Hostname: page-component-78c5997874-fbnjt Total loading time: 0 Render date: 2024-11-10T15:10:16.716Z Has data issue: false hasContentIssue false
  • English
  • Français

Evaluation of production efficiencies at pasture of lactating suckler cows of diverse genetic merit and replacement strategy

Published online by Cambridge University Press:  30 March 2020

S. McCabe ,
N. McHugh ,
N. E. O’Connell  and
R. Prendiville
S. McCabe
Affiliation:
Livestock Systems Research Department, Animal and Grassland Research and Innovation Centre, Teagasc, Grange, Dunsany, County MeathC15PW93, Ireland Institute for Global Food Security, School of Biological Sciences, Queens University Belfast, BelfastBT9 7BL, Ireland
N. McHugh
Affiliation:
Livestock Systems Department, Teagasc Animal and Grassland Research and Innovation Centre, Moorepark, Fermoy, County CorkP61C996, Ireland
N. E. O’Connell
Affiliation:
Institute for Global Food Security, School of Biological Sciences, Queens University Belfast, BelfastBT9 7BL, Ireland
R. Prendiville*
Affiliation:
Livestock Systems Research Department, Animal and Grassland Research and Innovation Centre, Teagasc, Grange, Dunsany, County MeathC15PW93, Ireland
*
†E-mail: robert.prendiville@teagasc.ie
Get access

Abstract

Feed costs account for the largest proportion of direct cost within suckler beef production systems. By identifying the cow type with enhanced capability of converting grazed herbage to beef output across lactations, suckler cow systems would become more efficient and sustainable. The objective of this study was to estimate grass DM intake (GDMI) and production efficiency among lactating suckler cows of diverse genetic merit for the national Irish maternal index (Replacement Index) which includes cow efficiency components such as milk yield and feed intake. Data from 131 cows of diverse genetic merit within the Replacement Index, across two different replacement strategies (suckler or dairy sourced), were available over two grazing seasons. Milk yield, GDMI, cow live weight (BW) and body condition score (BCS) were recorded during early, mid and late-lactation, with subsequent measures of production efficiency extrapolated. Genetic merit had no significant effect on any variables investigated, with the exception of low genetic merit (LOW) cows being 22 kg heavier in BW than high genetic merit (HIGH) cows (P < 0.05). Beef cows were 55 kg heavier in BW (P < 0.001), had a 0.31 greater BCS (P < 0.05) and 0.30 Unité Fourragère Lait (UFL) greater energy requirement for maintenance compared to dairy sourced beef × dairy crossbred (BDX) cows (P < 0.001). The BDX had 0.8 kg greater GDMI, produced 1.8 kg more milk (P < 0.001), had a 0.8 UFL greater energy requirement for lactation and produced weanlings that were 17 kg heavier in BW than beef cows (P < 0.05). Subsequent efficiency variables of milk per 100 kg BW (P < 0.001), milk per kg GDMI (P < 0.001) and GDMI per 100 kg BW (P < 0.001) were more favourable for BDX. The correlations examined showed GDMI had moderate positive correlations (P < 0.001) with intake per 100 kg BW, net energy intake per kg milk yield, RFI and intake per 100 kg calf weaning weight but was weakly negatively correlated to milk yield per kg GDMI (P < 0.001). No difference was observed across genetic merit for beef cows for any of the traits investigated. Results from the current study showed that, while contrasting replacement strategies had an effect on GDMI and production efficiency, no main effect was observed on cows diverse in genetic merit for Replacement Index. Nonetheless, utilising genetic indexes in the suckler herd is an important resource for selecting breeding females for the national herd and phenotypic performance generated from this study can be included in future genetic evaluations to improve reliability of genetic values.

Keywords

beefgenotypegrassintakemilk yield
Type
Research Article
Information
animal , Volume 14 , Issue 8 , August 2020 , pp. 1768 - 1776
Copyright
© The Animal Consortium 2020

