Reproductive and milk yield performance of indigenous and crossbred dairy cattle breeds in Ghana as influenced by non-genetic factors

J K Hagan, B A Hagan¹ and S A Ofori

Department of Animal Science, School of Agriculture, University of Cape Coast, Cape Coast, Ghana
bernard.hagan@uenr.edu.gh
¹ Department of Animal Production and Health, School of Agriculture and Technology, University of Energy and Natural Resources, Sunyani, Ghana

Abstract

A breed development programme with the objective of increasing milk production of dairy cattle breeds in Ghana is on-going. Therefore, a study was undertaken to assess the effect of genetic and non-genetic factors on the reproductive and milk yield performance of cows. A total of 555 milk yield records from 200 Sanga and 121 Friesian-Sanga crossbred cows born between 2012 and 2018 were evaluated. The effects of breed type, season of calving and dam parity on calving interval (CI), age at first calving (AFC), age at first heat (AFH), number of days open (DO), number of services per conception (NS), daily milk yield (DMY), gestation length (GL) and lactation length (LL) were determined using the general linear model procedure of GenStat. Average CI and conception rate (CR) over the period were 81.5 days and 85.0%, respectively. The mean AFH, AFC, DO, CI, NS, DMY, GL and LL were 20.1±0.6 months, 37.3±1.3 months, 98.4±0.7 days, 417.0±12.1 days, 1.4±0.01, 3.6±0.1kg/day, 278±0.7 days and 293.4±4.1, respectively. The reproductive performances studied were significantly influenced by dam parity, season of calving and genetic group. The Friesian-Sanga cows were found to be significantly superior in terms of DMY than the Sanga breed.

Keywords: age at first calving, calving interval, daily milk yield, Friesian-Sanga crossbred, Sanga

Introduction

In tropical Ghana, indigenous dairy cattle breeds which belong to the Bos indicus genetic group are adapted to the harsh, hot and humid tropical weather conditions (Nuraddis and Ahmed 2017) and perform reasonably well under limited feed resources. The indigenous breeds are, however, low milk producers compared to the Bos taurus group. Therefore, the sole use of the indigenous cattle breeds for dairying purposes to meet the increasing milk demands of tropical countries is not sustainable, which suggests the need for crossbreeding between the Bos indicus and Bos taurus cattle breeds to benefit from the robustness of the former and the improved milk productivity of the later (Apori and Hagan 2014; Neshagaran Hemmatabadi et al 2016).

In the dairy industry, productive and reproductive characteristics of dairy cows largely determine the economic viability of the industry. The key measure or indicator of productive performance in dairy cow is the average milk yield per lactation whilst measures of reproductive performances include age at first heat (AFH), age at first calving (AFC), number of services per conception (NS), gestation length (GL), calving interval (CI) and days open (DO) (Miah et al 2018). Nuraddis and Ahmed (2017) recommend average values for CI (12 to 13.5 months), NS (1.3 to 1.5) and DO (85 days) for indigenous dairy cows in the tropics under generally low input production system. In livestock species including dairy cattle, heritability for reproductive traits are generally low, which suggest the importance of environment on milk production and reproduction parameters of cows (Nuraddis and Ahmed 2017). Since climatic and management conditions for extensively reared livestock vary over time in many tropical countries, periodic evaluation of dairy cows is important for planning, management and development purposes in the dairy industry (Mengistu et al 2016).

Domestic milk production in Ghana is one of the lowest in the West African sub-region, and is mainly from indigenous cattle breeds such as the West African Shorthorn (WASH), White Fulani and Sanga and more recently from crosses of these indigenous breeds with the Friesian and Holstein cattle breeds (FAO 2016). Besides the low genetic potentials for milk production by dairy breeds in Ghana, the industry is also confronted with other challenges such as poor nutrition and health related problems (Apori and Hagan 2014). To address these challenges, a cross breeding programme targeted at utilising the adaptive potential of the indigenous Sanga breed and the high productive potential of the exotic Friesian dairy cattle breed has been on-going in Ghana since 1997 (Apori and Hagan 2014). Initial results from this crossbreeding programme between 1997 and 2014 showed average calving intervals of between 413.6 and 517.9 days, conception rates of 46.0 to 74.0%, calving rates of 56 to 76% and average gestation length of 273 days, with an average birth weight of 22.8 to 25.7 kg (Sottie et al 2009; Guinguina et al 2011; Obese et al 2013; Apori and Hagan 2014; Obese et al 2018).

