 |
| Figure 1. Map of the study area |
| Livestock Research for Rural Development 27 (8) 2015 | Guide for preparation of papers | LRRD Newsletter | Citation of this paper |
A cross-sectional survey was carried out to characterize the pig production systems in four districts along the Kenya-Uganda border. Information was collected by administering structured questionnaires to 645 households in 32 randomly selected clusters.
The study showed that the majority of the farmers owned very small pig herds (2.4±0.1) which were mainly tethered. Their main objective for pig keeping was income generation. Decisions on pig purchases were predominantly made by either women or by women and men in collaboration while day to day care of the animals was performed by women. Disease especially African swine fever (ASF) was considered to be the biggest risk to pig investment, while feeding was the biggest production constraint. Studies that look into cheaper locally available feed options should be undertaken to enable the farmers solve the feed constraint. Sensitization of farmers to adopt biosecurity measures would reduce disease risk especially ASF risk.
Key words: African Swine Fever, Busia, husbandry
Developing countries are making efforts to improve their food security but face difficult choices due to budgetary and institutional resource constraints (IFPRI 2002). Food security particularly in Africa is still a global challenge. This is due to the low pro-poor investment in agriculture and rural development (Van Donge et al 2012). As a major component of agriculture, livestock plays an important role in provision of employment, foreign exchange and livestock products including meat and milk (Ndung'u 2005). In the past decade, there has been substantial increase in the demand for food of animal origin especially in developing countries. Consumption of meat grew at 5.6 percent per annum between 1979 and 1999 and that of milk and dairy products at 3.4% per year (Pica-Ciamarra and Otte 2009). Urbanization is a factor in the increase in demand for and consumption of livestock products in the developing world, primarily in the monogastric sector (Ndung'u 2005).
Pig rearing has the potential for raising household incomes of smallholder farmers especially women (Ouma et al 2013). Pigs are increasingly contributing to improved nutrition and household incomes in regions of Africa where pork consumption and pig keeping are culturally acceptable. Recent studies have revealed a rapid increase in the production and consumption of pork over the recent past in some countries in Sub-Saharan Africa particularly in Nigeria, Uganda, Malawi, Democratic Republic of Congo, Rwanda, Burundi, Ghana and Kenya (FAO 2011). Production and consumption of pork increased rapidly in the 1990s in some countries in sub-Saharan Africa including Uganda. With growing per capita income, population and urbanization, this trend is predicted to continue increasing more than the increase in demand for cereals and root tubers (Pica-Ciamarra and Otte 2009).
In Uganda, pig production has become increasingly important over the past three decades. During this period pig numbers have grown rapidly from 0.19 in 1980 to 3.2 million in 2008. Consumption has risen tenfold whereas beef is on the decline (UBOS 2009); FAO 2011). Currently Uganda has the largest per capita consumption of pork (3.4 kg/person/year) in Sub-Saharan Africa (Ouma et al 2013; Pezo et al 2014). Attributes of pigs like high fecundity, high feed conversion rate, early maturity, short generation interval and minimal space requirements have made pigs a priority source of livelihoods for over 1.1 million rural poor farmers in 17.8% households in the rural and peri-urban communities in Uganda (UBOS 2008; Pezo et al 2014).
In Kenya, pig production is an important source of household income for pig farmers (Kagira et al 2010; Mutua et al 2010). In terms of livestock exports, pig meat ranked as the second highest earner for Kenya at USD $1,122,000 in 2002 (Kagira et al 2010). Pig farming plays an important role in the livelihoods of many families in rural villages of Western Kenya. The Western province has the largest pig population estimated to be 126,400, approximately 31 percent of the national pig herd (MLD 2010)
The majority of the pigs in Uganda and Western Kenya are kept by smallholder farmers (Kagira et al 2009; Mutua et al 2011; Pezo et al 2014). Smallholder farmers have limited resources and very few of them engage in improved pig management thus limiting their ability to engage in profitable pig farming (Muhangi et al 2014;Ouma et al 2014).
