Livestock Research for Rural Development 28 (4) 2016 Guide for preparation of papers LRRD Newsletter

Citation of this paper

Prospects for commercialization of indigenous chickens in Makoni District, Zimbabwe

D Maumburudze1, J Mutambara, P Mugabe and H Manyumwa1

University of Zimbabwe, Department of Agricultural Economics and Extension, Box MP 167, Mt Pleasant, Harare, Zimbabwe.
davyymau@gmail.com
1 University of Zimbabwe, Department of Animal Science, Box MP 167, Mt Pleasant, Harare, Zimbabwe.

Abstract

Enhancing the production and productivity of indigenous chickens can accelerate development of the rural social economy as indigenous chickens are an affordable source of protein as well as a viable income earner. However, there are few success stories of the commercialization of indigenous chickens in Africa south of the Sahara as compared to Asia and Latin America. This study therefore investigates the prospects for boosting production of indigenous chickens in Makoni District of Zimbabwe. It does so by assessing the constraints to commercialization and identifying the factors that significantly explain variation in indigenous chicken output during the dry season. A triangulation of descriptive and inferential methods is used to come up with possible answers to the commercialization conundrum as well suggestive strategies for increased food, nutrition and income security through indigenous chicken commercialization.

The results show that while respondents (rural farmers) indicated that the indigenous chicken enterprise was the most preferable to commercialize, only 20% of the respondents produced beyond subsistence levels. To overcome the constraints to commercialization, the study finds that supplementing feeds and medication can assist by reducing mortality rates and enhancing productivity. However, by employing a variety of analytical methods to the research problem, the study results also suggest that feed and medication supplementary strategies should not be over emphasized but rather a holistic approach which combines these with sustainable animal husbandry practices, for instance healthy and hazard-free housing, as well as sufficient price and market incentives, is required to ensure successful commercialization of indigenous chickens in rural areas such as Makoni District in Zimbabwe.

Key words: biosecurity, poultry production, rural economy, sustainable livelihoods


Introduction

This study focuses on the production of indigenous chickens by rural farmers in Makoni District in Zimbabwe for both local and external markets. Commercialization is increasingly gaining recognition in the smallholder agriculture and rural development discourse. Rukuni et al (2006) define commercialization as a transition from mostly subsistence agriculture (based on production for own consumption) to production for the market, i.e. both local and export markets. Commercialization implies managing or exploiting resources in a way to make profit. However, for simplicity this study takes commercialization as the ability to produce quantities of indigenous chickens beyond a certain threshold value in a particular time of the year.

Commercialization of indigenous chickens, like any other poultry enterprise, faces threats from diseases. Disease is any condition that interferes with the normal functioning of the living cells, tissues, organs or systems of the body (Fossum 2013). Some causes of diseases in poultry include: consumption of toxic substances e.g. poisons; physical damage e.g. from environmental extremes and/or injury; parasitic infestations (both external and internal) such as lice and worms; and, infectious diseases caused by micro-organisms e.g. bacteria and viruses. Vaccination is a mitigation response to disease which entails triggering the birds’ immune system to produce antibodies to fight infection. Biosecurity is the set of practices designed to keep disease from a farm and to prevent the transmission of disease from an infected farm to neighbouring farms (Nordmann 2010; Meyerson & Reaser 2002). An inadequate biosecurity program increases the risk of disease, which may result in high mortality and contribute to loss of farm income.

Commercialization of free range poultry production is fundamental for overcoming poverty and food insecurity in Africa south of the Sahara where almost 80% of livelihoods are agro-reliant and the majority of the world’s poor and food insecure reside (AFDB 2010; UN 2014). Indigenous poultry commercialization in rural households has potential economic and nutritional benefits, being a source of additional income as well as household protein.

Poultry is amongst the world’s major and fastest growing sources of proteins, and chickens are the most numerous birds in the world. Recent studies show that world poultry populations have more than tripled, and commercial production of exotic chicken breeds is dominating poultry in many countries, particularly in Zimbabwe (Thornton 2010). Communal poultry production in sub-Saharan African countries however, is dominated by indigenous chickens though they are seemingly being replaced by the foreign breeds. Nearly all communal households in sub-Saharan Africa depend on crop production for much of their livelihoods, and most of them usually rear indigenous chickens which they usually use to supplement their crop produce earnings. This study is born out of the need to ascertain whether there are any prospects for commercializing indigenous poultry production in rural areas, with a particular focus on Zimbabwe.

