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Citation of this paper

Genetic analysis of meat production traits of rabbits in Dagwom Farms, Vom, Nigeria

T Ibrahim, S T Mbap, Z Russom*, S D Abdul**and M S Ahmed***

Animal Production Programme, Abubakar Tafawa Balewa University, P.M.B. 0248, Bauchi
*Crop Production Programme, Abubakar Tafawa Balewa University, P.M.B. 0248, Bauchi
**
Biological Sciences Programme, Abubakar Tafawa Balewa University, P.M.B. 0248, Bauchi
***National Veterinary Research Institute, Vom, Plateau State, Nigeria
tahibatta@yahoo.com

Abstract

The productivity of five rabbit genotypes namely: Locals, pure New Zealand White (NZW), 50% and 75% NZW and 'Others' were monitored from 1997 to 1998 at the Dagwom Farms in Vom, Nigeria . Records of mating involving 45 sires and l45 dams were used to obtain estimates of heritability (h2 ) for body weight (BW) at 7, 21, 42 and 56 days and the genetic and phenotypic correlations existing between them.

Estimates of h2 were mostly moderate to high (0.17-0.90). The phenotypic and genotypic correlations between the traits were mostly positive and moderate to high (0.02-0.57 and 0.18-0.75 for phenotypic and genotypic correlations, respectively).The study has shown that considerable variations exist in BW at various ages within the rabbit population of Dagwom Farms. The traits could therefore be improved by simple selection procedures. In addition, considerable correlated responses in the traits should be expected, considering the strong relationships existing between them.

Key words: Correlation, genotypic, heritability, phenotypic, rabbit


Introduction

With the continued rise in the cost of beef, sheep and chicken that are the primary sources of animal protein in Nigeria, it has become necessary for researchers to explore other less common sources. A panacea to this deficiency is to embark on accelerated animal protein production from livestock species with short generation interval and high fecundity. The priority therefore, should be to rear animals with potential for quick income generation, high profit, short term capital investment content and simple management skill requirement (Aduku and Olukosi 1990). One of the high potential sources of animal protein, which is not commonly exploited in Nigeria, is the rabbit. Best known for high prolificacy, rabbits are herbivores, which efficiently convert fodder to food. They return 20 percent of the protein eaten into edible meat as compared to 22 to 23 percent for broiler chickens, 16 to 18 percent for pigs and 8 to 12 percent for beef. They can easily convert available proteins in cellulose -rich plants, in situations where they may not be economical to feed to chickens and turkeys, the only animals with higher protein efficiency (Lebas et al 1997). In terms of growth, rabbits excel ruminants and ranks close to modern broiler chicken (Adegbola et al 1986). Its meat has the highest percentage protein (21%) and the least fat content as compared to other meat sources and is low in cholesterol and sodium, which makes it highly recommendable for people with cardio-vascular diseases (Aduku and Olukosi 1990).

Although, once in a while, rabbits have been imported into Nigeria, the first concerted effort at organized rabbit production started between 1988 and 1989, when the Directorate for Food, Roads and Rural Infrastructure imported several rabbit breeds in to the country for the genetic improvement of the local ones. One of the centres established across country for this purpose, was the Dagwom Farms at the National Veterinary Research Institute (NVRI) Vom, Plateau state. However, since its establishment, no study was carried out to estimate heritabilities (h2) of production traits and their relationships which are required in the design and application of practical breeding programmes (personal observation).


Materials and methods

Management

The experimental work was carried out at the Dagwom Farms of NVRI, Vom, Plateau state, Nigeria, from March 1997 to December 1998.Vom is 1280m above sea level and lies on longitude 8º 45´ East and latitude 9º 43´ North (Knudsen and Sohael 1970). Rainy season extends from April to October with peak rainfall in July/August while the dry season starts in November and ends in March. The mean annual rainfall ranges between 1250 to 1650 mm. The average air temperature ranges from 19.5 to 23.5ºC. Compared to the surrounding lowland areas, the climate shows characteristic coldness common at high altitudes. The climate has therefore been described as being sub-tropical (Mbap and Ngere 1989).

The breeding programme started in 1988 with the procurement of mongrel rabbits from households and farms within and around Vom to form the foundation stock. In 1989, the New Zealand White (NZW) breed was imported and a crossbreeding programme between the two groups was initiated. This gave rise to 50 and 75% NZW groups. Later, another group called 'Others' that included rabbits from higher order crosses and those whose original parentage could not be ascertained came into being. These distinct groups were maintained generation after generation.

