Livestock Research for Rural Development 29 (2) 2017 Guide for preparation of papers LRRD Newsletter

Citation of this paper

Characterisation of the phenotypes associated with body growth and egg production in local chickens from three agro-climatic zones of Kenya

P B Aswani, J K Lichoti1, J Masanga, P A Oyier2, S G Maina2, M Makanda, G K Moraa, A E Alakonya, K J Ngeiywa1 and S C Ommeh

Institute for Biotechnology Research, Jomo Kenyatta University of Agriculture and Technology, P O Box 6200-00200, Nairobi Kenya
sommeh@jkuat.ac.ke
1 State Department of livestock, Ministry of Agriculture, Livestock and Fisheries, Kenya
2 Department of Information Technology, Jomo Kenyatta University of Agriculture and Technology, Kenya

Abstract

We aimed to characterize body growth and egg production phenotypes associated with local chickens in Kenya from different ecological zones. Data was collected from a total of 296 chickens spread across three agro-climatic zones: Lamu Archipelago (semi-arid coastal), Mt. Elgon catchment (humid highlands) and Lake Turkana basin (arid pastoral). The analysis of variance showed significant interactions between shank length, body length and live weight for meat production and the number of yolks per egg with a strong significance of 4.34e-13, 2e-16, <2e-16, and 0.01 respectively. However, we did not find any significant relationship between the numbers of eggs laid per hen per clutch, the number of eggs seated on per hen per clutch and the number of eggs hatched per hen per clutch, in the various agro-climatic zones.

Despite being the lightest and small bodied, chickens from Lake Turkana which had an average mean body weight (g) of 1190.96 358.16 produced more eggs (9.42eggs 6.87eggs) than the heaviest and big bodied (Lamu Archipelago) which had an average body weight (g) of 2198.74 656.32 and produced an average of 8.29 eggs 5.95 eggs per clutch. Mount Elgon catchment chickens had an average weight (g) of 1974.75 572.92 and produced an average of 8.75 7.77 eggs per hen. Lamu Archipelago had eggs with the highest number of double-yolked eggs with a frequency of 89%.

Generally, we revealed relevant production traits for meat and egg production among indigenous chickens from different ecotypes in different regions that historically were migration points of entry for humans and livestock into Kenya. We propose further genetic studies on the Lamu and Turkana Chicken ecotypes since these two are from regions in Kenya that have previously been understudied.

Key words: chicken ecotypes, food security, meat, poultry, production systems


Introduction

Chickens were domesticated in Asia over 8000 years ago and have spread worldwide to adapt in several agro-ecological zones. Chickens are especially important in developing countries since they provide a large proportion of protein in human diet in terms of meat and eggs. They have also been used for ornamental purposes for instance the silkie or bantams in China and also during entertainment for example game cocks used for cock fighting Magothe et al (2012). Kenya has about 32 million domesticated poultry and out of these, almost 70% are indigenous. These have not undergone any genetic improvement to form breeds and are distributed in several ecological zones i.e. local chicken ecotypes. On the other hand, the commercial and hybrid chickens constitute about 20% Kenya Bureau of Statistics (2009) and the remaining 10% comprises the other poultry such as turkeys, ducks, geese, quails, ostrich, pigeons and guinea fowls FAO (2007). Most of the local chicken ecotypes are kept by the majority rural poor to fulfill multiple functions among them supply of affordable protein in their nutrition and source of income FAO (2007). Local chicken ecotypes are reared under the free range system Okeno et al (2012) where they are left to scavenge for food, without any feed supplementation or veterinary inputs (Kingori et al 2010). Characterization of phenotypes is necessary for important production and adaptation traits. A study by Moraa et al (2015) was able reveal tolerance to heat stress as an important adaptation trait.

Different studies in Africa have revealed the existence of considerable variations in production traits (Shank length, Body Length, Live weight, No of eggs laid, number of eggs seated, and number of eggs hatched, Sitting times/year, number of yolks /egg among others) within and among local chicken populations FAO (2012, Adeleke et al (2011). Halima (2007) reported the existence of variations between genetic groups of local chicken in Ethiopia as indicated by high heterozygosity values. On the other hand, Ajayi (2010) reported the heritability estimates for body weight in the Nigerian local chicken populations that indicated the dual potential for development into a meat or egg strains.

