ox Louis while working individually and in pair with Ox Clark. In both cases the tractive effort exerted was 0.68 kN. It can be deduced that when the oxen works alone, the exhaustion (based on high heart rate level) is higher than when working in pair. Similar deductions can be made for the rectal temperature as shown in Figure 5.9. I I » Hork-Cycles £ £ 3 Single Pair Figure 5.8 Average rate of change of the heart rate (HR) at the end of each work-cycle for Louis while working individually and as a pair. (Average resting: 10 minutes). c 0 .1 8 \ 0 .1 6 - s 014 -*----- c O.Ofi t - 0 .0 4 0.0^ -t ^ * H ^ V 5 0.00 Work-Cycles Single ESSd Pair Figure 5.9 The rate of change of the rectal temperature for Louis when working as a pair and individually. 119 Figure 5.10 shows another aspect of gauging work load and its effect on the animal, i.e., weight loss of the animal per minute of total work-cycle time for various tractive effort. Although this work is not conclusive it appears that high tractive effort is linked to high weight loss. The most visible loss was through faeces and urine. 1.60 e 1.20 + ~ r - x 1.00 g 0.80 ------ £ •2f 0.40 + 1.5 2.0 :i.o Drawbar Pull (kN) Figure 5.10 Body weight loss per minute of total work-cycle time with respect to different drawbar pull. 5.5 Conclusions 5.5.1 Traction Animal Dynamometer System Observations of the performance of the dyno-cart system lead to the following conclusions. Although the brake lining can withstand temperatures of up 120 to 205 QC, from the stand point of safety and possible seizure of the bearings supporting the brake shaft, the temperature should be kept well below 205 °C. Furthermore high brake temperature results in loss of friction and eventual loss of tractive ability of the dyno-cart. Water drops can be directed to the surface of the drum for cooling, however water should not go between the band and the brake drum. It is advisable to reduce the tension in the brake drum at the end of the work-cycle so that as the drum cools the band does not bind on the drum surface, which on re-start results in uneven tractive ability. Faster response in controlling the brake tension can be achieved by use of a screw with at least 6 mm pitch. Unfortunately this would require 100 mm size bolt if ordinary machine bolt is used, therefore the ordinary screw which is currently used should be replaced with a square thread power screw. The problems which are likely to arise as regards to heart rate monitoring using the bi-polar heart rate monitor include: (i) Bad or poor contact between the electrodes and the animal’s skin could prevent the signal from being registered. It is necessary to have a clean shave with moist electrodes. At times this might result in getting the signal late. It is suggested that post work heart rates with respect to time be obtained so that these curves can be used to extrapolate the heart rate which may have been missed. (ii) Poor electrode location. The positive polarity of the electrode lead should be closest to the heart. A good signal is obtained when the electrodes are 121 located along the heart girth with the positive electrode located behind the scapula cartilage and the negative electrode behind the point of elbow. Unfortunately this location might be dangerous to the investigator because the animal is likely to kick as one attaches the electrode. In this case suitable locations can be obtained by trial and error. (iii) The presence of electromagnetic fields (such as produced by power lines) causes erroneous readings. Testing should be done where the effect of the electromagnetic field is minimal. 5.5.2 Traction Animal Testing The importance of accumulating characteristic performance tests is that the farmers can be advised on the best managerial practices for the use of draft animal power. This is particularly important in the beginning when most farmers are just being introduced to this technology. After a generation, experience among farmers will be dominant propellent factor. It is imperative that oxen be tested in a manner which closely resembles the way the animals are used in practice. Mukherjee at al. (1961) and Pearson (1989) subjected the animals to six hours of continuous endurance testing. Although this might be a good endurance test for simulating transportation workload, it is not appropriate for field work. In the field, the animals work for a short time and then rest. 122 The travel speed of the oxen at the beginning of a work-cycle is high but with time it falls to a steady level. Although these findings are based on ten minute work-cycles, the work of Devadattam and Maurya (1978) indicates similar trends for one hour duration. Speed trends with respect to tractive effort indicate that as the tractive effort increases, the speed falls. Similar findings were observed by Devadattam and Maurya (1978). It should be noted that when the animals exerted tractive effort in excess of ten percent of their body weight, they required longer time of rest. Therefore, reduced field capacity is the penalty for overloading the animals. Although the power of the animal team increases with increased tractive effort, the overall power and productivity may decrease because of reduced endurance. Testing and observation of performance work-cycles versus rest periods are necessary to determine optimum performance. Foting of the mouth is a qualitative assessment which is likely to relate to stress due to extended work-cycle. There appears to be three stages. The first stage foaming has many air bubbles. This stage may not reflect workload stress in most cases. In the second stage the fluffy froth has less air bubbles and it covers the mouth. It is more viscous than that of the first stage. This appears to be linked to early signs of exhaustion. In the third stage the froth becomes more viscous and starts drooling. At this stage the animals looses concentration. The teamster issues commands more frequently and the animals are apt to stop without command. 123 List of References Devadattam, D.S.K.; Maurya, N.L. (1978) Draftability of Hariana bullocks. Journal of Dairy Science, 31 (2): 120-127. Kebede, A. and Pathak, B.S. (1987) Draft characteristics of Ethiopian oxen. Draft Animal News, Center for Tropical Veterinary Medicine, Edinburgh, ( 8): 12- 13. Lawrence, P.R.; Stibbards, R.J. (1990) The energy costs of walking, carrying and pulling loads on flat surfaces by Brahman cattle and swamp Buffalo. Animal Production, 50: 29-39. Mukherjee, D.P.; Dutta, S.; Bhattacharya, P. (1961) Studies on the draft capacity of Hariana bullocks. Indian Journal of Veterinary Science and Animal Husbandry, 31,(1): 39-50. Pearson, A.R. (1989) Reduced work output of well-fed Buffaloes pulling carts on the Terai in East Nepal. Tropical Animal Health 21: 273-276. Roosenberg, R. (1992) Wood-Framed Spike-Tooth Harrow. Tillers Tech-Guide. CHAPTER VI CONCLUSIONS AND RECOMMENDATIONS 6.1 Introduction The goal of this dissertation was to explore the status of agricultural mechanization in Uganda by investigating the three major mechanization levels namely: human, animal and engine powered mechanization. An overview of the progress of the latter two and the constraints of the former have been presented. Critical engineering problems hindering the adoption of draft animal power have been investigated. A traction animal dynamometer system has been developed and will be used in future research work on draft animals. A preliminary testing of Shorthorn oxen was used to verify the system. 