Hostname: page-component-cd9895bd7-fscjk Total loading time: 0 Render date: 2024-12-25T13:49:07.820Z Has data issue: false hasContentIssue false
  • English
  • Français

Assessing feed efficiency in beef steers through feeding behavior, infrared thermography and glucocorticoids*

Published online by Cambridge University Press:  16 December 2009

Y. R. Montanholi ,
K. C. Swanson ,
R. Palme ,
F. S. Schenkel ,
B. W. McBride ,
D. Lu  and
S. P. Miller
Y. R. Montanholi*
Affiliation:
Department of Animal and Poultry Science, University of Guelph, 50 Stone Road East – building 70, Guelph, N1G 2W1, Ontario, Canada
K. C. Swanson*
Affiliation:
Department of Animal and Poultry Science, University of Guelph, 50 Stone Road East – building 70, Guelph, N1G 2W1, Ontario, Canada
R. Palme
Affiliation:
Department of Biomedical Sciences, University of Veterinary Medicine, Veterinärplatz 1, 1210 Vienna, Austria
F. S. Schenkel
Affiliation:
Department of Animal and Poultry Science, University of Guelph, 50 Stone Road East – building 70, Guelph, N1G 2W1, Ontario, Canada
B. W. McBride
Affiliation:
Department of Animal and Poultry Science, University of Guelph, 50 Stone Road East – building 70, Guelph, N1G 2W1, Ontario, Canada
D. Lu
Affiliation:
Department of Animal and Poultry Science, University of Guelph, 50 Stone Road East – building 70, Guelph, N1G 2W1, Ontario, Canada
S. P. Miller
Affiliation:
Department of Animal and Poultry Science, University of Guelph, 50 Stone Road East – building 70, Guelph, N1G 2W1, Ontario, Canada
*
†E-mail: [email protected], [email protected]
†E-mail: [email protected], [email protected]
Get access

Abstract

A better understanding of the factors regulating feed efficiency and their potential as predictors of feed efficiency in cattle is needed. Therefore, the potential of three classes of traits, namely, feeding behavior characteristics: daily time at feeder (TF; min/day), time per meal (TM; min), meal size (MS; g DM), eating rate (ER; g DM/min), number of daily meals (NM) and daily visits to the feeder (VF); infrared (IR) thermography traits (°C): eye (EY), cheek (CK), snout (SN), ribs (RB) and hind area (HA); and glucocorticoid levels: fecal cortisol metabolites (FCM; ng/g) and plasma cortisol (PC; ng/ml) as predictors of efficiency were evaluated in 91 steers (436 ± 37 kg) over 2 years (Y1 = 46; Y2 = 45). Additionally, the individual traits of each of these three classes were combined to define three single traits. Individual daily feed intake of a corn silage and high-moisture corn-based diet was measured using an automated feeding system. Body weight and thermographs were taken every 28 days over a period of 140 days. Four productive performance traits were calculated: daily dry matter intake (DMI), average daily gain (ADG), feed to gain ratio (F : G) and residual feed intake (RFI). Steers were also classified into three RFI categories (low-, medium- and high-RFI). Among the feeding behavior characteristics, MS and ER were correlated with all efficiency traits (range: 0.26 to 0.75). Low-RFI (more efficient steers) had smaller MS, lower ER and fewer VF in comparison to high-RFI steers. Less efficient steers (high-RFI) performed more VF during the nocturnal period than more efficient steers. More efficient steers had lower CK and SN temperatures than less efficient steers (28.1°C v. 29.2°C and 30.0°C v. 31.2°C), indicating greater energetic efficiency for low-RFI steers. In terms of glucocorticoids, PC was not correlated with efficiency traits. In contrast, more efficient steers had higher FCM in comparison to less efficient steers (51.1 v. 31.2 ng/g), indicating that a higher cortisol baseline is related to better feed efficiency. The overall evaluation of the three classes of traits revealed that feeding behavior, IR thermography and glucocorticoids accounted for 18%, 59% and 7% of the total variation associated with RFI, respectively. These classes of traits have usefulness in the indirect assessment of feed efficiency in cattle. Among them, IR thermography was the most promising alternative to screen cattle for this feed efficiency. These findings might have application in selection programs and in the better understanding of the biological basis associated with productive performance.