The Results from these studies showed existence of many genotypes, phenotypes and varied productivity potential within local chicken populations hence indicating the possibility of improving genetic potential through selective breeding within and between local chicken populations. (Msoffe et al 2004) reported large variations in reproduction and production performance of local chickens in Tanzania. Recently Guni et al (2013) characterized selected local chickens from southern highlands of Tanzania.

In Kenya Okeno et al (2012) and Njenga et al (2005) revealed that farmers carry out chicken selection at household level based on growth rate, large body size, high egg production, hatchability and good mothering ability whereas farmers, marketers and consumers prefer the above mentioned traits as traits of economic importance and therefore should be given priority when developing breeding objectives for improvement of indigenous chicken. Magothe et al (2010) inferred that linear body measurements like shank length, drumstick length, drumstick circumference and chest circumference are easy to measure and suggested that these variables may be used to predict body weight of local chicken ecotypes especially under field conditions. (Olwande et al 2010) reported significant clutch sizes and hatchability rates in Kenya. Njenga et al (2005) reported the three major objectives of poultry rearing found to be for food, sale, and cultural uses and concentrated more on the hatchability so as to achieve the objectives.

Although the performances of local chicken ecotypes have been evaluated and documented in Kenya, data are scarce on key attributes and not all regions have been studied hence we collected data from previously unstudied areas. We looked at some morphological traits, reproductive and morphometric attributes and revealed that there are important differences within and between the local chicken populations with respect to egg production, reproductive attributes and morphometric attributes that were considered in the study. This suggested that there is room for selection within and between the local chicken ecotypes for both meat and egg production. We targeted regions with no previous poultry improvement programs and were also human and livestock domestication/migration corridors into Kenya hence harboring distinct local chicken ecotypes Aswani et al (2015) and Moraa et al (2015). This study therefore aimed to characterize the various phenotypes associated with meat and egg production in local chicken ecotypes from three


Materials and Methods

Study Area

The three agro-climatic zones chosen for this study were Lake Turkana basin arid area, Lamu archipelago semi arid coastal area and Mount Elgon catchment humid highland area. These were the preferred study sites since the areas sampled were not adversely affected by the cockerel and pullet exchange breeding program and they were routes of livestock domestication/migration corridors into Kenya (Mwacharo et al 2013). Mount Elgon catchment study area is a highland found in zone I, II and III of the agro-climatic zones of Kenya. These three zones are considered wet and they are characterized by an annual rainfall of 500-1000 mm per annum and an annual temperature of 17.1C minimum and 29.4C maximum (Jaetzold and Schmidt 1983). Lamu is semi arid area and it lies within zones IV and V of the agro-climatic zones, this zone is considered dry and humid and receives an annual rainfall of 800mm and an annual temperature of 24.1C minimum and 29.2C maximum. Turkana basin is arid, it lies within zone VI and zone VII of the agro- climatic zones of Kenya. These zones are characterized by annual rainfall of 200-600 mm which is quite unreliable since crops can hardly survive in this environment but livestock have adapted and they survive. It’s also characterized by an annual temperature of 23.7C and 34.9C (Paron et al 2013). A map showing the study areas is shown in figure 1 while the specific counties from which data was collected are outlined in table l.

Figure 1. Map of study area. Source (http://www.infonet.biovision.org)


Table 1. Summary of sampled locations

Agro-climatic zones

Population

Number of samples

Feeding

Reproduction

Lake Turkana basin

Lake Turkana East

33

scavenging

Random mating

Lake Turkana West

61

scavenging

Random mating

Total

94

scavenging

Random mating

Lamu Archipelago

Lamu North

27

scavenging

Random mating

Lamu central

30

scavenging

Random mating

Lamu South

46

scavenging

Random mating

Total

103

scavenging

Random mating

Mt. Elgon catchment

Mt. Elgon north

31

scavenging

Random mating

Mt. Elgon south

44

scavenging

Random mating

Lake Victoria

24

scavenging

Random mating

Total

99

scavenging

Random mating

 

