Phenotypic and genetic parameters of milk traits of Fogera cattle in Ethiopia

Demelash Kassahun^1,2, Damitie Kebede², Aynalem Haile³, Adebabay Kebede², Assemu Tesfa², Mekonen Tilahun², Addisu Bitew², Tewodros Bimrow², Eyasu Lakew², Mulugeta Meseret², Zeleke Tesema⁴ and Mengistie Taye^2,5

¹ Andassa Livestock Research Center, P.O. Box 27, Bahir Dar, Ethiopia
² College of Agriculture and Environmental Sciences, Bahir Dar University, P O Box 5501, Bahir Dar, Ethiopia
mengistietaye@gmail.com
³ International Center for Agricultural Research in the Dry Areas (ICARDA), P O Box 5689, Addis Ababa, Ethiopia
⁴ Sirinka Agricultural Research Center, P O Box 74, Sirinka, Ethiopia
⁵ Biotechnolgy Research Institute, Bahir Dar University, P O Box 79, Bahir Dar, Ethiopia

Abstract

This study was conducted to estimate the production performance and the genetic parameters for milk traits of Fogera cattle at Andassa Livestock Research center. Data collected on milk production traits from 2000 to 2017 from Fogera cattle herds maintained at Andassa Livestock Research Center were used. The General Linear Model (GLM) procedure of SAS was used to analyze the least-squares mean for phenotypic traits, and Wombat software was used to estimate genetic parameters and breeding values. The performance milk traits analyzed include daily milk yield (DMY), lactation milk yield (LMY), and lactation length (LL). Dam parity, calving year and season were the main fixed effects considered for performance estimation of the milk traits.

The overall means for DMY, LMY, and LL obtained were 1.98±0.40 liters, 482±0.02 liters, and 238±0.3 days. The direct heritability estimates for DMY, LMY, and LL of Fogera cows were 0.33±0.27, 0.27±0.001, and 0.20±0.23. The repeatability estimates for DMY, LMY and LL were 0.33, 0.55, and 0.48. The phenotypic correlation for DMY-LMY, DMY-LL, and LMY-LL were 0.49, 0.48, and 0.55, while the genetic correlations were 0.53, 0.46, and 0.53 The mean breeding values for DMY, LMY and LL were 0.016 liters, 18.77. liters and 4.30 days. LMY increased by 0.86 liters/year while the DMY and LL decreased by 0.0008 liters/year and 0.17 days/year. Both, heritability and repeatability estimates for milk production traits indicate the presence of moderate variation within the studied cattle population and thus selection could be used as the best tool of genetic improvement of Fogera cattle for milk production.

Keywords: estimated breeding value, genetic trend, heritability, lactation length

Introduction

With its diverse and suitable agro-ecological zones, Ethiopia has been recognized for its huge and diverse (35 cattle breeds) genetic resources ( http://dagris.ilri.cgiar.org/). Despite this, the contribution of the sector to the livelihood of farm households and the country is below what is expected due to several factors including high prevalence of disease, feed shortage, and low productive potential of local breeds. With this regard, the government of Ethiopia has initiated breed improvement programs through selective breeding.

Fogera cattle is Zenga cattle adapted to the Fogera plains around Lake Tana with characteristics of: docile use for draft, meat and milk; short stumpy pointed horns; hump ranging from thoracic to cevico-thoracic; folded to moderately large dewlap; and black-and-white or black-and-gray coat color (Rege and Tawah 1999). Fogera cattle, because it is selected for environmental adaptation, its production and productivity is low. The Andassa Livestock Research center has been working on the improvement of Fogera cattle through selective breeding.

The potential for genetic improvement of a trait largely depends on genetic variation existing in the population of the study. Understanding the potential of indigenous cattle and identification of responsible factors for milk production is essential to improve the milk production performance. Previously, the milk production performances of Fogera cattle under station management conditions was reported by Bitew et al (2010). However, information on the genetic parameter estimates of milk production traits of Fogera cattle is lacking. Therefore, the aim of this study was to estimate phenotypic, genetic parameters and breeding values for milk traits of Fogera cattle at Andassa Livestock Research Center.

Material and methods

Description of the study area and herd management

Milk production data of Fogera cattle collected from 2000 to 2017 from Andassa Livestock Research Center in Ethiopia were used. The center is located in Amhara National Regional State at 11⁰29’ north latitude and 37⁰29’ east longitude, at an elevation of 1730 meters above sea level. The average annual rainfall is 1150 mm, and the temperature ranges from 6.5 ^OC to 30 ^OC.

Cattle in the center were allowed to graze natural pasture for 8 hours, and during the dry season, they were provided with hay harvested from the natural pasture. Animals were watered from Andassa river. The mating system was natural, a bull being assigned to 40-50 Fogera cows based on pedigree information. Herd groups were managed based on age, sex, breed and physiological status of the animal. Calves after birth had free access to suckle their dams for 4 days to consume enough colostrum. Then calves were separated from their dams and allowed to partially suckle (two teats) at milking times until weaning age of 8 months. Cows were partially hand-milked (two teats) twice a day at about 6:00 AM in the morning and 4:00 PM in the afternoon. The total milk yield produced per day was calculated by doubling the daily milk yield.

