برآورد روند و پارامترهای ژنتیکی برای تداوم شیردهی گاوهای هلشتاین در ایران

نوع مقاله : علمی پژوهشی- ژنتیک و اصلاح دام و طیور

نویسندگان

1 گروه علوم دامی، دانشکده کشاورزی، دانشگاه صنعتی اصفهان

2 گروه علوم دامی، دانشکده کشاورزی، دانشگاه شهرکرد

چکیده

به منظور تخمین پارامترهاو روند ژنتیکی تداوم شیردهی از تعداد 2487378 رکورد روز آزمون متعلق به336164 راس گاو هلشتاین شکم اول ایران متعلق به 2581 گله که در طی سال‌های 1371 تا 1391 زایش داشتند، استفاده شد. برای محاسبه تداوم شیردهی از پارامترهای برآورد شده تابع وود، توسط نرم‌افزار R استفاده گردید. آنالیز عوامل موجود در مدل جهت ارزیابی ژنتیکی تداوم شیردهی با کمک نرم‌افزار SASانجام گردید که همگی معنی‌دار بودند. اجزای واریانس ژنتیکی افزایشی، فنوتیپی و وراثت پذیری براساس مدل دام تک صفته با استفاده از نرم‌افزار WOMBAT محاسبه گردیدند. واریانس ژنتیکی افزایشی، فنوتیپی ووراثت پذیری صفت مزبور به ترتیب 03/0، 37/0 و 08/0 برآورد شدند. مقادیر روندهای ژنتیکی و فنوتیپی به ترتیب حدود 01/ و 022/0 برآورد شدند که هر دو از لحاظ آماری معنی دار بودند. نتایج این پژوهش نشان داد که روند ژنتیکی و فنوتیپی تداوم شیردهی در گاوهای هلشتاین ایران مثبت و مطلوب بوده است.

کلیدواژه‌ها


عنوان مقاله [English]

Estimation the Trend and Genetic Parameters of Persistency of Holstein Cows

نویسندگان [English]

  • somayeh hasanvand 1
  • hossein mehrban 2
  • Ali Sadeghi-Sefidmamazgi 1
1 Department of Animal Sciences, Collage of Agriculture, Isfahan University of Technology
2 Department of Animal Sciences, College of Agriculture University of Shahr kord
چکیده [English]

Introduction: Lactation yield and persistency are two economic important traits in dairy cow. The production level of a dairy cow is determined by a joint effect of genetic and environmental factors.The main factors determining the total amount of milk production are milk yield at the peak of lactation and persistency as well as length of lactation period. Persistency are defined as a extent to which early lactation milk is preserved(22), orability of cow to produceat a high level of milk during lactation period(8). Also, it’s defined as adecreasing rate of milk production after peak, that more milk Persistency means lower rate of milk yield (31).Persistency is as an economic important trait in dairy cattle because of therelationship between I tandother traits such as production, Reproduction, Health costs and Nutrition (28). In general, Selecting on milk production is caused weak reproductive performance(9 and 11), more Sensitivity to expose disease and increasing risk of culling due to it (11). One possible way to increase milk production without increasing the incidence of diseases and reproductive problems is to select for persistency as well as milk production. This strategy may be reduced stress of peak production and maintain high production after the peak.as a result of this selection,the lactation curve is flatter and persistency increases (17 and 24). So far, various functions and models are used to evaluate the appropriate daily milk production in dairy cows,Such that it can be pointed to exponential functions. The most famous application of this method was invented by Wood in 1967(15). Persistency would be estimated and evaluated by considering shape of lactation curve for each animal. The objective of present study was to estimate genetic parameters and trend of milk persistency for Holstein cows in Iran using Wood’s function.
Material and methods: Data consist of 2487378 test day of milk yield belonging to 336164 primiparous Holstein which calved from 1992 to 2012. At the first, persistency was estimated based on lactation curve parameters by the Wood’s function (32), mathematical form This function is as follows:
= where, Yt: daily milk yield in tth days in milk, t: Days In Milk, e: The exponential number, a: a parameter representing yield at the beginning of Lactation, b and c: Factors associated with the up ward and down ward slopes of the curve, respectively.
The Dim at peak production was defined as: Tmax = (b/c), expected maximum yield (peak production) was calculated as: Ymax= a( b/c)b e-b, Persistency was calculated as: S = -(b+1) ln(c).
The next step data were edited based on below conditions: animals were remove if they had two time calving
only animals were evaluated that had at least 4 test day records, lactation period was limited from 5 to 305.
parameters of lactation curve were estimated by nonlinear method in R software,then its variance components were estimated by REML method (AI-REML) under univariate animal model in wombat software .
The model for genetic evaluation of milk persistency was as follows:

