Performance evaluation and sustainability challenges of tropically adopted exotic chicken breeds in Northwest Ethiopia

Abstract

The study aimed to describe performance and challenges of village-based exotic chicken production in Northwest Ethiopia. Three zones, 13 districts, and 300 households were selected. The data were collected via semi-structured questionnaires, field observations, and key informant interviews. In the study area, the average exotic chicken holding per household was 4.27 ± 0.13 birds. The most dominant flocks were hens followed by pullets with high significant difference (P < 0.01) in the midland agro ecology. The annual number of egg production of Sasso, Bovans brown, and Koekoek was 110.99 ± 1.45, 123.29 ± 1.16, and 102.92 ± 1.22, respectively. The average age of pullets at first egg laying was 5.25 ± 0.03 (Sasso), 5.53 ± 0.02 (Bovans brown), and 5.71 ± 0.03 (Koekoek) months. The age of cockerels (mean ± SE) at first mating was 4.18 ± 0.06 (Sasso), 4.89 ± 0.06 (Bovans brown), and 5.15 ± 0.06 (Koekoek) months. Male age (mean ± SE) at slaughter of Sasso, Bovans brown, and Koekoek were 4.24 ± 0.06, 6.28 ± 0.05, and 5.68 ± 0.06 months, respectively. The lack of improved breed supply was the first production challenge followed by feed shortages and disease outbreaks. Therefore, designing exotic chicken market supply, practicing ration formulation with locally available feed resources, controlling disease, and predator with biosecurity measures and other proper management strategies in respective of agro ecologies could be mandatory.

Keywords:

• Agro ecologies
• challenges
• exotic chicken
• performance
• sustainable production

1. Introduction

The poultry industry improves the socio-economic status of households in low- and middle-income countries and contributes to the inclusion of vulnerable groups such as the pro-poor community, women, the disabled, orphans, and the unemployed (Kleyn & Ciacciariello, 2021; Manyelo et al., 2020; Mohamed et al., 2022). Similarly, in Ethiopia, chicken plays a pivotal role in poverty reduction and alleviation, nutrition and food security, growth of domestic products (GDP), and employment opportunities (Bayesa & Merah, 2021).

In Ethiopia, the term poultry is synonymous with domestic chicken (Gallus gallus domesticus) due to almost non-sources of egg and meat from other types of poultry. Currently, the nation has 56.99 million chickens with 44.94 million indigenous (78.86%), 6.85 million hybrid (12.02%), and 5.19 million exotic breeds (9.12%) (CSA, 2021). Particularly, in Amhara region, 19.06 million chickens (33.44% of the national) with 16.30 million indigenous (85.52%), 1.62 million hybrids (8.55%), and 1.13 million exotic (5.93%) were found (CSA, 2021).

Despite the large population and the great contribution of local chicken to the livelihood of poor farmers, the performance of chickens under smallholder production systems is poor and varies in different parts of Ethiopia (Matawork, 2018). Consequently, commercial exotic genomes were introduced to Ethiopia to improve the performance of indigenous chickens and increase the income level of farmers from the sector (Alemneh & Getabalew, 2019). However, importing has been done over the last two decades continuously via the distribution of fertile eggs, day-old chickens, pullets, and cockerels (Fulas et al., 2018; Hailu et al., 2012; Moges et al., 2010). However, neither the population of the improved breed nor the egg production potential is significantly increased (Tilahun et al., 2018). Different authors argued that exotic chicken breed supply is found in an advancing way, but there could be different challenges that are constantly faced by poultry producers (Aklilu et al., 2007; Dessie et al., 2013; Fulas et al., 2018).

All available evidence showed that exotic breeds of chicken perform well under the intensive management system. Still, the contribution of exotic chicken to the country's economy is significantly lower than other African countries (Alemu et al., 2009; Kebede, 2016). The reasons might be poor distribution strategies and low awareness of producers about exotic chicken management practices. Information about the production and productivity potential of different exotic breeds across agro-ecological variations (comparative studies) was scant in the region. Therefore, this research was initiated to describe the productive, reproductive, and sustainability challenges of exotic chicken production under village-based production systems in different agro-ecologies of in Northwest Ethiopia.