Multiple economic challenges beleaguered Zimbabwe over the decades 1998 to 2008. This undermined the living standards of many rural communities largely driven by the low capacity utilization and high unemployment levels in industry (RBZ 2014). Fertilizer and seed shortages, a growing population, exposed to the vagaries of climate change and degrading land resources impacted on the livelihoods of rural households especially those that solely depend on producing crops as a source of livelihoods.

An advanced understanding of social and economic factors of the indigenous chicken production system is required for its transformation into an economically rewarding enterprise for rural households (Kitalyi 1997). Further, the socio-economic values of local poultry should be recognized, but an investigation to identify and evaluate problems, and plan appropriate intervention for development is paramount (Sonaiya 2000). Commercialization of indigenous chickens in the rural areas can be viewed as step towards more sustainable and resilient agriculture and food systems as it has lower input costs (Magothe et al 2012). However, it has been seemingly difficult for communal farmers in African to commercialize free range chickens, with problems such as low quality, high mortality rates and minimal participation in higher parts of the value chain (Justus et al 2013).

Indigenous free-range species (Gallus Domesticus), remain predominant in rural Africa despite the introduction of exotic types, because farmers have not been able to acquire high quality inputs that exotic breeds require. Hence, rural households rely on indigenous free range chickens which, usually have no regular health control program and often may not require complex shelter. Indigenous chickens also play a pivotal role in rural household food and nutrition security. While the commercialization of free range chickens has proven successful in Bangladesh and in South East Asia, there are no apparent improvements of the enterprise in sub Saharan Africa at present (FAO 2005; Kondombo 2005). This calls for research that examines the constraints to commercialization of indigenous chickens in sub Saharan Africa, as this spur the development and transformation of rural communities.


Materials and methods

Study site

Field work was conducted in Ward 16 of Makoni District in Manicaland Province of Zimbabwe. The area is located within 15 km radius, south west of Rusape town, and is flanked by two major roads (Wedza road and Mutare road) both emanating from Rusape town. There are two growth centers in the area namely; Tsanzaguru and Chiware. The area falls within Agro-ecological Region II b of Zimbabwe, with an annual rainfall range of 850 – 1000 mm and average annual temperature range of 12-24 C. Site selection was based on the availability of indigenous chickens reared under the free-range system, the proximity of the area to formal markets particularly, Rusape town. The area also has good major and minor roads that make it more accessible than other rural areas.

Sampling strategy

Ward 16 of Makoni District consists of 26 communal villages. Cluster sampling technique was used to randomly select ten villages namely: Munyengwa, Muziti, Nezambe, Kanyangira, Mavhawani, Tekede, Manyeku, Chipomho, Gunda and Muvhimwa. Thus, the population elements, i.e. communal farmers in Makoni District were first divided into clusters, i.e. villages and then farmers were randomly selected from the clusters to constitute the sample. Cluster sampling is cost effective, especially for a population that is spread over a wide geographic area. The sampling technique is also ideal for this particular study given that the sampling frame was not available, making it impossible to conduct simple random sampling.

Data collection

Primary data were collected through a communal farmers’ survey. The survey collected data such as: cost of producing the chickens; the monetary value of each chicken produced and sold; diseases infecting the chicks and the percentage of the chickens that is consumed by the household; income from sales; selection parameters for brooding indigenous chickens; and, constraints to commercialization of indigenous chickens among other issues.

The data collected were for the dry season of the year, i.e. from July to November. This is because the majority of the farmers supplement feeds to free range chickens especially in the dry seasons of the year because that is when there is little for the chickens to scavenge. (Kondombo 2005) asserts that feed supplements of free range chickens in the sub Saharan Africa region usually decreases or even disappears during the wet season. Semi structured questionnaires were employed to collect the data during the survey. These were used to obtain much required information on issues which are directly or indirectly associated with indigenous chicken production. Ethical considerations were made in collecting the data with the principles of informed consent and voluntary participation upheld.

