Effect of Management Interventions on Productive Performance of Indigenous Chicken in Western Kenya

J Ochieng^1,2, G Owuor¹, B O Bebe³ and D O Ochieng¹

¹Department of Agricultural Economics and Agribusiness Management, Egerton University, Box 536, Egerton, Kenya
jastopheli@yahoo.com
²African Economic Research Consortium (AERC)/CMAAE, Box 62882-00200 Nairobi, Kenya
³Livestock Production Systems Group, Department of Animal Sciences, Egerton University, Box 536, Egerton, Kenya

Abstract

This paper emphasizes the role of management interventions package in productive performance of indigenous chickens in Western Kenya. The management intervention package comprises feed supplementation, housing, chick rearing, brooding and vaccination. The effect was analyzed using log linear regression model which takes the form of Cobb-Douglas production function.

The results indicate that farmers who had adopted full management intervention package as recommended by extension service had higher productive performance than farmers who modified and selectively adopted components of management intervention package. Farm production assets, expenditure on feeds, labour, access to extension, group membership and female gender significantly influenced productivity of indigenous chickens. Therefore, rural farm households should adopt management intervention package as recommended to increase productivity, thereby improving financial and food security in rural areas. The study also recommends the formulation and implementation of pro-poor policies aimed at improving socio-economic conditions of farmers to enable them to fully adopt the recommended management intervention package.

Keywords: Food security, household, management interventions package, productivity

Introduction

In most developing countries, indigenous chickens are kept by households using family labour and occasionally use commercially and locally available feed resources. They are usually kept under scavenging production systems often with very limited application of management interventions to improve flock productivity. Indigenous chickens are of great importance to smallholder farmers in Kenya but they face the challenge of improving productivity of their flock that could benefit them by increasing financial and food security.

This challenge is particularly great in Western Kenya where 80% of the rural households keep indigenous chickens. Indigenous chicken production is characterized by low levels of inputs and outputs (Okitoi et al 2007; Sonaiya et al 1999), with low productivity levels which limit their potential for commercialization. The indigenous chickens are of low commercial exploitation compared to the industrial hybrid poultry because of low productivity. Many farmers in Africa have always ignored the growing preference for meat and eggs from indigenous chickens for their tasty, safe and nutritious qualities. However, consumers are increasingly shifting their preference towards traditionally produced animal products (Upton 2000) which often fetch premium prices relative to the industrial hybrid chickens.

Indigenous chicken enterprise is common among poor rural households as it is better adapted to production circumstances of scavenging systems characterized by continuous exposure to disease incidence, inadequate quantity and quality feeding, poor housing and health care (Guèye 1998; Kitalyi 1998). To achieve increased productivity of indigenous chickens, extension service has continuously disseminated management intervention package to smallholders for mitigating these constraints. However, the majority of smallholder farmers with flock size averaging 10 to 50 chickens hardly realize improved productivity, which could be explained by the manner in which they adopt disseminated management intervention package. The management intervention package designed to improve productivity of indigenous chickens include housing, feed supplementation, vaccination, brooding, and chick rearing (Njue et al 2006). Proper adoption of the management intervention package should improve productivity and enhance commercialization of the indigenous chicken flocks. This paper therefore, intends to give insights on the effect of management intervention package on productivity of indigenous chickens in Western Kenya.

Methodology

Data Collection Approach

 Data for this study was collected through a cross-sectional stratified random sample survey of smallholder households in Rongo and Homabay districts of Western Kenya. The districts are within the Lake Victoria basin and have an estimated 54% of the households living below the poverty level Republic of Kenya (RoK) (2005). The national extension services and Non-governmental organizations (NGOs) have for a long time targeted the two districts for dissemination of management intervention package designed to improve productivity of indigenous chickens flocks (Okitoi et al 2007).

 Smallholder farmers keeping indigenous chickens in Rongo and Homabay districts were the target population. The study applied stratified random sampling by population density and indigenous chicken market prominence, based on local expert knowledge to obtain the sample farmers. In each district, two divisions were selected with one representing low indigenous chicken population density and low markets while the other division represented high indigenous chicken population density and high markets. The sampling frame was obtained from the list of farmers provided by Kenya Poultry Farmers Association (KEPOFA) and Poultry Farmers Associations in the two districts. Application of simple random sampling yielded 30 farmers from each of the four divisions giving a total of 120 respondents.