The rabbits were housed in three enclosed buildings with windows providing adequate ventilation. Breeding females and males were kept separately in 610x762x457mm individual cages, while weaned bunnies were kept in cages in groups of 6 to 10 individuals. All cages were fitted with aluminum feeders and drinkers. Each rabbit bore an identification number on the inner surface of its ear lobe. Throughout the period of study, the rabbits were fed ad libitum a concentrate diet containing 16% crude protein twice daily (morning and afternoon). Green forages were also given when available. Fresh clean water was available to the rabbits at all times.

Young does and bucks were considered to have attained breeding age at 210 to 240 days. Each doe was transferred to the buck's cage and restrained to ensure copulation. They were palpated 10 days thereafter to determine their pregnancy status. Those that failed to conceive were returned to the same buck to be re-mated and every other day thereafter, until a successful service was observed. On the 25th day of pregnancy, the nest boxes were examined. After kindling, the kits were inspected and record on them taken within 24 hours. The young rabbits remained with their dams until weaning at 42 days. Young doe replacements were added to the breeding groups as needed throughout the period covered by the study.

Data collection and analysis

Information from mating involving 45 sires and 145 dams, which produced 1631 offspring at birth, was used to generate data for the study. The traits considered were body weights at 7 (BW7), 21 (BW21), 42 (BW42) and 56 days (BW56). Prior to analysis the records were crosschecked for improbable dates and omissions, while dams or sires with single records were dropped. The sizes of data after this process became 545,456 354, and 264 for BW7, BW21, BW42 and BW56, respectively.

The data were analyzed using the Mixed Model Least Squares and Maximum Likelihood Procedure (Harvey 1990). The data were corrected for the effects of genotype, season, panty, sex, year (all considered as fixed effects), and litter size at birth (LSB) considered as a covariate. Preliminary analysis had revealed that interactions between the factors were not significant and as such were not included in the final model. Sire, dam and within individual variance components were obtained according to Henderson (1953). Individual were nested within dams and sires cross-classified with dams as follows:

Yijk = µ + Si + Dij + E ijk

Where:

µ = common mean
Si = effect of the ith sire

Dij = effect of the ijth dam within the ith sire

Eijk = uncontrolled environmental deviations associated with each record which is assumed to be random, independent and normally distributed with a mean 0 and a common variance

Heritabilities were estimated from sire and dam variance components, according to Becker (1984) as follows: -

h2s = 4 δ2s / (δ2s + δ2d + δ2w).

h2d = 4 δ2d / (δ2s + δ2d + δ2w).

where:

h2s = heritability from sire component
h2d = heritability from dam component
δ2s = sire variance component

δ2d = dam variance component

δ2w = within progeny variance component

Standard errors for heritability estimated were approximated following the method of the same author. Phenotypic and genotypic correlations were also estimated according to Becker (1984).


Results and discussion

The genetic group means and standard errors of BW at 7, 21, 42 and 56 days are presented in table 1.

Table 1.   Means and standard errors of body weight (BW) at various ages ( 7, 21, 42 and 56 days)  in rabbits at Dagwom Farms

Traits

No. of observations

Mean s.e., kg

BW7      

519

0.230.003

BW21

441

0.450.007

BW42    

350

0.590.010

BW56

264

0.120.002

kg=kilogrammes

The components of variance and h2 estimates for BW at various ages are shown in table 2. The values of h2 were mostly moderate to high and ranged from 0.17 for BW7 to 0.90 for BW56 (all obtained using the maternal half sib correlation method) , while some estimates were absurd (outside the parameter limit of unity).

Table 2.  Estimates of variance components (δ2)and heritabilities of body weight (BW) in rabbits at various ages ( 7,21,42 and 56 days) at Dagwom Farms

Traits

Variance Components

Heritability estimate from

δ2s

δ2d

PHS

s.e.

MHS

s.e.