Total samples

296

scavenging

Random mating

Data collection

Interviews were conducted at the farmers’ homes with the assistance of local agricultural extension officers from the Ministry of Agriculture. Pre-tested questionnaire on open data kit (ODK) on phones were used to obtain the morphological and physiological data of the local ecotype chickens based on the production traits. Data was collected on a total of 296 genetically unrelated adult (above 1 year) local ecotype chickens from 10 populations each having 20-30 individuals according to (Hale et al 2012). Data was collected on various phenotypic attributes including the number of eggs laid per hen, colour of the eggs laid, eggs seated on per clutch per hen, eggs hatched per clutch per hen, number of yolks in each egg and sitting times per hen per year. Physical measurements like body weight, body length, shank length, were also taken using a measuring tape, vernier caliper and recorded as described by (FAO 2012). The weights of chickens were measured using portable sensitive weigh balance. The body weight was the individual live weight of the chicken. Body length was taken as the distance between the caudal (tail, exclusive of feathers) and tip of the rostrum maxillae (beak) when chicken was fully stretched while the shank length was measured from the spur to the hock joint of either leg according to (Adeleke et al 2011). A global positioning system (GPS) was used to record coordinates for the study sites.

Study clearance

This study got a no objection for the research under the permit number “RES/POL/VOL.XXVII/162” from the Ministry of Agriculture, Livestock and Fisheries state department of veterinary services.

Data analysis

Data was analyzed using R core statistics software version 3.0.1, Graph Pad Prism™ version 6.0 and Microsoft excel 2013. Significant differences within means were determined using Tukey’s test at 95% confidence level. We also used analysis of variance (ANOVA) tests to determine relationships between various production traits and the ecosystem.


Results and discussion

Analysis of Body Measurements (Body Length and Shank Length) In Indigenous Chickens from Different Agro-Climatic Zones
Figure 2. Average shank length (A) and body length (B) of chickens sampled in 3 agro-climatic zones of Kenya.
Vertical bars represent standard deviation of the mean according to Tukey’s test at P<0.05

The average body lengths and shank lengths are outlined in figure 2 above. Chickens from Lamu archipelago were found to have the longest average shanks, followed by those from Mt Elgon while those from Lake Turkana recorded the shortest average shank (Figure 2A above). A similar pattern was observed for the body length of chickens in the agro-climatic zones. Chickens from Lamu Archipelago recorded the highest body lengths followed by those from Mt Elgon and Lake Turkana (Figure 2B above). The results differed from Guni et al (2013) who reported a range of 40.2cm and 45.7cm in body length. The observed variation in body length between agro-climatic zones indicates the existence of different diverse subpopulations within the local chicken ecotypes.

Analysis of Body Weight of Chickens Sampled in the Three Agro-Climatic Zones
Figure 3. Analysis of average body weight of chickens sampled in 3 agro-climatic zones in Kenya.
Vertical bars represent standard errors of the mean according to Tukey’s test at P<0.05

Lamu archipelago recorded the heaviest chickens, based on body live weight, followed by Mt Elgon with Lake Turkana recording the lowest average weight (Figure 3 above). The average body weights(g) observed in the present study fell within the range of 1030 and 2860, 1108 and 2915 and 1525 and 2095 as reported by Katule (1998); Msoffe et al (2001); Guni et al (2013) respectively. However, the results were higher than the ones reported by Dana (2010); Olawunmi et al (2008); Mwalusanya et al (2002) and Guye E F (1998). In Kenya, they were higher than the results reported by Magothe et al (2010) who reported a range of 1330.2-1741.0, slightly different from Olwande et al (2010) who reported a range of 1599g-2096 respectively though they were lower than the ones reported by King’ori (2004) who reported a range of 1950-3150.

We observed a significant variation in body weight between agro-climatic zones indicating the existence of different diverse subpopulations within the local chicken ecotypes.

Agro-climatic zones and the various traits: Shank length, body length and live weight

Table 2. ANOVA Summary results of analysis of agro-climatic zones and various traits attributed to body growth production in indigenous chickens of Kenya

Traits

p

Agro-climatic zones and Shank Length

Agro-climatic zones and Body Length

Agro-climatic zones and Live weight

***

***

***

Significant codes: 0 '***' 0.001 '**' 0.01 '*' ns-not significant p<0.001

Upon analysis of variance on the obtained data, there was a significant relationship between the shank length, body length and live weight and the agro-climatic zones (Table 2). The significant interaction between body weight and other body measurements imply that these easily measured parameters can be used for estimation of body weight and hence important in selection criteria that can be used to improve body weight. The existence of positive and significant correlations between body weight and body measurement traits have also been reported by Alabi and Ng`ambi (2012) and Guye et al (1998) from Nigeria and Senegal respectively for local chickens.