2. Materials and methods

2.1. Description of the study area

The study was conducted in the Amhara region, located in the northwestern and north central parts of Ethiopia. The Amhara region comprised 11 administrative zones and 169 districts (BoARD, 2020). According to Aynalem (2021), there are about 3429 Kebeles (the smallest administrative units) in the region. The region is located between 9°20“and 14°20” North latitude and 36° 20“and 40° 20” East longitude. The area coverage of the region is 170,752 km² (BoARD, 2020).

High altitude (>2500 masl), mid-altitude (1500–2500 masl), and low altitude (1500 masl) make up 25%, 44%, and 31% of the region’s three primary agro-ecological zones, respectively. The annual mean temperature of the region lies between 15°C and 21°C. The area receives 80% of the nation’s total rainfall, which is the greatest percentage (BoARD, 2020).

2.2. Sampling techniques

Different sampling techniques such as stratification, purposive, simple random, and proportionate allocation sampling techniques were employed. From a total of 11 zones, three zones which have the highest exotic chicken population (West Gojjam, Central Gondar, and South Wollo) were selected deliberately. All districts found in these zones were stratified based on their agro-ecological division; highland (13), midland (28), and lowland (15) districts. A total of 13 districts (3 highland, 6 midland, and 4 lowland) were selected using proportional sampling techniques.

Forty-five study Kebeles were quantified based on Yamane’s (1967) sample size determination formula; these Kebeles were selected using simple random sampling procedures. As per the sample size determination methods, a total of 300 households were interviewed. Proportional sampling techniques were also used for the determination of the sample size of households from the agro-ecological-based stratified sampled Kebeles. Hence, lowland (93), midland (130), and highland (77) households were used. Those respondents were selected using simple random sampling procedures from those households having at least one exotic chicken under village-based production systems.

Therefore, Kebeles and the total respondent size were determined by Yamane (1967) sample size determination formula with 95% confidence interval and a precision level of 5% and 10% for household and Kebeles, respectively.

$\mathrm{n}=\frac{\mathrm{N}}{1+\mathrm{N}{\mathrm{e}}^2}$

where

N = Study population

n = Sample size

e = Precision level with the above indicated

The distributions of sample size across each agro ecology division were calculated by using below formula:

n’ = n(N’/N) … … … … … … … … … . (Israel, 1992)

2.3. Methods of data collection

Semi-structured questionnaires were developed to discover flock dynamics, supply of chickens, performances of chickens, and sustainable production challenges. Field observations were also made to assess available chicken breeds and other observable parameters of chicken production systems. Key informant interviews were also held at zonal level with village leaders, youth, elders, women, and socially respected individuals for verification of the collected information through questionnaire interviews. Secondary data were also collected using Google Scholar, PubMed, Science Direct, and reference lists of previous studies from different sources.

2.4. Data analysis and management

Both qualitative and quantitative datasets were analyzed with SPSS version 20.0. Analysis of variance procedure (ANOVA) and descriptive statistics were employed and presented with standard error (SE) dispersion. Moreover, least significant differences (LSD) and χ² square procedure tests were applied at 5% significant level to compare mean values with agro-ecological differences for both qualitative and quantitative data, respectively. The statistical model was as follows: Yij = μ+Ai+eij; where Yij = response variable, µ = overall mean, Ai = effect of agro-ecology and eij = random error.