The present work, which is a sequel to the previous works on the same population, was therefore undertaken to determine the effects of genetic and non-genetic factors on milk yield and reproductive performances of the Sanga and Friesian-Sanga crossbred cows kept at the Amrahia Dairy Farm. The findings from this study would be useful to facilitate the formulation of strategies to advance the dairying industry in Ghana since the research farm is the foremost supplier of breeding and foundation stock to dairy farmers.

Materials and methods

Location of study

The study was undertaken at the Amrahia Dairy Farm which is situated at latitude 05º 44' N and longitude 00º 08' W in the Accra Plains of Ghana. The rainfall pattern of the study area is bimodal rainfall with major rainy season from April to July and minor rainy season from August to November with the remaining months making up the dry season. The study area falls within the coastal savannah vegetation type which comprise small grasses with little thickets of bushes and limited number of trees. The average yearly rainfall is between 740 mm and 890 mm with environmental temperatures ranging from 20°C to 34°C, and high relative humidity throughout the year which compensates for the scanty annual rainfall (MoFA 2012).

Management of animals

The Sanga and Friesian-Sanga crossbred cattle breeds at the Amrahia Dairy Farm were reared under the agro-pastoral system to adapt the cows to the management practices of dairy farms on the Accra Plains. The cows were accommodated in open kraals and released to graze on natural pasture comprising grasses such asPanicum maximum, Sporobolus pyramidalis and Stylosanthes haemata and browse species such as Griffonia simplicifolia, Baphia nitida and Milletia thoningii from 05.00-10.00 and 13.00-15.00 hours daily (MoFA 2012; Apori and Hagan 2014). Apori and Hagan (2014) have adequately described the management of the dairy herd at the Amrahia Dairy farm.

Data collection and trait definitions

A total of 555 milk yield records from 321 cows made up of 121 Friesian-Sanga crossbred and 200 indigenous Sanga calves born between 2012 and 2018 were used for this study. The influence of breed, season of calving and dam parity on CI, AFC, NS, AFH, average DMY, DO, GL and LL were determined. All data on cows used for this study were taken from normal births and normal calves. For season of calving, calendar months April to July constituted the major rainy season whilst August to November formed the minor rainy season with December to March making up the dry season. The data obtained were coded according to season of birth, breed type and dam parity. The traits studied were defined and described by Apori and Hagan (2014) and Miah et al (2018) as follows:

Age at first heat is the age at which the heifer had its first heat expressed in months.

Age at first calving is the age a cow had its first calf, expressed in months.

Calving interval is the time interval between two successive calvings, expressed in months.

Calving rate is the percentage of cows that calf per the number of cows inseminated.

Conception rate is the percentage of calves that conceived per the number of cows inseminated.

Service per conception is the average number of services resulting in conception.

Days open is the intervals from calving date to the date of the next heat after calving expressed in days.

Gestation length is the length of time between conception and calving expressed in days.

Lactation length is the length of time of milking after calving expressed in days.

Average daily milk yield is the average milk yield per cow per day recorded during the lactation period expressed in kilograms.

Statistical analyses

Data on productive and reproductive traits of dairy cows were analysed using the Generalized Linear Model (GLM) procedure of the GenStat (GenStat 2009) and differences between means for a given trait by a factor were separated using the least significant difference at 5% probability level. The models used for the analyses were designated as models 1 and 2. For AFC and AFH, season of calving and breed type were fitted in the model below. The statistical models used for analysing the productive and reproductive traits are presented below:

Y_ijk = μ +S_i +B_j + e_ijk

Where Y_ijk = observation on a cow in the i^th season and j^th breed (AFC and AFH)

μ = overall mean of the trait

S_i = fixed effect of the i^th season of calving (major rain, minor rain, or dry seasons)

B_j = fixed effects of the j^th breed type (Sanga or Friesian-Sanga crossbred)

e_ijk = random error associated with each observation ~N(0, σ²_e), where σ²_e is residual variance.