Distribution of Production Traits Associated With Egg Production among Chickens in Different Agro-Climatic Zones
Figure 4. Comparison of frequencies of eggs seated on and eggs hatched in chicken sampled from 3 agro-climatic zones in Kenya.
Vertical bars represent standard errors of the mean according to Tukey’s test at P<0.05.
The average number of eggs laid per hen in each zone are shown inset.

We found no significant differences between the agro-climatic zones with respect to this variable. These results were in consistent to those reported by Guni et al (2013) who reported 13.7 eggs. Mwalusanya et al (2002) and Olwande et al (2010) reported the mean clutch size to be 11.8 eggs and 11 eggs respectively, lower than the mean value reported in the study. We found out the frequencies of eggs sat on yearly showed a slight variation within the agro-climatic zones of Kenya. For instance, Mt Elgon catchment recorded the highest frequency of eggs seated on by the local ecotype chickens while Lake Turkana had the lowest frequency of eggs seated on at (Figure 4). The difference in the frequencies of eggs sat on was mainly based upon the farmers’ decision to give out the eggs to the hens. We found out that the farmers give out a certain fraction to the hens to lay on and consume or sell the rest for cash. The results were confirmed with extension officers from the Ministry of Agriculture, livestock and fisheries who also keep records of livestock production.

Analysis of hatchability among the 3 zones similarly revealed slight differences in the frequencies of eggs hatched. We obtained high hatchability in Lamu archipelago followed by Mt Elgon and Lake Turkana at 84.6% and 77.62% respectively (Figure 4). These results were consistent with Guni et al (2013); Kugonza et al (2008); Njenga et al (Development and Veterinary 2005); Mammo et al (2008), who reported a hatchability of between 83.2% and 92.6% in chickens from different districts in Tanzania with an exception for Lake Turkana basin which had lower hatchability. In Kenya Olwande et al (2010); King’ori (2004); Okitoi and Mukisira (2001) reported lower results than the ones reported in this study as follows: 70%-80%, 43%-47% and 46%-48% respectively. The results were confirmed with extension officers from the Ministry of Agriculture, livestock and fisheries who also keep records of livestock production.

Figure 5. Average sitting cycles of indigenous chickens sampled from 3 agro-climatic zones of Kenya.
Vertical bars represent standard deviation of the mean according to Tukey’s test at P<0.05

We further estimated the number of sitting cycles per hen per year. Results of the present study showed that Lamu archipelago had the highest average sitting cycles per hen per year followed by Lake Turkana basin and Mt. Elgon (Figure 5). We observed average mean number of 1.78 clutches per year in the present study was lower as compared to the ones that were reported from other studies in different countries such as Tanzania Guni et al (2013); Bangladesh Hossen (2010); Botswana Moreki, (2010); Namibia (Petrus, 2011) and India Iqbal and Pampori (2008). The latter reported a sitting cycle of four clutches per year.

Figure 6. Analysis of the number of yolks per egg in chickens from 3 agro-climatic zones of Kenya.
Vertical bars represent standard deviation of the mean according to Tukey’s test at P<0.05.

Lamu Archipelago had heavy-bodied chickens though they produced fewer eggs which were often double-yolked. The study found out that despite the fact that Local ecotype chickens in Lake Turkana basin were small but produced more eggs as compared to the ones in Lamu Archipelago which were heavy-bodied though they produced fewer eggs that were often double-yolked. Double yolk is a trait that possesses no selective advantage (Lowry, 1967).

Table 3. ANOVA Summary results of analysis of agro-climatic zones and various traits

Traits

p

Agro-climatic zones and number of yolk in an egg

Agro-climatic zones and number of eggs laid

Agro-climatic zones and number of eggs sat on

Agro-climatic zones and number of eggs hatched

Agro-climatic zones and number of sitting times per year

**

ns

ns

ns

**

Significant codes: 0 '***' 0.001 '**' 0.01 '*' ns-not significant P<0.05

We also sought to find out the existence of significant interactions between the numbers of eggs laid per clutch, sat on, hatched and the number of sitting times per year in different agro-climatic zones; the results are summarized in table 3. There is a significant relationship between the agro-climatic zones and the number of yolks in an egg and the number of sitting times per year at 95% confidence interval level. However, the study confirmed that there was no significant relationship between the agro-climatic zones and the number of eggs laid, number of eggs seated on and number of eggs hatched per hen per clutch.