Previous studies have shown that smallholder pig production systems in developing countries are low input, low output, high mortality rates, low off take, low reproductive rates, minimal health care, lack of supplementary feeding and lack of proper housing (Nsoso et al 2006; Deka et al 2007; Mutua et al 2011). Despite these challenges, most smallholder farmers still opt for pig production systems instead of adopting other forms of intensive farming (Mutua et al 2011). It was therefore important to understand how the current smallholder pig production was being done so that management interventions can be designed so as to improve pig production and productivity. It was against the above background that this study was undertaken to characterize the smallholder pig production systems in four districts along the Kenya Uganda border. In this region pig keeping is an important activity. Also this area was reported by officials of Ministry of Livestock Development in Kenya to be a hotspot for ASF outbreaks. Therefore understanding the trans-boundary dynamics of ASF is important for disease control to enhance household incomes and food security.
ASF, a viral disease that can cause high mortality in pigs, is endemic in Uganda and Kenya (Penrith et al 2013). While pig production offers opportunities to improve rural livelihoods, smallholder production systems are recognized as presenting multiple pathways for transmission of the ASF virus (Penrith et al 2013). Design of interventions that promote behavioral change amongst value chain actors for reducing ASF risk, needs to be informed by a sound understanding of production systems including processing, marketing and consumption.
Previous studies of pig production systems among rural smallholders have been carried out in Western Kenya focusing on farmer perceptions relating to pig keeping (Mutua et al 2011), characteristics of free-range pig production system (Kagira et al 2009) and market value chain analysis (Kagira et al 2010). However, no study has yet characterized smallholder pig production systems in districts located along the Kenya Uganda border. This is key to understanding trans-boundary issues and cultural and administrative issues that potentially impact on the epidemiology of African Swine Fever (ASF), with the goal of identifying mechanisms to mitigate disease impact.
The study was carried out in the border districts of Uganda (Tororo and Busia) and Kenya (Busia and Teso) an area extending 75 km north from Lake Victoria as shown in Figure 1.
Data was collected through household cross sectional surveys using structured questionnaires. The household surveys were conducted between 12th July and 30th November 2012.The target respondents were household heads in pig keeping households. The aspects covered in the questionnaire included household information, pig production systems, socioeconomic indicators, ASF awareness, biosecurity practices, access to advisory services and social networks.
|
| Figure 1. Map of the study area |
The study targeted pig farmers in the districts of Tororo and Busia (Uganda) and Busia and Teso (Kenya). The sampling frame was pig keeping households. Twenty pig keeping households were randomly sampled from each of the 32 selected villages, yielding a total of ≥640 households. The villages were sampled through a randomised cluster design. The sample size was influenced by resources available for the cross-sectional survey. The sample size was also guided by Thrusfield (2007) who proposed determining a sample size for random sampling n=z²*p(1-p)/m², where n = sample size, z= confidence level at 95% (standard value of 1.96), p = estimated prevalence of ASF in the project area and m = margin of error at 5% (standard value of 0.05), then multiplying by a factor of 2 for cluster sampling to account for potential distortions due to study design.
Using an estimated prevalence of ASF in pigs of 0.3 (Okoth et al 2013), a sample size of 645 households was indicated after design effect of cluster sampling was accounted for as indicated above. The methodology used to select households was based on a two stage sampling process.
Village clusters were selected by spatial random sampling executed using GIS and the 2008 Kenya and 2010 Uganda administrative boundaries, the most recent data sets available in mid-2012. Villages were selected within Level 3 administrative units that had any part of their boundary within 25 km of Kenya-Uganda border. Level 3 units correspond to location and sub-county in Kenya and Uganda, respectively. In Uganda, for each district (level 2 administrative unit), four level 3 administrative units (sub counties) were selected being sub counties that contained one of the four random points in each level 2 administrative unit that were generated using GIS. In Kenya, for each district (level 2 administrative unit); four level 3 administrative units (locations) were also selected using the above criteria. With each selected level 3 administrative unit in each country, two level 4 administrative units being parishes in Uganda and sub locations in Kenya that contained one of the two random points were selected. One of these level 4 administrative units was randomly selected. For the selected level 4 administrative units in Kenya and Uganda, lists of villages and number of households keeping pigs were obtained assisted by veterinary officers and local chiefs. A criterion was adopted such that each of the villages had at least 20 pig keeping households to be selected for sampling. Where more than two villages of at least 20 pig keeping households existed in selected level 4 administrative units, then two villages of this size were randomly selected. In villages that had less than 20 pig keeping households, the selection was extended to include households from adjoining villages to make up a total of about 20 households across a contiguous area. In total 32, villages’ clusters were randomly sampled.
