 |
| Figure 1. Distribution of livestock in the study area |
| Livestock Research for Rural Development 28 (5) 2016 | Guide for preparation of papers | LRRD Newsletter | Citation of this paper |
The poultry industry in Kenya is a key contributor to the economy of local communities as well as food security, incomes and improved nutrition. Over 90% of households in Kenya own a flock of poultry. A cross-sectional study was done to assess how the factors influencing production affect rural and peri urban chicken farmers in Katulani District, Kitui County. The main points of comparison were; house hold demographics, livelihood and income sources, opportunities and challenges, factors affecting adoption of chicken management technologies, flock structure and dynamics. There were 70 rural respondents and 40 peri urban respondents. In total, there were 110 respondents. Data was collected through questionnaires, personal observations, photography and interviews. Simple random sampling technique was used to select the respondents, data collected was analysed using Statistical Package for Social Sciences software to generate descriptive statistics.
All households kept indigenous chicken, with about 72.7% reared for both income and subsistence. Majority (96.4%, n=110) reared chicken under free range and mainly used family labour. Household size had influence on flock size, where larger households kept larger flocks. There were more female headed households (59.1%) rearing chicken in the study area, however male headed households reared larger flock sizes in both study sites. Education level determined the size of poultry flock, peri urban respondents with an average 10 years of study kept larger flock sizes compared to the rural households (average of 8 years studying). There were high levels of unemployment in both study sites. Employment had a significant positive correlation (p<0.05, r=0.64) on purchasing power, with funds available for initial poultry acquisition in both study sites, hence the employed had higher flock sizes. About 84.5% of respondents earned their livelihood from mixed farming as compared to crop farming or livestock keeping in isolation with the employed having higher monthly incomes than from any farm related activities. Chicken contributed about 4.18% and 26.9% of total Tropical Livestock Units in rural and peri urban sites respectively. Opportunities for poultry rearing were the small start-up and low capital investment whereas, the main challenges were diseases, predators, limited poultry production skills and high cost of drugs/vaccines. There were low adoption of all chicken rearing technologies in both rural and peri urban sites although periurban site had higher technology adoption rates. Therefore, more awareness creation and initial promotion of low cost technologies is recommended.
Key words: challenges, chicken, household, opportunities, technology
Majority of the rural populations in the developing world keep a flock of poultry either in free range or confined system (Anders 2008; IFPRI 2010). Chicken (Gallus domesticus) dominates (Anders 2008) with 80% and 20% of chicken in Kenya being of indigenous and exotic types respectively (KNBS 2009). Kitui County, where the study area falls constitutes 2.76% and 0.73% of the national indigenous and exotic chicken population respectively. Kitui County also ranks number 13 and 26 nationally in populations of indigenous and commercial chicken respectively (KNBS 2009). Other poultry species kept include ducks, geese, pigeons and guinea fowls.
This study focussed on chicken rearing because of their resilience to harsh climate, need for less space. In addition, they are preferred and reared by the majority of Kenyan population for cash or subsistence. In Kenya, indigenous chicken flocks were estimated at about 25.7million (KNBS 2009). They are reared by about 90% of the population in small flocks of up to 30 birds, mainly under free range system (Kingori et al 2010; Kirwa et al 2010). Chicken are family owned and managed mostly by women and children. Their products are used for home consumption, as gifts, religious purposes or are sold to earn some income to buy basic household food items (Anders 2008). There has been a high demand for chicken products due to the rapidly growing human populations, demand for high quality food especially protein and improving income levels and standards of living.
Despite the growing demand for chicken, several factors influence their production; 1) production related challenges like diseases, predators, theft, harsh environment, lack of and/or inadequate production skills, poor nutrition, high feed costs and inappropriate flock sizes (KARI 2006; Kirwa et al 2010; Ochieng et al 2013). These result in reduction of chicken numbers productivity in a household and therefore impact on the food security of the farmer (FAO 2007). 2) Adoption of various management interventions like feed supplementation, vaccination, brooding, housing and labour (Ochieng et al 2013). 3) Institutional support to farmers like limited access to; extension services, veterinary services, credit facilities, trainings, access to markets and market information and group memberships (Ochieng et al 2013).
The objective of this study was to shed light on how various factors affect rural and peri urban chicken farmers and propose mechanisms to address challenges and maximise opportunities for enhanced productivity and improved livelihoods.
