Genetic parameters for growth traits in N’Dama cattle under tsetse challenge in the Gambia

N A Bosso*,**, E H van der Waaij**,***, K Agyemang* and J A M van Arendonk**

*International Trypanotolerance Centre, PMB 14 Banjul, The Gambia

**Wageningen Institute of Animal Sciences, PO Box 338, 6700 AH Wageningen, The  Netherlands

***Department of Farm Animal Health, Veterinary Faculty, University of Utrecht, PO Box 80151, 3508 TD, Utrecht, The Netherlands

nguetta.bosso@gmail.com   and   nabosso@yahoo.fr

Abstract 

Heritabilities and correlations for growth traits in N'Dama cattle under tsetse challenge were estimated using an animal model. Animals were born and weaned in a low to medium tsetse challenge area and, after weaning at 12 months of age, they were transported to a high tsetse challenge area until three years of age. Measurements included body weight and growth rate during seasons from 12 to 36 months of age. Two seasons were defined: the dry season from November to June representing the period of feed shortage and low tsetse fly density; and the wet season from June to November where sufficient feed was available and the tsetse density was the highest.

Heritabilities for body weight ranged from 0.28 for body weight at 36 months of age to 0.48 for body weight at 15 months of age. For growth rate, the heritability was 0.09 during the dry season and 0.15 during the wet season. Genetic correlations of birth weight with body weight at 12 and 15 months of age were moderately high (0.49 and 0.51, respectively). Genetic correlations between most body weights and growth rates during seasons ranged from –0.40 to 0.80. The genetic trend due to the selection programme was highest for body weight at 36 months of age from 1994 to 2004. For growth traits, an increasing genetic trend was observed in growth between 15 and 36 months of age and in growth during the dry season from 12 to 36 months of age.

It was concluded that selection for growth should focus on growth during dry and wet seasons.

Keywords: genetic correlation, genetic trend, heritability, selection, tropical cattle

Introduction 

Increasing awareness of the potential of indigenous livestock breeds is becoming evident in the activities of both national and international organizations in Sub-Saharan Africa. Indigenous livestock breeds have always played an important role in the lives of the people of Sub-Saharan Africa. They contribute to a wide variety of activities; providing sustenance, transport and protection against harsh environments. Indigenous livestock breeds serve to transform feeds into food and marketable products adding value to farming enterprises by increasing income and enhancing the biophysical and economic viability of agriculture (Winrock 1992).

Few of these indigenous livestock breeds have been introduced in modern genetic improvement programmes that aim to serve the larger livestock farming population and to demonstrate a sustainable approach to livestock development in the region. Examples of genetic improvement programmes show that the potential to significantly improve breeds in terms of productivity do exist in this part of Africa (Diallo et al 1992; Ebangi et al 2000).

Of the several epizootic diseases that plague livestock agriculture in West Africa, trypanosomiasis is argued to be the single most important constraint to animal agriculture.  Direct impacts are associated with losses of milk and meat production as well as mortality and morbidity. The indirect trypanosomiasis impact is related to the opportunity cost of land and other resources currently not used for livestock production owing to the presence of tsetse flies (Agyemang 2005). Livestock breeds that possess the ability to survive, reproduce and remain productive under trypanosomiasis risk without recourse to trypanocidal drugs are said to exhibit trypanotolerance and are referred to as trypanotolerant. This ability is exhibited to the highest degree in a few breeds of cattle in West and Central Africa, namely N’Dama. The exploitation of the genetic resistance to trypanosomiasis through the use of indigenous, tolerant ruminant livestock is one approach to the control of the disease. In 1981, a comprehensive breeding effort to genetically improve milk and meat production of N’Dama cattle was started in Guinea (Diallo et al 1992). Following this initiative, other breeding programmes for were instigated. In 1985 a programme to evaluate the productivity of N’Dama cattle under village conditions started in Senegal (Fall 1992). More recently in 1994, the International Trypanotolerance Centre (ITC) in the Gambia implemented a genetic improvement programme for low input systems. The programme aims at a better utilization of the local trypanotolerant N’Dama cattle breed in West African countries, especially in the Gambia. In the genetic improvement programme, the performance of the animals has been monitored since 1995. In 1998, selection of animals based on estimated breeding values for growth rate and milk off-take was introduced.