3. Results and discussion

Chicken Breed, Holding, and Flock Composition

The types of exotic chicken distribution, chicken flock composition, and average flock size per household are presented in Table 1. In the area, the average chicken holding per household was 4.27 ± 0.13 birds. It was significantly higher in midland (5.44 ± 0.20) followed by highland (3.53 ± 0.22) agro-ecologies. This is similar to the report of Hailu et al. (2012) which revealed that the mean number of Bovans brown breed per household in the midland (4.29 ± 0.52) was higher than in the highland (4.28 ± 0.63) and lowland (3.76 ± 1.07) areas. The current findings also showed that the most dominant flocks were hens, followed by pullets, with a highly significant difference (P < 0.01) in the midland agro-ecology. The purpose of keeping chickens for egg production in the area could be focused on this type of flock population, and those unproductive hens might be kept in the flock. Most of the farmers were kept Sasso, Bovans brown, Koekoek, and Sasso RR with descending distribution patterns. This might be explained by the fact that private poultry farms, particularly Ethio chicken private farms, offer Sasso breeds. Sasso and Koekoek breeds were distributed in all the agro-ecology of the study area without significant variations (P > 0.05). However, the distribution of Bovans brown was significantly higher in the midland agro-ecologies. This difference might be due to favorable climatic conditions for them, farming systems, and rearing objectives that influence the genetic diversity of chickens (Leroy et al., 2012).

Table 1. Exotic chicken holding and flock composition per household

Chicken in the area			Agro ecologies				P Value
			Highland	Midland	Lowland	Overall
			HHN= 77	HHN=130	HHN=93	HHN= 300
Chickens holding (Mean± SE)
			3.53±0.22^b	5.44±0.20^a	3.24±0.18^b	4.27±0.13	0.000**
Flock composition (Mean± SE)
	Chicks		0.30±0.10^b	1.25±0.13^a	0.20±0.07^b	0.68±0.07	0.000**
	Cockerel		0.13±0.09	0.16±0.05	0.05±0.03	0.12±0.03	0.406^ns
	Pullet		1.40±0.12^b	1.78±0.11^a	1.22±0.11^b	1.51±0.07	0.001**
	Hens		1.34±0.12^b	1.85±0.09^a	1.32±0.12^b	1.56±0.06	0.000**
	Cocks		0.36±0.06	0.38±0.05	0.44±0.06	0.40±0.03	0.603^ns
Breed distribution N (%)
	Sasso		64 (83.1)	102 (78.5)	70 (75.3)	236 (78.7)	0.460^ns
	Koekoek		13 (16.9)	29 (22.3)	10 (10.8)	52 (17.3)	0.079^ns
	Sasso-R		5 (6.5)	10 (7.7)	25 (26.9)	40 (13.3)	0.000**
	Bovans Brown		39 (50.6)	80 (61.5)	36 (38.7)	155 (51.7)	0.003**
	Fayoumi		4 (5.2)	20 (15.4)	10 (10.8)	34 (11.3)	0.080^ns
	Isa Brown		4 (5.2)	17 (13.1)	3 (3.2)	24 (8.0)	0.016**

a,b,c Means in the same row with different superscript letters are significantly different (P<0.05), SE=Standard Error, ** = highly significant (P<0.01), NS= non-significant, HHN= Household Number

3.1. Exotic chicken and other input sources

Most of the respondents (91.7%) got foundation chicken and other inputs by purchasing from private cooperatives, local markets, and NGOs (Ethio chicken and other) (Table 2). Similarly, Aman et al. (2017) reported that the majority of interviewed respondents (58.20%) purchased initial stocks and other inputs from private farms and local cooperatives. This study also revealed that few respondents were given chickens as gifts (6.3%) and a combination of both (2.0%). Although the major source of chicken was by purchase, there were significantly varied variations among different agro-ecological zones of the study area.

Table 2. Exotic Chicken and other input supplier in the region

Agro ecologies
Input and Supplier	Highland	Midland	Lowland	Overall	χ^2	P value
	HHN= 77	HHN=130	HHN=93	HHN= 300	value
Source of foundation stock N (%)
Purchased only	70(90.9)	126(96.9)	79(84.9)	275(91.7)	10.26	0.006**
Gift only	4(5.2)	2(1.5)	13(14.0)	19(6.3)	14.37	0.001**
Both	3(3.9)	2(1.5)	1(1.1)	6(2.0)	1.96	0.375^ns
Chicken and input sources for the households N (%)
Agricultural Office	30(39.0)	57(43.8)	33(35.5)	120(40.0)	1.63	0.443^ns
Market	49(63.6)	67(51.5)	46(49.5)	162(54.0)	3.97	0.138^ns
Ethio chicken & other NGO	27(35.1)	57(43.8)	77(82.8)	161(53.7)	47.49	0.000**
Research Centers	18(23.4)	21(16.2)	16(17.2)	55(18.3)	1.80	0.407^ns
Local cooperatives	32(41.6)	113(86.9)	35(37.6)	180(60.0)	69.56	0.000**