6.2 Conclusions 1. Agricultural production in Uganda is greatly hindered by lack of adequate power necessary for various operations. The majority of the farmers rely on hand power. There is a need to make a transition to higher appropriate mechanization levels. 124 There are three options to the transition: draft animal power, engine power (tractors) and hand power supplemented by a combination of these two forms of power. Although animal power was introduced to Ugandan farmers at the beginning of the twentieth century, draft animal technology did not take firm roots due to the introduction of tractors in the late 40’s. Despite great efforts to popularize tractor usage, social, economic and technical problems have hindered the adoption by the farmers. A model which presents forecasts of hand labor and/or draft animals has been developed. Farmers need to rely upon advanced planning. The research pertaining to draft animal power is inadequate in Uganda. Critical engineering problems which need attention from researchers are: (i) Investigation and documentation of the characteristic performances of draft animals. Studies in this broad area would range from endurance tests to nutritional requirements of the draft animals for optimum performance, (ii) Evaluation and selection of draft animal implements and equipment. This would involve appraising implements and equipment used successfully elsewhere for the purpose of adaptive design to suit local draft animals and farming practices. Implements for the following operations need adaption: plowing, planting, row crop weeding, land levelling, and selected harvest equipment, and (iii) Ergonomic studies of draft animal- operators system. As a step towards addressing the above problems, a draft animal dynamometer system for testing animals has been developed. The system which consists of a loading cart and instrumentation for mechanical and physiological parameters of the animal has been developed and tested. Using the prototype dynamometer system, preliminary characteristic performance of oxen was carried out on a pair of dairy Shorthorns at Tillers International in Michigan, USA. The work will provide guidelines for future research work in Uganda. The speed of the Shorthorns while exerting tractive effort ranging from 0.7 to 2.8 kN varied from 1.5 to 1.0 m/s. Therefore an average power of 3.5 kW was being expended. The heart rate does reflect the tractive effort level. Higher tractive efforts are associated with a high rate of change of the heart rate. Weight loss after work is related to the level of tractive effort exerted and the duration. Where there is justification and the means of utilizing engine power, optimum sized tractors should be used. A tractor power requirement model has been developed which can be used in selecting the appropriate small tractors. 127 6.3 Recommendations 1. The input parameters of the model for prediction labor need to be collated for each agricultural zone in Uganda so that it can be used widely and reliably throughout the country. 2. The emphasis of agricultural mechanization should be on draft animal power. There is a need to incorporate engineering into animal mechanization and to develop improved and more efficient methods and systems. There is a need to study and understand draft animal system. There are four major disciplines which should be involved: economics, engineering, agronomy and veterinary medicine. 3. In order to reduce the overall production cost of the dyno-cart wooden chassis frame could replace the existing metallic frame. Furthermore the rubber tires could be replaced with metallic rims bolstered with old rubber tires. 4. The size of the pair of draft animals used had a nominal body weight of 1500 kg and they were capable of exerting 2.8 kN tractive effort while carrying out primary tillage. Typical draft requirement of a 20 cm plow in Ugandan conditions is about 2.4 kN. This would require a pair which is at least 1500 kg. Unfortunately, the size of a pair of Ugandan animals rarely exceeds 900 kg. Therefore of the following needs to be done: (i) Develop breeding programs of multipurpose draft animals which have 128 comparable size to the diary Shorthorns used at Tillers. (ii) Use more than two animals. This aspect may present other problems such as hitching arrangements and extra maintenance requirements. (iii) Adopt sustainable tillage practices which reduce or eliminate the high energy demand of primary tillage. (iv) Use existing animal size in pairs but reduce the implement size which unfortunately would greatly reduce the field capacity. It is recommended that options (i) and (iii) be pursued. LIST OF REFERENCES Anderson A.L (1943) Introductory Animal Husbandry. MacMillan Co. NY. Alexander R., McN. (1983) Animal Mechanics. Blackwell Scientific Publishers, Oxford. Alexander R., McN. and Goldspink, G, (1977) Mechanics and Energetics of Animal Locomotion. John Wiley & Sons. 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(1965) Criteria for physiological limits for work in heat. Journal of Applied Physiology, 20 (1): 30-45. APPENDIX A THEORETICAL POWER REQUIREMENT MODELS 136 137 A.1 Tractor Power Requirement Model This program estimates the tractor power size required for a particular operation. This is done by minimizing the cost of the operation, subject to the constraints outlined in section 2.5.1.1. The parameters to be provided in subroutine USER1 are as follows: XI - critical land preparation time, obtained from agro-zone data (see section 2.5.2). X2 - working hours per day. B3 - operators labor charge Z - farm size (ha). Cn - wheel numeric, obtained from technical data accumulated on trafficabilty of the soils in the area. FCE - field efficiency, obtained from accumulated work study of different operations. TRB - machinery reliability, obtained same way as FCE. PWD - probability for working day as defined by ASAE(1992). ALPH2 - fuel cost ($/l). ALPH4 - oil cost ($/]). The coding is as follows: 138 C PROGRAM TAPOR C THIS PROGRAM SELECTS TRACTOR POWER SIZE BY OPTIMIZING C OPERATING TRACTOR COSTS C THERE ARE 2 NON LINEAR INEQUALITY CONSTRAINTS, C AND 3 VARIABLES: IN ADDITION THERE ARE 16 PARAMETERS C ASSOCIATED WITH THE MODEL. C THE CONSTRAINTS ARE : C (i) Timeliness operation. C (ii) Power requirement C C TAPOR - MAIN PROGRAM C C PROGRAM DESCRIPTION C C ACCESS C EXECUTE THE PROGRAM C C EXTERNAL REFERENCES C OPK - EXTERNAL SUBROUTINE FOR MINIMIZATION C (VANDERPLAATS (1984) C U S E R 1 - USER SUPPLIED OPK PARAMETERS SUBROUTINE C USER2 - USER SUPPLIED OPK PARAMETERS SUBROUTINE C USER3 - USER SUPPLIED PRIMARY MODEL PARAMETERS C SUBROUTINE C LOCAL VARIABLES C A -RL ARY-DIM(21,30)- ARRAY FOR CONSTRAINT GRADIENTS C ALPH1 -RL VBL-FUEL CONSUMPTION (L/kW-hr) C ALPH2 -RL VBL-FUEL COST ($/L) C ALPH3 -RL VBL-OIL CONSUMPTION (L/hr) C ALPH4 -RL VBL-OILCOST ($/L) C ATF -RL