Genetic and phenotypic parameter estimates are scarce for purebred N'Dama cattle populations. The ITC's genetic improvement programme has placed a large emphasis on increasing growth. Knowledge on genetic parameters in this population was lacking and therefore the design of the programme was based on literature and on experiences from experiments related to trypanotolerance (Trail et al 1991). Further development of the genetic improvement programme could be achieved once genetic parameters for the population of interest are known. With the genetic improvement programme conducted at the ITC, a unique data set is being collected, which offer the opportunity to estimate genetic parameters in N'Dama cattle and evaluate consequences of selection.

The aim of this study is to utilize the information available from the ITC breeding programme to estimate the genetic parameters for growth traits and evaluate the genetic trends in N'Dama cattle kept under natural tsetse challenge.

Materials and methods 

Production environment

ITC’s cattle were originally distributed in herds all over the country. The concentration of the stock in a single nucleus-breeding scheme in two sites, Keneba and Bansang, was achieved in 1994.  

All animals in this research are now station based and belong to the ITC. Keneba is situated in the Kiang West District approximately at 80 km from the Atlantic coast. Degraded savannah woodlands, riparian woodlands and long-term fallows characterize the vegetation (Agyemang et al 1997). The tsetse challenge (Glossina morsitans submorsitans) in Keneba is classified as low to medium (Wacher et al 1994). Bansang is situated approximately 200 km from the Atlantic coast and comprises two adjacent villages situated 1.5 km apart in the Niamina East District. The vegetation consists mainly of woodlands interspersed with more open savannah woodland and fresh water swamps (Agyemang et al 1997). The tsetse challenge (Glossina morsitans submorsitans and Glossina palpalis) in Bansang is classified as very high (Wacher et al 1994), and the area is infested with high densities of both species of tsetse flies.

Animal type and management

The Gambian N'Dama is slightly taller than the typical Guinean type. The colour varies from foam to white. It has a small body frame and long strong horns. The birth weight of the Gambian N'Dama is on average 18 kg for males and 17 kg for females. Average mature live weight is 295 kg for males and 227 kg for females. Animals in the ITC breeding programme are maintained under a low input management system which means that they are raised as animals under village conditions. They are tethered individually overnight, and are accompanied by ITC's herdsmen to graze far away from the station during the day.

Feeding behaviour varies between Keneba and Bansang but animals generally graze from 09:00 to 16:00 h daily over an extensive area (communal grazing) and are not supplemented. Calves stay with the dams for a long time for natural suckling. From November to June i.e. in the dry season, the animals generally lose weight, because the quantity and quality of feed is low. The animals endure serious feed shortages in the late dry season and the beginning of the wet season (April–August). In Keneba with its medium tsetse challenge, animals graze on grass in the wet season. During the early dry season, after the harvest, there is a shift to crop residues in the village fields. In the late dry season, animals feed themselves with browse and fruits and graze over extensive areas of burnt bush. In Bansang with its high tsetse challenge, the feeding habits are different and the shortage is less accentuated than in Keneba. Grass is available most of the year with a small reduction in the middle of the wet season. Generally, grass regeneration occurs at the end of the wet season and before the beginning of the early dry season. Details of herd management have been described by Agyemang et al (1988) and Jeannin et al (1988).

Trypanosomosis prevalence

During a period of five consecutive years (between 1995 and 2000), trypanosomosis surveys were conducted at the ITC’s research station in Bansang. Randomly selected cattle were sampled monthly and their blood was investigated using parasitological diagnostic methods. At the same time, the population of biting flies was sampled. These data was used to determine the monthly average prevalence and therewith the seasonal change in bovine trypanosomosis of trypanosome infection in cattle. 

Trypanosomiasis prevalence was found to vary from very high to very low; the mean annual prevalence ranged from 1% to 52%. Since 1995, the prevalence has decreased considerably.

From Figure 2 it can be seen that the number of tsetse flies starts to rise slowly in July and they become abundant between the months of November and March. The peak prevalence is found in November i.e. just at the end of the wet season. Between March and June in the late dry season), bush fires destroy tsetse habitats causing a rapid decline in tsetse density to a very low level. Seasonal changes in body condition show that animals reach their maximum body conditions in November i.e. at the beginning of the dry season. During  the dry season they lose weight and reach their minimum body conditions in May i.e. at the end of the dry season. Throughout the dry season, animals are stressed due to disease and lack of adequate feed.