Assumptions of the study

The research assumed that each poultry farmer makes sales at a given price. The biosphere of the study area is also assumed to be static. The value of the chicken consumed was assumed to be equal to the value of the chicken sold, hence quantity of chickens produced regardless whether they are sold or consumed is used as a proxy for commercialization. Hence farmers who sold (or consumed) more than 49 indigenous chickens were taken to be commercializing them. Costs of labour and housing are not included in the analysis as these are assumed not to vary sufficiently from household to household.

Data Analysis

Farmers’ survey data were analysed using Software Package for Social Scientists (SPSS). Determinants of indigenous chicken production were ranked and analysed using Multiple Response frequencies and Multiple Linear regression model. Descriptive statistics were used to describe the basic features of the data in the study as they render simple summaries about the sample and measures. Each descriptive statistic reduces vast data into a simpler summary, for example; a frequencies table of the different constraints to commercialization shows the percentage of respondents encountering a particular constraint.

The Independent-Samples t-Test, a well-known statistical hypothesis test, was employed to ascertain whether the mean number of farmers operating at subsistence level and the mean number of farmers operating at commercial level was significantly different. In order to use the test, it was assumed that observations for the two groups of farmers were independent random samples that are normally distributed obtained from populations with the same variance.

The Multiple Response Frequencies method was used to analyse questions with multiple responses. The method is a set of procedures which generates frequency tables for sets of multiple response questions. Tabulation of the multiple categories’ set excludes variable cases with missing values. Usually, a case becomes missing only when no one of its components is important within the given range. For example an enumerator asks which of two livestock enterprises, indigenous chicken or beef is preferred by farmers to be commercialized. After defining a multiple category set, the values are tabulated by adding the same codes in the elementary variables together. The counts and percentages (of cases and responses) for the two enterprises were displayed in a single table of frequencies.

The model assumes the importance of counts and percentages as they essentially describe information from any distribution. Merit for using Multiple Response Frequencies model is that, the total responses’ percentage represented by each service is reported by the Percent column, as this is not easily obtainable from individual frequency tables.

Multiple Linear Regression model

The multiple linear regression model was used to analyse the factors affecting the output of the indigenous chicken enterprise. A linear relationship was assumed between the dependent variable, output of indigenous chickens and explanatory variables. The expected a priori function is as below;

Y= ∞+β1X1 + β2X2+…..+ β11X11+μ

Where Y is the criterion variable, and it represents output per enterprise, i.e. number of birds sold or consumed. The explanatory variables XXis are: X1 (supplementary feed costs), X2 (vaccination/medication), X3 (selling price of birds), X4 (farm size), X 5 (disinfection), X6 (age of the producer), X7 (mortality), X8 (education level), X9 (experience by the producer), X10 (credit facility), and X11 (extension and training). is are the coefficients of given variables, and μ is the error term and it represents the unexplained variation in the dependent variable.

Table 1 shows an a priori expectation of the factors that explain variation in the output of indigenous chickens, i.e. factors that determine the commercialization of indigenous chickens by smallholder-communal farmers. The table also shows the expected relationship between each elementary variable and the output and the explanations to support the presumed relationship.

Y= ∞+β1X1 + β2X2+…..+ β11X11+μ

Table 1. A priori analysis for the determinants of commercialization of indigenous chickens in Makoni District, Zimbabwe

Variable

Expected effect

Explanation

Education level

+ve

As the farmer’s level of education increases he/she tends to employ better management practices.

Producer’s experience

+ve

More years spend in the industry usually bring better understanding about the industry.

Access to credit facilities

+ve

Enables the free range producer to have increased his/her scale of production.

Age of the producer

-ve

Senescence decreases the human activity, i.e. as the farmer ages he/she becomes less energetic.

Mortality rate

-ve

Decreases the output, and also de-motivates the farmer to produce more.

Disinfection

+ve

Reduces the chances of attacks by diseases and parasites.

Farm size

+ve

Provides large space for the chickens to scavenge, without encroaching into neighbours’ premises. Also, implies more supplementary feed for the chickens

Selling price

+ve

Increased bird price implies increased revenue.

Vaccination/medication

+ve

Vaccination decreases the incidence of disease and medication reduces mortality.