VBL-TEMPERATURE/ALTITUDE FACTOR C B -RL ARY-DIM(5,5)- DUMMY ARRAY ASSOCIATED WITH A C B1 -RL VBL-RATIO OF FIXED TO INITIAL COST C B3 -RL VBL-OPERATOR’S COST ($/hr) C BX -RL VBL- C CN -RL VBL-WHEEL NUMERIC INDEX C COST -RL ARY-DIM(100)-ARRAY FOR COST FUNCTION ($) C DAL1DB -RL VBL- DERIVATIVE OF ALPH1 WRT X(3) C DAL3DB -RL VBL- DERIVATIVE OF ALPH3 WRT X(3) C DALDPE -RL VBL- DERIVATIVE OF ALPH1 WRT X(l) C DALDRT -RL VBL- DERIVATIVE OF ALPH1 WRT RT C DALDVT -RL VBL- DERIVATIVE OF ALPH1 WRT X(2) 139 C DF -RL ARY-DIM(21)- ARRAY FOR OBJECTIVE GRADIENTS C DPATDB -RL VBL- C DRTDB -RL VBL- C DRTDPE -RL VBL- C DRTDVT -RL VBL- C DRTDWT -RL VBL- C DTR -RL VBL- NET TRACTION RATIO C FCE -RL VBL- FIELD EFFICIENCY C FCOST -RL ARY-DIM(IOO)- C FIXC -RL ARY-DIM(IOO)- FIXED COST ARRAY C FUEC -RL ARY-DIM(IOO)- C G -RL ARY-DIM(IOO)- C IC -IN ARY-DIM(21)- PARAMETER FOR SUBROUTINE OPK C ICNT -IN ARY-DIM(IOO)- C IDG -IN ARY-DIM(21)- PARAMETER FOR SUBROUTINE OPK C IGRAD -IN VBL- PARAMETER FOR SUBROUTINE OPK C INFO -IN VBL- PARAMETER FOR SUBROUTINE OPK C INRS -IN VBL- PARAMETER FOR SUBROUTINE OPK C IONED -IN VBL- PARAMETER FOR SUBROUTINE OPK C IOPT -IN VBL- PARAMETER FOR SUBROUTINE OPK C IPRINT -IN VBL- PARAMETER FOR SUBROUTINE OPK C ISTRAT -IN VBL- PARAMETER FOR SUBROUTINE OPK C ITMAX -IN VBL- PARAMETER FOR SUBROUTINE OPK C IWK -IN ARY-DIM(5000)-ARRAY FOR SUBROUTINE OPK C J -IN VBL- C K -IN VBL- C KT -IN VBL- C L -IN VBL- C LFLAG -IN VBL- C NCOLA -IN VBL- PARAMETER FOR SUBROUTINE OPK C NCON -IN VBL- PARAMETER FOR SUBROUTINE OPK C NDV -IN VBL- PARAMETER FOR SUBROUTINE OPK C NGT -IN VBL- PARAMETER FOR SUBROUTINE OPK C NRA -IN VBL- PARAMETER FOR SUBROUTINE OPK C NRIWK -IN VBL- PARAMETER FOR SUBROUTINE OPK C NRWK -IN VBL- PARAMETER FOR SUBROUTINE OPK C OBJ -RL VBL- OBJECTIVE FUNCTION C PAQ -RL VBL- C PAR -RL ARY-DIM(IOO)- C PAT -RL VBL- C PHI1 -RL VBL- REPAIR COST AS % OF FIXED COSTS C POWER -RL ARY-DIM(IOO)- C PWD -RL VBL- PROBABILITY OF WORKING DAY Z R R-I(O) ARRAY F A E R A R FO Y A R S R A ETER M A R PA ARY-DIM(IOO)- F O -RL SION C EN DIM SET ARY-DIM(IOO)- Z C L -R ARY-DIM(IOO)- C XLUBC -RL C XLABC C C X -L B- IL DEP H DAY E PT E R TIM D PE N E G S IO R T U A O R TILLA H EPA G VBL- PR IN RK -RL O W LAND L VBL- -RL CRITICA VBL- X3 -RL X2 C I X C C X -L B- OT ER RATED P ER W PO D E T A R R PE R O T C A R T F O COST VBL- -RL XI C X R DI 2)ARRAY F SGN VARIABLES A V OPK N E IN T ESIG U D O R R B FO SU Y R A R FO R Y A (21)-A R R IM -D Y R A 10000)-A ( -RL -DIM ARY -RL X ARY-DIM(IOO)- WK -RL T H ARY-DIM(IOO)- C IG W -RL TH C ID W C C c c c c c c c c c c c c c non non c FL RES OUT F UT PU T U O R FO T U .O T L SU E R FILE A E T A E R C OOP OR N SI I E RAL AR SIZES. RM FA L A ER SEV G TIN A ESTIG INV R FO P O LO O D F C (0) REP 10, LB (0) XAC 10, TF (100), XLABC (100), XLUBC (100) (100), FCOST PC E R (100), (100), EC FU + + (0) WI (0) SEED (0) IN (0) FXC (100), C FIX (100), ICNT (100), D E A SPE (100), (100), Z T 5), H IG (5, W B (100), (5000), K IW ( (10000), (21),WK F D + + + 0 -) - L NEW 50 O 0 D = = STATUS ’,LFLAG T U .O T L SU E R = FILE 9, = IT N (U PEN O DIM EN SION X (21), VLB (21), VU B (21), G (100), IDG (21), IC (21), (21), IC (21), IDG (100), G (21), B VU (21), VLB (21), X SION EN DIM E R T B TR ME-L B- RNMISO EFI ENCY C N IE FFIC E VLB ISSION TRANSM VBL- -RL E ARY-DIM(IOO)- TM -RL Y TH F T VUB PE R ARY-DIM(IOO)- -RL SPEED SL TO R RT1 T R PC E R QX 21 -RL VBL- W H E E L SLIP L E E H W VBL- -RL RL VBL- L -R -RL VBL- -RL VBL- -RL R Y-I 2) ARRAY F UBROUTI OPK E IN T U O R B SU R FO Y A R R A (21)- -DIM RY A -RL R VL TRACTI FI E Y C IEN EFFIC E IV T BILITY C A R T RELIA R VBL- O T C -RL A R T VBL- -RL R VL P E R YEA R PE S R U O H R O T C A R T VBL- -RL R AR DM(1- R OR UBROUTI OPK E IN T U O R B SU R FO Y RRA A (21)- -DIM RY A -RL VBL- -RL 3) P (0) C T(0)P 10, DTH ID W (100), R E W (100),PO ST CO (100), R PA 30), , R ARY-DIM(IOO)- -RL 1 15 , 140 141 C C PROVIDE REQUIRED PARAMETERS FOR OPK C CALL USER1 (NRA, NCOLA, NRWK, NRIWK, NDV, IGRAD, NCON, + X,ITMAX,VLB, VUB, IDG, ISTRAT, IOPT, IONED, IPRINT, + INFO) C C CALL OPK FOR THE FIRST TIME C CALL OPK (INFO, ISTRAT, IOPT, IONED, INRS, IPRINT, IGRAD, + NDV, NCON, X,VLB, VUB, OBJ, G, IDG, NGT, IC, DF, A, + NRA, NCOLA, WK, NRWK, IWK, NRIWK) C C OVERRIDE OPK DEFAULTS VALUES C CALL USER2 (IWK, WK, ITMAX) C C PROVIDE PARAMETER VALUES C CALL USER3 (XI, X2, CN, B3, FCE, TRB, ALPH2, ALPH4, PWD) X3 = .2 Z (L) = 5*L B1 = .2 XI = 230. SL = .15 TM E = .85 TRE = (1. - (1.2/CN + 0.04) / (.75* (1. - EXP ( - CN*0.3*SL) ) + ))*(1.-SL) DTR = .60 ATF = .802 THY = 1000. PHI1 = .0001 C C PERFORM THE OPTIMIZATION C 10 CALL OPK (INFO, ISTRAT, IOPT, IONED, INRS. IPRINT, IGRAD, + NDV, NCON, X,VLB, VUB, OBJ, G, IDG, NGT, IC, DF, A, + NRA, NCOLA, WK, NRWK, IWK, NRIWK) C C CHECK THE CONVERGENCE C IF (INFO .EQ. 0) GO TO 40 C C THE FOLLOWING CODING IS ACTIVATED IF IGRAD =1 C IF (INFO GT. 1) GO TO 20 C C EVALUATE OBJECTIVE AND CONSTRAINTS C PAR (L) = Z (L) / (X (2) * (1. - SL) *X (3) *.3600* FCE *TRB) PAT = PAR (L) RTO = X (2) * (1. - SL) * (10* (7. + 0.635* (X (2) **2) * (1 - + SL) **2) *X (3)*X3 + (1.2/CN + 0.04) *.25*X (4) /1000.*9.81) / + (0.96*TRE) RT1 = X (1) *0.9 RT = RTO/RT 1 ALPH 1 = 2.64*RT + 3.91 - 0.203*SQRT ( (738.*RT) + 173.) ALPH3 = 0.00059*X (1) + 0.00657 OX = ( (B1*XI/THY + (ALPH1 *ALPH2) + (PHI1*XI) ) *X (1) ) + (ALPH3*ALPH4) + B3 OBJ = QX*PAT G (1) = Z (L) / (X (2) * (1. - SL) *X (3) *.36*FCE*TRB) - + X1*X2*PWD PAQ = 10*X (3) *X3* (7. + .635* (X (2) **2) * (1. - SL) **2) + + (0.25 *X (4) *9.81/1000.) * (1.2/CN + 0.04) G (2) = ( - X ( 1) *TRE*ATF*TME) + (PAQ*X (2) * ( 1. - SL) ) G (3) = 0.85*X (3) *X3*10.**4* (7. + .635* (X (2) * (1. - SL) + ) **2) + (1.2/CN + .04) * (.25*X (4) *9.81) - (0.75*X (4) + *9.81 *DTR) G (4) = (0.98*X (1) *700.) - (0.75*X (4) *9.81) C C CONTINUE WITH OPTIMIZATION C G O T O 10 20 CONTINUE C C COMPUTE GRADIENT OF THE OBJECTIVE FUNCTION C PAT = Z (L) / (X (2) * ( 1. - SL) *X (3) *.3600*FCE*TRB) OX = ( (B1*XI/THY + (ALPH 1 *ALPH2) + (ALPH3*ALPH4) + + (PHI1*XI) + ) *X (1) ) + B3 BX = (10.* (7. + 0.635* (X (2) **2) * (1 - SL) **2) *X (3) + *X3) + (1.2/CN + 0.04) *.25*X (4) /1000.*9.81 PAQ = 10.*X (3) *X3* (7. + .635* (X (2) **2) * (1. - SL) **2) + + (0.25*X (4) *9.81/1000.) * (1.2/CN + 0.04) COMP ONSR NT ENT AD S BIJ F R FO B(I,J) USE AND TS N IE D A R G T IN STRA R N FO CO T E N T IE D PU A M R O G C C TE PU M O C C C C n o n E R E H W o E G A R n O ST Y R A R PO M E T C UTE ENT OR G(2) R FO T N IE D A R G E T PU M O C I L N. J NT NO. T IN A R T S N O C J= NO., BLE RIA A I V = *.102/00) (.609TEX 1 ) (1) /(0.96*0.9*TRE*X *9.81*0.25/1000.) + DPATDB QX* + + .3* X 2 *2* 1 - L **2) SL) - (1. **2)* (2) (X 0.635* + + AP4 DVT V LD A D ALPH4* + + (1. - SL) / (0.9*0.96*TRE*X (1) ) ) *10.*X (3) *X3*2.*0.635*X (3) *10.*X ) ) (1) *PAT ( * PH11*X1) (2) + (0.9*0.96*TRE*X / ) PE SL) D - L A (1. + 4*D PH L +(A + ) ) PE D L A (D + + + (, ) (. S) PQ X 2 * 1 - L * 1.X 3 *X3* (3) (10.*X * SL) - (1. * (2) X + *PAQ SL) - (1. = 2) (2, B ( B (, ) - A/ (3) PAT/X (4, - B = 1) (3, B (, ) - A/ (2) PAT/X - = 1) (2, B 0.0 = 1) (1, B ( () ( * (2) (X = T W D T R D 4 = (LH2X 1 *DAL ) (L 4 DWT ) *PAT ) T) W LD A D H4* (ALP + T) W LD * A D (1) 2*X (ALPH ( = T (4) W 0.0 F TD D R = D RT* T W LD LD DA A D = T W LD A D IF (N G T .EQ. .EQ. T G (N IF D F (3) = PAT* ( (ALPH2*X (1) *DAL1DB) + (A LPH 4*D A L3D B) ) + + ) B) L3D A 4*D LPH (A + *DAL1DB) (1) (ALPH2*X ( PAT* (3) = PAT/X (3) - F D = B TD B PA 0.0 D RTD = D RT* B LD A L3D D DA = B L1D DA DB = () (. S) 09*.