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Challenges and Opportunities of Small-Holder Pig Production and
Marketing in Western Kenya
by
Michael Levy
A Thesis
presented to
The University of Guelph
In partial fulfillment of requirements
for the degree of
Doctor of Philosophy
in
Population Medicine
Guelph, Ontario, Canada
© Michael Anthony Levy, 2014
ABSTRACT
CHALLENGES AND OPPORTUNITIES OF SMALL-HOLDER PIG PRODUCTION AND MARKETING IN
WESTERN KENYA
Michael Anthony Levy Advisor:
University of Guelph, 2014 Dr. Cate Dewey
In Western Kenya pigs are important for the livelihood of smallholder farmers and
create income opportunities for pig butchers and their employees. Improvements to marketing
systems can contribute to poverty alleviation, increase consumer and producer benefit, and
stabilize food supplies. The objective of this thesis was to evaluate the organization and
efficiency of local pork marketing and the challenges of butchers and farmers in rural and peri-
urban settings of Western Kenya.
A cross-sectional, observational study was conducted on fifty pig butchers to collect
their demographic information, challenges, operating practices, and costs. Factors associated
with pig prices, pork prices, marketing and operating costs, profit, and marketing margins were
determined using mixed and generalized linear models. A unique algorithm that emulates least-
cost pig feeding was developed to assess the impact of season, average daily gain, opportunity
cost of farm grown feed, pig weight, and butcher price variation on farmers’ maximum revenue
and profit potential when pigs are sold to butchers.
Butchers were 36.5 years (SD=10.71) of age, had been in business for 8.5 years (SD =
7.41); 31% had less than 2 years experience. Butchers were central in coordinating activities
required to connect pig farmers to pork consumers. Capital constraint, government license
fees, and pig prices were common challenges to butchers. Yearly licenses and fees are double
the cost of a 30 kg pig (2346 KES). Slaughter plus inspection fees are 247 KES per pig. The
butcher business was competitive and profit margins were moderate, ranging from 5% to 10%.
Marketing margins ranged from 27% to 41% for 45 and 22 kg pigs respectively. Butcher
education was positively associated with pork prices charged to consumers and butcher profit.
Butchers in larger markets had higher pork prices, pig prices paid to farmers, marketing and
operating costs, profit, and marketing margins.
Variation in average daily gain of pigs, opportunity costs of feed, and weaning season
resulted in feed cost differences of 982 KES, 947 KES, and 379 KES respectively for 30 kg market
pigs. Variation in revenues attributable to butcher and season for a 30 kg pig were 744 KES and
225 KES respectively.
iv
DEDICATIONS
This thesis is dedicated to the memory of Rodger and Hazel Gray, whose warmth,
optimism, and unconditional love inspired four generations within my loving family.
v
ACKNOWLEDGEMENTS
Dr. Cate Dewey, thank you for your mentorship, support, and friendship throughout this
research project. You have inspired me and so many other people through your acts of kindness
and dedication. You have invested so much of your time in me. I will always appreciate all that
you have done!
Dr. Alfons Weersink and Dr. Zvonimir Poljak, as committee members, thank you for your
patience, insightful comments, and numerous writing tips. Thank you also for the time you put
into editing papers, providing guidance and listening.
Dr. Florence Mutua, thank you for introducing me to your wonderful country Kenya, and
for all of the co-ordination and communication you did for this project. I so enjoyed your gifts of
negotiating and communicating.
Pig butchers and farmers in Western Kenya, you offered so much time to someone you
knew so little; I hope we gave back enough to you to have made it worthwhile for you to
participate. Government inspectors, village elders, Kenyan research assistants, thank you for
supporting this project and for your efforts.
Veterinarians without Borders, Canada and the University of Guelph contributed to the
funding of the research. The Veterinary Director General of Kenya and the University of Guelph
Research Ethics Board approved this research.
vi
William Sears provided statistical guidance. Dr. Judith Bell provided writing assistance.
Karen Richardson provided all kinds of tactical support. Sally, Linda, Julie, Mary and Sandra
provided Administrative support and encouragement. Sandy Auld provided Ethics support.
Thank you everyone.
Dr. Andria Jones, Dr. Jan Sargeant, Dr. David Pearl, Dr. Peter Physick-Sheard, and Dr.
Wayne Pfeiffer thank you for providing such intriguing graduate courses.
Thank you Laura F, Natalie C, Natalia S, Dan S, Steve R, Claire W, Janet H, Pasha M, Kevin
M, Andrea T (and other fellow graduate students) for your friendship, support and inspiration.
Michele, Alex, Mom, Tony, Dad, Terri, little Miss Tweed, the rest of my family, and my
dear friends, thank you for your unconditional love and support.
To my dear Elizabeth, thank you for being so supportive and patient in the final stretch,
and thank you for your editing help.
vii
STATEMENT OF WORK DONE
Funding for this project was obtained by Dr. Cate Dewey, through Veterinarians Without
Borders.
Questionnaires were created and administered by Mike Levy, with the guidance of Dr.
Cate Dewey and support of Dr. Florence Mutua. Dr. Florence Mutua co-ordinated contact with
Livestock officers, village elders and butchers that participated in the study. Additional data
collection was co-ordinated by Dr. Cate Dewey, Dr. Florence Mutua and Natalie Carter.
Data was collated, cleaned, and coded in Microsoft Excel, and analyzed in SAS, by Mike
Levy. Statistical analysis for all chapters was completed by Mike Levy, with the help of William
Sears and Drs. Cate Dewey, Alfons Weersink, and Zvonimir Poljak. The algorithm for
determining the feasibility of semi-intensive pig rearing was developed by Mike Levy. The
chapters were written by Mike Levy, with formal edits and feedback provided by Drs. Cate
Dewey, Alfons Weersink and Zvonimir Poljak.
viii
TABLE OF CONTENTS
DEDICATIONS .................................................................................................................................. iv
ACKNOWLEDGEMENTS .................................................................................................................... v
STATEMENT OF WORK DONE ........................................................................................................ vii
TABLE OF CONTENTS..................................................................................................................... viii
LIST OF TABLES .............................................................................................................................. xvi
LIST OF FIGURES ............................................................................................................................ xix
CHAPTER 1....................................................................................................................................... 1
Introduction and Objectives ........................................................................................................ 1
1.1. Kenya’s agricultural sector ............................................................................................... 1
1.1.1. Brief history of Kenya’s agricultural sector ................................................................ 1
1.1.2. Role of livestock ......................................................................................................... 3
1.2. Kenya’s pig industry .......................................................................................................... 4
1.2.1. Pork value chain in Kenya .......................................................................................... 4
1.2.1.1. Pig farmers .............................................................................................................. 6
1.2.1.2. Pig butchers ......................................................................................................... 7
1.2.1.3. Consumers ........................................................................................................... 8
1.2.1.4. Government ........................................................................................................ 8
1.2.1.5. Conclusion ........................................................................................................... 8
1.3. Pig husbandry ................................................................................................................... 9
ix
1.3.1. Diversification ............................................................................................................ 9
1.3.2. Intensification .......................................................................................................... 10
1.3.3. Feeding pigs ............................................................................................................. 11
1.3.3.1. Common feeds .................................................................................................. 11
1.3.3.2. Feed research .................................................................................................... 12
1.3.3.3 Nutrient requirements ....................................................................................... 13
1.3.3.4. Fulfilling nutrient requirements ........................................................................ 14
1.4. Livestock marketing systems in developing countries ................................................... 15
1.4.1. Value chain analysis ................................................................................................. 16
1.4.1.1. Performance Measures ..................................................................................... 17
1.4.2. Local and informal markets ..................................................................................... 18
1.4.3. Challenges and limitations ....................................................................................... 18
1.4.4. Transaction costs ..................................................................................................... 19
1.4.4.1 Overcoming transaction costs and lowering risk ............................................... 21
1.4.4.2. Factors associated with marketing and transaction costs ................................ 21
1.4.5. Seasonality of markets in Sub-Saharan Africa (SSA) ................................................ 22
1.4.6. Pig marketing in SSA ................................................................................................ 23
1.4.7. Conclusion ................................................................................................................ 24
1.5. Extension and Education in Kenya.................................................................................. 24
1.5.1. Common extension typologies ................................................................................ 25
x
1.5.2. Education for pig butchers ....................................................................................... 26
1.5.3. Limitations of education and extension .................................................................. 27
1.6. Thesis objectives ............................................................................................................. 27
1.7. References ...................................................................................................................... 30
CHAPTER 2: COMPARING THE OPERATIONS AND CHALLENGES OF PIG BUTCHERS IN RURAL
AND PERI-URBAN SETTINGS OF WESTERN KENYA ................................................................ 40
2.1. Introduction .................................................................................................................... 40
2.2. Materials and methods................................................................................................... 43
2.2.1. Study area ................................................................................................................ 43
2.2.2. Butcher selection ..................................................................................................... 43
2.2.3. Survey design, questions and beta test ................................................................... 44
2.2.4. Interview process ..................................................................................................... 45
2.2.5. Data management and analysis ............................................................................... 46
2.2.5.1. Describing butchers and assessing differences across district ......................... 46
2.2.5.2. Assessing butcher challenges and seasonal variation ...................................... 47
2.3. Results ............................................................................................................................. 47
2.3.1. Butchers ................................................................................................................... 47
2.3.2. An overview of the pig marketing system ............................................................... 48
2.3.3. Procurement ............................................................................................................ 49
2.3.4. Transportation ......................................................................................................... 51
2.3.5. Slaughter .................................................................................................................. 53
xi
2.3.6. Marketing ................................................................................................................. 53
2.3.7. Government regulation ........................................................................................... 54
2.3.8. Butchers’ perspectives on their challenges ............................................................. 54
2.4. Discussion ....................................................................................................................... 55
2.4.1. The butcher and the role of butcher enterprise in pork marketing ........................ 55
2.4.2. Procurement ............................................................................................................ 56
2.4.3. Slaughter and transport ........................................................................................... 59
2.4.4. Marketing ................................................................................................................. 59
2.4.5. Challenges and rural and peri-urban differences .................................................... 60
2.4.6. Study limitations and challenges ............................................................................. 62
2.5. Conclusions ..................................................................................................................... 63
2.6. References ...................................................................................................................... 65
2.7 Tables ............................................................................................................................... 69
2.8. Figures............................................................................................................................. 74
CHAPTER 3: PIG MARKETING AND FACTORS ASSOCIATED WITH PRICES AND MARGINS IN
WESTERN KENYA ................................................................................................................... 75
3.1. Introduction .................................................................................................................... 75
3.2. Materials and methods................................................................................................... 77
3.2.1. Study location .......................................................................................................... 77
3.2.2. Pork marketing chain ............................................................................................... 78
3.2.3. Survey ....................................................................................................................... 78
xii
3.2.4. Sampling frame ........................................................................................................ 80
3.2.5. Data Analysis ............................................................................................................ 80
3.3. Results and discussion .................................................................................................... 83
3.3.1. Butchers, their characteristics, and operational practices ...................................... 83
3.3.2. Competitiveness ...................................................................................................... 85
3.3.3. Net income statement and differentiating profit groups ........................................ 86
3.3.3.1. Revenues ........................................................................................................... 86
3.3.3.2. Costs .................................................................................................................. 87
3.3.3.3. Profit .................................................................................................................. 88
3.3.4. Margins .................................................................................................................... 89
3.3.5. The determinants of prices, profit and marketing margin ...................................... 91
3.3.5.1. Pig weight .......................................................................................................... 91
3.3.5.2. Education ........................................................................................................... 92
3.3.5.3. Location ............................................................................................................. 93
3.3.5.4. Pigs purchased per year .................................................................................... 94
3.3.6. Limitations and Other considerations ..................................................................... 95
3.4. Conclusion ...................................................................................................................... 97
3.5. References ...................................................................................................................... 99
3.6. Tables ............................................................................................................................ 103
CHAPTER 4: IMPROVING BUSINESS PRACTICES AND PORK SAFETY: A CASE STUDY OF PIG
BUTCHERS IN BUSIA, WESTERN KENYA ............................................................................... 113
xiii
4.1. Introduction .................................................................................................................. 113
4.2. Materials and Methods: ............................................................................................... 114
4.2.1. Area of study and enumeration of butchers ......................................................... 114
4.2.2. Questions from 2008 survey .................................................................................. 115
4.2.3. Describing the 2009 workshop .............................................................................. 115
4.2.4. Business training .................................................................................................... 116
4.2.5. Public health and pork safety training ................................................................... 118
4.2.6. Weight estimation Training ................................................................................... 119
4.2.7. Follow-up survey .................................................................................................... 119
4.2.8. Data management and summary .......................................................................... 120
4.3. Results: ......................................................................................................................... 120
4.3.1. Training and follow-up participation ..................................................................... 120
4.3.2. Business practice training recall ............................................................................ 120
4.3.3. Public health training recall ................................................................................... 122
4.3.4. Weight estimation training recall .......................................................................... 123
4.4. Discussion: .................................................................................................................... 124
4.4.1. Uptake of information ........................................................................................... 124
4.4.2. Comparing training methodologies ....................................................................... 125
4.4.3. Strengths ................................................................................................................ 126
4.4.4. Weaknesses ........................................................................................................... 127
xiv
4.4.5. Going forward ........................................................................................................ 128
4.5. References .................................................................................................................... 130
4.6. Tables ............................................................................................................................ 134
4.7 Figures ............................................................................................................................ 138
CHAPTER 5: EVALUATING CRITICAL FACTORS TO THE ECONOMIC FEASIBILITY OF SEMI-
INTENSIVE PIG REARING IN WESTERN KENYA ..................................................................... 142
5.1. Introduction .................................................................................................................. 142
5.2. Materials and methods................................................................................................. 145
5.2.1. Study location ........................................................................................................ 145
5.2.2. Software algorithm ................................................................................................ 146
5.2.3. Data for the linear program ................................................................................... 150
5.2.4. Data for the software algorithm ............................................................................ 152
5.2.5. Data for comparing algorithm with farmer experiences ....................................... 154
5.3. Results ........................................................................................................................... 155
5.3.1. Opportunity cost of farm-grown feeds .................................................................. 155
5.3.2. Average daily gain .................................................................................................. 156
5.3.3. Profit maximizing or total revenue maximizing goals ........................................... 157
5.3.4. Feeding costs and butcher price variations ........................................................... 158
5.3.5. Pig slaughter records ............................................................................................. 158
5.3.6. Farmer responses .................................................................................................. 158
5.4. Discussion ..................................................................................................................... 159
xv
5.4.1. Feeds ...................................................................................................................... 159
5.4.2. Season .................................................................................................................... 160
5.4.3. Opportunity costs .................................................................................................. 161
5.4.4. Average daily gain .................................................................................................. 163
5.4.5. Comparing our model outputs to what farmers reported .................................... 165
5.4.6. Conclusion .............................................................................................................. 166
5.5. References .................................................................................................................... 168
5.6. Tables ............................................................................................................................ 172
5.7. Figures........................................................................................................................... 184
CHAPTER 6. GENERAL DISCUSSION AND RECOMMENDATIONS ......................................... 185
6.1. General discussion ........................................................................................................ 185
6.2 Recommendations ......................................................................................................... 189
6.3. Suggestions for further research .................................................................................. 191
APPENDICES ......................................................................................................................... 192
APPENDIX I. PIG BUTCHER SURVEY, 2008 ........................................................................ 192
APPENDIX II. BUTCHER SURVEY, 2009 ............................................................................. 212
APPENDIX III. DETAILED BUDGET SHEETS ........................................................................ 222
APPENDIX III. DETAILED BUDGET SHEETS ........................................................................ 223
APPENDIX III. DETAILED BUDGET SHEET .......................................................................... 224
APPENDIX III. DETAILED BUDGET SHEETS ........................................................................ 225
xvi
APPENDIX IV. OUTCOME MAPPING SURVEY ................................................................... 226
APPENDIX V. PIG PRICES, VARIABLE COSTS, OPERATING COSTS AND REVENUES FOR PIG
BUTCHERS, 2008-2009. .................................................................................................... 232
LIST OF TABLES
Table 2.7.1: Count of pig butchers who were enumerated and voluntarily participated in a
cross-sectional observational study in Busia and Kakamega Districts of Western Kenya, 2008-
2009. ............................................................................................................................................. 69
Table 2.7.2: The operating practices of pig butchers found to be significantly different between
rural (Busia) and peri-urban (Kakamega) Districts in Western Kenya, 2008-2009....................... 70
Table 2.7.3: Proportion of butchers using various modes of transportation to locate and
transport pigs to the butcher shop and slaughter slab in Busia (Bus) and Kakamega (Kak)
Districts of Western Kenya, 2008-2009. ....................................................................................... 71
Table 2.7.4: Challenges in operating a pig butcher enterprise as scored by the relative
importance by butchers, illustrated by the mean value of a score from 1 (low) to 5 (high)
challenge in Busia and Kakamega Districts, Western Kenya, 2008-2009. .................................... 72
Table 2.7.5: Number of pigs purchased per month by Butchers in Western Kenya. ................... 73
Table 3.6.1a: Independent variables collected in butcher interviews in Western Kenya, 2008-
2009 and assessed in models on the outcomes pig price per kg, pork price per kg, marketing
and operating costs per kg, profit per kg, and marketing margin per kg. .................................. 103
Table 3.6.1b: Continued. ............................................................................................................. 104
Table 3.6.2: The characteristics and operating practices of 49 pig butchers in Western Kenya,
2008-2009. .................................................................................................................................. 104
Table 3.6.2: The characteristics and operating practices of 49 pig butchers in Western Kenya,
2008-2009. .................................................................................................................................. 105
xvii
Table 3.6.3: Net income (per kg) in Kenyan shillings for butchers categorized into low, medium,
and high profit groups for purchases of pigs weighing 22, 30, 35, and 45 kg (live weight) in
Western Kenya, 2008-2009. ....................................................................................................... 106
Table 3.6.4: Spearman correlation coefficients of prices on butchers’ profit per kg for 22, 30, 35,
45 kg pig purchase weights in Western Kenya, 2008-2009 ........................................................ 108
Table 3.6.5: Profit margins and marketing margins for pig purchases of 22, 30, 35, 45 kg by
division and education level of butchers operating in Western Kenya, 2008-2009. ................. 109
Table 3.6.6: Factors associated with pork prices charged to consumers, pig prices, marketing
and operating costs, profit and marketing margins on a per kg basis for pig butchers operating
in Western Kenya, 2008-2009. ................................................................................................... 110
Table 3.6.7: Covariance parameter estimates for butcher, 22, 30, 35, and 45 kg weight and the
between-butcher variability accounting for the proportion of variance for each weight for each
mixed model outcome (pig price, profit, marketing and operating costs, and marketing margin
all on a per kg basis) presented in Table 3.6.6 from butcher surveys conducted in Western
Kenya (2008-2009). ..................................................................................................................... 112
Table 4.6.1: Summary of pricing components from initial butcher surveys in 2008, which were
used to aid in workshop discussions in Western Kenya, 2009. .................................................. 134
Table 4.6.2: Management changes made by butchers (n=12) one year after attending butcher
training that included business practice and pork safety information, Western Kenya, 2010. . 135
Table 4.6.3: Butchers’ practices used to ensure safe pork for human consumption, Western
Kenya, 2010. ................................................................................................................................ 136
Table 4.6.4: Butchers’ practices used to ensure the pig is free of the tape worm, Western Kenya,
2010. ........................................................................................................................................... 137
Table 5.6.1: Table of assumptions used in the pig feeding to market weight and market
evaluation algorithm for pigs in Western Kenya, 2009. ............................................................. 172
Table 5.6.2: Nutrient levels and market prices of locally grown feeds from Western Kenya made
available to the lowest cost feed ration models, collected in Busia markets in 2009. .............. 174
xviii
Table 5.6.3: Seasonal availability and cost assumptions of feed ingredients available in Busia,
and suggested restrictions for each ingredient made available to the lowest cost feed models.
..................................................................................................................................................... 176
Table 5.6.4: A sample of feed rations and the costs generated by the lowest cost feed model for
different ADG scenarios, pig weight, season, and proportion of true market prices when farmers
feed pigs in Western Kenya, 2009. ............................................................................................. 178
Table 5.6.5: The proportion of the least-cost feed rations that included each specific feed
ingredient for pigs between 8 and 65 kilograms grouped by opportunity cost of farm-grown
feeds, evaluated as a proportion of the market price in Western Kenya in 2008-2009. ........... 180
Table 5.6.6: The most profitable, and the highest revenue earning pig scenarios in Western
Kenya, using locally available free feeds, and feed prices from Busia markets which were
collected in 2009. Median butcher prices were used to assess profit which was calculated using
feed costs, an initial piglet purchase price of 500 KES, piglet purchased at 8 kilograms, 2 months
of age. ......................................................................................................................................... 181
Table 5.6.7: A comparison of the ranges of feed costs against the ranges of bargaining for pig
price, feed is valued at 25% of market price (KES). Net income is calculated from realistic
combinations of ADG, butcher price, and season based on linear weight gain, and includes the
cost of the 500 KES piglet. When feed is valued at 100% of the market price, the total feed cost
does not increase that much as was shown in table 5.6.3. ........................................................ 183
Table A5.1: Average prices paid for market pigs and breeding animals as estimated by butchers
in Busia and Kakamega Districts, Western Kenya, 2008-2009 ................................................... 232
Table A5.2: Variable costs for operating a pig butcher enterprise in Busia and Kakamega
Districts of Western Kenya, 2008-2009. ..................................................................................... 233
Table A5.3: Operating costs and barriers to entry associated with running a small pig butcher
enterprise in the Busia and Kakamega Districts of Western Kenya, 2008-2009. ....................... 234
Table A5.4: Revenue associated with pig butcher enterprises in the Busia and Kakamega
Districts, Western Kenya, 2008-2009. ........................................................................................ 235
xix
LIST OF FIGURES
Figure 2.8.1: The communication of people, the movement of the pig, and the activities
coordinated by pig butchers in getting pigs to local markets in the Busia District (rural) and
Kakamega District (peri-urban) of Western Kenya. ...................................................................... 74
Figure 4.7.1: An example of training material for profit and break-even pig price provided to
Kenyan pig butchers in 2009. ...................................................................................................... 138
Figure 5.7.1: Algorithm used to emulate growing a pig from weaning weight to market weight
to determine the impact of various factors (month of weaning, ADG, opportunity cost of feed,
season, market weight) on profit and total revenue for pig farmers in Busia, Western Kenya
2009. ........................................................................................................................................... 184
Figure 7.1: Survey used to interview pig butchers in Western Kenya, 2008 .............................. 192
Figure 7.2: Survey used to interview pig butchers in Western Kenya, 2009 .............................. 212
Figure 7.3 Complete budget survey for pig butchers in Western Kenya, 2009.......................... 222
Figure 7.3 Butcher outcome mapping survey in Busia, Western Kenya, 2010 .......................... 226
1
CHAPTER 1
Introduction and Objectives
1.1. Kenya’s agricultural sector
Kenya’s economic growth is highly correlated to its agricultural sector (ASDS, 2010). Fifty
percent of gross domestic product (GDP) is either directly or indirectly attributable to
agricultural productivity. Eighty percent of the population are rural inhabitants with the
majority relying on agriculture as a food source and principal livelihood (ASDS, 2010; Nganga et
al., 2010). Nearly one-third of the population is impoverished (Rarieya and Fortun, 2010).
Efforts to understand and improve agricultural knowledge and productivity therefore have pro-
poor relevance (OECD, 2006).
1.1.1. Brief history of Kenya’s agricultural sector
After gaining independence from Britain in 1963 the Kenyan government controlled
agricultural markets; setting prices, subsidizing inputs and managing commodity purchases
from farmers (ASDS, 2010). Agriculture was productive in the first twenty years after
independence with average yearly growth rates of 3.5% (ASDS, 2010). The productivity is
attributed to the expansion of zoned land for cultivation, redistribution of colonized land, the
introduction of hybrid maize technologies and the rally of smallholders to produce for an
inspired independent government (ASDS, 2010; Gautam, 2000). Many of the parastatal
organizations offered uniform prices to farmers regardless of their location or the season which
reduced farmer risk and encouraged production (Kijima et al., 2009). Over time, large deficits,
corruption, and organizational inefficiencies made the government’s role unsustainable and
2
agricultural productivity declined (Kijima et al., 2009). In the 1980’s, most Sub-Saharan African
(SSA) countries adopted market reform policies with the objective of reducing government
interference in the markets, allowing market forces to set prices and for prices to act as a
signals for resource allocation and investment (Minten and Kyle., 2000). In the mid 1980s Kenya
adopted the structural adjustment programs imposed on them by international lenders when
budget deficits became unmanageable (Jayne et al., 2002). In the first two decades after market
reform, agricultural growth continued to stagnate (ASDS, 2010). Several explanations are
offered to explain why farmers responded poorly in their supply response to market reforms. In
many cases reforms were never fully implemented (Poulton et al., 2006). For example, some
parastatals remained active in supporting maize prices in politically motivated locations (Jayne
et al., 2002; Kherallah et al., 2000; Kherallah et al., 2002). The proponents of reform
underestimated how poorly developed marketing institutions would impact transaction costs
and risks of trade (Kijima et al., 2009; Poulton et al., 2006 ). State investment in research,
extension and infrastructure declined too abruptly and the liberalization was poorly sequenced
(Poulton et al., 2006; ASDS, 2010).
In the early 2000s, the Kenyan government recognized the need to re-invest in the
agricultural sector and began to take measures to revitalize extension and research. The
agricultural sector has been growing at 2.5% since then with the exception of set-backs induced
by the political violence in 2008 and the drought that occurred in 2008-2009 (ASDS, 2010). The
budget allocation for the agricultural sector is currently at 4% of GDP, which is double what it
3
was immediately following market reforms. However, pre-market reform allocation was 13% of
GDP (ASDS, 2010).
As the politics and investment choices in agricultural marketing and extension have
changed over time; research across a variety of sectors will be important to understand the
impacts and to measure the changes in productivity and knowledge of smallholder farmers and
marketing agents.
1.1.2. Role of livestock
Livestock accounts for 12% of Kenya’s GDP (FAO, 2005; Kagira et al., 2010) and 17% of
Kenya’s agricultural GDP (ASDS, 2010). Small-scale producers dominate the sector (FAO, 2005)
relying on animals for food, manure, power, accumulating capital (ie livestock is a “living
savings account”), insurance, social relevance (loans and gifts), and as a significant source of
income (Randolph et al., 2007; Reithmuller, 2003; Tegebu et al., 2012). In rural settings, families
with the smallest incomes tend to derive a higher proportion of their income from livestock
(Delgado and Siamwalla, 1997). Livestock production has remained stagnant for more than two
decades (FAO, 2005) and productivity is far below industrialized countries (Randolph et al.,
2007). Livestock remains the highest asset holding of rural farmers after land (Tegebu et al.,
2012).
Prices are an important determinant of the type of livestock systems that can be
adopted; low meat prices or high input prices mean owners have limited incentives to invest in
inputs or intensify production (Simpson 1988; Randolph et al., 2007). Prices are influenced by
4
local demand, export market proximity, local incomes, and marketing efficiency (Anderson,
2003). Market prices, market access and feed prices are commonly reported livestock
challenges as are risk of disease, lack of extension and health services, changing climate, and
lack of infrastructure and credit (ASDS, 2010; FAO, 2005; Rarieya and Fortun, 2010).
1.2. Kenya’s pig industry
The pig industry in Kenya is relatively small compared to other livestock. However, the
number of pigs slaughtered in Busia, Western Kenya between 2001 and 2005 was
approximately 44% of the number of cattle slaughtered (Kagira et al., 2010). The relatively high
number of slaughters may be indicative of the fast growth rates of pigs (Lekule and Kyvsgaard,
2003; Thomas et al., 2013) or of poverty levels in this location (FAO, 2012). Pig slaughters in
Kenya have been steadily rising (FAOSTAT, 2010). In 2009, there were approximately 280,000
pigs slaughtered compared to 163,908 in 2000 which represents and annual growth rate of
7.78% (FAOSTAT, 2010).
1.2.1. Pork value chain in Kenya
The majority of pig processing is done by Farmers Choice in Nairobi (Kagira et al., 2010).
The company is vertically integrated, owning grower operations which provide almost half of
the pigs that are processed (FAO, 2012). The remaining pigs come from commercial farms in the
Eastern and Central provinces which are located close in proximity to Nairobi. Distance and the
stringent standards of Farmers Choice exclude smallholder farmers in rural areas of Western
and Nyanza provinces who rely mainly on traditional/back-yard pig management (Wendoh,
5
2013; FAO, 2012). Only 5% of the pigs grown in rural areas are transported to larger city centers
(Githigia et al., 2005). There are no primary livestock markets or auctions for pigs in Kenya
(FAO, 2012).
Eighty percent of the pigs produced in Kenya are raised by smallholder farmers (Lekule
and Kyvsgaard., 2003) who rely on farm gate sales (Mutua et al., 2010) which generally
translate to low incomes (Kagira et al., 2010). Pigs are sold to small-scale pig butcher
enterprises who operate in rural and peri-urban market areas (FAO., 2012). The pork from local
marketing chains is safer than pork from on-farm slaughter because meat inspection is an
important value-add of local butchers (Levy et al., 2009). Infection from zoonotic pathogens
such as porcine cysticercosis, trichinellosis and toxoplasmosis can occur from the consumption
of infected and undercooked pork (Thomas et al., 2013).
There is a paucity of research on the characteristics and efficiency of the local pork
marketing chains which predominate in rural areas of Kenya. To the author’s knowledge, only
one descriptive study by Kagira et al. (2010) covers the subject, presenting challenges of
butchers in Busia and the profit potential of their business. The study by Kagira et al. (2010) was
published after the studies in this thesis were underway. The most common challenges for
Busia butchers reported by Kagira et al. (2010) include conflict with police and authorities,
finding pigs (after ASF outbreaks), and transport.
6
1.2.1.1. Pig farmers
Western Kenya is dense in population compared to other parts of Kenya and as a
consequence farm sizes range from 0.2 to 2.5 acres with an average of seven people per
household (Rarieya and Fortun, 2010). The Western Province has a very high prevalence of
poverty (Rarieya and Fortun, 2010; FAO, 2005) and has the 2nd highest population of pigs in
Kenya (FAO, 2012). The majority of pigs are cared for by women (Mutua et al., 2010) and many
households are headed by women (Lekule and Kyvsgaard, 2003). In rural areas, 27% of farmers
have no formal education (Mutua et al., 2011).
Pigs are a good livestock choice for the poor because they do not require a lot of space
(farms are becoming smaller due to generational sub-dividing), are relatively inexpensive in
comparison to cattle, convert feed efficiently, have fast growth rates, have shorter breeding
cycles, and produce a greater number of offspring than most other domestic animals (Lekule
and Kyvsgaard, 2003; Ajala and Adesehinwa, 2008, Mutua et al.,2011b; Bebe et al., 2002;
Akanni and Onasanya, 2004; Thomas et al., 2013). The money earned from selling pigs is most
often used to pay for household items such as farming inputs, medicines, school fees and food
(Lekule and Kyvsgaard, 2003; Mutua et al., 2011; Kagira et al., 2010b). Many rural farmers in
resource-poor locations aim to maximize revenues from their pigs rather than profits (Lemke et
al., 2007). Farmers tend to sell their pigs to meet critical cash requirements, not necessarily
when they reach a particular market weight (Ajala and Adesehinwa, 2007).
7
1.2.1.2. Pig butchers
A precursor to pigs being an effective source of animal protein and to being a viable
income option for farmers is a functional marketing system for pork (Ajala & Adesehinwa). In
Western Kenya almost 90% of pigs are sold to local pig butchers who sell pork in their
butcheries (butcher shops) (Kagira et al., 2010; FAO, 2012). Butchers make extensive use of
bicycles in Busia as they travel as far as 20 km from their shop to source pigs (Kagira et al.,
2010). Generally, in domestic markets, trekking is the most common form of moving animals
from farm gates to markets (Kyeyamwa et al., 2008). Pigs are slaughtered in private slaughter
facilities, before being inspected by government veterinarians, and then sold in butcheries in
local markets (Kagira et al., 2010; FAO, 2012). Butchers purchase 12 to 30 pigs per month at a
mean price of US$ 31, earning a mean US$ 3.8 per pig (Kagira et al., 2010).
Marketing margins, the factors associated with variations in the number of pigs sold, pig
prices, pork prices, marketing margins and marketing and operating costs of rural and peri-
urban butchers have not been addressed. Kagira et al., 2010 studied pork marketing in Busia
which is rural; there are no studies contrasting rural and peri-urban settings, which could be
different as marketing conditions are known to vary by place and time (Chamberlin and Jayne,
2012). In Nigeria, pig marketing indicators (margins, pig prices, profits) are higher in urban
locations than rural location (Ajala and Adesehinwa, 2008).
8
1.2.1.3. Consumers
Consumption and availability of animal sourced proteins is inadequate in rural areas of
Kenya (Nganga et al., 2010; Nieman et al., 2003). Animal sourced proteins are necessary for
cognitive and physical development, and preventative of stunting and anemia (Nieman et al.,
2003). In rural communities of Western Kenya pork is a preferred meat and is typically fried
(Kagira et el., 2010; Mutua et al., 2011; Githigia et al., 2005). Consumption of pig products is
expected to increase with changes in social attitudes resulting from urbanization, education
(Wabacha et al 2004), and increased incomes (Jayne et al., 2010; Thomas et al., 2013). One
third of the households surveyed by Githigia et al. (2005) in the Funyula Division (remote rural
location) were slaughtering their pigs on farm, and consuming the pork un-inspected.
1.2.1.4. Government
The Kenyan government established the Pig Industry Act, to establish the requirements
for the pig industry including the regulations for selling live pigs, the licenses required to
slaughter pigs and the conditions upon which a butcher can sell cooked and raw pork (Anon,
2006). Slaughter slabs are privately owned, however the government is responsible for pork
inspection employing livestock officers to visit slaughter slabs.
1.2.1.5. Conclusion
As numbers in pigs marketed increase, there is value in a greater understanding of the
indigenous pig markets and in making efforts to increase marketing capacity and improve
product quality and efficiency. An important first step is to gain an understanding of the pig
9
marketing system in its current institutional and socio-cultural setting (Kyeyamwa et al., 2008;
Kagira et al., 2010).