yijlklmn:observation of kthanimal Persistency, ithMilking frequency (MF),jthherd-year-season of calving, lthage of first Calving and mthDays In Milk (DIM), MFi:Fixed effect of Milking Frequency, AFCijk:Fixed effect of Age at First Calving as a covariate variable, DIMijk:Fixed effect of Days In Milk as a covariatevariable, bn:nthregression coefficients, HYSj:jthherd-year-season of calving which was considered as a random effect, ak:Random additive genetic effect ofkthanimal, eijk:Random residual effect .
Results and Discussion: In general, amount of milk yield in beginning of the lactation was 14.19 kg (parameter of ) with an increasing steep (parameter of ) about 0.278 kg/day as well as 0.003 decreasing rate (parameter of ) in Holstein dairy cattle. time to peak (Tmax) and milk yield at peak (Ymax) were 91 day and 33 kg, respectively. Heritability of persistency was low and estimated about 0.08 (table 1). Results showed that phenotypic and genotypic trends were significant (p < 0.05) and estimated 0.022 and 0.01, respectively (table2).


Table 1- heritability, additive genetic variance and phenotypic variance persistency of Holstein cows
trait Heritability ± SE Additive genetic variance ± SE
Phenotypic varianc ± SE

persistency 0.08 ± 0.004
0.03 ± 0.0014 0.37 ± 0.001

Table 2-Phenotypic and genotypic trends of Persistency
trait Genetic trend ± SE
R2 Phenotypic trend ± SE
R2
persistency 0.01 ± 0.001
0.93 0.022 ± 0.0006
0.96

Conclusion: Low heritability of Persistency show that interested trait is affect by environmental effects compared with genetic effect. Therefore, for increasing Persistency of milk yield should be more pay attention to improve environmental factors such as herd health and animal nutrition. The results of the present study shows that the genetic and phenotypic trends milk persistency of Holstein cows were positive and favorable

کلیدواژه‌ها [English]