*R* () *31. (7. *X3*10.* ) (1) + T V (0.96*0.9*TRE*X / LD A SL) *D - (1. (1) * (2) X ALPH2*X = + ) B TD (2) R D *PAT/X (QX - = (2) 0.0 F D = T V LD A D ( 1 * L / 09*.*R* () *X + ( () * T V D (2) T R (X D ( RT* LD + A D = *BX) ) T V (1) LD A D (0.96*0.9*TRE*X / * SL) (1. ( = T V D T R D - XX 2 * 1 - L 09*9TE ( ( (X (0.96*.9*TRE* / SL) - (1. * (2) BX*X - = E P D T R D () ( (B ( = PE D (1) T R F *D D T R D L A D = PE LD A D DP = 0.00059 = PE LD A D DRT = .4 (.0* 05 *3. (3.R + 7. * ( - ( ** 173.) + (738.*RT *738.* (0.5) (0.203* - 2.64 = T R LD A D -5)) 1 2 = T * FT E TF*TM E*A TR - = 2) , 1 = 0.0 = ) 1 - L **2) SL) - . 1 0 X/H) ( P 1* P ) ( ( (X + 2) 1 LPH *A LPH (A + *XI/THY) GO TO 10 O T O G ) 1 - L * 12C + 0.04) + (1.2/CN * SL) - . G(l) 1 *ALPH2* ) 1 *2 ) **2) ) 143 144 + 2*.635*X (2) * ( (1. - SL) **2) ) B (3, 2) = 10.*X3* (7. + .635* (X (2) **2) * (1. - SL) **2) *X + (2)*(1.-SL) B (4, 2) = 0.25*9.81/1000.* (1.2/CN + 0.04) *X (2) * ( 1. - SL) C C COMPUTE GRADIENT FOR G(3) C B (1, 3) = 0.0 B (2, 3) = 0.85*X (3) *X3* (10.**4) *2.*.635*X (2) * (1. - SL) + **2 B (3, 3) = 0.85*X3* (10.**4) * (7. + .635* (X (2) **2) * (1. - + SL) **2) B (4, 3) = ( (1.2/CN + .04) * (.25*9.81) ) - 0.75*9.81 *DTR C C COMPUTE GRADIENT FOR G(4) C B (1, 4) = 0.98*700. B (2, 4) = 0.0 B (3, 4) = 0.0 B (4, 4) = - 0.75*9.81 C C STORE GRADIENTS IN ARRAY A C DO 30 J = 1, NGT K = IC (J) A (1, J) = B ( 1, K) A (2, J) = B (2, K) A (3, J) = B (3, K) 30 A (4, J) = B (4, K) GO TO 10 40 CONTINUE POWER (L) = X ( 1) SPEED (L) = X (2) *3.6 WIDTH (L) = X (3) * 100. WIGHT (L) = X (4) LFLAG = LFLAG + 1 COST (L) = OBJ ICNT (L) = IWK. (68 ) FIXC (L) = B1*XI*X (1) /THY FUEC (L) = ALPH1*ALPH2*X (1) REPC (L) = PHI1*XI*X ( 1) XLUBC (L) = ALPH3*ALPH4 XLABC (L) = B3 145 50 CONTINUE WRITE (9, 80) DO 60 K = 1, LFLAG 60 WRITE (9, 90) Z (K), POWER (K), SPEED (K), WIDTH (K), WIGHT (K), +PAR (K), COST (K), ICNT (K) W RITE (9, 100) DO 70 KT = 1, LFLAG 70 WRITE (9, 110) Z (KT), FIXC (KT), FUEC (KT), REPC (KT), XLUBC +(KT), XLABC (KT) STOP C 80 FORMAT/ \2X,’AREA’,3X,’POWER’,3X,’SPEED’,3X,’WIDTH’,3X, + ’WEIGHT’/ ’,2X,,(ha)’,2X,’(kW)’,3X,’(KM/H)’,2X,’(CM)’,4X, + ’(K G )’,8X,’HOURS’,5X,’COST $’,3X,’VIOLATED CONS.’) 90 FORMAT (’ ’, 2X, F5.0, IX, F5.1, 2X, F4.1, 2X, F5.1, 2X, F7.0, 3X, + F7.2.3X, F9.2, 3X, 12) 100 FORMAT(’ \2X,’BREAK DOWN OF COSTS PER HOUR/ \4X,’AREA’,6X, + ’FIXED’,2X,’FUEL’,2X,’REPAIR’,2X,’LUBRICANTS’,2X,’LABOR’) 110 FORMAT (’ ’, 2X, F5.0, 2X, 5 (3X, F5.2) ) C END C SUBROUTINE USER1 (NRA, NCOLA, NRWK, NRIWK, NDV, IGRAD, + NCON, X, ITMAX,VLB, VUB, IDG, ISTRAT, IOPT, + IONED, IPRINT, INFO) C C USERl - USER SUPPLIED OPK PARAMETERS SUBROUTINE C C PROGRAM DESCRIPTION C C ACCESS C CALL USERl (NRA, NCOLA, NRWK, NRIWK, NDV, IGRAD, NCON, X, C + ITMAX,VLB, VUB, IDG, ISTRAT, IOPT, IONED, C + IPRINT, INFO) C DIMENSION X (21), VLB (21), VUB (21), IDG (21) NRA = 21 NCOLA = 30 NRW K = 10000 OPI Z S N OUTPUT C R LS TRO N CO , Y T U P TEG T U O STRA AND ETERS: H M C R RA A PA ,SE R C N IZE TIO IZA PTIM O C PTIM O T PU IN C noon non o nnn on I QUALITY A U EQ IN D N A ID E N T IFY T H E CO N STRA IN T TY PES:LIN EA R, NON LINEA R, R, LINEA NON R, EA PES:LIN TY T IN STRA N CO E H T IFY T N E ID DE RAS E IIS F O TRI AL OL I N TIO LU SO L IA IV R T NON R FO LIMITS. LE B A N SO REA E ID V O R P NP NII S F X R O T C E V R FO ESS U G L ITIA IN E H T T PU IN STRAINTS CON E T PU M O C R PO A T LET ND EN N R U T E R NF - 2 - = FO 2020 IN = T IPRIN ONE 7 = ED N IO 4 = PT 0 IO = T ISTRA D () 0 = (2) 0 IDG = (1) IDG U () 4. = (2) VUB U () 10 + 20 + 1.0E = (4) 2.3 VUB = (3) VUB ( VLB U ( 10. VUB = (4) .2 VLB = (3) VLB = (2) VLB () 1500. = (4) X = (3) X 2. = (2) X 2. = (1) X T X 300 = AX ITM 4 = NCON = 4 = V D 5000 N = K RIW N IG R A D = = D A R IG 1 1 ) = = ) = 100. = ) 1 . 1 .1 1 . 146 147 C SUBROUTINE USER2 (IWK, WK, ITMAX) C C USER2 - USER SUPPLIED OPK PARAMETERS SUBROUTINE C C PROGRAM DESCRIPTION C C ACCESS C CALL USER2 (IWK, WK, ITMAX) C DIMENSION IWK (5000), WK (10000) IWK (3) = ITMAX IWK (7) = ITMAX IWK (5) = 6 R ETU RN END C SUBROUTINE USER3 (XI, X2, CN, B3, FCE, TRB, ALPH2, ALPH4, + PW D) C C USER3 - USER SUPPLIED PRIMARY MODEL PARAMETERS C SUBROUTINE C C PROGRAM DESCRIPTION C C ACCESS C CALL USER3 (XI, X2, CN, B3, FCE, TRB, ALPH2, ALPH4, PWD) C XI = 18. X2 = 8. CN = 15. B3 = 5. FCE = .65 TRB = .6 PW D = .9 ALPH2 = .8 ALPH4 = .5 RETU RN END 148 A.2 Labor and Draft Animal Model The model is intended to estimate separately laborers, animal pairs, and a combination of the two, required to carry out task operations on small farms in the Teso farming system. In the Teso farming system, there are two rain seasons, and it is during this time that crops are planted. In the first rains, it is recommended (Serunjogi 1987), that any of the following major crops are planted: cotton, corn, peanuts, and millet. While in the second rains the major crops which are recom mended are: corn, sorghum, sweet potatoes, cassava, and cowpeas. Cassava is disregarded in the model because it is generally used as a resting crop for the field for up to two years. The inputs to the model are: (1) Number of oxen pair available to the farmer. (ii) Number of separate farm fields which the farmer wishes to cultivate. (iii) Size of each farm field (iv) Cropping pattern for each field in the first and second rains. A FORTRAN coding for this model is as follows: 149 C PROGRAM MIXMOD C C THIS PROGRAM ESTIMATES NUMBER OF HAND LABORERS AND C NUMBER OF ANIMAL PAIRS REQUIRED BY A SMALL HOLDER C IN A DEVELOPING COUNTRY. C C MIXMOD - MAIN PROGRAM C C PROGRAM DESCRIPTION C C ACCESS C EXECUTE THE PROGRAM C C EXTERNAL REFERENCES C SECROP - SUBROUTINE FOR VARIABLES OF SECOND RAIN C CROPS C XFASCR - SUBROUTINE FOR VARIABLES OF FIRST RAIN C CROPS C XFLGIN - SUBROUTINE FOR CROP IDENTIFICATION C PARMT2 - SUBROUTINE FOR WORKING DAY PARAMETERS C PROHED - SUBROUTINE FOR INTRODUCTORY REMARKS C PARMT1 - SUBROUTINE FOR IDENTIFICATION OF MONTHS C XMNANI - C CONFST - C XOPTAM - C XNCROP - C CRPIND - C C SET DIMENSION OF PARAMETERS C CHARACTER *5 DATE (22) CHARACTER*20 FCP (22), SCP (22) DIMENSION XHR1A (22), XHR2A (22), XHR3A (22), XHR4A (22), + XHRA (22), THRA (22), CHRA (22), AH (22), BH (22). CH + (22), DH (22),LFIN (22), XTLBA (22), WD (22), XNOLA + (22), XHRBA (22), THRH (22), XHROA (22),XHROH (22), + XHR1H (22), XHR2H (22), XHR3H (22), XHR4H (22), ARFH + (22), XHR6H (22), XHR7H (22), XHRH (22), CHRH (22), + ARFA (22), AA (22), BA (CA (22), DA (22), ARF (22), XT A + (22), XTLBH (22), XNOLH (22), XHRBH (22),QA (22), QH + (22), SA (22), SH (22), THA (22, 22), THH (22, 22), CHH + (22),TAH (22), XNH (22), CHHA (22), CHHH (22) 150 INTEGER XNAA (22), XNAH (22) DATA CHRA/22*0/, XHRBA/22*0/, CHRH/22*0/, XHRBH/22*0/ DATA XTLBA/22*0/, XTLBH/22*0/ OPEN (UNIT = 11, FILE = ’MIXMOD.OUT’, STATUS = ’NEW’) CALL PROHED (N, NAPA) CALL PARMT1 (DATE, TPH1, TPH2, TPH3, TPH4) L = 1 10 IF (L .LE. N) THEN WRITE (5, *) ’ENTER SIZE (HA) OF FARM FIELD NO \ L W RITE (5, *) REA D (5, *) A