Data were captured using Palm Digital Assistants (PDA) manufactured by Aceeca Limited in Christchurch, New Zealand ( http://aceeca.com/about-us). The PDA device was Aceeca Meazura™ MEZ-1000. The Software run on Pendragon forms 5.1 and data were downloaded into a Microsoft Access database on a computer Product URL: Data was also exported from MS Access to the Statistical Package for the Social Sciences (SPSS) version 18 and Microsoft Excel for analysis. The data were analyzed using descriptive statistics.
The households were predominantly headed by males (86.4%). There were more female headed households in Kenya compared to Uganda. Pertaining to the age of household head, the highest proportion was aged above 50 years, followed by those in their 30s and 40s respectively, while the rest were below 30 years. About five-in-every-nine household heads had primary as highest education level attained, followed by those who had secondary education while the rest had either post-secondary or no formal education. Regarding the best educated member of the household, the highest proportion had secondary education, followed by those with primary education while the rest had post-secondary and no formal education (Table 1).
|
Table 1. Characteristics of household heads |
|||
|
Characteristics |
Percentage (%) |
||
|
Overall |
Kenya |
Uganda |
|
|
Gender |
|||
|
Male |
86.4 |
86.3 |
86.6 |
|
Female |
13.6 |
13.7 |
13.4 |
|
Age(years) |
|||
|
Below 30 |
11.4 |
12.1 |
10.6 |
|
30-39 |
26.5 |
27.7 |
25.2 |
|
40-49 |
24.6 |
24.9 |
24.3 |
|
50 Above |
37.5 |
35.5 |
39.6 |
|
Education Level of head |
|||
|
None |
10.0 |
11.5 |
8.4 |
|
Primary |
55.3 |
62.0 |
48.8 |
|
Secondary |
26.3 |
19.9 |
32.8 |
|
Post-secondary |
8.4 |
6.9 |
10.0 |
|
Best Educated member in HH |
|||
|
None |
0.8 |
0.6 |
0.9 |
|
Primary |
37.4 |
45.0 |
29.7 |
|
Secondary |
45.8 |
38.8 |
54.4 |
|
Post-secondary |
16.0 |
24.4 |
15.0 |
|
Occupation |
|||
|
Business |
12.1 |
14.3 |
10.0 |
|
Casual Laborers |
2.6 |
3.1 |
2.2 |
|
Farmers |
65.9 |
63.7 |
68.1 |
|
Civil servants |
10.4 |
9.0 |
11.9 |
|
Others |
8.9 |
9.9 |
7.8 |
|
Country |
100.0 |
50.2 |
49.8 |
|
Household Size |
|
|
|
|
1-5 |
32.2 |
37.2 |
27.2 |
|
6-9 |
51.1 |
49.4 |
52.8 |
|
above 10 |
16.7 |
13.4 |
20.0 |
|
Average household size |
7.1±0.1 |
6.7±0.2 |
7.5±0.2 |
|
Dependency level |
1.8 |
1.6 |
2.5 |
As for household size, slightly more than half of the respondents had six to nine people in their households, followed by one to five people and above ten people. The average household size was 7.1±0.1. Households in Uganda had the highest average household size compared to Kenya. The overall dependency ratio in the study area was 1.8. Households in Uganda had the highest dependency level compared to Kenya’s. Busia district in Uganda had the highest dependency level amongst the four districts (Table 1).
The highest proportion of the sampled households had 2-5 acres of land. The average land holding was 3.04 ±0.10 acres. Acres were used as a measurement of land instead of hectares which is the standard scientific unit because the households owned very small pieces of land (Table 2).
|
Table 2. Percentage of households owning a certain size of land among the sampled households |
||
|
Land owned in acres |
Number of households |
Percentage (%) |
|
<1 |
92 |
14.4 |
|
1-2 |
214 |
33.3 |
|
2-5 |
228 |
35.5 |
|
5-10 |
68 |
10.6 |
|
>10 |
40 |
6.2 |
|
1acre=1.42hectares |
||
The average number of livestock kept per households was: cattle 2.6 ± 0.1, sheep 0.14 ± 0.02, goats 1.6 ± 0.9, poultry 13.5 ± 0.5 and pigs 2.4 ± 0.09. The majority of the households kept very few pigs mean pig herd size of 1.39 ±0.02. The overall mean pig herd size was 2.43±0.10.