1.3. Pig husbandry
Mixed crop and livestock farms predominate and in farms with low acreage, chickens
and pigs tend to be commonly chosen livestock (Kagira et al., 2010). Pigs can be sustained on a
wide ranging diet and are highly adaptable to various husbandry practices (Akanni and
Onasanya, 2004). Traditional pig management is the dominant pig rearing system in Western
Kenya, with 95% of the nearly 90,000 pigs raised in this manner (FAO, 2012; Lekule and
Kyvsgaard, 2003). In traditional management systems, pigs are provided with minimal housing
(27% of farms provide any housing) because of a scarcity of raw building materials or
investment capital (Mutua et al., 2010; Muhanguzi et al., 2012). Family members are
responsible for the management of pigs (Mutua et al., 2012). The pigs are allowed to free-range
or scavenge for food during non-harvest seasons (Mutua et al., 2011; Lekule and Kyvsgaard.,
2003). Piglets are purchased after weaning and are grown for up to two years (FAO, 2012) and
are a mix of native or crossbred species (Mutua et al., 2010; Mutua et al., 2011b). Farmers keep
few pigs (between 1 and 3 growing pigs) on their farms (Kagira et al., 2010; Mutua et al., 2010).
Commonly identified challenges in small-scale pig rearing include feeding, breeding, diseases,
and low selling prices ( Mutua et al., 2011; Kagira et al., 2010).
1.3.1. Diversification
10
Diversifying livestock and crops and operating mixed farms (crop and livestock) help
stabilize farm incomes and employment, enhance environmental sustainability and increase
resiliency from disease outbreaks such as African Swine Fever (ASF) (Delgado and Siamwalla,
1997; Udo et al., 2011). Livestock can protect farmers from crop failure and provide quick
income to purchase crop inputs (seeds, pesticides and fertilizers) (Tegebu et al., 2012).
Generally, households choose different livestock to fulfill different functions;
accumulation choice is complex (Tegebu et al., 2012). The need for transport and draft labour,
agro-ecology, perceived liquidity, proximity to markets, proximity to grazing land, access to
technical information, current asset portfolio, availability of inputs, gender of household head,
expected returns, seasonality, risk aversion, level of self-provision (because of high transaction
costs) and off farm income opportunities all influence livestock choice (Delgado and Siamwalla,
1997; Tegebu et al., 2012). Diversification is required to stabilize income and consumption and
to minimize risk against climatic uncertainty, disease, market volatility and the impacts of weak
financial infrastructure (Barrett et al., 2001). The need to minimize risk offers an explanation as
to why transactions are not always economically maximized (Duflo, 2003). Famers are thought
to be efficient but poor (Shultz, 1964; Duflo, 2003);
1.3.2. Intensification
Intensification is intended to make more efficient use of production inputs (veterinary,
de-worming, access to commercial feed) to increase the value of the livestock (Reardon et al.,
1999). For example, dairy farmers in Kenya keep small herds allowing them to use more planted
11
fodder and purchased feeds for cows (Bebe et al., 2002). Intensifying small animal systems does
not necessarily increase income substantially (Udo et al., 2011).
Lekule and Kyvsgaard, (2003) recommend making production systems more intensive
(confining pigs) to improve pork safety (Lekule and Kyvsgaard, 2003) as free-ranging pigs run
higher risks of parasitic diseases (Kagira et al., 2012) and zoonotic pathogens such as Taenia
solium (Thomas et al., 2013; Mutua et al., 2011). The feasibility of intensification is determined
by input costs (feed, care) and output prices which are influenced by local demand, export
market proximity, local incomes, and marketing efficiency (Anderson, 2003). The feasibility of
intensification for pig rearing in Western Kenya has not been studied, nor have the factors that
most influence the costs or benefits of pig rearing. Free-range pigs require fewer inputs and are
thought to be in general, more economically feasible (Verhulst, 1993).
1.3.3. Feeding pigs
Many (65%) farmers find it challenging to feed pigs (Mutua et al., 2011). The cost of
feeding pigs can account for as much as 70-85% of production costs (Verhulst, 1993; FAO, 2012;
Ajala and Adesehinwa, 2008). Although feed costs in Western Kenya have not been quantified,
Kagira et al., (2010) and Mutua et al., (2012) have reported on the types of feeds farmers
typically use.
1.3.3.1. Common feeds
12
Farmers feed their pigs combinations of farm-grown, free, and purchased feeds (Mutua
et al., 2012). The most frequently used feeds reported by farmers in Busia are ugali (ground
maize or millet cooked in oil and water) (88% of farmers), kitchen leftovers (83%), omena (dried
local fish) (78%), sweet potatoes (75%), sweet potato vines (65%), cassava (57%), brewers’
waste (48%), maize (33%), fish innards (30%), and less frequently vegetables, mango, avocado
and banana peels (Mutua et al., 2012). Kagira et al., (2010b) reported similar feeds and also
included swill collected from local markets. Commercial feed is rarely used as it is hard to
acquire in rural settings and the quality of commercial feeds is thought to vary considerably
(Kihuria, 2011).
1.3.3.2. Feed research
Significant research in the dietary requirements of pigs and the optimization of feed
rations for pig production has been undertaken for economically efficient breeds in temperate
(Western) climates (NRC, 1998; NRC 2012; Paul et al., 2007). The genetic potential and growth
rates of African pigs differ from Western pigs and so does the environment and quality of feeds
available; minimizing the applicability of Western research for African pig production (Paul et
al., 2007).There is a paucity of research on feed requirements and protein accretion rates of
native and crossbred pigs in SSA. Paul et al., (2007) has provided estimation equations for pigs
in India which could be used as an approximation. To determine the nutrient requirements for
pigs in India, Paul et al. (2007) used weight gains recorded from 27 studies and 102 dietary
treatment groups on a total of 652 animals across India. The analysis was stratified to derive
equations for digestible energy (DE), crude protein (CP), and essential amino acids (sub-
13
components that make up protein) for pigs between 7 and 20, 20 to 35 and 35 to 60 kg (Paul et
al., 2007; The animals were a mix of indigenous, nondescript, crossbred, and improved exotic
breeds (Paul et al., 2007).
1.3.3.3 Nutrient requirements
Energy is the most fundamental of all nutrients consumed by pigs because it is required
to maintain and moderate bodily functions and to retain protein for growth (NRC, 1998;
Queensland Government, 2010). Pigs naturally regulate their energy intake. Fibrous foods
which have lower energy concentration can be used in place of carbohydrates; however pigs
will require more food to compensate. If the fibre content of a ration exceeds 15%, growth
rates diminish (Peters et al., 2005). Pigs are fed high-fibre diets in SSA and as a consequence
tend to have low growth rates which result in poor economic efficiency (Peters et al., 2005).
Amino acids are essential for growth and are found in protein-rich foods (Queensland
Government, 2010). Essential amino acids are required in higher concentrations when energy
content of the diet is more concentrated (NRC, 1998).
Vitamins are organic compounds which play a role in the metabolism of nutrients (NRC,
1998). It is generally recommended to supplement feeding with vitamins in a production
environment to prevent vitamin deficiencies (Queensland Government, 2010).
Calcium and Phospohorus are essential minerals for physiologic functions, and the
skeletal system's development and maintenance (NRC, 1998).
14
Water is important for temperature regulation and every chemical reaction that takes
place (NRC, 2009). Water helps move nutrients to and waste products from the cells of the
body tissue (NRC, 2009). Water intake has a positive correlation with feed intake, and weight
gain (NRC, 2012).
1.3.3.4. Fulfilling nutrient requirements
The nutrient content for many feedstuffs in the tropics have been collected and
organized by the FAO and are available at Feedipedia.org (Feedipedia, 2012). With many feed
ingredients available, a linear programming algorithm can be used to assess the ration
(proportion of each feed item) which fulfills the nutrient requirements of pigs at the lowest cost
(Queensland Government, 2010; Tempitope, 2007; Jayasuriya, 2002). This technique along with
more sophisticated linear programming derived algorithms is commonly used for formulating
commercial feeds at a large scale (Roush et al., 1994).
For small-scale pig farming in developing economies, Jackson (1981) argues that feeding
standards based on least-cost feed modeling are irrelevant because the feeds required to
achieve high performance are not readily available (Jackson, 1981). However, modeling least-
cost feed rations may still be useful for educational purposes or for learning more about the
decision factors that influence farmers. Manuals intended for small-scale farmers do provide
sample feed rations which provide farmers a basis for balancing nutrient requirements for pigs
(NAERLS, Ikani and Dafwang, 1995). Linear programming can also be used to better understand
15
the rationale of farmers (Schiere and de Wit, 1993), particularly where it is financially
impractical to conduct animal feed trials (Schiere and de Wit, 1993).
There is a dearth of information on how to feed pigs in Western Kenya optimally from
locally available feeds. Sample rations would likely be helpful. Also there has been no
evaluation on the cost of feeding pigs or the viability of pig production under the local market
conditions.
1.4. Livestock marketing systems in developing countries
Improving market access and efficiency has been identified as an important area of
focus for rural development and poverty reduction (Ajala and Adesehinwa, 2008; Fischer and
Qaim, 2012). Efficient marketing systems increase the economic benefits of produce and
livestock for producers, reduce food costs, stabilize food supply for consumers, and create
employment opportunities (Randolph et al., 2007). When markets are thin, smallholders tend
to produce for subsistence, with little incentive to be more productive (Shiferaw et al., 2011).
Market failure can occur because of natural monopolies (firm has interest in maximizing profit
because it can produces at lower cost than any other firm), externalities (spillover costs or
benefits that are not reflected in the price of a good such as pollution which is negative
externality) , asymmetric information (parties act based on different information), moral hazard
(similar to asymmetric information where the party that has more information is protected
from the risk after a transaction has occurred), adverse selection (asymmetry in information
prior to a transaction, and prevents the transaction because the seller would not a get price
16
that reflects the value of the good) and transaction costs (costs of making a transaction such as
seeking price information and partner search) (Landsburg, 1954).
Since market liberalization, generally prices have become more stable, market
integration has improved (price changes in one market are associated with price changes in
another), many efficiency gains have been observed, including lowering of transport and
storage costs as traders could function openly within a legal framework, creating economies of
scale (Gabre-Madhin, 2001; Chamberline and Jayne, 2012; Staatz et al., 1989). However private
trader investment has not been substantial, market volumes and value added products have
not increased, producers still bear too much of the marketing risks (Gabre-Madhin, 2001), and
there has been uncertainty with respect to government regulations (Staatz et al., 1989).
1.4.1. Value chain analysis
Value chain analysis is a necessary component of development efforts, as farm level
improvements from research and development are subject to the limitations of the marketing
outlets available to the smallholder farmer (Puskur et al., 2011). When evaluating marketing
chains it is important to identify challenges and inefficiencies and to analyze how stakeholders
interact (Webber and Labaste, 2010). Power relations between stakeholders should be
addressed (Webber and Labaste, 2010). Understanding the socio-economic situation of the
people involved in exchange is also critical because it reflects abilities to negotiate (Kyeyamwa
et al., 2008). Farmers in SSA are assumed to be price takers because they lack market
17
information and are poor negotiators (Kyeyamwa et al., 2008). If there is a social connection
between the buyer and seller, that can impact the negotiation as well (Kyeyamwa et al., 2008).
1.4.1.1. Performance Measures
The structure and distribution of profits and margins provide information which can
help identify opportunities for improving welfare of marketing chain participants (Shively et al.,
2010).
Marketing margins encapsulate the costs of the marketing services and are commonly
used as an indicator of marketing efficiency, with lower marketing margins being more efficient
and generally better for producer and consumer welfare (Ajala and Adesehinwa, 2007;
Fafchamps et al., 2005).The marketing margin is the difference or spread between the retail
price that the consumer pays and the price that the producer receives for a good (Toure and
Wang., 2013; Kijima et al., 2009).
Profit in the context of marketing agents is the remuneration for the risks assumed
during trade, the opportunity costs of capital tied up in trade, and the transaction costs
involved in making trades occur (Gabre-Madhin, 2001; Minten and Kyle, 2000). Although new
institutional economics uses the transaction as the unit of analysis (Gabre-Madhin, 2001), the
success or failure of any business ultimately relies on costs and returns (Simpson, 1998).
A simple way to gauge the competitiveness is to evaluate the concentration ratio (Ajala
and Adesehinwa, 2008):
18
Concentration ratio = (sales volume of largest four firms) / (total volume for all firms) *100%
A concentration ratio of less than 33% is considered competitive as the majority of the
pigs are not sold by the largest four firms.
1.4.2. Local and informal markets
Smallholder farmers gain easy access to informal markets (Puskur et al., 2011). Domestic
agricultural marketing activities in SSA are worth US$ 50 billion per year, more than three times
that of international exports (16.6 billion US per year) and 25 times that of intercontinental
trade (1.9 billion US per year) (Poulton et al., 2006; Diao et al., 2003). This highlights the need
to make local and domestic marketing efficient and equitable. Local markets can also
accommodate the diversity of agricultural products and are more forgiving of un-met quality
standards which often limit smallholder farmers from participating in exports (traditional and
non-traditional) and super-market channels (Randolph et al., 2007; Otte and Upton, 2005;
Poulton et al., 2006; Hazell, 2005).
The downside to local marketing is the high price volatility seen because of the seasonal
variation in supply and lack of arbitrage trading between markets which can help to stabilize
prices during shortages or over-supply in bumper-crop years (Poulton et al., 2006). Marketing
agents with little access to capital cannot contribute to price stabilization because they do not
have storage or the financial means to absorb some of the price impact (Poulton et al., 2006).
1.4.3. Challenges and limitations
19
Most farmers operate in remote areas which have limited infrastructure. The distance
between farmers and the limited scale of production makes coordination difficult and provides
little incentive for private companies to offer inputs and marketing services (Shiferaw et al.,
2011; Ajala and Adesehinwa, 2007). Transportation costs are high, resulting in few rural to
urban market trade linkages (Shiferaw et al., 2011). Transportation costs increase considerably
when moving animals across borders which requires use of trucks or rail (Williams et al., 2006).
Fuel, a short supply of trucks and illegal road taxing all add to transportation costs (Williams et
al., 2006). Long marketing chains with many exchanges also tend to increase transaction costs
(Shiferaw et al., 2011; Gabre-Madhin, 2001) and prices as each actor takes a marketing margin
(Kyeyamwa et al., 2008). The result is often lower producer shares of the total revenue
(Kyeyamwa et al., 2008). Famers do not have transparent information on prices and often rely
on marketing agents to share market prices (Gabre-Madhin, 2001).
Marketing systems tend to involve cash transactions because market actors lack of trust
and there are few practical enforcement mechanisms to prevent commitment failure
(Kyeyamwa et al., 2008; Gabre-Madhin, 2001; Minten and Kyle, 2000; Fafchamps and Hill,
2008).
1.4.4. Transaction costs
The transaction costs of any market exchange influence the behavior of market
participants and ultimately the quantities of goods produced and traded (Chamberlin and
Jayne, 2012). Transaction costs are unique to each market participant and marketing channel
20
(Chamberlin and Jayne, 2012). High transaction costs discourage trade and can lead to thin (low
trade volumes) markets (Jabbar et al., 2008). Market participation is a function of both
transaction costs, and the fixed and variable costs involved in doing business (Chamberlin and
Jayne, 2012).
In countries with underdeveloped institutional and physical infrastructure, transaction
costs play a more prominent role (Minten and Kyle, 2000). Examples of transaction costs
experienced by marketing agents include inter alia: finding a partner to exchange with, finding
information about the trustworthiness of a potential partner, negotiating prices with trade
partners, assessing quality of purchases or monitoring agreement made about a purchase,
seeking price (market) information, monitoring and enforcing (or seeking damages for)
unfulfilled or violated agreements (Kyeyamwa et al., 2008; Ajala and Adesehinwa., 2007;
Poulton et al., 2006).
Marketing agents also face high levels of risk when transacting which include inter alia:
having to carry large sums of cash (in the absence of financial institutions), loss of livestock such
as death or theft during transport, animal is condemned during slaughter (in the absence of
insurance institutions), animal is pregnant when slaughtered (less pork meat than butcher
anticipated prior to the trade), missing an arranged connection with a buyer or a seller (Kagira
et al.,2010; Poulton et al., 2010; Kyeyamwa et al., 2008).
The marketing systems in SSA tend to involve cash transactions, with few or no
arrangements or agreements in place which is an indicator of lack of trust, lack of negotiation
21
enforcement and lack of risk management on the part of the farmer and marketing agent
(Kyeyamwa et al., 2008).
1.4.4.1 Overcoming transaction costs and lowering risk
Moving from personal exchange to anonymous exchange under legal frameworks which
enforce contracts is of critical importance for development (Gabre-Madhin, 2001).
Producer groups and Farmer organizations can arrange the bulking of transactions
(inputs and outputs) and the coordination of production to help reduce transaction costs,
increase buying power, spread marketing risks, and increase information by promoting peer to
peer exchanges (Kyeyamwa et al., 2008; Shiferaw et al., 2011; Poulton et al., 2010). Marketing
Information Systems (MISs) and technology can increase efficiency, promote competition, and
increase information access by way of radio, mobile phones, internet, and commodity exchange
boards (Poulton et al., 2010). Relational contracts and intermediaries help increase trust and
decrease transaction costs of long market chains (Kyeyamwa et al., 2008; Gabre-Madhin, 2001)
Provisions for enforcing contracts would also reduce transaction costs (Kyeyamwa et al., 2008).
1.4.4.2. Factors associated with marketing and transaction costs
The common narrative in SSA is that marketing agents operate competitively but at
different levels of efficiency which leads to varying profits (Jabbar et al., 2008; Fafchamps
2005). Less efficient marketing agents bring down average efficiency, increasing marketing
22
margins and allowing more efficient marketing agents to capture economic rents (earning
higher profits than what would be expected or average) (Fafchamps, 2005). Fafchamps (2005)
argues that the economic rents could be removed if efficient marketing agents used their
higher productivity to eliminate inefficient marketing agents. Ajala and Adesehinwa (2008)
contest this solution because reducing the number of marketing agents could create
opportunity for oligopolistic behavior.
Regardless of proposed solutions, the differences in efficiency are attributed to the way
marketing agents manage their transaction costs. Marketing agents all experience unique
transaction costs (Jabbar et al.,2008 Gabre-Madhin, 2001), which is why there is not one price
in the market (Gabre-Madhin, 2001). Traders with high levels of education, better access to
financial capital, who make regular use of brokers, have repeated interaction with suppliers and
customers (better social networks) have been found to be more efficient (Ajala et al., 2008;
Jabbar et al., 2008; Abankwah et al., 2013; Toure and Wang, 2013; Shively et al., 2010; Nganga
et al., 2010).
1.4.5. Seasonality of markets in Sub-Saharan Africa (SSA)
Seasonal variation impacts prices, trade volumes and profits of livestock market
(Williams et al., 2006). Fluctuating rainfall coupled with low proportions of production being
23
sold creates highly volatile prices for grain, crops and livestock products (Staatz et al., 1989;
Jabbar et al., 2008). In Nigeria pig prices are high during festive seasons such as Christmas and
Easter (Ajala and Adesehinwa, 2007). Pork prices and pig prices in Busia decrease in the wet
season when cattle and beef are in abundance (Kagira et al., 2010).
1.4.6. Pig marketing in SSA
Pig marketing has been studied in Nigeria where primary, secondary and terminal
markets are used to exchange pigs (Ajala and Adesehinwa, 2008). Intermediate traders and
assemblers operate in several small markets in local villages building up herds to sell in the
larger urban market (Ajala and Adesehinwa, 2008). Pigs may be exchanged two to three times
before reaching the urban market; the criterion for exchange is based on size of the pig (Ajala
and Adesehinwa, 2007). Assemblers trek pigs until enough are collected to transport by a hired
truck to the urban market (Ajala and Adesehinwa, 2007). Lack of refrigeration and poor
sanitation were noted at the slaughter facilities (Ajala and Adesehinwa, 2007) and the overall
market was considered to be oligopolistic after authors calculated a concentration ratio (Ajala
and Adesehinwa, 2008). Challenges included capital constraint, transport costs, lack of
standardization, and poor abattoir conditions and storage (Ajala and Adesehinwa, 2008). The
average marketing margin was 39% (Ajala and Adesehinwa, 2008).
Pig marketing has been studied in Busia, Western Kenya (Kagira et al, 2010b) where
challenges and characteristics were highlighted. The challenges presented by Kagira et al.,
(2010b) included inter alia ‘conflict with regulatory authorities’, erratic pig supply particularly
24
after an ASF (African Swine Fever) outbreak, excessive travelling distances to purchase pigs,
seasonal fluctuations in the market, transport, and competition.
Traditional, semi-intensive and intensive pig rearing systems in Nigeria have all been
found to be profitable (Akanni and Onasanya, 2004; Ogunniyi and Omoteso, 2011; Adetunji and
Adeyemo, 2012), while only traditional husbandry practices were found to be profitable in
Burkina Faso and Cameroon (Verhulst, 1993). Lemke et al., (2007) compared extensive (i.e.
using indigenous pigs in rural locations) and intensive (i.e. using improved breeds in more urban
locations) pig systems in North Vietnam and found no difference in net benefit between the
two pig-rearing systems.
1.4.7. Conclusion
Efforts to describe how markets function along with identifying the challenges and
inefficiencies can potentially lead to innovations which can increase capacity, improve quality,
broaden market scope, or diversify products; the essential outcomes of a value-chain
analysis/intervention (Webber and Labaste, 2010). An increased understanding of the supply
chain of livestock in developing countries will lead to identifying opportunities required to
overcome the limitations that exist (Kydd and Dorward, 2004). The financial benefit to farmers
for rearing pigs depends on remunerative marketing opportunities.
1.5. Extension and Education in Kenya
Extension efforts have varied in their effectiveness to increase knowledge, influence
adoption rates and increase farmer productivity (Davis, 2008). However, when properly
25
designed, extension is widely accepted as effective and necessary for farmers to increase
agricultural productivity (Muyanga and Jayne, 2008). Kenya has recognized that a decline in
effective extension is a major factor for declining agricultural productivity (ASDS, 2010;
Muyanga and Jayne, 2008).Extension in Kenya consists of government run programs such as the
National Agriculture and Livestock Extension Program (NALEP) in support of general food crops
and livestock, parastatal organizations which run commodity based extension for traditional
exports such as tea and coffee, and private extension from various organizations (NGO, Faith
based organizations, farmer groups) operating in Kenya (Muyanga and Jayne, 2008; Davis,
2008).
1.5.1. Common extension typologies
Training and Visit (T&V) systems in Kenya were supported by donors for two decades up
to the early 90's (Gautam, 2000). The top down T&V system was financially unsustainable,
allowed for no farmer input and lacked accountability to the needs of smallholder farmers
(Agricultural Extension – the Kenya experience, 1999).
Participatory research and Farmer field schools (FFS) topologies accommodate location
and situational differences from region to region by involving local communities in problem
identification and in solution building (Muyanga and Jayne, 2008; FAO, 1994; Davis, 2008).
Farmer organizations can facilitate peer-to-peer learning, strengthen bargaining position, and
create economies of scale in marketing (Kahan, 2007). The two paradigms have had positive
impacts in productivity, empowerment and knowledge retention, but most of the benefit is
26
limited to the farmers most directly involved, with little spillover, and programs are expensive
to implement (Davis, 2008; van den Berg, 2004).
The performance and reach of private sector delivery has remained poor particularly in
rural areas because of thin markets, widely dispersed smallholder farmers, bias away from low-
value crops and poor farmers (Muyanga and Jayne, 2008). Muyanga and Jayne, (2008) suggest a
hybrid model where extension is considered a public good in very rural and poor locations and
is paid for in other locations. In 1986, Kenya instituted a policy where farmers that clearly
benefit from livestock rearing were required to pay for services and resource-poor farmers
would be at least partially subsidized (Otieno Oruko et al., 2000).
1.5.2. Education for pig butchers
Education for small, medium and micro-enterprise (SMME) is essential to growth in SSA
economies and training is offered by government institutions, NGO’s, Community Based
Organizations (CBO’s) and foreign donors (Nieman, 2001). The focus of much of the training has
been on budgeting, business and technical skills (Nieman, 2001; FAO 2011; ILRI 2010; IFAD
2010). de Mel et al. (2009) found that 52% of small enterprises responded positively to
education by continuing the use of records after training. In the study by Karlan and Validivia
(2011), small-scale entrepreneurs that were equipped with business training had higher
retention and repayment rates with microfinance institutions, suggesting that budget training
helps with cash-flow management.
27
Health education has been recommended as an essential component for Taenia solium
prevention programs (Ngowi et al., 2011). Wohlgemut et al, 2010 evaluated the impact of
training farmers about the Taenia Solium lifecycle; finding that educated farmers (grade 8 and
above) were better able to comprehend the relationship between epilepsy and Taenia Solium.
Pig butchers have not been included in these prevention programs.
1.5.3. Limitations of education and extension
In Kenya, a disproportionate allocation of investment has historically been directed
toward extension personnel, limiting investment in agricultural science (Otsuka, 2006).
Agricultural research is necessary because technologies are subject to agro-ecological
limitations (Poulton et al., 2010). Although technology improvements to livestock and crop
varieties with corresponding education was the hope for agricultural transformation (Shultz,
1964); these alone are not likely to transform agriculture in SSA. Unpredictable rainfall and
drought hamper agricultural productivity and remove incentives for farmers to invest in
fertilizer or improved seed varieties (Karlan and Validivia, 2011; Otuska, 2006). The timing of
inputs and credit and complementary coordination of services in the supply chain are additional
challenges (Poulton et al., 2006, Poulton et al., 2010; Kydd and Dorward, 2004) that education
and farm technologies alone will not resolve.
1.6. Thesis objectives
The overall goal of this thesis was to evaluate the organization of the pork marketing
chain in Western Kenya, highlight challenges, and find opportunities for improving the
28
sustainability of the pig industry in rural and peri-urban areas. The specific objectives of this
thesis were:
1. (a) To describe the pig butcher and his role in the process of pork marketing while
assessing differences between butchers in rural and peri-urban settings; and (b) to assess the
butchers’ perspectives on the challenges facing their operations (Chapter 2).
2. (a) To examine the competitiveness, efficiency (using marketing margins as a proxy),
and profitability of pig butchers; and (b) determine associations between butcher related
factors (characteristics and operating practices) and pork price, pig price, marketing and
operating costs, profit, and marketing margins using regression analysis (Chapter 3).
3. (a) To describe the components of a training workshop intended to enhance butchers’
business skills, knowledge of pork safety, and ability to estimate pig weights; and (b) evaluate
the outcomes that resulted from the workshop one year later to assess whether butchers who
were trained made changes that could be expected to improve their business, including using
budgeting skills to assess profitability when purchasing pigs, weight estimation charts (Mutua et
al., 2011c) and/or changes to enhance public health through the production of safe pork
(Chapter 4).
4. (a) To evaluate the economic potential of semi-intensive pig-rearing in the local pork
marketing chains of Western Kenya; and (b) assess the relative importance of season, average
29
daily gain, opportunity costs of farm-grown feeds, pig weight, and pig price variation on
economic outcomes of smallholder pig farmers (Chapter 5).
30
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CHAPTER 2: COMPARING THE OPERATIONS AND CHALLENGES OF PIG BUTCHERS IN
RURAL AND PERI-URBAN SETTINGS OF WESTERN KENYA
Adapted from: Levy MA, Dewey CE, Poljak Z, Weersink A, Mutua FK (2014). Comparing the
operations and challenges of pig butchers in rural and peri-urban settings of Western
Kenya. African Journal of Agricultural Research, 9(1): 125-136.
2.1. Introduction
In rural economies of many tropical countries, pigs are an important livelihood activity
(Mutua et al., 2011; Lekule and Kyvsgaard., 2003). In Western Kenya almost 90% of pigs are
sold to local pig butchers who sell pork in their butcheries (butcher shops) (Kagira et al., 2010;
FAO, 2012). The appreciation for pork as an animal food source in the Western Province has
been recognized (Kagira et el., 2010b; Mutua et al., 2011) and the number of pigs slaughtered
in Kenya has been steadily rising (FAOSTAT, 2009). Approximately 280,000 pigs were
slaughtered in Kenya in 2009, compared to 165,000 in 2000, representing an annual growth
rate of 8% (FAOSTAT, 2009). As pig slaughter numbers increase there is value in furthering our
understanding of pig marketing, particularly in rural areas where farmers often face challenging
marketing conditions (Chamberlin and Jayne, 2013). The financial benefit to farmers for rearing
pigs depends on remunerative marketing opportunities. Improvements to marketing systems
not only increase the economic benefits of livestock to the individual producer but also reduce
food costs to consumers and stabilize food supply for the communities which these markets
serve (World Bank, 2008; Randolph et al., 2007).
The Western Province has a very high prevalence of poverty (Krishna et al., 2004), and
has the 2nd highest population of pigs in Kenya (FAO, 2012), so studying the marketing
41
opportunity for pig farmers in this location is important. In contrast, pig-rearing in the Central
province is more intensive and farmers can market their pigs to butcheries in urban centers and
to pork processing factories within their proximity (FAO, 2012). Smallholder farms in the
Western Province range from 0.2 to 2.5 acres and average seven people per household (Rarieya
and Fortun, 2010). Mixed crop and livestock farms are the most common and in farms with low
acreage, chickens and pigs tend to be the most commonly chosen livestock (Kagira et al., 2010).
Traditional pig management is the dominant pig rearing system in Western Kenya, with 95% of
the nearly 90,000 pigs raised in this manner (FAO, 2012). The pigs are native or crossbred
species and are allowed to scavenge for food during non-harvest seasons to keep input costs
low (Mutua et al., 2010; Lekule and Kyvsgaard., 2003). Farmers have been encouraged by
researchers and local government staff to keep their pigs tethered during education workshops
intended to reduce the transmission of the Taenia solium parasite (Wohlgemut et al., 2010).
Farmers keep between 1 and 3 growing pigs on their farms and women are predominantly
responsible for their care (Kagira et al., 2010; Mutua et al., 2010). The challenges commonly
identified include feeding, breeding, diseases, and low selling prices (Mutua et al., 2011; Mutua
et al., 2010; Kagira et al., 2010). Strengthening extension servicess has been recommended to
promote healthy pig production, improve breeding and increase farmers’ knowledge of pig
rearing (Mutua et al., 2011).
The pig industry is monitored by the Kenyan government. The Pig Industry Act outlines
the regulations for selling live pigs, the licenses required to slaughter pigs and the conditions
upon which a pig butcher can sell pork (Anonymous, 2006). Although the pig industry in Kenya
42
is relatively small (0.3 million) compared to other livestock, the consumption of pig meat is
anticipated to increase with urbanization and social views resulting from education (Wabacha
et al., 2004; FAO, 2012).
Pig marketing has been studied in Busia, Western Kenya (Kagira et al, 2010b) where
challenges and characteristics were highlighted. The challenges presented by Kagira et al.,
(2010b) included inter alia ‘conflict with regulatory authorities’, erratic pig supply particularly
after an ASF(African Swine Fever) outbreak, excessive travelling distances to purchase pigs,
seasonal fluctuations in the market, transport, and competition. At the time this study began,
there was a paucity of literature available on the subject of pig marketing in Western Kenya.
This study provides a detailed description of the processes involved in getting a pig from the
farm gate to the consumer which has not been previously documented for these locations. This
study is also an extension of the work by Kagira et al., (2010b) as it includes butchers from two
districts; Busia which is rural, and Kakamega which is peri-urban, allowing us to compare the
characteristics and challenges of butcher enterprises between the two districts.
The primary purposes of this research are to: 1) describe the pig butcher and his role in
the process of marketing pork while assessing differences between rural and peri-urban
settings; 2) assess the butchers’ perspectives on the challenges facing their operations.
Understanding the key differences will aid policy makers in addressing disadvantaged settings,
or aid in prioritizing extension material and services for rural or peri-urban settings. A record of
43
current pig marketing and the processes of pig butchers will allow for future monitoring of how
the industry evolves.
2.2. Materials and methods
2.2.1. Study area
This cross-sectional, observational study was conducted in the Busia and Kakamega
Districts of Western Kenya. Busia is a rural district bordering on Uganda, with a population of
488,075 (Anonymous, 2009). Kakamega, the capital of the Western Province, is surrounded by
peri-urban farms and is situated in the Kakamega District, with a population of 1,660,651
(Anonymous, 2009).
Two sub-locations were included from each district, Butula and Funyula in rural Busia,
and Shinyalu and Ikolomani in peri-urban Kakamega, chosen out of convenience because of
their large population of pigs, history of pig keeping, high prevalence of poverty, and because
smallholder farmers in these locations had been previously studied (Mutua et al., 2011; Kagira
et al., 2010b; Thornton et al., 2002).
2.2.2. Butcher selection
All butchers known to source pigs from the villages within the four sub-locations were
enumerated in 2008 and 2009 by local government meat inspectors, pig farmers, and village
elders based on their personal recollection. The enumeration process was repeated in 2009 to
ensure that new butchers, or those not enumerated in 2008, were invited to participate. Each
44
enumerated butcher was invited to participate in the study either in June of 2008 or June of
2009. To fit the inclusion criteria for the study, butchers had to purchase pigs at least once
every month for the purpose of butchering and selling the pork; middlemen who purchased
pigs for the purpose of reselling to butchers were excluded. Un-licensed butchers were allowed
to participate in the study.
2.2.3. Survey design, questions and pre-test
Structured questionnaires (Figure 7.1, Figure 7.2, Figure 7.3) were designed to capture
information about butchers, their processes and their opinions on the challenges of pig butcher
operations in the areas of procurement, transport, slaughter, marketing, and government
regulation. Questions about the butcher included age, education levels, how long the butcher
had been in the business, and how the butcher got into the business. Questions about the
procurement of pigs included who the butchers purchased pigs from, how many pigs were
purchased weekly, whether or not they resold pigs they purchased, all of the methods they
used to find pigs, and whether the butchers had contracts with farmers. Transport questions
included methods of getting to the farm to see pigs, methods of transporting the pigs, how far
the butcher typically travelled in a day searching for pigs, how much time the butcher spent in a
day searching for pigs. Slaughter questions included how often the slaughter slab was used,
what proportion of pigs were inspected by government inspectors, and the labour required for
slaughter slab help. Questions about the marketing of pork included whether the butcher sold
raw pork or both raw and cooked pork, the number of pigs purchased and sold in for the shop
each month of the year, the number of employees in the shop, and whether ugali (staple food
45
made with ground maize) was sold with cooked pork. Questions about government regulation
included the costs of their license renewals, the nature of the licenses, and how often they
were required to renew their licenses. The survey also included a 5-point Likert scale rankings
for a list of potential challenges in the areas of procurement, slaughter, inspection, transport,
capital, marketing, and regulation.
In 2008, the questionnaire was pre-tested on one butcher in the field and then modified
before other interviews were conducted. The questionnaires are found in Appendix 1 and
Appendix 2.