R F (L) LFIN (L) = L CALL CRPIND (L, ARF, NCI A, NC1B) CALL XFLGIN (L, NClA NC1B, FCP, SCP) IF (NClA .EQ. 0 ) THEN CALL XNCROP (XHROA XHROH) CALL SECROP (XHRA XHRH, NC1B) CALL XFASCR (XHROA, XHRA, XHROH, XHRH, THRA, THRH, + XNOLA XNOLH, L, ARF,THH, THA) ELSE IF (NClA .EQ. 1) THEN CALL COTTON (TPH1, THRA, THRH, XHR1A, XHR1H) CALL XFASCR (XHR1A, XHRBA, XHR1H, XHRBH, THRA, THRH, + XNOLA,XNOLH, L, ARF,THH, THA) ELSEIF (NClA .EQ. 2) THEN CALL XMILET (XHR2A, XHR2H, TPH2) CALL SECROP (XHRA, XHRH, NC1B) CALL XFASCR (XHR2A, XHRA, XHR2H, XHRH, THRA, THRH, + XNOLA,XNOLH, L, ARF,THH, THA) ELSEIF (NClA .EQ. 3) THEN CALL PEANUT (XHR3A, XHR3H, TPH3) CALL SECROP (XHRA, XHRH, NC1B) CALL XFASCR (XHR3A, XHRA, XHR3H, XHRH, THRA. THRH, + XNOLA,XNOLH, L, ARF,THH, THA) ELSEIF (NClA .EQ. 4) THEN CALL CONFST (XHR4A XHR4H, TPH4) CALL SECROP (XHRA, XHRH, NC1B) CALL XFASCR (XHR4A XHRA, XHR4H, XHRH, THRA, THRH, + XNOLA XNOLH, L, ARF,THH, THA) ELSE WRITE (5, *) ’ERROR IN DATA ENTRY’ 151 G O TO 110 ENDIF DO 20 LQ = 1, 12 CHRA (LQ) = CHRA (LQ) + THRA (LQ) CHRH (LQ) = CHRH (LQ) + THRH (LQ) XTLBA (LQ) = XTLBA (LQ) + XNOLA (LQ) XTLBH (LQ) = XTLBH (LQ) + XNOLH (LQ) 20 CONTINUE L = L + 1 GO TO 10 ENDIF CHHA (1) = 0.0 CHHH (1) = CHRH (1) XNAH (1) = INT (XTLBH (1) ) XNAA (1) = 0.0 CHHA (6) = 0.0 CHHH (6) = CHRH (6) XNAH (6) = INT (XTLBH (6) ) XNAA (6) = 0.0 DO 30 NH = 11, 12 CHHH (NH) = CHRH (NH) XNAH (NH) = INT (XTLBH (NH) ) XNAA (NH) = 0.0 CHHA (NH) = 0.0 30 CONTINUE DO 40 LY = 2, 5 IF (XTLBA (LY) .GT. 1.) THEN CALL XMNANI (ARF, ARFH, ARFA THA, THH, AG1, AG2, AG3, + AG4,LY, N, NAPA XTLBH, XTLBA, CHRA) CHHA (LY) = AG1 CHHH (LY) = AG2 XNAH (LY) = INT (AG3) XNAA (LY) = INT (AG4) ELSE XNAA (LY) = 1 XNAH (LY) = 0 CHHA (LY) = CHRA (LY) CHHH (LY) = 0.0 ENDIF CALL XOPTAM (CHHA CHRH, XNAA, XTLBH, CHHH, XNAH, + NAPA, LY) 40 CONTINUE DO 50 LC = 7, 10 152 IF (XTLBA (LC) .GT. 1.) THEN CALL XMNANI (ARF, ARFH, ARFA, THA, THH, AG1, AG2, AG3, + AG4,LC, N, NAPA, XTLBH, XTLBA, CHRA) CHHA (LC) = AG1 CHHH (LC) = AG2 XNAH (LC) = INT (AG3) XNAA (LC) = INT (AG4) ELSE XNAA (LC) = 1 XNAH (LC) = 0 CHHA (LC) = CHRA (LC) CHHH (LC) = 0.0 ENDIF CALL XOPTAM (CHHA, CHRH, XNAA, XTLBH, CHHH, XNAH, + NAPA, LC) 50 CONTINUE W RITE (5, 120) DO 60 NZ = 1, N WRITE (5, 130) LFIN (NZ), ARF (NZ), FCP (NZ), SCP (NZ) 60 CONTINUE W RITE (5, 100) N, NAPA W RITE (5, 101) DO 70 JO = 1, 12 WRITE (5, 110) DATE (JO), CHHH (JO), XNAH (JO), CHHA (JO), + XNAA (JO) 70 CONTINUE WRITE (11, 120) DO 80 NT = 1, N WRITE (11, 130) LFIN (NT), ARF (NT), FCP (NT), SCP (NT) 80 CONTINUE W RITE (11, 100) N, NAPA WRITE (11, 101) DO 90 JL = 1, 12 WRITE (11, 110) DATE (JL), CHHH (JL), XNAH (JL), CHHA (JL), + XNAA (JL) 90 CONTINUE W RITE (11, 112) DO 100 JE = 1, 12 IF (XTLBA (JE) .GT. 0.0 .AND. XTLBA (JE) .LT. 1.) XTLBA (JE) = + 1. IF (XTLBH (JE) .GT. 0.0 .AND. XTLBH (JE) .LT. 1.) XTLBH (JE) = + 1. NM = INT (XTLBH (JE) ) 153 NA = INT (XTLBA (JE) ) WRITE (11, 111) DATE (JE), CHRH (JE), NM, CHRA (JE), NA 100 CONTINUE STOP 110 E N D SUBROUTINE SECROP (XHRA, XHRH, NC1B) DIMENSION AH (22), BH (22), CH (22), DH (22), XHRA (22), XHRH + (22), XHR4A (22),XHR4H (22), AA (22), BA (22), CA (22), 4- DA (22) CHARACTER * 5 DATE (22) TPH5 = 1.5 TPH6 = 0.8 TPH7 = 5.0 T PH 4 = 1.5 IF (NClB .EQ. 0) THEN D O 10 NJ = 1, 12 XHRA (NJ) = 0.0 XHRH (NJ) = 0.0 10 CONTINUE ELSEIF (NClB .EQ. 4) THEN DO 20 KA = 1, 5 AA (KA) = 0 AH (KA) = AA (KA) 20 CONTINUE AH (6) = 180 AA (7) = 52 AA (8) = 15 AA (9) = 14 AA (10) = 0 AH (11) = 152TPH4 AA (11) = 0 AH (12) = 0 AA (12) = 0 AA (6) = 0 AH (7) = 600 AH (8) = 80 AH (9) = 265 AH (10) = 0 DO 30 LL = 1, 12 XHRA (LL) = AA (LL) XHRH (LL) = AH (LL) 30 CONTINUE ELSEIF (NClB .EQ. 5) THEN 154 DO 40 KN = l, 5 BA (KN) = 0 BH (KN) = BA (KN) 40 CONTINUE BA (6) = 0 BA (7) = 52 BA (8) = 15 BA (9) = 14 BA (10) = 0 BA (11) = 0 BA (12) = 0 BH (6) = 180 BH (7) = 600 BH (8) = 80 BH (9) = 265 BH (10) = 0 BH (11) = 210*TPH5 BH (12) = 0 DO 50 LK = 1, 12 XHRA (LK) = BA (LK) XHRH (LK) = BH (LK) 50 CONTINUE ELSEIF (NC1B .EG. 6) THEN DO 60 K = 1, 5 CA (K) = 0 CH (K) = CA (K) 60 CONTINUE CH (6) = 180 CA (7) = 52 CA (8) = 15 CA (9) = 14 CA (10) = 0 CA (11) = 0 CA (12) = 0 CA (6) = 0 CH (7) = 600 CH (8) = 85 CH (9) = 265 CH (10) = 0 CH (11) = 200TPH6 CH (12) = 0 DO 70 LI = 1, 12 XHRA (LI) = CA (LI) 155 XHRH (LI) = CH (LI) 70 CONTINUE ELSEIF (NClB .EQ. 7) THEN DO 80 KT = 1, 5 DH (KT) = 0 DA (KT) = DH (KT) 80 CONTINUE DH (6) = 180 DA (7) = 52 DA (8) = 15 DA (9) = 14 DA (10) = 0 DA (11) = 0 DA (12) = 0 DA (6) = 0 DH (7) = 600 DH (8) = 85 DH (9) = 265 DH (10) = 0 DH (11) = 200*TPH6 DH (12) = 0 DO 90 LM * 1, 12 XHRA (LM) = DA (LM) XHRH (LM) = DH (LM) 90 CONTINUE ELSE WRITE (5, *) ’ERROR IN DATA ENTRY’ ENDIF RETURN END SUBROUTINE XFASCR (QA, SA, QH, SH, THRA, THRH, XNOLA, + XNOLH, L,ARF,THH, THA) DIMENSION THRA (22), THRH (22), QA (22), XNOLA (22), ARF (22), + WD (22), OH (22), SH (22), XNOLH (22), ARFH (22), ARFA + (22), SA (22),CHRA (22), CHRH (22), XTLBA (22), XTLBH + (22), THH (22, 22), THA (22, 22) CALL PARMT2 (WD, RPIH, RPIA, WHPDH, WHPDA) DO 10 KK - 1, 12 THRH (KK) = (QH (KK) + SH (KK) ) *ARF (L) XNOLH (KK) = THRH (KK) / (WHPDH*WD (KK) *RPIH) THH (L, KK) = QH (KK) + SH (KK) THRA (KK) = (QA (KK) + SA (KK) ) *ARF (L) XNOLA (KK) = THRA (KK) / (WHPDA*WD (KK) *RPIA) 156 THA (L, KK) = QA (KK) + SA (KK) 10 CONTINUE RETU RN END SUBROUTINE XFLGIN (L, NC1A, NC1B, FCP, SCP) CHARACTER * 20 FCP (22), SCP (22) IF (NC1A .EQ. 0) THEN FCP (L) = ’NO CROP’ ELSEIF (NC1A .EQ. 1) THEN FCP (L) = ’COTTON’ ELSEIF (NC1A .EQ. 2) THEN FCP (L) = ’MILLET’ ELSEIF (NC1A .EQ. 3) THEN FCP (L) = PEANUTS’ ELSEIF (NC1A .EQ. 4) THEN FCP (L) = CORN’ ELSEIF (NC1A .LE. 0 .OR. NC1A .GT. 4) THEN FCP (L) = ’**ERROR**’ ENDIF IF (NC1B EQ. 0) THEN SCP (L) = ’NO CROP’ ELSEIF (NC1B .EQ. 4) THEN SCP (L) = ’CORN’ ELSEIF (NC1B .EQ. 5) THEN SCP (L) = ’SORGHUM’ ELSEIF (NC1B .EQ. 6) THEN SCP (L) = ’COWPEA’ ELSEIF (NC1B .EQ. 7) THEN SCP (L) = ’SWEET POTATOES’ ELSEIF (NC1B .EQ. 0) THEN SCP (L) = NO CROP’ ELSEIF (NC1B .LT. 4 .OR. NC1B .GT. 0) THEN SCP (L) = **ERROR**’ ELSEIF (NC1B .GT. 7) THEN SCP (L) = **ERROR**’ ENDIF IF (FCP (L) .EQ. ’COTTON ) THEN SCP (L) = ’NOT FEASIBLE’ ENDIF RETURN END SUBROUTINE PARMT2 (WD, RPIH, RPIA, WHPDH, WHPDA) DIMENSION WD (22) 157 WD (1) = 18 WD (2) = 15 WD (3) = 12 WD (4) = 12 WD (5) = 15 WD (6) = 18 WD (7) = 18 WD (8) = 15 WD (9) = 12 WD (10) == 12 WD (11) == 15 WD (12) == 18 RPIA = 0.8 RPIH - 0.9 WHPDH = 10 W HPDA = 6 R ETU R N END SUBROUTINE PROHED (N, NAPA) WRITE (5, 10) C 10 FORMAT(’ \THIS PROGRAM IS BEING DEVELOPED BY JOE + KIBALAMA\1X, +/’ VAT THE OHIO STATE UNIVERSITY’/’ \1X, + ’IT IS CONCERNED WITH ANIMAL POWER MODELLING OF + SMALL’/ ’ MX, + ’FARMS IN UGANDA: BASED ON TESO FARMING SYSTEM’/’ MX, + ’PROGRAM INPUTS ARE THE FOLLOWING’/’ ’,1X, + 1. NO OF SEPERATE FARM FIELDS’/* MX, + ’2. FARM SIZE IN HECTARES’/1 ’,1X, + ’3. NO. OF AVAILABLE OXEN PAIRS’/1 MX, + ’4. CROPPING PATTERN FOR EACH FIELD’/’ ’,/’ MX, + ’START BY FOLLOWING THE PROMPTS’/’ ’,/’ ’,1X, + ’ENTER Separate NO OF FARM FIELDS’) C READ (5, 30) N 30 FO RM A T (16) C WRITE (5, 60) C 60 FORMATf ’,lX,’NO. OF AVAILABLE OXEN PAIRS’) C RETURN 158 END SUBROUTINE PARMT1 (DATE, TPH1, TPH2, TPH3, TPH4) CHARACTER*5 DATE (22) DATE (1) = ’JAN’ DATE (2) = ’FEB' DATE (3) - ’MAR’ DATE (4) = ’APR’ DATE (5) = ’MAY’ DATE (6) = ’JUN’ DATE (7) = ’JUL’ DATE (8) = ’AUG’ DATE (9) = ’SEP’ DATE (10) = ’OCT’ DATE (11) = ’NOV’ DATE (12) = DEC’ TPH1 = 0.4 TPH2 = 1.5 TPH 3 = 1.0 TPH4 = 1.5 R E T U R N END SUBROUTINE COTTON (TPH1, THRA, THRH, XHR1A, XHR1H) DIMENSION XHR1A (22), THRA (22), THRH (22), XHR1H (22) XHR1H (I) = 180 XHR1A (2) = 28 X H R 1A (3) = 24 XHR1A (4) = 22 X H R 1A (5) = 7 D O 10 M R = 6, 11 XHR1A (MR) = 0 10 CONTINUE XHR1H (12) = 620*TPH1 XHR1A (12) = 0 XHR1A (1) = 0 XHR1H (2) = 300 XHR1H (3) = 300 XHR1H (4) = 200 XHR1H (5) = 120 DO 20 M F = 6, 11 XHR1H (MF) = 0 20 CONTINUE DO 30 NL = 1, 12 THRA (NL) = XHR1A (NL) 159 THRH (NL) = XHR1H (NL) 30 CONTINUE R ETU R N END SUBROUTINE XMILET (XHR2A, XHR2H, TPH2) DIMENSION XHR2A (22), XHR2H (22) XHR2H (1) = 180 XHR2A (2) = 52 XHR2A (3) = 15 XHR2A (4) = 14 XHR2A (5) = 0 XHR2A (6) = 0 DO 10 MM = 7, 12 XHR2H (MM) = 0 XHR2A (MM) = XHR2H (MM) 10 CONTINUE XHR2A (1) = 0 XHR2H (2) = 600 XHR2H (3) = 80 XH R2H (4) = 265 XHR2H (5) = 0 XHR2H (6) = 210TPH2 RETU RN END SUBROUTINE PEANUT (XHR3A, XHR3H, TPH3) DIMENSION XHR3A (22), XHR3H (22) XHR3A (1) = 0 XHR3A (2) = 52 XHR3A (3) — 15 XHR3A (4) = 14 XHR3A (5) — 0 XH R3A (6) = 0 XHR3H (1) = 180 XHR3H (2) = 600 XHR3H (3) — 80 XH R3H (4) = 265 XHR3H (5) = 0 XH R3H (6) — 545*TPH3 DO 10 MX 7, 12 XHR3A (MX) = 0 XHR3H (MX) = XHR3A (MX) 10 CONTINUE RETURN 160 END SUBROUTINE CONFST (XHR4A, XHR4H, TPH4) DIMENSION XHR4A (22), XHR4H (22) X H R 4A (1 = 0 X H R 4H (2 = 600 X H R 4H (3 = 80 X H R 4H (4 = 265 X H R 4H (5 = 0 X H R 4A (6 = 0 X H R 4H (1 = 180 X H R 4A (2 = 52 X H R 4A (3 = 15 X H R4A (4 = 14 XHR4A (5 = 0 X H R 4H (6 = 152* TPH 4 DO 10 MA = 7, 12 X H R 4A MA) = 0 X H R 4H MA) = XHR 10 CONTINUE RETURN END SUBROUTINE XMNANI (ARF, ARFH, ARFA THA, THH, AG1, AG2, + AG3, AG4, JW, N, NAPA, XTLBH, XTLBA, CHRA) DIMENSION ARF (22), ARFH (22), ARFA (22), THA (22, 22), THH (22, + 22),TAH (22), TAA (22), WD (22), XTLBH (22), XTLBA (22), + CHRA (22) CALL PARMT2 (WD, RPIH, RPIA, WHPDH, WHPDA) T TH = 0 TTHA = TTH DO 10 LU = 1, N TTHA = TTHA + THA (LU, JW) 10 CONTINUE TAA (JW) = WHPDA*WD (JW) *RPIA ARFA (JW) = (TAA (JW) /TTHA) *NAPA IF (XTLBA (JW) .GE. NAPA) THEN DO 20 LR = 1, N IF (ARF (LR) - ARFA (JW) .LE. 0.0) THEN ARFH (LR) = 0.0 ELSE ARFH (LR) = ARF (LR) - ARFA (JW) TTH = TTH + THH (LR, JW) *ARFH (LR) E N D IF 20 CONTINUE AG1 = NAPATAA (JW) AG2 = TTH AG3 = TTH/ (WHPDH*WD (JW) *RPIH) AG 4 = NAPA ELSE AG1 = CHRA (JW) AG2 = 0.0 AG3 = 0 AG4 = XTLBA (JW) ENDIF RETURN END SUBROUTINE XNCROP (XHROA, XHROH) DIMENSION XHROA (22), XHROH (22) D O 10 MK = 1, 12 XHROA (MK) = 0.0 XHROH (MK) = 0.0 CON TIN UE RETU RN END SUBROUTINE XOPTAM (CHHA, CHRH, XNAA, XTLBH, CHHH, + XNAH, NAPA, LD) INTEGER XNAA (22), XN0AH (22) DIMENSION CHHA (22), CHRH (22), XTLBH (22), CHHH (22) IF (NAPA .EQ. 0) THEN CHHA (LD) = 0.0 XNAA (LD) = 0 CHHH (LD) = CHRH (LD) XNAH (LD) = XTLBH (LD) ENDIF IF (CHHA (LD) .EQ. 0.0) THEN XNAA (LD) = 0 ENDIF RETU RN END SUBROUTINE CRPIND (L, ARF, NC1A, NC1B) DIMENSION ARF (22) W RITE (5, 10) L, A R F (L) WRITE (5, 20) READ (5, *) NCI A, NC1B RETURN 162 10 FORMAT(’ ’/SIZE OF FARM FIELD NO’,lX,I3,lX/=\F5.2,lX,’(HA)’/) 20 FORMATf ’/ENTER CROPPING PATTERN FOR FIRST AND + SECOND’, IX, + ’RAINS, SEPARATED BY A COMMAV/’FIRST CROPS ARE: COTTON + = i\ix, +’MILLET = 2; PEANUTS = 3; MAIZE = 47SECOND CROPS ARE: + M A IZE’, IX, + ’ = 4; SORGHUM = 5; COWPEAS = 6; SWEET POTATOES = 7’/) END APPENDIX B LOADING CART DESIGN ANALYSIS 163 164 B.1 Working Drawings An outline of some of the working drawings is shown in the following Figures. 1061 178 — t r ____ Part Oty Section Size 1 1 Square 1060 DRW NO 3 LOWER CHASSIS QTY:1 2 2 Square 762x 755 3 2 Square 1360 X1353 PROJECT Traction Animal Dynamometer 4 1 Square 2649 x 621 DRAWN BY Joe Kibalania J3tm: inches 5 2 Plate 187x 51x 13 Agricutura Engineering Dept.. 6 2 Square 186 x 89 8 8 7 1 Plate X X Figure B.l Layout of the lower part of the chassis. a 1276 1029 DRW NO 3A UPPER CHASSIS QTY:1 619 PROJECT Traction Animal Dynamometer DRAWN BY Joe Klbatama Dim: mm 117 Agrlcutural Engineering Dept. OSU «■ 356 189 Part aty Section Size * Part Qtjj' Section Size 1 1 Square 972 4 Square 483 2 2 Square 189 5 A Square 145 3 2 Square 1276 6 8 plate 6 x 76 x 19 166 Figure B.2 Layout of the upper part of the chassis. 1270 -1168 IHO- 152 R22 R5 62-* x 6 x 25 16 x 16 x 51 DRW NO 1 REAR SHAFT OTY: 1 IS PROJECT T radon A rtind Dynamometer Z Keyway 16 x16 x51 to ft stppied key 3. Filet elzee R are only gJdelnee MATERWL AIS KK5 CD DRAWN BY Jo* Kbdama | D** A g tailrd En^eerhg Dept. OSU Figure B.3 The rear shaft. DRW NO 2 REAR SHAFT HUB QTY: 2 PROJECT tracton Artnal Dynamcmetr MATERIAL AISI 1045 CD DRAWN BY Joe KIbalama Dim: mm Agricultural Engineering Dept.. OSU Figure B.4 The rear shaft hub. 260 168 Flanged adopter far twh sprockets 108 10 x 10 x25 M 6- 1 m 1.25 Remarks 2 DRW NO 6 Intermediate shaft QTY: 1 Bearing to be located at ports 1 and 3. PROJECT Traction Animal Dynamometer 11 tooth sprocket to be at port 2. MATERIAL AISI 1045 CD Double sprocket rtog fastened an to a fknged adcpter to be located at pt 4. DRAWN BY Joe Klbalama Dim: mm Suggested fltot rad 4 Agricultural Engineering Dept.. OSU Key seat to match applied key. 169 Figure B.5 The layout of the intermediate shaft. Mate treaded collar (adapter) M 36-2 210 keyed on 20 mm shaft 168 x25 ke t way 108 3 x 6 x 13 key way 2 Beartig to be located at pokMs 1 and 3. DRW NO 7 Final drive shaft QTY; 1 Point 2 Is location of band braka PROJECT Traction Animal Dynamometer Mutti sprocket rhg be located at pt 4. MATERIAL AISI 1045 CD on the cotter. Suggested fBet rad 4 mm DRAWN BY Joe Klbalama Dbm mm Key seat to match stppllsd key. Agricultural Engineering Dept OSU Figure B,6The layout of the final drive shaft. Bend brake Inrtig 5 x 25 mm 4 equal pcs rtvetted on 3 mm band Bend ends V to sJk mocnfrig brakets 3 - 1 127 597 DRW NO 10 Bend Brake QTY: 1 PROJECT Tracfion Animal Dynamometer DRAWN BY Joe Ktxkma Din mm AofcUfcjd E :rtfieerhg Dept, OSU Figure B.7Band and Brake lining layout. DYNO-CART PARTS UST Chassis frame Drlvhg wheals Stabltzhg wheel Drivhg sprocket Intermeddle sprocket Final dve sprocket Brake dun Brd«e aduatog lever beamy DracMet 10. Eqdpmsnt platform DRW NO 3E DYNO-CART ASSEMBLY PROJECT Trodon Antnd Dynamometer DRAWN BY Joe Kbdama Dfcrt nvn Apfcutud En^eerhg Dept. OSU Figure B.8 The dyno-cart assembly. - j N) 146 r . " - ~ s u 64 + DflW NO 14 PI7OT TTORT BRACKET lOTYil PROJECT Tradon Arind Dvnanomstar MATERAL SAE 1020 _ _ DRAWN BY Joe Kbdama Dht mm AortouHtfol E nrtM tta D*ot 06U 173 Figure B.9 Pivot bracket for the brake band. DRW NO 17 POWER SCREW | QTY:1 WOJbCI Trocton A rM Dynamomaier DRAWN BY Jos Kbdama Din mm Afftaltud ErtfnMrhg D«pt. OSU 174 Figure B. 10 The brake actuating power screw. 16 T DRW NO 15 POWER SCREW COLLAR PROJECT Trodon Artnal Dynamometer MATERIAL SAE 1020 DRAWN BY Joe Kfcdama Dht mm AgricUturd E n £ w h g Dept. QSU Figure B.ll The power screw collar. 