The study area is a semi-arid area where crop farming is unsustainable due to unreliable and insufficient rainfall leading to recurrent crop failure. Therefore chicken provide an alternative land use option since they are more resilient to climate variability. FAO (2007) noted that the arid and semi-arid neighbouring areas of Kitui (where study area falls), Makueni, Mwingi and Machakos have high concentration of indigenous chicken.
The study area covers an area of 330.4 square km with a population of 45042 persons according to the Kenya National Bureau of Statistics (KNBS) 2009 population and housing census. A cross-sectional survey research design was used. The area had 14 sub locations, of which 4 were in peri urban while 10 were in a rural setup. Out of the total 9593 households in the area, 3465 and 6128 households were located in peri urban and rural areas respectively; this represented 36% and 64% of the households. It was on that basis of household distribution that 40 questionnaires were administered to peri urban zone and 70 questionnaires to rural zone proportionately. In total the sample size was 110 households, it was obtained according to Israel (1992). The sampling design was multi stage, two sub locations were randomly selected in both rural and peri urban areas. Then two villages were randomly selected from each sub location. The final stage was a simple random sampling from each village to proportionately select the respondents according to population distribution in the villages which were the final sampling units. Data was collected through observations, photography and using structured questionnaires. These were then analyzed accordingly using Statistical Package for Social Sciences (SPSS). Simple descriptive statistics mainly means and percentages were used to present data.
About 84.5% of the respondents earned their livelihoods from mixed farming (Table 1).
|
Table 1. Distribution of respondents by livelihood sources |
|||
|
Livelihood |
Rural
|
Peri urban
|
Overall |
|
Livestock |
1.4% |
2.5% |
1.85% |
|
Crop cultivation |
20% |
2.5% |
13.6% |
|
Mixed farming |
78.6% |
95% |
84.5% |
This finding is similar to GOK (2013) that most of the farmers in the area engage in mixed farming. Monthly incomes from mixed farming were found to be highest (USD 54) compared to incomes from either livestock farming (USD 34) or crop (USD 37.4) farming singly (Table 2).
|
Table 2. Average monthly incomes for the respondents in USD |
|||
|
Variable |
Rural
|
Peri urban
|
Overall
|
|
Chicken farming |
5.55 |
6.32 |
5.94 |
|
Livestock income |
18.9 |
36.5 |
34 |
|
Crop income |
38.7 |
31.6 |
37.4 |
|
Mixed income |
53.4 |
55.5 |
54 |
|
Employment income |
89.5 |
120 |
118 |
|
Overall mean income |
41.4 |
50 |
49.8 |
|
Chicken contribution to overall mean income |
13.4% |
12.6% |
11.9% |
|
1USD=Ksh 95 |
|||
Those in formal employment had higher monthly incomes (USD 118) than those relying on agricultural activities. Employment income had a significant positive correlation p<0.05, r=0.64 on how farmers acquired initial poultry flocks, which was mainly through purchase. Income from chicken farming constituted 12% of overall mean household income in the study area. Mean household incomes were USD 41.4, USD 50, USD 49.8 for rural, peri urban and study area respectively.
Majority (99%) of respondents in the study area reared chicken. About 72.7% reared poultry for income and subsistence, 11.8% for subsistence and 15.5% for income generation. In terms of experience, only 2.86% of respondents in rural areas had reared poultry for less than five years compared to 27.5% in peri urban areas (Table 3).
|
Table 3. Summary of poultry flock dynamics |
||||
|
Variable |
Choice |
Rural |
Peri urban |
Overall |
|
Type of poultry kept |
Chicken only |
98.6% |
100% |
99.1% |
|
|
Chicken +Ducks |
1.4% |
0% |
0.9% |
|
Purpose of keeping poultry |
Subsistence |
4.3% |
25% |
11.8% |
|
|
Income |
22.9% |
2.5% |
15.5% |
|
|
Subsistence and income |
72.9% |
72.5% |
72.7% |
|
Duration of keeping poultry |
≤ 5 years |
2.86% |
27.5% |
11.8% |
|
|
> 5 years |
97.1% |
72.5% |
88.2% |
|
Method of poultry acquisition |
Purchase |
95.7% |
90% |
93.6% |
|
|
Gift |
1.4% |
10% |
4.5% |
|
|
Inheritance |
2.9% |
0% |
1.8% |
|
Breed of poultry |
Indigenous |
100% |
100% |
100% |
|
Production system |
Free range |
100% |
90% |
96.4 |
|
|
Small scale confined |
0% |
10% |
3.6% |
|
Labour source |
Nuclear family |
82.9% |
82.5% |
82.7% |
|
|
Extended family |
17.1% |
17.5% |
17.3% |
The study found that 82.7% utilised nuclear family labour, this agrees with studies done in Machakos County, Kenya by Nduthu (2015) who found out that 82% of households were depending on family labour as it was cheap. The main method of initial poultry acquisition was through purchase (93.6%). This agrees with other studies done elsewhere by Ochieng et al (2013) who found that the main method of initial stock acquisition was through purchase by 74% of farmers in western Kenya.