The study employed farm household’s survey using structured interview schedule and focus group discussions. The data collected included household socio-economic characteristics, management interventions adopted, access to extension services and credit facilities, distance to major market outlet, sources of household income, costs and revenues realized from indigenous chickens flock during 2008 production year.

 Statistical Approach for determinants of productive performance of indigenous chickens

The log linear regression model was employed to evaluate the effect of adopted management intervention package on indigenous chicken productive performance. The regression model takes the log specification because not all the explanatory variables (X_i) are linearly related to the value of output (Y₁) and parameters’ estimates can be interpreted as elasticities. It takes the form of flexible Cobb Douglas Production function. Log linear regression model is a transformed model and assumes that there exist a linear relationship between log dependent variable and log explanatory variable. This transformation into logs allows estimation by traditional OLS procedure where LnY_i is a linear function of logs of regressors, logs of X’s (Gujarati 2003).

LnY₁=µ₀ + µ₁lnX₁ + µ₂lnX₂ + µ₃lnX₃ + µ₄lnX₄ + µ₅lnX₅ + µ_iD_i + µ_cD_c + µ_gD_g+ µ_grD_gr + µ_eD_e + ε

 Where: Ln-Natural logarithm, α₀ –constant term, α₁ –α₅ and α_r ,α_i- parameters to be estimated, Y-Value of output for the year 2008 which comprised values of chicken sold, consumed at household, eggs sold, eggs consumed, given as gifts and values of chickens on farms. X₁-Labour, X₂-Expenses on feed, X₃-Value of production assets (Capital Expenditure), X₄ –Age of the farmer, X₅ – Flock size, D_i- Logical variable for the adopted components of management interventions (1, 2 and 3) obtained from PCA followed by Cluster Analysis (Ochieng 2010) and D_c, D_g, D_gr, D_e– Dummy variable for credit access, group membership, female gender and extension services respectively and ε – Error term (ε independently, normally distributed with zero mean and constant variance- (V_i~N (0, δ²). The tests were done to determine whether explanatory variables were correlated based on variance inflation factor (VIF) or tolerance of variables (TOV) (Greene 2003; Gujarati 2003).

Results and Discussion

 In the log linear regression models both dependent and independent variables have been transformed into logs thus Ordinary Least Squares (OLS) estimation procedure is appropriate. The assumption is that there exist a linear relationship between log of dependent variable and independent variables. Socio-economic characteristics were included in the model on assumption that they influence indigenous chicken productive performance. The estimated coefficients of value of production assets, cost of feed, labour, credit, flock size, group membership, gender and adopted management interventions were positive and negative for age.

The coefficient for production assets was 0.177 and significant (P<.01), indicating that assets such as chicken house, feed troughs, water troughs and brooders were important for production of indigenous chickens. Hence, farmers with relatively higher number of these assets had higher productivity compared to farmers with few assets. Chicken production assets are used to protect flock from bad weather, reduce disease infection, watering and feeding, all for improved productivity.

The coefficient for value of feed (0.299) was positive and significant (P<.05) indicating that 1% increase in feed input resulted in 29.8% increase in value of output. This means that feeding supplementation was an important contributor to chicken productivity because of protein and energy requirements for egg and meat production. Limited feed resources restrict the potential productivity of indigenous chickens (Mekonnen 2007). According to Sonaiya (2000), energy is the first limiting nutrient in the feed available as it contains a lot of crude fiber. This may be reason why energy supplements may increase production of indigenous chicken significantly. Therefore, income from indigenous chicken can be increased by improving the feed in quantity and quality.

Labour contributed positively to chicken productivity since its coefficient was 0.344 and statistically significant (P<.01). Labour activities involved giving feeds, repairing chicken production assets, cleaning chicken house, preparing brooders and ensuring that all the flock return to the house in the evening.

The group membership (0.714) was positive and highly significant (P<.05), indicating that there was a significant difference in indigenous chicken productivity between the group and non-group members. The difference can be attributed to easy access to credit, extension, training and group based vaccination by farmers in groups. Groups can also be entry points for Newcastle disease (NCD) control programmes. Ndegwa et al (2000) found groups to be effective, especially in pooling external inputs and disseminating information.