Note: χ² = chi square, ** = highly significant (P<0.01), NS= non-significant, HHN= Household Number, N= Number of respondents, NGO= Non governmental organization

3.2. Chicken productive and reproductive performances

The annual egg production potential of chickens is an important trait for egg producers. The annual egg production of Sasso, Bovans brown, and Koekoek under a scavenging production system was 110.99 ± 1.45, 123.29 ± 1.16, and 102.92 ± 1.22, respectively. This is lower than the report of Desalew (2012)—Koekoek (187.04 ± 13.49), Tadesse et al. (2013)—Bovans Brown (292.4 eggs/year), Aman et al. (2017)—Sasso (229.14 ± 52.49), Yirgu et al. (2017)—Bovans brown (266.32), and Serkalem et al. (2019)—Sasso (134), Bovans (117), and Koekoeck (138). However, which is close to the report of Gutu et al. (2021) revealed that the total number of eggs produced by Sasso, Sasso-RIR, and Koekoek was 82.5, 59.8, and 64.8/hen up to 44 weeks in western Oromia. The authors postulated that, except for Koekoek, the two studied strains had significant differences (P < 0.001) in agro-ecological location interaction. In the current study, all the studied breeds had better annual egg production performance in midland agro-ecology than others. This is supported by Singh et al. (2009) who showed that the interaction between breed and location could be significant for egg production. This could be due to variations in feed management, breed, age of chicken, feed intake, and production systems.

From a producer’s economic perspective, age at first egg lay is a crucial trait of layer breeds. The fact that they laid their first egg at such a young age suggests that egg production was expected to increase over the course of their lifetime (Okoro et al., 2017). The average age of pullets at first egg laying of Sasso, Bovans brown, and Koekoek was 5.25 ± 0.03, 5.53 ± 0.02, and 5.71 ± 0.03 months, respectively (Table 3). Similarly, Desalew (2012) reported that the average first egg lay of Isa Brown, Bovans Brown, and Potchefstroom Koekoek was 5.35 ± 0.45, 5.52 ± 0.44, and 5.11 ± 0.2 months in East Shoa, respectively. Unlikely, the mean age at the first lay of studied chickens in the current study was longer than the report of Aman et al. (2017) for Sasso (4.47 months) in southern Ethiopia and shorter than the report of Dirsha (2009) 6.34 ± 0.46 months for RIR in Cheha district, Ethiopia. The finding also confirmed that Sasso breeds earlier reach an age of egg production than Bovans brown and Koekoek breeds, which could be attributed to breed variation, adaptability, and feed conversion efficiency. Birds that have short age at the first egg laying are supposed to be more efficient in feed consumption (Teketel, 1986). Though Bovans brown are hybrids, the Koekoek is a synthetic breed, and Koekoek layers had a longer age at first egg laying than Sasso and Bovans brown hens. This might be attributed to management, age of the chickens, and feed availability differences in the studied areas. This is supported by Guni et al. (2013) who revealed variation in age at first egg laying in different districts and within districts, which is attributable to genetic and non-genetic factors.