Keywords

beef cattle, cortisol, fecal cortisol metabolites, residual feed intake, skin temperature
Type
Full Paper
Information
animal , Volume 4 , Issue 5 , May 2010 , pp. 692 - 701
Copyright
Copyright © The Animal Consortium 2009

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.)

Footnotes

*

Paper winner of the Tewolde Family Award from the World Association for Animal Production at the 10th World Conference on Animal Production, Cape Town, Republic of South Africa, November 2008.

References

Adam, I, Young, BA, Nicol, AM, Degen, AA 1984. Energy cost of eating in cattle given diets of different form. Animal Production 38, 53–56.Google Scholar
Archer, JA, Richardson, EC, Herd, RM, Arthur, PF 1999. Potential for selection to improve efficiency of feed use in beef cattle: a review. Australian Journal of Agriculture Research 50, 147–161.Google Scholar
Arkin, H, Kimmel, E, Berman, A, Broday, D 1991. Heat transfer properties of dry and wet furs of dairy cows. Transactions of the ASAE 34, 2550–2558.CrossRefGoogle Scholar
Baldwin, RL, Smith, NE, Taylor, J, Sharp, M 1980. Manipulating metabolic parameters to improve growth rate and milk secretion. Journal of Animal Science 51, 1416–1428.CrossRefGoogle ScholarPubMed
Basarab, JA, Price, MA, Aalhus, JL, Okine, EK, Snelling, WM, Lyle, KL 2003. Residual feed intake and body composition in young growing cattle. Canadian Journal of Animal Science 83, 189–204.CrossRefGoogle Scholar
Benjamini, Y, Hochberg, Y 1995. Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society: Series B 57, 289–300.Google Scholar
Birkett, S, de Lange, K 2001. Limitations of conventional models and a conceptual framework for a nutrient flow representation of energy utilization by animals. The British Journal of Nutrition 86, 647–659.CrossRefGoogle Scholar
Blaxter, KL 1962. The energy metabolism of ruminants. Hutchinson Scientific and Technical, London, UK.Google Scholar
Canadian Council on Animal Care. 1993. Guide to the care and use of experimental animals (ed. ED Olfert, BM Cross and A McWillians), vol. 1, Canadian Council of Animal Care, Ottawa, Canada.Google Scholar
Castro Bulle, FCP, Paulino, PV, Sanches, AC, Sainz, RD 2007. Growth, carcass quality, and protein and energy metabolism in beef cattle with different growth potentials and residual feed intakes. Journal of Animal Science 85, 928–936.CrossRefGoogle ScholarPubMed
Chapinal, N, Veira, DM, Weary, DM, von Keyserlingk, MA 2007. Technical note: validation of a system for monitoring individual feeding and drinking behavior and intake in group housed cattle. Journal of Dairy Science 90, 5732–5736.CrossRefGoogle ScholarPubMed
Colditz, IG, Ferguson, DM, Greenwood, PL, Doogan, VJ, Petherick, JC, Kilgour, RJ 2007. Regrouping unfamiliar animals in the weeks prior to slaughter has few effects on physiology and meat quality in Bos taurus feedlot steers. Australian Journal of Experimental Agriculture 47, 763–769.CrossRefGoogle Scholar
Curley, KO Jr, Neuendorff, DO, Lewis, AW, Cleere, JJ, Welsh, TH Jr, Randel, RR 2008. Functional characteristics of the bovine hypothalamic-pituitary axis vary with temperament. Hormones and Behavior 53, 20–27.CrossRefGoogle ScholarPubMed
Deswysen, AG, Dutilleul, P, Godfrin, JP, Ellis, WC 1993. Nycterohemeral eating and ruminating patterns in heifers fed grass or corn silage: analysis by finite Fourier transform. Journal of Animal Science 71, 2739–2747.CrossRefGoogle ScholarPubMed
Forbes, JM 1986. Voluntary food intake and diet selection in farm animals, 2nd edition. CAB International, Oxfordshire, UK 453p.Google Scholar