  • Variance components
  • milk production traits
  • Heritability
1- Atashi, H. M, Moradi shahr Babak, A. Moghimi esfand Abadi. 2007.Evaluation the trend of milk yield change indoring with used of mathematical functions in Iranian of Holstein. 38(1): 67-76. IJASR.(In persion)
2- Ezadkhah, R. H., F. Arhangfar, M. Fathi Nasri and H. Naeimi por younes. 2011.Using a willaing function in genotypic analysis 305 days production traits and persistency Holstein dairy cows in khorasan razavi.3(3): 297-303..(In persion)
3- Bakhtiarzade, M., M. Moradi shahr Babak. 2010. Estimeated curve lactation parameters using an incomplete gamma function and nomination udder triat their genetic relationships with in Iranian of Holstein cows .41(1)1-10..(In persion)
4- Atashi, H. 2003. Determination of the best lactation curve function in Iranian ofHolstein dairycattle.M.Sc. thesis. Fac. Agric. Tehran Univ., Iran.
5- Araujo, C., R. F. Euclydes, C. N. Costa, R. D. Torres, P. S. Lopes, and C. S. Pereira. 2007. Genetic evaluation for persistency of lactation in Holstein cows using a random regression model. Genetic and Molecular Biology.65:349-355.
6- Bar-Anan, R., and M. Ron. 1985. Association among milk yield, yield persistency, conception, and culling of Israeli Holstein dairy cattle. J. Dairy Sci. 68:382–386.
7- Boostan, A. 2005.Comparsion of lactation curve functions and lactation persistency criteria with daily milk records. M. Sc. thesis. Fac. Agric. Tehran Univ., Iran.
8- Cupps, P., H. H. Cole and W. H. Freeman. 1966. Breeds of dairy cattle. in: Introduction to Livestock Prod.2nd Edition. San Francisco.
9- Castillo-Juarez, H., P. O. Oltenacu, R. W. Blake, C. E. Mcculloch, and E. G. Cienfuegos- Rivas. 2000. Effect of herd environment on the genetic and phenotypic relationships among milk yield, conception rate and somatic cell score in Holstein cattle. J. Dairy Sci. 83:807-819.
10- Dekkers, J. C. M., J. H. Ten Haag, and A. Weersink. 1998. Economic aspects of persistency of lactation in dairy cattle. Livest. Prod. Sci. 53:237–252.
11- Dematawewa, C. M. B. and P. J. Berger. 1998. Genetic and phenotypic parameters for305-day yield, fertility and survival in Holsteins. J. Dairy Sci. 81:2700–2709.
12- DeVries, A. 2006. Economic value of pregnancy in dairy cattle. J. Dairy Sci. 89:3876-3885.
13- Farhangfar, H. P. and P.Rowlinson.2007.Genetic analysis of woods lactation curve for Iranian Holestein heifers. Journal of Biological Science. 7: 127-135.
14- Gengler, N .1995 .Use of mixed models to appreciate the persistency of yield duringthe lactation of milk cows. Ph. D. Thesis. Faculteuniversitaire de SciencesAgronomiques de Gembloux, Gembloux, Belgium, 231pp.
15- Gengler, N .1996 .Persistency of lactation yields review .proc. international workshop on genetic improvement of functional traits in cattle. gembloux, Belgium.Interbull bulletin. No 12. Uppsala, Sweden. pp. 87-96.
16- Gengler, N., A. Tijani, G. R. Wiggans, J. C. Philpot. 2001. Indirect estimation of covariance functions for test-day yields production traits. during first and second lactations in the United States. J. Dairy Sci. 84, Available: http: / /www.adsa.org.
17- Haile-Mariam, M., P. J. Bowman and M. E. Goddard. 2003. Genetic and environmental relationships among calving interval, survival, persistency of milkyield and somatic cell count in dairy cattle. Livest. Prod. Sci. 80:189–200.
18- Jakobsen, J. H., P. Madsen, J. Jensen, J. Pedersen, L. G. Christensen, and D. A. Sorensen. 2002. Genetic parameters for milk production and persistency for Danish Holsteins estimated in random regression models using REML. J. Dairy Sci. 85:1607–1616
19- Khorshidie, R., A. A. Shadparvar, N. Ghavi Hossein-Zadeh, and S. Joezy Shakalgurabi. 2012. Genatic trends for 305-day milk yield and persistencyin Iranian Holsteins. Livest. prod. Sci. 144: 211-217.
20- Leon Velarde, C. U., I. McMilan, R. D. Gentry and J. W. Wilton. 1995. Models for estimating typical lactation curves in dairy cattle. J. Anim. Breed. Genet.112:333-340.
21- Madsen, O. 1975.A Comparison of some suggested measures of persistency of milk yield in dairy cows. Anim. Prod. 20:191-197.
22- Mahadevan, P. 1951. The effect of environment and heredity on lactation.II.Persistency of lactation. J. Agric. Sci. 41:89–93.
23- Meyer, K., and M. Kirkpatrick. 2005. Quantitative genetics of curvaceous traits. Phil. Trans. R. Soc. B. 360:1443-1455.
24- Muir, B. L., J. Fatehi and L. R. Schaeffer. 2004. Genetic Relationships betweenpersistency and reproductive performance in first-lactation Canadian Holsteins. J.Dairy Sci. 87:3029–3037.
25- Papajacsik, I. A., and J. Bodero. 1988. Modeling lactation curve of Friesian cows in asubtropical climate. Anim. Prod. 47:201-207.
26- Sherchand, L. R.,W. McNew, D. W. Kellogg, and Z. B. Johnson. 1995. Selection of a mathematical model to generate lactation curves using daily milk yields of Holstein cows. J. Dairy Sci. 78:2507-2513.
27- Slama, H., M. E. Wells, G. D. Adams, and R. D. Morrison.1976. Factors affecting calving interval in dairy herds. J. Dairy Sci. 59:1334-1339.
28- Swalve, H. H. and N. Gengler, 1999.Genetics of lactation persistency. Pages 75–82 in Metabolic Stress in Dairy Cows. J. D. Oldham, G. Simm, A. F. Groen, B. L. Nielsen, J. E. Pryce, and T. L. J. Lawrence, ed. BSAS occasional publication 24. Br. Soc. Anim. Sci. Penicuik, UK.
29- Turner, C. W. 1925.A quantitative form of expressing persistency of milk or fatsecretion. J. Dairy Sci. 9:203-214
30- Tekerli, M., Z. Akinci, I. Dogan and A. Akcan. 2000. Factors affecting the shape oflactation curves of Holstein cows from the balikesir Province of Turkey. J. Dairy Sci. 83:1381-1386.
31- Togashi, K., and C. Y. Lint. 2009. Economic weights for genetic improvement of lactation persistency and milk yield.J. Dairy Sci. 92:2915–2921.
32- Wood, P.D.P. 1967: Algebraic model of the lactation curve in cattle. Nature 216: 164-165.
33- Weller, J. I., and E. Ezra. 2004. Genetic analysis of the Israeli Holstein dairy cattle population for production and nonproduction traits with a multitrait animal model. J. Dairy Sci. 87:1519-1527.