Breeding strategy

In the ITC breeding programme, animals are selected from an index containing information on daily weight gain in the post-weaning period and on milk off-take. Daily weight gain in the post-weaning period, i.e. between 15 and 36 months of age, is determined in an area with extremely high tsetse challenge via monthly weighing of all animals. Milk off-take is defined as the portion of the 0-100 day milk yield which is not consumed by the calf, but taken for human use. Milk off-take is measured weekly in the females. The index integrates information on the animal itself and all its relatives using the BLUP animal model. Selected candidates are located at the ITC’s Keneba station. At any time the breeding herd consists of 5 sires and 400 cows.. In each year, at least 220 cows are mated to produce 100 male and 100 female calves. The newborn calves are maintained at Keneba until weaning at 12 months of age, after which approximately 95 males i.e. 90 born on station and 5 from the screening operation, and 90 females are moved to Bansang. Males and females stay in separate herds for approximately 2 years. At any time, approximately 230 males and 225 female weaners are present at Bansang. There is an annual loss of 10% among selection candidates for reasons of health and survival. At the end of the testing period at 36 months of age), approximately 84 males and 80 females are available for selection and are moved back to Keneba for breeding. Each year 1–2 males are selected to replace some of the breeding males. That are used for 2–3 years in the herds. Females are first mated at around 4 years of age and the milk yield of the first lactation is measured. Around 75 females are selected and mated after which 55 animals are retained based on their first lactation performance.

Traits evaluated

Body weight records collected monthly at the ITC research stations, Keneba and Bansang, from 1994 to 2004 were available for this study. Traits considered in the analysis included: body weight at birth (BW), at 12 months of age (W12, weaning), at 15 months of age (W15, after 3 months of adjustment at Bansang), at 24 months of age (W24), the final weight of the test period at 36 months of age (W36); the selection criteria currently used i.e. daily weight gain between 15 and 36 months of age, G15–36 and the daily weight gain between 12 and 36 months of age (G12–36). It was hypothesised that growth during each season might have a slightly different genetic background. To investigate this, two other traits were defined: growth rate during the dry season from 12 to 36 months of age (GD12–36) and growth rate in the wet season from 12 to 36 months of age (GW12–36). These traits were derived by taking the difference between the first and last recorded weights within seasons. These were accumulated across the two years and divided by the respective accumulated time interval in days between the weight records. Growth during a season was calculated as:

where WL represents the last weight during the respective season, WF represents the first weight during the season; DL represents the last day of recording and DF is the first day of recording, 1 and 2 represent the respective year.

Statistical analysis

The data file included 1711 animals born from 1987 to 2004 and was analysed using the following models: (1) to estimate genetic parameters for body weight traits, growth G15–36 and growth G12–36, and (2) to estimate genetic parameters for growth traits during seasons.

                               (1)

                                                                           (2)

Where:

sex_i is the fixed effect of sex (male or female),
bhd_j is the fixed effect of the herd in which the animals were born (six herds),
thd_k is the fixed effect of the herd in which the animals were tested (four herds),
sea_l is the fixed effect of season, yea×sea_lm is the fixed effect of the interaction between year and season,
a_n is the random effect of animal, and
e_ijklmn is the random residual error.

The PROC GLM procedure (SAS 1999) was used to select the main effects (sex, birth and test herd, year and season of birth) as well as interactions that influenced the weights and growth rates. Effects that influenced the records significantly (P<0.05) were included in the animal model.

An animal model was applied to estimate variance components and genetic parameters using ASREML (Gilmour et al 2000). Ancestors with at least two offspring were included in the relationship matrix. Heritabilities and genetic and phenotypic correlations were estimated using a bivariate model. Average estimated breeding values (EBVs) of animals were calculated and regressed across birth year of the calves to predict annual genetic trends for body weight at different age BW, W12 and W36 as well as genetic trends for G15–36 and growth during dry and wet seasons GD12–36 and GW12–36.

Results 

Summary statistics

A summary of the number of animals recorded at different ages and mean, standard deviation, minimum and maximum for each of the traits is presented in Table 1.

The number of records decreased with age. This is partly caused by censoring, i.e. the animals born in the most recent years have not yet reached the age of 36 months of age. There is a large variation in body weight at different ages. Means and standard deviations for GW12–36 were higher than those for GD12–36. Table 1 illustrates that large phenotypic differences in growth performances were found between animals.