Mean pig herd sizes per country and per district were as shown in Table 3. The overall mean pig herd size (including piglets) was 2.43 ±0.10. Uganda had slightly larger mean pig herd sizes compared to Kenya. Busia district Uganda had the largest mean pig herd size of 2.79±0.28
|
Table 3. Mean pig herd sizes per country and per district |
||
|
Country |
District |
Mean pig herd size |
|
Kenya |
Overall |
2.28±0.11 |
|
Busia |
1.99±0.12 |
|
|
Teso |
2.57±0.19 |
|
|
Uganda |
Overall |
2.60±0.17 |
|
Busia |
2.79±0.28 |
|
|
Tororo |
2.41±0.17 |
|
|
Overall mean |
|
2.43±0.10 |
The largest proportion of pigs was local weaners (Table 4).
|
Table 4. Percentage herd composition per pig age, sex and breed category in each district |
|||||
|
District |
Busia_Ke |
Busia_Ug |
Teso |
Tororo |
Overall |
|
Local piglets |
14.5 |
26.2 |
26.8 |
18.3 |
22.3 |
|
Cross breed piglets |
0.9 |
0.7 |
6.1 |
0.0 |
2.2 |
|
Local weaners |
40.6 |
42.1 |
38.1 |
51.2 |
42.7 |
|
Cross breed weaners |
10.7 |
7.6 |
3.1 |
3.1 |
5.8 |
|
Local sows |
16.7 |
13.9 |
15.2 |
16.7 |
15.5 |
|
Cross breed sows |
2.8 |
1.8 |
1.6 |
0.5 |
1.6 |
|
Local boars |
4.1 |
2.0 |
2.9 |
3.1 |
3.0 |
|
Cross breed boars |
0.9 |
0.4 |
0.6 |
0.5 |
0.6 |
|
Local castrated boars |
7.9 |
4.7 |
5.7 |
6.5 |
6.0 |
|
Cross breed castrated boars |
0.9 |
0.7 |
0.0 |
0.0 |
0.4 |
The majority of the households kept very few pigs (Table 5).
|
Table 5. Percentage of households owning certain pig herd size and mean size per pig size cluster |
||
|
Pig herd size cluster |
Percentage |
mean |
|
1-2 |
72.4 |
1.39±0.02 |
|
3-5 |
21.3 |
3.68±0.09 |
|
more than 5 |
6.3 |
9.90±0.7 |
In most cases, pigs were tethered. Majority of households had purchased at least one pig during the previous year. Parasite control (internal and external parasites) was common among farmers. The majority of households did not have sick pigs in the previous year. However, there were more sick pigs reported in Uganda compared to Kenya (Table 6).
|
Table 6. Percentage of households practicing a certain pig husbandry system in Uganda and Kenya along the border |
||||
|
Characteristics |
Number of households |
Percentage |
||
|
Overall |
Kenya |
Uganda |
||
|
Pig management |
|
|||
|
Free range |
7 |
1.1 |
0.0 |
2.2 |
|
Tethered |
392 |
61.2 |
61.9 |
60.5 |
|
Housed |
3 |
0.5 |
0.3 |
0.6 |
|
Tethered/free range |
226 |
35.4 |
35.6 |
35.1 |
|
Housed/tethered/free range |
2 |
0.3 |
0.3 |
0.3 |
|
Other (includes housed & free range or housed & tethered) |
10 |
1.6 |
1.9 |
1.3 |
|
Purchase of pigs in previous year |
|
|||
|
Yes |
425 |
66.2 |
64.0 |
68.4 |
|
No |
219 |
33.8 |
36.0 |
31.6 |
|
Treatment for external parasites |
|
|||
|
No |
246 |
38.1 |
36.4 |
38.4 |
|
Yes |
399 |
61.9 |
63.6 |
61.3 |
|
Treatment for internal parasites |
|
|||
|
No |
206 |
31.9 |
34.3 |
28.0 |
|
Yes |
440 |
68.1 |
65.7 |
72.0 |
|
Have these pigs been sick |
|
|||
|
No |
568 |
88.5 |
90.1 |
68.9 |
|
Yes |
74 |
11.5 |
9.9 |
13.1 |
|
Swill feeding |
|
|||
|
No |
500 |
77.6 |
||
|
Yes |
144 |
22.4 |
||
In the study area 14% of the household heads were female. Women in Kenya had a stronger role in decision making on pig purchases, day-to-day pig care and ownership of pigs compared to Uganda (Table 7).