The coefficient of female gender was positive and highly significant (P<.01), indicating that there was significant difference between female and male farmers. Females dominated the enterprises and had higher productivity than males. This may be because more (75.8%) were involved in indigenous chicken production and they stay more at home caring for indigenous chickens (Ochieng 2010). The implication is that women generate more income from indigenous chickens than men. Thus, strategies for improving indigenous chicken productivity should consider women as the entry point. Alubi and Aruna (2006) reported similar findings on productivity of chicken among women headed households. These findings are further affirmed by Okitoi et al (2007) in their study in Siaya and Vihiga districts of Kenya.

The estimated coefficient of adopted components of management interventions package was positive and highly significant (P<.05), indicating that there was a significant difference in indigenous chicken productivity between farmers selectively adopting components of management interventions package and full package adopters. The smallholder farmers intensifying their production by using full package had higher productivity. The value of output increases as farmers increased adoption of components of management intervention package to full package comprising feeding supplementation, poultry house, vaccination, brooding and chick rearing. In Nigeria, Alabi and Aruna (2006) found that productivity increases as innovations related to improved management are adopted into the production system. About 98% of farmers were giving feeding supplements, with few able to vaccinate and build chicken house for their flock. The differences in chicken productivity could also be attributed to access to veterinary services and general improved management of the flock among full package adopters.

Intensification of indigenous chicken production requires large amounts of inputs, thus making many farmers to shy away from adopting management interventions package. However, efficient use of management interventions with limited wastage of resources would lead to higher productivity of indigenous chickens. KARI (2006) also reported that indigenous chickens were profitable if managed well and common diseases are controlled to improve survival rate of chicks by at least 30% while improved feeding, housing and disease control increases survival rate by up to 80%.The estimated coefficient of farmer’s age was negative (-0.567) and statistically insignificant (P>.05). This shows that productivity declines with increase in farmer’s age. In the present study, it is apparent that the conventional assumption that age has a positive impact on chicken productivity due to increase in experience does not hold. In the study area, few younger farmers who adopted the management intervention packages realized higher productive performance. The coefficient of extension services (0.439) was positive and statistically significant (P<0.1) which indicates that there was high productivity among farmers who had access to extension services. Inability to access extension services is an indication of unfavorable government policies (Adebayo et al 2005). According to Farooq et al (2000), accessibility to extension service significantly improves free range indigenous chicken production systems.

The results on credit were positive but insignificant (P>0.1). Nonetheless, it indicates that access to credit plays an important role in improving indigenous chicken productivity. The fungibility of credit allows the borrowers to meet array of needs ranging from medical, school fees, food and social emergencies like funerals and accidents, leading to limited purchase of inputs for indigenous chicken production.

The mean VIF was used to test for multi-collinearity in explanatory variables. The mean VIF of 1.44 was below the acceptable range of 10 (Gujarati 2003). The F-test of 8.41 was significant at 95% confidence interval, further implying that management intervention package influenced productivity. Thus, there exists a significant difference in indigenous chicken productivity between farmers using full package and those using some components of management intervention package.

Conclusion and Recommendations

• Adoption of full management intervention package has higher influence on productive performance of indigenous chickens. Farmers who had adopted fully management interventions package had higher productivity than farmers who modified and selectively adopted components of management intervention package. The key determinants of indigenous chicken productivity include available production assets, expenditure on feeds (local and commercial feeds), labour input, access to credit facilities and extension services, group membership and management interventions adopted. Therefore, rural farm households should adopt management intervention package as recommended by the extension service in order to increase productivity, thereby improving financial and food security in rural areas. The policy-makers and stakeholders in this industry should design programs aimed at increasing farmers’ access to inputs, extension service and credit services. Formation and participation in groups aimed at enhancing social capital may pay off in terms of facilitating access to production resources for increasing productivity of indigenous chicken in rural areas.

Acknowledgements

The authors are grateful for financial support from Collaborative Masters in Agricultural and Applied Economics (CMAAE) Secretariat and African Economic Research Consortium (AERC).

References

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Received 20 September 2010; Accepted 2 April 2011; Published 1 May 2011

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