تجزیه و تحلیل بقاء و همبستگی آن با صفات وزن بدن و متوسط افزایش وزن در بلدرچین ژاپنی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه علوم دامی، دانشکده کشاورزی، دانشگاه زابل، زابل، ایران

2 پژوهشکده دام‌های خاص، دانشگاه زابل، زابل، ایران

3 بخش تحقیقات علوم دامی، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی خراسان رضوی، سازمان تحقیقات، آموزش و ترویج کشاورزی، مشهد، ایران

چکیده

این تحقیق با هدف تجزیه و تحلیل بقاء و ارتباط آن با صفات وزن بدن و متوسط افزایش وزن بدن در بلدرچین ژاپنی انجام شد. بدین منظور از داده ­های 1854 بلدرچین ژاپنی طی 4 نسل از سال­ های 96 تا 98 که در مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی خراسان رضوی جمع ­آوری شده بود، استفاده گردید. برای تعیین اثرات عوامل مؤثر بر بقاء و محاسبه ریسک حذف در زمان­ های مختلف از دو بسته آماری (Survival) و (cmprsk)و برای برآورد مؤلفه ­های واریانس صفت بقاء از بسته نرم ­افزاری MCMCglmm استفاده شد. پارامترهای ژنتیکی صفات با استفاده از تجزیه و تحلیل تک و دو صفتی از طریق نمونه­ گیری گیبس برآورد شد. میانگین مرگ و میر دوره پرورش (0/206) و متوسط نرخ بقاء (0/793) محاسبه شد. میانگین وراثت­ پذیری برآورد شده برای بقاء در تجزیه و تحلیل تک صفتی و دو صفتی به ترتیب 0/216 و 0/153 محاسبه شد. دامنه وراثت­ پذیری وزن بدن در تجزیه و تحلیل تک صفتی بین 0/307 تا 0/135 با میانگین 0/219 برآورد شد. در تجزیه و تحلیل دو صفتی وراثت ­پذیری وزن بدن در محدوده 0/014- 0/155 متغیر بود. بالاترین همبستگی ژنتیکی، 0/3113- (بین صفت وزن بدن و افزایش وزن روزانه) و پایین ­ترین میزان همبستگی ژنتیکی، 0/0227 (بین صفت بقاء و افزایش وزن روزانه) بود. نتایج نشان داد مدیریت بهینه عوامل محیطی در کاهش خطر حذف اثرگذار هستند و انتخاب ژنتیکی برای صفت بقاء می­ تواند باعث بهبود پتانسیل ژنتیکی بقاء گردد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Survival analysis and its correlation with body weight and Average Daily Gain traits in Japanese quail

نویسندگان [English]

  • Razieh Saghi 1
  • Mohammad Rokouei 1
  • Gholam Reza Dashab 1
  • Hadi Faraji Arough 2
  • Davoud Ali Saghi 3
1 Department of Animal Sciences, Faculty of Agriculture, University of Zabol, Zabol, Iran
2 Research Center of Special Domestic Animals, University of Zabol, Zabol, Iran
3 Department of Animal Science, Khorasan Razavi Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Mashhad, Iran
چکیده [English]

The aim of this study was to analyze survival and its relationship with body weight and average daily gain traits in Japanese quail. For this purpose, Data base with 1854 Japanese quail survival records were used which collected during 4 generations from 1396 to 1398, by Khorasan Razavi Agricultural and Natural Resources Research and Education Center. The Survival and cmprsk statistical packages were employed to determine the non-genetic effects on survival and culling risk at different times, and variance components estimates of survival trait was performed by MCMCglmm package. Genetic parameters of traits were estimated using single and two-trait analyses via Gibbs sampling. The mean mortality of breeding period (0.206) and the average survival rate (0.793) were calculated. The estimated average heritabilities for survival in single and two-trait analyses were 0.216 and 0.153, respectively. The range of heritability of body weight in single trait analysis was estimated between 0.135 to 0.307) with a mean of 0.219 by two- trait analysis. In two-trait analysis, heritability of body weight trait ranged from 0.155 to 0.014. The highest genetic correlation was -0.3113 (between body weight and average daily gain) and the lowest genetic correlation was -0.0277 (between survival trait and average daily gain). The results showed that optimal management of environmental factors is effective in reducing the culling risk and genetic selection for survival trait can improve the genetic potential of survival.

کلیدواژه‌ها [English]