Supplementary feed costs

-ve

Increase variable costs

Training and extension

+ve

Improves farmer management skills


Results

Level of production of indigenous chickens

While the majority of the respondents in the survey (67%) indicated that they would prefer to commercialize indigenous chickens among other livestock enterprises, the survey also showed that only 20% of farmers actually commercialized their indigenous chicken enterprises, i.e. producing over 50 chickens in the dry period of July to November 2012. Table 2 provides descriptive statistics on commercialization preferences of farmers involved in the survey. The data reveals that 21.7% and 8.30% of the total respondents prefer to commercialize their cattle and goat enterprises respectively. 66.7% prefer commercializing their indigenous chicken enterprises, and the remaining 3.30% prefer to commercialize pigs. This shows that more than half of the farmers prefer to commercialize indigenous chickens as compared to cattle, goats and/or pigs, with only a very small percentage preferring commercializing the pig enterprise.

Table 2. Percentage of farmers according to their commercialization preference

Livestock enterprise preferred to be commercialized

Proportion of respondents (%)

Cattle

21.7

Goats

8.30

Indigenous chickens

66.7

Pigs

3.30

TOTAL

100

While the statistics in Table 1 show that most respondent preferred to commercialize indigenous chickens, only 20% of the indigenous chicken producers actually commercialized them. Commercialization has been defined as producing a total output of more than 49 indigenous chickens, over the dry season of the year between July and November. The majority of indigenous chicken producers were not commercializing. This is illustrated by figure 1.

Figure 1. Percentage of indigenous chicken producers who are commercializing and those who are not commercializing

 While respondents showed a strong preference for commercializing indigenous chickens, only a minority of them actually commercialized indigenous chicken production. Average production levels remain below the commercialization benchmark of 50 indigenous chickens in the dry season. To further investigate this, inferential statistics, particularly the independent samples t-test and multiple linear regression were applied to compare the socioeconomic characteristics of commercial and non-commercial farmers as well as to assess the relative importance of the determinants of commercialization among farmers.

Socio-economic characteristics of indigenous chicken producers

Independent samples t-test of comparing means was used to test the difference in means of variables that include: demographic characteristics (measured by household size, average age of farmer, education level of farmer); supplementing feed, medicines or water (measured by the respective average cost and frequency of water provision); benefits realized from indigenous chickens (measured by birds consumed, income earned from birds, and price at which birds are sold); and mortality rate. Level of operation, i.e. commercial or not commercial is the variable that was used to group the data as shown in Table 3. The test was carried out at 5% level of significance, and equal variances were assumed.

In terms of the difference in demographic characteristics between commercial and non-commercial farmers, age of farmer and education level differed significantly with commercial indigenous chicken producers being older and having spent less time in formal education as compared to those who are not commercial. Average household size however did not differ between commercial and non-commercial farmers.

The frequency of providing water significantly differed between those farmers who are commercial and those who are not. Other supplementary activities such as the average amount of money spent on medicines and commercial feed differed though not significantly between commercial and non-commercial indigenous chicken producers.

In terms of the difference in both the nutritional and economic benefits from indigenous chickens between commercial and non-commercial farmers there was no significant difference. Particularly, the number of birds consumed, the average income from selling birds and the average price at which the birds are sold did not differ significantly.

However, the mortality rate differed significantly, with that of commercial producers being lower than that of non-commercial producers.

Table 3. Independent samples t-test results for socio-economic characteristics of commercial and non-commercial indigenous chicken producers

Variable

Commercial

Not
commercial

Significance
level

Household characteristics

Age of farmer (years)

53.9

50.1

**

Average number of years spent in formal education

9.67

9.88

***

Average household size

6.50

5.19

Supplements

Average amount of money spent on modern medicines (US$)

14.0

5.00

Average amount of money spent on commercial feeds (US$)

86.0

19.0

Average frequency of providing water per day

2.00

1.85

**

Benefits from indigenous chickens

Average number of birds consumed

17.0

13.0

Average income generated from indigenous chickens (US$)

311

104

Average price at which birds are sold (US$)

5.00

6.00

Mortality rate (percentage)

9.32

29.9

***

*p<0.1, **p<0.05, ***p<0.01

Determinants of commercial indigenous chicken production

The survey data were analysed using Multiple Response frequencies, and using the Multiple Linear regression model to assess the determinants of commercial indigenous chicken production. The Multiple Response frequencies method was used to find out the intensity of constraints to commercially produce indigenous chickens, as given by the respondents. The results are shown in Table 4. The results show that 26.9% of the total respondents indicated that the lack of access to modern medicines prevented commercialization of their indigenous chicken enterprises. 17.9% indicated that it is the lack of access to commercial feeds, and 15.2% indicated that inadequate experience was the hindrance to commercializing their indigenous chicken enterprises. Other constraints highlighted include poor pricing system (cited by 11.0% of respondents), aging or senescence (by 10.3%), lack of access to credit (by 9.00%), theft (by 6.90%) and lack of training and extension on indigenous chickens (cited by 2.80% of respondents).