176 B.2 Braked Wheel Traction Dynamics W T i— P _ e Rsx Figure B.12 Free body kinematics of a braked wheel. The principle of the dyno-cart operation is based on braked wheel traction dynamics. In Figure B.12 R, is the total ground reaction, T is the brake torque on the wheel and W is the axle loading. The horizontal component of R, is given as: R = F + MR (B .l) Thus considering equilibrium P = F + M R (B.2) Summing moments about the center of the wheel we have: 177 T = (F + MR) ro - e (B.3) But Liljedahl et a]. (1989) argue that: MRr = eR (B.4) ° *y Therefore, T = Fr (B.5) where F is the gross traction MR is the motion resistance. From Standard D 497 ASAE(1992) and using the corrected version (see Section 4.9 of this dissertation) we have: L. = i^+0.79 -0.75c"0'3C**1 (B.6) w c a 178 B.3 Shaft Design The following three equations (Shigley and Mischke, 1989) were used in determining the shaft size. At critical points where there is abrupt change in size equation B.7 was used. (B.7) W here dj = shaft diameter at the critical point "i" Kt — stress concentration factor FS = factor of safety (1.8) Se = endurance limit of the shaft material corrected for surface, size and load factors. Ma = alternating bending moment at the critical point Tm = steady torque at the critical point Sull - ultimate tensile strength of the shaft material. In case there is no torque and bending moment, the design is based on shear stress as follows: ^ 16 V FS (B -8) ' = n| 37r(.5)Syp W here 179 V = shearing force Syp = yield strength of the shaft material In case there is no abrupt change in size equation B.9 is used. 32 FSi (B.9) - ^ [ 4 M a2 + 3 T 2] n Y * m J 180 B.4 Brake Band Analysis Q (Atuating force) Q 2 a Brake drum Band Brake Figure B.12 Free body diagram of the band brake. Because of friction and the direction of rotation of the brake drum the tension in the band, Q2 is less than (Orthwein, 1986). Under equilibrium conditions the following equations ensure: Oj - = 0 (B IO) Qi - Q2 - Tb/R (B. 11) where (x = coefficient of friction between the brake lining and the brake drum 181 Tb = torque on the braking Q2 = actuating force (B.12) (B.13) Assuming negligible loss between the transmission and the brake shafts, G). a1 1 b - 1 — a (B.14) where T = torque on the rear shaft o>d = angular speed of the rear shaft (i»b = angular speed of the final drive shaft But from equation B.5 (B. 15) r Substituting equations B.5 and B.16 into B.15 and rearranging where n, is the gear ratio between the rear and the final drive shaft. (B. 16) APPENDIX C INSTRUMENT SPECIFICATIONS 183 184 C.1 Force Transducer The capacity of the electrical strain gage load cell is 8.9 kN. There was no calibration chart available hence a standard calibration procedure was used. Figure C.l shows the calibration curve obtained based on 10 volt excitation. 7.0 + - ...... - + ------ 6.C > t f------' 1 i ^ 5.0 t 4 + X ' ' rx .o f ------1- 1— I .i.c j .-j— _ 2.C • r. - ■ ■■ ■■ - ...... IX i - ■ t i ■ ■ "i----- + ...... C'.c * i * ! 0.0 0.5 l.c 1.5 2.0 2.5 3.0 Tensile lood (kM) Figure C. 1 The calibration curve of the force transducer excited with 10 Volts. C.2 Chart Recorder Type : 2 pen portable recorder Model : Primeline 6723 Manufacturer: SOLTEC Distribution Power supply: Either 110 V or 12/24 V battery supply C.3 Veterinary Rectal Probe 185 Supplier : Omega Engineering Inc. Model : VIP-T Type : Thermocouple type T (copper-constantan) sensors. Complete with stainless steel tip and a flexible polyurethane tubing. Length of the entire probe is 1.8 m. C.3.1 Digital Thermometer Supplier : Omega Engineering Inc. Model : HH22/23 Input thermocouple types: J (iron-constantan (copper/nickel)) K (chromel (nickel/chromium)-alumel (nickel/aluminum)) T (copper-constantan) Features : Dual thermocouple input ports Power supply : 9 V battery C.4 Heart Rate Monitor Manufacturer : Polar Electro Oy (Finland) Model : Polar Pacer -HRM Components: Sensor, transmitter, receiver Power supply : Receiver and transmitter use lithium battery BR2325 APPENDIX D EXPERIMENTAL DATA 186 187 D.l Oxen Features Table D.l Particulars of the oxen used in the experiments. Name Average weight H oof base Hip height (kg) (m) (m) Louis (near) 809 1.30 1.42 Clark (far) 705 1.30 1.37 Average dailv feed ration Hay*: 7.5 kg Hayb: 4 kg Corn: 1.5 kg Wheat: 2 kg (Note hay* ( first cut hay) which is harvested in June is less nutritious than hayb (second cut) which is harvested in August) The animals were fed twice, early in the morning and late in the afternoon. The average ration for each animal is shown in Table D.l. D.2 Oxen Yokes Figures D.l shows a sketch of a double neck yoke with a dropped hitch point. This yoke was used when testing paired animals. 188 Wooden Bow Chain r a g Tongue Ting Figure D. 1 An outline of the drop hitch neck yoke. Figure D.2 A Sketch of single neck yoke. Figure D.5 shows a sketch of the neck yoke used while testing a single yoked draft animal. D.3 Experimental Data Tables D.l through D.10 show the data obtained for the different tests done. 189 Table 0.1 Experiment No. 1 Date and Time : 4 .1.93 / PM Ixication of end flags: I and 12 Fast: 6 and 7 West Animal weight (kg) Initial Final l^ouis 814 801 Clark 712 708 Ambient temperature (C) Average dry temperature : 2 Average wet temperature : 2 Hear axle load : 2.5 kN Average tractive efforl : 0.82 kN Tractive effort inclination angle : 12 degrees Fraction surface : Asphalt Work-cycle/Lap Observation lim e Work-cycle/Lap Observation Time Point (Min :Sec ) Point (Min :Sec ) 1/2 7 2:39 2/4 1 31:16 12 3:44 6 32:21 1/3 1 4:02 7 32:40 6 5:10 12 33:43 9 5:49 3/1 1 44:58 12 6:29 6 45:57 1/4 1 6:50 7 46:17 6 8:06 12 47:24 8 8:22 3/2 I 47:37 12 9:20 6 48:44 2/1 1 13:05 7 49:04 6 24:08 12 50:16 7 24:22 3/3 1 50:33 12 25:23 50:58 2/2 1 15:39 9 52:26 5 26:33 12 53:08 6 26:47 3/4 1 53.21 7 27:03 o 54:34 12 28:11 7 54:48 2/3 1 28:27 12 55:58 6 29:35 7 29:53 12 31:01 Table 0.2 Experiment No. 2 190 Date and Time : 4.3.93 / PM Indention of i he end flags: 1 and 12 liast;6 an d 7 West Animal weight (kg) Initial Linal I ouis 814 800 Clark 725 715 Ambient temperature (C) Average wet temperature : 2 Average dry temperature : 4.5 Rear axle load : 2.5 kN Average tractive effort : 2.2 kN t ractive effort inclination angle: 12 degrees Traction surface : Asphalt Initial heart rate of Louis: 50 Initial rectal temperature of Clark: 58.0 Work -cycle/I .ap Observation Time Rectal Temperature Heart rate 0 (Min :Sec (Celsius) Pulses/min.) 1/1 1 0.00 38.0 50.0 6 1.01 7 1.15 12 2.22 1/2 1 2.35 6 3.44 7 4,01 12 5.05 1/3 1 5.20 6 6.25 7 6.43 12 7.48 1/4 1 8.01 f> 0.08 7 y 22 12 10.31 38.1 (>2.0 2/1 1 18.31 (> 10.35 7 10.5 1 12 21.00 Table D.2 (continued) 2/2 I 21.12 6 22.21 7 22.34 12 13.47 2/3 I 24.03 6 13.17 7 11.33 12 26.37 2/4 1 26.49 6 27.51 7 28.06 12 29.39 3/1 1 36.57 6 37.58 7 38.12 12 39.15 3/2 1 39.26 6 40.29 7 40.41 12 41.42 3/3 1 41.54 6 42.54 7 43.10 12 44.15 3/4 1 44.29 6 45.36 7 45.52 12 46.55 4/1 1 53.19 6 54.25 7 54.40 12 55.47 192 Table D.3 Experiment No. 3 Dale and Time : 4.5.93 / AM Location of the end flags: 1 and 12 I vast; 6 and 7 Wesi Animal weight (kg) Initial Final Louis 815 80] Clark 717 710 Ambient temperature (C) Average wet temperature : 2 Average dry temperature : .1.5 Rear axle Lud : 2.5 kN Average tractive effort : 0.96 kN Tractive effort inclination agnle: 12 degrees Tractive surface : Asphalt Initial heart rate of louis: 49 Initial rectal temperature of Clark: 18.2 Work-cycle/I^tp Observation