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Divergence for residual feed intake of Holstein-Friesian cattle during growth did not affect production and reproduction during lactation

Published online by Cambridge University Press:  29 April 2016

K. A. Macdonald*
Affiliation:
DairyNZ, Cnr. Ruakura & Morrinsville Rds, Hamilton 3240, New Zealand
B. P. Thomson
Affiliation:
DairyNZ, WTARS, 42 Whareroa Rd, RD 12, Hawera 4672, New Zealand
G. C. Waghorn
Affiliation:
DairyNZ, Cnr. Ruakura & Morrinsville Rds, Hamilton 3240, New Zealand
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Abstract

Residual feed intake (RFI) is the difference between actual and predicted dry matter intake (DMI) of individual animals. Recent studies with Holstein-Friesian calves have identified an ~20% difference in RFI during growth (calf RFI) and these groups remained divergent in RFI during lactation. The objective of the experiment described here was to determine if cows selected for divergent RFI as calves differed in milk production, reproduction or in the profiles of BW and body condition score (BCS) change during lactation, when grazing pasture. The cows used in the experiment (n=126) had an RFI of −0.88 and +0.75 kg DM intake/day for growth as calves (efficient and inefficient calf RFI groups, respectively) and were intensively grazed at four stocking rates (SR) of 2.2, 2.6, 3.1 and 3.6 cows/ha on self-contained farmlets, over 3 years. Each SR treatment had equal number of cows identified as low and high calf RFI, with 24, 28, 34 and 40/11 ha farmlet. The cows divergent for calf RFI were randomly allocated to each SR. Although SR affected production, calf RFI group (low or high) did not affect milk production, reproduction, BW, BCS or changes in these parameters throughout lactation. The most efficient animals (low calf RFI) lost similar BW and BCS as the least efficient (high calf RFI) immediately post-calving, and regained similar BW and BCS before their next calving. These results indicate that selection for RFI as calves to increase efficiency of feed utilisation did not negatively affect farm productivity variables (milk production, BCS, BW and reproduction) as adults when managed under an intensive pastoral grazing system.