For data on DMY, DO, CI, NS, GL and LL, the model below was used for the analysis.

Y_ijkl = μ + B_i + S_j + P_k + e_ijkl

Where Y_ijkl = observation on a cow in the i^th breed type, j^th season of calving and k^th dam parity (DMY and other reproductive traits)

μ = overall mean of the trait

B_i = fixed effects of the i^th breed (Sanga or Friesian-Sanga crossbred)

S_j = fixed effect of j^th season of calving (major rain, minor rain, or dry seasons)

P_k = fixed effect of k^th parity of dam (1, 2, 3 or 4)

e_ijkl = random error associated with each observation ~N(0, σ²_e), where σ²_e is residual variance.

Results and discussion

The number of animals per year and the indicators of fertility of dairy cattle (Sanga and Friesian-Sanga crossbred) raised at the Amrahia Dairy Farm has been presented in Table 1.

Within the 7-year period, 394 cows were inseminated with resultant average conception and calving rates of 85.0% and 81.5%, respectively. These were higher than earlier conception and calving rates of 74.3% and 76.1%, respectively reported by Apori and Hagan (2014) and calving rate of 46.0% reported by Obese et al (2010) for the same cattle population between 1997 and 2012. The conception rate recorded in this study was also higher than 65.78±4.5% and 54% obtained by Das (2008) and Gaur et al (2002) for Red Chittagong cattle of Bangladesh and Ongole cattle of India, respectively. The higher conception rate in this study could partly be attributed to good heat detection in cows, high semen quality of bulls and appropriate timing of artificial insemination (Obese et al 2010). The conception and calving rates obtained in this study were comparable to rates reported by Madibela and Mahabile (2015) for Friesian-Holstein cows raised under similar environmental conditions in Botswana.

Age at first heat and age at first calving

Age at first heat and AFC are economically important traits that determine the ages when dairy cows begin their economic return to milk production. How early or late a heifer comes on heat or has its first calf is important because the longer it takes for a heifer to calf, longer time it will take to produce milk and cause high cost of production (Frickle 2004). Muller and Botha (2000) reported that heifers with relatively shorter AFC have higher milk production during their lifetime than those having longer AFC.

The overall mean age at first calving (37.3±1.3 months) obtained in this study was lower and better than the 41.5 months reported by Okantah et al (2006) for Sanga breed and 47.51±1.6 months for Friesian-Sanga crossbred (Guinguina et al 2011; Obese et al 2013) in Ghana, 41.1 months for Holstein-Friesian and their crosses (Mengistu et al 2016), 40.9 months for local and crossbred cattle in North Shoa zone in Ethiopia (Ayalew and Assefa 2013) and 41.2 months for Holstein Friesian-Arsi and Holstein Friesian-Boran crossbred cattle in Ethiopia (Wassie et al 2015). On the contrary, mean age at first calving in this study was higher as compared to the 30.8 months for Friesian-Bunaji crossbreds in Nigeria (Mureda and Mekuriaw 2007) and 36 months for Friesian-Holstein crossbred cows in Botswana (Madibela and Mahabile 2015).

Season of calving did not influence (p>0.05) AFC (Table 2). This concurs with earlier studies (Habtamu et al 2010; Tadesse et al 2010; Guinguina et al 2011; Obese et al 2013; Wassie et al 2015) which also did not observe any significant seasonal effect on AFC. However, Million et al (2006) and Chenyambuga and Mseleko (2009) found important influence (p<0.05) of season of calving on AFC for dairy cattle breeds in Ethiopia and Tanzania, respectively. Matings on the farm was planned such that calving would coincide with periods of abundance of fresh and nutritious forage. This may be the reason behind lower (p<0.05) AFC during the rainy seasons thank in the dry season. Even though the animals were zero-grazed during the greater parts of the day, most grass species dried up during the dry season with their resultant reduction in nutrient contents leading to decline in the quality of the grasses fed to the animals.

