Czech J. Anim. Sci., 2022, 67(12):475-482 | DOI: 10.17221/149/2022-CJAS

General resilience in dairy cows: A reviewReview

Eva Kašná ORCID..., Ludmila Zavadilová ORCID..., Jan Vařeka ORCID..., Jitka Kyselová ORCID...
Institute of Animal Science, Prague - Uhříněves, Czech Republic

Dairy farming is deeply affected by climate change, especially by rising temperatures and heat waves, poorer availability of quality food and water, and the spread of new diseases and pests outside their original ecological niche. Their impact can be mitigated not only by changes in technologies, management and treatment, but also by breeding and selection of more resilient cows. General resilience encompasses the animal's capacity to cope with environmental, social and disease challenges. It is described as the capacity of the animal to be minimally affected by a disturbance or to rapidly return to the physiological, behavioural, cognitive, health, affective and production states that pertained before exposure to a disturbance. As disturbances can be of different natures, general resilience is a composite trait consisting of different resilience types according to the nature of the disturbance. Resilience can be quantified through time series data that capture fluctuations in the daily performance. Recent studies have worked with deviations in the daily milk yield and daily live weight from optimal performance or have focused on the assessment of the daily activity in terms of the daily step count. To observe the duration and magnitude of the response to perturbance, two indicators were suggested: the autocorrelation (rauto) and the natural logarithm of deviations (LnVar). Based on the daily milk yield deviations, both indicators have shown sufficient genetic variabilities with the estimated heritability ~0.1 for rauto and ~0.2 for LnVar. Low values of both indicators were genetically related to better udder health, better hoof health, better longevity, better fertility, higher body condition score, less ketosis but also lower milk yield level. The selection for improved resilience could benefit from the use of genomic information as several genes and biological pathways associated with disease resilience and resilience to heat stress have already been identified. The presented results suggest that the integration of resilience into the cattle breeding programmes would improve the capacity of the dairy industry to cope with global climate change.

Keywords: dairy cattle; animal breeding; adaptability; health; sustainability

Published: December 21, 2022  Show citation

ACS AIP APA ASA Harvard Chicago Chicago Notes IEEE ISO690 MLA NLM Turabian Vancouver
Kašná E, Zavadilová L, Vařeka J, Kyselová J. General resilience in dairy cows: A review. Czech J. Anim. Sci. 2022;67(12):475-482. doi: 10.17221/149/2022-CJAS.
Download citation

