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Farmer views on calving difficulty consequences on dairy and beef farms

Published online by Cambridge University Press:  27 July 2016

D. Martin-Collado*
Affiliation:
AbacusBio Limited, Ground Floor, PublicTrust Building 442 Moray Place, PO Box 5585, Dunedin 9016, New Zealand
F. Hely
Affiliation:
AbacusBio Limited, Ground Floor, PublicTrust Building 442 Moray Place, PO Box 5585, Dunedin 9016, New Zealand
T. J. Byrne
Affiliation:
AbacusBio Limited, Ground Floor, PublicTrust Building 442 Moray Place, PO Box 5585, Dunedin 9016, New Zealand
R. Evans
Affiliation:
Irish Cattle Breeding Federation, Highfield House, Shinagh, Bandon, Co. Cork, Ireland
A. R. Cromie
Affiliation:
Irish Cattle Breeding Federation, Highfield House, Shinagh, Bandon, Co. Cork, Ireland
P. R. Amer
Affiliation:
AbacusBio Limited, Ground Floor, PublicTrust Building 442 Moray Place, PO Box 5585, Dunedin 9016, New Zealand
*
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Abstract

Calving difficulty (CD) is a key functional trait with significant influence on herd profitability and animal welfare. Breeding plays an important role in managing CD both at farm and industry level. An alternative to the economic value approach to determine the CD penalty is to complement the economic models with the analysis of farmer perceived on-farm impacts of CD. The aim of this study was to explore dairy and beef farmer views and perceptions on the economic and non-economic on-farm consequences of CD, to ultimately inform future genetic selection tools for the beef and dairy industries in Ireland. A standardised quantitative online survey was released to all farmers with e-mail addresses on the Irish Cattle Breeding Federation database. In total, 271 farmers completed the survey (173 beef farmers and 98 dairy farmers). Both dairy and beef farmers considered CD a very important issue with economic and non-economic components. However, CD was seen as more problematic by dairy farmers, who mostly preferred to slightly reduce its incidence, than by beef farmers, who tended to support increases in calf value even though it would imply a slight increase in CD incidence. Farm size was found to be related to dairy farmer views of CD with farmers from larger farms considering CD as more problematic than farmers from smaller farms. CD breeding value was reported to be critical for selecting beef sires to mate with either beef or dairy cows, whereas when selecting dairy sires, CD had lower importance than breeding values for other traits. There was considerable variability in the importance farmers give to CD breeding values that could not be explained by the farm type or the type of sire used, which might be related to the farmer non-economic motives. Farmer perceived economic value associated with incremental increases in CD increases substantially as the CD level considered increases. This non-linear relationship cannot be reflected in a standard linear index weighting. The results of this paper provide key underpinning support to the development of non-linear index weightings for CD in Irish national indexes.