Fujishima, H, Toda, I, Yamada, M, Sato, N, Tsubota, K 1996. Corneal temperature in patients with dry eye evaluated by infrared radiation thermometry. The British Journal of Ophthalmology 80, 29–32.CrossRefGoogle ScholarPubMed
Geverink, NA, Schouten, WCP, Gort, G, Wiegant, VM 2002. Individual differences in aggression and physiology in peri-pubertal breeding gilts. Applied Animal Behavior Science 77, 43–52.CrossRefGoogle Scholar
Geverink, NA, Heetkamp, MJW, Schouten, WCP, Wiegant, VM, Schrama, JW 2004. Backtest type and housing condition of pigs influence energy metabolism. Journal of Animal Science 82, 1227–1233.Google Scholar
Golden, JW, Kerley, MS, Kolath, WH 2008. The relationship of feeding behavior to residual feed intake in crossbred Angus steers fed traditional and no-roughage diets. Journal of Animal Science 86, 180–186.CrossRefGoogle ScholarPubMed
Gomez, RR, Bourg, BM, Paddock, Z, Carstens, GE 2007. Evaluation of feed efficiency in Santa Gertrudis steers and relationship with temperament and feeding behavior traits. Journal of Animal Science 85 (suppl. 1), 454.Google Scholar
Herd, RM, Johnston, DJ, Moore, K, Graser, H-U, Arthur, PF 2004. Using plasma IGF-1 concentration for genetic improvement of feed efficiency in beef cattle. Journal of Animal Science 82, 378–379.Google Scholar
Hurnik, JF, DeBoer, S, Webster, AB 1984. Detection of health disorders in dairy cattle utilizing a thermal infrared scanning technique. Canadian Journal of Animal Science 64, 1071–1073.CrossRefGoogle Scholar
Kleiber, M 1961. The fire of life: an introduction to animal energetics. John Wiley & Sons, Inc., New York, NY, USA, 454 p.Google Scholar
Koch, RM, Swiger, LA, Chambers, D, Gregory, KE 1963. Efficiency of feed use in beef cattle. Journal of Animal Science 22, 486–494.CrossRefGoogle Scholar
Kolath, WH, Kerley, MS, Golden, JW, Keisler, DH 2006. The relationship between mitochondrial function and residual feed intake in Angus steers. Journal of Animal Science 84, 861–865.CrossRefGoogle ScholarPubMed
Koolhaas, JM, Korte, SM, De Boer, SF, Van Der Vegt, BJ, Van Reenen, SG, Hopster, H, De Jong, IC, Ruis, MAW, Blokhuis, HJ 1999. Coping styles in animals: current status in behavior and stress physiology. Neuroscience and Biobehavioral Reviews 23, 925–935.CrossRefGoogle ScholarPubMed
Lancaster, PA, Cartens, GE, Crews, DH Jr, Woods, SA 2005. Evaluation of feed efficiency traits in growing bulls and relationships with feeding behavior and ultrasound carcass estimates. Proceedings, Western Section, American Society of Animal Science 56, 461–464.Google Scholar
Mader, CJ, Montanholi, YR, Wang, YJ, Miller, SP, Mandell, IB, McBride, BW, Swanson, KC 2009. Relationships among measures of growth performance and efficiency with carcass traits, visceral organ mass, and pancreatic digestive enzymes in feedlot cattle. Journal of Animal Science 87, 1548–1557.Google Scholar
Möstl, E, Palme, R 2002. Hormones as indicators of stress. Domestic Animal Endocrinology 23, 67–74.CrossRefGoogle ScholarPubMed
Moberg, GP 2000. Biological response to stress: implications for animal welfare. In The biology of animal stress (ed. GP Moberg and JA Mench), pp. 123–146. CABI Publishing, Wallingford, UK.Google Scholar
Montanholi, YR, Swanson, KC, Miller, SP, Palme, R, Schenkel, FS 2007. Relationships between residual feed intake and infrared thermography and glucocorticoid levels in feedlot steers from three different sire breeds. Canadian Journal of Animal Science 88, 179.Google Scholar