2.2.4. Interview process
Pig butchers were initially contacted by telephone or in person by a village elder or a
government inspector who described the research study. The butchers who were willing to
participate provided a convenient time and location for an interview. An individual, face-to-face
interview was conducted with each butcher in either 2008 or 2009 by one of the researchers
and a local villager who spoke both English and Swahili. The survey questions were asked in
Swahili unless the butcher was comfortable responding in English. All answers were translated
into English and transcribed by the researcher onto the data collection form. Neither the
government inspectors nor the village elders were present for the interview. The butchers were
assured that the information they provided was confidential and that only aggregated data
would be used for the study. The butchers were interviewed at their shop or home, or while
they were in transit searching for pigs. All butchers volunteered to be part of the survey and
46
gave approximately 1.5 hours of their time each visit to complete a questionnaire. As a gesture
of appreciation, butchers were given a package of 100 small bags which are commonly provided
to customers to carry purchased pork.
Research ethics approval was granted by the University of Guelph in Ontario, Canada
and by the Veterinary Director General in Nairobi, Kenya before the interviews were conducted.
2.2.5. Data management and analysis
The data were entered into Microsoft Excel 2007 (Microsoft, Redmond, WA, USA) by
one researcher and then validated independently by a second researcher. All analyses were
conducted in SAS 9.1. (SAS Institute Inc. Cary, NC), except for the Dosksum’s RCBD tests
(Hollander and Wolfe, 1999), which were performed using custom software developed by
William Sears.
2.2.5.1. Describing butchers and assessing differences across district
Descriptive tables were created using means and standard deviations (sd) for
continuous variables, and proportions for categorical variables. To assess differences
experienced by butchers across districts (rural Busia or peri-urban Kakamega), Student’s t-tests
were used on continuous variables. To assess differences experienced by butchers across
districts, chi-squared analysis was used and odds ratios were calculated on categorical
variables. A Fisher’s exact test was used rather than the chi-square test if an expected cell value
for any categorical outcome was less than 5 (Davis, 2007). Where variables differed between
47
districts, they were presented separately in the results section; otherwise the overall result was
presented.
2.2.5.2. Assessing butcher challenges and seasonal variation
To assess the differences between butchers’ scores given to the challenges between
districts, a Kruskal-Wallis test was performed. Each challenge was then individually assessed
using a Wilcoxin-Mann-Whitney test. Bonferroni and Sidak adjustments were performed on p-
values to control for experiment-wise error rates. To assess the differences in the butchers’
scores among challenges within each district, a Doksum’s RCBD test using Tukey’s p-values was
performed.
To assess the differences of monthly pig purchases between districts, the Kruskal-Wallis
and Wilcoxin-Mann-Whitney tests were performed as described above for the butchers’
challenges. To assess the differences in the butchers’ monthly pig purchases within each
district, a Doksum’s RCBD test using Tukey’s p-values was performed.
2.3. Results
2.3.1. Butchers
Table 2.7.1 provides the number of butchers who were enumerated and the number of
butchers who participated in the study. In total, 51 pig butchers were enumerated, and 50 were
studied; 25 from rural Busia and 25 from peri-urban Kakamega. The majority of butchers were
interviewed in 2008 however additional butchers were added in 2009 because they were either
missed in the 2008 enumeration or they were new to the business in 2009 (Table 2.7.1). One
48
butcher that was enumerated in 2008 could not be reached in either year, and was not
interviewed (Table 2.7.1). One farmer who purchased pigs only in the busy season and then
slaughtered and sold the pork from his farm and one middleman, were interviewed but
excluded from the study.
All butchers were male except one. The butchers were between the ages of 20 and 60
with a median age of 33 years (mean age of 36.5 years [sd = 10.71]). On average, the butchers
had been in the business for 8.5 years (sd = 7.41). There were several new butchers in the
business with 19% having less than 1 year, 12% between 1 and 2 years, 16% between 3 and 5
years, and 53% with more than 5 years experience. Twenty-six percent of the butchers
identified farming as another livelihood activity but none of the pig butchers butchered other
livestock. Education levels varied: 10% had no education, 20% attended some primary school,
37% completed primary, 6% attended some secondary school, 25% completed secondary
school, and 2% completed college.
Many butchers learned the butchering business from a family member (44%). Others
learned on their own (19%), from working for another butcher (17%), from a friend (14%), from
a farmer group or co-operative (3%), or in school (3%). The butcher business was sometimes
generational as 30% of the butchers had fathers who butchered either cattle or pigs.
2.3.2. An overview of the pig marketing system
In the indigenous pig-marketing system being described, the pig butcher was
responsible for the coordination of activities and people necessary to transform pigs into
49
marketable pork. Figure 2.8.1 depicts the interactions, activities, and stakeholders linked to the
pig-butcher enterprise. The pigs were not purchased in a central market; instead, butchers
purchased pigs directly from the smallholder farmer at the farm gate, sometimes using an
agent to aid in finding pigs. A purchased pig was transported to the butcher’s shop, the
butcher’s home, or directly to the slaughter slab (abattoir), depending on the time of day that
the pig was purchased. From the butcher’s shop or home, the pig was transported to the
slaughter slab. Pigs were usually slaughtered in the morning. The pork was inspected at the
slaughter slab before being transported back to the butcher shop to be sold to consumers
either as raw or cooked pork. The butcher enterprise, slaughter slab, and meat inspection were
regulated by the government.
2.3.3. Procurement
Most market-weight pigs changed ownership only once between the farmer and the
butcher before being sold for pork. Half of the butchers (53%) purchased live pigs and resold an
average of 4.8 pigs per month (20% of the pigs they purchased) to other butchers. Butchers
found pigs by having farmers coming to their shops to notify them (97% of respondents), using
agents to find pigs (75%), going to farms to look (69%), calling a farmer on a cell phone (67%),
or getting a call from a farmer on a cell phone (54%). Few butchers reported farmers bringing
pigs to the shop (11%). Butchers discouraged people from bringing pigs to the shop to protect
themselves from inadvertently purchasing a stolen pig. No butchers from Busia reported
purchasing pigs from a supplier on a truck, whereas a small percentage of butchers from
Kakamega (20%) did report that as a method for finding pigs. Table 2.7.2 presents the
50
operational practices of pig butchers that differed significantly between districts. Busia butchers
were 6.1 times (p ≤ .05) more likely to do repeat business with farmers than butchers in
Kakamega (Table 2.7.2). Few (11%) butchers said they had an agreement with farmers for
purchasing pigs, however none of the agreements were financial in nature. The agreements
were only verbal arrangements to do business in the future. Prices were never discussed until
time of the transaction. All exchanges were completed using cash. Although most butchers
(75%) reported using agents to find pigs, the proportions of pigs purchased through an agent in
rural Busia was significantly lower than that of peri-urban Kakamega (Table 2.7.2). Agents were
more like informants in that they put the butcher and farmer into contact with one another for
a flat fee.
Whether informed by an agent or contacted by a farmer, the butcher always travelled
to the farm to see the pig. Butchers reported travelling for 5.4 hours (sd=3.39) or 24.2 km
(sd=28.79) in a day to source pigs. Travel time and distances did not significantly differ between
districts. None of the butchers had access to credit for the procurement of pigs. A few butchers
explained that they often could not purchase their next pig until they had sold enough pork
from the pig currently in their shop. Sometimes a butcher had an opportunity to purchase a pig,
but by the time the capital was raised, the pig had been sold to another butcher. Butchers
mentioned, informally, a desire to expand their inventory of pigs, seeing opportunity in buying
young pigs to feed to market weight or to have pigs as a safety net for when they lacked capital
or could not find a pig to purchase. Busia butchers were 11.1 times (p ≤ .10) more likely to keep
pigs on their farm than Kakamega butchers (Table 2.7.2). Busia butchers also reported
51
significantly lower average pig weights and pig purchase prices (per kg) than Kakamega
butchers (Table 2.7.2). Butchers classified the factors affecting the price they were willing to
pay for pigs on a 5-point Likert scale from most important (5) to least important (1) as follows:
size of pig (4.91), health of pig (4.86), time of year (3.86), sex (3.29), breed (3.27), and age
(2.73). The size and health of the pig were scored significantly higher than the time of year (p ≤
.09), sex, breed, and age (p ≤ 0.0002). All butchers estimated the weight of the pigs without use
of a weight scale. Butchers reported that 29% of the farmers knew the weight of their pig.
Butchers negotiated the price of the pig directly with the farmer. Negotiations began with a
farmer stating the price. The gender of the farmer who bartered with the butcher was
approximately evenly distributed between males (54%) and females (46%). Purchases were
cash sales, so once a butcher purchased the pig, he bore the cost of the pig if the carcass was
condemned at the time of inspection, if the pig was stolen, or if the pig died during transport.
2.3.4. Transportation
Butchers required transportation in several situations; to get to farms to look at the
pigs, to move the pig back to a temporary holding space such as the butcher shop or the
butcher’s home, to move the pig to the slaughter slab, and to transport the pork carcass in a
transport box from the slaughter to the butcher shop. Butchers purchased 62% of their pigs
from outside of their own village. The main reason cited by 97% of the butchers was that the
farmers wanted too much money in their village. One butcher commented that neighbors could
see him making progress and therefore thought they expected a higher price due to jealousy.
52
Other reasons included; not enough pigs in their own village (83%), pigs too small in their own
village (81%), and pigs not healthy in their own village (81%).
Table 2.7.3 lists the methods of transport that butchers used for getting to farms to see
pigs, transporting pigs from the farm, and transporting pork from the slaughter to the shop. A
butcher walked to a farm to see a pig if the farm was close enough. However, pig butchers in
Busia were more likely to use bicycles, whereas Kakamega butchers were more likely to use
rented motorcycles for farms that were not within walking distance (Table 2.7.3). Purchased
pigs were most often walked from the farm, but might have been tied to a bicycle in Busia or to
a motorcycle in Kakamega (Table 2.7.3). Some butchers mentioned that transporting a pig on a
bicycle was illegal. If butchers found pigs close enough to their business, they did not incur
transportation costs because they could walk the pigs. Butchers less frequently paid for
transport in Busia than butchers in Kakamega (Table 2.7.3). Some problems associated with
transport that were mentioned informally by the butchers included; during transport,
authorities asked the butcher for a letter from the person who sold him the pig, pigs were too
far away, cycling through rough terrain was very difficult, bicycles got damaged while looking
for pigs, butchers were fined for allegedly purchasing a stolen pig. Some problems with travel
that were mentioned informally by the butchers included; farmers not being at the farm when
they arrived to purchase the pig (and therefore the butcher needing to make another visit),
farmer had sold the pig by the time the butcher got to the farm, or the butcher got to the farm
but the pig wasn’t large enough to be slaughtered.
53
2.3.5. Slaughter
Slaughter slabs were privately run enterprises, and butchers were charged a fee for each
pig slaughtered. A government inspector examined the carcass at the slaughter slab and
condemned unsafe meat. After inspections, the butcher was provided with a ticket to display
alongside the pork in the shop to show the inspection date. All but one butcher said that 100%
of their pigs were slaughtered at the slab. However, some butchers (14%) admitted that not all
pigs were inspected, especially in very busy seasons such as Christmas. Government inspectors
were to be available at each slaughter slab for a short time each day, usually in the mornings.
Two butchers mentioned informally that government inspectors did not come every day, or
came later than expected on some days, resulting in some missed pork inspections. Overall,
butchers reported that 93% of the pigs they slaughtered were inspected. This did not differ by
district.
2.3.6. Marketing
Pork was sold in local shops either as raw pork or as a plate of cooked pork, served
optionally with ugali which was sold separately. Ugali, the staple food in the area, is maize flour
cooked with water into a dough-like consistency. Butchers in rural Busia were 20 times (p ≤ .05)
more likely to sell cooked pork than butchers in peri-urban Kakamega (Table 2.7.3). For
butchers that sold cooked pork, less than half (41%) of the pork they sold was cooked, while
59% was sold raw.
54
Butchers hired 2.8 employees (sd=1.38) to help run their operations. Employees served
many functions, including cutting pork, serving customers, cleaning, cooking, and helping with
slaughter (Figure 2.8.1). Some butchers relied on employees to look for and transport pigs.
2.3.7. Government regulation
Butchers were required to have health certificates for each employee who handled pork
in their shops. A local business license was also a prerequisite for keeping a shop. One butcher
admitted he was operating part-time without a license. Business licenses, health certificates,
and weigh-scale inspections were charged to butchers on an annual or semi-annual basis.
2.3.8. Butchers’ perspectives on their challenges
Table 2.7.4 lists the challenges scored by butchers (using a Likert scale) in each district
from highest (5) to lowest (1). Busia butchers scored seasonal variation and access to capital as
their highest challenges (Table 2.7.4). The Busia butchers scored seasonal variation higher than
butchers in Kakamega (p ≤ .05). Seasonality reduced sales and forced butchers to lower prices.
The reasons cited for lower sales were that people needed money for school fees, farm inputs,
and planting, and therefore did not have extra money to buy pork. Kakamega butchers scored
pig prices and finding pigs as their highest challenges. Kakamega butchers scored finding pigs as
a higher challenge than butchers in Busia (p ≤ .05). Selling the pork was the lowest scored
challenge for butchers in Busia and Kakamega (Table 2.7.4).
Table 2.7.5 provides the seasonal variation of pig purchases by month. From August
through September, pig purchases increase, after the biggest harvest and the sale of crops
55
which gave farmers disposable income to purchase pork. November and December were very
busy months, attributed to people having money available from the second harvest. Also,
family members came back to the villages for the December holidays, bringing money from
their city jobs, and families were more likely to eat pork during the holidays. No significant
differences in pig purchase counts were found between Busia and Kakamega butchers for any
given month.
2.4. Discussion
2.4.1. The butcher and the role of butcher enterprise in pork marketing
The butchers in the local pig-marketing system are central to the coordination of
activities required to connect pig farmers to pork consumers in their communities. The
butchers provide smallholder farmers the only legal marketing outlet for inspected pork, as
they are required to have health and business licenses to handle and sell pork. Butchers invest
their own capital and assume the risks associated with purchasing pigs, transporting them,
having them inspected, and selling the pork. They also create employment opportunities in
their communities. Employment creation is an important benefit of local markets (Puskur et al.,
2011). Many butchers, particularly in rural locations also cook the pork. Consumers rely on the
butchers to have the pork inspected and to safely handle and cook the pork. It is important that
butchers appreciate the need to have pigs inspected and to ensure that pork is properly
cooked. Infection from zoonotic pathogens such as porcine cysticercosis, trichinellosis and
toxoplasmosis can occur from the consumption of infected and undercooked pork (Thomas et
al., 2012). Estimates on the prevalence of porcine cysticercosis in the study locations has been
56
reported to be between 4 and 4.5% at the pig level, and between 9% and 15% at the farm level
depending on the testing method and the study (Kagira et al., 2010c; Mutua et al.,2011). The
outreach and training on prevention of zoonotic pathogens has tended to focus on farmers
(Flisser et al.,2003; Ngowi et al., 2009; Wohlgemut et al., 2010). Educating butchers is also
important as results from this research show that butchers do not have all their pork inspected
and the butchers that sell cooked pork are the last prevention point before pork is consumed.
Kagira et al., (2010b) reported that the District Veterinary Officer felt there was insufficient
staffing and transport capacity to support the number of slaughter slabs in Busia District. The
government should equip inspectors with the resources to travel to each slaughter slab more
frequently than once a day during high seasons and ensure visits are consistent during lower
seasons. In this study, the one unlicensed butcher that operated part-time did not use slaughter
slab facilities, or have pork inspected, or have a license to handle and sell pork. Un-inspected
pork increases the health risk to the community as discussed above and may compromise the
reputation of the industry if people fall ill due to consuming un-inspected pork. Butchers that
do not pay for slaughter, inspection or licenses have fewer expenses which make for illegal and
unmerited competition. Further research should be completed to understand community
perceptions of illegal pig slaughtering, and the impact unlicensed butchers have on the pork
industry.
2.4.2. Procurement
Butchers spent a considerable time searching for pigs. The travel time and expense of
travelling to farms only to find the pigs were not market weight, the farmer was not present at
57
the farm to negotiate a price, or the pig had already been sold was challenging for butchers. It is
also costly to have to visit each farm and negotiate each pig purchase given the distances that
butchers must cover. The cash-only exchange of goods without any pre-arranged agreements
or warranties has been characterized as a “flea market economy” by Fafchamps (2004). In the
absence of weigh scales, grading systems, and contracts, butchers will not risk a pig acquisition
without seeing the pig despite doing repeat business with farmers, and farmers will not allow
the butcher to take the pig without cash payment. The lack of contractual enforcement (and
therefore use of contracts) and grading systems has been recognized as costly to marketing
systems in SSA (Poulton et al.,2010; Coulter et al.,2002; Kyeyamwa et al.,2008). The pig weight
was the most important criteria for butchers in evaluating pig prices. Without weigh scales,
butchers and farmers had to estimate the weight of the pig to negotiate the price. Since
butchers reported that only 29% of farmers were able to estimate the weight of pigs, there was
likely inequality of abilities and to estimate pig weights during price negotiations. Farmers who
under-estimate their pigs’ weight, may under-value the pig and consequently receive a poor pig
price. Smallholder farmers generally only sell 1 pig per year (Kagira et al., 2010b) so low
revenue from a poorly negotiated pig sale could have a substantial impact on annual income,
and lower farmers’ incentive to raise pigs. Kyeyamwa et al. (2008) identified a similar scenario
in Ugandan cattle markets, where traders had the experience of negotiation, could better
estimate cattle weights, and knew prices in the various markets available to them. Busia
farmers reported receiving low prices in the study by Kagira et al., (2010). To reduce a butcher’s
advantage of being able to better estimate pig weights, the use of tape measures should be
58
encouraged. Weight charts have been produced for pigs in the area of study (Mutua et al.,
2011). Tape measures have been used in the absence of weigh scales for sheep and other
ruminants (Kunene et al., 2009). Better estimated weights could also improve communication
with the butcher to further reduce search costs and increase information flow. Producer groups
could also help increase the efficiency of pig exchanges between butchers and farmers by
producing a set of standards for pricing pigs, and tracking the prices of pigs sold based on the
standards applied. These pig sales could be shared on local marketing boards (Kyeyamwa et al.,
2008; Shiferaw et al., 2011). Lack of market information was a reported challenge by pig
farmers in Busia (Kagira et al., 2010). Shiferaw et al. (2011) suggested that collective action is
not as important for local markets as it would be for upstream markets. However, farmer
groups could help to reduce the transaction costs associated with the local marketing system
described and could benefit and promote cooperation between all stakeholders in the market.
Leveraging technology such as SMS messaging for cell phones or other cellular
communication protocols could also improve the information flow for pig exchange. Not all
farmers have cell phones, but the results from this study have shown that farmers and butchers
do communicate about potential pig exchanges using cell phones. Use of electronic media has
been acknowledged as a potential solution for increasing information access (Kyeyamwa et al.,
2008; Poulton et al., 2010). Electronic solutions have already seen traction in larger markets.
Kenya does have an electronic commodity exchange board called KACE (Kenya Agricultural
Commodity Exchange), which is a privately operated and facilitates commodity exchanges. A
simplified, localized messaging system (either electronic or a simple bulletin board) could
59
effectively service rural markets as well if it could be made cost effective and sustainable. A lack
of sustainable financing has hindered the potential benefit that could be achieved with market
information systems in SSA (Tollens, 2006).
2.4.3. Slaughter and transport
The challenges associated with slaughter and transport included condemned carcasses
and death or loss of the pig in transit. Butchers assumed the risks of loss of the pig from the
moment the cash was exchanged with the farmer. Loss of one pig could result in a complete
depletion of capital, which could force the butcher out of business. The risk of purchasing a pig
and not being able to receive revenue from it due to loss is amplified in a marketplace where
butchers are constrained by capital. Insurance programs to protect butchers from losses due to
condemned carcasses or transport should be researched for feasibility and discussed with
butchers to evaluate uptake of such programs. Currently, if a butcher has the carcass
condemned, he may not have enough capital to purchase another pig for his shop, so we feel
that butchers would take an interest in insurance products to back their pig purchases.
Targeting butchers for insurance programs could reduce the costs associated with monitoring,
moral hazard, and adverse weather conditions that have disrupted farmer insurance programs
in the past (Poulton et al., 2010).
2.4.4. Marketing
Selling the pork was not a highly scored challenge for the butchers. An evaluation of cost
structures, and marketing margins was beyond the scope of this paper; however detailed net
60
income statements should be assessed to understand the efficiency of butchers in rural and
peri-urban settings, and the potential profitability of pigs for farmers and pig butchers in these
markets.
2.4.5. Challenges and rural and peri-urban differences
Butchers faced a myriad of challenges in the day-to-day functioning of their enterprises.
The rural Busia butchers scored seasonal variation and capital as their highest challenges (Table
2.7.4). The two challenges are likely related. In Busia, farmers are more dependent on farm
income, so their disposable income fluctuates with harvest or wet and dry seasons. The dry
seasons are difficult for marketing pigs, so butchers buy and market fewer pigs and lower their
pork price, which negatively impacts their income, and working capital. The effect of seasonal
market fluctuations is not unique to pork demand and reflects the seasonal pricing challenges
of many commodities in SSA (Williams et al., 2006; Michelson H., 2012). Suggested approaches
to consumption smoothing include the use of warehouse receipt systems (Coulter J. and
Onumah G., 2002), and better infrastructure to promote distance trading (Poulton C., 2010).
However, warehousing pork requires electricity and freezers, neither of which is available to
these butchers.
Kakamega butchers’ greatest challenges were high pig prices and finding pigs. In turn,
they relied more on agents to find pigs. Butchers used agents to find pigs, rather than
middlemen, likely because it was less expensive to pay a search fee to an agent, than a mark-up
fee to a middleman. Generally, as the number of exchanges increase, the farmer’s share of the
61
retail price tends to decrease and deters participation (Kyeyamwa et al., 2008). Researchers did
not get the sense from butchers that there were many pig middlemen in the market, and only
encountered and interviewed one middleman (excluded from the study), who claimed to
purchase most of his pigs in Uganda (Busia borders Uganda). However, Kagira et al. (2010)
suggested that in Busia, “amorphous” middlemen did purchase pigs to resell them to butchers
but these researchers could not quantify margins or numbers of pigs. The Kenyan Pig Industry
Act discourages the activities of middlemen, as it is legal for a farmer to sell pigs only to other
farmers, a licensed pig butcher, or a licensee of a bacon factory (Anonymous, 2006).
Butchers were capital constrained, with no access to credit as is seen with many small
enterprises in marketing chains in SSA (Atieno, 2001; Kyeyamwa et al., 2008; Ajala &
Adesehinwa, 2007; Jabbar et al., 2008). Some butchers could not purchase their next pig until
they had enough revenue from the pork currently being sold in their shop. During low seasons,
when butchers are charging less per kg of pork, raising the capital for the next pig becomes
even more difficult, and butchers in turn have to lower the price they offer farmers. Busia
butchers were more likely to keep pigs as part of their own farm asset mix, likely, to ensure
having a steady supply of pork for their shops, or a buffer from short-fall of capital to purchase
another pig. It also may indicate that the transaction costs associated with purchasing pigs is
higher in Busia, and therefore butchers have more incentive to integrate their operations
vertically (Klein et al., 1978; Coase, 1937). The Busia butchers also purchased smaller pigs,
which meant they had less marketable pork per pig, requiring them to purchase pigs more
often.
62
The challenges described in this paper agree with those presented by Kagira et al. (2010)
who identified travel, pig transport and seasonality as challenges in Busia. Their research also
mentioned police and authoritative conflicts and outbreaks of African Swine Fever causing pig
shortages. Butchers in the current study were given the opportunity to add to the list of
challenges provided by the researchers. However, they did not add the challenges mentioned
by Kagira et al. (2010). Other researchers have more broadly attributed credit, transportation,
communication, and corruption as limitations to the effectiveness of agricultural markets in
emerging economies (Barrett and Mutambatsere, 2005; Kydd et al., 2004; Kyeyamwa et al.,
2008)
Rural butchers rode bicycles and paid for transport less often, whereas peri-urban
butchers relied more on motor transport. Most butchers in rural Busia but only a few butchers
in Kakamega sold cooked pork. People in Busia may find it more challenging to cook meat
because of firewood scarcity or the additional costs incurred. The demand for cooked pork in
Kakamega may have been too low to make cooking pork worthwhile in most market places.
Another possible explanation is that in Busia, there were two market days each week. Local
farmers converged to the market to sell their wares on these two days. In contrast, Kakamega
markets were established marketplaces that were always open. As there are differences
between the rural and peri-urban markets, approaches to intervention, educational
programming, or regulatory policy should consider these differences.
2.4.6. Study limitations and challenges
63
This study used a convenience sample from 4 sub-locations; Butula and Funyula in Busia,
and Shinyalu and Ikolomani in Kakamega. The differences which contrasted Busia and
Kakamega butchers were extensive. Our samples are therefore not likely representative of
many markets in Kenya which differ in population density, pig rearing systems, infrastructure,
and consumer demand. Central Kenya and markets around Nairobi for example are much
higher density areas, pig-rearing is more intensive, transport conditions are different and
commercial pork processors such as Farmers Choice operate large facilities likely offer a greater
marketing opportunity to farmers in those areas (FAO, 2012; Wabacha et al., 2004). Having
livestock officers and village elders enumerate and enroll pig butchers likely made butchers feel
compelled to participate in the study, and butchers may have been reluctant to discuss some
aspects of their business as a result. Un-licensed butchers may have been under represented as
livestock officers were likely unaware of their operations to enumerate them. The proportion of
pigs that were reported to be slaughtered may have been over-reported as a result. Surveying
pig butchers was challenging as they are often in transit searching for pigs.
2.5. Conclusions
Understanding the pig-butcher enterprise and the pork marketing system may lead to
innovations, interventions, or education opportunities to increase marketing efficiencies and
improve product quality, which ultimately should increase profitability for farmers and butchers
and make safe protein sources more accessible to resource-poor people. Several differences
between rural and peri-urban market settings were identified in this study including pig sizes,
pig prices, agent use, farmer-butcher relationships, methods of travel and transport, and the
64
marketing of pork (cooked or raw), and should be given consideration when addressing policy
issues, or extension services.
Butchers service a large number of smallholder farmers and are key to the marketing of
pork. They also add employment opportunities to people in their communities. Further
research is required in the areas of public health, innovation, profit margins, value-chain
improvements, and marketing approaches to ensure a sustainable indigenous pork market. For
example, public health can be enhanced by ensuring inspectors are available more frequently
during high consumption seasons. Market information can be improved by innovations such as
a marketing board. Marketing efficiencies and profitability for farmers and butchers can be
improved by promoting the tape measure as a tool to estimate the weight of the pigs. If
farmers become more knowledgeable about the weight of the pigs they are selling, the
communication between butchers and farmers will be better and the trade of pigs will be more
equitable. Farmer groups could aid in reducing transaction costs incurred by both the farmer
and the butcher, and should be further explored.
65
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69
2.7 Tables
Table 2.7.1: Count of pig butchers who were enumerated and voluntarily participated in a
cross-sectional observational study in Busia and Kakamega Districts of Western Kenya, 2008-
2009.
Busia Kakamega Total
Enumerated and interviewed in 2008 only 16 20 36
Enumerated and interviewed in 2009 only
(in business in 2008 but not enumerated)
4 2 7
Enumerated and interviewed in 2009 only
(new to business in 2009)
5 3 8
Enumerated in 2008 but not interviewed in 2008 or
2009
0 1 1
Enumerated and interviewed but excluded from
study because inclusion criteria not met
2 0 2
Total butchers enumerated in 2008 or 2009 that met
inclusion criteria
25 26 51
Total butchers interviewed in 2008 or 2009 that met
inclusion criteria and were included in study
25 25 50
Participating butchers responded to a questionnaire in either English or Swahili. The questionnaire was exploratory in
nature, designed to capture information about the butchers, their processes, and their opinions on challenges of pig
butcher operations in the areas of procurement, transport, slaughter, marketing, and government regulation.
70
Table 2.7.2: The operating practices of pig butchers found to be significantly different
between rural (Busia) and peri-urban (Kakamega) Districts in Western Kenya, 2008-2009.
Operational practice being compared Busia
(rural)
Kakamega
(peri-urban)
P-value
a% of butchers who do repeat business with farmers 81 40 ≤ .01 a% of pigs purchased using an agent 27 47 ≤ .05 a% of butchers that keep pigs on their farm 81 30 ≤ .01 a% of butchers that pay for transport 46 72 ≤ .01 a% of butchers that sell cooked pork 88 26 ≤ .01 bTypical pig purchase weight (kg) 33
(sd=9.96)
43.4
(sd=11.51)
≤ .01
bTypical pig purchase price (Kenyan shilling) per kg
live weight
78.2
(sd=12.3)
85.4
(sd=12.9)
≤ .05
Source: Field data from survey of pig butchers taken in 2008 or 2009 (Table 2.7.1). a Differences of proportions (%) across districts were assessed with a chi-squared analysis.
b Differences in means between districts were assessed with Student’s t-tests.
71
Table 2.7.3: Proportion of butchers using various modes of transportation to locate and transport pigs to the butcher shop and
slaughter slab in Busia (Bus) and Kakamega (Kak) Districts of Western Kenya, 2008-2009.
Travel to farm to buy pig Transport pig from farm Transport pig to slaughter slab
Bus
%
(n=16)
Kak
%
(n=20)
OR P value Bus
%
(n=16)
Kak
%
(n=20)
OR P value Bus
%
(n=16)
Kak
%
(n=20)
OR P value
Walk 15 35 - - 40 57 - - 30 79 8.5 (≤ .05)
Bike 95 35 .029 (≤ .01) 95 0 0.011 (≤ .01) 70 7 0.03 (≤ .01)
Motor
bike
10 71 22.5 (≤ .01) 15 29 - - 5 7 - -
Motor
car
0 7 - - 0 7 - - 0 0 - -
Hire a
person
n/a n/a n/a n/a 0 21.4 - - 5 0 - -
Source: Field data from survey of pig butchers taken in 2008 or 2009 (Table 2.7.1).
Odds Ratio (OR) based on Fisher’s exact test (Davis, 2007).
n/a Not applicable
- Not significantly different
72
Table 2.7.4: Challenges in operating a pig butcher enterprise as scored by the relative
importance by butchers, illustrated by the mean value of a score from 1 (low) to 5 (high)
challenge in Busia and Kakamega Districts, Western Kenya, 2008-2009.
Busia Kakamega
Challenge Mean Median Challenge Mean Median
Seasonal
variation x
4.3 4 a Pig prices 4.4 4
Capital 4.3 4.5 ab Finding pigs y 4.4 5
Licenses 4.2 5 ab Licenses 4.2 4
Pig prices 4.2 4.5 ab Travel 4.2 4
Transport 3.6 4 ab Capital 4.2 4
Travel 3.4 3.5 ab Transport 4.1 4
Competition 3.0 2 ab Profit 3.4 3
Profit 2.9 3 b Seasonal
variation y
3.3 3
Finding pigs x 2.8 3 ab Competition 2.9 3
Selling pork 2.8 3 b Selling pork 2.6 2
Source: Field data from survey of pig butchers taken in 2008 or 2009 (Table 2.7.1).
The Busia butchers scored seasonal variation higher than Kakamega butchers (p ≤ .05).
Kakamega butchers scored finding pigs higher than Busia butchers (p ≤ .05).
ab challenges within district (columns) with different superscripts were rated differently at p ≤ .05
xy rating of challenges differed between districts (rows) at p ≤ .05
73
Table 2.7.5: Number of pigs purchased per month by Butchers in Western Kenya.
Busia Kakamega
Month Mean sd Mean sd
January 16.1a,c, g 5.08 16.0a 6.30
February 15.2a,c,g 4.61 15.7a,b 6.41
March 14.5a 4.85 14.2a,c 6.88
April 14.7a,c,g 6.99 14.1a,c 6.67
May 14.0a,c 6.42 13.1a 7.52
June 14.7a,c,g 7.52 13.6a 7.31
July 18.7a,c,b,e 7.58 14.1a 6.94
August 21.0b,d,f 6.82 17.2a 7.60
September 19.1a,c,f 7.54 19.8a,c 7.85
October 19.2a,c,g 7.39 19.0a,c 8.13
November 20.6e,d, g 7.10 24.1b,c,f 7.86
December 27.2h 7.82 25.8bg 6.62
abcdefgh Pig purchases per month within columns with different superscripts differed based on Tukey p-values
(p≤.05).
74
2.8. Figures
Figure 2.8.1: The communication of people, the movement of the pig, and the activities
coordinated by pig butchers in getting pigs to local markets in the Busia District (rural) and
Kakamega District (peri-urban) of Western Kenya.
Agents Butcher
Cooker
CutterServer
Smallholder farmers (pig producer)
1. Procurement
Transporter or butcher
2. Transportation
Slaughter help
Government inspector
3. Slaughter
Slaughter slab owner
Consumer
4. Marketing
Public health
inspector
5. Regulation
Business license
officer
Weigh scale
inspector
Legend:
communication path between various stakeholders
flow of the pig moving chronologically through the marketing system
75
CHAPTER 3: PIG MARKETING AND FACTORS ASSOCIATED WITH PRICES AND
MARGINS IN WESTERN KENYA
Published as: Levy MA, Dewey CE, Weersink A, Mutua FK, Poljak Z (2014). Pig marketing
and factors associated with prices and margins in Western Kenya. Journal of Agricultural
Economics and Development, 2(10): 371-383.
3.1. Introduction
Efficient marketing plays a critical role in economic development and poverty
alleviation (Fischer and Qaim, 2012; Ajala and Adesehinwa, 2008; Timmer, 1995; Diao et
al., 2003). Despite marketing reforms of the 1980s, farmers in Sub-Saharan Africa (SSA)
still face dismal marketing conditions because of remoteness, high risks of trade,
underdeveloped financial, institutional and physical infrastructure, and an
underdeveloped private sector (Poulton, 2010; Shiferaw et al., 2011; Kydd and Dorward,
2004, Fischer & Qaim, 2012; Minten and Kyle, 2000; Gabre-Madhin, 2001).
This study focuses on the marketing margins as a proxy for the performance of
pork value chains in rural and peri-urban settings of Western Kenya. High transport
costs and the high standards of urban processing centers limit smallholder farmers to
selling pigs to local butchers (Kagira et al., 2010; FAO, 2012). The FAO (2012) claim pig
butchers offer farmers 'low and exploitative prices’. “Exploitative” might suggest that
the market is not competitive (Ajala and Adesehinwa, 2008; Marsh and Brester, 2004);
physical marketing costs such as transport, travel and storage are high (Fafchamps et al.,
2005); or pig butchers require significant compensation for the opportunity cost of
76
invested capital, risks of trade, and transaction costs, which are prominent in SSA
(Gabre-Madhin, 2001; Minten and Kyle, 2000).