Type
Research Article
Copyright
© The Animal Consortium 2016 

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References

Amer, PR, Simm, G, Keane, MG, Diskin, MG and Wickham, BW 2001. Breeding objectives for beef cattle in Ireland. Livestock Production Science 67, 223239.Google Scholar
Barnes, AP, McCalman, H, Buckingham, S and Thomson, S 2013. Farmer decision-making and risk perceptions towards outwintering cattle. Journal of Environmental Management 129, 917.Google Scholar
Berger, PJ, Cubas, AC, Koehler, KJ and Healey, MH 1992. Factors affecting dystocia and early calf mortality in Angus cows and heifers. Journal of Animal Science 70, 17751786.Google Scholar
Berry, D, Shalloo, L, Cromie, A, Olori, V, Veerkamp, R, Dillon, P, Amer, P, Evans, R and Kearney, F 2007. The Economic Breeding Index: a generation on. Technical Report, Irish Breeding Cattle Federation, Retrieved on 7 December 2015 from http://www.icbf.com/publications/files/economic_breeding_index.pdf.Google Scholar
Bleul, U 2011. Risk factors and rates of perinatal and postnatal mortality in cattle in Switzerland. Livestock Science 135, 257264.Google Scholar
Cole, JB, Wiggans, GR, VanRaden, PM and Miller, RH 2007. Stillbirth (co)variance components for a sire-maternal grandsire threshold model and development of a calving ability index for sire selection. Journal of Dairy Science 90, 24892496.Google Scholar
Cromie, AR, Kearney, F, Evans, R and Berry, DP 2014. Genomics for pedigree and cross-bred beef cattle populations; some experiences from Ireland. Proceedings of the 10th World Congress of Genetics Applied to Livestock Production, 22 August 2014, Vancouver, Canada, 260pp.Google Scholar
Dekkers, JCM 1994. Optimal breeding strategies for calving ease. Journal of Dairy Science 77, 34413453.Google Scholar
Duguma, G, Mirkena, T, Haile, A, Okeyo, AM, Tibbo, M, Rischkowsky, B, Sölkner, J and Wurzinger, M 2011. Identification of smallholder farmers and pastoralists’ preferences for sheep breeding traits: choice model approach. Animal 5, 19841992.Google Scholar
Evans, JR and Mathur, A 2005. The value of online surveys. Internet Research 15, 195219.Google Scholar
Evans, R, Kearney, F, McCarthy, J, Cromie, AR and Pabiou, T 2014. Beef performance evaluations in a multi-layered and mainly crossbred population. Proceedings of the 10th World Congress of Genetics Applied to Livestock Production, 18 August 2014, Vancouver, Canada, 732pp.Google Scholar
Evans, R and Pabiou, T 2012. The benefits of using farmer scored traits in beef genetic evaluations. Proceedings of the 38th ICAR Biennial Session, 28 May–1 June 2012, Cork, Ireland.Google Scholar
Guzman, RM and Kolstad, CD 2007. Researching preferences, valuation and hypothetical bias. Environmental and Resource Economics 37, 465487.Google Scholar
Hanrahan, K, Hennessy, T, Kinsella, A and Moran, B 2013. Teagasc national survey results 2013. Agricultural Economics & Farm Surveys Department, Teagasc, Athenry, Ireland.Google Scholar
Hely, FS, Evans, R, Amer, PR and Cromie, A 2015. Non-linear calving difficulty weightings in the Irish dairy industry. Proceedings of the AAABG 21st Conference, 28–30 May 2015, Lorne, Australia.Google Scholar
Kraut, R, Olson, J, Banaji, M, Bruckman, A, Cohen, J and Couper, M 2004. Psychological research online: report of board of scientific affairs’ advisory group on the conduct of research on the internet. American Psychologist 59, 105117.Google Scholar
Lopez de Maturana, E, Ugarte, E and Gonzalez-Recio, O 2007. Impact of calving ease on functional longevity and herd amortization costs in Basque Holsteins using survival analysis. Journal of Dairy Science 90, 44514457.Google Scholar
Martin-Collado, D, Byrne, TJ, Amer, PR, Santos, BFS, Axford, M and Pryce, JE 2015. Analyzing the heterogeneity of farmers’ preferences for improvements in dairy cow traits using farmer typologies. Journal of Dairy Science 98, 41484161.Google Scholar
Martin-Collado, D, Byrne, TJ, Visser, B and Amer, PR 2016. An evaluation of alternative selection indexes for a non-linear profit trait approaching its economic optimum. Journal of Animal Breeding and Genetics, doi:10.1111/jbg.12220, Published online by Wiley Online Library, 1 June 2016.Google Scholar
McHugh, N, Kearney, JF and Berry, DP 2012. The effect of dystocia on subsequent performance in dairy cows. Proceedings of the Agricultural Research Forum 2012, 12 March 2012, Tullamore, Ireland, pp. 22–24.Google Scholar
Mee, JF 2008. Prevalence and risk factors for dystocia in dairy cattle: a review. Veterinary Journal 176, 93101.Google Scholar
Mee, JF, Berry, DP and Cromie, AR 2008. Prevalence of, and risk factors associated with, perinatal calf mortality in pasture-based Holstein-Friesian cows. Animal 2, 613620.Google Scholar
Nielsen, HM, Amer, PR and Byrne, T 2013. Approaches to formulating practical breeding objectives for animal production systems. Acta Agriculturae Scandinavica, Section A –Animal Science 64, 212.Google Scholar
Nix, JM, Spitzer, JC, Grimes, LW, Burns, GL and Plyler, BBE 1998. A retrospective analysis of factors contributing to calf mortality and dystocia in beef cattle. Theriogenology 49, 15151523.Google Scholar
Reips, UD 2002. Standards for internet-based experimenting. Experimental Psychology 49, 243256.Google Scholar
Sadeghi-Sefidmazgi, A, Moradi-Shahrbabak, M, Nejati-Javaremi, A, Miraei-Ashtiani, SR and Amer, PR 2012. Breeding objectives for Holstein dairy cattle in Iran. Journal of Dairy Science 6, 34063418.Google Scholar
Suchman, L and Jordan, B 1990. Interactional troubles in face-to-face survey interviews. Journal of the American Statistical Association 85, 232253.CrossRefGoogle Scholar
Vaske, J, Jacobs, M, Sijtsma, M and Beaman, J 2011. Can weighting compensate for sampling issues in internet surveys? Human Dimensions of Wildlife 16, 2002015.Google Scholar
Yao, C, Weigel, KA and Cole, JB 2014. Genetic evaluation of stillbirth in US Brown Swiss and Jersey cattle. Journal of Dairy Science 4, 24742480.Google Scholar
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