  • Culling risk
  • Genetic parameter
  • Gibbs sampling
  • Heritability
  • Japanese quail
  1. Aggrey, S.E. and Marks, H.L., 2002. Analysis of censored survival data in Japanese Quail divergently selected for growth and their control. Poult. Sci. 81, pp: 1618-1620.
  2. Ajili, N.; Rekik, B.; BenGara, A. and Bouraoui, R., 2007. Relationships among milk production, reproductive traits, and herd life for Tunisian Holstein-Friesian cows. Afr. J. Agric. Res. Vol. 2, pp: 47-51.
  3. Allore, H.G.; Warnick, L.D.; Hertl, J. and Grhn, Y.T., 2001. Censoringin survival analysis: A simulationstudyof theeffect of milk yield on conception. Prev. Vet. Med. Vol. 49, pp: 223-234.
  4. Borg, R.C., 2007. Phenotypic and genetic evaluation of fitness characteristics in sheep under a range environment. Ph.D. Thesis. Virginia University.
  5. Brinker, ; Raymond, B.; Bijma1, P.; Vereijken, A. and Ellen, E.D., 2016. Estimation of total genetic effects for survival time in crossbred laying hens showing cannibalism, using pedigree or genomic Information. J. Anim. Breed. Genet. Vol. 134, pp: 60-68.
  6. Cox, D.R., 1972. Regression Models and life tables. J R Stat Soc Series B. Vol. 34, No. 2, pp: 187-220.
  7. Ducrocq, V., 1997. Survival analysis, a statistical tool for longevity data. 48th Annual Meeting of the EAAP, Vienna, Austria.
  8. Ellen, E.D.; Visscher, J.; van Arendonk, J.A.M. and Bijma, P., 2008. Survival of Laying Hens: Genetic Parameters for Direct and Associative Effects in Three Purebred Layer Lines. Poult. Sci. Vol. 87, No. 2, pp: 233-239.
  9. Famula, T.R., 1981. Exponential stability model with censoring and covariates. J. Dairy Sci. Vol. 64, pp: 538-545.
  10. Franklin, W.; Martin, G. and Alison, A., 1998. Quail: an egg and meat production system. http://www.echonel.org/.
  11. Hafez, H. and Hauck, R., 2005. Genetic selection in turkeys and broilers and their impact on health conditions. Proc. World Poultry Science Association, 4th European Poultry Genetics Symposium. Dubrownik, Croatia.
  12. Lee, E.T., 1992. Introduction censored observation. pp: 1-7 in Statistical Methods for Survival Data Analysis, Probability and Mathematical Statistics. Wiley, New York.
  13. Marks, H., 1990. Genetics of growth and meat in other galliforms, in: Crawford, R.D., Poultry Breeding and Genetics, Elsevier, Amsterdam. pp: 677-690.
  14. Moghadam, H.K.; Mcmillan, I.; Chambers, J.R.; Julianand, R.J. and Tranchant, C.C., 2005. Heritability of sudden death syndrome and its associated correlations to ascites and body weight in broilers. Br. Poult. Sci. Vol. 46, pp: 54-57.
  15. Quinton, C.D.; Wood, B.J. and Miller, S.P., 2011. Genetic analysis of survival and fitness in turkeys with multiple-trait animal models. Poult. Sci. Vol. 90, pp: 2479-2486.
  16. Pollock, K.H.; Moore, C.T.; Davidson, W.R.; Kellogg, F.E. and Doster, G.L., 1989. Survival Rates of Bobwhite Quail Based on Band Recovery Analyses. J. Wildl. Manage. Vol. 53, No. 1, pp: 1-6.
  17. Puigcerver, M.; Gallego, S.; Rodriguez-Teijeiro, J.D. and Senar, J.C., 1992. Survival and mean life span of the quail Coturnix c. coturnix. Bird Study. Vol. 39, No. 2, pp: 120-123.
  18. Rollins, D.; Taylor, B.D.; Sparks, T.D.; Buntyn, R.J.; Lerich, S.E.; Harveson, L.A.; Wadell, T.E. and Scott, C.B., 2009. Survival of female scaled quail during the breeding season at three sites in the Chihuahuan Desert. National Quail Symposium Proceedings. Vol. 6, pp: 456- 466.
  19. Sisson, D.C.; Terhune, T.M.; Stribling, H.L.; Sholar, J.F. and Mitchell, S.D., 2006. Survival and causes of mortality for northern bobwhites in the south eastern USA. in Cederbaum SB, Faircloth BC. pp: 467-478.
  20. Taylor, J.D.; Burger, L.W.; Scott, J.R.; Manley, W. and Brennan, L.A., 2000. seasonal survival and cause-specific mortality of northern bobwhites in Mississippi. National Quail Symposium Proceedings. 4, pp: 103-107.
  21. Smith, M.R.; Moon, D.A. and Scherer, R.D., 2014. Seasonal Survival and Treatment Use of Northern Bobwhites in Kansas. Transactions of the Kansas Academy of Science. Vol. 117, No. 1-2, pp: 1-14.
  22. Smith, B.J., 2007. Boa: An R package for MCMC output convergence assessment and posterior inference. J. Stat. Soft. Vol. 21, No. 11, pp: 1-37.
  23. VanRaden, P.M. and Wiggans, G.R., 1995. Productive life evaluations: Calculation, accuracy and economic value. J. Dairy Sci. Vol. 78, pp: 631-638.
  24. Vollema, A.R. and Groen, A.F., 1996. Genetic parameters of longevity traits of an upgrading population of dairy cattle. J. Dairy Sci. Vol. 79, pp: 2261-2267.
  25. Weeks, C.A.; Lambton, S.L. and Williams, A.G., 2016. Implications for Welfare, Productivity and Sustainability of the Variation in Reported Levels of Mortality for Laying Hen Flocks Kept in Different Housing Systems: A Meta- Analysis of Ten Studies. PLOS ONE. Vol. 11, No. 1, pp: 1-15.
  26. Wood, B.J., 2009. Calculating economic values for turkeys using a deterministic production model. Can. J. Anim. Sci. Vol. 89, pp: 201-213.