In Nigeria, Ajala and Adesehinwa (2008) studied the performance of pig
marketing in rural and urban markets and reported an average marketing margin (cost
of marketing services as a proportion of the consumer price) of 39%. The market
structure is oligopolistic which the authors attributed to the large amount of operating
capital required by marketing agents (Ajala and Adesehinwa, 2008). Marketing agents
with high levels of education, better access to financial capital, who make regular use of
brokers, have repeated interaction with suppliers and customers (better social
networks) often earn higher profit margins (Minten and Kyle, 2000; Fafchamps et al,
2005; Ajala et al., 2008; Jabbar et al., 2008; Abankwah et al., 2013; Toure and Wang,
2013; Nganga et al., 2010). Ajala and Adesehinwa (2008) also noted the importance
traders placed on pig weight when evaluating pig price. However, the impact of pig
weight on marketing margins has not been quantified. Addressing this gap, we
hypothesize that pig weights will impact the prices farmers receive, butchers’ profits and
the marketing margin.
In this study we evaluate pig prices, pork prices, marketing costs, profitability,
marketing margins and butcher-related factors associated with them. Using a unique
data set of 49 pig butchers, respondents were first categorized into low, medium, and
high profitability groups and the components of net income that differed among the
77
groups were determined. Using regression analysis, we examined specific butcher
characteristics and operating practices associated with pork price, pig price, marketing
and operating costs, butcher profit, and marketing margins. This analysis was essential
to determine the factors which impact butchers, farmers, and consumers in local
marketing chains and to identify opportunities to improve pork marketing and the
welfare of stakeholders.
3.2. Materials and methods
3.2.1. Study location
Four divisions in the Western Province of Kenya: Butula, Funyula, Ikolomani, and
Shinyalu were selected because of their large population of pigs, history of pig keeping,
and high prevalence of poverty (Mutua et al., 2011; Kagira et al., 2010b). Butula and
Funyula are located approximately 30 km apart within Busia District, a rural area,
population 488,075 (Anonymous, 2009). Butula has larger, more trafficked market
places than Funyula and is situated closer to the city of Busia in Busia District. Shinyalu
and Ikolomani are located approximately 9 km apart in the peri-urban Kakamega District
(population 1,660,651; Anonymous, 2009). Shinyalu has larger, more trafficked market
places than Ikolomani, with most butchers situated on or near the main road between
Kakamega, a city of 100,000 in Kakamega District, to Kisumu, a city of 400,000 in Kisumu
District.
78
3.2.2. Pork marketing chain
There are no central markets for trading live pigs in Kenya (FAO, 2012). This is
likely attributed to the limited volume of pigs and high transport costs for shipping pigs
to urban centers and because most pigs in rural locations do not meet the standards of
urban processing plants (Kagira et al., 2010). Pigs are traded at the farm-gate (FAO,
2012) based on a negotiated price between the farmer and butcher. The pork is sold
locally by the pig butchers. Butchers are required by law to have their pork inspected by
government inspectors.
3.2.3. Survey
A structured price sheet (Figure 7.3) was designed to elicit pricing information
from butchers on their revenues, marketing and operating costs, and pig prices in order
to evaluate each pig butcher’s net income statement. Revenue items included the per kg
pork price posted in the butcher shop, any premium charged for cooking pork, and a line
item for each additional revenue from pig parts (including the head, feet, legs, ears,
tongue, heart, kidney, liver and lungs) that a butcher sold at a different price than the
posted pork price. Marketing items included transportation, slaughter, agent use,
inspection of pork, labour, cooking costs, and amenities on a per pig basis. Operating
cost items included yearly license fees and monthly rent. Pig prices were collected by
having butchers provide an average price they pay farmers for a live pig weight of 22,
30, 35, and 45 kg, or the corresponding dressed weight of 16, 22, 26, and 33 kg
respectively. The weight categories provided to butchers were based on the 25th, 50th,
79
and 75Th percentile weights (22, 30 and 35 kg) for pigs in Busia at market age (5.1 to 9.9
months) (Mutua et al., 2011c) and a median breeding pig weight of 42 kg (Mutua et al.,
2011b). In the study by Mutua et al. (2011c), pigs were weighed by researchers using
weight scales in order to develop a tape measure system for estimate pig weights. The
tape measure and weight chart tables were provided to farmers one year before our
study began. The uptake of the tape measure method by pig farmers has not been
studied. Butchers can weigh pig carcasses after slaughter as weight scales are available
at slaughter slabs.
To assess factors associated with the pig prices (paid to farmers), pork prices
(charged to consumers), marketing and operating costs, butcher profits, and marketing
margins, an accompanying questionnaire was developed with three sections. The first
section included questions on butcher characteristics including age, years of experience,
education, and location of shop. The second section contained general questions to
attain the butchers’ operational practices including hours of travel per day, number of
pigs purchased per month, use of agents, use of cell phone, contractual agreements,
credit access, and marketing type (sells cooked pork or only raw pork). The third section
gathered information on the butchers’ assets including the number of telephones,
bicycles, availability of electricity and piped water, armchair sets, water tanks,
generators, glass windows, wheelbarrows, hand carts, motorcycles, latrines, radios,
televisions, and clocks.
80
3.2.4. Sampling frame
An enumeration of all pig butchers in the retail market locations within the four
study divisions was carried out in 2008-2009 with the help of government meat
inspectors, pig farmers, village elders, and other pig butchers. All enumerated butchers
were invited to participate in the interview. Pig butchers were initially contacted by a
village elder or a government inspector who described the research study. In total, 25
butchers in Busia and 26 in Kakamega were enumerated. One butcher could not be
reached in 2008 or 2009 and another butcher was excluded from this study because he
was unable to provide pig purchase prices for any of the provided pig weights.
3.2.5. Data Analysis
All collected data were entered into Microsoft Excel 2007 (Microsoft, Redmond,
WA, USA), and descriptive tables were created using SAS 9.1 (SAS Institute, Cary, NC,
USA). Net income statements for each butcher were produced, and each butcher was
placed into a low, medium, or high profit category. Butchers with an average net income
per kg of less than zero were assigned to the low-profit group. Butchers in the upper
75th percentile of average net income per kg were assigned to the high-profit group, and
the remaining butchers were assigned to the medium-profit group. Analysis of variance
(ANOVA) was used to determine which cost components of the net income statement
differed by profit group, using the year of interviewing as a fixed effect to control for
price variation between years. Statistical significance was assessed by the overall F-test,
followed by the t-test comparison among different profit groups.
81
The level of competition was evaluated using a concentration ratio (Ajala and
Adesehinwa, 2008).
Concentration ratio = sales volume of pig purchases in a year of largest four firms
/ total volume for all butchers *100
A concentration ratio of less than 33% is considered competitive as the highest
volume butchers do not sell the majority of the pigs in the market. The concentration
ratio was calculated for each District (Busia and Kakamega), and each Division (Butula,
Funyula, Shinyalu and Ikolomani).
The pork price for consumers, pig price and marketing margins (of interest to
farmers), marketing costs and profits for butchers are vital indicators for participation
and impact the sustainability of local market chains. Determining the factors associated
with the variation in these prices, costs and profits will provide a more comprehensive
understanding of the marketing value chain than cost structures alone. To determine
the associations, linear regression modeling was applied, and took the forms:
Yi = a + biXi + Ei
where Y is the outcome variable of interest (either pork price, pig price, marketing and
operating costs, butcher profit or the marketing margin, all measured on a per kg basis);
XI is the vector of independent variables which are outlined in Tables 3.6.1a and 3.6.1b;
b is the vector of corresponding parameter estimates; a is the intercept; and Ei is the
82
error term. For the dependent variables of pig price, marketing and operating costs,
profit, and marketing margin, there were four observations per butcher because
butchers provided their price for each pig weight category (22, 30, 35, 45 kg). To
account for the dependence between observations at the butcher level, individual
butcher identification was included as a random effect, blocking on pig weight category.
We therefore chose a general linear mixed model (GLMM) which was fit in SAS 9.1 (SAS
Institute, Cary, NC, USA). Unequal variance was allowed for by pig weight, because
residual plots suggested unequal variances. Significance was assessed at p<0.05.
Independent variables were first screened using a significance level at p<0.25. Manual
backwards elimination was employed to reach reduced final models. An ICC was
calculated for each reduced model to determine the random variation attributable to
the butcher for each pig weight. Several plausible interactions were evaluated during
the model building process including division and hours of travel, division and education
level, and years of experience and education level. Residuals of each categorical variable
were visually evaluated for homoscedasticity. Residuals were also assessed to test for
linearity using a Shapiro-Wilk W statistic. The linearity assumption was not met
according to the Shapiro-Wilk W statistic; however the histogram of the residuals
appeared bell-shaped after plotting. The same models were also fit using logarithmic
transformations on the outcome variables and continuous independent variables but
the residuals were not normally distributed based on Shapiro-Wilk statistic. Models with
non-transformed outcome variables were presented for simplicity of interpretation.
83
For the dependent variable pork price per kg, it was not necessary to block on
weight, as butchers charged one pork price regardless of the weight of the pigs they
purchased. Since there was only one observation per butcher, a general linear model
was fit to assess the associations between the independent variables outlined in Tables
3.6.1a and 3.6.1b, and the pork price per kg. Independent variables were first screened
using a significance level at p<0.25. Manual backwards elimination was employed to
reach a reduced final model. Linearity and homoscedasticity assumptions were met for
the general linear model, using a Shapiro-Wilk W statistic, and visual inspection
respectively.
3.3. Results and discussion
3.3.1. Butchers, their characteristics, and operational practices
In total, 49 butchers were included in the study. Table 3.6.2 provides a summary
of butcher characteristics and operational practices by profit group. Butula in Busia and
Shinyalu in Kakagmega had the highest concentration of butchers and all of the butchers
in the high profit group. These two Divisions were observed to have the highest
trafficked market centers; they also have the highest populations and are closer in
proximity to the major cities within their respective Districts. Conversely, no butchers
from Funyula or Ikolomani were in the high profit group. These two Divisions were
observed to have the lowest trafficked market centers. They also have the lowest
populations and are situated furthest from the city centers within their corresponding
Districts.
84
The education levels of the butchers varied. Approximately one third (34.7%) had
no formal education or a few years of primary school; 36.7% had completed primary;
and 28.6% had at least some high school (Table 3.6.2). Sixty percent (60%) of the
butchers in the high profit group had at least some high school education (Table 3.6.2).
More than half of the butchers sold cooked pork in their enterprise (Table 3.6.2).
Cooked pork was sold by 79% of butchers that operated in the Busia District. Butchers in
Kakamega reported informally that most of them do not provide cooked pork due to
low demand in that district.
No butcher reported having access to credit or electricity, and a small proportion
of butchers had piped water (Table 3.6.2). In the absence of capital, electricity, and
running water, butchers lack the ability to process pork. The absence of value-added
processing has been noted to limit market expansion in developing markets of SSA
(Gabre-Madhin, 2001).
A small proportion of butchers (16%) had contracts with farmers; the contracts
were simply verbal agreements to buy market weight pigs from farmers without delivery
standards or any commitment to prices. Absence of contracts increases transaction
costs of trading in SSA because personal travel increases to compensate for lack of co-
ordination, and costs of assessing an unknown trading partner’s trustworthiness
increase (Fafchamps et al., 2005). The age and experience of butchers was homogenous
across profit groups (Table 3.6.2); however 22% of the butchers interviewed had less
85
than 2 years of experience. Butchers purchased pigs almost daily, with a third of the pigs
being purchased through an agent (Table 3.6.2).
3.3.2. Competitiveness
By District, the concentration ratio (a measure of competitiveness) for Busia and
Kakamega was 24% and 26% respectively, indicating a competitive market structure.
When evaluated by Division, the concentration ratio for Butula, Funyula, Ikolomani, and
Shinyalu was 29%, 75%, 33%, 75%, indicating Funyula and Shinyalu to be more
oligopolistic. As butchers travel 5 hours (Table 3.6.2) or 25 kilometers per day (Levy et
al., 2009) searching for pigs, it is likely most appropriate to assume that butchers within
each District compete with each other for purchasing pigs, so we conclude that
purchasing pigs is competitive because of the low concentration ratio by District. With
respect to selling pork, consumers are not likely to travel the same distances as butchers
to purchase pork, so evaluating concentration ratio by Division is likely more
appropriate. The higher concentration ratios in the rural Divisions would indicate that
Funyula and Shinyalu butchers have greater opportunity to act as oligopolies than their
more urban counterparts in terms of pork sales. However, pig butchers are also thought
to be competing with the marketing of beef and chicken which could make them act
more competitively. Kagira et al. (2010) suggested that pork prices are lower during the
wet seasons when fish and beef supply is high. Pork is also likely to have high income
elasticity particularly in very rural locations where there are high levels of poverty which
86
should limit any price fixing practices. The barriers to entry included a yearly business
license fee and a health license fee. Working capital to purchase pigs was also required.
3.3.3. Net income statement and differentiating profit groups
Table 3.6.3 provides revenues, pig prices, marketing costs, operating costs, and
profit on a per kg basis for butchers categorized by profit group for each pig weight (22,
30, 35, 45 kg live weight). Prices with different superscripts within each weight category
are statistically different from one another.
3.3.3.1. Revenues
The revenues from pork sales ranged from 86% to 93% of the total revenue
earned from a pig, depending on the pig weight and the butchers’ profit group (Table
3.6.3). The remaining revenue came from selling additional pig parts which ranged from
7% to 14% of the total revenue (Table 3.6.3). Butchers in the high and medium profit
groups were charging a higher pork price than butchers in the low profit group (Table
3.6.3). The pork prices charged to consumers varied more than any of the other prices in
the net income statement (Table 3.6.3). In 93% (56/60) of the pig purchases that had
negative profits, the butcher was charging less than the mean pork price of the butcher
population (after adjusting for the year of purchase). The variation in pork prices is likely
driven by the demand for pork in the various market locations; which are spread over
large distances. Some price fixing may occur, as there is less competition for pork selling
in rural locations, but as discussed earlier, butchers are most likely acting competitively.
87
The butcher related factors associated with pork prices are further assessed and
discussed later.
3.3.3.2. Costs
Pig price accounted for 61% to 81% of the butchers’ total costs (Table 3.6.3).
Butchers in the high profit group offered lower prices for smaller (22 kg) pigs than
butchers in low and medium profit groups. The 30 kg pig price did not differ significantly
among profit groups (Table 3.6.3). Butchers in the low profit group offered higher prices
for larger (35, 45 kg) pigs than the medium and high profit butchers (Table 3.6.3). In 76%
(46/60) of the pig purchases that had negative profits, the butcher offered more than
the mean pig price per kg for pigs in each weight class, after adjusting for the year of
purchase. Variation in pig prices between butcher profit groups likely reflects the pig
supply in the locations butchers operate and butchers’ ability to assess the value of pigs
at different weight levels. Butchers in Kakamega have reported greater challenges in
finding pigs than butchers in Busia (Levy et al., 2009). While pig purchasing is likely
competitive, farmers still need to have good price information when selling pigs at the
farm-gate as the price is determined by negotiation. Butchers reported that some
farmers invite multiple butchers to their farm when selling a pig to gain pricing
information and to promote competition.
Marketing costs and operating costs as a proportion of total revenue ranged
from 15% to 37% depending on the pig weight and butcher profit group (Table 3.6.3).
88
Within each profit group, marketing and operating costs decreased with pig weight,
because slaughter, inspection and transport costs are charged on a per pig, rather than
a per kg, basis. This suggests that butchers can economize costs by purchasing larger
pigs (Table 3.6.3). Butchers in the high profit group had significantly lower transport and
slaughter slab costs than those in the low and medium profit categories (Table 3.6.3).
Slaughter slabs are privately owned and different arrangements exist for use of water
and labour which could explain differences in costs. Transport costs may also be
influenced by butchers’ proximity to slaughter slabs and better infrastructure near
larger cities.
3.3.3.3. Profit
The net income of butchers differed significantly by profit group for each pig
weight category (Table 3.6.3). The mean profits ranged from -9.7 to 30.5 KES per kg
(Table 3.6.3). Thirty-three percent (60/182) of pig purchases were not profitable. In 10%
(19/182) of pig purchases, the price offered for the pig exceeded the potential revenue
from the pork and 43% (21/49) of butchers had at least one unprofitable purchase,
indicating that some butchers did not always calculate a break-even price for their pig
purchases even when they were provided the pig weights by researchers. The variation
in profitability and the high proportion of negative profits experienced by butchers in
this study is not unusual for marketing systems of SSA (Minten and Kyle, 2000; Toure
and Wang, 2013; Fafchamps et al., 2005).
89
Table 3.6.4 presents the correlation coefficients between the price components
of the net income statement and profit. There was a moderate (.59) correlation (p <
0.001) between the butcher rankings for pork price charged per kg and profit earned per
kg (Table 3.6.4). There was a moderate (-.51) correlation (p < 0.001) between the
butcher rankings for pig price per kg and profit earned per kg (Table 3.6.4). The results
indicate the dependence of butcher profits on pig price and pork price.
3.3.4. Margins
Table 5 provides the profit margins and marketing margins grouped by pig
weight, division and education. The average profit margin for all of the butchers was 7%,
5%, 6%, and 10% for 22, 30, 35, and 45 kg pigs, respectively (Table 3.6.5). The interest
rate in Kenya at the time of the study was between 8 and 9 percent (Anonymous,
2009c). On average, pig butchers were not acting exploitatively as they were earning
profits comparable to the cost of acquiring the capital to purchase pigs. Abankwah et al.
(2013) used the same approach for the fertilizer market in Ghana and concluded that
marketing agents were not exploitative (Abankwah et al., 2013).
Butchers in Butula and butchers with at least some high school education earned
profit margins of up to 17% and 18% respectively for some pig weight categories (Table
3.6.5). The higher margins might be justified to compensate butchers for their
transaction costs (pig search, personalized negotiation, arranging transport for single
purchase). Also the risks of trade such as having pork condemned at inspection or pigs
90
perishing during transport may justify higher profit margins. It is also possible that some
butchers are capturing economic rent (Fafchamps et al., 2005). Economic rent is the
financial compensation above what would be considered normal or above what most
butchers would be willing to work for (Lado et al., 1997).
Butchers operating in Funyula earned on average profit margins ranging
between -3% and -9% depending on the weight of the pig (Table 3.6.5). Funyula is a very
rural location with poorly developed market places and high levels of poverty, likely
explaining problems in profitability.
Farmers and consumers usually benefit from lower marketing margins (Staatz et
al., 1989) which reflect that a smaller proportion of the retail price is diverted to
marketing costs, including butcher profits. The mean marketing margins were 41%, 30%,
28%, and 27% for 22, 30, 35, and 45 kg pigs respectively (Table 3.6.5). The mean
marketing margin we observed (30%) for pigs at mean market weight of 30 kg (Mutua et
al., 2011c) was 9% lower than the reported marketing margin in Nigerian pig markets
(Ajala and Adesehinwa, 2008) and nearly half the reported marketing margin of
Ugandan cattle markets (Kyeyamwa et al, 2008). Pigs in the Kenyan market chain
changed hands only once, and travelled shorter distances than the pigs and cattle in the
studies by Ajala and Adesehinwa (2008) and Kyeyamwa et al. (2008). Costs of transport,
the number of exchanges, and the transaction costs (partner search, screening,
monitoring) associated with increased distance have been reported to contribute to
91
higher marketing margins in SSA (Gabre-Madhin, 2001; Kyeyamwa et al., 2008; Ajala and
Adesehinwa, 2007). The lower marketing margins in the Kenyan marketing chain studied
may also be attributable to farmers having access to the pork price that is posted in the
local butcher shops. The farmers who can estimate pig weights, or who make use of the
tape measure and lookup table to estimate the their pigs weight (Mutua et al.,2011c)
can better assess the value of their pig when they are aware of the posted consumer
pork price.
3.3.5. The determinants of prices, profit and marketing margin
The butcher characteristics and operational practices outlined in Table 3.6.1 that
were associated with the outcomes of pork price, pig price, marketing and operating
costs, profit, and the marketing margin on a per kg basis are presented in Table 3.6.6.
The covariance parameter estimates and the between-butcher variability for pig weight
and each outcome are presented in Table 3.6.7.
3.3.5.1. Pig weight
Pig weight was associated with the pig price paid to farmers, marketing and
operating costs, profit, and marketing margins (Table 3.6.6). Butchers paid 10 KES less
per kg for pigs in the 22 kg weight class than the referent 45 kg weight category (Table
3.6.6). There are a few plausible reasons why butchers pay farmers less for 22 kg pigs.
Butchers may realize farmers are desperate to sell a pig when it weighs only 22 kg so
they negotiate a lower price. The lower price may be partially justified because
92
slaughter, transport, and inspection costs are charged per pig rather than per kg,
effectively increasing the marketing costs of smaller pigs. Another explanation is that
butchers are adjusting their prices because of increased transaction costs as more
frequent searches and travel results when purchasing smaller pigs more often.
Butcher profits on a per kg basis were highest for pig weight 22 and 45 kg; the
weights which deviated most from the mean marketing weight of 30 kg (Table 3.6.6).
The higher profits for 22 kg pigs can be explained from the low pig prices butchers
offered, particularly butchers in the high profit group (Table 3.6.3). The higher profits for
45 kg pigs was a result of butchers not compensating farmers with higher prices, even
though their marketing costs per kg were considerably lower when purchasing larger
pigs (Table 3.6.3 and Table 3.6.6).
3.3.5.2. Education
Education was associated with pork prices and profit (Table 3.6.6). After
controlling for division and interview year, butchers with at least some high school
education charged a higher pork price and earned higher profits per kg than butchers
with no high school education (Table 3.6.6). The positive correlation between profit and
education is in agreement with study by Shively et al. (2010). In Kenya, the first two
years of high school (forms 1 and 2) mathematics is compulsory and business electives
are offered. These courses would provide the mathematical and budgeting skills
required for butcher enterprises. The increased knowledge likely makes budgeting
93
easier which increases bargaining power (Shively et al., 2010; Kyeyamwa et al., 2008).
Education is a form of human capital and has been found to be a critical factor in
marketing decisions (Toure and Wang, 2013).
Further research is required to understand why higher educated butchers are
able to charge higher prices for the pork they sell. One explanation is that butchers who
are better educated have stronger social networking abilities allowing them to charge
higher prices.
3.3.5.3. Location
Division was associated with pork price, pig price, marketing and operating costs,
profits, and marketing margins (Table 3.6.6). In the peri-urban district of Kakamega,
Shinyalu butchers charged the highest pork prices, paid the highest pig prices to
farmers, had the highest marketing and operating costs and earned the 2nd highest
profits of any of the butchers. The higher pork prices in Shinyalu were likely attributed
to the heavier traffic, larger and more concentrated market centres which were situated
close to Kakamega city on route to Kisumu. Butchers in the Ikolomani Division also
operating in the Kakamega District charged less for their pork than Shinyalu butchers
(Table 3.6.6). The difference in pork price caused Ikolomani butchers to earn lower
profits by approximately the same proportion (Table 3.6.6). Ikolomani butchers paid
farmers the same price for pigs as Shinyalu butchers and incurred similar marketing and
operating costs (Table 3.6.6). Shinyalu and Ikolomani neighbor each other and it is likely
94
that butchers from both divisions purchase pigs from overlapping areas. This likely
explains why pig prices paid by butchers in Ikolomani did not differ significantly from the
pig prices paid by butchers in Shinyalu (Table 3.6.6), even though pork prices differed.
In the more rural Busia District, butchers in Butula charged higher pork prices
than butchers in Funyula. The pig prices and marketing and operating costs did not
differ significantly from each other. Similarly to butchers in Shinyalu, Butula butchers
operated in higher trafficked, more established market locations, charged higher pork
prices and in turn made higher profits (Table 3.6.6). The butchers in the more remote
divisions (Funyula and Ikolomani) within each district had lower profit margins and as a
result farmers experienced lower marketing margins.
When comparing Divisions, farmers in rural Busia received lower pig prices than
farmers in peri-urban Kakamega, which is in agreement with observations in Nigeria
where pig prices were higher in urban markets than in rural markets (Ajala and
Adesehinwa, 2008). In general, farmers in rural locations experience higher input costs
and lower output prices (Chamberlin and Jayne, 2012). In this study rural farmers were
paid lower prices for pigs, and butchers operating in more remote markets earned lower
revenues and lower profits.
3.3.5.4. Pigs purchased per year
The number of pigs a butcher purchased per year was associated with an
increase in marketing and operating costs per kg (Table 3.6.6). This is likely because
95
butcher enterprises are small and costs of search and travel increase as butchers
increase their volumes. The practice of visiting each pig at the farm gate to ensure size
and quality prior to purchase limits the number of pig purchases a butcher can make.
Butchers hired labour to market pork, but not to negotiate pig prices, making their
labour time expensive (Gabre-Madhin, 2001). Bulking purchases could reduce unit costs,
but is often not done, as pigs are purchased on a need basis from farms spread over
large distances. Smallholder farmers keep few pigs so butchers may seldom find farmers
who are willing to sell more than one pig at a time. Butchers are challenged to raise
capital in the absence of formal credit (Table 3.6.2) and in finding pigs (Levy et al., 2009).
They also reported that they often need to sell enough pork in their shop to enable the
purchase of a subsequent pig. Traders and retailers in SSA are often limited by financial
capital and poor access to credit (Poulton et al., 2006). Lack of refrigeration also limited
the number of pigs a butcher could slaughter at a time, limiting the opportunity to
economize slaughter and transaction costs.
3.3.6. Limitations and Other considerations
In this study, pig purchases were influenced by the researchers’ provision of pig
weight to butchers. In practice, butchers may be more capable of evaluating appropriate
pig prices by visual inspection. This may have influenced the pig purchase prices
butchers provided to the researcher and accounted for some of the variation between
butchers.
96
There are several factors that might impact butcher profits or margins which
were not accounted for in this study. The first is the butchers’ ability to sell all of the
pork before it spoils. We assumed all the pork from each pig purchase was sold, which
would increase profit. Second, a butcher’s ability to determine the health of the pig is
also important to profitability because pork carcasses that are condemned and pigs that
die on the way to slaughter are financial risks borne by the butcher. Third, season will
impact profitability and marketing margins as prices are volatile in local markets due to
fluctuating demand for goods corresponding to harvest seasons (Chamberlin and Jayne,
2012). Further research to understand the impact of season on the pork marketing chain
is required. Fourth, supply and demand factors can also influence profits and marketing
margins (Marsh and Brester, 2004). In this study we found that location was a
determinant for profits and margins, but we did not quantify the differences in the
supply of pigs and the demand of pork by location.
Butchers may have had a tendency to exaggerate their costs in this study
including the pig prices they pay to farmers, as has been found in previous studies (de
Mel et al., 2009). Pig prices may have also been higher because farmers were provided a
method of estimating pig weights with tape measures, a year before this study. In this
study, butchers provided an average pig price for each weight. On average, these prices
were not found to be exploitative. However, farmers still need to be aware of pig weight
and the pork price butchers charge in their shops to ensure to ensure an equitable
exchange.
97
3.4. Conclusion
This study’s aim was to determine the marketing margins of the local pork
marketing chain by evaluating cost structures of small-scale pig butcher enterprises, and
the factors that impact the participants’ pork marketing in rural and peri-urban settings
of Western Kenya. The market structure of local pig marketing was mostly competitive
and marketing margins were lower than in other livestock marketing chains. Marketing
margins tended to decrease with pig weight, so raising the average marketing weight
could improve overall marketing efficiency.
Average profit margins were un-exploitative when compared to the cost of
acquiring capital. However, profit margins of well educated butchers were higher which
indicates they are likely capturing economic rents, rather than increasing marketing
shares and offering the benefit of their efficiencies back to consumers or farmers. More
efficient pig butcher enterprises do not capture a larger market share because the
entrepreneur is involved in each exchange, capital is constrained, and supply contracts
are non-existent, limiting the volume potential of the micro-enterprise and preventing
expansion.
For butchers, location is important for profit. Larger volume markets have higher
revenue potential from higher pork prices, translating into higher profitability. Farmers
received lower prices per kg for pigs that were below the mean market weight of 30 kg.
98
For larger pigs, farmers did not receive any of the savings in marketing costs butchers
experienced.
Institutions which facilitate financial exchange, promote accessible use of weigh
scales for trade, and provide transparent market information could be beneficial to local
marketing of pigs to ensure trade margins are moderate regardless of the animal weight
or the negotiation skills of the farmer. Farmer groups have had success in ensuring
equitable trades for farmers while lowering transaction costs for marketing agents in
SSA (Shiferaw et al., 2011; Fischer and Qaim, 2012).
99
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3.6. Tables
Table 3.6.1a: Independent variables collected in butcher interviews in Western Kenya,
2008- 2009 and assessed in models on the outcomes pig price per kg, pork price per
kg, marketing and operating costs per kg, profit per kg, and marketing margin per kg.
Variable Description Type
Butcher characteristics
Age Age of the butcher continuous
Asset score An asset index variable used to proxy butchers’ social economic
position was derived using the asset-based approach as
described by Morris et al., 2000 and the asset questions from the
third section of the survey
continuous
Butcher id a unique identifier for the butcher treated as random effect
variable
categorical
Division The division the butcher operated out of.
(Butula, Funyula, Ikolomani, Shinyalu*)
categorical
Education The coded education level of the butcher into 3 categories (no
education/incomplete primary; completed primary, or at least
two years of high school up to college education*)
categorical
Experience Years of experience the butcher had in the pig butcher
enterprise
continuous
Operating or marketing practices
Agent use The percentage of purchases a butcher paid agents to help find
pigs.
continuous
Contract Whether the butcher had any agreements with farmers (yes* or
no)
categorical
Hours of
travel
Hours of travel time the butcher spent per day searching for pigs continuous
Marketing
type
Whether the butcher sold raw pork only or both raw and cooked
pork (raw* or cooked)
categorical
Pigs per year The number of pigs that a butcher purchased in a year continuous
Phone Use of phone for business (yes* or no) categorical
*referent variable in model
104
Table 3.6.1b: Continued.
Variable Description Type
Price components of net income statement
Marketing
costs+
The total marketing costs per kg excluding pig price. continuous
Operational
costs+
The operational costs per kg continuous
Pork price+ The price the butcher charged in his shop for raw pork per kg in
KES
continuous
Pig price+ The price butchers reported paying farmers for the pig per kg
(live weight) in KES
continuous
Control variables
Interview
year
The year that the butcher was most recently interviewed (2008
or 2009*)
categorical
Weight Weight of the pig being purchased in kg (22, 30, 35, 45*). All
butchers were asked for the price they would typically pay for a
pig that size
categorical
*referent variable in model
+ not used to model the outcome profit per kg because variable was used in the derivation of profit per kg
105
Table 3.6.2: The characteristics and operating practices of 49 pig butchers in Western
Kenya, 2008-2009.
Butchers by profit group
Item All butchers %
n = 49
Low %
n = 16
Med %
n = 18
High %
n = 15
District/Division
Busia/Butula 40 19 41 60
Busia/Funyula 12.5 31 6 0
Kakamega/Ikolomani 12.5 19 18 0
Kakamega/Shinyalu 35 31 35 40
Education Level
Less than primary 34.7 37 44 20
Completion of primary 36.7 44 44 20
Completion of at least 2 years
secondary
28.6 19 11 60
Use of Telephone
Uses telephone for business 83 88 89 72
Does not use telephone for
business
17 12 11 28
Marketing of pork
Raw only 43 25 56 45
Cooked and raw 57 75 44 54
Access to credit 0 0 0 0
Piped water or water tank 12 12 11 13
Electricity 0 0 0 0
Contracts with farmers 16 1 27 1
Age of butchers (years) 36.6 (11.1) 36.8 (11.5) 37.7 (10.9) 35.8 (11.5)
Years of experience 8.6 (7.7) 7.2 (6.1) 10.4 (9.2) 7.8 (7.3)
Hours of travel per day 5.4 (3.4) 5.3 (3.2) 5.4 (3.9) 5.6 (2.9)
Pigs purchased per year 209 (73.9) 209 (91.9) 223 (47.8) 193 (78.3)
Asset score 0.28 (0.30) 0.19 (0.17) 0.37 (0.41) 0.27 (0.22)
Percent of pigs purchased
through an agent
34.5 (27.2) 41.3 (29.5) 39.1 (30.1) 23.1 (19.5)
Source: Data collected (2008 and 2009). Profits for butchers placed into low, medium and high profit groups
were -27.7 to 0 KES per kg, 1 to 20 KES per kg, and 21 to 42 KES per kg respectively.
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Table 3.6.3: Net income (per kg) in Kenyan shillings for butchers categorized into low, medium, and high profit groups for
purchases of pigs weighing 22, 30, 35, and 45 kg (live weight) in Western Kenya, 2008-2009.
22 kg 30 kg 35 kg 45 kg
Profit Group Low Med High Low Med High Low Med High Low Med High
Revenues
Pork price (posted in shop) 125a 144.7
b 145.5
b 127.5
a 143.9
b 153.8
b 127.5
a 143.9
b 153.8
b 127
a 144
b 154
b
Adjusted pork price * 93.8a 108.5
b 111.6
b 95.8
a 107.9
b 117.4
b 95.8
a 107.9
b 117.4
b 95.8
a 108.1
b 118.3
b
Additional pork parts ** 14.7 18.3 17.6 10.7 12.6 12.6 9.2 10.8 10.8 7.2 8.7 8.6
Total Revenue (A) 108.5 126.8 129.2 106.5 120.5 130 105 118.7 128.2 103 116.8 126.9
Costs
Pig price 73.9a 74.2
a 62.9
b 85.7 80.4 79.5 89.2
a 81.0
ab 79.1
b 89.7
a 79.7
b 78.7
b
Marketing costs
Agent 2.2 2.2 1.1 1.5 1.7 0.9 1.3 1.4 0.8 1.0 1.2 0.7
Transport 7.1 a 9.7
a 5.7
b 5.6
a 6.8
a 3.9
b 4.8
a 5.9
a 3.3
b 3.7
a 4.5
a 2.8
b
Slaughter 6.5 a 8.9
a 5.9
b 5.1
a 6.0
a 4.5
b 4.3
a 5.2
a 3.8
b 3.4
a 4.2
a 3.0
b
Inspection 3.7 4.3 3.7 3.1 2.9 2.6 2.6 2.5 2.2 2.0 2.0 1.7
Labour 10.4 8.6 7.2 7.1 6.3 5.8 6.0 5.4 5.0 4.7 4.2 4.1
Cooking 4.2 3.6 4.4 2.7 2.7 4.0 2.3 2.3 3.5 1.8 1.8 2.9
Amenities 2.9 3.7 4.0 2.0 2.5 2.8 1.7 2.2 2.4 1.3 1.7 1.9
Operating costs
License/Fees 1.3 1.4 1.7 1.0 1.0 1.1 0.8 0.9 1.0 0.6 0.7 0.7
Rent 2.5 3.6 2.1 1.9 2.5 1.9 1.7 2.1 1.6 1.3 1.7 1.3
Marketing + Operating 40.8 46 35.8 30 32.4 27.5 25.5 27.9 23.6 19.8 22 19.1
Total costs (B) 114.8 120.2 98.7 115.7 112.8 107 114.7 108.9 102.7 109.5 101.7 97.8
Net Income per kg (A-B) -6.3a 6.6
b 30.5
c -9.2
a 7.7
b 23
c -9.7
a 9.8
b 25.5
c -6.5
a 15.1
b 29.1
c
Net Income per pig -138a 145
b 671
c -276
a 231
b 690
c -339
a 343
b 892
c -292
a 679
b 1309
c
Source: Data collected (2008 and 2009) and calculated (2012). Adjusted pork price (adjusted for difference between live and dressed weight) = pork price charged in
shop * 0.75. The exchange rate to convert Kenyan shilling (KES) to the US dollar (USD) is 0.01278 KES = 1 USD (Anonymous 2009b).