Table 4. Frequencies of free-range chicken producers facing a particular constraint

Constraint

Number of responses

Percent ( %)

Ranking

Lack of access to modern medicines

39

26.9

1

Lack of access to commercial feeds

26

17.9

2

Inappropriate experience

22

15.2

3

Poor pricing system

16

11.0

4

Ageing

15

10.3

5

Lack of access to credit facilities

13

9.00

6

High mortalities

10

6.90

7

Inadequate training and extension on indigenous chicken

4

2.80

8

Total

145

100

The constraints were ranked order from the most important, i.e. lack of access to modern medicines and lack of training and extension on rearing indigenous chickens being the least important.

The Multiple Response frequencies analysis was coupled with Multiple Linear Regression analysis in order to investigate the nature of the relationship between commercialization of indigenous chickens and various explanatory variables. The backward method was used to run the regression analysis. The backward regression method removes variables which are not important until the model is at its best. The dependent variable was number of indigenous chickens produced which is a proxy for commercialization. Major explanatory variables were medication, supplementary feeding and mortality.

Table 5. Model Summary

R

R Square

Adjusted R Square

Durbin Watson

0.95

0.91

0.89

1.94

Multiple Linear Regression coefficients

Table 6 summarizes the Multiple Linear Regression results showing that economic factors such as supplement feeds and medication costs, price per bird and access to credit; biophysical factors such as mortality rate; and, experience significantly explain the degree of commercialization.

There is a positive relationship between commercializing and the cost of supplement feeds and medication. This relationship is statistically significant at 1% level. The degree of commercialization is also positively related with the age of the farmer and the relationship is significant at the 5% level.

The degree of commercialization is negatively related with the price per bird, mortality rate, access to credit and production experience. The relationship between degree of commercialization and price per bird as well as with production experience is statistically significant at 1%. The relationship between degree of commercialization and access to credit is significant at 5%, while that with mortality is significant at 10%.

Table 6. Multiple Linear Regression coefficients

Symbol

B
Coefficient

Part
Correlation

Significance
level

(Constant)

55.3

***

Supplement feeds’ cost

X1

0.37

0.51

***

Price per bird

X3

-4.74

-0.17

***

Training and extension

X11

-5.17

-0.05

Percent mortality rate

X7

-0.14

-0.09

*

Access to credit

X10

-7.60

-0.12

**

Medication

X2

0.89

0.21

***

Disinfection

X5

-0.61

-0.06

Production experience

X9

-0.39

-0.13

***

Age of the farmer

X6

0.25

0.11

**

Education

X8

-0.58

-0.07

Dependent variable; output (number of birds sold and/or consumed during the entire season).
*p<0.1, **p<0.05, ***p<0.01

Relative importance of explanatory variables

The part correlations given in table 6 can be used to arrange the explanatory variables in order of their relative importance. Similarly, the Multiple Response frequencies were used to rank the responses of the farmers on the constraints to commercialization. Table 7 shows a comparison of the results from the two analyses. From the Multiple Response frequencies, the constraint for the majority of farmers was lack of modern medicines, followed by lack of access to modern feeds, inadequate producer experience, poor pricing system, aging (10.3%), lack access to credit facilities, high chicken mortalities and lastly, lack of training and extension on indigenous chickens.

From the Multiple Linear Regression analysis, supplementary feeds had the greatest explanatory power as evidenced by highest absolute value of the part correlation of 0.51. This is then followed by lack of access to modern medicines with a part correlation of 0.21, price per bird (0.17), producer experience (0.13), access to credit facilities (0.12), producer age (0.11), and mortality rate (0.09).

However, in both methods, access to modern medicines, supplementary feeds, producer experience and price per bird were among the top four factors affecting commercialization, while and training and extension ranked the least important in both analyses.

