본문 바로가기
KERD
논문KCI 등재

Development of an index that decreases birth weight, promotes postnatal growth and yet minimizes selection intensity in beef cattle

2

조회

0

다운로드

0

인용

0

참고문헌

키워드

초록

Objective: The main goal of our current study was to improve the growth curve of meat animals by decreasing the birth weight while achieving a finishing weight that is the same as that before selection but at younger age.Methods: Random regression model was developed to derive various selection indices to achieve desired gains in body weight at target time points throughout the fattening process. We considered absolute and proportional gains at specific ages (in weeks) and for various stages (i.e., early, middle, late) during the fattening process.Results: The point gain index was particularly easy to use because breeders can assign a specific age (in weeks) as a time point and model either the actual weight gain desired or a scaled percentage gain in body weight.Conclusion: The point gain index we developed can achieve the desired weight gain at any given postnatal week of the growing process and is an easy-to-use and practical option for improving the growth curve.

Abstract

Objective: The main goal of our current study was to improve the growth curve of meat animals by decreasing the birth weight while achieving a finishing weight that is the same as that before selection but at younger age. Methods: Random regression model was developed to derive various selection indices to achieve desired gains in body weight at target time points throughout the fattening process. We considered absolute and proportional gains at specific ages (in weeks) and for various stages (i.e., early, middle, late) during the fattening process. Results: The point gain index was particularly easy to use because breeders can assign a specific age (in weeks) as a time point and model either the actual weight gain desired or a scaled percentage gain in body weight. Conclusion: The point gain index we developed can achieve the desired weight gain at any given postnatal week of the growing process and is an easy-to-use and practical option for improving the growth curve.

참고문헌 (35)

  1. Gregory KE, "Symposium on performance testing in beef cattle : Evaluating postweaning performance in beef cattle", J Anim Sci, 24, pp.248~258 (1965)[DOI]
  2. Cartwright TC, "Selection criteria for beef cattle for the future", J Anim Sci, 30, pp.706~711 (1970)[DOI]
  3. Dickerson GE, "Selection criteria for efficient beef production", J Anim Sci, 39, pp.659~673 (1974)[DOI]
  4. Fitzhugh HA, "Analysis of growth curves and strategies for altering their shape", J Anim Sci, 42, pp.1036~1051 (1974)[DOI]
  5. Foulley JL, "Some considerations on selection criteria and optimization for terminal sire breeds", Genet Sel Evol, 8, pp.89~ (1976)[DOI]
  6. Schaeffer LR, "Random regressions in animal models for test-day production in dairy cattle", 5th WCGALP, pp.443~446 (1994)
  7. Jamrozik J, "Genetic evaluation of dairy cattle using test day yields and random regression model", J Dairy Sci, 80, pp.1217~1226 (1997)[DOI]
  8. Togashi K, "Modifying the lactation curve to improve lactation milk and persistency", J Dairy Sci, 86, pp.1487~1493 (2003)[DOI]
  9. Togashi K, "Development of an optimal index to improve lactation yield and persistency with the least selection intensity", J Dairy Sci, 87, pp.3047~3052 (2004)[DOI]
  10. Boligon AA, "Covariance functions for body weight from birth to maturity in Nellore cows", J Anim Sci, 88, pp.849~859 (2010)[DOI]
  11. Meyer K, "Scope for a random regression model in genetic evaluation of beef cattle for growth", Livest Prod Sci, 86, pp.69~83 (2004)[DOI]
  12. Meyer K, "Random regression analyses using B-splines to model growth of Australian Angus cattle", Genet Sel Evol, 37, pp.473~500 (2005)[DOI]
  13. Mota LFM, "Genetic evaluation and selection response for growth in meat-type quail through random regression models using B-spline functions and Legendre polynomials", Animal, 12, pp.667~674 (2018)[DOI]
  14. Přibyl J, "Trajectory of body weight of performance tested dual-purpose bulls", Czech J Anim Sci, 52, pp.315~324 (2007)[DOI]
  15. Togashi K, "Predicting the rate of inbreeding in populations undergoing four-path selection on genomically enhanced breeding values", Anim Biosci, 35, pp.804~813 (2022)[DOI]
  16. Togashi K, "Selection for milk production and persistency using eigenvectors of the random regression coefficient matrix", J Dairy Sci, 89, pp.4866~4873 (2006)[DOI]
  17. Legarra A, "A relationship matrix including full pedigree and genomic information", J Dairy Sci, 92, pp.4656~4663 (2009)[DOI]
  18. Aguilar I, "Hot topic : a unified approach to utilize phenotypic, full pedigree, and genomic information for genetic evaluation of Holstein final score", J Dairy Sci, 93, pp.743~752 (2010)[DOI]
  19. Christensen OF, "Compatibility of pedigree-based and markerbased relationship matrices for single-step genetic evaluation", Genet Sel Evol, 44, pp.37~46 (2012)[DOI]
  20. Henderson CR, "Applications of linear models in animal breeding" (1984), University of Guelph
  21. Dekkers JCM, "Asymptotic response to selection on best linear unbiased predictors of breeding values", Anim Prod, 54, pp.351~360 (1992)[DOI]
  22. Togashi K, "Asymptotic response to four-path selection due to index and single trait selection according to genomically enhanced breeding values", Livest Sci, 231, pp.103846~ (2020)[DOI]
  23. Searle SR, "Matrix Algebra for the Biological Science" (1966), John Wiley & Sons
  24. Takeda M, "Evaluation of feed efficiency traits for genetic improvement in Japanese black cattle", J Anim Sci, 96, pp.797~805 (2018)[DOI]
  25. Onogi A, "Development of a structural growth curve model that considers the causal effect of initial phenotypes", Genet Sel Evol, 51, pp.19~27 (2019)[DOI]
  26. Teixeira BB, "Genetic evaluation of growth traits in nellore cattle through multi-trait and random regression models", Czech J Anim Sci, 63, pp.212~221 (2018)[DOI]
  27. Ferreira JL, "Estimation of(co)variances for growth traits in Nellore cattle raised in the Humid Tropics of Brazil by random regression", Ciênc Agrár, 36, pp.1713~1723 (2015)[DOI]
  28. "The trend of genetic ability in Japanese Black cattle" (2022)[URL]
  29. Harris, DL, "Expected and predicted progress from index selection involving estimates of population parameters", Biometrics, 20, pp.46~72 (1964)[DOI]
  30. Heidhues T, "Relative accuracy of selection indices based on estimated genotypic and phenotypic parameters", Biometrics, 17, pp.502~503 (1961)
  31. "Estimation of heritabilities and genetic correlations by time slices using predictivity in large genomic models" (2023)[URL]
  32. James JW, "Index selection with restrictions", Biometrics, 24, pp.1015~1018 (1968)[DOI]
  33. Kempthorne O, "Restricted selection indices", Biometrics, 15, pp.10~19 (1959)[DOI]
  34. Ma J, "Gut microbiota composition and diversity in different commercial swine breeds in early and finishing growth stages", Animals(Basel), 12, pp.1607~ (2022)[DOI]
  35. Koivula M, "Genetic(co)variances and breeding value estimation of Gompertz growth curve parameters in Finnish Yorkshire boars, gilts and barrows", J Anim Breed Genet, 125, pp.168~175 (2008)[DOI]