Conclusions


Implications


Acknowledgments

The authors wish to acknowledge financial support awarded to Dr. Sheila Ommeh by the Jomo Kenyatta University of Agriculture and Technology research grant no. JKU/2/4/RP/181. We would also like to thank the Department of Veterinary Services for supporting this research. Appreciation is also extended to the extension officers and the farmers for their co-operation during data collection.


References

Adeleke M A, Peters S O, Ozoje M O, Ikeobi C O N, Bamgbose A M and Adebambo O A 2011 Genetic parameter estimates for body weight and linear body measurements in pure and crossbred progenies of Nigerian indigenous chickens. Livestock Research for Rural Development. Volume 23, Article #19. Retrieved July 19, 2016, from http://www.lrrd.org/lrrd23/1/adel23019.htm

Ajayi FO 2010 Nigerian Indigenous Chicken: A Valuable Genetic Resource for Meat and Egg Production. Asian Journal of Poultry Science, 4: 164-172. DOI: 10.3923/ajpsaj.2010.164.172 URL: http://scialert.net/abstract/?doi=ajpsaj.2010.164.172

Alabi O J, Ng`ambi J W, Norris D and Egena S S A 2012 Comparative Study of Three Indigenous Chicken Breeds of South Africa: Body Weight and Linear Body Measurements. Agricultural Journal, 7: 220-225.DOI: 10.3923/aj.2012.220.225. http://medwelljournals.com/abstract/?doi=aj

Aswani B P, Lichoti J, Oyier P, Maina S, Makanda M, Wamuyu L, Alakonya A, Ngeiywa J K and Ommeh S 2015 Functional Polymorphisms at a Candidate Gene for Meat and Egg Production in Indigenous JKUAT 2015 Scientific Conference, 1, 107–114.

Dana N, Dessie T, Waaij L H, Van Der, and Arendonk J A M Van 2010 Morphological features of indigenous chicken populations of Ethiopia, 411(September 2009), 11–23.

Development S P and Veterinary T R 2005 Productivity and socio-cultural aspects of local poultry phenotypes in coastal Kenya.

Entrepreneurship D L and Sufficiency F 2010 Animal Production Society of Kenya Proceedings of the Annual Scientific Symposium 2010 Nomad Palace Hotel, Garissa, Kenya 20th to 22nd April, 2010 “Driving Livestock Entrepreneurship towards Attainment of Food

FAO 2007 Food and Agriculture Organization of The United Nations Strategies for the Prevention and Control of Infectious Diseases ( including Highly Pathogenic Avian Influenza ) in Eastern Africa in small scale commercial and scavenging production systems in Kenya.

FAO 2012 Phenotypic characterization of Animal Genetic Resources (n.d.) Retrieved 28 November 2016, from http://www.fao.org/docrep/015/i2686e/i2686e00.htm

Guye E F, Ndiaye A and Branckaert R D S 1998 Prediction of body weight on the basis of body measurements in mature indigenous chickens in Senegal, 10(3). Retrieved from http://www.lrrd.org/lrrd10/3/sene103.htm

Guni F S, Katule A M and Mwakilembe P A A 2013 Characterization of local chickens in selected districts of the Southern Highlands of Tanzania: II Production and Morphometric traits.Livestock Research for Rural Development Volume 25, Article #190. Retrieved July 19, 2016, from http://www.lrrd.org/lrrd25/11/guni25190.htm

Hale M L, Burg T M and Steeves T E 2012 Sampling for Microsatellite-Based Population Genetic Studies: 25 to 30 Individuals per Population Is Enough to Accurately Estimate Allele Frequencies, 7(9). http://doi.org/10.1371/journal.pone.0045170

Halima H 2007 Phenotypic and Genetic Characterization of Indigenous Chicken Populations in Northwest Ethiopia PhD Thesis; University of the Free State, Bloemfontein, South Africa

Hossen M J 2010 Effect of management intervention on the productivity and profitability of indigenous chickens under rural condition in Bangladesh.Livestock Research for Rural Development Volume 22, Article #192. Retrieved July 19, 2016, from http://www.lrrd.org/lrrd22/10/hoss22192.htm

Iqbal S and Pampori Z A 2008 Production potential and qualitative traits of indigenous chicken of Kashmir. Volume 20, Article #182 Retrieved July 19, 2016, from http://www.lrrd.org/lrrd20/11/iqba20182.htm

Jaetzold R and Schmidt H 1983 Farm management handbook of Kenya, Natural Conditions and Farm Information, 11