BW7

0.0031

0.0028

0.49

0.153

0.17

0.103

BW21

0.6053

1.2764

0.23

0.154

0.67

0.187

BW24

1.2217

1.6268

2.10

0.219

1.26

0.258

BW56

0.5027

0.0642

1.34

0.270

0.90

0.261

PHS  = Paternal half sib method

MHS = Maternal half sib method

s.e    = Standard error   

The h2 estimate of 0.23±0.15 for BW21 from the dam component is lower than an estimate of 0.33 reported by Ngo Ndjon and Nwakalor (1998a). However, Blasco et al (1982) reported a value of 0.09±0.08 using the method of intra-sire regression of offspring on dam. The estimate of 0.90±0.26 for BW56 obtained from the paternal half-sibs correlation is higher than values of 0.23 and 029±0.13 reported by Mostageer et al (1970) and Khalil et al (1986) using the same method of estimation. However, the latter reported a similar value of (0.92±0.17) obtained by the maternal half-sibs method. Discrepancies between the estimates in this study and those reported in literature is as expected since heritability values depend on the genetic make-up of the stocks, management and climate conditions and period of study as well as differences in data size, models of data correction and method of analysis (Khalil et al 1986). The moderate to high estimates of h2 of BW at the various stages of growth suggest that the characters are susceptible to genetic influence and could be improved by simple selection methods such as one based on individual performance as advocated by Khalil et al (1986) and Lukefahr (1988) in their reviews on genetics of growth in rabbits.

The fact that some estimates of h2 could not be derived or were outside the parameter limit could be attributed to inadequacy of records, limitations to appropriate control over some environmental factors, effects of selection and inbreeding, assortative mating or maternal effects, as postulated by several investigators (Blasco et al 1982; Khalil et al 1986;Ngo Ndjon and Nwakalor 1998a). However, Hill and Thompson (1978) showed that the probability of a parameter lying outside the parameter range increases when its true value lies near the boundary of the range. For low h2 such as for reproductive traits the probability is considerable. At a true h2 of 0.10 using 20 sires and 400 offspring in a paternal half-sibs analysis, Gill and Jensen (1968) showed that the probability might be as high as 15%.

Estimates of phenotypic and genotypic correlations between the traits are shown in Table 3. They were mostly positive and moderate to high and ranged from 0.18 (between BW7 and BW56) to 0.75 (between BW21 and BW 56) for genetic correlation and from 0.02 (between BW42 and BW56) to 0.57 (between BW7 and BW21) for phenotypic correlation. For both types of correlation, the estimates derived from the sire component were larger than those from the dam component. However some values could not be obtained due to negative variance components.

Table 3.   Phenotypic and genotypic correlations between body weights (BW)  at various ages ( 7, 21, 42 and 56 days) in rabbits at Dagwom Farms

Traits

Phenotypic

Genotypic

BW21

BW42

BW56

BW21

BW42

BW56

BW7

0.56***

0.14*

0.32***

0.33***

-

0.18*

0.57***

0.16*

0.34***

0.71***

0.42***

0.70***

BW21

 

0.08

0.54***

 

-

0.65***

 

0.09

0.54***

 

0.19*

0.75***

BW42

 

 

0.02

 

 

-

 

 

0.03

 

 

0.46***

First value =  estimate from dam component

Second value = estimate from sire component

* =  P < 0.05       ** = P < 0.01      ***  = P < 0.001

Values without superscripts are non-significant

The strong genetic and phenotypic correlations between BW at various ages have been observed in rabbits (Khalil et al 1986; Ngo Ndjon and Nwakalor 1998b). Falconer (1989) and Mohiuddin (1993) ascribed genetic correlation among traits to the effect of linkage between the genes controlling them (particularly in populations derived from crosses between divergent strains) and pleiotropy (a situation whereby a gene influences the expression of more than one trait). Based on the theory of pleiotropy, Koots et al (1994) concluded that many growth traits are simply measures of growth at different ages and as such body weights at various stages of growth are expected to associate significantly. Therefore, market weight of rabbits at Dagwom Farms should improve considerably, if body weights at early ages are used as basis for selection due to correlated response. This would go a long way to reduce cost of production and improve its efficiency. The fact that most estimates of phenotypic and genotypic correlations obtained from the sire component were higher than the corresponding estimates from the dam component, may be due to sampling error or the effect of selection, as suggested by Khalil et al (1987).

The fact that most estimates of genotypic correlations were higher than the corresponding phenotypic correlations has been established by several scientists (Khalil et al 1987; Boujenene and Kerfal 1990; Koots et al 1994). According to Searle (1961) this phenomenon could be due to negative environmental correlations between the associated traits.


Conclusion


References

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Received 2 May 2006; Accepted 6 July 2006; Published 1 January 2007

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