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** Additional pig parts = sum of pork parts sold separately / live pig weight. a b
Different superscripts within each weight class differ by profit group (p < 0.05).
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Table 3.6.4: Correlation coefficients between prices on butchers’ profit per kg for 22,
30, 35, 45 kg pig purchase weights in Western Kenya, 2008-2009 (based on Spearman
correlation coefficients)
22 kg 30 kg 35 kg 45 kg All kg
Pork price .59 * .58 * .58 * .62 * .59 *
Additional pig parts
revenue
.26 .22 .08 .06 .10
Pig price -.56 * -.47 * -.46 * -.57 * -.49 *
Agent .04 -.19 -.21 -.16 -.16
Transport -.17 -.30* -.21 -.19 -.26 *
Slaughter -.11 -.08 -.07 .00 -.11
Inspection .14 -.26 -.23 -.26 -.17 *
Labour -.21 -.06 -.03 .001 -.11
Cooking -.27 -.06 -.00 .13 -.06
Amenities .14 .23 .19 .14 .09
Total Marketing -.25 -.17 -.08 .01 -.19
Licenses .04 -.07 .08 .06 -.05
Rent .01 -.03 -.15 -.14 -.10
Total Operating .11 -.03 -.11 -.11 -.06
Source: Data collected (2008 and 2009).
*significant at p ≤ 0.05
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Table 3.6.5: Profit margins and marketing margins for pig purchases of 22, 30, 35, 45
kg by division and education level of butchers operating in Western Kenya, 2008-2009.
Profit margin (%) Marketing margin (%)
Pig weight (kg) 22 30 35 45 22 30 35 45
All 7 5 6 10 41 30 28 27
Division
Butula 8 8 12 17 41 32 33 34
Funyula -4 -9 -5 -3 29 16 17 15
Ikolomani 7 1 1 5 41 28 25 24
Shinyalu 9 8 7 9 44 34 29 27
Education Level
Less than primary 3 1 4 7 40 29 28 26
Completion of primary 2 3 3 6 38 30 26 25
At least some high school 18 12 14 18 45 33 33 33
Source: Data collected (2008 and 2009).
Profit margin = profit per kg / total revenue per kg *100
Marketing margin = total revenue – pig price / total revenue * 1
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Table 3.6.6: Factors associated with pork prices charged to consumers, pig prices, marketing and operating costs, profit and
marketing margins on a per kg basis for pig butchers operating in Western Kenya, 2008-2009.
Pork pricesGLM
Pig prices GLMM
Marketing + operating costs GLMM
Profit GLMM
Marketing margin GLMM
Pr >F Estimate SE Pr >F Estimate SE Pr >F Estimate SE Pr >F Estimate SE Pr >F Estimate SE
Intercept 124.56* 10.5 89.86* 4.36 14.73* 3.45 5.94 21.95* 3.79
Weight (kg) n/a n/a n/a <.001 <.001 .006 <.001
-22 n/a n/a n/a -10.79* 2.21 20.8* .48 -3.14 2.33 13.5** 1.94
-30 n/a n/a n/a -0.40 1.77 10.1* .47 -5.92* 1.9 2.6 1.62
-35 n/a n/a n/a 0.77 1.30 5.8* .47 -4.34* 1.33 0.8 1.2
-45 . . . . . . . . . . . . . .
Education Level .09 .011
-none -10.21** -11.44* 5.07
-primary -11.77* -15.54* 5.03
-high school . . . . . . . . . . .
Division .01 <.001 .009 .006 0.01
-Butula -10.05* -20.72* 4.19 -8.1* 2.54 5.08 4.6 8.24** 4.2
-Funyula -23.19* -14.66* 5.50 -6.4** 3.46 -14.98* 6.47 -8.1 5.4
-Ikolomani -14.52* -0.34 4.96 -0.1 3.44 -13.4** 6.9 -5.36 5.0
-Shinyalu . . . . . . . . . . .
Interview year .01
-2008 <.001 -19.48* 4.56 -8.63* 3.43
-2009
Marketing Type 0.05
-Raw -7.83* 3.96
-Cooked . . . . . . . . .
Marketing costs <.001 .036 .009 n/a n/a n/a n/a n/a n/a
Hours travel .03 1.77* 0.78
Asset index .007 62.40* 20.54 .01 51.33* 20.07
Asset index ^2
.002 -40.53* 14.31 .01 -36.78* 14.23
Pigs per year .004 .045* .001
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Source: Data collected (2008 and 2009)
. Referent category; * is significant t-test at p < .05; ** is significant t-test at p < .10; blank are not significant;
n/a not applicable
Mixed models were used for each outcome, using butcher as a random effect, blocking on pig weight to account
for dependence between observations, except for the model with the outcome pork price GLM
which was a GLM
model. The Adjusted R-square for the pork price model = .53. The covariance and estimate parameters for the
mixed models are provided in Table 3.6.7.
Profit margin = profit per kg / total revenue per kg *100
Marketing margin = total revenue – pig price / total revenue * 100
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Table 3.6.7: Covariance parameter estimates for butcher, 22, 30, 35, and 45 kg weight
and the between-butcher variability accounting for the proportion of variance for
each weight for each mixed model outcome (pig price, profit, marketing and operating
costs, and marketing margin all on a per kg basis) presented in Table 3.6.6 from
butcher surveys conducted in Western Kenya (2008-2009).
Covariance parameter estimates
and between-butcher variability
Butcher 22 kg 30 kg 35 kg 45 kg
Covariance parameter estimates
Pig price 91.38 133.48 98.52 28.95 50.25
Marketing and operating costs 40.06 30.03 32 40.69 41.37
Profit 156.76 143.98 111.52 24.01 56.16
Marketing margin 101.77 96.77 76.95 19.95 47.05
Between-butcher variability (%)
Pig price n/a 40.7 48.1 75.9 64.5
Marketing and operating costs n/a 57.2 55.6 49.6 49.2
Profit n/a 52.1 58.4 86.7 73.6
Marketing margin n/a 51.2 56.9 83.6 68.3
n/a is not applicable.
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CHAPTER 4: IMPROVING BUSINESS PRACTICES AND PORK SAFETY: A CASE
STUDY OF PIG BUTCHERS IN BUSIA, WESTERN KENYA
4.1. Introduction
Marketing systems in SSA face several challenges. Marketing agents and farmers
operate at different skill levels and achieve varying efficiencies (Muyanga and Jayne,
2008; Fafchamps, 2004). Poor quality standards give rise to food safety concerns
(Wagacha et al., 2008) and the equity of trade between farmers and marketing agents is
often in question because the purchase occurs in the absence of weight-scales (FAO,
2012; Kyeyamwa et al., 2008). Extension services tend to focus on farmer productivity.
However, in the absence of remunerative marketing opportunities, farmers (even when
well supported) have little incentive to adopt new technologies or to increase
investment in inputs needed to produce beyond subsistence levels (Kherallah et al.,
2002). For these reasons, extension efforts directed toward marketing agents are
required along with an assessment of their impact.
The aforementioned challenges apply to the pork value chain in Western Kenya.
Almost one-third of butchers are unprofitable in at least some of their pig purchases and
profits vary considerably (Levy et al., 2009). Many butchers find it challenging to pay for
their annual business and public health fees (Levy et al., 2009b). Pigs are purchased at
the farm-gate without the use of weight-scales (Levy et al., 2009). Approximately 4.5%
of pigs in Western Kenya are infected with Cysticercus cellulosae which is the larval form
of Taenia solium (pork tapeworm) (Mutua et al., 2011a). T. solium leads to human
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neurocysticercosis, characterized by epileptic seizures, headaches, confusion, blindness,
or stroke (Ngowi et al., 2011; Kagira et al., 2010). Humans can contract the tapeworm by
eating undercooked pork that is contaminated with cysticerci. Kagira et al. (2010)
recommend education for pig butchers in the areas of safe pork handling and zoonoses
as a result of inspecting slaughter facilities in Busia.
In this study, we provided pig butchers a novel training opportunity to help them
improve their business skills, ability to estimate pig weights, as well as pork safety
knowledge. The primary objectives of this study were to describe the components of the
training program and to evaluate its outcomes one year later to assess whether
butchers who were trained made changes that could be expected to improve their
business practices and/or enhance public health through the production of safe pork.
4.2. Materials and Methods:
4.2.1. Area of study and enumeration of butchers
The Busia district was chosen for this study because researchers had already
established a multi-year research and training program involving smallholder farmers
from 2006 to 2009 (Dewey et al., 2011). A description of the sampling frame and study
sites for farmers has been previously described (Wohlegumut et al., 2010; Mutua et al.,
2011b). All butchers who sourced pigs from the farmers (in Busia) described in the
studies conducted by Wohlegumut et al. (2010) and Mutua et al. (2011a) were
enumerated by village elders and extension officers in 2008-2009. All 16 enumerated
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butchers in 2008 participated in a pig marketing survey, described by Levy et al. (2013).
In 2009, nine more butchers were enumerated (five butchers were new to the business;
four butchers had been overlooked in 2008). In 2009, all 25 enumerated butchers in
Busia were invited to participate in a half-day workshop.
4.2.2. Questions from 2008 survey
This research used data gathered from the following questions in the survey of
pig butchers conducted in 2008 (Levy et al. 2013): (a) What are the prices or costs of the
following items in your pig butcher shop? (i) pork price per kg; (ii) slaughter costs; (iii)
inspection fees; (iv) marketing costs (transport, agent, cooking fees, labour) (v) 30 kg
pig; (b) Have you ever seen tiny cysts in any pork meat (the butchers were shown a
picture)?; (c) Do you know the cause of the cysts?; (d) Out of every 10 pigs you
purchase, how many are inspected?; (e) How do you estimate pig weight at the farm?
4.2.3. Describing the 2009 workshop
Workshops were promoted by village elders and livestock officers. Each three- to
four-hour workshop was followed by an individual 30 minute one-on-one budgeting
exercise specific to each butcher. The training was provided in English and Kiswahili
(when necessary) by Canadian and Kenyan researchers with the aid of village elders,
local translators, and livestock officers. To compliment the training and discussions in
the workshop, butchers were provided with a package consisting of training
documentation, a pencil, a tape measure, 100 plastic bags for use in selling pork, and a
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plastic envelope to hold all the distributed materials. Calculators were not offered to the
butchers, as authors felt it would be perceived as unfair if butchers were provided
calculators when these were not available to farmers. However, many butchers used the
calculator on their mobile phone. The content of the workshop is described below.
4.2.4. Business training
The business training emphasized the importance of co-operation and trust
between farmers and butchers to ensure a sustainable pig industry. Butchers were
encouraged to discuss what would happen to the supply of pigs if farmers thought that
pig prices offered by butchers were too low, or if butchers purchased all of the breeding
sows in the village. Butchers were also shown the feeding costs incurred by farmers, to
illustrate that feeding pigs was the most expensive part of a smallholder pig operation.
The workshop also contained a discussion about the challenges reported by butchers in
the 2008 survey (Levy et al., 2009b; Levy et al., 2014). Butchers shared how they might
address some of these challenges.
Butchers were then taught how to calculate profit and break-even pig prices for
pigs of various weights. This was done in several steps (full handout available in Figure
4.7.1). Step 1 was to enumerate and add all the costs incurred with each pig purchase.
Step 2 was to enumerate and add all the costs incurred monthly and then divide that by
the number of pigs the butcher purchased each month. The monthly expenses averaged
over the number of pig purchases per month was noted to inform the butcher about
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how much money must be saved for monthly expenses from each pig sold. Step 3 was
to enumerate and add all the costs incurred yearly and then divide the total by the
number of pigs purchased each year. The yearly cost per pig averaged over the number
of pig purchases per year was noted to inform the butcher about how much money
must be saved for yearly expenses from each pig sold. Step 4 was to total the three
costs (per pig costs, monthly costs per pig, and yearly costs per pig) to know the total
expenses spent on each pig. Step 5 was to divide the total derived in step 4 (all per-pig
costs) by the pork price to derive how many kilograms of pork from each pig sold was
required to cover all expenses (i.e. expenses in terms of kg of pork). Step 6 was to
estimate the live weight of the pig using the tape measure method using the training
materials provided by Mutua et al., (2011b). Step 7 was to estimate the dressed weight
of the pig after slaughter by multiplying the live weight estimate by 80%. Step 8 was to
multiply the dressed weight estimate by the pork price and add any additional revenue
that would be obtained from selling non-meat pork parts (feet, head, lungs) to the total
revenue potential of the pig. Step 9 was to calculate the break-even price for the pig by
subtracting the total costs per pig from the estimated revenue. Step 10 was to calculate
the potential profit by subtracting the purchase price from the break-even price.
Butchers were also shown the proportional costs for the use of the slaughter slab and
government inspection compared to all of the per-pig expenses.
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4.2.5. Public health and pork safety training
Butchers were asked to consider and discuss the impacts of people getting sick in
their communities as a result of unsafe pork. The life cycle of the tape worm, T. solium
was presented. The public health and pork safety training emphasised the following
points concerning safety: (a) if pork has C. cellulosae which is seen as visible white cysts
the carcass must not be sold, and it is therefore important to have pork inspected by a
government inspector; (b) eating pork infected with C. cellulosae can cause infection in
people which could lead to neurocysticercosis which causes epileptic seizures,
headaches, confusion, blindness or stroke; (c) keeping from contaminating the meat
when a pig is slaughtered by avoiding getting fecal matter and intestinal tract contents
on any pork surface; (d) if pork is contaminated by intestinal contents, the pork must be
cleaned thoroughly with hot water, a dilute solution of chlorine bleach, and again with
hot water; (e) fluids from the lungs, trachea, and nose must also not spill onto the pork;
(f) the butcher shop must be cleaned with soap and hot water and disinfected daily
(soap and chlorine bleach kill more bacteria than just water); (g) the surface where pork
is laid and the knife that is used to cut the pork must be well cleaned and disinfected
multiple times per day; (h) do not cut the pork into small pieces until it is ready to be
sold to reduce the surface area of the pork exposed to heat, contaminated surfaces, and
flies; (h) regularly wash hands with soap; (i) keep meat as cold as possible and away
from flies and other insects that carry bacteria; (j) cook the pork until there is no pink
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color, to kill bacteria; (k) consider sharing a pig with another butcher to reduce the
amount of time pork is in the shop during slow seasons.
4.2.6. Weight estimation Training
Butchers were shown how to measure the length and girth of a pig in
centimeters using a standard tape measure that was given to the butcher. They were
then shown how to use the weight chart to look up the estimated weight (Mutua et al.,
2010b).
4.2.7. Follow-up survey
In 2010, one year after the workshops, researchers interviewed butchers using a
structured survey (Figure 7.3) to assess the impact of the training. The interview began
with an open-ended question that asked if they were doing anything differently in their
business since the researchers conducted the workshops. Butchers were encouraged to
describe all changes by being asked “did you make any other changes?” until they were
not able to recall anything else. The butchers were then asked the following specific
questions concerning the workshop they had attended: (a) Are you using any form of
record keeping in your business; if yes, which ones: (i) pig purchase sheets, (ii) profit
calculation, (iii) your own record-keeping system; (b) Do you buy a pig and share pork
with other butchers? (c) How do you ensure the pork you sell is safe for consumption?;
(d) How do you ensure pork is free of the tapeworm?; (e) Do you have a copy of the pig
weight charts, and if so, are you using the tape measure for estimating pig weights?.
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4.2.8. Data management and summary
The data from the original survey in 2008 and from the follow-up training survey
in 2010 were entered into Microsoft Excel 2007 (Microsoft, Redmond, WA, USA) by one
researcher and then validated independently by a second researcher. The data were
then imported into SAS 9.1 using Enterprise Guide 4.0 (SAS Institute, Cary, NC, USA).
Descriptive tables were created using means and standard deviations (sd) for
continuous variables and proportions for categorical variables in SAS 9.1 (SAS Institute,
Cary, NC, USA).
4.3. Results:
4.3.1. Training and follow-up participation
In total, 25 butchers were initially surveyed in 2008/2009. Sixteen of the 25
butchers (64%) participated in the training program in 2009. Twelve of the 16 butchers
(75%) that participated in the training program participated in the follow-up survey in
2010.
4.3.2. Business practice training recall
Table 4.6.1 summarizes pricing components of the pig butcher enterprise from
the 2008/2009 survey, measured in Kenyan Shillings (KES). Butchers were shown their
mean slaughter and inspection costs in terms of the value of pork, which were 1.13 and
0.62 kg respectively (Table 4.6.1). The mean purchase price of a 30 kilogram pig in Busia
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is 2346 KES (SD=411.05). Butchers were also shown that the average butcher needed to
set aside approximately 60 KES and 30 KES per pig to cover monthly expenses (759 KES)
and yearly fees (5892 KES) respectively. Yearly fees include business license, weigh-scale
inspection, and public health licenses. Butchers purchase an average of 209 (SD= 73.2)
pigs per year.
The business management changes made by the butchers in response to the
training in 2009 are reported in the top half of Table 4.6.2. The first column summarizes
butchers’ responses to what they had changed in their business, without prompting.
Responses indicated that butchers began to calculate the profit potential and use the
tape measure to estimate the weight of the pig before purchasing the pig. Fewer
butchers remarked on having increased pig prices paid to farmers, or having ensured
that all their pigs were inspected as a result of the training. The second column in Table
4.6.2 pertaining to the business component of the training summarizes the butchers’
responses when asked specifically about changes they had initiated in record keeping,
profit calculation, and sharing pork with other butchers. Most butchers were keeping
records and over half of the butchers were using the tape measure to estimate pig
weights as a result of the training.
Butchers’ comments about the business training they had received included:
• “I now have an equity bank account which I opened after the training”
• “I make sure to save parts of my profit now [for licenses and rent]”
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• “My communication with farmers has greatly improved as I understand their
business”
• “I now make sure I do my profit calculation well so that I don’t take a loss when
buying a pig”
• “I feel like I don’t exploit the farmer now”
• “I keep a record of my pig purchases and profits and losses”
4.3.3. Public health training recall
In the initial 2008 survey, 31% (5/16) of butchers said they had seen cysts in pork
meat, but none of them knew the cause of the cysts. Nineteen percent (19%) (3/16) of
the butchers did not have all of their pigs inspected.
One year after the training, 25% (3/12) of the butchers reported to the open-
ended question that they improved cleanliness (Table 4.6.2). Seventeen percent (17%)
(2/12) said they now use the slaughter facilities and have all of their pigs inspected, and
17% (2/12) said they store meat in a better location (Table 4.6.2). As an example, one
butcher built a cupboard with a screened door to keep the flies off the carcass. Half
(6/12) of the butchers mentioned that they had improved the way they cleaned or the
frequency of cleaning their knives, counter tops, and the floor of the butcher shop
(Table 4.6.2).
Table 4.6.3 presents open-ended responses from the butchers on how they
ensure that pork is safe for human consumption. Fifty-eight percent (7/12) of the
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butchers mentioned using slaughter facilities and veterinary inspection (Table 4.6.3).
Table 4.6.4 presents responses from butchers in an open-ended question about how
they ensure the pig they buy is free of the pork tapeworm.
Comments by butchers about the health training;
• “We have improved on the hygiene at the butchery”
• “I keep pork in a better storage area where flies cannot go”
• “Before the training, not all of my pigs were slaughtered at the slaughter [slab],
now all the meat is inspected”
4.3.4. Weight estimation training recall
The results of the 2008 survey showed that none of the butchers were using the
tape measure and weight chart to estimate weights of pigs.
One year after the workshop, 58% (7/12) of the butchers mentioned in the open-
ended segment that they were using the tape measure (Table 4.6.2). When asked
directly if they were using the tape measure, 83% (10/12) of butchers responded
positively (Table 4.6.2).
Comments by butchers about weight estimation;
• “I use the tape measure now when buying pigs, now I am able to estimate the
weight of pigs”
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• “I can now tell the weight of the pig by using the tape measure”
4.4. Discussion:
4.4.1. Uptake of information
Butchers most positively responded to the training aspects of using tape
measures for pig weight estimation, record keeping, and calculating profit potential of
pigs. This is not unexpected given that the pig butchers are in business with motivation
to improve their livelihood. Similarly, de Mel et al. (2009) found that 52% of small
enterprises responded positively to education by continuing the use of records after
training. In this study, we also observed that butchers began setting aside money to
overcome the challenge of raising capital to renew their licenses each year. License fees
and capital are two of the three biggest challenges raised by Busia butchers (Levy et al.,
2014). The cost of yearly licenses and fees were more than double the cost of a 30 kg
pig, so it is important for butchers to know how much to save from each pig to ensure
the continuity of their business from year to year.
In the study by Karlan and Validivia (2011), small-scale entrepreneurs that were
equipped with business training had higher retention and repayment rates with
microfinance institutions, suggesting that budgeting training helps with cash-flow
management. Chu et al. (2007) identified budgeting as one of the most critical
competencies for successful businesses in developing countries, so supporting pig
butchers by equipping them with skills required to operate their businesses efficiently
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and sustainably contributes to the development and welfare of the wider pig marketing
community (Johanson and Adams, 2004).
The proportion of butchers (58%) who responded openly that inspection and
slaughter use was a way to ensure safe pork, suggests that there is still room for
improvement in reinforcing the importance of slaughter-use and inspection. It is
encouraging that 3 of the 16 butchers that participated in the follow-up survey
improved their efforts to have all of their pork inspected as a result of the training. The
remaining butchers already fully complied with having all of their pork inspected. Due to
the complexity of the life cycle of T. solium, we are not surprised that only a quarter of
the butchers knew that pig inspection was a way to ensure pigs are free of the
tapeworm larvae. Butchers should be given training repeatedly, as it has been illustrated
that farmer retention of T. solium information improves over repeated sessions, and
one-on-one training was also found to be more effective than group lessons
(Wohlgemut et al., 2010; Dewey et al., 2011).
4.4.2. Comparing training methodologies
Teaching business skills to small-scale enterprises using budget templates for
calculating potential profits and break-even costs has been used in training for small-
scale enterprises (FAO, 2011). Unlike budget templates in other training programs which
include a section for variable costs, we additionally showed butchers how to incorporate
the costs of rent and yearly license fees into their variable costs to be accounted for in
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the pig price, and to set aside the money required from each pig to pay for these
expenses. In the training manual ‘Hygienic Pork Production and Marketing’, the
International Livestock Research Institute (ILRI) includes skills and entrepreneurial
advice such as ‘pleasant bargaining capability’ and ‘managing conflict’ (Deka and Wright
2011). We did not include related material in our training.
4.4.3. Strengths
To the authors’ knowledge this is the first study targeting pig butchers for
training on T. solium. Health interventions have typically been targeted towards farmers
(Ngowi et al., 2011; Wohlgemut et al., 2010). The butchers in this study purchased pigs
from the same farmers who participated in the training by Mutua et al. (2010) and
Wohlgemut et al. (2010). Concentrating efforts towards all stakeholders in the local
supply chain will likely have a stronger impact on the industry than if the training
occurred in only some sectors of the industry.
Sessions opened with a discussion-style approach where butchers were invited
to share how they addressed various challenges and their opinions about different
business scenarios they may face. This approach promoted empowerment and
receptivity toward the training being offered. Participation of butchers in small group
settings also promoted information sharing and discussions about sustainability of the
local pork marketing chain. Having business practices in the training curriculum provided
butchers’ incentives to attend the program and simultaneously created an opportunity
127
for researchers to discuss with butchers how they can ensure safe pork for their
customers. Outlining the risks of selling uninspected pork and illustrating, in kilograms of
pork, the small proportion of pork revenue required for the slaughter facilities and
inspection, promoted the success of increasing butchers’ willingness to have pork
inspected. Producing education material specifically for pig butchers made the training
relevant to one sector (pig marketing sector) which is a recommended approach for
providing training in sub-Sahara Africa (Nieman, 2001).
4.4.4. Weaknesses
The behavioural changes butchers made were collected retrospectively
(Nyagnaga et al., 2010) among a small number of participants, and statistical
significance of behavior changes resulting from the training program could not be
assessed. A more traditional outcome mapping approach with a pre- and post-workshop
survey, or a paired samples approach would have made the results of this research
stronger (Ngowi et al., 2011). However, butchers were asked specifically what changes
they had made since the training, so the responses are indicative of behavioural
improvements made.
Resource limitations prevented the use of the Training-of-Trainers (TOT)
methodology for the business segment of the program, which is a recommended
practice (Nieman, 2001). However livestock officers and extension personnel had
already participated in the pig tapeworm lifecycle TOT and were invited to attend the
128
butcher training sessions. We did have a few extension officers attend in some villages.
TOT is helpful to ensure sustainable knowledge transfer after study completion (Dewey
et al., 2011). Livestock officers should be encouraged to include butchers in training as
they continue offering support to the pig industry. Kenya’s Strategy to Revitalize
Agriculture (SRA) has emphasized the importance of agricultural extension for poverty
alleviation in Kenya (Muyanga and Jayne, 2008).
Locating and co-coordinating times with butchers for the original survey and the
follow-up survey was a challenge in this project because butchers were often searching
for pigs or busy attending their shops. Twenty-five percent of the butchers that
completed the training were not reached during the follow-up visit in 2010 which may
have biased results.
4.4.5. Going forward
Progress has been made in this study to improve butchers’ understanding of
farmers’ feed cost challenges and butcher-farmer communication with tools such as the
tape measure. The role of trust and communication in the performance of supply chains
is well documented (Masuke & Kirsten, 2004; Fafchamps, 2004). Further development
of institutions which promote mutual respect and trust between butchers and farmers
would be valuable. In this study, we found that training butchers on business practices
and the challenges of farmers improved butcher attitudes toward farmers. A few
butchers suggested that they should try to increase pig prices paid to farmers. Further
129
studies should focus on how budgeting education impacts the variability of pig prices,
whether budget knowledge reduces exploitative pricing behavior, and if education can
ensure butchers operate without interruption (closing for periods of time because of
capital constraint).
The condemnation of pork meat due to the tapeworm has economic impacts on
both farmers (Mutua et al., 2010; Ngowi et al., 2007) and pig butchers (Levy et al.,
2009b; Kagira et al., 2010). Farmers in rural areas who are informed of the dangers of
cooking and consuming infected pork still continue to do so, likely because of the high
poverty levels (Ngowi et al., 2011). The incentive for pig butchers to inspect and sell safe
pork is to maintain a sustainable livelihood and reputation in the community. Although
in this study we saw increased willingness by butchers to ensure all of their pork was
inspected after being made aware of the dangers of infected pork to their customers,
butchers do face the disincentive of condemnation of infected pork.
130
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Fafchamps M (2004) Market institutions in Sub-Saharan Africa: theory and evidence.
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Johanson R K, Adams, A V 2004 Skills development in sub-Saharan Africa. The World
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s+development+in+sub-Saharan+Africa&ots=AE1oTiESfE&sig=6-
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Kagira J M, Maingi N, Kanyari P W N, Githigia S M, Ng’ang’a J C, Gachohi J M 2010
Seroprevalence of Cysticercu cellulosae and associated risk factors in free-range pigs in
Kenya. Journal of Helminthology 84: 398-403.
Karlan D, Valdivia M 2011 Teaching Entrepreneurship: Impact of Business Training on
Microfinance Clients and Institutions. The Review of Economics and Statistics 93 (2):
510-527.
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traveled: Agricultural market reform in Sub-Saharan Africa. Oléagineux, Corps Gras,
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Kyeyamwa H, Verbeke W, Speelman S, Opuda-Asibo J, Van Huylenbroeck G (2008).
Structure and dynamics of livestock marketing in rural Uganda: constraints and
prospects for research and development. Journal of International Food & Agribusiness
Marketing 20(4): 59-89.
Levy, M A; Dewey C E; Weersink A, Mutua F K 2009. ‘Comparative profitability of pig
butcher businesses in Western Kenya’, Proceedings 12th International Society for
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ISSN: 0754-2186.
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Levy M A, Dewey C E, Weersink A, Mutua F K 2009b ‘Challenges of rural and peri-urban
pig butcher businesses in Western Kenya’, Proceedings of the 12th Symposium of the
International Society for Veterinary Epidemiology and Economics, Durban, South Africa,
August, 2009. http://www.sciquest.org.nz/elibrary/edition/5251 ISSN 1177-360X.
Levy M A, Dewey C E, Weersink A, Poljak Z, Mutua F K 2014 The role of pig butchers in
pig marketing systems of Western Kenya. African Journal of Agricultural Research,
Forthcoming (accepted September 30th, 2013).
Masuku M B, Kirsten JF 2004 The role of trust in the performance of supply chains: A
dyad analysis of smallholder farmers and processing firms in the sugar industry in
Swaziland. Agrekon, 43(2): 147-161.
Mutua F K, Dewey C E, Arimi S M, Ogara W O, Githigia S M, Levy M A, Schelling E 2011a
Indigenous pig management practices in rural villages of Western Kenya. Livestock
Research for Rural Development 23 (7).
Mutua F K, Dewey C E, Arimi S M, Schelling E, Ogara W O 2011b Prediction of live body
weight using length and girth measurements for pigs in rural Western Kenya. Journal of
Swine Health Production 19 (1): 26–33.
Muyanga M, Jayne T S 2008 Private agricultural extension system in Kenya: practice and
policy lessons. Journal of Agricultural Education and Extension 14 (2): 111-124.
Nieman G 2001 Training entrepreneurs and small business enterprises in South Africa: a
situational analysis. Education + Training 43(8): 445-450.
Ngowi H A, Mlangwa J E D, Carabin H, Mlozi M R S, Kassuk A A, Kimera S I and
Willingham III A L 2007 Financial efficiency of health and pig management education
intervention in controlling porcine cysticercosis in Mbulu district, northern
Tanzania. Livestock Research for Rural Development 19 (5).
Ngowi H A, Mkupasi E M, Lekule F P, Willingham III AL, Thamsborg S M 2011 Impact of
farmer education on their knowledge, attitudes, and practices in southern Tanzania: a
case for Taenia solium control. Livestock Research for Rural Development 23 (1).
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implications to food safety and health and possible management
strategies. International Journal of Food Microbiology, 124 (1): 1-12.
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Methods Regarding Prevention of Human Epilepsy Caused by Taenia solium
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134
4.6. Tables
Table 4.6.1: Summary of pricing components from initial butcher surveys in 2008,
which were used to aid in workshop discussions in Western Kenya, 2009.
Question from initial survey in 2008 KESa In Kilograms of pork
Mean SD Mean SD
Pork price per kilogram 141.1 19.1 1.0 0
Slaughter costs (including wood and water) per
pig
160.0 57.7 1.13 .39
Inspection costs per pig 87.6 33.2 0.62 0.24
All marketing costs (excluding pig price) per pig 815.9 240.8 5.7 4.7
Rent per pig 61.9 39.4 0.44 0.23
License fees (business and public health) per pig 29.2 18.4 0.21 0.15
a Prices are presented in Kenyan shillings (KES) at an exchange rate (June 2009) of 1 USD ~ 78.74 KES
(Anonymous, 2009).
135
Table 4.6.2: Management changes made by butchers (n=12) one year after attending
butcher training that included business practice and pork safety information, Western
Kenya, 2010.
Habit Change described with
no prompting a
Butchers who
made each change b
Business Practice
Calculates profit potential before purchasing a
pig
83% 83%
Increased pig prices and doesn’t exploit farmer
when purchasing
25% N/A
Record keeping 17% 58%
Puts money aside for rent or for license fees 17% N/A
Shares pork with another butcher 0% 50%
Public health
Improved cleanliness 25% N/A
-Wearing a white coat 33%
-Disinfect knife 50%
-Clean countertop 64%
-Clean floor of butchery 50%
Ensures all pigs are inspected 17% N/A
Stores meat in better location 17% N/A
Estimating weights
Using tape measure as regular practice in
purchasing pigs
58% 83%
a Proportion of butchers who mentioned changes without prompting (in an open ended question) about what
they changed in their business since the training sessions.
b Proportion of butchers who responded affirmatively when asked about specific changes
N/A is not applicable as butchers were not asked specifically.
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Table 4.6.3: Butchers’ practices used to ensure safe pork for human consumption,
Western Kenya, 2010.
Management Practice Responded to open ended question about how
butcher ensures safe pork
(n=12)
Inspection and slaughter use 58%
Store meat in better location 17%
Cleanliness and improved hygiene 75%
Fly screen or enclosed pork 41%
137
Table 4.6.4: Butchers’ practices used to ensure the pig is free of the tape worm,
Western Kenya, 2010.a
Management practice Proportion of response
(n=12)
Pork inspected 25%
Pork is cooked well 25%
Purchase tethered pigs 33%
You can’t tell until it is slaughtered 17%
Inapplicable responses
-associated with cleanliness 17%
- visual inspection of live pig (see the parasites
or skin infection)
17%
-did not remember 8%
a response to open ended question “How do you ensure the pig is free of the tape worm?”
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4.7 Figures
Figure 4.7.1: An example of training material for profit and break-even pig price provided to
Kenyan pig butchers in 2009.
Working out profits and break even costs (an example)
1. Calculate per pig costs.
For every pig Wally purchases, he pays the costs outlined in the table below.
2. Gather monthly costs and calculate how much that is for each pig
Wally wants to ensure he has enough money saved for his monthly expenses. He has
them listed below. Wally estimates that he will purchase 4 pigs per month. He can add
a proportion of these costs to each pig to ensure he saves for these costs in the future.