References

  1. Adriaens I, Friggens NC, Ouweltjes W, Scott H, Aernouts B, Statham J. Productive life span and resilience rank can be predicted from on-farm first-parity sensor time series but not using a common equation across farms. J Dairy Sci. 2020 Aug;103(8):7155-71. Go to original source... Go to PubMed...
  2. Albers GAA, Gray GD, Piper LR, Barker JSF, Le Jambre LF, Barger IA. The genetics of resistance and resilience to Haemonchus contortus in young Merino sheep. Int J Parasitol. 1987 Oct;17(7):1355-63. Go to original source... Go to PubMed...
  3. Ben Abdelkrim A, Tribout T, Martin O, Boichard D, Ducrocq V, Friggens NC. Exploring simultaneous perturbation profiles in milk yield and body weight reveals a diversity of animal responses and new opportunities to identify resilience proxies. J Dairy Sci. 2021 Jan; 104(1):459-70. Go to original source... Go to PubMed...
  4. Berghof TVL, Poppe M, Mulder HA. Opportunities to improve resilience in animal breeding programs. Front Genet. 2019 Jan 14;9: 15 p. Go to original source... Go to PubMed...
  5. Bezdicek J, Nesvadbova A, Makarevich A, Kubovicova E. Negative impact of heat stress on reproduction in cows: Animal husbandry and biotechnological viewpoints: A review. Czech J Anim Sci. 2021 Jul 27;66(8):293-301. Go to original source...
  6. Bisset SA, Morris CA. Feasibility and implications of breeding sheep for resilience to nematode challenge. Int J Parasitol. 1996 Aug-Sep;26(8-9):857-68. Go to original source... Go to PubMed...
  7. CENIA. Zprava o zivotnim prostredi Ceske republiky 2020 [Report on the environment of the Czech Republic 2020] [Internet]. Prague: Czech Environmental Information Agency; 2021. 312 p. Available from: https://www.cenia.cz/wp-content/uploads/2021/11/Zprava2020.pdf. Czech.
  8. Cheruiyot EK, Haile-Mariam M, Cocks BG, MacLeod IM, Xiang R, Pryce JE. New loci and neuronal pathways for resilience to heat stress in cattle. Sci Rep. 2021 Aug 17; 11(1): 16 p. Go to original source... Go to PubMed...
  9. Colditz IG, Hine BC. Resilience in farm animals: Biology, management, breeding and implications for animal welfare. Anim Prod Sci. 2016 Dec;56(12):1961-83. Go to original source...
  10. Elgersma GG, do Jong G, van der Linde R, Mulder HA. Fluctuations in milk yield are heritable and can be used as a resilience indicator to breed healthy cows. J Dairy Sci. 2018 Feb;101(2):1240-50. Go to original source... Go to PubMed...
  11. Fang H, Kang L, Abbas Z, Hu l, Chen Y, Tan X, Wang Y, Xu Q. Identification of key genes and pathways associated with thermal stress in peripheral blood mononuclear cells of Holstein dairy cattle. Front Genet. 2021 Jun 10;12: 15 p. Go to original source... Go to PubMed...
  12. FAO, GDP. Climate change and the global dairy cattle sector - The role of the dairy sector in low-carbon future. Rome: Food and Agriculture organization of the United Nations and Global Dairy Platform Inc.; 2018. 36 p.
  13. Gauly M, Bollwein H, Breves G, Brugemann K, Danicke S, Das G, Demeler J, Hansen H, Isselstein J, Konig S, Loholter M, Martinsohn M, Meyer U, Potthoff M, Sanker C, Schroder B, Wrage N, Meibaum B, von Samson-Himmelstjerna G, Stinshoff H, Wrenzycki C. Future consequences and challenges for dairy cow production systems arising from climate change in Central Europe - A review. Animal. 2013 May;7(5):843-59. Go to original source... Go to PubMed...
  14. Hermesch S, Dominik S. Breeding focus 2014 - Improving resilience. Armidale, Australia: University of New England, Animal Genetics and Breeding Unit; 2014. 141 p.
  15. Klopcic M, Reents R, Philipsson J, Kuipers A. Breeding for robustness in cattle. (EAAP publication No. 126). Wageningen Academic Publishers; 2009. 281 p. Go to original source...
  16. Knap PW, Doeschl-Wilson A. Why breed disease-resilient livestock, and how? A review. Genet Sel Evol. 2020 Oct 14;52(1): 18 p. Go to original source... Go to PubMed...
  17. Kok A, Tsousis G, Niozas G, Kemp B, Kaske M, van Knegsel ATM. Short communication: Variance and autocorrelation of deviations in daily milk yield are related with clinical mastitis in dairy cows. Animal. 2021 Oct;15 (10): 100363. Go to original source... Go to PubMed...
  18. Konig S, May K. Invited review: Phenotyping strategies and quantitative-genetic background of resistance, tolerance and resilience associated traits in dairy cattle. Animal. 2019 May;13(5):897-908. Go to original source... Go to PubMed...
  19. Krupova Z, Krupa E, Zavadilova L, Kasna E, Zakova E. Current challenges for trait economic values in animal breeding. Czech J Anim Sci. 2020 Dec;65(12):454-62. Go to original source...
  20. Liu S, Yue T, Ahmad MJ, Hu X, Zhang X, Deng T, Hu Y, He C, Zhou Y, Yang L. Transcriptome analysis reveals potential regulatory genes related to heat tolerance in Holstein dairy cattle. Genes. 2020 Jan 7;11(1): 12 p. Go to original source... Go to PubMed...
  21. Llonch P, Hoffmann G, Bodas R, Mirbach D, Verwer C, Haskell MJ. Opinion paper: Measuring livestock robustness and resilience: Are we on the right track? Animal. 2020 Apr;14(4):667-9. Go to original source... Go to PubMed...
  22. Mulder HA. Genomic selection improves response to selection in resilience by exploiting genotype by environment interactions. Front Genet. 2016 Oct 13;7: 11 p. Go to original source... Go to PubMed...
  23. Poppe M, Veerkamp RF, van Pelt ML, Mulder HA. Exploration of variance, autocorrelation, and skewness of deviations from lactation curves as resilience indicators for breeding. J Dairy Sci. 2020 Feb;103(2):1667-84. Go to original source... Go to PubMed...
  24. Poppe M, Mulder HA, van Pelt ML, Mullaart E, Hogeveen H, Veerkamp RF. Development of resilience indicator traits based on daily step count data for dairy cattle breeding. Genet Sel Evol. 2022 Mar 14;54(1): 16 p. Go to original source... Go to PubMed...
  25. Samy AM, Peterson AT. Climate change influences on the global potential distribution of bluetongue virus. PLoS One. 2016 Mar 9;11(3): 12 p. Go to original source... Go to PubMed...
  26. Scheffer M, Carpenter SR, Dakos V, van Nes EH. Generic indicators of ecological resilience: Inferring the chance of a critical transition. Annu Rev Ecol Evol Syst. 2015 Dec;46(1):145-67. Go to original source...
  27. Scheffer M, Bolhuis JE, Borsboom D, Buchman TG, Gijzel SMW, Goulson D, Kammenga JE, Kemp B, van de Leemput IA, Levin S, Martin CM, Melis RJF, van Nes EH, Romero LM, Olde Rikkert MGM. Quantifying resilience of humans and other animals. PNAS. 2018 Nov 20; 115(47):11883-90. Go to original source... Go to PubMed...
  28. Silpa MV, Konig S, Sejian V, Malik PK, Nair MRR, Fonseca VFC, Maia ASC, Bhatta R. Climate-resilient dairy cattle production: Applications of genomic tools and statistical models. Front Vet Sci. 2021 Apr 29;8: 16 p. Go to original source... Go to PubMed...
  29. Strandberg E, Felleki M, Fikse WF, Franzen J, Mulder HA, Ronnegard L, Urioste JI, Windig JJ. Statistical tools to select for robustness and milk quality. Adv Anim Biosci. 2013 Jul;4(3):606-11. Go to original source...
  30. Wiggans GR, Cole JB, Hubbard SM, Sonstegard TS. Genomic selection in dairy cattle: The USDA Experience. Annu Rev Anim Biosci. 2017 Feb 8;5:309-27. Go to original source... Go to PubMed...

This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY NC 4.0), which permits non-comercial use, distribution, and reproduction in any medium, provided the original publication is properly cited. No use, distribution or reproduction is permitted which does not comply with these terms.