Table 3. Production and reproduction performance of exotic chickens in different agro ecologies of the study area

Performance Parameters	Agro-ecology				P value
	Highland	Midland	Lowland	Total
	HHN= 77	HHN=130	HHN=93	HHN=300
Egg production per hen per year (Mean± SE)
Sasso	118.61±3.11^a	112.87±1.99^a	102.06± 2.48^b	110.99±1.45	0.000**
Bovans Brown	127.11±1.65^b	133.49±1.85^a	109.49±1.83^c	123.29±1.16	0.000**
Koekoek	101.20±2.34	104.10±1.78	102.70±2.35	102.92±1.22	0.629^ns
Age of pullets at first egg laying in months (Mean± SE)
Sasso	5.22±0.05^b	5.11±0.05^b	5.47±0.05^a	5.25±0.03	0.000**
Bovans Brown	5.51±0.04	5.54±0.03	5.52±0.04	5.53±0.02	0.834^ns
Koekoek	5.66±0.06^b	5.65±0.04^b	5.84±0.06^a	5.71±0.03	0.018*
Age of cockerels at first mating in months (Mean± SE)
Sasso	4.39±0.12^a	4.00±0.08^b	4.2±40.11^a	4.18±0.06	0.016*
Bovans Brown	5.32±0.10^a	4.52±0.10^b	5.06±0.12^a	4.89± 0.06	0.000**
Koekoek	5.08±0.09^b	4.90±0.08^b	5.55±0.10^a	5.15±0.06	0.000**
Male age at slaughter in months (Mean± SE)
Sasso	4.37±0.12^a	4.04±0.08^b	4.40±0.11^a	4.24±0.06	0.011*
Bovans Brown	6.49±0.11^a	6.14±0.08^b	6.31±0.08^a	6.28±0.05	0.018*
Koekoek	6.10±0.13^a	5.23±0.09^b	5.90±0.08^b	5.68±0.06	0.000**

Note: a,b,c Means in the same row with different superscript letters are significant different (P<0.05), * = significant (P<0.05), ** = highly significant (P<0.01), NS= Not significant, SE=Standard Error

The current study postulated that first mating age of cockerel Sasso (4.18 ± 0.06), Bovans brown (4.89 ± 0.06), and Koekoek (5.15 ± 0.06) months (Table 3). This is in line with a report by Sisay and Ewonetu (2020), who revealed that the average age at sexual maturity of exotic chickens ranges from 19.6 to 26.8 weeks for males in different parts of Ethiopia. Sasso reached maturity for mating faster than other studied genotypes in the study area. Bovans brown also had a shorter age at maturity compared to the Koekoek breed, this finding being in agreement with the report of Desalew (2012). This might be due to the smaller size of the Bovans browns compared to Koekoek of the same age group. Thus, they require a low amount of nutrients for their maintenance and thereby attain the shorter age of maturity with the levels of feed available to them. The male slaughter age of Sasso, Bovans, and Koekoek was 4.24 ± 0.06, 6.28 ± 0.05, and 5.68 ± 0.06 months, respectively. The high growth rate in Sasso and Koekoek might be a result of being dual-purpose breeds. This is supported by the report of Yonas (2020); the Sasso chickens had higher growth rate and the lowest slaughter age (5.24 ± 0.43 months) compared to Bovans brown and local chicken ecotypes. This could be in spite of genetic variation and environmental factors like nutrition and temperature (Sisay & Ewonetu, 2020).

3.3. Challenges of sustainable exotic chicken production

Determining and defining village-based exotic chicken production methods in various agro climatic zones could aid in identifying significant issues impeding the sector’s success in certain agro-ecological locations. Lack of an improved breed supplier was the first ranked (0.31) exotic chicken production problem in the study area, followed by feed shortage (0.29) and disease outbreak (0.27) presented in Table 4. The result is in agreement with the reports of Kebede (2016) and Hailu et al. (2012). Similarly, shortage of improved chicken breeds and disease challenges in Ethiopia (Zemelak et al., 2016), as well as disease, predators, poor extension services, feed shortages, and housing were the main drawbacks for village-based exotic chicken production in Banja, and Burie districts, Ethiopia (Tilahun et al., 2018).

