Genetic analysis of milk yield by fixed and random regression models in Shirvan Kurdi sheep

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KAZEMI BORZEL ABAD F.; HASSANI S.; SAMADI F.; AHANI AZARI M.; SAGHI D.A.

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Journal: ANIMAL SCIENCE RESEARCHES (FACULTY OF AGRICULTURE, UNIVERSITY OF TABRIZ) Year:2018 | Volume:28 | Issue:2 Page(s): 127-141

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Title

Genetic analysis of milk yield by fixed and random regression models in Shirvan Kurdi sheep

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Keywords

Milk yieldQ2

Random regressionQ2

SheepQ2

Test day modelQ2

Abstract

Introduction: Estimates of the amount of milk produced by lactating ewes provide information for the implementation of optimum management and feeding strategies for ewes and their lambs. Lamb survival and subsequent birth weight gains until weaning reﬂ ect milk production abilities of ewes. Genetic evaluation of Milk yield traits in dairy Sheep may be based on whole lactation records (Rahman Ahmad, 2010) or test day records (Horstick et al. 2001; Komprej et al. 2009; Carlos 2014). The Random regression method of data analysis seems to be the most appropriated technique to apply in longitudinal data including growth and milk production and the corresponding models have been incorporated in animal breeding for the estimation of breeding values (Schaeffer, 2004). The main objective of this study was genetic analysis of test day milk records for Kurdi ewes of Shirvan Kodri Sheep breeding station using fixed and Random regression models. Matherial and methods: Kordi Sheep is an Iranian fat-tailed native breed developed mainly for meat production but produce milk and wool production as well. This breed is distributed in North Khorasan Province of Iran and is mainly grown traditionally by nomadic people in pastures. Kordi Sheep breeding station is located in Shirvan city, North Khorasan Province, Iran. This station was established in 1988. The breeding system in this station is semi-intensive. Considering local weather conditions, lambs and ewes are usually sent to the pastures around the station for daily grazing in late April. Sheep are grazed in the pasture until early July and during the wheat and barley harvest in farm lands of the town. With the onset of the cold season the herd is transferred to the station, and by setting appropriate diets each animal group (pregnant ewes, male and female lambs and rams) is fed separately and manually three meals a day. Mating season is from mid August to late October and the lambing begins in early January and continues until late March (Saghi et al, 2014). Data included 1124 test day records of Milk yields collected from 250 Kurdi ewes. Milking was carried out by hand combined with lamb suckling at 14 days intervals starting from May to August 2012. General linear model was used to identify effective fixed effects on the trait by SAS 9. 1 software. Fixed effects of litter size, parity and month of recording and random effects of direct genetic and permanent environmental effects were included in the models. Variance and covariance components were estimated using restricted maximum likelihood procedure. Genetic analysis of Milk yield was carried out using fixed and Random regression models by Wombat software. Results and discussion: Average Milk yield of studied Kurdi ewes was 0. 38 kg. Average heritability estimates of Milk yield were 0. 04 and 0. 07 in fixed and Random regression models, respectively. In Random regression model, the highest and the lowest heritability estimates were found at 14 (0. 18) and 84 (0. 006) days, respectively. Heritability of Milk yield was higher in the first than in the second part of lactation period. Repeatability of Milk yield in different days of lactation was ranged from 0. 51 (day 28) to 0. 89 (day 126). Genetic correlations between Milk yields at different days in milk were ranged from-0. 942 to 0. 999. Permanent environmental correlations between Milk yields at different days in milk were ranged from-0. 850 to 0. 920. Milk yield additive genetic and permanent environmental correlations between adjacent test days were more than between distant test days. Kominakis et al. (2001) were found low heritabilities for Milk yields in different days of lactation for dairy ewes (0. 05 to 0. 25). Komprej et al. (2013) were also reported estimated heritabilities of Milk yields in different days for Slovenian dairy Sheep ranged from 0. 08 to 0. 16. Lower genetic correlations between Milk yields at different days with increase in intervals between test day records were also found by other researchers (Zavadilova et al. 2005; Madad et al. 2013). Conclusion: Results indicated that Kordi Sheep has a relatively good potential for milk production among Iranian native Sheep breeds. For Milk yield in the studied population, orthogonal Legendre polynomials of order 2 and 3 for additive genetic and permanent environmental effects, respectively, was found the most appropriate model. Considering low heritability of Milk yield, improvements in environmental conditions could result in increasing Milk yield performance in the studied flock. Lower genetic correlations with increase in intervals between test-day records may suggest that different genes are involved in Milk yield in different days of lactation.

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APA: Copy

KAZEMI BORZEL ABAD, F., HASSANI, S., SAMADI, F., AHANI AZARI, M., & SAGHI, D.A.. (2018). Genetic analysis of milk yield by fixed and random regression models in Shirvan Kurdi sheep. ANIMAL SCIENCE RESEARCHES (FACULTY OF AGRICULTURE, UNIVERSITY OF TABRIZ), 28(2 ), 127-141. SID. https://sid.ir/paper/397141/en

Vancouver: Copy

KAZEMI BORZEL ABAD F., HASSANI S., SAMADI F., AHANI AZARI M., SAGHI D.A.. Genetic analysis of milk yield by fixed and random regression models in Shirvan Kurdi sheep. ANIMAL SCIENCE RESEARCHES (FACULTY OF AGRICULTURE, UNIVERSITY OF TABRIZ)[Internet]. 2018;28(2 ):127-141. Available from: https://sid.ir/paper/397141/en

IEEE: Copy

F. KAZEMI BORZEL ABAD, S. HASSANI, F. SAMADI, M. AHANI AZARI, and D.A. SAGHI, “Genetic analysis of milk yield by fixed and random regression models in Shirvan Kurdi sheep,” ANIMAL SCIENCE RESEARCHES (FACULTY OF AGRICULTURE, UNIVERSITY OF TABRIZ), vol. 28, no. 2 , pp. 127–141, 2018, [Online]. Available: https://sid.ir/paper/397141/en

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