Other livestock species kept by farmers in the study area were goats, cattle, donkey and sheep. Rural areas had more livestock than peri urban as shown in Figure 1.
|
| Figure 1. Distribution of livestock in the study area |
Chicken and other livestock kept in the area were converted into Tropical Livestock Units (TLU) and compared to determine the contribution of chicken to overall TLU as shown in Table 4. Chicken were found to contribute 4.18% and 26.88% of total TLU in rural and periurban areas respectively. The finding than peri urban site had more chicken TLU can be explained by the fact that they had higher adoption rates of poultry management technologies (Refer Table 6) which have been shown to improve productivity (Teklewold et al 2006; Ochieng et al 2013) in addition to the availability of free ranging land, cheap labour and less distances to water sources in the area.
|
Table 4. Distribution of livestock in TLU in the study area |
||||||
|
Livestock Type |
Stratum |
|||||
|
Rural (n=70) |
Peri urban (n=40) |
Overall (n=110) |
||||
|
Number |
Total TLU |
Number |
Total TLU |
Number |
Total TLU |
|
|
Cattle |
725 |
363(42.2) |
25 |
12.5(37.9) |
750 |
375(42)* |
|
Goats |
1855 |
186(21.6) |
100 |
10(30.3) |
1955 |
196(21.9) |
|
Sheep |
251 |
25.1(2.92) |
- |
- |
251 |
25.1(2.81) |
|
Donkey |
313 |
250(29.1) |
2 |
1.6(4.85) |
315 |
252(28.2) |
|
Chicken |
3592 |
35.9(4.18) |
886 |
8.86(26.9) |
4478 |
44.8(5.02) |
|
Ducks/doves |
6 |
0.18(0) |
- |
- |
6 |
0.18(0) |
|
Total |
- |
860(100) |
- |
33(100) |
- |
893(100) |
|
*Figures in brackets are in percentage. TLU values used: Cattle 0.5, Goats/sheep 0.1, Donkey 0.8, |
||||||
Chicken were found to contribute 5.02% of total livestock TLU in the study area. Using the KNBS 2009 census results, chicken represented 1.88% of total livestock TLU in Kitui County, while nationally chicken represented 1.74% of total livestock TLU.
Factors influencing chicken rearing were categorised into opportunities and challenges as shown in Table 5. Labour, water and space availability were the main opportunities for chicken rearing in both areas. Diseases, theft, predation and high cost of vaccines/drugs were the main challenges in both areas.
|
Table 5. Opportunities and challenges of chicken rearing in rural and peri urban areas |
||||
|
Variable |
Rural (n=70) |
Peri urban (n=40) |
||
|
Opportunity (%) |
Challenge (%) |
Opportunity (%) |
Challenge (%) |
|
|
Feed |
47.2 |
52.8 |
65 |
35 |
|
Disease |
0 |
100 |
2.5 |
97.5 |
|
Theft |
14.3 |
85.7 |
20 |
80 |
|
Skills |
1.4 |
98.6 |
72.5 |
27.5 |
|
Vet/extension skills |
2.8 |
97.1 |
62.5 |
37.5 |
|
Inputs |
12.9 |
87.2 |
57.5 |
42.5 |
|
Technology availability |
8.6 |
91.5 |
67.5 |
32.5 |
|
Credit availability |
22.9 |
77.1 |
60 |
40 |
|
Quality breed availability |
15.7 |
84.3 |
37.5 |
62.5 |
|
Predators |
11.4 |
88.6 |
2.5 |
97.5 |
|
Climate effects |
52.9 |
47.1 |
20 |
80 |
|
Markets |
50 |
50 |
62.5 |
37.5 |
|
Selling prices |
60 |
40 |
75 |
25 |
|
Water availability |
95.7 |
4.3 |
92.5 |
7.5 |
|
Labour availability |
97.1 |
2.8 |
92.5 |
7.5 |
|
Drugs/vaccine costs |
1.4 |
98.6 |
20 |
80 |
|
Land/space availability |
91.4 |
8.5 |
85 |
15 |
The finding that diseases were the major challenge agrees with studies by Kyule et al (2014) and Ochieng et al (2013) who report that diseases are the major cause of chicken deaths and discourage farmers from keeping large flocks for fear of losing them during disease incidences. Epiphane and Arne (2012) indicate that unavailability of chicken rearing technologies usually prevents farmers from overcoming traditional chicken farming behaviours thereby unable to increase income and reduce poverty. Unavailability of superior chicken breeds was reported by 84.3% and 62.5% of respondents in rural and periurban areas respectively. Okeno et al (2010) indicates that the improved breeds are important since they possess characteristics of economic importance such as bigger body size, improved growth rate and egg yield, better mothering ability, disease tolerance and improved fertility. Overall there were more challenges in rural areas.