Table 4. Challenges of sustainable exotic chicken production

	Agro ecologies
	Highland				Midland					Lowland					Overall
Challenges	Number of HH ranking				Number of HH ranking					Number of HH ranking					Result
	1	2	3	N(I)	R	1	2	3	N(I)	R	1	2	3	N(I)	R	N(I)	R
Lack of breed supplier	20	18	8	104 (0.22)	3	58	45	27	291(0.37)	1	33	18	30	165(0.30)	2	560(0.31)	1
Poor extension services		1	4	6 (0.01)	6	-	4	4	12(0.02)	5	4	1	1	15(0.03)	6	33(0.02)	5
Disease	7	31	31	114 (0.25)	2	12	77	4	194(0.25)	3	13	66	8	179(0.32)	1	487(0.27)	3
Predator		14	8	36 (0.08)	4	-	2	35	39(0.05)	4	4	1	13	27(0.05)	5	102(0.06)	4
Formulated feed shortage	44	13	19	177 (0.38)	1	49	-	67	214(0.27)	2	27	1	48	131(0.23)	3	522(0.29)	2
Poor environment adaptable breed	7		6	27 (0.06)	5	12	-	-	36(0.05)	4	12	2	1	41(0.07)	4	104(0.06)	4
Total N				464		Total N			786		Total N			558		1808

Note: N= number of households, I = Index value, R= Rank, Index= [(3 for rank 1) + (2 for rank 2) + (1 for rank 3)] divided by sum of all weighed reasons mentioned by respondent

Although lack of improved breed supplier, feed shortage, and disease outbreak were the most-prioritized problems in all agro-ecological zones, the first-ranked problems in different agro-ecologies were shortage of formulated feed, breed supplier, and disease challenge in highland, midland, and lowland agro-ecologies, respectively. The authors postulated that the prioritization of encountered problems or the severity of problems varied based on agro-ecology. In agreement with this, Zemelak et al. (2016) reported that the most priority constraints in the lowlands were the diseases, whereas lack of locally adapted and well-performing chicken breeds was the most priority constraint in the midlands.

4. Conclusion and recommendation

The number of chickens kept per household, flock structure, breed distribution types, and most productive and reproductive performances of exotic chickens varied on an agro-ecological basis. Midland was the most preferred agro-ecological zone for most traits of exotic chickens. The most common exotic chicken breeds in the Amhara region were Sasso, Bovans-Brown, and Koekoek. Although respondents had different sources for their foundation stock, most households got it by purchasing from private cooperatives, local markets, and NGOs. The main barriers to distributed exotic chicken production in the area were a lack of breed supply, a lack of commercial feed, disease, and predators. These prominent challenges were seriously affecting the sustainability of exotic chicken production and their contribution to the farmers’ economy.

Thus, research and development initiatives should focus on designing an appropriate market chain of exotic chickens and other input supplies, utilizing locally available feed, and engaging in disease and predator control activities to increase production and productivity performances of exotic chickens and subsequently maximize the financial gains of producers in the area.

Authors contribution

HA contributed to the conception or design of the work, write-up of the manuscript, and coordination of the entire research activities. AY, TK, GM, and DA contributed to data collection and coding. HA and AY involved in data analysis and interpretation of results. MM, MB, DC, AY, and HA carried out the organization and drafting of the manuscript. Finally, all authors participated in revising critically for important intellectual content and approval of the final manuscript.

Consent for publication

Not applicable.

Ethics approval and consent to participate

Not applicable

Acknowledgments

The authors would like to acknowledge the University of Gondar and the College of Veterinary Medicine and Animal Sciences for their funding support for this study. The authors would also like to thank farmers and district agricultural expertise for their cooperation during data collection.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data that support the findings of this study are available in “figshare” at https://doi.org/10.6084/m9.figshare.20009492.

Additional information

Funding

The authors declare that this manuscript work was funded by the University of Gondar, Ethiopia, under Grant (672020). The entire required budget starting from conception or design of the work was covered.

Notes on contributors

Habtamu Ayalew

Habtamu Ayalew is an assistant professor of animal production at the University of Gondar, Ethiopia. He has vigorous experience in teaching and research work in the area of animal nutrition and production, more focused on monogastric gut health, microbiota, and antibiotic alternative feed additives. He has many published works in national and international reputable journals. Other co-authors of the manuscript work at the University of Gondar and research institutes with different positions and research experiences.