Breed had important (p<0.05) influence on AFC (Table 2) with crossbred cows having their first calves earlier than the Sanga cows. Earlier studies also reported important effect of breed on AFC (Mureda and Mekuriaw 2007; Sottie et al 2009). Perry (1991) reported that Bos indicus breeds reach sexual maturity at older ages than their Bos taurus counterparts.

The body weight of an animal is the key determinant of minimum age of heifer to be ready for insemination or breeding (Nuraddis and Ahmed 2017). The weight of the heifer at the time of breeding influences her weight at her first parturition. Averagely, heifers in temperate regions come on first heat from 8 to 10 months while their counterparts in the tropics reach puberty from 17 to 27 months. The overall age at first heat (20.1 months) recorded in this study is within the range expected in the tropics.

Breed had appreciable effect (p<0.05) on AFH and it was found that crossbred heifers have lower AFH than the Sanga breed. The findings agree with report by Duguma et al (2012) that Ethiopian zebu (Bos indicus) cattle reached puberty at a later age of 22.6 months compared to Bos taurus cattle and their crosses which reach sexual puberty at around 17 months of age. The wide genetic variation between the Sanga and Friesian cattle breeds ensured the exploitation of heterosis with respect to AFH.

Season of calving had important effect (p<0.05) on the age at which the heifers reached puberty, with heifers that calved in the major rainy season reaching puberty earlier than heifers that calved in the dry season. This could be attributed to the fact that season influences growth, development and availability of forages, the main source of nutrition for cattle in the tropics. Low nutrition intake, especially, in the tropics will slow the growth rate of animals and subsequently delay onset of puberty since onset of puberty is more influenced by body weight (Nuraddis and Ahmed 2017) rather than age.

Calving interval and days open

According to Madebela and Mahabile (2015), CI and DO (post-partum anoestrus) are directly related and are usually used as measures of reproductive efficiency and profitability of dairy farms. Cows in extended periods of non-productivity have increased cost associated with them in terms of feed expenditure and lost income resulting from the absence of saleable milk. For profitable dairying, shorter DO and shorter CI are recommended (Madebela and Mahabile 2015).

The overall mean CI (417.0±12.1 days) observed in this study was similar to those obtained for Friesian-local crosses (Munim et al 2006) and Friesian-Sanga crossbred (Guinguina et al 2011) in Bangladesh and Ghana, respectively. Apori and Hagan (2014) also previously reported mean CI of 414.6±13.4 days in the same herd.

However, comparatively shorter CIs of 346.8 to 411.3 days were reported by Munim et al. (2006) in Jersey-local crosses. Other authors have also reported shorter CIs of 402.6±3.0, 412 and 413 days in cattle breeds in Tanzania, Ethiopia and Ghana, respectively (Chenyambuga and Mseleko 2009; Nuraddis et al 2011; Apori and Hagan 2014).

The current CIs were, however, lower than the 453 days recorded in Teso cattle breed and their crosses with the Sajiwal and Boran in Uganda (Mulindwa et al 2006) and 562 days reported for Holstein-Friesian cattle in Ethiopia (Fekadu et al 2011). Other authors have also reported longer calving intervals for Sanga (Okantah et al 2005) and Friesian-Sanga crosses (Obese et al 2013) in Ghana.

The decline in CI with increase in dam parity agrees with the observation of Fekadu et al (2011) that CI decreased with increasing age of cows. This could partly be attributed to the inability of primiparous and earlier parity dams to meet their full nutrient requirement for re-breeding activities (Fekadu et al 2011). However, Stephen (2002) has reported that involution of uterus is prolonged in pluriparous cows as against primiparous cows and the interval from calving to first oestrus is greater in older pluriparous cows with 4 or more parturitions.

The overall mean DO (98.4±0.7 days) observed in this work was lower than the 134.84 days’ reported by Madibela and Mahabile (2015); 200.1 days by Mengistu et al (2016); 280.0 days by Melaku et al. (2011); 100.7 days by Chenyambuga and Mseleko (2009) and 135.0 days by Yifat et al (2009).