|
Table 7. Percentage gender participation in decision making in management and use, husbandry and ownership of pigs in four districts along the Kenya-Uganda border |
|||||||
|
Characteristics |
Percentage (%) |
||||||
|
Overall in the study area |
Kenya |
Uganda |
|||||
|
Busia |
Teso |
overall |
Busia |
Tororo |
overall |
||
|
Decisions on pig purchases |
|
|
|||||
|
Male |
35.0 |
31.0 |
26.4 |
28.4 |
47.7 |
35.0 |
42.3 |
|
Female |
35.5 |
50.6 |
36.3 |
42.6 |
24.5 |
30.6 |
27.6 |
|
Collaborative |
28.5 |
17.7 |
36.8 |
28.4 |
23.3 |
33.8 |
28.5 |
|
Other |
1.0 |
0.6 |
0.5 |
0.5 |
2.5 |
0.6 |
1.6 |
|
Day- to-day care of pigs |
|
|
|||||
|
Male |
5.6 |
8.8 |
11.8 |
10.5 |
13.3 |
5.6 |
9.4 |
|
Female |
51.3 |
77.4 |
77.3 |
77.3 |
60.1 |
51.3 |
55.7 |
|
Collaborative |
40.0 |
13.2 |
8.9 |
10.8 |
24.7 |
40.0 |
32.4 |
|
Other |
0.03 |
0.006 |
0.019 |
0.01 |
0.18 |
0.03 |
0.02 |
|
Ownership of pigs |
|
|
|||||
|
Male |
35.5 |
22.6 |
23.6 |
23.3 |
45.6 |
41.9 |
43.7 |
|
Female |
25.3 |
50.3 |
32.2 |
40.2 |
22.2 |
33.1 |
27.7 |
|
Collaborative |
27.9 |
26.4 |
42.6 |
35.5 |
28.5 |
20.6 |
24.5 |
|
Other |
11.3 |
0.6 |
1.5 |
1.1 |
1.3 |
3.8 |
2.5 |
The number of households keeping pigs was increasing between 2000 and 2012 (Table 8).
|
Table 8. Year households started pig keeping from 2000 to 2012 |
|||||||
|
Year started |
No. of households |
No. in Kenya |
No. in Uganda |
||||
|
Busia |
Teso |
Kenya total |
Busia |
Tororo |
Total |
||
|
2000 |
25 |
7 |
6 |
13 |
7 |
5 |
12 |
|
2001 |
8 |
3 |
0 |
3 |
1 |
4 |
5 |
|
2002 |
26 |
6 |
7 |
13 |
4 |
9 |
13 |
|
2003 |
7 |
1 |
3 |
4 |
3 |
0 |
3 |
|
2004 |
16 |
2 |
5 |
7 |
3 |
6 |
9 |
|
2005 |
19 |
1 |
4 |
5 |
6 |
8 |
14 |
|
2006 |
18 |
5 |
5 |
10 |
6 |
2 |
8 |
|
2007 |
38 |
13 |
10 |
23 |
9 |
6 |
15 |
|
2008 |
29 |
8 |
3 |
11 |
9 |
9 |
18 |
|
2009 |
48 |
12 |
13 |
25 |
13 |
10 |
23 |
|
2010 |
62 |
15 |
26 |
41 |
11 |
10 |
21 |
|
2011 |
81 |
26 |
22 |
48 |
20 |
13 |
33 |
|
2012 |
85 |
18 |
30 |
48 |
26 |
21 |
47 |
|
Total |
462 |
117 |
134 |
251 |
118 |
103 |
221 |
Pig keeping was not a continuous activity as shown in Table 9. There were slightly more households in Kenya that were discontinuous compared to Uganda.
|
Table 9. Continuity in pig keeping |
|||
|
Country/district |
Number of households |
||
|
Continuous |
Discontinuous |
Grand Total |
|
|
Kenya |
128 |
175 |
303 |
|
Busia_Ke |
63 |
65 |
128 |
|
Teso |
65 |
110 |
175 |
|
Uganda |
148 |
157 |
305 |
|
Busia_Ug |
71 |
81 |
152 |
|
Tororo |
77 |
76 |
153 |
|
Grand Total |
276 |
332 |
608 |
Respondents explained that their households came in and out of pig keeping because of various reasons as shown in Table 10.