Montanholi, YR, Odongo, NE, Swanson, KC, Schenkel, FS, McBride, BW, Miller, SP 2008. Application of infrared thermography as an indicator of heat and methane production and its use in the study of skin temperature in response to physiological events in dairy cattle (Bos taurus). Journal of Thermal Biology 33, 469–475.CrossRefGoogle Scholar
Montanholi, YR, Swanson, KC, Schenkel, FS, McBride, BW, Caldwell, TR, Miller, SP 2009. On the determination of residual feed intake and associations of infrared thermography with efficiency and ultrasound traits in beef bulls. Livestock Science 125, 22–30.CrossRefGoogle Scholar
Nkrumah, JD, Okine, EK, Mathison, GW, Schmid, K, Li, C, Basarab, JA, Price, MA, Wang, Z, Moore, SS 2006. Relationships of feedlot feed efficiency, performance, and feeding behavior with metabolic rate, methane production, and energy partitioning in beef cattle. Journal of Animal Science 84, 145–153.CrossRefGoogle ScholarPubMed
Palme, R, Möstl, E 1997. Measurement of cortisol metabolites in feaces of sheep as a parameter of cortisol concentration in blood. Zeitschrift für Säugetierkunde 62 (suppl. 2), 192–197.Google Scholar
Palme, R, Robia, C, Messmann, S, Hofer, J, Möstl, E 1999. Measurement of fecal cortisol metabolites in ruminants: a noninvasive parameter of adrenocortical function. Wiener Tierärztliche Monatsschrift 86, 237–241.Google Scholar
Palme, R, Robia, C, Baumgartner, , Möstl, E 2000. Transport stress in cattle as reflected by an increase in fecal cortisol metabolite concentrations. The Veterinary Record 146, 108–109.Google Scholar
Palme, R, Rettenbacher, S, Touma, C, El-Bahr, SM, Möstl, E 2005. Stress hormones in mammals and birds: comparative aspects regarding metabolism, excretion, and noninvasive measurement in fecal samples. Annals New York Academy of Sciences 1040, 162–171.CrossRefGoogle ScholarPubMed
Pesenhofer, G, Palme, R, Pesenhofer, RM, Kofler, J 2006. Comparison of two methods of fixation during functional claw trimming – walk-in crush versus tilt table – in dairy cows using fecal cortisol metabolite concentrations and daily milk yield as parameters. Wiener Tierärztliche Monatsschrift 93, 288–294.Google Scholar
Rauw, WM, Kanisb, E, Noordhuizen-Stassenc, EN, Grommersc, FJ 1998. Undesirable side effects of selection for high production efficiency in farm animals: a review. Livestock Production Science 56, 15–33.Google Scholar
Richardson, EC, Herd, RM 2004. Biological basis for variation in residual feed intake in beef cattle. 2. Synthesis of results following divergent selection. Australian Journal of Experimental Agriculture 44, 431–440.CrossRefGoogle Scholar
Richardson, EC, Herd, RM, Oddy, VH 2000. Variation in body composition, activity and other physiological processes and their associations with feed efficiency. In Feed efficiency in beef cattle. Proceedings of the feed efficiency workshop (ed. JA Archer, RM Herd and PF Arthur), pp. 46–50. University of New England, Armidale, NSW, Australia.Google Scholar
Richardson, EC, Herd, RM, Oddy, VH, Thompson, JM, Archer, JA, Arthur, PF 2001. Body composition and implications for heat production of Angus steer progeny of parents selected for and against residual feed intake. Australian Journal of Experimental Agriculture 41, 1065–1072.CrossRefGoogle Scholar
Richardson, EC, Herd, RM, Archer, JA, Arthur, PF 2004. Metabolic differences in Angus steers divergently selected for residual feed intake. Australian Journal of Experimental Agriculture 44, 441–452.CrossRefGoogle Scholar
Robinson, DL, Oddy, VH 2004. Genetic parameters for feed efficiency, fatness, muscle area and feeding behavior of feedlot finished beef cattle. Livestock Production Science 90, 255–270.CrossRefGoogle Scholar