Item Per Pig Cost KES
1 Transportation 100
2 Slaughter slab 150
3 Inspection of meat 100
4 Employees 150
5 Salt, soap, water, wood 100
6 Total costs for each pig 600
Item Costs paid each month Per month costs
7 Rent 200
8 Total per month 200
9 Number of pigs per month 4
10 Monthly costs on a per pig basis = total of
monthly costs divided by the number of
pigs purchased per month
= 25 (200/4)
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Figure 4.7.1(Continued)
3. Gather yearly costs and calculate how much that is for each pig
Wally wants to ensure he has enough money saved for his yearly expenses. He has
them listed below. Wally estimates that he will purchase 48 pigs per year. He can add a
proportion of these costs to each pig to ensure he saves for these costs in the future.
Wally needs to save 25 KES for monthly costs plus 50 KES for yearly costs from each pig.
4. Total all the costs on a per pig basis
Wally wants to ensure he knows the total amount he spends for each pig that he
purchases. This amount plus the pig purchase price is Wally’s break-even cost which will
be shown below.
Item Costs paid each year Per year costs
11 Government business license 1000
12 Public health certificate 1400
13 Total costs per year 2400
14 Number of pigs per year 48
15 Yearly costs on a per pig basis = total of
yearly costs divided by the number of pig
purchased per year
= 50 (2400 / 48)
Item All costs (per pig, per month, per year)
averaged over number of pigs
Costs
6 Total costs for each pig 600 (from line 6
above)
10 Total costs for each month per pig 25 (from line 10
above)
15 Total costs for each year per pig 50 (from line 15
above)
16 Add each cost to get total of expenses per
pig
675
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Figure 4.7.1(Continued)
5. Expenses in pork terms (how many kilograms of pork from each pig to cover
expenses)
675 KES in expenses / 100 KES per KG = 6.75 KG for expenses.
Wally realizes that the revenue from 6.75 kg (almost 7 kg) of pork sold from any pig goes
toward his expenses. The 7 kilograms excludes the expense of purchasing a pig.
6. Estimate the live weight of the pig using the tape measure
Wally found a pig that he is interested in buying. Before he negotiates with the farmer
over the price of the pig, he decides to estimate the weight of the pig. He measures the
pig’s length and girth with a tape measure. Wally finds the pig is 90 cm’s long and 82
cm’s in girth. He estimates the pig to be 8 months old and uses the chart to lookup the
pigs weight. It weighs 40 kgs.
7. Estimate the number of kgs of sellable pork from the pig after slaughter
To figure out the amount of pork, Wally will get from his 40 kg pig, he estimates that
80% of the live weight will be available for pork. He multiplies .8 * 40 = 32 kgs
8. Estimate sales revenue from the pig.
Sales revenue is the money received from selling the product. Wally sells pork for 100
KES per kg. So his estimated sales are:
32 kgs * 100 KES/kg = 3200 KES + 300 KES for pig parts sold separately
9. Calculate the break-even price for the pig
Break-even price is the maximum price that the butcher can pay for the pig without
losing money.
Break-even price = estimated revenue from pork sales – expenses per pig (line 16)
Wally calculates his break-even price = 3500 – 675
Wally’s break-even price = 2825 KES. This means Wally can pay up to 2825 without
losing money on the pig purchase.
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Figure 4.7.1(Continued)
10. Calculate potential profit
Profit is the amount of money remaining from sales after all expenses are paid for.
Wally purchases the pig for 2400 KES. His profit will be 2825 – 2400 = 425 KES
providing he can sell all the pork from the pig.
Profit = total pork sales – pig price - per pig costs – share of per month costs – share of
per year costs
Put monthly and yearly costs aside
After Wally sells the pork, he puts 25 KES aside for his monthly costs, and the 50 KES
aside for his yearly costs.
Short cut for figuring price to pay
Wally now knows that for each pig he must consider his costs ( 600 + 25 + 50 ) = 675;
which is about 700.
Because Wally charges 100 KES per kg, his costs are approximately 700 / 100 which is =
7 kg of pork. Wally decides that from the 40 kg pig, he will get 32 kg of pork after
dressing the pig – 7 kg of pork for expenses = 25 kg of pork to sell to make the price of
the pig. So he knows that his break-even price is 25 * 100 = 2500 KES + 300 for pig parts
= 2800. This is very similar to our previous calculation, but is much simpler to do.
After the formal presentation, researchers worked individually with butchers to
calculate their costs in terms of kg of pork so that in the future, each butcher could
understand his or her potential profit.
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CHAPTER 5: EVALUATING CRITICAL FACTORS TO THE ECONOMIC FEASIBILITY
OF SEMI-INTENSIVE PIG REARING IN WESTERN KENYA
The final publication is available at Springer via http://dx.doi.org/10.1007/s11250-
014-0568-7
5.1. Introduction
Pig rearing is an important livelihood activity for many smallholder farmers
across Sub-Saharan Africa (SSA) (Mutua et al., 2011; Halimani et al., 2013; Madzimure et
al., 2013). Traditional management systems (i.e. pigs run free-range and scavenge for
part of their food) predominate (Lekule and Kyvsgaard, 2003) because of the economic
feasibility (Verhulst, 1993) but there are negative consequences. Allowing pigs to
scavenge on land dedicated for agriculture has been a source of conflict between
neighbors, and in extreme cases has lead to pig shootings or salt poisoning (FAO, 2012;
Mutua et al., 2010). Free-ranging pigs are also at risk of contracting parasites (Kagira et
al., 2012) and zoonoses such as Taenia solium (Thomas et al., 2013; Mutua et al., 2011;
Lekule and Kyvsgaard, 2003). The economic feasibility of semi-intensive pig production
(i.e. pigs confined and food provided) is important to consider because of the potential
for improving pork safety (Lekule and Kyvsgaard, 2003) and social harmony. A better
understanding of the critical factors that enable smallholder farmers to economically
benefit from semi-intensive pig rearing may help to direct extension efforts and inform
policy makers in SSA who advocate confining pigs (Madzimure et al., 2013; Mutua et al.,
2010).
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Because feed costs account for 70-85% of pig production costs (Verhulst, 1993;
FAO, 2012), several research studies have focused on feed optimization, either by
generating least-cost feed rations (Olorunfemi, 2007; Parris and Devendra, 1972) or by
performing feed trials to assess growth performance results from different feed
ingredients or compositions (Balogun and Bawa, 1997; Parris and Devendra, 1972;
Alhassan and Odoi, 1982; Tuitoek, 1992). The feed recommendations that result are
only optimal if the farmer has access to the recommended feeds at a similar cost
(relative to other feeds) evaluated by the researcher (Jackson, 1981). Little attention has
been given to the variety of conditions and constraints smallholder farmers face and the
resulting impact on their feed choices and the overall cost of feeding pigs. Season
influences the prices and feeds that are available to include in a ration because locally-
available and farm-grown feed items change seasonally (Kagira et al., 2010; Mutua et
al., 2012). The opportunity costs of feeding pigs farm-grown feed vary with productivity
and marketing potential of the farm-grown feeds (Amills et al., 2013). Poverty levels
influence the quality and quantity of feeds a farmer is able to provide which influences
the average daily gain of pigs (Mutua et al., 2012; Carter et al., 2013). Nutritional
requirements for body weight maintenance and growth also differ with body weight
(NRC, 1998). All of these factors influence the appropriate least-cost feed rations. To
better understand how these factors influence the composition of optimal feed rations
and the economic impact to the farmer, a more rigorous approach than generating a
least-cost feed ration is required. In this study we develop an algorithm which generates
144
thousands of least-cost feed rations to analyze how feed rations and feeding costs are
impacted by the aforementioned factors. This novel approach and the algorithm
described in this study are applicable beyond pig production in SSA.
In addition to feed costs, farmers’ economic benefit from pig-rearing is
influenced by the price they receive for pigs. Results of pig-rearing feasibility studies
vary. Traditional, semi-intensive and intensive pig rearing systems in Nigeria have all
been found to be profitable (Akanni and Onasanya, 2004; Ogunniyi and Omoteso, 2011;
Adetunji and Adeyemo, 2012), while only traditional husbandry practices were found to
be profitable in Burkina Faso and Cameroon (Verhulst, 1993). Lemke et al., (2007)
compared extensive (i.e. using indigenous pigs in rural locations) and intensive (i.e. using
improved breeds in more urban locations) pig systems in North Vietnam and found no
difference in net economic benefit between the two pig-rearing systems. Although
profitability was addressed in these studies, the variability of prices that farmers
received because of trader variability, seasonal variation of pig prices, and the influence
of marketing weight on the economic impact to farmers have not been quantified. This
information would be valuable for smallholder farmers to enhance their marketing
decisions regardless of their production objective. Lemke et al. (2007) reported that
most rural farmers in resource-poor locations have the objective of earning higher total
revenues rather than profits.
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The purpose of this research is to evaluate the economic potential of semi-
intensive pig-rearing under local marketing conditions in Western Kenya and to assess
the relative importance of season, average daily gain, opportunity costs of farm-grown
feeds, pig weight, and pig price variation on economic outcomes. In this study, we
developed a software algorithm to emulate least-cost pig-feeding under a variety of
scenarios expected to influence semi-intensive pig-rearing. A linear program is nested
inside the algorithm to determine least-cost feed rations and daily feed costs for each
combination of factors (season, opportunity cost of farm-grown feed, average daily gain,
and pig weight). Economic feasibility was evaluated by determining both the profit-
maximizing and total income-maximizing market weight of pigs.
5.2. Materials and methods
5.2.1. Study location
The study was conducted in Busia District, Western Province, Kenya. Busia is
characterized as rural with most people living via subsistence agriculture. The high
population of pigs has been attributed to the high incidence of poverty in the area (FAO,
2012). Busia was purposively chosen because of high levels of poverty, high population
of pigs, and because several research studies have focused on pig butchers and
smallholder pig farmers with a specific focus on pig feeding, management and
productivity (Mutua et al., 2010; Mutua et al., 2011; Kagira et al., 2010b; Carter et al.,
2013; Kagira et al., 2010). To our knowledge there have been no studies of the economic
potential of pig-rearing for smallholder farmers in this location.
146
Farmers feed their pigs combinations of farm-grown, free, and purchased feeds
(Mutua et al., 2012). The most frequently used feeds reported by farmers in Busia were
ugali (ground maize with or without millet cooked in oil and water) (88% of farmers),
kitchen leftovers (83%), omena (small dried local fish) (78%), sweet potatoes (75%),
sweet potato vines (65%), cassava (57%), brewers’ waste (48%), maize (33%), fish
innards (30%), and less frequently vegetables, mango, avocado and banana peels
(Mutua et al., 2012). Kagira et al., (2010b) reported similar feeds and also included swill
collected from local markets.
5.2.2. Software algorithm
We developed an algorithm to emulate growing a pig from weaning weight to
market weight for every combination of weaning month (January to December),
opportunity cost of feeding pigs farm-grown feeds (100%, 75%, 50%, 25%, 0%, and 0%
of the market price with no free feeds available), and average daily gain (80 to 180
grams per day in 25 gram increments). At each pig weight and for each combination of
factors that we varied, the algorithm used a linear program to determine the least-cost
feed ration and feeding cost required for feeding a pig to gain one kilogram. The
incremental feeding cost and the cumulative feeding costs were tracked. For each pig
weight the cumulative feeding cost and piglet purchase price were added together and
compared to the price that could be received if the pig was sold to a local pig butcher.
The main components of the algorithm are presented in Figure 5.7.1. The assumptions
used to create the algorithm are presented in Table 5.6.1.
147
The algorithm runs once for each starting month of pig ownership from January
to December (Figure 5.7.1). We hypothesized that the season would influence the costs
of feeding pigs because certain crops have limited seasonal availability and would
change the optimal feed rations (Lemke et al., 2007). For each starting month of pig
ownership, the algorithm runs once for each opportunity cost (100%, 75%, 50%, 25%,
0%, and 0% of the market price with no free feeds) of farm-grown feeds evaluated
(Figure 5.7.1). As most smallholder farmers have mixed crop-livestock farms (Kagira et
al., 2010) many of the feeds provided to pigs are grown on farm. The opportunity cost of
feeding pigs farm-grown crops was valued as the forgone revenue that could have been
earned by selling the crops at the market. We hypothesized that the opportunity costs
of feeds would influence the composition of the least-cost feed rations and the feed
costs. For each month and opportunity cost, the algorithm runs once for each average
daily gain between 80 and 180 grams/day in increments of 25 (Figure 5.7.1). The range
of 80 to 180 grams per day was based on the 25th and 75th percentiles for average daily
gains in Busia reported by Carter et al, (2013) (Table 5.6.1). Average daily gain was held
constant over the duration of pig ownership regardless of the average daily gain
scenario being assessed. This assumption was based on findings by Carter et al., (2013)
who did not find differences in the mean average daily gain by age. We hypothesized
that average daily gain would influence the feed rations chosen and the economic
feasibility of pig ownership. Most farmers in resource-poor areas feed their pigs what
they have available rather than feeding pigs ad libitum (Mutua et al., 2012; Muhanguzi
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et al., 2012) because food is scarce, especially during non-harvest periods. High average
daily gains are not necessarily useful if the feed required to obtain weight gain is too
costly (Parris and Devendra, 1972; Lekule and Kyvsgaard, 2003). Low average daily gains,
particularly in semi-intensive or commercial pig rearing systems can also be
economically inefficient (Peters et al., 2005) because most of the feed costs and
nutrients from the feeds are expended on maintaining the pigs’ bodily functions rather
than contributing to protein acquisition (NRC, 1998). For each evaluated starting month
of pig ownership, opportunity cost of farm-grown feeds being evaluated, and average
daily gain, the algorithm runs once for each pig weight from 8 kilograms (Table 5.6.1) to
65 kilograms incremented by 1 kg (Figure 5.7.1). A least-cost feed ration and subsequent
feed cost for the pig to grow 1 kg is calculated at each pig weight.
Before the linear program is executed, several adjustments are made to the
inputs. The first adjustment is to the feeds that are made available based on the month
that the pig is being fed. The month of feeding is derived by multiplying the number of
grams the pig has grown since weaning by the average daily gain (grams per day) to get
the number of days the pig has been owned. The number of days is then added to the
starting month to get the month the pig is being fed in the current iteration of the
algorithm. The second adjustment is made on the prices of the farm-grown feeds, which
are multiplied by the opportunity cost being evaluated in the current iteration. The
highest opportunity cost of feeding farm-grown feeds (100%) would be the full market
price, whereas with 50% opportunity cost would be half the market price for farm-
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grown feed. Some farm-grown feeds are made available in small quantities for free to
emulate farmers providing pigs with table left-overs and spoiled crops. Any additional
quantities of farm-grown feeds are evaluated at the opportunity cost being evaluated in
the current iteration of the algorithm. The items made available for free in small
quantities when in season include avocado (<150 grams per day), ugali (<250 grams per
day), mango (<200 grams per day), cassava peel, and banana peel. The third adjustment
is made on the nutrient contents of each feed available to the linear program. The linear
program is run with feed nutrients provided on an as fed basis, so the nutrients in each
feed item are adjusted based on the feed intake assumed for the pigs’ weight in the
current iteration.
Pigs were assumed to intake 1/20th of their weight (Table 5.6.1) based on
approximate ratios from NRC (NRC, 2012). Pigs fed ad libitum alter their feed intake
based on the digestible energy of the feed (NRC, 1998) However, pigs in the study area
were not assumed to be fed ad libitum, even under semi-intensive conditions
(Muhanguzi et al., 2012), so the nutrient requirements had to be fulfilled in the assumed
weight of the feed (1/20th of pig weight). The last adjustment programmed in the
algorithm is on the daily digestible energy, crude protein, lysine, and phosphorus and
calcium requirements of the pig. The requirements are based on pig weight and the
average daily gain of the current iteration of the algorithm. For digestible energy, crude
protein, and lysine the requirements are derived by summing the equations for growth
and maintenance for the respective nutrients from Paul et al., (2007) (Table 5.6.1
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equations 1 through 6). The calcium and phosphorus requirements are derived using
NRC recommendations, stratified by pig weight (Table 5.6.1).
Data from every feed ration created by the linear program is kept so that
example feed rations, and statistics on how many times a feed item appears in the
models can be calculated. As the algorithm emulates the pig growth through time, a
cumulative cost is derived which includes the initial piglet cost of 500 KES (Table 5.6.1)
and the subsequent feeding costs for each kilogram of weight gain. After all of the
feeding scenarios are run, the butcher price (adjusted for the live weight by adding 25%
to the dressed weight that was recorded to determine the price per kilogram of live
weight) is compared against the cumulative feed cost to determine the weight which
maximizes profit (marginal cost of feed = marginal cost of feeding pig to the next
weight) and the weight which maximizes the total revenue of the pig (closest weight
where pig price – cumulative feed cost + piglet purchase price was still above 0). All the
algorithm output prices were presented in Kenyan shillings at an exchange rate (June
2009) of 1 USD ~ 78.74 KES (Anonymous, 2009).
5.2.3. Data for the linear program
To determine least-cost feed rations using linear programming, three sources of
data were required: the nutrient content of feeds, the prices of feeds, and the nutrient
requirements of pigs.
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Key informant interviews with livestock officers and farmers helped identify
commonly used feeds. Farm-grown feeds, free feed items, feeds that could be
purchased from the local market and commercial feeds were all considered. Nutrient
content of locally available feeds and the suggested restrictions within a pig diet were
gathered from feedipedia.org (Feedipedia, 2012) and the National Research Council
(NRC) (NRC, 1998; NRC, 2012) and are provided in Table 5.6.2. Several free feeds were
available for feeding pigs including banana leaves and peels, cassava foliage and peels,
grass, and sweet potato vines (Table 5.6.2).
The market prices of feeds were collected by local research assistants who
purchased food items at the main Busia market in July 2009 and are included in Table
5.6.2. Each food item was weighed using a digital scale (Salter RTM), and price was
divided by the weight to derive the price per kilogram in Kenyan shillings (KES). The
price of commercial pig feed was collected from a local veterinary and agronomic
company in Busia. All of the free feeds tended to be high in fiber (Table 5.6.2). Omena
dust (dried fish), soybeans, blood, and brown beans had the highest proportions of
protein, and were the most expensive feeds (Table 5.6.2). Omena dust is the dust
remaining from a dried local fish, and can be purchased at local markets. Millet and
maize were the densest sources of energy as they were high in digestible energy and
low in fiber (Table 5.6.2).
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The nutrient requirements of growing pigs reflect the amounts of energy,
protein, vitamins, minerals and water required to sustain a pig’s bodily processes,
temperature and body weight, and to ensure protein deposition for growth (NRC, 2012).
Nutrient requirements of pigs in resource-poor environments differ from what is
reported by NRC for commercial pigs in developed economies, due to differences in
genetics, growth rates, full-grown body weights, feed quality and climatic conditions
(Paul et al., 2007). Paul et al., (2007) used recorded weight gains from 27 studies and
102 dietary treatment groups on a total of 652 pigs to provide equations for digestible
energy (DE), protein (CP), and amino acid requirements for pigs in India, stratified by
weight. We assume that the nutrient requirements for pigs in Kenya more closely reflect
the equations provided by Paul et al., (2007) than those of NRC because of greater
similarities in climatic and socio-economic conditions, and metabolic rates of local pigs.
The scope of nutrient requirements in our study was limited to digestible energy, crude
protein, lysine, as derived from Paul et al. (2007), and calcium and phosphorus as
derived from NRC (NRC, 2012), as values for these minerals were not provided by Paul
et al., (2007).
5.2.4. Data for the software algorithm
To determine the influence of season on feed costs, the harvest months of farm-
grown feeds were collected from the FAO crop calendar website (FAO, 2013) and are
presented in Table 5.6.3 along with any feed restriction recommendations from the
NRC1 or Feedipedia2. Grains such as millet and maize were assumed to be available for
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feeding pigs during harvest months and one month after. Beans were assumed to be
available during harvest months and for two months after. All other farm-grown feeds
were assumed to be available during harvest seasons only. Under the assumption that
grains were available for two months after harvest, at least one of the staple grains,
pearl millet or maize, was available in any given month (Table 5.6.3). Pearl millet was
available from January to March and from July to September and maize was available
from February to June and from August to December (Table 5.6.3). Ugali is a meal made
of maize flour or millet flour, and was available all year round (Table 5.6.3). Avocado and
mango were only available from June through August (Table 5.6.3 and Table 5.6.4).
Small quantities of mango, avocado, and ugali were made available for pigs at no cost
because pigs may be tethered under trees to scavenge fallen fruit or be provided left-
overs (Table 5.6.3). Sweet potato vines were available from May to December, and
cassava foliage was available year round (Table 5.6.3).
The prices that farmers received for their pigs were collected from pig butchers
at three slaughter slabs located close to the Busia market where feed cost data were
collected. The slaughter slabs were purposively chosen for the convenience of being
able to visit them daily and because of their local proximity to the main local market.
Slaughter slabs are privately owned, government-regulated facilities where butchers are
required by law to slaughter their pigs. Each slaughter slab was visited approximately 3
times per week between July and September 2010 and again between December and
February of 2011 by a local villager who helped survey butchers and farmers throughout
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the research program. Butchers provided research assistants with the purchase price of
the pig before the pig was dressed and weighed. The pig purchase price and dressed
weight were recorded. Weigh-scales at the slaughter slabs are regularly inspected by
government inspectors. Slaughters at each of the facilities occurred at the same time
each day corresponding to the time a livestock officer was scheduled to inspect
slaughtered pigs.
Pigs were categorized into three pig weight categories of <22 kilograms, 22-35
kilograms, and >35 kilograms, reflecting the 25th, 50th, and 75Th percentile weights,
respectively, for pigs at market age (5.1 to 9.9 months) reported by Mutua et al., (2011)
in the same location.
5.2.5. Data for comparing algorithm with farmer experiences
To understand farmers’ pig selling experience, farmers were interviewed. All of
the pig farmers in each village of the Butula and Funyula divisions of Busia District were
invited to participate in a farmer-training workshop located near or in their home village
in 2008. The invitations were extended by assistant chiefs and village elders. The face-
to-face survey was administered by translators either before or after each workshop
and is described thoroughly by Dewey et al., (2011). Five questions were used from that
survey. Each farmer was asked how many pigs they sold within the last year, the
approximate selling weight of each pig, the approximate daily feed cost for each pig, the
age of the pig was when it was sold, and why the pig was sold.
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5.3. Results
The algorithm generated 20520 least-cost feed rations across all combinations of
average daily gain (80 – 180 in increments of 25), pig weight (1 kg increments from 8 kg
to 65 kg), season (monthly), and opportunity cost of feeds (0%, 25%, 50%, 75%, 100%
and 100% non-free feeds).
Table 5.6.4 provides samples of least-cost feed rations generated by the
algorithm and nested linear program for several combinations of factors. Columns 1 to 5
illustrate how the rations changed across different months of the year as pig weight,
opportunity cost of feed, and average daily gain were held constant. Feeding a 35
kilogram pig to sustain a daily weight gain of 180 grams per day, when opportunity cost
of feed was valued at 25%, cost 52% more in April than in September (Table 5.6.4,
columns 2 and 4). Sweet potato vines were used to their maximum allocations for
rations during the months they were available, and cassava foliage was chosen for
rations in each month (Table 5.6.4). Months when maize was the staple grain of the diet
were more expensive than the months when pearl millet was the staple grain (Table
5.6.4). Omena and bone meal were consistently used across all seasons (Table 5.6.4).
5.3.1. Opportunity cost of farm-grown feeds
Table 5.6.4 (columns 6-11) provides samples of least-cost feed rations generated
when opportunity costs of farm-grown feed vary, holding season, pig weight and
average daily gain constant. As opportunity cost of feeding pigs farm-grown feed
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increased, smaller proportions of millet and maize were chosen for the least-cost feed
rations, and higher proportions of the free feeds such as cassava foliage, mango, and
avocado were substituted in; higher proportions of purchased omena were also used as
opportunity costs of feeding farm-grown feeds increased (Table 5.6.4, columns 6-11).
When the opportunity cost of farm-grown feeds was valued at 100% of the market
price, and there were no free feeds made available to the model, commercial feed made
up the majority of the ration. The daily feeding costs were double that of the scenario
where opportunity cost of farm-grown feeds was 100% and there was access to free
feeds such as mango, cassava, and ugali (Table 5.6.4, columns 10 and 11).
Table 5.6.5 lists the percent of rations in which the respective feeds appeared for
each opportunity cost evaluated. As the opportunity cost of farm-grown feeds
increased, the use of free feeds such as banana peels, cassava peel, cassava foliage,
avocado, mango increased (Table 5.6.5). When farm-grown feeds were valued at 75% of
the market price, or higher, half of the rations required commercial feed. Farm grown
beans and sorghum were only chosen when the opportunity cost was 0% (Table 5.6.5).
5.3.2. Average daily gain
Table 5.6.4 (columns 12-17) provides samples of least-cost feed rations
generated when average daily gains vary, holding season, pig weight and opportunity
costs of farm-grown feeds constant. As average daily gains increased, the feed items
chosen by the least-cost feed rations did not change, just their proportions within the
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rations changed (Table 5.6.4). Daily feed costs increased by 28% as pig weight increased
from 15 kg to 35 kg at an average of 80 grams per day, whereas feed costs increased by
3.5% as pig weight increased from 15 kg to 35 kg at an average of 180 grams per day
(Table 5.6.4).
5.3.3. Profit maximizing or total revenue maximizing goals
Table 5.6.6 provides the profit maximizing pig weights, and the total income
maximizing pig weights generated from the model, after pig butcher prices, feed costs,
and the cost of purchasing the piglet at weaning age were considered. In the absence of
free feeds (100% opportunity costs – no free feeds) there were no profit maximizing pig
weights and the maximum total revenue (zero profit) occurred when the pig was 12
kilograms or smaller (last 5 rows of table 5.6.6). As opportunity costs of farm-grown
feeds decreased, profit, total revenues, and market weight increased for each average
daily gain (Table 5.6.6). As average daily gains increased the potential profit, total
revenue and market weight increased (Table 5.6.6). When maize was valued at 25% of
the market price, the total revenue (which earned zero profit) from daily weight gain of
180 grams per day was double that of daily weight gain of 80 grams per day (Table
5.6.6). If there were opportunity costs of farm-grown feeds, maximizing profit for
average daily gains of 80, 105, and 130 grams per day was not achievable (Table 5.6.6).
Total revenue was maximized when pigs were sold at 15, 22, 25, 29-35, and 33-35
kilograms for average daily gains of 80, 105, 130, 155 and 180 grams/day respectively
when the opportunity cost of farm-grown feed was valued at 25% (Table 5.6.6).
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5.3.4. Feeding costs and butcher price variations
Table 5.6.7 illustrates how average daily gain, opportunity costs of farm-grown
feeds, and the season a pig is weaned impacts feeding costs and how butcher price
variation and the season in which a pig is sold impacts revenues. The variation in feed
costs attributable to average daily gain and opportunity cost was emphasized at larger
pig weights as feed costs cumulated (Table 5.6.7). Butcher price variation between 25th
and 75th percentiles of the pig price within each season was relatively higher at smaller
pigs weights (Table 5.6.7). The feeding costs to grow a pig to 30 kilograms varied by 982
KES, 947 KES, and 379 KES attributable to average daily gain, opportunity costs of farm-
grown feed, and weaning season respectively (Table 5.6.7). The revenues for a 30
kilogram pig varied by 744 KES and 225 KES attributable to butcher or butcher
negotiation variance and seasonal variance respectively (Table 5.6.7).
5.3.5. Pig slaughter records
A total of 212 pig slaughter records were collected. Median pig weights at the
slaughter were 23 kg and 38 kg, for low pig purchasing seasons (June to August) and
high pig purchases seasons (November to February) respectively. Median pig prices for
live weight of pigs < 22 kg, 22-35 kg, and > 35 kg were 81.7, 87.4, and 77.9 KES/kg in low
season and 96.2, 93.7, and 82.2 KES/kg in high season respectively.
5.3.6. Farmer responses
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Sixty-seven percent (40/59) of the 59 the farmers interviewed at the training
sessions in Busia had sold at least one growing pig within the year prior to the interview.
The median estimate of feed costs per day for a growing pig was 9.9 KES (25th percentile
= 0; 75th percentile = 45). Thirty-one percent (12/38) of farmers reported 0 cost for
feeding growing pigs. Farmers reported selling pigs at a median age of 8 months (range
3 to 18) and at a median weight of 28 kilograms (range 12 to 150). The reasons farmers
sold pigs included; needing money for school fees (26%), funeral or health expenses
(21%), specified household problems (17%), purchase school uniform (15%), farm inputs
(9%), food for the family (9%), and the pig was ready for market (2%).
5.4. Discussion
5.4.1. Feeds
Compositionally diverse least-cost feed rations were found resulting from
variability in season, opportunity costs of feed, average daily gain, and pig weight
experienced in rural pig rearing. Given the range of factors that smallholder farmers are
subject to, it may not be achievable to use generic least-cost feed rations under real
conditions to always achieve minimum feeding costs. Feeds most commonly appearing
in the least-cost feed rations were omena, ugali, maize, millet, cassava foliage, sweet
potato vines, bone meal, avocado, and mango, which generally agrees with feeds that
are typically used to feed pigs in Busia (Mutua et al., 2012 and Kagira et al., 2010), with a
few exceptions. Brewers’ waste, sugarcane stems, cassava, and sweet potatoes are
common feed items in Busia (Mutua et al. 2012), but were rarely or never chosen in any
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of the optimum feed rations in our algorithm. Hotel waste, innards from fish and
pawpaw are also fed to pigs in Busia (Mutua et al., 2012) but we did not include these
items in our study. Bone meal is not in common use by farmers in Busia (Mutua et al.,
2012), but did appear in most of the least-cost feed rations in our study. As bone meal is
a significant source of phosphorus and calcium and contributes to the protein content of
a ration (Adeshinwa, 2008), non-use of bone meal in pig feeds could indicate suboptimal
provision of these nutrients. Further research on the dietary requirements of pigs in
Western Kenya is required to improve the accuracy of feeding rations.
5.4.2. Season
Season influences the availability of feeds and therefore the cost of feed rations.
Similarly, Lemke et al., (2007) found that seasonal feed availability influenced the cost
and composition of feed rations in Vietnam, with pigs receiving lower energy diets
during crop shortages. In our study, we found that feed costs could vary by as much as
52% due to differences in seasonal availability of feeds alone. However, our model only
partially accounted for the impact of season on feed costs: while accounting for
seasonal availability of feeds, seasonal price fluctuations were not incorporated into the
model as market prices of feeds were collected only in June. Seasonal price fluctuations
are attributed to production fluctuation, lack of storage, lack of seasonal loans, and
small traders’ inability to absorb price differences (Poulton et al., 2006). Further
research on seasonal feed price fluctuations is required to fully quantify the impact of
season on feed costs.
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Season may also influence the opportunity cost of using farm-grown feeds
because the market price of farm-grown feeds tends to decline when supply increases
at harvest time (Jayne et al., 2010). Grain prices in particular tend to be highly volatile in
local markets. In periods of high grain prices, farmers may be less inclined to use millet
and maize to feed pigs, while with lower grain prices, using surplus grains to feed pigs is
more viable. Our model consistently selected maize and millet in rations when valued at
an opportunity cost of ≤ 50% of the market price. The trend of increased feeding costs
due to lower market supplies of maize, rice bran, and soybean has been identified to
impact smallholders pig farmers in Vietnam (Lemke et al., 2007).
5.4.3. Opportunity costs
When opportunity costs of maize and millet were high, the use of free feed items
such as cassava foliage, cassava peel, sweet potato vines, mango, avocado and banana
leaves increased. All of these items are lower in protein value and contain more fiber
than millet and maize (Table 5.6.2). The most cost effective way to meet protein needs
utilizing mostly free feeds was to increase the proportions of purchased omena or
commercial feed (Table 5.6.4). As millet and maize are substituted for higher-fibre, free
feeds, less omena is required to fulfill nutritional requirements. This suggests that to
fulfill pigs’ nutritional requirements, farmers must either use greater proportions of
farm-grown maize or millet or spend more money on purchased omena or commercial
feeds. Omena has been found to promote weight gain equally to or better than soybean
(Tuitoek JK, 1992), and in this study it was chosen extensively for its protein value. In the
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study location, only 7% of farmers purchase commercial feeds, likely due to cost
aversion (Mutua et al., 2012). Omena is purchased by 78% of farmers, but it is not
provided in feeds in quantities believed sufficient to meet pigs’ protein requirements
(Mutua et al., 2012). Purchasing dried fish products for pig feed is a common practice
for smallholders with extensive management practices in Vietnam (Lemke et al., 2007).
When farm-grown feeds are valued at the full market price and in the absence of
free feeds, our algorithm selected commercial feed extensively (Table 5.6.4). This
situation yielded no realistic profit-maximizing or total revenue-maximizing pig weights
(Table 5.6.6). Commercial pig farming is therefore not economically viable in Busia at
the current feed costs and pig prices. This contrasts the situation in Ibadan Zone of Oyo
State, Nigeria, where large-scale commercial pig farmers are reported to be earning 57%
returns (Ogunniyi and Omoteso, 2011). Feed costs in Nigeria accounted for 59% of
farmers’ variable costs, and pig selling prices were 2 to 3 times the pig selling prices in
Kenya after accounting for currency exchange (Ogunniyi and Omoteso, 2011).
Controlling for all other factors, the profit-maximizing and revenue-maximizing
weights, profits, and total revenues increased with lower opportunity costs of feed.
Semi-intensive pig rearing was feasible when farm-grown feed was valued at low
opportunity costs and when free feeds were available. When no free feeds were
available and farm-grown feeds were full market value, no profit- or revenue-
maximizing scenarios were generated (Table 5.6.6). Increasing the number of pigs on a
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farm would reduce the amount of free feed, and thereby increase the opportunity cost
of farm-grown feeds for each pig. As a result, semi-intensive pig rearing is best viewed
as an economy of scope activity rather than an economy of scale activity. Lemke et al.,
(2007) found that farmers who grew more maize, experienced higher maize yields, or
had higher household revenues were more likely to earn positive gross margins from
pigs. We assume that higher maize yields lower opportunity costs of feeding pigs farm-
grown maize. Under this assumption, our research is in agreement with Lemke et al.,
(2007) as higher household revenues are in part achieved with lower opportunity costs
of farm-grown feeds because pigs are sold at larger weights.
5.4.4. Average daily gain
Faster growth rates result in higher daily feeding costs (Table 5.6.4), but greater
revenues per pig (Table 5.6.6). When pigs experience slow growth, the cumulative cost
of feeding is much higher (Table 5.6.7), holding all other factors equal. With slower
average daily gains, a higher proportion of feed nutrients are utilized for maintenance
(NRC, 1998), particularly as pigs get large. Achieving higher average daily gains by
keeping only the number of pigs that can be fed free feed with low opportunity cost is
the most rational choice when food is scarce and is likely the reason most farmers in the
study area reported keeping between 1 and 3 pigs (Kagira et al., 2010; Mutua et al.,
2012).
