Hostname: page-component-848d4c4894-2pzkn Total loading time: 0 Render date: 2024-05-13T19:55:29.014Z Has data issue: false hasContentIssue false

Validation of a system for monitoring individual feeding and drinking behaviour and intake in young cattle

Published online by Cambridge University Press:  18 August 2017

B. R. Oliveira Jr
Affiliation:
Departamento de Zootecnia, Escola de Veterinária, Universidade Federal de Minas Gerais, 31270-901 Belo Horizonte, Minas Gerais, Brazil
M. N. Ribas
Affiliation:
CNPq, RHAE – SEVA Engenharia, Projeto Intergado, 32280-300 Contagem, Minas Gerais, Brazil
F. S. Machado
Affiliation:
Embrapa Dairy Cattle, 36038-330 Juiz de Fora, Minas Gerais, Brazil
J. A. M. Lima
Affiliation:
Departamento de Zootecnia, Escola de Veterinária, Universidade Federal de Minas Gerais, 31270-901 Belo Horizonte, Minas Gerais, Brazil
L. F. L. Cavalcanti
Affiliation:
CNPq, RHAE – SEVA Engenharia, Projeto Intergado, 32280-300 Contagem, Minas Gerais, Brazil
M. L. Chizzotti
Affiliation:
Departamento de Zootecnia, Universidade Federal de Viçosa, 36570-900 Viçosa, Minas Gerais, Brazil
S. G. Coelho*
Affiliation:
Departamento de Zootecnia, Escola de Veterinária, Universidade Federal de Minas Gerais, 31270-901 Belo Horizonte, Minas Gerais, Brazil
Get access

Abstract

The objective of this study was to validate an electronic system for monitoring individual feeding and drinking behaviour and intake developed for young cattle housed in group. A total of 35 Holstein–Gyr crossbred heifers (BW: 180±52 kg; age: 121.5±32.5 days), fitted with an ear tag containing a unique passive transponder, were distributed in three groups of 12, 12 and 11 animals per period and had free access to 12 electronic feed bins and two electronic water bins (Intergado® Ltd). The dimensions of feed and water bins, as well as the sensors position were appropriate for young cattle. The system documented the visit frequency and duration, as well as the feed and water intakes, by recording the animal’s identification tag, bin number, initial and final times of visits and the difference of feed/water weight at the start and end of each bin visit. Feed bins were monitored using time-lapse video recording over 4 days and the water bins were monitored over 6 days. For each feed bin, two feeding events were monitored using manual weighings with an external scale immediately before and after the animal’s visit and the difference between them was assumed as feed intake (n=24 observations). For the water bins, 60 manual weighings were made. Video and manual weighing data were regressed on the electronic feeding and drinking behaviour and intake data to evaluate the system’s precision and accuracy. The system showed high specificity (98.98% and 98.56% for the feed and water bins, respectively) and sensitivity (99.25% and 98.74%, respectively) for identifying an animal’s presence or absence. Duration of feed and water bin visits as well as feed and water consumption per visit estimated by the system were highly correlated and precise compared with the observed video and manual weighing data (r2=0.917, 0.963, 0.973 and 0.986, respectively). It was concluded that Intergado® system is a useful tool for monitoring feeding and drinking behaviour as well as water and feed intakes in young cattle housed in groups.

Type
Research Article
Copyright
© The Animal Consortium 2017 

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

AOAC: Official Methods of Analysis. Vol. I. 1990. 15th ed. Association of official Analytical Chemists, Arlington, VA.Google Scholar
Bach, A, Iglesias, C and Busto, I 2004. Technical note: a computerized system for monitoring feeding behavior and individual feed intake of dairy cattle. Journal of Dairy Science 87, 42074209.Google Scholar
Chapinal, N, Veira, DM, Weary, DM and Von Keyserlingk, MAG 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, 57325736.Google Scholar
DeVries, TJ, Von Keyserlingk, MAG, Weary, DM and Beauchemin, KA 2003. Technical note: validation of a system for monitoring feeding behavior of dairy cows. Journal of Dairy Science 86, 35713574.Google Scholar
Friend, TH, Polan, CE and McGilliard, ML 1977. Free stall and feed bunk requirements relative to behavior, production and individual feed intake in dairy cows. Journal of Dairy Science 60, 108116.Google Scholar
González, LA, Tolkamp, BJ, Coffey, MP, Ferret, A and Kyriazakis, I 2008. Changes in feeding behavior as possible indicators for the automatic monitoring of health disorders in dairy cows. Journal of Dairy Science 91, 10171028.CrossRefGoogle ScholarPubMed
Huzzey, JM, von Keyserlingk, M AG and Weary, DM 2005. Changes in feeding, rinking, and standing behavior of dairy cows during the transition period. Journal of Dairy Science 88, 24542461.Google Scholar
Lancaster, PA, Carstens, GE, Crews, DH, Welsh, TH Jr, Forbes, TDA, Forrest, DW, Tedeschi, LO, Randel, RD and Rouquette, FM 2009. Phenotypic and genetic relationships of residual feed intake with performance and ultrasound carcass traits in brangus heifers. Journal of Animal Science 87, 38873896.CrossRefGoogle ScholarPubMed
Luechinger, R, Duru, F, Zeijlemaker, VA, Scheidegger, MB, Boesiger, P and Candinas, R 2002. Pacemaker reed switch behavior in 0.5, 1.5, and 3.0 tesla magnetic resonance imaging units: are reed switches always closed in strong magnetic fields? Pacing and Clinical Electrophysiology 25, 14191423.Google Scholar
Mendes, EDM, Carstens, GE, Tedeschi, LO, Pinchak, WE and Friend, TH 2011. Validation of a system for monitoring feeding behavior in beef cattle. Journal of Animal Science 89, 29042910.Google Scholar
Quimby, WF, Sowell, BF, Bowman, JGP, Branine, ME, Hubbert, ME and Sherwood, HW 2001. Application of feeding behavior to predict morbidity of newly received calves in a commercial feedlot. Canadian Journal of Animal Science 81, 315320.Google Scholar
Robles, V, González, LA, Ferret, A, Manteca, X and Calsamiglia, S 2007. Effects of feeding frequency on intake, ruminal fermentation, and feeding behavior in heifers fed high-concentrate diets. Journal of Animal Science 85, 25382547.Google Scholar
Tedeschi, LO 2006. Assessment of the adequacy of mathematical models. Agricultural Systems 89, 225247.Google Scholar
Vasilatos, R and Wangsness, PJ 1980. Feeding behavior of lactating dairy cows as measured by time-lapse photography. Journal of Dairy Science 63, 412416.Google Scholar
Weary, DM, Huzzey, JM and Von Keyserlingk, MAG 2009. Board-invited review: using behaviour to predict and identify ill health in animals. Journal of Animal Science 87, 770777.CrossRefGoogle ScholarPubMed