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A model for the prediction of dairy cow body weight based on a physiological timescale

Published online by Cambridge University Press:  27 March 2009

S. Devir ,
B. Zur ,
E. Maltz ,
A. Genizi  and
A. Antler
S. Devir
Affiliation:
Institute of Agricultural Engineering, ARO, PO Box 6, Bet Dagan 50250, Israel
B. Zur
Affiliation:
The Technion – Israel Institute of Technology, Haifa 32000, Israel
E. Maltz
Affiliation:
Institute of Agricultural Engineering, ARO, PO Box 6, Bet Dagan 50250, Israel
A. Genizi
Affiliation:
Department of Statistics and Operational Research, ARO, PO Box 6, Bet Dagan 50250, Israel
A. Antler
Affiliation:
The Technion – Israel Institute of Technology, Haifa 32000, Israel
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Summary

A multivariate linear model was developed to evaluate dairy cow body weight (BW) during lactation on a commercial dairy farm. The model was calibrated separately for first, second and greater than second parities, and also for winter and summer calvers, fed a total mixed ration of 65% concentrates. Average weekly BW was predicted using the following variables on a weekly basis: 4% fat-corrected milk (FCM) yield, time of conception (PREG), time from calving (w), initial body weight (1BW) measured within 2 days after calving, and weeks remaining until the end of the calving season (SWR). The ability of the model to predict mean BW along lactations was tested in the same herd following calibration and during the same period. The prediction capacity of the model for average BW of groups of cows was examined on two timescales: (i) time from calving (physiological timescale) and (ii) any time during the year (calendar timescale). Results indicated that predicted mean BW deviated from measured values either by 1–2% with a maximal deviation of c. 5% on the physiological timescale or by up to 2% on the calendar timescale.

Type
Animals
Information
The Journal of Agricultural Science , Volume 125 , Issue 3 , December 1995 , pp. 415 - 424
Copyright
Copyright © Cambridge University Press 1995