관련 논문AI추천

Selection index for beef cattle that maximizes overall growth yet constraining birth weight and other traitsKurogi Kazuhito, Nurimoto Masanobu, Ogino Atsushi, Shinomiya Masakazu, Togashi Kenji, Watanabe Toshio아세아·태평양축산학회 · Animal Bioscience2026 · 제39권 제1호Genomic and phenotypic selection indices for decreased birth weight, shortening fattening period, and regulating total weight gain in beef cattleKinukawa Masashi, Kurogi Kazuhito, Nurimoto Masanobu, Ogino Atsushi, Shinomiya Masakazu, Togashi Kenji, Watanabe Toshio아세아·태평양축산학회 · Animal Bioscience2025 · 제38권 제2호Estimation of genetic relationships between growth curve parameters in Guilan sheepNavid Ghavi Hossein-Zadeh한국축산학회 · 한국축산학회지2015 · 제57권 제5호Effects of selection index coefficients that ignore reliability on economic weights and selection responses during practical selectionAkio Onogi, Kazuhito Kurogi, Kazunori Adachi, Kenji Togashi, Takanori Yasumori, Takayoshi Nozaki, Tsutomu Takahashi, Yamato Atagi아세아·태평양축산학회 · Animal Bioscience2018 · 제31권 제1호Genetic parameters and correlations of related feed efficiency, growth, and carcass traits in Hanwoo beef cattle이득환, Ibáñez-Escriche Noelia, Mehrban Hossein, Naserkheil Masoumeh아세아·태평양축산학회 · Animal Bioscience2021 · 제34권 제5호Single-step genomic evaluation for growth traits in a Mexican Braunvieh cattle populationNilforooshan Mohammad Ali, Pérez-Rodríguez Paulino, Ruíz-Flores Agustín, Valerio-Hernández Jonathan Emanuel아세아·태평양축산학회 · Animal Bioscience2023 · 제36권 제7호

이 간행물의 다른 논문 (15건)