Time Body Temp. Heart rate Point (Min:Sec ) (F) (bcats/min) 1/1 2 0:00 18.2 49 5 0:38 7 1:03 12 2:10 1/2 1 2:20 (i 3:25 7 3:39 12 4:40 1/1 s 5:02 6 5:59 7 6:15 12 7:16 i/4 1 7:27 6 8:35 7 8:50 12 9:54 1/5 1 10:06 0 1 1:16 7 11:28 12 12:36 Table 0.3 {continued) 1/6 1 12:49 6 13:54 7 14:06 12 15:07 1/7 1 15:25 6 16:36 7 16:49 12 17:58 1/8 1 18:17 6 19:29 7 19:42 11 20:36 2/1 2 30:51 6 31:41 7 31:52 12 32:58 2/2 1 33:17 6 34:21 7 34:33 12 35:38 2/3 2 36:06 6 36:59 7 37:10 11 38:02 2/4 2 38:50 6 39:43 7 39:57 12 41:06 2/5 2 41:35 6 42:23 7 42:47 11 43:42 2/6 2 44:33 6 45:30 7 45:45 12 46:54 2/7 2 47:28 (> 48:23 194 Table D.4 Experiment No. 4 Date and Time : 4.6.92 / AM [x»aciion of the end flags: 1 and 12 liast: 6 and 7 West Animal weight (kg) Initial Final Ixjuis 806 794 ('lark 714 702 Ambient temperature (C) Average dry temperature : 9.8 Average dry temperature : 6 Rear axle load : .1.2 kN Average tractive effort : 1,65 kN Tractive effort inclination: 12 Tractive surface : Asphalt Initial heart rate or Louis: 48 Initial rectal temperature of Clark:18.1 100.5 Work-cycle/I jip Observation Time Hody Temp. Heart rate Point (Min :Sec ) (1;) (beats/min) 1/1 2 0:00 28.1 48 6 0:56 7 1:15 12 2:21 1/2 1 2:19 6 2:48 7 4:01 12 5:12 1/2 1 5:11 6 6:45 7 6:59 11 8:00 28.1 ‘8) 2/1 *> 17:41 6 18:19 7 18:58 1 1 19:58 2/2 ? 20:19 6 21:25 7 21:58 12 22:19 Table D.4 (continued) 2/3 1 23:36 6 24:52 7 25:20 11 26:08 2/4 2 26:59 6 28:01 7 28:34 11 29:24 3/1 2 47:48 6 48:48 7 49:11 12 50:26 3/2 2 51:04 6 52:04 7 52:22 12 53:44 3/3 1 54:06 6 55:23 7 55:42 11 56:43 3/4 2 57:33 6 58:37 7 59:00 II 60:00 196 Table 0.5 Experiment No. 5 Date and Time : 4.6,93 / PM luxation of end flags: 1 ans 2 West; 3 and 4 Hast Animal weight (kg) Initial Final U>uis 802 793 Clark 710 704 Average ambient dry temperature : IS Celsius Average ambient wet temperature : 10 Average tractive effort : 2.23 kN Tractive effort inclination agnle : IS Tillage implement: 300 mm moldboard plow worked in silt loam corn stubble Initial heart rate of Ixiuis: SO Initial rectal temperature of Clark: 37.9 Work-cycle/l^ip Observation Time Body Temp. Heart rate Point (Min :S ec) (H) (beats/ti 1/1 2 0:00 37.9 50 3 1:13 1/2 4 1:30 1 2:53 1/3 T 3:09 3 4:42 38.4 94 2/1 4 12:51 1 14:08 2/2 ■> 14:28 3 15:48 38.5 101 3/1 4 28:34 1 29:49 3/2 2 30:10 3 31:34 38.0 111 4/1 4 45:58 1 47:20 4/2 1 47:45 3 49:11 38.6 123 S/1 4 50:44 ] 51:56 S/2 -i 53:02 3 54:15 38.7 128 6/1 4 65:37 1 66:46 6/2 ■> 67:06 3 68:19 .38.0 127 197 Table D.6 Experiment No. 6 Date and Time : 4.8.9? / AM I .ocution of end flags : 1 and 12 i-uisi; 6 and 7 West Animal’s weight (kg) Initial Final l^ouis 806 792 Clark 711 701 Average ambient dry temperature (C): 12.5 Average ambient wet temperature (C): 9.5 Rear axle load: .V2 kN Average tractive effort: 2.15 kN T ractive effort inclination: 12 Tractive surface: Asphalt Initial heart rate of Ixjuis: 51 Initial rectal temperature of Clark:?8.1 Work-cycle/I ap Observation lime Body Temp. Heart rate Point (Sec ) (!') (beats/min) I/I 1 0 28.1 51 6 7? 7 98 12 168 28.2 111 1/2 I 976 6 1049 7 1077 12 114? 28.2 100 I/? ? 20? 1 6 2071 7 2089 12 2155 28.2 10? 1/4 1 27?6 6 2802 7 2827 12 2880 28.2 1 16 1/5 1 ?58? 6 2651 7 2670 12 272? 28.2 112 198 Table D.6 (continued) 1/6 1 4428 6 4494 7 4511 12 4580 58.1 120 1/7 1 5242 6 5516 7 5555 12 5404 58.4 154 Heart rate drop of lx>uis after lap 1 Time H ear rate Time Hear rate (Sec) Ucats/min (Sec) Bcats/min I) 111 74 74 2 110 78 71 4 108 81 70 7 107 85 69 8 106 94 69 10 104 99 68 15 102 112 68 15 101 116 67 18 99 127 65 22 97 142 61 27 95 161 62 52 90 168 65 57 88 172 62 45 85 176 61 54 78 201 58 58 77 256 59 71 76 199 Table 0.7 Experlemnt No. 7 Dale and Time : 4.8.93 / PM l.ocation of end flags : 1 and 12 West; 6 and 7 Fast Initial Final Clark’s weight (kg) 708 704 Average ambient dry temperature : 14 Average ambient wet temperature : 12 Rear axle load : 2.5 kN Average tractive effort : 0.62 kN Tractive effort inclination angle: 12 Tractive surface : Asphalt Initial rectal temperature of Clark: 37.9 Work-cycle/I^ip Observation lime Body Temp. Point (Sec ) (I7) 1/1 1 0 37.9 6 70 7 108 12 181 1/2 1 200 6 272 7 287 12 370 38.3 2/1 1 567 6 668 7 686 12 750 2/2 1 760 6 833 7 851 12 918 38.6 3/1 1 1323 6 1388 7 1400 12 1474 3/2 I 1485 6 1553 7 1570 12 1642 38.7 200 Table D.8 Experiemnt No. 8 Dale and Time : 4.8.93 / PM I ocation of end flags : 1 and 12 West; 6 and 7 East Initial Final Louis's weight (kg) 796 790 Average ambient dry temperature (C) ; 14 Average ambient wet temperature (C) : 12 Rear axle load : 2.5 kN Average tractive effort : 0.62 kN Tractive effort inclination: 12 Tractive surface : Asphalt Initial rectal temperature of I.ouis:38.1 Work-cycle/I .up Observation lim e Body 1'emp. Heart rate Point (Sec ) (I) (Pulses/min) 1/1 1 0.00 38,1 52 6 70.00 7 108.00 12 181.00 1/2 1 200.00 6 272.00 7 287.00 12 370.00 38.3 81 2/1 1 567.00 6 668.00 7 686.00 12 750.00 2/2 1 760,00 6 833.00 7 851.00 12 918.00 38.6 9 4 3/1 1 1260.00 6 1388.00 7 1406.00 12 1474.00 3/2 1 1485.00 6 1553.00 7 1570.00 12 1642.00 39.1 201 Table D.9 Experiment No. 9 D ate and 'l ime : 4.1(1.‘>.1 / AM I i teal ion of end flags : 1 and 4 West; 2 and 3 East Animal’s weight (kg) Initial Final Louis 800 789 Clark 708 701 Average ambient dry temperature (C ): 10 Average ambient wet temperature (C ): 26 Rear axle load : .1.2 kN Average tractive effort : 2.8 kN Tractive effort inclination: 12 Tractive surface : Asphalt Initial heart rate of Louis: 50 Initial rectal temperature of Clark: 17.0 Work-cycle/l^ap Observation Time Body Temp. I Icurt rate Point (Sec ) (F) (beats/min) 1/1 I 0:00 17.9 50 T 1:04 18.2 115 2/1 1 8:24 4 9:11 18.1 111 1/1 1 21:18 T 22:28 18.7 121 4/1 1 11:28 4 14:28 18.9 120 202 Table 0.10 Experiment No. 10 D ate and Time : 4,12.9.1 / AM Location of end flags : 1 and 12 liasi; 6 and 7 West Animal’s weight (kg) Initial Final Louis 816 805 Clark 722 711 Average ambient dry temperature (C) : 10 Average ambient wet temperature (C ): 8 R ear axle load : 2.5 kN Average tractive effort : 0.64 kN Tractive effort inclination: 12 Tractive surface : Asphalt Initial heart rate of Ijouis: 50 Initial rectal temperature of Clark:17.9 Work-cycle/Lap Observation Lime Rectal Temp. Heart aret Point ( Min. Sec ) (Celsuis) (Pulses/mm) 1/1 1 0.00 17.9 50 6 I 10 7 1.10 12 2.12 1/2 1 2.48 6 .1.58 7 4.17 12 5.24 1/1 1 5.51 6 7.01 7 7.25 12 8.15 1/4 I 8.51 <> 10.00 7 10.17 12 11 29 2/1 7 27.(8) 12 28.10 I 28.24 0 29.17 7 29.54 12 11.07 1 11,21 U 12.14 203 Table D.10 (continued) 2/3 7 32-50 12 34.03 1 34.13 6 35.24 2/4 7 35.40 12 36.53 3 /I 1 44.34 6 45.38 7 45.53 12 46.56 3/2 1 47.06 6 48.14 7 48.32 12 49.39 3/3 1 49.52 6 51.01 7 51.18 12 52.30 3/4 1 52.44 6 53.58 7 54.13 12 55.25 4 /1 1 64.05 6 65.20 7 65.31 12 66.42 4/2 I 67.03 6 68.07 7 68.25 12 69.36 4/3 1 69.55 6 71.11 7 71.27 12 72.42 4/4 I 73.01 6 74.21 1 74.36 12 75.55 5/1 1 83.06 0 84.06 7 84,13 12 85.27 5/2 1 85.52 6 86.55 7 87,1 1 12 88,24 204 Table D.10 (continued) 5/3 1 88.38 6 89.53 7 90.06 12 91.20 5/4 1 91.40 6 92.51 7 93.10 12 94.22 6/1 1 105.32 6 106.36 7 106.52 12 108.07 6/2 1 108.23 (i 109.35 7 109.49 12 110.55 6/3 1 111.13 6 112.26 7 112.46 12 113.53 6/4 1 114.08 6 115.13 7 115,28 12 116.37