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References

Achten, A. & Tollens, E. (1987). Linear modelling of resource utilization for milk production. EUR Report Commission of the European Communities. EUR 10818, 37–65.Google Scholar
Badinga, L., Collier, R. J., Wilcox, C. J. & Thatcher, W. E. (1985). Interrelationships of milk yield, body weight and reproductive performance. Journal of Dairv Science 68, 1828–1831.CrossRefGoogle ScholarPubMed
Bar-Anan, A. & Genizi, A. (1990). Monthly milk yield as affected by months from calving, calendar month and pregnancy month. Israel Breeders Association, Meshek Habakar Vehachalav 173 (in Hebrew).Google Scholar
Bermann, A., Wolfenzone, D. & Flemenbaum, I. (1990). Alternatives for diminishing the seasonal fluctuations in milk yield. In Proceedings of the Annual Symposium for Ruminant Sciences. Israel Agricultural Extension Service, Maale' Hachamisha, Israel (in Hebrew).Google Scholar
Broadbent, P. J., Topps, J. H., Clark, J. J. & Bruce, J. M. (1984). Evaluation of a model of the energy system of lactating and pregnant cows. Animal Production 38, 363–375.Google Scholar
Brody, S. (1945). Bioenergetics and Growth: with Special Reference to the Efficiency Complex in Domestic Animals. New York: Reinhold.Google Scholar
Brown, J. E., Fitzhugh, H. A. Jr, & Cartwright, T. C. (1976). A comparison of nonlinear models for describing weight-age relationships in cattle. Journal of Animal Science 42, 810–818.CrossRefGoogle Scholar
Bruce, J. M., Broadbent, P. J. & Topps, J. H. (1984). A model of the energy system of lactating and pregnant cows. Animal Production 38, 351–362.Google Scholar
de Assis, A. G. & France, J. (1983). Modelling dairy cattle feeding in the south-east region of Brazil. Agricultural Systems 12, 129–170.CrossRefGoogle Scholar
Deresz, F., Jaume, C. M., de Carvalho, M. R. & González, C. A. (1987). The effect of body weight at calving on milk production and reproductive performance of Friesian x Zebu heifers. Animal Production 45, 325–333.Google Scholar
Forbes, J. M. (1983). Models for the prediction of food intake and energy balance in dairy cows. Livestock Production Science 10, 149–157.CrossRefGoogle Scholar
Israel Milk Council (1987/1988). Annual Reports.Google Scholar
Israel Milk Council (1988). Annual Reports.Google Scholar
Israel Milk Council (1989). Annual Reports.Google Scholar
Kahn, H. E. (1982). The development of a simulation model and its use in the evaluation of cattle production systems. Research Report. ARO, The Volcani Center, Bet Dagan, Israel (in Hebrew).Google Scholar
Kahn, H. E. (1990). Smoothing the Israeli milk yield curve. In Proceedings of the Annual Symposium for Ruminant Sciences. Israel Agricultural Extension Service, Maale' Hachamisha, Israel.Google Scholar
Kahn, H. E. & Lehrer, A. R. (1984). A dynamic model for the simulation of cattle herd production systems: Part 3 – reproductive performance of beef cows. Agricultural Systems 13, 143–159.CrossRefGoogle Scholar
Lin, C. Y., McAllister, A. J. & Lee, A. J. (1985). Multitrait estimation of relationships of first-lactation yields to body weight changes in Holstein heifers. Journal of Dairy Science 68, 2954–2963.CrossRefGoogle ScholarPubMed
Lower, O. J. (1987). Using the concept of physiological age to predict the efficiency of growth in beef animals. Agricultural Systems 24, 269–289.CrossRefGoogle Scholar
Maltz, E., Kroll, O. & Spahr, S. L. (1987). Parameters required for individual concentrate supplementation of the dairy cow: their recording, analysis and use. In Proceedings of the 3rd Symposium on Automation in Dairying, pp. 91–101. Wageningen, The Netherlands: IMAG.Google Scholar
Maltz, E., Devir, S., Kroll, O., Spahr, S. L. & Shanks, R. D. (1990). Computer feeding according to performance potential to economize on intake of concentrates. Journal of Dairy Science 73, Supplement, Abstract P 311.Google Scholar
Maltz, E., Kroll, O., Spahr, S. L., Devir, S., Genizi, A. & Sagi, R. (1991). Milk yield, parity, and cow potential as variables for computerized concentrate supplementation strategy. Journal of Dairy Science 74, 2277–2289.CrossRefGoogle ScholarPubMed
Maltz, E., Devir, S., Kroll, O., Zur, B., Spahr, S. L. & Shanks, R. D. (1992). Comparative responses of lactating cows to total mixed rations or computerized individual concentrates feeding. Journal of Dairy Science 75, 1588–1603.CrossRefGoogle ScholarPubMed
Mertens, R. D. (1985). Factors influencing feed intake in lactating cows. In Proceedings of the Georgia Nutrition Conference for the Feed Industry, p. I. Atlanta, GA, USA.Google Scholar
Miller, R. H., Hooven, N. W. Jr., Smith, J. W. & Creegan, M. E. (1973). Usefulness of periodic body weights to predict yield, intake, and feed efficiency of lactating cows. Journal of Dairy Science 56, 1540–1545.CrossRefGoogle Scholar
Nachtomi, A., Amir, S., Halevi, A. & Brokental, I. (1990). The influence of the season on dairy cows' yield through different rationing strategies. In Proceedings of the Annual Symposium for Ruminant Sciences. Israel Agricultural Extension Service, Maale' Hachamisha, Israel (in Hebrew).Google Scholar
National Research Council (1988). Nutrient Requirements of Dairy Cattle, 6th edn. Washington DC: National Academic Press.Google Scholar
Peiper, U. M., Maltz, E., Edan, Y., Babazada, M., Schon, H. & Artmann, R. (1987). Routine automatic dairy cows' weight measurements for the use of husbandry decisions. In Proceedings of the 3rd Symposium on Automation in Dairying, pp. 118–128. Wageningen, The Netherlands: IMAG.Google Scholar
Rook, A. J., Dhanoa, M. S. & Gill, M. (1990). Prediction of the voluntary intake of grass silages by beef cattle. 2. Principal component and ridge regression analyses. Animal Production 50, 439–454.Google Scholar
Statistical Analysis Systems Institute (1980). SAS User's Guide. Cary, NC: SAS Institute Inc.Google Scholar
Vadiveloo, J. & Holmes, W. (1979). The prediction of the voluntary feed intake of dairy cows. Journal of Agricultural Science, Cambridge 93, 553–562.CrossRefGoogle Scholar
Walter, J. P., Mao, I. L. & Emery, R. S. (1984). Simultaneous fitting of energy requirements and intake for estimating daily energy balance in a lactation. Journal of Dairy Science 67, Supplement, Abstract P 221.Google Scholar
Williams, C. B., Oltenacu, P. A., Sniffen, C. J., Milligan, R. A. & Smith, T. R. (1987). Application of NDF in modelling feed intake, lactation response and body weight changes in dairy cattle, with different forage based rations. Journal of Dairy Science 70, Supplement, Abstract P23G.Google Scholar
Wood, P. D. P. (1976). Algebraic models of the lactation curves for milk, fat and protein production, with estimates of seasonal variation. Animal Production 22, 35–40.Google Scholar
Wood, P. D. P. (1979). A simple model of lactation curves for milk yield, food requirement and body weight. Animal Production 28, 55–63.Google Scholar
Wood, P. D. P., King, J. O. L. & Youdan, P. G. (1980). Relationships between size, live-weight change and milk production characters in early lactation in dairy cattle. Animal Production 31, 143–151.Google Scholar