This study showed important effect (p<0.05) of breed type, season of calving and dam parity on DO and CI (Table 2). The crossbred cows had significantly shorter DO and CI compared to their indigenous counterparts. The longer DO of the Sanga breed could be attributed to the fact that the Sanga breed was not genetically developed for milk production as compared to the crossbred which possessed the genes for high milk yield (Apori and Hagan 2014).

Cows that calved in the rainy seasons recorded shorter DO and CI compared to cows that calved in the dry season. This could partly be attributed to inadequate or less quality nutrition for cows during the dry season. Nuraddis and Ahmed (2017) indicated that provision of sufficient and quality nutrition to cows prior to and during the postpartum period is important for primiparous cows due to the nutritional requirements needed for growth and milk production during the postpartum period. Inadequate or poor nutrition during postpartum period induces delayed postpartum estrus, silent estrus, delayed ovulation, decreased ovulation rate, low conception rate and increased embryonic mortality since seasonal variations in nutrition affect CI. The observed significant influence of season of calving on CI agrees with findings of Melaku et al (2011) and Apori and Hagan (2014) but disagrees with the works of several authors (Getinet et al 2009; Habtamu et al 2010; Tadesse et al 2010).

The important effect (p<0.05) of dam parity on DO is in agreement with the results of other authors (Ayalew and Assefa 2013; Chenyambuga and Mseleko 2009), but disagrees with that of Melaku et al (2011), who observed a non-significant effects of dam parity on DO. The dam parity differences on DO found in this study could be attributed to lactation stress in young growing cows in their first pregnancy. In addition, the extra nutritional requirements of early lactating cows and the ability of old cows to gain body condition quickly after calving could also explain the effects of dam parity on DO. The inability of early parity cows to consume enough feed for their maintenance, growth and production leads to lower energy balance which results in delay in the onset of postpartum heat hence relatively longer DO in young cows (Giday 2001).

Number of services per conception

The overall mean NS was 1.4 ± 0.01 (Table 3), which is comparable to values reported by Nibret (2012) and Wassie et al (2015). The 1.4 ± 0.01 was, however, lower than 1.72 for Boran and its crosses (Tessema et al 2003), 1.72 for Friesian cows in a private dairy farm in Ethiopia (Goshu et al 2007) and 1.67 for smallholder crossbreed cows in Zeway, Ethiopia (Yifat et al 2009). The reduced NS achieved observed in this study could partly be attributed to high quality of semen used for insemination, better heat detection ability and highly skilled artificial insemination technicians at the Amrahia station.

There were no seasonal differences in the NS but dam parity and breed influenced (p<0.05) the number of times a cow had to be inseminated before conceiving. The non-significant effect of season of calving on NS confirms earlier reports by Goshu et al (2007) and Hammoud et al (2010) that season has no effect on NS in Ethiopia and Egypt, respectively. Wassie et al (2015), Nuraddis et al (2011) and Ibrahim et al. (2011) however reported significant effect of calving season on NS with cows calved in the dry season requiring more inseminations before conceiving relative to cows calved during the short rainy and major rainy seasons. Similar result has been reported by supported by Yifat et al (2009) in Ethiopia.

The importance of dam parity and breed on NS corroborate the results of Yifat et al (2009) and Mengistu et al (2016). On the contrary, Wassie et al (2015), Nuraddis et al (2011) and Ibrahim et al (2011) reported no effects of breed and dam parity on NS.

The Sanga breed achieved pregnancy with fewer (p<0.05) number of inseminations compared to the Friesian-Sanga crossbred cows. This could be attributed to problems with adaptation of the crossbred cows. According to Nuraddis and Ahmed (2017), high milk yielding dairy cows do not breed quickly, have longer service periods and take a longer time to conceive. Thus, high milk yielding cows require more services per conception than do cows with low milk yields.