|
Table 10. Reasons for discontinuity in pig keeping |
||||||
|
Country/district |
All pigs |
Conflict,
|
Feed
|
Financial
|
Other
|
Grand Total |
|
Kenya |
49 |
5 |
10 |
30 |
29 |
123 |
|
Busia_Ke |
30 |
3 |
3 |
10 |
14 |
60 |
|
Teso |
19 |
2 |
7 |
20 |
15 |
63 |
|
Uganda |
95 |
8 |
6 |
23 |
16 |
148 |
|
Busia_Ug |
35 |
6 |
4 |
18 |
8 |
71 |
|
Tororo |
60 |
2 |
2 |
5 |
8 |
77 |
|
Grand Total |
144 |
13 |
16 |
53 |
45 |
271 |
|
Other: Time needed to care for pigs, lack of space, lack of upgraded pig facility/housing needed, lack of access to credit, conflict with neighbors |
||||||
The major cause of discontinuity in pig keeping was pig disease. ASF was implicated as the most prevalent disease that households experienced. Majority of households reported sudden death as the major cause of death of their pigs. The largest proportion of sampled households with discontinuous pig production due to disease was in Tororo District, Uganda
The constraints to pig farming reported by respondents are summarized in Table 11. The major constraint was feeding related. There were more households in Uganda that reported pig health as a constraint compared to Kenya. ASF was implicated by farmers as being the biggest threat to pig investment.
|
Table 11. Percentage of households facing constraints to pig farming |
|||
|
Constraint |
Percentage |
||
|
Do you face any constraints |
Overall |
Kenya |
Uganda |
|
No |
17.1 |
11.8 |
5.3 |
|
Yes |
82.1 |
41.3 |
41.4 |
|
What constraints do you face? |
|
||
|
Feed constraints |
62.9 |
46.5 |
43.2 |
|
Pig health constraints |
18.7 |
3.0 |
12.1 |
|
Market constraints |
0.8 |
0.6 |
0.2 |
|
Risk to pig investment |
|
||
|
Disease |
54.7 |
26.6 |
28.0 |
|
Sabotage |
12.5 |
6.8 |
5.7 |
|
Feed supply |
8.9 |
3.8 |
5.1 |
|
Theft |
15.1 |
12.1 |
3.0 |
|
Other |
8.9 |
3.4 |
5.5 |
Household heads in the study area were literate containing significant proportion with primary and secondary education. The high literacy level in the study area could facilitate implementing extension services for disease control and improved pig management. Farmers can easily be educated with the help of extension staff about improved technologies aimed at enhancing sustainable income from pig production. These findings were in agreement with the national standard literacy levels for Kenya and Uganda where it was reported that the majority of the people aged above 15 years can read and write
The majority of the pig farmers were smallholder farmers. A limited proportion of household heads were businessmen, civil servants and farm workers or casual laborers in sectors other than farming implying that pig farming was an alternative source of income among these households.
Importantly decision making on pig purchases and pig ownership was not male dominated as compared to combined female and collaborative forms of decision making while the day to day care was performed almost exclusively by females. Furthermore, there were a larger proportion of female headed households in Kenya especially in Busia district that played the key role in decision making on pig purchases, day to day care and pig ownership compared to Uganda. This could have been due to cultural differences and level of female emancipation. These findings were in agreement with other studies carried out in Kenya (Mutua et al 2010;Ouma et al 2014) where women took a lead in the management of pigs. However, these results were in contrast with findings of a survey done in Botswana (Nsoso et al 2006) where males played a bigger role in all aspects of pig farming than women. Women play an important role in agricultural development and typically make greater contributions to household economics in the agricultural sector than men. Decisions made by women tend to benefit the whole family and society (Dolan 2005). Women are perceived to be key actors through whom poverty and food security issues must be addressed particularly in Africa through technological empowerment (DFID 2010). It has been argued that improving access to resources for rural women to the same extent as men would increase agricultural production by 20% (DFID 2010). Therefore innovations such as improvement of animal husbandry and adoption of disease control strategies would make a more significant impact if women or women’s groups are involved.