Romney, DL, Blunn, V, Sanderson, R, Leaver, JD 2000. Feeding behavior, food intake and milk production responses of lactating dairy cows to diets based on grass silage of high or low dry-matter content, supplemented with quickly and slowly fermentable energy sources. Animal Science 71, 349–357.Google Scholar
Sapolsky, RM 2002. Endocrinology of the stress response. In Behavioral Endocrinology (ed. JB Becker, M Breedlove, D Crews and MM McCarthy), pp. 409–450, 2nd edition. The MIT Press, Cambridge, Massachusetts, USA.Google Scholar
Schaefer, AL, Cook, N, Tessaro, SV, Deregt, D, Desroches, G, Dubeski, PL, Tong, AKW, Godson, DL 2004. Early detection and prediction of infection using infrared thermography. Canadian Journal of Animal Science 84, 73–80.Google Scholar
Schaefer, AL, Basarab, J, Scott, S, Colyn, J, McCartney, D, McKinnon, J, Okine, E, Tong, AKW 2005. The relationship between infrared thermography and residual feed intake in cows. Journal of Animal Science 83 (supl. 1), 263.Google Scholar
Schwartzkopf-Genwein, KS, Atwood, S, McAllister, TA 2002. Relationship between bunk attendance, intake and performance of steers and heifers on varying feeding regimes. Applied Animal Behavior Science 76, 179–188.CrossRefGoogle Scholar
Senn, M, Dürst, B, Kaufmann, A, Langhans, W 1995. Feeding patterns of lactating cows of three different breeds fed hay, corn silage, and grass silage. Physiology & Behavior 58, 229–236.CrossRefGoogle ScholarPubMed
Statistical Analysis Systems Institute. 2003. Statistical analysis systems, version 9.1. SAS Institute Inc., Cary, North Carolina, USA.Google Scholar
Stewart, M, Schaefer, AL, Haley, DB, Colyn, J, Cook, NJ, Stafford, KJ, Webster, JR 2008. Infrared thermography as a non-invasive method for detecting fear-related responses of cattle to handling procedures. Animal Welfare 17, 387–393.Google Scholar
Thun, R, Eggenberger, E 1996. Abhängigkeit zwischen Cortisol und Testosterone unter Ruhebedingungen, nach akutem Streβ und Hormonstimulierung beim Stier. Schweizer Archiv für Tierheilkunde 138, 225–233.Google Scholar
Tolkamp, BJ, Kyriazakis, I 1997. Measuring diet selection in dairy cows: effect of training on choice of dietary protein level. Animal Science 64, 197–207.Google Scholar
Tong, AKW, Schaefer, AL, Jones, SDM 1995. Detection of poor quality beef with infrared thermography. Meat Focus International 4, 443–445.Google Scholar
Van den Heuvel, CJ, Ferguson, SA, Gilbert, SS, Dawson, D 2004. Thermoregulation in normal sleep and insomnia: the role of peripheral heat loss and new applications for digital thermal infrared imaging (DITI). Journal of Thermal Biology 29, 457–461.CrossRefGoogle Scholar
Van Soest, PJ 1994. Nutrional ecology of the ruminant, 2nd edition. Cornell University Press, Ithaca, New York, USA.CrossRefGoogle Scholar
Voisinet, BD, Grandin, T, Tatum, JD, O’Connor, SF, Struthers, JJ 1997. Feedlot cattle with calm temperaments have higher average daily gains than cattle with excitable temperaments. Journal of Animal Science 75, 892–896.CrossRefGoogle ScholarPubMed
von Holst, D 1998. The concept of stress and its relevance for animal behavior. Advances in the Study of Behavior 27, 1–131.CrossRefGoogle Scholar
Webster, AJF 1978. Prediction of the energy requirements for growth in beef cattle. World Review of Nutrition and Dietetics 30, 189–226.Google ScholarPubMed
Whittow, GC 1962. The significance of the extremities of the ox (Bos taurus) in thermoregulation. The Journal of Agricultural Science 58, 109–120.CrossRefGoogle Scholar