Data source and management

Milk data (daily milk yield, lactation milk yield, and lactation length) collected and recorded in a herd book from 2000 to 2017 were used. The data were filtered and organized using Microsoft Excel. Records with no pedigree information were removed during data cleaning.

Statistical analysis

The data were analyzed using the General Linear Model (GLM) procedures of the Statistical Analysis System (SAS 2004). Dam parity, calving year, and season were the main fixed effects considered. WOMBAT software (Meyer 2012) was used to estimate the genetic parameters of heritability, repeatability, genetic and phenotypic correlation.

The statistical model used for the analysis of least squares means of milk traits was:

Y_ijk = µ+Y_i+S_j+P_k+e _ijk

Where:

Y_ijk = The observation on daily milk yield (DMY), lactation milk yield (LMY), and lactation length (LL)

µ = Overall mean,

Y_i = fixed effect of i^th calving year (2000-2017)

S_j = fixed effect of j^th calving season (dry, wet)

Q_k = fixed effect of k^th parity (1-7)

e_ijk = effect of random errors associated with each observation.

The model used to estimate variance components and heritability of milk traits was as follow:

Y = Xb + Za + Wpe + e

Where, Y is the vector of observations of the traits (DMY, LMY, and LL), b is the vector of fixed effects, a is the vector of solutions for the coefficients of direct animal (additive) genetic effects, pe is the vector of solution for permanent environmental effects and e is was the vector of residual effects. X, Z, W are the correspondent incidence matrices of the fixed effects, additive genetic and permanent environmental random effects, respectively.

The heritability and repeatability were computed as follows:

h² = σa²/ σp² and r = σa ² + σpe²/ σp²

Where: h² is heritability, r is repeatability, σa² is direct additive genetic variance, σpe² is permanent environmental variance related to repeated records and σp² is phenotypic variance (Falconer and Mackay 1996). The genetic trends for milk traits were estimated by averaging the estimated breeding value estimated by year of birth. The pedigree information and the descriptive statistics are presented in Table 1 and Table 2, respectively.

Results and discussion

The effect of non-genetic factors on milk production traits

Daily milk yield

The overall mean of daily milk yield of Fogera cattle was 1.98±0.2 liters (Table 3). This result is higher than the result (1.7±0.1 liters) reported for Boran cattle under on-station management (Haile et al 2009), 1.8±0.84 liters for Kereyu cattle (Garoma et al 2014) and 1.6±0.5 liters for highland Zebu around west Gojjam under on-farm conditions (Minuye et al 2016). On the other hand, higher result for daily milk yield was reported for Barca cattle breed (2.98±0.69 liters) by Tadesse and Dessie (2003), for Arsi (2.7 liters) and for Zebu cattle (2.8 liters) by Kiwuwa et al (1983). The mean here obtained is also lower than the reports (2.8±0.15 liters/day) for Boran cattle (Demeke et al 2004) and 2.2±0.5 liters/day for local cattle breed at Beddelle areas (Gelmessa et al 2013).

Parity had a significant effect on daily milk production of Fogera cattle ( p<0.001). This result is in line with the previous results of Bitew et al (2010) for Fogera cattle and Demeke et al (2004) for Ethiopian Boran cattle. Cows with lower parities had lower daily milk yield than those of higher parities. This might be because the size of udder and teats increased with the maturity of the cows and subsequently the milk production capacity increased with parity. However, this result contradicts the study of Bayou et al (2015) who noted that parity of cow had a non-significant effect on daily milk yield of Boran cattle.

The year of calving had an effect on daily milk yield (p<0.001). A similar result was reported by Bitew et al (2010) and Demeke et al (2004).

The overall mean lactation milk yield was 489±7.50 liters (Table 3). This figure is lower when compared with results for the other indigenous cattle breeds of Ethiopia. For instance, it was much lower than the average yield reported by Kiwuwa et al (1983) for Arsi cattle (809 liters) and for Zebu cattle (929 liters) and also lower than the report of Demeke et al (2004) for Boran cattle (529±65 liters). The present result is lower than 507±39 liters for Boran cattle (Haile et al 2009) and 672±196 litters for Zebu*HF crosses (Tadesse and Dessie 2003). The lower lactation milk yield for Fogera cattle may be due to the reason that milking persists only for eight months of lactation as the weaning age of Fogera calves is at eight months.

Parity had a significant effect on the lactation milk yield (Table 3). The finding of this study showed a consistent increase in milk yield with increasing yield up to the fifth parity and declined thereafter. This result was supported by the previous reports of Bitew et al ( 2010), Demeke et al (2004) and Bayou et al (2015). Udder development increases as the age of cows advances till maturity so that the mammary gland of cows with higher parities can produce more milk than in the case of cows of lower parities.