Table 7. Ranking of factors constraining commercialization of indigenous chickens

Multiple response frequencies results

Multiple linear regression results

Score %

Rank

Score %

Rank

Modern medicines

26.9

1

20.7

2

Supplementary feed

17.9

2

51.0

1

Producer experience

15.2

3

12.9

4

Price per bird

11.0

4

16.7

3

Farmer’s age

10.3

5

11.4

6

Access to credit facilities

9.00

6

11.5

5

Mortality rate

6.90

7

8.50

7

Training and Extension

2.80

8

5.40

8*

* The variable has been ranked although it is not significant at 10% level in the Multiple Linear Regression analysis


Discussion

Socio-economic characteristics of indigenous chicken producers

The results displayed in table 3 showed that there is significant difference in age of farmer, education level, frequency of providing water and mortality rate between commercial and non-commercial indigenous chicken producers. The higher mortality rate among subsistence producers shows underlying differences in animal husbandry and management practices between the commercial and non-commercial producers.

Differences in supplementary feed and medication

Since the average amount spent on medication does not differ significantly between the two groups of producers, it may be misleading to attribute the mortality differences to modern medicines. This calls for a need to recognize other factors that impact on productivity and mortality of free range chickens which may include the conditions of the housing of the birds, e.g. in terms of safety from predators. Kondombo 2005 asserts that a high mortality of indigenous chickens is observed due to unfavourable environmental conditions in relation with housing and diseases. There is still room to further understand the causes of mortality in indigenous chicken production in rural areas.

Differences in water supply

nother interesting difference between the commercial and non-commercial producers is the frequency at which additional water is provided to the chickens. Commercial producers provided additional water more frequently than subsistence producers possibly enhancing productivity. Water plays an essential role in digestion of feed by the chicken. Hence, water and food consumption rates can be perceived as interdependent leading to higher output (i.e. number of birds produced per time period).

Benefits from indigenous chicken commercialization

Additionally, the income generated from selling indigenous chickens, the selling price per bird as well the quantity of indigenous chickens consumed did not significantly vary between the commercial and subsistence farmers. This reveals some critical and marketing and agribusiness capacity gaps. Commercial indigenous chicken producers need the right capacities to access the best markets and get the best price so that they can maximise profits.

Determinants of commercialization of indigenous chickens
Supplementary feed and medicines

The multiple responses frequencies results showed that farmers perceive lack of modern medicines as the major inhibitor of commercialization. Farmers perceived that modern medicines such as ESB3 and Teramysine are effective in reducing mortalities, than traditional medicines such as aloe vera and sodium carbonate rock (gova). Lack of supplementary feeds was ranked the second after lack of access to modern medicines. The farmers argued that supplementary feeding significantly enhances the growth rate of free range chickens, especially when coupled with the use of modern medicines. While the opinion of farmers should be respected, it is important to note that this opinion is shaped by a variety of factors which may include perceived benefits. The independent samples t-test provided results that differ from the multiple response frequencies, showing that use of modern medicines and supplementary feeds did not differ significantly between commercial and subsistence producers.

The regression analysis showed that there is a positive relationship between supplementary feed costs and that indigenous chicken output. Using part correlations, this is the variable that had the strongest explanatory power. According to Roberts et al 2005, supplementing household food refuse with protein sources improves both survival rate and growth rate in indigenous chickens. While supplementary feeding may be assumed to enhance the growth rate of chickens, the results from other analyses discussed earlier, particularly the independent samples t-test lead us to conservatively attribute commercialization to supplementary feeds. There is a positive relationship between the provision of modern medication and indigenous chicken output as vaccination and modern medication increase the chances of survival of the birds. The incongruence between regression and the group difference analysis is expected because the correlation between variables does not always imply causation.

Age and experience

Multiple response frequencies showed that 15.2% of the farmers believed that inappropriate experiences in indigenous chicken production was the major hindrance to commercialization. Most farmers provide unstandardized fowl-runs for the indigenous chickens, and use poor marketing strategies. Some traditional chicken housing systems had a saddle roof and some were round thatched huts which are usually not large enough, safe enough and/or may have unfavourable hygienic conditions.