Use of each technology was categorised as; regularly or rarely as shown in Table 6. Overall, the results showed low adoption of all chicken management technologies in the study area especially in rural areas. This indicates a low input-low output production system which is characteristic of free range systems (Bwalya and Kalinda 2014; Ochieng et al 2013).
|
Table 6. Adoption rates (%) of various poultry management technologies |
||||
|
Variable |
Use |
Adoption rates (%) |
||
|
Rural |
Peri urban |
Overall |
||
|
Vaccination practice |
Regularly |
18.5 |
87.5 |
43.6 |
|
|
Rarely |
81.5 |
12.5 |
56.4 |
|
Predator/rodent control practices |
Regularly |
47.2 |
72.5 |
56.4 |
|
|
Rarely |
52.8 |
27.5 |
43.6 |
|
Feed supplementation practices |
Regularly |
1.4 |
80 |
30 |
|
|
Rarely |
98.6 |
20 |
70 |
|
Housing practices |
Regularly |
11.4 |
37.5 |
20.9 |
|
|
Rarely |
88.6 |
62.5 |
79.1 |
|
Brood/hatch practices |
Regularly |
10 |
55 |
26.3 |
|
|
Rarely |
90 |
45 |
73.7 |
|
Improved chick rearing |
Regularly |
1.4 |
5 |
2.7 |
|
|
Rarely |
98.4 |
95 |
97.3 |
|
Adoption of whole package |
Yes |
0 |
0 |
0 |
Only 20.9% of respondents regularly house their chicken. Most of the houses were built using local materials and designed to protect chicken from rodents and predators especially at night as shown in Figures 2 and 3.
 |
 |
|
Figure 2 and 3
are above ground chicken houses as an innovative way used by
farmers to protect chicken. The ladder is removed once chicken are inside to prevent rodents and predators from accessing the house at night . |
|
Overall 30% of respondents regularly supplemented their chicken in the study area. About 80% of respondents regularly supplemented their chicken in peri urban areas compared to 1.4% in rural areas. Most of the supplements were cereal grains thrown on the ground for chicken to feed on during free range within the compound as shown in Figures 4 and 5.
 |
 |
| Figure 4 and 5 are examples of supplementation mainly practiced in the study area using left over’s and mostly thrown on the ground | |
Brooding and hatching were regularly practiced by about 26% of respondents. There was no farmer who adopted the package as a whole. Farzin and Ineke (2011) indicate that hatching is more economical in time and money than artificial incubators while brooding allows chicks to feed without competition from other chicken and stay safe from predators. Technology adoption in chicken rearing can move indigenous chicken production from subsistence to income generation (Epiphane and Arne 2012).
In rural areas, cultural practices, awareness of expected benefits and cost of the technology/service were the only factors considered by over 50% of respondents. In peri urban, only awareness of expected benefits was considered by over 50% of respondents (Figure 6).
Live chicken markets were mainly dominated by middlemen who mainly used hand weighing to estimate weights thereby exploiting farmers; this has a potential to influence farmers into maintaining low input production systems instead of adopting modern chicken production technologies and extension support services (Anders 2008; Danda et al 2010).
 |
| Figure 6. Factors influencing adoption technologies and access to institutional support services. |
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Received 7 January 2016; Accepted 15 April 2016; Published 1 May 2016