Type
Research Article
Copyright
© The Animal Consortium 2016 

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References

Arthur, PF and Herd, RM 2005. Efficiency of feed utilisation by livestock – implications and benefits of genetic improvement. Canadian Journal of Animal Science 85, 281290.CrossRefGoogle Scholar
Arthur, PF, Herd, RM and Basarab, JA 2010. The role of cattle genetically efficient in feed utilisation in an Australian carbon trading environment. Australian Farm Business Management Journal 7, 514.Google Scholar
Barbano, DM, Lynch, JM and Fleming, JR 1991. Direct and indirect determination of true protein content of milk by Kjeldahl analysis: collaborative study. Journal of Association of Official Analytical Chemists 74, 281288.Google 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, 43184331.Google Scholar
Corson, DG, Waghorn, GC, Ulyatt, MJ and Lee, J 1999. Forage analysis and livestock feeding. In Proceedings of the 61st New Zealand Grassland Association, Napier, New Zealand, pp. 127–132.CrossRefGoogle Scholar
Davis, SR, Macdonald, KA, Waghorn, GC and Spelman, RJ 2014. Residual feed intake of lactating Holstein-Friesian cows predicted from high-density genotypes and phenotyping of growing Heifers. Journal of Dairy Science 97, 14361445.Google Scholar
Donoghue, KA, Arthur, PF, Wilkins, JF and Herd, RM 2011. Onset of puberty and early-life reproduction in Angus females divergently selected for post-weaning residual feed intake. Animal Production Science 51, 183190.Google Scholar
GenStat for Windows 2013. 16th edition. VSN International, Hemel Hempstead, UK.Google Scholar
Green, TC, Jago, JG, Macdonald, KA and Waghorn, GC 2013. Relationships between residual feed intake, average daily gain and feeding behavior in growing dairy heifers. Journal of Dairy Science 96, 30983107.CrossRefGoogle ScholarPubMed
Gregorini, P, Waghorn, GC, Kuhn-Sherlock, B, Romera, AJ and Macdonald, KA 2015. Short communication. Grazing pattern of dairy cows that were selected for divergent residual feed intake as calves. Journal of Dairy Science 98, 64866491.Google Scholar
Herd, RM and Arthur, PF 2009. Physiological basis for residual feed intake. Journal of. Animal Science 87 (E-suppl.), E64E71.Google Scholar
Herd, RM, Arthur, PF and Bottema, CDK 2014. Lessons Learnt from 25 Years of Feed Efficiency Research in Australia. Proceedings of 10th World Congress of Genetics Applied to Livestock Production. Retrieved on 20 November 2015 from https://asas.org/docs/default-source/wcgalp-proceedings-oral/110_paper_10178_manuscript_1215_0.pdf?sfvrsn=2 Google Scholar
Herndon, RS 2010. Comparison of the economics and costs of producing milk on a conventional vs. grass-based ‘New Zealand style’ dairies in Mississippi. Journal of Dairy Science 93 (E-suppl.), 243.Google Scholar
Horan, B, Mee, JF, O’Connor, P, Rath, M and Dillon, P 2004. The effect of strain of Holstein-Friesian cow and feed system on reproductive performance in seasonal-calving milk production systems. Animal Science 79, 453468.Google Scholar
International Dairy Federation 1987. Milk: determination of fat content-Röse Gottlieb gravimetric method (reference method). International IDF Standard, Brussels, Belgium 1C, 8.Google Scholar
L’Huillier, PJ and Thomson, NA 1988. Estimation of herbage mass in ryegrass–white clover dairy pastures. In Proceedings of the 49th New Zealand Grassland Association, Matamata, New Zealand, pp. 117–122.Google Scholar
Macdonald, KA and Penno, JW 1998. Management decision rules to optimise milksolids production on dairy farms. In Proceedings of the 58th New Zealand Society of Animal Production, Massey University, Palmerston North, New Zealand, pp. 132–135.Google Scholar
Macdonald, KA, Beca, D, Penno, JW, Lancaster, JAS and Roche, JR 2011. Short communication: effect of stocking rate on the economics of pasture-based dairy farms. Journal of Dairy Science 94, 25812586.Google Scholar
Macdonald, KA, Penno, JW, Lancaster, JAS and Roche, JR 2008. Effect of stocking rate on pasture production, milk production and reproduction of dairy cows in pasture-based systems. Journal of Dairy Science 91, 21512163.Google Scholar
Macdonald, KA, Pryce, JE, Spelman, RJ, Davis, SR, Wales, WJ, Waghorn, GC, Williams, YJ, Marett, LC and Hayes, BJ 2014. Holstein-Friesian calves selected for divergence in residual feed intake during growth also exhibit divergence in residual feed intake in their first lactation. Journal of Dairy Science 97, 14271435.CrossRefGoogle ScholarPubMed
McDougall, S, Williamson, NB and Macmillan, KL 1995. GnRH induces ovulation of a dominant follicle in primiparous dairy cows undergoing anovulatory follicle turnover. Animal Reproduction Science 39, 205214.Google Scholar
O’Donovan, M, Connolly, J, Dillon, P, Rath, M and Stakelum, G 2002. Visual assessment of herbage mass. Irish Journal of Agricultural Food Research 41, 201211.Google Scholar
Oikonomou, G, Valergakis, GE, Arsenos, G, Roubies, N and Banos, G 2008. Genetic profile of body condition score and blood metabolic traits across lactation in primaparous Holstein cows. Journal of Dairy Science 91, 28142822.Google Scholar
Pryce, JE, Arias, J, Bowman, PJ, Davis, SR, Macdonald, KA, Waghorn, GC, Wales, WJ, Williams, YJ, Spelman, RJ and Hayes, BJ 2012. Accuracy of genomic predictions of residual feed intake and 250 day bodyweight in growing heifers using 625,000 SNP markers. Journal of Dairy Science 95, 21082119.Google Scholar
Pryce, JE, Wales, WJ, de Hass, Y, Veerkamp, RF and Hayes, BJ 2014. Genomic selection for feed efficiency in dairy cattle. Animal 8, 110.Google Scholar
Reist, M, Erdin, DK, von Euw, D, Tschümperlin, D, Leuenberger, KM, Hammon, H, Morel, HM, Phillipona, C, Zbinden, Y, Künzi, N and Blum, JW 2003. Postpartum reproductive function: association with energy, metabolic and endocrine status in high yielding dairy cows. Theriogenology 91, 17071723.Google Scholar
Roche, JR, Dillon, PG, Stockdale, CR, Baumgard, LH and VanBaale, MJ 2004. Relationships among international body condition scoring systems. Journal of Dairy Science 87, 30763079.Google Scholar
Roche, JR, Macdonald, KA, Burke, CR, Lee, JM and Berry, DP 2007. Associations between body condition score, body weight and reproductive performance in seasonal-calving pasture-based dairy cattle. Journal of Dairy Science 90, 376391.Google Scholar
Roche, JR, Friggins, NC, Kay, JK, Fisher, MW, Stafford, KJ and Berry, DP 2009. Invited review: body condition score and its association with dairy cow productivity, health, and welfare. Journal of Dairy Science 92, 57695801.Google Scholar
SAS Institute 2010. Statistical analysis software, version 9.3. SAS Institute Inc., Cary, NC, USA.Google Scholar
Vagnoni, DB and Broderick, GA 1997. Effects of supplementation of energy on ruminally undegraded protein to lactating cows fed alfalfa hay or silage. Journal of Dairy Science 80, 17031712.CrossRefGoogle ScholarPubMed
Vallimont, JE, Dechow, CD, Daubert, JM, Dekleva, MW, Blum, JM, Barlieb, CM, Liu, W, Varga, GA, Heinreichs, AJ and Baumrucker, CR 2011. Short communication: heritability of gross feed efficiency and associations with yield, intake, residual feed intake, body weight and body condition score in 11 commercial Pennsylvania tie stalls. Journal of Dairy Science 94, 21082113.Google Scholar
Vallimont, JE, Dechow, CD, Daubert, JM, Dekleva, MW, Blum, JM, Liu, W, Varga, GA, Heinrichs, AJ and Baumrucker, CR 2013. Short communication: feed utilization and it association with fertility and productive life in 11 commercial Pennsylvania tie-stall herds. Journal of Dairy Science 96, 12511254.Google Scholar
Verbyla, AP, Cullis, BR, Kenward, MG and Welham, SJ 1999. The analysis of designed experiments and longitudinal data by using smoothing splines (with discussion). Journal of Applied Statistics 48, 269311.Google Scholar
Waghorn, GC, Macdonald, KA, Williams, Y, Davis, SR and Spelman, RJ 2012. Measuring residual feed intake in dairy heifers fed an alfalfa (Medicago sativa) cube diet. Journal of Dairy Science 95, 14621471.Google Scholar
Williams, YJ, Pryce, JE, Grainger, C, Wales, WJ, Linden, N, Porker, M and Hayes, BJ 2011. Variation in residual feed intake in Holstein Friesian dairy heifers in Southern Australia. Journal of Dairy Science 94, 47154725.Google Scholar