Fixed effects

The sex effect was significant (P<0.05) for all traits except for BW, GW12–36, GD12–36 and G12–36. The herd in which the animals were born had an effect only on BW and W12; the herd in which animals were tested had a significant effect only for W24, W36, G15–36, GW12–36, GD12–36 and G12–36. The season of birth had a significant effect (P<0.05) on all traits except W12 and GW12–36. The effect of year on all the traits, except BW and G12–36, was highly significant (P<0.01).

Genetic parameters

Heritability estimates with their standard error for each trait, along with estimates of genetic and phenotypic correlations between traits are shown in Table 2.

Heritabilities for body weight traits ranged from 0.28 for W36 to 0.48 for W15. Heritability estimates for growth traits during seasons were low for GW12–36 (0.15) and very low for GD12–36 (0.09).

The phenotypic correlations for body weight traits ranged from 0.17 (between BW and W36) to 0.82 (between W12 and W15). Phenotypic correlation for growth during dry and wet season was –0.09 (between GW12–36 and GD12–36). As to be expected, a high phenotypic correlation (0.89) was found between growth G15–36 and G12–36. Phenotypic correlations between body weights and growth traits ranged from –0.18 (between G15–36 and W15) to 0.85 (between G12–36 and W36).

Genetic correlations between birth weight and weights at later ages were moderately to highly positive and ranged from 0.28 (W36) to 0.61 (W24). The genetic correlation between weight at 15 months of age and final weight (W36) was high (0.84). The genetic correlation between growth rate in the dry and wet seasons could not be estimated. The standard errors related to the genetic correlations estimated in general were high.

Genetic trend

Figures 3 and 4 show the trend in mean EBV for body weight and growth traits during seasons from 1994 to 2004, respectively. Figure 3 shows a positive increase in the estimated genetic level for BW, W12 and W36. The average breeding values for W36 increased by 6.32 kg from 1994 to 2004. This corresponds to an annual genetic trend for W36 of 0.40 kg/year. The other body weight traits also exhibited positive, although smaller, genetic trends: 0.06 kg/year for BW and 0.17 kg/year for W12.

The average breeding values for growths traits are presented in Figure 4. An increasing level for G15–36 is seen from 1994 to 2004. This trait was used as one of the selection criteria and a positive genetic trend in this trait was expected. The pattern in mean EBV for GW12–36 is similar but smaller than that of G15–36. The patterns for the other growth traits showed large fluctuations.

Discussion 

Genetic parameters

This study has focussed on the estimation of genetic parameters for body weights and growth traits during seasons in N’Dama cattle and the evaluation of genetic trends. This is the first study to present estimates of genetic parameters for traits of N'Dama cattle under tsetse challenge and during different seasons. The results indicate that additive genetic variance exists for the traits considered.

The heritability estimate for BW is in the range of that found by Ahunu et al (1997) for the same breed, and of Koots et al (1994), Burrow (2001) and Mackinnon et al (1991) for different breeds. The heritability estimate for W12 is slightly higher than for BW and higher compared with those found in other studies (Mackinnon et al 1991; Eler et al 1995). This is in contrast with other results in the literature in which the heritability for W12 was consistently lower than that for birth weight. The absence of a maternal genetic effect in our model might have contributed to the high estimate for W12 (Meyer 1992). These effects were inestimable due to the small number of observations and the data structure. Accounting for maternal genetic effects resulted in a lower estimate of the heritability for body weight measured early in the life of the animals (Meyer 1992). The heritability estimate for G15–36 (0.24) in the present study is consistent with those from previous reports (0.26, Mackinnon et al (1991)) and (0.22, Burrow (2001)) in other breeds.

Olutogun (1976) reported phenotypic correlations between BW and W12 of 0.19, which is lower than the 0.28 that was estimated in this study. The extensive and adverse conditions under which the animals in this study are reared have a large effect on the growth of the young animals. The major factors playing an important role are the seasonal scarcity of water and feed. The scarcity and low feed quality force the young animals to range further to obtain the necessary amount of dry matter to meet their nutritional requirements. The low negative phenotypic and genetic correlation between GD12–36 and GW12–36 suggests that selection for GW12–36 alone is likely to have negative effects on GD12–36. This is supported by the genetic trend of GD12–36, which is opposite to that of GW12–36. This suggests that selection for GW12–36 might have adverse effects on the ability to maintain growth during times of limited nutrition and parasite challenge. It is important to realize that the weight of an animal under high tsetse challenge is determined by its genetic potential for growth, but also by its level of trypanotolerance (Trail et al 1992), and, therefore, may have a different genetic background compared to weight under low tsetse challenge. The physiological mechanisms, the nutritional level and the trypanosomiasis challenge levels are different in the two seasons.