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Higher average daily gains required more protein and digestible energy, resulting
in higher proportions of omena and maize or millet in the diet (Table 5.6.4) and reduced
fibre. Poor growth is often attributed to high-fibre diets composed mostly of free feeds
which are not sufficiently supplemented with protein (Adesehinwa, 2008). At the
highest average daily gain of 180 grams per day, the omena proportion of the diet was
21%. The digestibility of ash in the omena in such high quantities may be infeasible
(Tuitoek et al., 1992) and should be the subject of further research.
Higher average daily gains can be achieved by improving pig breeds, however,
smallholders with low income potential may not risk using unproven exotic breeds
because of concern for survival and reproductive rates (Anderson, 2003), and also their
higher costs and input requirements such as housing materials might increase the
perceived risk of keeping pigs (Lemke et al., 2007).
Our results show that pigs experiencing lower average daily gains should be sold
at younger ages (Table 5.6.6), and farmers whose pigs show lower average daily gains
(associated with lower protein intakes), experience steeper increases in daily feeding
costs as pigs grow (Table 5.6.4). This may explain why Anderson (2003) found poorest-
ranking (on a socio-economic scale) families sold their pigs at younger ages. Poorest-
ranked families may also require immediate revenue from selling their pigs sooner. Our
results are in agreement with other studies in finding that pigs are sold to meet critical
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consumption needs such as medical bills, education and food for the family (Lemke et
al., 2007; Mutua et al., 2012; Kagira et al., 2010).
5.4.5. Comparing our model outputs to what farmers reported
The 28 kilogram median reported selling weight falls within the weight range in
the revenue maximizing scenarios from our model (Table 5.6.6). The median selling age
of 8 months is older than most of the modeled optimum ages (Table 5.6.6), which
suggests that there is room for improving feeding efficiency. A crude calculation of the
average daily gain from the selling age and weights reported by farmers in our study
yields an approximate growth rate of 110 g/day (20000 grams /(6 months * 30.4 days
per month) assuming a weaning weight of 8 kilograms at 8 weeks of age). Selling pigs at
an age of 8 months, at an average daily gain of 110 grams per day, and a daily feeding
cost of approximately 10 KES per day, farmers likely are spending 2450 KES on feed. This
would suggest that farmers are feeding their pigs at low opportunity costs.
From the output of our algorithm, there were few realistic profit-maximization
scenarios (Table 5.6.6). However revenue-maximizing scenarios were achievable at
selling weights ranging from 15 kg to 35 kg when some free feeds were available (Table
5.6.6). Based on the model, semi-intensive pig rearing systems could be realistic if
farmers’ goals are to maximize revenues rather than profits. Feed trials would be the
next logical step to validate the algorithm and nested linear program, and to fully
166
conclude that semi-intensive pig rearing using locally available feeds can be
economically feasible.
5.4.6. Conclusion
The findings in this study were based on a model and formulas for pig growth.
Feed trials would be required to validate the metabolic response of pigs when fed the
rations generated by the algorithm. It is unrealistic that farmers would change feed
rations for every pig weight as in our simulation. However, the algorithm allowed us to
study the most commonly used feeds under a variety of seasons, opportunity cost of
feeding, average daily gains, and pig weights. It also allowed us to study the economic
feasibility of semi-intensive pig rearing under a variety of factors. Several factors were
not included or accounted for in the study including; parasite load, diseases, veterinary
costs, the benefit of manure to the farm, salt and vitamin requirements and costs,
provision of water, costs of labour to gather and prepare free foods, housing, and
variation in the genotype of the pigs.
The season of weaning and the season when the pig is purchased impacts the
benefit gained from pigs, however many farmers purchase piglets when they are
available and when they have some disposable income and sell their pigs to meet
immediate cash requirements, so they may not be able to make adjustments around
seasonal factors.
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From a policy perspective, the results from this research demonstrate that free
feed is essential to positive economic outcomes and commercial feed is too expensive
to be feasible. Under the current marketing conditions, local provincial policy makers
should support smallholder farmers rather than promoting large-scale piggery
operations. Several extension messages would be valuable to farmers:
1. Achieving higher average daily gains for the pig results in better economic
outcomes because total feeding costs are lower.
2. Fewer pigs that are fed larger quantities of free feed yield better economic
outcomes than several under-fed pigs.
3. The variance of butcher prices impacts the economic benefit of pigs. Farmers
should be educated and informed about prices, weight estimation and
negotiation techniques to ensure they make equitable trades with butchers.
4. Farmers that gather free feeds to feed pigs will still require a protein source (a
cash outlay) to achieve economically feasible average daily gains.
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5.5. References
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State, Nigeria: A Stochastic Production Frontier Approach, American Journal of
Experimental Agriculture, 2 (3), 382-394.
Adesehinwa, A.O.K., 2008. Energy and protein requirements of pigs and the utilization
of fibrous feedstuffs in Nigeria: A review, African Journal of Biotechnology, 7 (25), 4798-
4806.
Alhassan, W.S., Odoi, F., 1982. Use of Cassava Leaf Meal in Diets for Pigs in the Humid
Tropics, Tropical Animal Health Production, 14, 216-218.
Akanni, K.A. and Onasanya A.S., 2004. Economic Analysis of Private Sector Participation
in Swine Production in Ibadan Metropolis Oyo State, Nigeria, Journal of Agriculture,
Forestry and the Social Sciences, 2 (2), 51-57.
Amills, M., Ramirez O., Galman-Omitogun, O., Clop, A., 2013, Domestic Pigs in Africa,
African Archaeological Review, 30, 73-82.
Anonymous, 2009. Exhangerates24.com. Retrieved June 15, 2009 from
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Balagun, T.F., Bawa, G.S., 1997. Cassava Peels in the Diet of Young Pigs in Nigeria,
Tropical Animal Health Production, 4, 209-215.
Carter, N., Dewey, C., Mutua, F., de Lange, C., & Grace, D., 2013. Average daily gain of
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172
5.6. Tables
Table 5.6.1: Table of assumptions used in the pig feeding to market weight and market
evaluation algorithm for pigs in Western Kenya, 2009.
Assumption Background / Source
Weaned pig is 8 kg
Thirty percent of farmers weaned at 2 months or older,
24% between 1 and 2 months, 19% less than a month
whereas 27% did not know the age (Kagira et al., 2010b)
Pigs grow linearly from weaning to market weight. ADG did not change with age of the pig from 1 month to 10
months of age in Western Kenya (Carter et al., 2013).
ADG is between 80 and 180 grams/day Mean weight for pigs in Western Kenya was 120 – 140
g/day. Lowest 25th
percentile was 80 g/day. Highest 75th
percentile was 180 g/day (Carter et al., 2013).
Growth requirements for pigs in Western Kenya are
based on growth equations for models presented
by Paul et al., 2007 for pigs in India.
DE = ADG * de_growth_const (KJ per g ADG) (Eq. 1)
CP = ADG * cp_growth_const (g per g ADG) (Eq. 2)
LY = ADG * ly_growth_const (g per g ADG) (Eq. 3)
Maintenance requirements for pigs in Western
Kenya are based on maintenance equations for
models presented by Paul et al., 2007 for pigs in
India.
DE = de_maint_const (KJ/KG) * Wt^0.75 (Eq. 4)
CP = cp_maint_const (g/KG) * Wt^0.75 (Eq. 5)
LY = ly_maint_const (g/KG) * Wt^0.75 (Eq. 6)
Calcium and phosphorus requirements taken from
NRC 2012.
Ca =2.26 g; Ph = 1.86 g; pig weight 3-6 kg
Ca =3.75 g; Ph = 3.04 g; pig weight 7-11 kg
Ca =6.34 g; Ph = 5.43 g; pig weight 12-21 kg
Ca =9.87 g; Ph = 8.47 g; pig weight 22-51 kg
Ca =12.43 g; Ph = 10.92 g; pig weight 52-85 kg
Feed intake = 1/20th
* Wt
Feed intake is the same across all ADG’s for each pig
weight
Based on estimated feed intake ratios (NRC, 1998)
(Eq. 1) Growth constant for digestible energy = 32, 35, 28.6 for pig weights 8-19, 20-34, and 35-65 kg
respectively.
(Eq. 2) Growth constant for crude protein = 0.39, 0.31, 0.27 for pig weights 8-19, 20-34, and 35-65 kg
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respectively.
(Eq. 3) Growth constant for lysine = 0.0071, 0.0101, 0.0075 for pig weights 8-19, 20-34, and 35-65 kg
respectively.
(Eq. 4) Maintenance constant for digestible energy = 532, 516, 702 for pig weights 8-19, 20-34, and 35-65 kg
respectively.
(Eq. 5) Maintenance constant for crude protein = 11.62, 11.52, 10.68 for pig weights 8-19, 20-34, and 35-65 kg
respectively.
(Eq. 6) Maintenance constant for lysine = 0.568, 0.567, 0.664 for pig weights 8-19, 20-34, and 35-65 kg
respectively.
Wt= pig weight, CP = Crude Protein, DE = Digestible Energy, LY = Lysine, Ca = calcium, Ph = phosphorus
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Table 5.6.2: Nutrient levels and market prices of locally grown feeds from Western
Kenya made available to the lowest cost feed ration models, collected in Busia
markets in 2009.
DE
MJ/kg
of
DM
CP
% of
dry
matter
ADF
% of
dry
matter
Ly
% of
protein
Ca
g/kg of
dry
matter
Ph
g/kg of
dry
matter
% dry
matter
KES/kg
Avocado 19.7 7.4 15.8 1.3 0.7 2.1 95 10
Banana (peeled fruit) 14.2 5.2 7.4 1.3 0.2 0.9 21.9 25.77
Banana leaves 2.6 7.7 48.2 1.7 8.1 2.6 94.3 0
Banana peel 13.8 7.1 9.9 1.6 4.6 1 15.4 0
Blood (from cattle) 20.2 91.8 0 8.7 8.9 4.1 19.1 80.47
Bone Meal-calcinated 1.4 0 3 4.7 303.2 140.2 95.4 56.67
Brown bean (common) 15.3 24.8 6.3 6.8 12.3 2.1 19 64.57
Cassava foliage 12.4 24.8 27.2 5.6 11.9 3.7 22.5 0
Cassava peel 10.1 4.8 17.1 1.1 1.7 2.1 28.2 0
Cassava tubers 15.3 2.9 5.4 3.9 1.7 1.1 87.6 28.88
Commercial pig feed 14.4 19.4 3.4 4.4 8 7 - 30
Distillers grain
(Machicha)
12.5 17.2 17.7 3 2.9 8.2 35.2 36.97
Grass 7.6 9.9 29.6 3.1 0.7 0.21 20.5 0
Maize flour or Ugali 16.6 8 3.2 2.9 0.4 2.9 90 35.69
Mango 14.1 4.7 6.9 1.1 1.9 1.1 17.1 24.39
Millet (pearl millet
grain)
13.7 12.5 4.5 2.8 0.4 3.3 89.7 27.81
Molasses (sugar-cane) 13.3 5.5 0.5 0.1 9.2 0.7 73 18.66
Omena dust 18.1 75.4 0 7.5 26.5 22.5 92.1 97
Posho mill waste 13.4 7.7 5.03 1.7 2.01 1.2 91.5 31.67
Potato (raw Irish tuber) 14.5 10.8 3.9 4.9 0.7 2.2 20.2 17.6
Rumen content (Fresh
from cattle)
8.7 16.2 22 3.7 2.1 6.2 12 46.38
Sorghum grain 16.1 10.8 4.3 2.2 0.3 3.3 87.6 47.85
Soybeans 20.3 39.6 8 6.2 3.3 6.1 88.8 92.23
Sugar cane forage 6.7 4.1 29.7 0.9 1.9 1.1 22.6 0
Sweet potato 14.6 5.5 5.2 4 1.2 1.5 30 21.12
Sweet potato vines 7.4 13.2 32.2 4.8 12.4 3.1 88.5 0
DE (digestible energy); CP (crude protein); ADF (Acid Detergent Fibre); Ly (Lysine); Ca (Calcium); Ph
(Phosphorus). Lysine values were imputed for cassava peel, mango, banana peel, and banana leaves using a
175
mean ratio of protein to lysine from the other feedstuffs. Feed values were obtained from Feedipedia.org or the
National Research Council (NRC).Omena is a sardine-like small fish from Lake Victoria. Ugali is a staple food
made with ground maize flour, water, and a small amount of oil. Machicha is waste from home-brewed beer.
Posho mill waste is the sweepings from the floor of grist mill that include maize, millet, cassava, and bean dust.
Calcinated bone-meal price was estimated because in Kenya the FAO reported it as about 1/3 cost of omena.
176
Table 5.6.3: Seasonal availability of feed ingredients available in Busia, and suggested
restrictions for each ingredient made available to the lowest cost feed models.
Feed Month the feed item is available (x) Suggested restrictions in a
ration
J F M A M J J A S O N D
Free
Banana leaves x x x x x x x x x < 15%
Banana peel x x x x x x x x x < 20% up to 0.5 kg
Cassava foliage x x x x x x x x x x x x < 40%
Cassava peel x x x x x x x x x x x x < 30% up to 0.5 kg
Free avocado
(150 g/day)
x x x < 25%
Free mango
(200 g/day)
x x x < 25%
Grass x x x x x x x x x x x x < 20%
Sugar cane forage x x x x
Sweet potato vines x x x x x x x x < 15% up to 0.5 kg
Ugali
(250 g/day)
x x x x x x x x x x x x
Valued at Opportunity
cost
Avocado x x x < 25%
Banana x x x x x x x x x < 25%
Brown bean x x x x x x x x x x
Cassava tubers x x x x x x x x x x x x
Maize x x x x x x x x x x
Mango x x x < 25%
Millet (pearl) x x x x x x x
Potato (tuber raw) x x x x x x
Sorghum grain x x x x x x x
Valued at full cost
Bone meal x x x x x x x x x x x x
Commercial feed x x x x x x x x x x x x
Distillers grain (Machicha) x x x x x x x
Omena dust x x x x x x x x x x x x
Soybeans x x x x x x x x x
x means feed item is available in the month. Blank means feed item is not available in the month.
All model restrictions for feed were based on research compiled from Feedipedia.org. The food available on farm
was based on harvests provided by FAO’s crop calendar website (FAO, 2013). Maize and millet were assumed to
177
be available during harvest season and one month after. Soybeans were assumed to be available on farm during
harvest season and two months after.
178
Table 5.6.4: A sample of feed rations and the costs generated by the lowest cost feed model for different ADG scenarios, pig
weight, season, and proportion of true market prices when farmers feed pigs in Western Kenya, 2009.
Factor that changes Month of feeding pig (season) Opportunity cost of feed ADG and pig weight
Column number 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17
Pig weight (KG) 35 35 35 35 35 35 35 35 35 35 35 15 15 22 22 35 35
Average daily gain (g/day) 180 180 180 180 180 180 180 180 180 180 180 80 180 80 180 80 180
Month of feeding Mar Apr May Sep Nov Aug Aug Aug Aug Aug Aug Jan Jan Jan Jan Jan Jan
Opportunity cost .25 .25 .25 .25 .25 0 .25 .50 .75 100 1001 .25 .25 .25 .25 .25 .25
Avocado .20
Avocado (free) .04 .17 .17 .17
Banana leaves .01
Banana peel .17 .17
Bone meal .01 .01 .003 .01 .003 .01 .01 .01 .01 .003 .001 .01 .02 .02 .01 .01
Brown bean
Cassava foliage .20 .36 .18 .13 .18 .13 .06 .15 .32 .20
Cassava peel
Commercial feed .69
Grass
Maize .39 .44 .44
Maize grain or Ugali (free maize) .14 .14 .14 .14 .14 .14 .14 .14 .14 .33 .33 .23 .23 .14 .14
Mango .11
Mango (free) .03 .23 .23
Omena .06 .10 .09 .05 .09 .05 .05 .06 .13 .13 .12 .21 .07 .10 .05 .06
Pearl millet .59 .51 .8 .48 .38 .54 .46 .53 .65 .47 .59
Sorghum
Soy bean
Sweet potato vines .15 .15 .15 .15 .15 .15 .15 .15
Cost per kg 10.4 13.8 12.7 9.1 12.7 5.1 9.0 11.8 12.4 12.4 25.4 15.7 23.4 11.9 15.7 8.62 10.4
Intake (kgs) 1.75 1.75 1.75 1.75 1.75 1.75 1.75 1.75 1.75 1.75 1.75 .75 .75 1.1 1.1 1.75 1.75
Total cost per day 18.2 24.2 22.2 15.9 22.2 8.9 15.8 20.6 21.8 21.8 44.5 11.8 17.6 13.1 17.3 15.1 18.2
179
1 No free feed such as free mango, cassava foliage, or ugali were made available to the model. All available
items were priced at the full market value.
180
Table 5.6.5: The proportion of the least-cost feed rations that included each specific
feed ingredient for pigs between 8 and 65 kilograms grouped by opportunity cost of
farm-grown feeds, evaluated as a proportion of the market price in Western Kenya in
2008-2009.
Opportunity cost of feed evaluated
Cost Feed 0% 25% 50% 75% 100% 100%1
Free
Banana leaves 100 26 21 21 21
Banana peel 27 55 60 60
Cassava peel 51 57 57
Cassava foliage 46 59 56 70 70
Free avocado 8 23 24 24
Free Mango 15 18 18
Grass 10 6 5 5
Sweet potato leaves 65 67 52 38 37
Ugali (free maize) 100 100 100 100
Valued at
opportunity
costs
Avocado 4 05 100
Banana 45
Brown bean 40
Cassava 8 3
Maize 33 33 21
Mango 19
Millet (pearl) 58 54 43 24 3
Sorghum 9
Soybeans
Full Bone meal 88 84 82 63 52 43
Commercial feed 12 50 64 100
Dried fish 100 100 100 97 91 23
1 No free feed such as free mango, cassava foliage, or Ugali were made available to the model. All farm-grown
feed items were priced at the full market value.
181
Table 5.6.6: The most profitable, and the highest revenue earning pig scenarios in Western Kenya, using locally available free
feeds, and feed prices from Busia markets which were collected in 2009. Median butcher prices were used to assess profit which
was calculated using feed costs, an initial piglet purchase price of 500 KES, piglet purchased at 8 kilograms, 2 months of age.
Maximizing profit (MR>MC) Maximizing revenue without loss (TR>TC)
ADG % of market price Final
Weight
Age Feed
cost
Revenu
e
Profit Final
Weight
Age Feed
cost
Revenue Profit
80 0% 17 5.7 925 1731 306 35 13.1 2802 3374 71
105 0% 35 10.4 2344 3374 530 35 10.4 2460 3374 413
130 0% 35 8.8 2122 3374 752 60 15.1 4506 5014 7.3
155 0% 50 11.0 3125 4192 566 60 14.1 4521 5425 403
180 0% 62 11.9 3866 5178 812 65 12.5 4135 5425 789
80 25% - - - - - 15 4.9 1012 1539 26
105 25% - - - - - 22 6.3 1681 2212 31
130 25% 21 5.3 1436 2116 180 30 7.6 2398 2905 7
155 25% 22 5.0 1478 2213 234 35 7.8 2740 3374 134
180 25% 34 6.9 2511 3280 269 35 7.05 2624 3374 249
80 50% - - - - - 15 4.9 1023 1539 16
105 50% - - - - - 22 6.4 1710 2212 2
130 50% - - - - - 26 6.5 2024 2530 6
155 50% 21 4.8 1402 2116 214 31 6.9 2490 2999 9
180 50% 22 4.7 1483 2212 229 35 7.05 2825 3374 49
80 100% - - - - - 15 4.9 1023 1539 16
105 100% - - - - - 22 6.4 1712 2212 0
130 100% - - - - - 25 6.3 1903 2437 34
155 100% 21 4.8 1403 2116 213 29 6.5 2269 2812 43
180 100% 22 4.7 1483 2212 229 33 6.7 2262 3187 25
80 100% (no free) - - - - - 10 2.8 545 1058 13
105 100% (no free) - - - - - 11 2.9 624 1154 30
130 100% (no free) - - - - - 12 3.0 725 1250 24
155 100% (no free) - - - - - 12 2.9 707 1250 43
180 100% (no free) - - - - - 12 2.8 724 1250 26
182
- no weight beyond 8 kilograms that maximizes profit.
*Feed cost to the next weight is more than what the butcher is offering per kilogram, so it never makes sense to
own the pig if the feed that is available yields an average daily gain of 80, 105, and 130 grams per day.
Note however that if the pig is purchased and the feed cost is low enough to sustain a small loss, then when the
butchers’ price/kg increases in Sept – Feb then the pig can be purchased to maximize total revenue and a very
small profit is earned as the negative profits turn positive as a result of the increased butcher price.
183
Table 5.6.7: A comparison of the ranges of feed costs against the ranges of bargaining
for pig price, feed is valued at 25% of market price (KES). Net income is calculated
from realistic combinations of ADG, butcher price, and season based on linear weight
gain, and includes the cost of the 500 KES piglet. When feed is valued at 100% of the
market price, the total feed cost does not increase that much as was shown in table
5.6.3.
Pig weight at selling 15 22 30 35 45
Cumulative feeding costs
Average Daily Gain (grams per day) 1
80 1139 2150 3556 4845 8119
130 900 1764 2798 3485 5365
180 887 1631 2574 3224 4472
Opportunity Cost (%) 2
0 685 1233 1864 2178 2995
25 873 1691 2641 3189 4709
50 900 1764 2798 3485 5365
75 900 1764 2811 3534 5591
100 900 1764 2811 3534 5593
Weaning season 3
Lowest 827 1542 2543 3293 5362
Highest 900 1764 2922 3798 5613
Butcher price Butcher price variation
Low season
-25th percentile 1003 1870 2466 2877 3168
-75Th percentile 1725 2373 3210 3748 3487
High price
-25th percentile 1210 2099 2691 3139 3577
-75th percentile 1780 2475 3057 3566 4090
1Opportunity cost = 50% and weaning season = May
2 Weaning season = February, average daily gain = 130
3 Weaning season varies to show the most extreme differences
184
5.7. Figures
Figure 5.7.1: Algorithm used to emulate growing a pig from weaning weight to market weight
to determine the impact of various factors (month of weaning, ADG, opportunity cost of feed,
season, market weight) on profit and total revenue for pig farmers in Busia, Western Kenya
2009.
185
CHAPTER 6. GENERAL DISCUSSION AND RECOMMENDATIONS
6.1. General discussion
The pig industry in Western Kenya provides income opportunities for
smallholder farmers, pig butchers, employees of pig butchers and government
employees. The organization and efficiency of the pork value chain influences how
incomes are distributed, how pig and pork prices are established, and the quality and
safety of the pork that is sold. The current research examined the organization of the
pork value chain and the challenges of butchers and farmers in order to identify
opportunities for ensuring a sustainable industry.
The structure of the pork value chain in Western Kenya has been given little
attention. The first study describes the organization of the pork value-chain and
compares the challenges and operations of rural and peri-urban butchers. Pig butchers
play a central role in the marketing activities of pork by investing capital, assuming risks
(such as the liability of transporting pigs and full financial responsibility for a condemned
carcass), and co-ordinating the transport, slaughter, inspection, and preparation of pork.
Butchers faced several business related challenges including the payment of yearly
government licenses, acquiring capital, and maintaining flow of capital for pig
purchases. Several differences emerged in the way butchers operate their practices in
rural and peri-urban settings. Peri-urban butchers used more modern methods of travel
(motorbike) and relied more on agents to find pigs than rural butchers. Rural butchers
made more regular use of the bicycle, were more likely to raise pigs on their own farms,
186
and more often marketed cooked pork as part of their operation compared to peri-
urban butchers. The limited contractual arrangements between farmers and butchers,
the restriction of capital available to butchers, and the need for butchers to visit the
farm for each pig they purchase limit the efficiency of pig butchers and the volume of
pigs they are capable of processing (when demand is high).
It has been suggested that pig butchers offer farmers low and exploitative prices
(FAO, 2012). Exploitative prices can occur if market conditions are not competitive, or if
butchers experience high marketing and/or transaction costs. The second study
evaluated the economic competitiveness of the butchers and assessed the association
between butcher-related factors and prices, profits, and marketing margins. Butcher
profits were moderate after considering the costs of acquiring capital. However,
exploitative opportunities may still exist if farmers sell pigs before they reach average
market weight or if farmers are misinformed about the size or value of their pig. In the
study, we found smaller pigs were associated with lower pig prices per kilogram. The
lower price may be justified as butchers experience increased costs per kg of pork for
smaller pigs based on expenses such as travel, slaughter, and inspection.
Butchers were operating in a competitive purchasing environment when
concentration ratios were assessed at the district level. It was assumed that butchers
within the same district were competing with each other to source pigs because of the
large distances they travel. Butchers operating in higher trafficked divisions within each
187
district and highly educated butchers charged higher pork prices and earned higher
profits than butchers operating in more sparse divisions or with lower education levels.
This suggests that location choice and education level can influence butcher livelihoods.
Education and extension can have a profound impact on agricultural
productivity. The varying levels of butcher education and experience, the challenges
butchers have in paying their yearly license fees and the threat of human epilepsy due
to Taenia solium (the pork tape worm) were the primary motivations for offering
training workshops to butchers in 2009. The components of the training and the results
of the follow up study to evaluate the impact of training on butchers were the focus of
the third study. The training program was successful in increasing butchers willingness
to have pork inspected, which will likely have positive impacts on the health of the
consumer. One quarter of the butchers associated inspection with preventing illness
caused from the pig tape worm. Most butchers reported some use of record keeping
after the workshop and many butchers began saving money to pay for annual license
fees which will ensure the continuity of their businesses. The small number of
participants in the study (12) prevents the presentation of statistical significance, but
the preliminary results from the workshop and the testimonials of the butchers indicate
that the workshop had a positive impact on butchers.
Average butcher profits were not exploitative when based on comparing the cost
of acquiring capital. However, this does not ensure pig rearing is economically beneficial
188
to farmers. The price that pig farmers are able to negotiate with pig butchers
determines the utility gained from keeping pigs and the kind of production intensity
farmers can afford. The Kenyan government and researchers concerned with preventing
Taenia solium (pork tape worm) advocate that farmers confine pigs instead of allowing
them to scavenge for food. The fourth study seeks to determine if semi-intensive pig
rearing is feasible under the local marketing conditions and evaluates the relative
impact of season, opportunity cost of feed, average daily gain, selling weight, and the
variation in butcher prices on the economic outcomes of rearing semi-intensive pigs.
When some free feeds are available (kitchen leftovers, collected feed such as weeds, or
farm-grown feeds not used for human consumption or waste-by-products), semi-
intensive pig rearing is feasible if the production goals are to maximize revenue rather
than profit and when farm-grown feeds are valued and low opportunity costs and free
feeds are available to feed pigs. In the absence of free feed or when using commercial
complete ration semi-intensive pig rearing is not economically sound based on the
conditions of the rural and peri-urban pig industries in the studied villages. Higher
average daily gains and low opportunity costs of feed result in the best economic
outcomes, suggesting that farmers should keep only as many pigs as they can feed with
some free feeds and meet the pig’s daily feed requirements for maintenance and
growth. Therefore, small holder farmers with limited resources are encouraged to keep
only one or two pigs to ensure they can feed the pigs on a daily basis. Even so, feeding
sufficient quantity to maximize average daily gain is a challenge.
189
6.2 Recommendations
Based on the work of this research, the following recommendations are made:
Key extension delivery for farmers:
• Several feed scenarios and rations can be presented to farmers to demonstrate
the relationship between the proportions of feed ingredients and expected
average daily gain. Higher average daily gains require rations with sufficient
protein and digestible energy, which are achieved optimally using higher
proportions of omena dust and maize or millet. As average daily gains increase,
the profit potential, revenue potential and optimal market weight increases.
• Famers can be shown the relationship between total revenue or profit and
ranges in average daily gain, optimal selling weight, opportunity cost of feed and
pig price.
• Pig rearing in rural and peri-urban settings should be promoted as an economy
of scope activity. Feeding pigs purchased feed results in no economic gain for
farmers under the current marketing conditions and with the costs of
commercial feed currently available.
• Farmers can be encouraged to discuss pig prices with neighbours and learn how
to estimate the weight of their pigs using the tape measure prior to negotiating
the pig price.
• The Kenyan government could enhance the infrastructure required to support
the pork value chains in rural and peri-urban settings. The provision of credit to
190
pig butchers could help facilitate butcher expansion or technology adaption and
could also ensure high levels of competition. The provision of weigh scales in
common locations could promote more equitable trades by increasing the
information trade parties have about pigs. Ensuring that inspectors are
consistently available to inspect pork by equipping them with transport (such a
motorcycles and petrol) and ensuring increased capacity during busy holiday
seasons to ensure that butchers are able to participate in inspecting all of their
pork when demand is high.
Key extension delivery for butchers:
• Butchers benefit from business skills such as record keeping for each pig
purchase and simplified net income statements to enable butchers to estimate
their break-even costs when purchasing a pig.
• Extension and research programs that target intervention strategies for pork
safety should include pig butchers as butchers market 90% of the pork that is
sold to consumers in rural and peri-urban settings of Western Kenya.
• Teach butchers to estimate the weights of live pigs using the tape measure
method.
• Describing costs in terms of kg of pork sold can be helpful to understand the
costs of their business. The math becomes simpler when costs are expressed in
191
terms of kilograms of pork rather than KES, especially when trying to determine
the break-even.
• Understanding farmer constraints is helpful for butchers to relate to farmers and
discourages exploitative behaviour.
6.3. Suggestions for further research
• Determine the relationship between parasite load and average daily gain.
• Determine the efficacy of parasite treatment and the cost-benefit with respect
to farmer income.
• Determine growth potential of pigs when fed a complete ration ad libitum.
• Based on growth rate and carcass quality of pigs, the nutrient requirements of
the pigs should be determined.
• Determine the impact a community scale has on farmer-butcher negotiations,
average pig prices and ranges of pig prices.
• Assess the accuracy of butcher pig weight estimations.
• Design and evaluate insurance program which would mitigate the risk of
condemned pork at the time of slaughter.
• Evaluate the impact of business training for butchers on the range of pig prices
they offer to farmer.
192
APPENDICES
APPENDIX I. PIG BUTCHER SURVEY, 2008
Figure 7.1: Survey used to interview pig butchers in Western Kenya, 2008
Pig Buyers in Western Kenya
We are part of Florence Mutua’s research project. Answers are confidential.
This survey will be used to gain a better understanding of pig buyers and butchers, and
their businesses in this area. Pig buyers are an integral part of the pig industry. We
would like to know about the processes of buying pigs and the challenges that you face
in your business. Our intention is to ensure stability, equity and profits for all
stakeholders in this area.
All answers on this questionnaire are confidential. We will produce a summary of
everyone’s answers all together but your answers will not be shown to anyone in the
area.
Respondent:
Name: _____________________________________
Household Head
Name: ______________________________________
1001. (1.1) Respondent’s Details:
Sex Age
(years)
Education Occupations Relation to household
head
Size of land
(acres)
[Sex Male, Female] [Education Informal, Primary (KCPE), Secondary (KCSE), College and
above [Relation: self, wife, husband, parent, son, daughter]
1002. Respondents Details: Are you the household head? Yes |__| No |__|
193
Figure 7.1 Continuation of 2008 pig butcher survey.
1003. (1.2) Household Head details
(household head is the name of the person making decisions in the family)
Sex Age (years) Occupations
1004 (1.1) Location information
Division: _____________Village: ____________ (Butchery)
Division: _____________Village: ____________Date: __________ (Home)
GPS : Latitude_______________ GPS: Longitude_________________
GENERAL QUESTIONS WE ASKED EVERYONE:
1005. Where was the interview conducted ? (please circle one)
Farm, Butcher shop, Training, Other: __________________________
1006. Is your farm one of the farms that is included in the previous pig farmer survey?
Yes / No
1007. If yes, were you interviewed as part of the previous study? Yes/No
1008. Did you attend farmer training in 2006 (Busia) or 2007 (Kakemega)? Yes/No
194
Figure 7.1 Continuation of 2008 pig butcher survey.
1009. (3.13) Which of the following does the household own? (Please insert the
number of the items owned by that household, 0 for any item the household does not
own)
1010. (1.12) How is each house in your compound constructed? Check all that apply.
House Roof Walls
1 [iron sheets] __ [Grass] ___
[other: specify] ______________
[mud]__ [bricks]__ [Stone]__ [Wood]__
[other: specify] ______________
2 [iron sheets] __ [Grass] ___
[other: specify] ______________
[mud]__ [bricks]__ [Stone]__ [Wood]__
[other: specify] ______________
3 [iron sheets] __ [Grass] ___
[other: specify] ______________
[mud]__ [bricks]__ [Stone]__ [Wood]__
[other: specify] ______________
4 [iron sheets] __ [Grass] ___
[other: specify] ______________
[mud]__ [bricks]__ [Stone]__ [Wood]__
[other: specify] ______________
1011. (1.6) How many people live in your home? ______ adults _____ children
1012. (1.7) How many people live in your compound? _____ adults _______ children
1017. (1.8) Where do you usually get your drinking water? Check all that apply
[River] ____ [Bore-hole]____ [Well]____ [Other (please specify) ______________
ITEM How many ITEM How many ITEM How many
Piped water |__| Armchair sets |__| Working
radio |__|
Water tank |__| Wheelbarrow |__| Working TV |__|
Electricity |__| Hand cart |__| Working
clock |__|
Generator |__| Bicycle |__| Tractor |__|
Telephone |__| Motor cycle |__| Car |__|
Glass windows |__| Working
Latrine |__| Pick up truck |__|
195
Figure 7.1 Continuation of 2008 pig butcher survey.
1018. (1.8b) How far is the nearest drinking water to your home? ___ km (estimate) or
how long does it take to walk there in one direction? ___ minutes
1021. For each livestock animal please complete the following table.
Animal How many do
you currently
keep on your
compound?
How many do you
personally own?
How many did
you personally
own 1 year ago
today?
Approximate cost
of feed and
housing of 1
animal per month
KSH per Month
Amount of hours
of labour for 1
animal per month
Hours per Month
Cattle
Sheep
Poultry
Goats
Sows
Boars
Growing
pigs
(pigs older
than 8
weeks but
not full
grown)
Piglets
(piglets
less than 8
weeks)
196
Figure 7.1 Continuation of 2008 pig butcher survey.