From the multiple responses frequencies results it was also observed that 10.3% of respondents mentioned that ageing was the major constraint. However, the independent samples t-test showed that age significantly differed between the two groups of producers, with commercial producers being more aged. Only 2.80% of respondents indicated that they were lacking training and extension on indigenous chickens in order to commercialize indigenous chicken production. Traditional training and extension does not offer adequate support in the area of indigenous chicken commercialization since there is limited documented and applied research in this area.

The regression analysis also shows that producer experience in indigenous chicken production negatively explains variation in output, i.e. the higher the number of years of experience the lower the average output of indigenous chickens. This may unearth the concern that farmers that have had previous negative experience, for instance due to market and price disincentives will produce less indigenous chickens.

Price and market incentives

The market incentives also remain poor for commercialization as 11% of respondents indicated that pricing was poor. This is in line with the independent samples t-test which revealed that the income from selling chickens did not differ significantly between the commercial and subsistence producers.

There is agreement in our analyses based on multiple response frequencies and independent samples t- test that market and price disincentives hinder commercialization of indigenous chickens. Regression results on the other hand show that selling price of birds is inversely related to output, i.e. the lower the price the greater the output of indigenous chickens. A possible explanation to this relationship is the existence of imperfect market conditions or asymmetric market information among indigenous chicken producers which pushes the price realized by commercial producers on the market downwards. Rural households may not fully comprehend or possess the required business acumen to negotiate with traders and middlemen.

The regression analysis introduced another form of market disincentive in the analysis, i.e. access to credit for commercialization. The results showed that there is an inverse relationship between output of indigenous chickens and access to credit facilities. This shows that credit for indigenous chicken commercialization may be diverted to other uses.


Conclusion

The current study shows that there is a significant difference in the socio-economic characteristics of indigenous chicken producers who are commercializing and those who are not, i.e. in terms of; age, education level, and management systems used. Also, the results showed that the bulk of farmers in Makoni District (approximately 80%) are not commercializing their free range chicken enterprises, i.e. they produce less than 50 birds in the dry season between July and November 2012.

Supplementary feed and medication, selling price per bird are related to output of indigenous chickens. However, the use of supplementary feed and medication does not differ significantly between commercial and subsistence farmers though the farmers’ opinion is that inadequate availability of supplementary feeds and modern medicines are the main constraints to commercialization. This suggested the importance of other husbandry and management practices such as housing and security in reducing mortality and increasing productivity. Market and price disincentives such as low prices and unfair negotiations with traders and middlemen were also identified as an important constraint to commercialization.

While it may be helpful to supplement feed and medicines to promote commercialization, this needs to be coupled with proper infrastructural support as well as market development.

Recommendations for producers

Commercialization of indigenous chickens has nutritional and economic benefits when the necessary preconditions have been met. Farmers can realize higher profits from the free range enterprise. Some of these preconditions include healthy environment particularly appropriate housing facilities. Farmers need to strengthen animal husbandry practices to reduce mortality and enhance productivity. Supplementing feed and medicines is encouraged though it should be done in combination with the other factors, particularly regular provision of clean water for the indigenous chickens.

Recommendations to training and extension agents

Training and extension agents are encouraged to employ demand driven and commodity-based approaches to programming where farmers are trained on subjects relevant to their knowledge needs and the market. Sustainable indigenous chicken production is one such area. Such approaches are more focused than broad programmes such as poultry production which may not go into enough detail.

Trainers and extension workers should work hand in glove with veterinary staff in order to control disease in indigenous chickens. Vaccination programmes should be targeted to prevent outbreaks. Trainers ought to emphasize in the benefits of producing indigenous chickens. Training programmes should also include how to maximize productivity by combining natural and supplementary feed.

Recommendations for policy

Indigenous chicken production can be an important tool for poverty alleviation. Policy makers should therefore formulate policies that promote and strengthen the production and marketing of indigenous chickens. Indigenous chickens should be promoted as an integral part of diets and be a part of agriculture training and education curriculum. Policies that reduce price and market disincentives for indigenous chicken commercialization should be put in place.

Recommendations for public private co-operatio

There are also areas for co-operation between the government and the private sector. This may include; input procurement, soft loans, training and extension services, and marketing and product promotion, as well as research and development.


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Received 1 June 2015; Accepted 4 November 2015; Published 1 April 2016

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