Gestation length and lactation length

The average GL and LL of cows were 278.4 days and 293.4 days, respectively (Table 3). The GL in this study was comparable to 277 to 280 days reported by Miah et al (2018). Genetic group (breed type) influenced the GL in this study with the indigenous breed having shorter (p<0.05) GL than their crossbred counterparts. This finding disagrees with results of Kabir and Islam (2009) and Miah et al (2018) that breed was not important determinant in the variations observed in GL. Islam et al (2006) indicated that differences in GLs due to differences in breed could be attributed to the maternal effect and foetal factors such as sex of the foetus, twinning and hormonal functions of the fetus.

The LL recorded in this study was longer than the 276.43±0.9 to 282.00±0.0 days reported by Miah et al (2018) in crossbred dairy cattle in Bangladesh. The different genetic groups differed (p<0.05) in the length of lactation with the crossbred having a prolonged lactation than the Sanga breed. This could partly be due to the positive heterotic effects of milk production conferred on the crossbred. Miah et al (2018) and Kumar and Abadi (2014), however, did not observe any significant effect of genetic group on LL.

Average daily milk yield

The primary goal of dairy farms is increased milk production. This goal aligns well with the dairy industry’s aim of attaining self-sufficiency in milk production and maximising profit in the tropics. Thus, most genetic improvement programmes of developing countries have focused on improving production performance of the dairy cattle. The daily milk yield recorded in this study was far below the 14-19 kg/day for crossbred dairy cows in Bangladesh (Miah et al 2018). The present values were, however, comparable to 3.59 kg/day reported by Sarkar et al (2007) in West Bengal, India. The mean daily milk yield of 3.6 kg/day and an average lactation length of 293.4 days, translates into a total lactation milk yield of about 1,056 kg, which is lower than 2,155±16.4 kg and 2,200 kg obtained by Hunde et al (2015) and Yosef (2006), respectively for Jersey cattle in Ethiopia and 2,229 kg for Jersey breed in Pakistan (Lateef 2007). In addition, Njubi et al (1992) also reported lactation milk yields ranging from 1257 to 1788 kg while Borland and Moyo (1996) reported yields of 3504 kg and 5141 kg per lactation for Jersey cattle in Zimbabwe. The dairy industry in Ghana is still developing with several challenges prominent among them being the use of less productive dairy breeds and poor nutrition, especially, during the dry season. This partly explains the low milk yield recorded for the genetic groups used in the present study. Crossbreeding strategy aimed at improving the milk yield is ongoing and highly productive breeds such as Friesian and Holstein are being used to cross the indigenous breeds as West African Short Horn, Sanga and White Fulani. The relatively higher milk yield performance of the crossbred Friesian-Sanga compared to the indigenous Sanga breed could be attributed to heterotic effect obtained from crossbreeding.

Dam parity had effect (p<0.05) on DMY, an observation which agrees with finding of Hunde et al (2015) who reported a progressively increasing trend in lactation milk yield with increasing dam parity. Similar observations have been reported by several authors (Yosef 2006; Tadesse et al 2010). Amimo et al (2007) and Amani et al (2007) also reported that Ayrshire and Friesian cows reach their peak milk production at the 4^th parity. Season of calving had significant (p<0.05) effect on DMY (Table 3), an observation which concurs with the findings of Madibela et al (2005) but differs from the results of Hunde et al (2015).

Conclusion

• Although the dairy industry in Ghana is at a relatively infant stage with several attempts to improve it, there has been gradual and consistent improvement in the productive and reproductive performance of the Sanga and Friesian-Sanga crossbred dairy cattle raised at the Amrahia Dairy Farm, Ghana. This is evidenced by the fact that performance indicators obtained in the present study are within the ranges considered acceptable in the tropics.
  
  
• Both genetic ad non-genetic factors significantly influenced many of the reproductive and milk production traits studied in the dairy cattle at the station.
  
  
• Due to the significant influence of environmental factors on the overall expression of the full potential of the available breeds, any attempts at improving the productive and reproductive performances of the breeds must take into consideration management and dry season feeding.

Acknowledgement

The authors would like to express their profound gratitude to the Amrahia Dairy Farm of the Ministry of Food and Agriculture for making their data available for the work.

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