Kenya Bureau of Statistics 2009 Ministry of State Planning, National Development and Vision 2030 Kenya population and housing Census: Volume II, 2009

Kingori A M, Wachira A M and Tuitoek J K 2010 Indigenous Chicken Production in Kenya: A Review. International Journal of Poultry Science 9(4): 309–316

Kugonza D R, Kyarisiima C C and Iisa A 2008 Indigenous chicken flocks of Eastern Uganda: I. Productivity, management and strategies for better performance. Volume 20, Article #137 Retrieved July 19, 2016, from http://www.lrrd.org/lrrd20/9/kugo20137.htm

Lowry D C 1967 The incidence of double-yolked eggs in relation to improvement in egg production Der Zchter, 37(2), 82–85 http://link.springer.com/article/10.1007/BF00329571

Lwelamira J, Kifaro G C and Gwakisa P 2008 Breeding strategies for improving performance of Kuchi chicken ecotype of Tanzania for production under village conditions. Volume 20, Article #171. Retrieved July 19, 2016, from http://www.lrrd.org/lrrd20/11/lwel20171.htm

Magothe T M, Okeno T O, Muhuyi W B and Kahi A K 2012 Indigenous chicken production in Kenya: I. Current status. World’s Poultry Science Journal, 68(01), 119–132

Mammo M, Berhan T and Tadelle D 2008 Village chicken characteristics and their seasonal production situation in Jamma District, South Wollo, Ethiopia.Volume 20, Article #109. Retrieved July 19, 2016, from http://www.lrrd.org/lrrd20/7/meng20109.htm

Moraa G K, Oyier P A, Maina S G, Makanda M, Ndiema E K, Alakonya A E, Ngeiywa K J, Lichoti J and Ommeh S C 2015 Assessment of phenotypic traits relevant for adaptation to hot environments in indigenous chickens from four agro-climatic zones of Kenya. Livestock Research for Rural Development. Volume 27, Article #200. Retrieved July 19, 2016, from http://www.lrrd.org/lrrd27/10/omme27200.html

Moreki J C 2010: Village poultry production in Serowe-Palapye sub-district of Botswana. Livestock Research for Rural Development. Volume 22, Article #46. Retrieved July 19, 2016, from http://www.lrrd.org/lrrd22/3/more22046.htm

Msoffe P L M, Mtambo M M A, Minga U M, Olsen J E, Juul-Madsen H R, Gwakisa P S, Mutayoba S K and Katule A M 2004 Productivity and reproductive performance of the free-range local domestic fowl ecotypes in Tanzania. Livestock Research for Rural Development. Volume 16, Art. #67.Retrieved July 19, 2016, from http://www.lrrd.org/lrrd16/9/msof16067.htm

Mwacharo J M, Bjrnstad G, Han J L and Hanotte O 2013 The History of African Village Chickens: an Archaeological and Molecular Perspective. African Archaeological Review, 30(1), 97–114. https://doi.org/10.1007/s10437-013-9128-1

Mwalusanya N A, Katule A M, Mutayoba S K, Mtambo M M A, Olsen J E and Minga U M 2002 Productivity of Local Chickens under Village Management conditions: Tropical Animal Health and Production, 34(5), 405–416.

Okeno T O, Kahi A K and Peters K J 2012 Characterization of indigenous chicken production systems in Kenya: Tropical Animal Health and Production, 44(3), 601–608.

Okeno T O, Magothe T M, Kahi A K and Peters K J 2012 Breeding objectives for indigenous chicken: Model development and application to different production systems. Tropical Animal Health and Production, 45(1), 193–203.

Olwande P O, Ogara W O, Okuthe S O, Muchemi G, Okoth E, Odindo M. O and Adhiambo R F 2010 Assessing the productivity of indigenous chickens in an extensive management system in southern Nyanza Kenya: Tropical Animal Health and Production, 42(2), 283–288.

Paron P, Olago D O and Omuto C T 2013 Kenya: A Natural Outlook: Geo-Environmental Resources and Hazards (Vol. 16). Newnes https://www.amazon.com/Kenya-Geo-Environmental-Resources-Developments-Processes/dp/0444595597

Petrus N P 2011 Characterization and production performance of indigenous chickens in northern Namibia regions, (March 2011) http://wwwisis.unam.na/theses/petrus2011.pdf


Received 2 October 2016; Accepted 1 December 2016; Published 1 February 2017

Go to top