1022. (1.4.3) If you had extra money, which farm animal would you rather buy and
why?
Farm animal:______________________
Reason: ____________________________________________
1023. If you had extra money, which farm animal would be the 2nd likeliest you would
buy and why?
Farm animal:______________________
Reason: ____________________________________________
1024. If you wished to sell an animal in hurry, even if you don’t own one now which
animal is the easiest to sell?
Farm animal:________________
Reason? ____________________________________________
1025. If you wished to sell an animal in a hurry, even if you don’t own one now, which
animal is the second easiest to sell?
Farm animal: _____________________
Reason? _____________________________________________
QUESTIONS ABOUT BUYING PIGS FOR YOUR BUSINESS
1100. (100). Approximately how long have you been buying pigs? ___months (__ years)
1101. Fill in the table to describe how many pigs you buy each year to butcher?
1101.1 What is the average number of pigs you buy in a week or month
_______ per week or ________ per month
197
Figure 7.1 Continuation of 2008 pig butcher survey.
1101.2 What is the average weight of the pigs you buy? ________ KGS
1101.3 What is the average purchase price? _______ KSH
1102. Is there an advantage or disadvantage to purchasing mature sows and boars?
________________________________________________________________
________________________________________________________________________
______________
1103.1 Do you sell any pigs as live pigs rather than butchering them after you buy
them?
[Yes;No]
1103.2 If yes, how many of these do you sell in a month? _____ per month?
1105. (103.) If yes, please indicate the months with a high, average and low number of
pigs purchased. Please check one box in each row.
Month High Low Why
January
February
March
April
May
June
July
August
September
October
November
December
198
Figure 7.1 Continuation of 2008 pig butcher survey.
1107. Is there a time of year, when pig farmers are willing to sell their pigs at a lower
price?
[Yes / No]
1108. If you answered yes to the question above, what are the times of year and the
reasons that farmers are willing to sell pigs cheaper to you?
_____________ time of year _______________________________________reason
_____________ time of year _______________________________________reason
_____________ time of year _______________________________________ reason
1109. How do you find pigs to buy? (ask the question, circle and star 1st response, then
ask all options as true or false one at a time.)
a. A farmer comes to tell me he or she has a pig to sell
b. Farmers just brings me pigs any time
c. I go out to farms asking if they want to sell their pig
d. I arrange to buy someone’s pig before I actually buy the pig
e. I usually know which farmers have market-age pigs and so I know when to
visit them
f. I buy from another local pig buyer
g. I buy from another pig buyer who delivers pigs in his truck
h. I drive in my truck to pick up pigs
i. Other: please specify __________________________________
____________________________________________________
j. Cell phones (farmer calls butcher to sell)
k. Cell phones (butcher calls farmer to buy)
l. Figure 7.1 Continuation of 2008 pig butcher survey
1110. Specify the problems you have finding pigs to buy? (Circle all that apply)
a. There are not enough pigs in the area
b. The pigs are not big enough to use for meat
c. The pigs are not healthy enough to use for meat
d. The farmers want too much money for their pigs
e. Other problem not listed (please describe)
________________________________________________________
________________________________________________________
199
Figure 7.1 Continuation of 2008 pig butcher survey.
1111. Out of every 10 pigs you buy how many come from your village and how many
come from outside your village?
___ pigs come from your village
___ pigs come from outside of your village
1113. Why do you purchase pigs outside of your village? (Circle all that apply)
a) Not enough pigs in village
b) Better pigs come from another village. Which village ___________________
c) Don’t like buying pigs from people within your village
d) Too much competition within the village for buying pigs.
e) Other: Specify: _________________________________
1114. How far do you usually travel to buy pigs? (Please answer all you can)
a) I usually travel ____ hours per day
b) I usually travel _____ kms per day
1115. Do you have specific pig farmers that you regularly buy pigs from? Yes / No
1116. If yes, what percent of the total pigs that you buy come from these farmers?
______%
1117. Do you have a contract or agreement in place with any of the farmers? Yes /
No
IF NO SKIP TO QUESTION 1121
1121. Is there competition for buying the pigs? Yes / No
1122. If yes, does the competition come from within your area or outside your area or
both?
a. Within the area
b. Outside the area
c. Both within and outside the area
200
Figure 7.1 Continuation of 2008 pig butcher survey.
1123. If there is competition, who else do you compete with in buying pigs?
a. Farmers
b. Neighbours wanting to slaughter pigs on their farms
c. Other pig buyers
d. Other pig butchers
e. Farmer groups operating in the villages
f. Big companies like Farmers Choice
g. Other Specify: _____________
1124. Approximately how many pig buyers are there in the area you source your pigs?
____ pig buyers
1125. Once you find a pig to buy do you buy it right away? [Yes; No]
If No,
Why?___________________________________________________________________
_______________________________________________________________________
201
Figure 7.1 Continuation of 2008 pig butcher survey.
1126. How do you decide what price to pay for a pig?
Always
Considered
Almost
always
considered
Sometimes
considered
Rarely
considered
Never
considered
I don’t
know
Size of the pig
Health of the
pig
Age of the pig
Pig is male or
female
Breed of the pig
Time of the year
Other?
Other?
1127. Do you usually estimate the weight of the pig before you buy it? Yes / No
1128. If yes, how do you estimate the weight of the pig? (Circle all that apply)
a. I can tell just by looking at the pig what it weighs
b. I use a scale
c. I use a tape measure
d. I just guess the weight
e. Other Specify: ___________________________________________
1129. When you are purchasing a pig, do you usually negotiate the price of the pig with
the farmer? Yes / No
1130. Briefly explain how this is done? ________________________________________
________________________________________________________________________
________________________________________________________________________
1131. What percent of the time do you negotiate with men or with women or both in
one family? ____% men ___% women ____
202
Figure 7.1 Continuation of 2008 pig butcher survey.
1132. What percent of farmers know what their pig weighs before they sell it? _____%
1133. What do farmers use to estimate the weight of their pigs? (Circle all that apply)
a. They can tell just by looking at the pig what it weighs
b. They use a scale
c. They use a tape measure
d. Other, Specify: ______________________________________
PRICES PAID FOR LIVE PIGS
1200. Fill in the tables of prices that you pay for a market pig?
Weight Lowest price
paid
Highest
price paid
Lowest
Profit
Highest
Profit
22 kg
____KSH
____KSH
____KSH
____KSH
30 kg
____KSH
____KSH
____KSH
____KSH
35 kg
_____KSH
_____KSH
_____KSH
_____KSH
46 kg Sow
(After weaning a
litter)
_____KSH
_____KSH
_____KSH
_____KSH
36 kg Boar
After used for
breeding
_____KSH
_____KSH
_____KSH
_____KSH
BUTCHER SPECIFIC QUESTIONS
1300. Do you own a butchery? [ Yes / No ]
1300.1 Do you butcher on the farm? [Yes; No]
If respondent does not butcher pigs SKIP TO QUESTION 1400
1301. How long have you been a butcher? ______ years.
203
Figure 7.1 Continuation of 2008 pig butcher survey.
1302. How did you learn how to be a butcher?
__________________________________________________________________
__________________________________________________________________
1302.1 Where is the slaughter slab that you butcher your pigs in?
______________________________ Name or Village or Market
1302.2 How far is the slab from butcher shop ____ Kms or ____ minutes walk.
1303. (1.8c) Do you have piped water to your butcher shop? Yes / No
If no, how far is the nearest drinking water to your Butcher shop? ___ km (estimate) or
how long does it take to walk there in one direction? ___ minutes
1304. Out of 10 pigs, how many do you purchase from a farmer and how many do you
purchase from a buyer? ____ pigs from buyer, _____ pigs from farmer.
1305. Who are you likely to get a better price from when you purchase a pig? (Pick one)
a) Pig farmer
b) Pig buyer
c) other please specify: __________________
d) Not applicable
204
Figure 7.1 Continuation of 2008 pig butcher survey.
1306. Please fill in the following table regarding prices of pig and other animal meat
that you butcher and sell.
Before January After January
Price of raw pork per kg
Other: ______________ raw per kg
Other: ______________ raw per kg
Other: ______________ raw per kg
1306.1 How much does it cost for a plate of Ugali and cooked pork from your shop?
_________ KSH or ___ not applicable as I don’t sell a meal of cooked pork.
1306.2 How many kg’s of cooked pork do you sell on a market day? ______ kg
1306.3 How many kg’s of cooked pork do you sell on a NON market day? ______ kg
1306.4 How many market days do you have? ________ / week.
205
Figure 7.1 Continuation of 2008 pig butcher survey.
1308. What is the biggest challenge to selling the pork you butcher?
Challenge Always a
Challenge
Frequently
a Challenge
Sometimes a
Challenge
Rarely a
Challenge
Never a
Challenge
Do not
Know
Selling all the
pork that was
butchered
Finding
unexpected
health problems
with the pig
after slaughter
Passing
government
inspections
Pork going bad
because not
sold fast enough
Getting the right
price
Earning a profit
Other: specify
___________
1309. Out of every ten pigs you butcher, how many are inspected by government
inspectors?
______ pigs out of 10.
1312. Have you ever butchered a pig that had cysts in its muscles? Yes / No
IF NO SKIP TO QUESTION 1400
1313. If yes, How many of these pigs did you see last year? _____ Pigs
1314. Do you know what causes the cysts in the pigs? Yes / No
206
Figure 7.1 Continuation of 2008 pig butcher survey.
1315. If yes, what? ___________________________________________
___________________________________________________________
___________________________________________________________
1316. What do you do when you have a pig with cysts? _____________
___________________________________________________________
___________________________________________________________
___________________________________________________________
1317. Do you think pork with cysts is safe to eat? Yes / No
1318. How can you make sure the pork is safe to eat? _____________
___________________________________________________________
___________________________________________________________
___________________________________________________________
1319. What problems can people get if they eat under cooked pork with cysts?
___________________________________________________________
___________________________________________________________
___________________________________________________________
HUMAN RESOURCES COSTS
1400. Do you employ any people for your business? Yes / No
207
Figure 7.1 Continuation of 2008 pig butcher survey.
1401. For each person you employ or family members that do work for you, please fill
out the following table:
Person Hours
worked
per day
KSH per Day Family
Member
Yes / No
Main job(s) done by the person
1
Butcherman
KSH
2 KSH
3 KSH
4 KSH
5 KSH
1403. Do you have any other jobs beside your businesses that pay you money? Yes / No
Specify? _________________________________
IF NO, SKIP TO QUESTION 1500
1404. If yes, how much time do you spend at your other job each week?
Job:__________________ Hours:_________________
Job:__________________ Hours: _________________
Job:__________________ Hours: _________________
208
Figure 7.1 Continuation of 2008 pig butcher survey.
QUESTIONS ABOUT IMPROVING BUYER’s and BUTCHER’s BUSINESS
1500. If the change mentioned below happened in my village, I think that my pig
buying/butchering business would:
Definitely
improve
Likely
improve
Not
change
Be
somewhat
less
successful
Be much
less
successful
Do not
know
Each farmer raised more
pigs
More farmers raised pigs
Better roads to improve
trading
Better feed for pigs
Healthier pigs
Credit available to pig
farmers
Credit available to pig
buyers
Government supplies low
cost weaned pigs
Improved breeds brought
to the area
Farmer groups
Cooperation between pig
buyers and farmers
Cell phones for farmers
Other
Other
209
Figure 7.1 Continuation of 2008 pig butcher survey.
1501. If you think credit to farmers would help, why would this help?
_____________________________________________________________
_____________________________________________________________
_____________________________________________________________
_____________________________________________________________
1502. If you think credit for pig buyers/butchers would help, why would this help?
_____________________________________________________________ _____________________________________________________________ _____________________________________________________________ _____________________________________________________________
1503. What types of things could help you with your business of pigs buying in the
community?
_____________________________________________________________________
_____________________________________________________________________
1504. If you wanted to expand your business, do you have any access to credit? Yes /
No
1505. If yes, whom can you get credit from? (check all that apply)
a)Government
b)Non Governmental organizations (Give the name of the NGO)
_________________________________________
c) Other pig farmers
d)Farmer groups (merry-go-rounds)
e) relatives
f) Others: Please specify____________________________
210
Figure 7.1 Continuation of 2008 pig butcher survey.
QUESTIONS ABOUT THE POLITICAL EVENTS IN JANUARY
1600. If you compare the availability of pigs from before January
to the time period since January, has the supply of pigs (select one)
a. Increased a lot
b. Increased a little
c. Stayed the same
d. Decreased a little
e. Decreased a lot
1601. If the availability has changed, please describe the reason(s) for this change
___________________________________________________________
____________________________________________________________
____________________________________________________________
1604. What changes in your business resulted because of the political events in
January?
____________________________________________________________
____________________________________________________________
____________________________________________________________
1605. What changes in your business did you choose to make because of the political
events in January?
____________________________________________________________
____________________________________________________________
____________________________________________________________
1606. (3.12) Are there any household members who are employed in this family? [Yes;
No]
1606.1 Was anyone employed in the family before January? [Yes; No]
IF NO SKIP TO QUESTION 1900.
211
Figure 7.1 Continuation of 2008 pig butcher survey.
1607. (3.12.1) If yes, approximately how much salary does each member earn per
month? )
Household
member
≤ 2000 KSH 2001-4000 KSH 4001-10000 KSH ≥ 10,001 KSH
1
2
3
QUESTIONS ABOUT THE IMPACT OF PREVIOUS RESEARCH
Explain the training workshops that were given to pig farmers.
1700. Did you notice any changes in the quality of pigs or in the farmers selling
behaviors since the Pig Research project was conducted in your area?
________________________________________________________________________
________________________________________________________________________
________________________________________________________________________
WRAP UP
1900. Do you have any other comments or suggestions or questions regarding pig
buying, or butchering?
_____________________________________________________________
_______________________________________________________________
_______________________________________________________________
_______________________________________________________________
_______________________________________________________________
Thank you very much for taking this time to answer our questions. We really value the
input you have provided us.
Provide the butchers with weight sheets and tape measures.
212
APPENDIX II. BUTCHER SURVEY, 2009
Figure 7.2: Survey used to interview pig butchers in Western Kenya, 2009
Pig Buyers in Western Kenya
We are part of Florence Mutua’s research project. Answers are confidential.
This survey will be used to gain a better understanding of pig buyers and butchers, and
their businesses in this area. Pig buyers are an integral part of the pig industry. We
would like to know about the processes of buying pigs and the challenges that you face
in your business. Our intention is to ensure stability, equity and profits for all
stakeholders in this area.
All answers on this questionnaire are confidential. We will produce a summary of
everyone’s answers all together but your answers will not be shown to anyone in the
area.
Respondent:
Name: _____________________________________
Were you interviewed Last year? [Yes; No]
If no, please include additional pages of survey. SEE PAGE 7.
QUESTIONS ABOUT BUYING PIGS FOR YOUR BUSINESS
213
Figure 7.2 Continuation of 2009 pig butcher survey.
9020. For each of the following months, please tell us approximately how many pigs
you purchase each week?
Month Pigs Purchased Per Week?
January
February
March
April
May
June
July
August
September
October
November
December
9021. Are there months where you lower the price of your pork per kg ? [Yes; No]
If yes, which months? ______________________________ by how much per kg?
_______ ksh / kg
9022. Are there months where you have trouble selling all the pork from pigs you buy?
[Yes; No]
9022.1 If yes, which months? _________________________________
9022.2 How many kgs per pig get wasted in these months?_________ kgs / pig
9023. Are there months when the pigs generally seem bigger? [Yes; No]
9023.1 If yes, which months? _________________________________
9023.2 Why do you suppose that is? _________________________________
214
Figure 7.2 Continuation of 2009 pig butcher survey.
QUESTIONS ABOUT CHALLENGES
9030. Show us on the dice how big each of the following challenges are.
1 (minor challenge) ......... 6(major challenge)
Challenges to being a pig butcher Record number between 1 and 6
Finding pigs to buy
Transporting pigs
Seasonal variation of business
Paying for health licenses and other yearly
fees
Travelling to buy a pig
Raising capital to expand business or buy
pigs
Competition with other butchers to buy or
sell pigs
Selling pork
Earning a profit
Pigs too expensive
*9031. How do you usually find the pigs you buy?
1. _________________________________________________________
2. __________________________________________________________
9032. Do you have agents that source pigs for you?[yes;no] How many agents? ______
Out of every 10 pigs you buy, how many come from agents? _________ out of 10.
215
Figure 7.2 Continuation of 2009 pig butcher survey.
9033. When you buy a pig through an agent, choose does the agent bargain for the pig
on your behalf or does the agent inform you of a pig and you go to the farm to
negotiate?
a) agent negotiates
b) agent only informs me
c) both apply, but usually it is a or b _______? (choose a or b for this spot)
9034. Out of 10 pigs you buy, how many are local _____, cross breed ______,
exotic ______?
QUESTIONS ABOUT TRAVEL AND TRANSPORT
9036. When you go to a farm to see a pig, how do you usually get there?
______________________________________________________
9039. How is the pig transported from the farm to your business or home? (walked,
biked,pay someone, do they walk bike…)
9039.b How is the pig transported from the business or home to the slaughter slab?
QUESTIONS ABOUT SLAUGHTERING THE PIG
9042. Out of every 10 pigs, how many are killed at the slaughter slab? _____ out of 10
pigs.
9044. Out of every 10 pigs that you slaughter, how many of the carcasses are weighed
before you start selling pork. ________ Carcasses are weighed before selling pork.
9045. Do you charge different prices for different cuts of pork? [Yes; No]
If yes, what charges for what pieces? _________________________________________
216
Figure 7.2 Continuation of 2009 pig butcher survey.
PRICES PAID FOR LIVE PIGS
9201.1 Out of every 10 pigs, how many do you think you lose money on?
______________pigs out of 10 pigs
9201.2 What are the main reasons you would lose money on a pig?
1st Reason: ______________________________
2nd Reason: ______________________________
9201.3 Are there any times when you would buy a pig knowing that you will lose money
once you have sold the pork? [Yes / No]
If yes, what are the reasons?
QUESTIONS ABOUT SWINE INFLUENZA H1N1?
9704. What impact has the swine flu had on the price you charge for pork?
No impact
The price of pork per kg has gone down from __ KSH to to ___ KSH / kg
The price of pork per kg has gone up from __ KSH to ___ KSH / kg
Other____________________________________________
9705. What impact has the swine flu had on the price you pay for pigs?
• No impact
• The price of pigs has gone down a little
• The price of pigs has gone down a lot
• The price of pigs has gone up a little
• The price of pigs has gone up a lot
• Other____________________________________________
217
Figure 7.2 Continuation of 2009 pig butcher survey.
9706. What impact has the H1N1 (swine) flu had on the consumption of pork?
• No change observed
• Consumption has gone down a little
• Consumption has gone down a lot
• Consumption has gone up a little
• Consumption has gone down a lot
• Other ____________________________________
Explain to each participated the following about H1N1:
This new H1N1 (swine) influenza virus spreads from person to person. Spread of this
new virus from a pig to a person has not yet happened. When a pig is sick with
influenza, the pig has a high fever, stops eating, does not want to stand up and acts
depressed. Pigs will shed the virus for 5 to 7 days. The virus will be in the discharge from
their nose and in their breath when they cough. People who handle pigs for this one
week when they are sick may become infected by the influenza virus from the pig. They
are infected by breathing the air coughed out by the pig.
We do not recommend you buy or butcher sick pigs. In the week when the pig is sick
with the influenza virus, there will be virus in the pig’s lungs, nose and tonsils. The meat
of a pig that has been infected with the influenza virus is safe.
Influenza viruses are killed if they dry out, if they are heated or if they come in contact
with soaps, detergents or disinfectants.
218
Figure 7.2 Continuation of 2009 pig butcher survey.
QUESTIONS ABOUT IMPROVING BUYER’s and BUTCHER’s BUSINESS
WRAP UP
9800. What are the biggest challenge(s) of running a butcher business?
1st biggest challenge ____________________________________________________
2nd biggest challenge____________________________________________________
3rd biggest challenge____________________________________________________
[finding pigs to buy][selling pork before it goes bad][making profit][travelling][other:
][Transporting Pigs][Capital to buy pigs]
9900. Are there any other things that you would like to tell us?
_______________________________________________________________
_______________________________________________________________
_______________________________________________________________
_______________________________________________________________
_______________________________________________________________
_______________________________________________________________
_______________________________________________________________
_______________________________________________________________
_______________________________________________________________
Thank you very much for taking this time to answer our questions. We really value the
input you have provided us.
Provide the butchers with weight sheets (they will have been given tape measues by Flo
in June. What about giving them recording sheets for their butcher business or cost
sheets so they can keep track of those. Are we going to give them something like that?)
219
Figure 7.2 Continuation of 2009 pig butcher survey.
The following questions are only asked for new butchers.
Respondent:
Name: _____________________________________
Household Head
Name: ______________________________________
1001. (1.1) Respondent’s Details:
Sex Age
(years)
Education Occupations Relation to
household head
Size of land
(acres)
[Sex Male, Female] [Education Informal, Primary (KCPE), Secondary (KCSE), College and
above [Relation: self, wife, husband, parent, son, daughter]
1002. Respondents Details: Are you the household head? Yes |__| No |__|
1003. (1.2) Household Head details
(household head is the name of the person making decisions in the family)
Sex Age (years) Occupations
220
Figure 7.2 Continuation of 2009 pig butcher survey.
1004 (1.1) Location information
Division: _____________Village: ____________ (Butchery)
Division: _____________Village: ____________Date: __________ (Home)
GPS : Latitude_______________ GPS: Longitude_________________
GENERAL QUESTIONS WE ASKED EVERYONE:
1005. Where was the interview conducted ? (please circle one)
Farm, Butcher shop, Training, Other: __________________________
1006. Is your farm one of the farms that is included in the previous pig farmer survey?
Yes / No
1007. If yes, were you interviewed as part of the previous study? Yes/No
1008. Did you attend farmer training in 2006 (Busia) or 2007 (Kakemega)? Yes/No
1009. (3.13) Which of the following does the household own? (Please insert the
number of the items owned by that household, 0 for any item the household does not
own)
ITEM How many ITEM How many ITEM How many
Piped water |__| Armchair sets |__| Working
radio |__|
Water tank |__| Wheelbarrow |__| Working TV |__|
Electricity |__| Hand cart |__| Working
clock |__|
Generator |__| Bicycle |__| Tractor |__|
Telephone |__| Motor cycle |__| Car |__|
Glass windows |__| Working
Latrine |__| Pick up truck |__|
221
Figure 7.2 Continuation of 2009 pig butcher survey.
1010. (1.12) How is each house in your compound constructed? Check all that apply.
House Roof Walls
1 [iron sheets] __ [Grass] ___
[other: specify] ______________
[mud]__ [bricks]__ [Stone]__ [Wood]__
[other: specify] ______________
2 [iron sheets] __ [Grass] ___
[other: specify] ______________
[mud]__ [bricks]__ [Stone]__ [Wood]__
[other: specify] ______________
3 [iron sheets] __ [Grass] ___
[other: specify] ______________
[mud]__ [bricks]__ [Stone]__ [Wood]__
[other: specify] ______________
4 [iron sheets] __ [Grass] ___
[other: specify] ______________
[mud]__ [bricks]__ [Stone]__ [Wood]__
[other: specify] ______________
5 [iron sheets] __ [Grass] ___
[other: specify] ______________
[mud]__ [bricks]__ [Stone]__ [Wood]__
[other: specify] ______________
1011. (1.6) How many people live in your home? ______ adults _____ children
1012. (1.7) How many people live in your compound? _____ adults _______ children
1017. (1.8) Where do you usually get your drinking water? Check all that apply
[River] ____ [Bore-hole]____ [Well]____ [Other (please specify) ______________
1018. (1.8b) How far is the nearest drinking water to your home? ___ km (estimate) or
how long does it take to walk there in one direction? ___ minutes
222
APPENDIX III. DETAILED BUDGET SHEETS
Figure 7.3: Complete budget survey for pig butchers in Western Kenya, 2009.
223
APPENDIX III. DETAILED BUDGET SHEETS
Figure 7.3 Continuation of budget
224
APPENDIX III. DETAILED BUDGET SHEET
Figure 7.3 Continuation of budget
225
APPENDIX III. DETAILED BUDGET SHEETS
Figure 7.3 Continuation of budget survey, 2009
226
APPENDIX IV. OUTCOME MAPPING SURVEY
Figure 7.4 Butcher outcome mapping survey in Busia, Western Kenya, 2010
Butcher Outcome Survey: Universities of Nairobi and Guelph Pig follow-up project
(May/June 2010)
Questionnaire Number: _______________________ Date __________
Butcher name: ____________________________
Location of the butcher shop: ___________________________
This is a follow up to the pig project carried out by the University of Guelph, University of
Nairobi and the International Livestock Research Institute, Nairobi. The project would
like to document the changes that might have occurred in your pork business since the
time we started working with the butchers in this District. We continue to value the
great working relationship that you have shown us, many thanks from the research
team.
For all the butchers
19001. Were you interviewed by this team before? Yes / No
i. Yes in 2008
ii. Yes in 2009
19002 Did you attend the training in 2009? Yes / No
19003. If yes, are you doing anything differently in your business since the researchers
interviewed you and conducted the workshops? Yes / No
If yes, please describe these changes
________________________________________________________________________
________________________________________________________________________
________________________________________________________________________
________________________________________________________________________
________________________________________________________________________
227
Figure 7.4 Continuation of outcome mapping survey, 2010.
If no, would you like to have a brief training now? Yes / No
If yes, provide a tape measure, weight sheets and give a brief overview of the project. Give a
brief mini-training, and the handout.
We have a few specific questions about potential areas of change to your business.
19004. Are you using any form of record keeping in your pig business? Yes / No
If yes, which ones?
i. Pig purchase sheets yes/no
ii. Profit calculation yes/no
iii. Your own record keeping system yes/no
If yes to any of the above, please explain how you are using them
________________________________________________________________________
________________________________________________________________________
________________________________________________________________________
___________________________
19005. Which of the following do you do when you buy a pig? Compared to last year
(2009), are you more likely to:
a. Use a telephone to get pigs to buy (Yes / No)
b. Use a middle man to get the pigs to buy (Yes / No)
c. Identify specific farmers to buy the pigs from (Yes / No)
d. Buy a pig with another butcher man and share the pork (Yes / No)
e. List other changes that might have happened in your business with regards
to sourcing the pigs for slaughter
f. ____________________________________________________________
g. ____________________________________________________________
h. ____________________________________________________________
228
Figure 7.4 Continuation of outcome mapping survey, 2010.
19022. For the months listed below, please tell us approximately how many pigs you
purchase each week? (Be sure that the question is clear that we want the weekly
purchase)
Pigs Purchased Per
Week in 2009
Pigs per weekIn 2009 Pig purchased per week in
2010
Pigs per week in
2010
June
July
August January
September February
October March
November April
December May
For butchers previously interviewed
19023. Do you have a copy of the pig weight charts provided by the project in June
2009? Yes / No
19024. If yes, have you been using this tool? Yes / No
19025. Briefly describe how you have used the tool?
i. ________________________________________
ii. ________________________________________
iii. ________________________________________
iv. ________________________________________
19026. If you have not been using the charts, briefly explain why?
________________________________________________________________________
__________________________________________________________________
19027. In what ways can the weight chart tool be improved?
________________________________________________________________________
________________________________________________________________________
________________________________________________________________________
229
Figure 7.4 Continuation of outcome mapping survey, 2010.
19028. How do you ensure the pork you sell is safe for human consumption?
What do you do? Did you do this before the
training? (Yes/No)
19029. Do you wear a white coat all the time while in the butcher shop? Yes / No
19030. We are interested to know how often you clean the various parts of the butchery
and if the cleaning protocol has changed since the training
Item How is it cleaned?
(if plain water alone
or water and soap)
How often is it
cleaned?
How often was it
cleaned before
the training?
White Coat
Butcher Knife
Counter of butchery
Floor of butchery
19037 Are there specific measures you undertake to ensure the pig you buy is free of
the pork tape worm? Yes/No
230
Figure 7.4 Continuation of outcome mapping survey, 2010.
19038. Please tell me if you do any of the following when you are buying a pig:
Please answer yes or no to each of the following:
a. I only buy pigs that are housed Yes / No
b. I only buy pigs that are tethered Yes / No
c. I only buy pigs that are confined Yes / no
d. I only buy pigs that are healthy Yes / No
e. Is there any other consideration you use to prevent buying a pig with the
pork tapeworm? Other:________________________________________
19039 Assuming all of the pigs are healthy, if you had your choice, which pig would you
prefer to buy? (please select only one)
b. Market pig
c. Sow that has had a litter
d. Boar that has been used for breeding
19040 If a farmer offered to sell you a healthy breeding sow that has weaned her first
litter, what did you do (in the last year) or what would you do if that happens this year?
a. Buy her to butcher
b. Encourage farmer to rebreed her
c. Encourage farmer to sell to another farmer so she can be re-bred
d. Buy her for a sow on your own farm
e. Other: ______________________________________________
New Butchers interviewed in 2009 for the first time and those not previously
interviewed
19041When did you begin your butcher business? ____ month _______ year
19042 How did you learn to be a butcher?
19043 Do you sell cooked and raw pork or only raw pork? Cooked & Raw; Raw
only
231
Figure 7.4 Continuation of outcome mapping survey, 2010.
19044 What is the average price you would pay and the average profit you would expect
for pigs that are 22, 30 and 35 kg live weight when you buy them
Live Weight Average Price (KSH) Average Profit (KSH)
22 kg
30 kg
35 kg
Please provide the butcher with new record sheets and briefly explain how to fill these
records. Encourage the butcher to record all pigs purchased until we return between
May 24th and June 5th (ask him/her how many sheets they will need for a four week time
period)
Thank you very much for your time and assistance with this survey
232
APPENDIX V. PIG PRICES, VARIABLE COSTS, OPERATING COSTS AND
REVENUES FOR PIG BUTCHERS, 2008-2009.
Table A5.1: Average prices paid for market pigs and breeding animals as estimated by
butchers in Busia and Kakamega Districts, Western Kenya, 2008-2009
Location
Busia Kakamega
Pig type
(weight in kg)
Mean SD Mean SD aP-value
Market pig (22)
1517 214.62 1604 268.31 -
Market pig (30) 2346 411.05 2564 388.47 0.01
Market pig (35)
2626 396.89 3119 493.57 0.0003
Market pig (45)
3409 512.11 4307 544.15 0.0001
Breeding sow (45)
3437 634.11 3969 635.94 0.005
Breeding boar (35) 2644 462.29 3114 810.61 0.052
a Price differs by location based on student’s t-test
233
Table A5.2: Variable costs for operating a pig butcher enterprise in Busia and
Kakamega Districts of Western Kenya, 2008-2009.
Location
Busia Kakamega
Variable Cost Mean
(Ksh)
SD N Proportion
butchers
incurring
the cost %
Mean
(KSh)
SD N Proportion
butchers
incurring
the cost
ap-
value
Agent to find pig 97 54.7 17 100% 108 52.3 17 100 %
-
Transport pig from farm
to shop
97 41.7 16 66.7%
119 46.8 16 93.8% -
Transport pig from shop
to slab
51 25.1 20 45% 61 32.3 14 50%
-
Slaughter slab 197 75.7 24 100% 241 95.5 22 86.4% -
Government inspection
of pig
76 38.3 22 100%
98 30.3 19 94.7%
-
Transport pork from
slaughter slab to shop
54 29.6 20 55%
56 34.4 14 78.6% -
Cost of renting a
transport box per pig
19 13.9 7 57.1%
65 77.8 10 80%
-
Weigh scale rental cost
per pig
54 46.4 10 80%
25 27.2 6 83.3% -
Labour Costs 182 115.8 24 95.8% 240 148.2 25 92% 0.0068
Amenities 55 26.9 24 100% 63 60.0 17 100% -
Cooking costs 202 174.5 24 87.5% 83 53.3 26 26.9% 0.0002
Total Variable Costs
(excluding cooking) b
912 171.9 25 100% 1150 279 26 100% 0.0006
a Differences in mean between districts based on linear regression analyses.
b Total variable costs include an agent and weigh scale rental cost and transport box rental cost which not all
butchers regularly incur. b
Total variable costs include an agent and weigh scale rental cost and transport box rental cost which not all
butchers regularly incur. c Labour costs for cooking pork are included in the cooking costs table.
234
Table A5.3: Operating costs and barriers to entry associated with running a small pig
butcher enterprise in the Busia and Kakamega Districts of Western Kenya, 2008-2009.
Location
Busia Kakamega
Fixed Cost Mean
(Ksh)
SD N Proportion
butchers
incurring the
cost
Mean
(Ksh)
SD N Proportion
butchers
incurring
the cost
ap-value
Purchase
transport box
1488 972.0 15 100% ***
1671 1614.15 9 88.9%
-
Rent per month 759 346.9 23 91.3 %
1377 967.57 19 94.74%
-
Purchase weigh
scale
4725 2313.1 14 92.86% 5184 2713.42 13 100%
-
Personal health
certificate per
person
684 529.6 20 100%
1665 1158.73 14 92.86%
0.003
Business license
per year
3269 901.5 23 100%
2121 740.83 18 88.89%
0.0003
Weigh scale
inspection per
year
1939 1234.6 20 95.0%
1057 578.07 14 92.86%
0.026
Total Fixed Costs 15179 5595.7 25 100% 21505 10971.3 25 96.15% 0.036
Total Purchase
Costs
6117 2189.9 25 100% 6581 2295.3 26 100% -
a Differences in mean between districts based on linear regression analyses
235
Table A5.4: Revenue associated with pig butcher enterprises in the Busia and
Kakamega Districts, Western Kenya, 2008-2009.
Location
Busia Kakamega
Pork
sold as
raw or
cooked
Revenues Mean
(Ksh)
SD N Proportion
of butchers
earning
revenue
Mean
(Ksh)
SD N Proportion
of butchers
earning
revenue
ap-
value
Raw ¼ kg pork 34 4.0 25 100 %
36 5.2 26 100%
-
1/2 kg
pork
67 9.0 25 100 %
72 10.4 26 100%
-
1 kg pork 134 18.1 25 100 %
145 21.4 26 100%
-
Cooked ¼ kg pork 35 5.7 25 68%
39 9.8 7 26.9% -
½ kg pork 70 12.7 25 68% 77 19.8 7 26.9%
-
1 kg pork 143 23.1 25 68%
159 46.9 26 26.9%
-
Head and
feet
189 97.1 20 95.0 %
335 77.4 13 100%
0.0002
Organs 41 13.7 20 95.0%
162 75.0 4 100%
0.001
Steak
premium
per kg
35 19.2 12 33%
53 32.5 11 72.7%
-
a Differences in mean between districts based on linear regression analyses