Lactation length

The overall mean lactation length was 243±0.3 days (Table 3). The lactation length of indigenous cattle ranged from 193±6 days for Boran (Demeke et al 2004) to 303 days for Zebu (Kiwuwa et al 1983). Lactation length of 305 days is usually accepted as a benchmark in modern dairy farms. However, the lactation length of Fogera cattle was lower than most of the other indigenous breeds due to the weaning age of Fogera calves at 8 months.

Parity had no effect on the lactation length. This result contradicts with the results of Demeke et al (2004) and Bitew et al (2010). However, cows that calved in the dry season had shorter lactation length than those calved during the wet season, which is in with the results of Bitew et al (2010) and Bayou et al (2015). This could be associated with the availability of feed resources i.e. the availability of feed is better during the wet season than dry season.

The variation of lactation length with the different years might be explained by the variation of annual rainfall, which directly or indirectly is associated with the availability of feeds.

Variance component and heritability estimates for milk yield traits

The direct heritability estimates for DMY, LL and LMY were 0.33±0.27, 0.20±0.23 and 0.27±0.001, respectively (Table 4). The current estimate for milk yield is lower than the value (0.34±0.13) reported for Ethiopian Boran cattle by Gebreyohannis et al (2014) and that reported by Haile et al (2009). The present direct heritability estimate for lactation length is lower than that (0.26) of Ethiopian Boran cattle reported by Haile et al (2009). However, the heritability of lactation length for Ethiopian Boran and Horo breeds reported by (Gebreyohannes et al 2013) was lower than the present study. The observed moderate level of heritability estimates for milk traits indicates that there is enough variation within the study population and confirms the possibility of genetic improvement through selection.

Repeatability (r) of milk traits

The repeatability estimates for milk yield (Table 4) are lower than reported by Haile et al (2009) for Ethiopian Boran cattle and higher than reported by Gebreyohannes et al (2013) for Horro and their crossbreds. The repeatability estimates of lactation length (Table 4) are lower than the result (0.13 ± 0.17) reported for Mpwapwa cattle (Chawala et al 2017) and that (0.46) noted by Haile et al (2010) for Boran cattle. The estimated repeatability of lactation milk yield and lactation length was highly repeatable while daily milk yield was moderately repeatable. Therefore, selection and culling of animals based on their lactation milk yield performance could be carried out with a reasonable degree of accuracy.

Phenotypic and genotypic correlation among milk traits

Moderate phenotypic and genetic correlations were observed between daily milk yield and lactation milk yield (Table 5). Haile et al (2009) reported higher phenotypic correlation between daily milk yield and lactation length (0.78±0.12); and daily milk yield and lactation milk yield (0.57±0.23) of Ethiopian Boran cattle. The authors also reported a higher genetic correlation (0.57) between daily milk yield and lactation milk yield than the current estimates. The current genetic correlation estimates indicate that selection for one of the traits could have a moderate effect on the other traits through correlated responses.

Breeding value estimates for milk production trait

The estimated mean breeding values for daily and lactation milk yield and lactation length were 0.02 liters, 10.3 liters and 6.64 days, respectively (Figures 1 and 2). Means of estimates of breeding value by year of birth for the studied traits showed the opposite trend; the highest estimated mean breeding value (0.068 liters) for daily milk yield was observed in 2013 whereas the lowest estimated mean breeding value (-0.02) was observed in 2005. The breeding value for lactation milk yield ranged from -25.2 to 64.1 liters while the breeding value for lactation length was between 2.0 and 11.7 days. The high ranges of breeding values for milk production traits maybe because of the existence of high and low producing cows with the absence of culling and due to non-efficient breeding programs.

Figure 1. Estimated genetic trend for daily and lactation milk yield of Fogera cows at Andassa Livestock Research Center

Figure 2. The estimated genetic trend for lactation length of Fogera cows at Andassa Livestock Research Center

Lactation milk yield increased by 0.86 liters/year while the DMY and LL genetically decreased by 0.0008 liters/year and 0.17 days/year, respectively. The decreasing trend for DMY and LL implies inefficiency in selection based on phenotypic performance and absence of proper culling of unproductive cows. In addition, environmental stresses (heat stress, low quality and quantity of nutrition) and lack of accurate pedigree structure of the herds could be the possible reasons. Researchers and experts should think how to reverse the trend through an appropriate and accurate method of selection.

Conclusions

• The heritability of milk traits of Fogera cattle was medium which indicated the possibility of selection.
  
  
• Moderate to high repeatability estimates suggest that a relatively large contribution of additive genetic variance and successful selection could be feasible for that trait.

Acknowledgment

The authors would like to thank Andassa Livestock Research Center and Amhara Region Agricultural Research Institute (ARARI) for financing this research work.

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Received 9 December 2019; Accepted 27 January 2020; Published 2 March 2020

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