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Archer, JA, Richardson, EC, Herd, RM and Arthur, PF 1999. Potential for selection to improve efficiency of feed use in beef cattle: a review. Australian Journal of Agricultural Research 50, 147–162.CrossRefGoogle Scholar
Berry, D, O’Donovan, M and Dillon, P 2009. Potential to genetically alter intake and energy balance in grass fed dairy cows. In Breeding for robustness in cattle (ed. Klopcic, M, Reents, R, Philipsson, J and Kuipers, A), EAAP Publication 126, pp. 219–224. Wageningen Academic Publishers, The Netherlands.Google Scholar
Boggs, DL, Smith, EF, Schalles, RR, Brent, BE, Corah, LR and Ruitt, R 1980. Effects of milk and forage intake on calf performance. Journal of Animal Science 51, 550–553.CrossRefGoogle Scholar
Coleman, J, Berry, DP, Pierce, KM, Brennan, A and Horan, B 2010. Dry matter intake and feed efficiency profiles of 3 genotypes of Holstein-Friesian within pasture-based systems of milk production. Journal of Dairy Science 93, 4318–4331.CrossRefGoogle ScholarPubMed
Crews, JD 2005. Genetics of efficient feed utilization and national cattle evaluation: a review. Genetics and Molecular Research (GMR) 4, 152–165.Google ScholarPubMed
Department of Agriculture Food and the Marine 2016. AIM Bovine statistics report. p. 65. Department of Agriculture Food and the Marine, Ireland. Retrieved on 31 July 2017, from https://www.agriculture.gov.ie/media/migration/animalhealthwelfare/animalidentificationandmovement/AIMStatisticsRpt2016190517.pdfGoogle Scholar
Dillon, P 1993. The use of n-alkanes as markers to determine intake, botanical composition of available or consumed herbage in studies of digesta kinetics with dairy cows. PhD thesis, National University of Ireland, Dublin, Ireland.Google Scholar
Edwards, SR, Hobbs, JD and Mulliniks, JT 2017. High milk production decreases cow-calf productivity within a highly available feed resource environment. Translational Animal Science 1, 54–59.CrossRefGoogle ScholarPubMed
Enríquez, D, Hötzel, MJ and Ungerfeld, R 2011. Minimising the stress of weaning of beef calves: a review. Acta Veterinaria Scandinavica 53, 28.CrossRefGoogle ScholarPubMed
Evans, R, Kearney, F, McCarthy, J, Cromie, A and Pabiou, T 2014. Beef performance evaluations in a multi-layered and mainly crossbred population. In Proceedings of the 10th World Congress of Genetics Applied to Livestock Production, volume 18, p. 732.Google Scholar
Finneran, E, Crosson, P, O’kiely, P, Shalloo, L, Forristal, D and Wallace, M 2010. Simulation modelling of the cost of producing and utilising feeds for ruminants on Irish farms. Journal of Farm Management 14, 95–116.Google Scholar
Fiss, C and Wilton, J 1992. Contribution of breed, cow weight, and milk yield to the traits of heifers and cows in four beef breeding systems. Journal of Animal Science 70, 3686–3696.CrossRefGoogle ScholarPubMed
Fraga, FR, Lopez-Villalobos, N, Martin, N, Kenyon, P, Morris, S and Hickson, R 2016. Intake of milk and pasture and growth rate of calves reared by cows with high or low potential for milk production. Animal Production Science 58, 523–529.CrossRefGoogle Scholar
Gaskins, CT and Anderson, DC 1980. Comparison of lactation curves in Angus-Hereford, Jersey-Angus and Simmental-Angus Cows. Journal of Animal Science 50, 828–832.CrossRefGoogle Scholar
Jenkins, T and Ferrell, C 2002. Beef cow efficiency–revisited. In ‘34th Annual Beef Improvement Federation Annual Meeting’, 10–13th July 2002, Omaha, NE, volume 34, pp. 32–43.Google Scholar
Koch, RM, Swiger, LA, Chambers, D and Gregory, KE 1963. Efficiency of feed use in beef cattle. Journal of Animal Science 22, 486–494.CrossRefGoogle Scholar
Lawrence, P, Kenny, D, Earley, B and McGee, M 2012. Grazed grass herbage intake and performance of beef heifers with predetermined phenotypic residual feed intake classification. Animal 6, 1648.CrossRefGoogle ScholarPubMed
Lawrence, P, Kenny, DA, Earley, B and McGee, M 2013. Intake of conserved and grazed grass and performance traits in beef suckler cows differing in phenotypic residual feed intake. Livestock Science 152, 154–166.CrossRefGoogle Scholar
Lowman, BG, Scott, NA and Somerville, SH 1976. Condition scoring of cattle. Bulletin (East of Scotland College of Agriculture), No. 6, 31p. Edinburgh School of Agriculture, Edinburgh.Google Scholar