Given the fact that calves are born all year round, with a peak during October and November, calves born in these months will spend relatively more time in the wet season than calves born in, for example, January.

The consequence of defining the growth period from 15 to 36 months of age is that the environment the animal will experience from 15 to 36 months of age differs between animals depending on the month of birth of the calve. For the breeding program, it is important to pay attention to growth during the dry and the wet seasons to ensure that the ability of animals to handle harsh environments does not deteriorate as a consequence of selection on final weight (i.e. the trait of economic interest to the farmers).

All animals observed for growth during seasons have completed the 24 months in the high tsetse infested area in Bansang. Thus, they have experienced an equal number of months in the wet and dry seasons. Growth during season was defined as the average growth during the entire time the animal was in Bansang during the dry or during the wet season. Furthermore, if an animal arrived in Bansang towards the end of the season, observations for growth during that season were still included in the trait definition. Consequently, for each season considered, an animal had two to three observations, which were subsequently averaged. The problem with this way of defining the growth during a season is that, despite the fact that information is available and is included in the trait definition, the environment in Keneba (where the animal was born) is much less demanding than the environment in Bansang. Therefore, animals arriving in Bansang towards the end of the season may have an advantage over animals that have arrived early in the season. An alternative way to define growth during seasons, therefore, would be to only include the observations of growth during complete seasons in Bansang.

W36 is the trait considered to be the most important (more than growth). In our analysis, W36 was corrected for the seasonal effect when estimating the breeding values of the animals. However, this will only be a correction for the average effect of the season. The genetic and phenotypic correlations between seasonal growth and the opposite sign of the genetic trend of both seasonal growth traits indicate that there is genetic variation in reaction to different seasons. These differences are not exploited when selecting on W36.

The moderate genetic correlations between BW and the other body weight traits are in agreement with results of Davis (1993) and Mackinnon et al (1991). These correlations indicate that animals with higher birth weight usually also have faster postnatal growth.

We realise that the limited size of our data set results in large standard errors especially for the genetic correlations. However, the phenotypic correlations are estimated more accurately, and could serve as indicators of the magnitude and sign of the genetic correlations (Lynch and Walsh 1998). Even if insufficient data reduces the accuracy of the estimates, there is evidence of existing additive genetic variance for the body weight and seasonal growth traits. When more records become available the parameter estimates should be re-evaluated.

Genetic trend

Genetic trends are a very useful tool to evaluate the effects of the genetic improvement programme. Genetic trends for the body weight traits were positive over years but large variations between years were found. The latter result is due to the small number of sires used in the breeding scheme. As expected, there was little improvement during the initial years from 1994 to 1997. Genetic progress became visible after 1997. The genetic trends demonstrated that the selection was effective in realising improvement in BW, W12 and W36. The largest improvement was found in W36. This was expected because the genetic improvement programme placed much emphasis on increasing W36. The genetic trends for the traits characterising growth during seasons were generally positive but of low magnitude indicating that there has been only small genetic changes in growth during seasons since 1994. Figure 4 clearly shows the increasing trend in G15–36 and GD12–36 suggesting that the genetic improvement programme has been successful in improving growth from 15 to 36 months of age and at the same time improving the adaptability of the animal to the harsh conditions. However, as stated before, it also shows the opposite trend pattern of G15–36 and GW12–36, on the one hand, and GD12–36 on the other hand. The trends confirm the ability of the N'Dama to survive and be productive in tsetse infested areas without the aid of treatment (Murray et al 1982), but also point out the necessity to include growth from 12 months onwards.

Conclusions 

• The results presented in this study indicate that genetic variation exists between the traits. Selection on growth performance should include the clear influence of season, and thus on the genetic background to cope with the season.

Acknowledgements 

The financial support of The Netherlands Foundation for the Advancement of Tropical Research (WOTRO) and the Programme Concerté de Recherche-Développement sur L'Élevage en Afrique de L'Ouest (PROCORDEL) are greatly acknowledged. Sincere thanks are extended to Nerry Corr and Mamud Njie for providing assistance when needed. The authors also wish to thank all ITC's field assistants and herdsmen for their co-operation.

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Received 8 February 2008; Accepted 23 April 2008; Published 10 March 2009

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