The study showed that the majority of the households owned small pieces of land. Households in Busia Uganda that had the largest percentage of households with the smallest land holdings would have been influenced by the increasing human pressure on the land. These findings reinforce what was reported earlier by Kagira (2009) where the households in Busia district Kenya were reported to own very small plots of land. With small land holdings, households cannot easily engage in multiple activities such as growing of food crops, cash crops and keeping a range of livestock species. It was noted that households that had large land holdings in Tororo had relatively higher incomes because they had diversified income sources obtained from growing crops such as maize, millet, cassava, peas, beans, sweet potatoes, simsim, sunflower, cotton, onions and rice in addition to raising various species of livestock. These findings were reported in another study (Adato and Meinzen-Dick 2002) where households were engaged in multiple livelihood strategies to both attain an improved standard of living and to spread risk.
The majority of the households kept very few pigs and these findings were in agreement with a study carried out by Mutua (2010). Uganda had larger mean pig herd sizes compared to Kenya. Busia district Uganda had the largest mean pig herd size while Busia district in Kenya had the lowest. This was in contrast with findings among smallholder pig farmers in Busia district, Kenya (Kagira et al 2009), Vietnam (Lemke and Zarate 2007) and Nigeria (Ajala et al 2007) that reported populations of pigs owned by households. There were generally very few breeding boars both local and crossbred. Most farmers in the study area obtained breeding services for their pigs from boars that were owned by other farmers within their village. A study carried out in Uganda reported that most farmers were not keeping breeding boars for economic gain (Ouma et al 2014). Keeping boars meant that farmers had to spend extra funds to purchase feed stuffs and care for the boar yet it would have been possible to borrow or hire this service and pay in cash or in kind. Some farmers used to leave their pigs to be serviced by freelance boars, hence completely avoiding such costs. The habit of sharing boars for breeding purposes increased the risk of spread of ASF (Fasina et al 2012) but farmers were not aware of this.
The majority of the households had kept pigs for over ten years with additional households adopting pig keeping between 2000 to 2012. It was shown that households were adopting pig keeping at an increasing rate indicating a growing interest in pig rearing. This was in agreement with findings of Kagira et al (2009) among pig farmers in Busia Kenya where a large proportion of farmers had kept pigs for more than one year. However, pig keeping was not a continuous activity. Farmers moved in and out of the sector for a variety of reasons. The major cause of discontinuity in pig keeping was mainly because of disease risk, or the perception of especially African Swine Fever. The largest proportion of households in this category was located in Tororo District, Uganda.
Almost all farmers faced constraints to pig production particularly feeding but also pig health. These results were in agreement with Kagira et al (2009) who reported that the majority of the households in Busia district Kenya indicated had disease and lack of feeds as the major constraints. During months of food scarcity, farmers would either sell off the pigs or leave them to scavenge which increased the risk to ASF due to increased contact with pigs from other households (Nantima et al 2015). ASF was the biggest risk to their investment. These findings were in agreement with the findings of Kagira et al (2010) and Mutua (2010) where it was reported that feeding was a major constraint in pig farming.
The major pig husbandry practice was tethering. Some farmers kept pigs partly tethered and free range depending on the season. During the planting season, pigs were mostly kept tethered to avoid destroying the young crops in the gardens. Pigs would be left to roam freely after harvesting. Full time free range pig keeping was not frequently practiced in the study area which helped households to control infectious diseases. These findings were in agreement with the findings in Mutua (2010) and Ouma et al (2014) where it was reported that the predominant type of pig management was tethering. On the contrary, Kagira et al (2009) reported that free range systems were the most common among smallholder farmers in Busia district, Kenya. Another study among smallholder pig farmers in Uganda (Ouma et al 2014) found higher percentages of farmers (two in every ten) practicing free range.
The research was performed under the ASF Epidemiology module within the Africa Food Security Initiative funded by Australian Aid and implemented by Biosciences Eastern and Central Africa and the International Livestock Research Institute in partnership with the Commonwealth Scientific and Industrial Research Organisation (Australia). We are grateful to all partners and also appreciate salary support provided to RB under CGIAR consortium research project CRP 3.7.
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Received 30 January 2015; Accepted 12 June 2015; Published 1 August 2015