Marshall, S, Campbell, C and Buchanan-Smith, J 1998. Herbage biomass and intake of beef cows with calves grazing a grass-legume pasture in southern Ontario. Canadian Journal of Animal Science 78, 211–218.CrossRefGoogle Scholar
Mayes, R, Lamb, C and Colgrove, PM 1986. The use of dosed and herbage n-alkanes as markers for the determination of herbage intake. The Journal of Agricultural Science 107, 161–170.CrossRefGoogle Scholar
McCabe, S, McHugh, N, O’Connell, NE and Prendiville, R 2019. Comparative grazing behaviour of lactating suckler cows of contrasting genetic merit and genotype. Livestock Science, 220, 129–136.CrossRefGoogle Scholar
McCabe, S, McHugh, N and Prendiville, R 2017. Evaluation of production efficiencies among primiparous suckler cows of diverse genetic index at pasture. Advances in Animal Biosciences 8, s55–s59.CrossRefGoogle Scholar
McCabe, S, Prendiville, R, Evans, R, O’Connell, N and McHugh, N 2018. Effect of cow replacement strategy on cow and calf performance in the beef herd. Animal 13, 631–639.CrossRefGoogle ScholarPubMed
McEvoy, M, Delaby, L, Murphy, JP, Boland, TM and O’Donovan, M 2010. Effect of herbage mass and allowance on sward characteristics, milk production, intake and rumen volatile fatty acid concentration. Grass and Forage Science 65, 335–347.Google Scholar
McGee, M 2009. What feed efficiency in the suckler cow has to offer beef farmers. Irish Grassland Association Journal 43, 125–131.Google Scholar
McGee, M, Drennan, MJ and Caffrey, PJ 2005a. Effect of suckler cow genotype on energy requirements and performance in winter and subsequently at pasture. Irish Journal of Agricultural and Food Research 44, 157–171.Google Scholar
McGee, M, Drennan, MJ and Caffrey, PJ 2005b. Effect of suckler cow genotype on milk yield and pre-weaning calf performance. Irish Journal of Agricultural and Food Research 44, 185–194.Google Scholar
McHugh, N, Cromie, A, Evans, R and Berry, D 2014. Validation of national genetic evaluations for maternal beef cattle traits using Irish field data. Journal of Animal Science 92, 1423–1432.CrossRefGoogle ScholarPubMed
Montano-Bermudez, M, Nielsen, MK and Deutscher, GH 1990. Energy requirements for maintenance of crossbred beef cattle with different genetic potential for milk. Journal of Animal Science 68, 2279–2288.CrossRefGoogle ScholarPubMed
Mrode, RA and Thompson, R 2005. Linear models for the prediction of animal breeding values, 2nd edition. CABI, Wallingford, Oxfordshire, UK.CrossRefGoogle Scholar
Murphy, BM, Drennan, MJ, O’Mara, FP and McGee, M 2008. Performance and feed intake of five beef suckler cow genotypes and pre-weaning growth of their progeny. Irish Journal of Agricultural and Food Research 47, 13–25.Google Scholar
O’Donovan, M, Connolly, J, Dillon, P, Rath, M and Stakelum, G 2002. Visual assessment of herbage mass. Irish Journal of Agricultural and Food Research 41, 201–211.Google Scholar
O’Mara, F 2000. A net energy system for cattle and sheep. Version 1.2, Report, Department of Animal Science and Production, University College Dublin, Ireland.Google Scholar
Prendiville, R, Pierce, KM and Buckley, F 2009. An evaluation of production efficiencies among lactating Holstein-Friesian, Jersey, and Jersey × Holstein-Friesian cows at pasture. Journal of Dairy Science 92, 6176–6185.CrossRefGoogle ScholarPubMed
Taylor, R, McGee, M, Kelly, A, Grant, J and Crosson, P 2018. A comparison of production systems and identification of profit drivers for Irish suckler beef farms. International Journal of Agricultural Management 6, 100–110.Google Scholar
Walker, R, Martin, R, Gentry, G and Gentry, L 2015. Impact of cow size on dry matter intake, residual feed intake, metabolic response, and cow performance. Journal of Animal Science 93, 672–684.CrossRefGoogle ScholarPubMed
Walmsley, BJ, Lee, SJ, Parnell, PF and Pitchford, WS 2016. A review of factors influencing key biological components of maternal productivity in temperate beef cattle. Animal Production Science 58, 1–19.CrossRefGoogle Scholar
Wright, IA, Jones, JR, Maxwell, TJ, Russel, AJF and Hunter, EA 1994. The effect of genotype × environment interactions on biological efficiency in beef cows. Animal Science 58, 197–207.Google Scholar
Yan, T, Mayne, CS, Keady, TWJ and Agnew, RE 2006. Effects of dairy cow genotype with two planes of nutrition on energy partitioning between milk and body tissue. Journal of Dairy Science 89, 1031–1042.CrossRefGoogle ScholarPubMed