Hostname: page-component-848d4c4894-pftt2 Total loading time: 0 Render date: 2024-05-10T09:07:56.001Z Has data issue: false hasContentIssue false
  • English
  • Français

The prediction of live weight from body measurements on female Holstein calves by digital image analysis

Published online by Cambridge University Press:  15 November 2012

S. OZKAYA
S. OZKAYA*
Affiliation:
Department of Animal Science, Agricultural Faculty, Suleyman Demirel University, 32260, Isparta, Turkey
*
Email: serkanozkaya@sdu.edu.tr
Get access Rights & Permissions [Opens in a new window]

Summary

The objective of the current study was to determine the accuracy of the prediction of live weight (LW) from body measurements (BMs) by using digital image analysis on female Holstein calves. The calves were measured with a measurement stick and digital image analysis. The following linear parameters were taken: body length (BL), wither height (WH), chest depth (CD), hip height (HH) and hip width (HW). LW and BMs were recorded at birth, at weaning and at 24 weeks of age. Regression coefficients, which included all BMs at birth, gave a low R2 value (66·7%), but the R2 value was found to be 87·6 and 86·0% at weaning and 24 weeks of age, respectively. A high correlation coefficient was found among LW and CD, HH and HW at weaning (0·90, 0·91 and 090, respectively) and at 24 weeks of age (0·89, 0·90 and 0·91, respectively). The results confirm that for female Holstein calves, digital image analysis is an effective measuring system for the prediction of LW from BMs.

Type
Animal Research Paper
Information
The Journal of Agricultural Science , Volume 151 , Issue 4 , August 2013 , pp. 570 - 576
Copyright
Copyright © Cambridge University Press 2012 

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

REFERENCES

Berger, R. & Miller, S. (2003). Predicting Lean Meat Yield in Yearling Bulls using Alternative Ultrasound and Linear Body Measurements. Ontario Beef Research Update. Guelph, Ontario, Canada: University of Guelph. Available from: http://bru.aps.uoguelph.ca/Articles03/2003-pg6.pdf (verified 13 November 2011).Google Scholar
Bozkurt, Y., Aktan, S. & Ozkaya, S. (2007). Body weight prediction using digital image analysis for slaughtered beef cattle. Journal of Applied Animal Research 32, 195–198.CrossRefGoogle Scholar
Burke, J., Nuthall, P. & McKinnon, A. (2004). An analysis of the feasibility of using image processing to estimate the live weight of sheep. FHMG Research Report. Canterbury, New Zealand: Applied Management and Computing Division, Lincoln University.Google Scholar
Eker, M. (1958). Türkiye'de Yerli Sığır Irklarında Canlı Ağırlığı Tahmin Metodları (Estimation Methods of Live Weights on the Domestic cattle in Turkey). Ankara Üniversitesi Ziraat Fakültesi Yayinlari, No. 145. Ankara, Turkey: Ankara Üniversitesi Ziraat Fakültesi.Google Scholar
Heinrichs, A. J., Rogers, G. W. & Cooper, J. B. (1992). Predicting body weight and wither height in Holstein using body measurements. Journal of Dairy Science 75, 3576–3581.CrossRefGoogle ScholarPubMed
Minitab (2001). Minitab User's Guide. Release 13 for Windows. State College, PA, USA: Minitab Inc.Google Scholar
Negretti, P., Bianconi, G., Bartocci, S., Terramoccia, S. & Verna, M. (2008). Determination of live weight and body condition score in lactating Mediterranean buffalo by visual image analysis. Livestock Science 113, 1–7.CrossRefGoogle Scholar
Ozkaya, S. (2012). Accuracy of body measurements using digital image analysis in female Holstein calves. Animal Production Science 50, 917–920.CrossRefGoogle Scholar
Ozkaya, S. & Bozkurt, Y. (2008). The relationship of parameters of body measures and body weight by using digital image analysis in pre-slaughter cattle. Archives of Animal Breeding, Dummerstorf 51, 120–128.CrossRefGoogle Scholar
Stajnko, D., Brus, M. & Hocevar, M. (2008). Estimation of bull live weight through thermographically measured body dimensions. Computers and Electronics in Agriculture 61, 233–240.CrossRefGoogle Scholar
Tasdemir, S., Urkmez, A. & Inal, S. (2011 a). Determination of body measurements on the Holstein cows using digital image analysis and estimation of live weight with regression analysis. Computers and Electronics in Agriculture 76, 189–197.CrossRefGoogle Scholar
Tasdemir, S., Urkmez, A. & Inal, S. (2011 b). A fuzzy rule-based system for predicting the live weight of Holstein cows whose body dimensions were determined by image analysis. Turkish Journal of Electrical Engineering and Computer Sciences 19, 689–703.Google Scholar
Tuzemen, N., Yanar, M., Akbulut, O., Ugur, F. & Aydin, R. (1995). Prediction of body weights from body measurements in Holstein-Friesian calves. Journal of Ataturk University Agriculture Faculty 26, 245–252.Google Scholar
Ulutas, Z., Saatci, M. & Ozluturk, A. (2001). Prediction of body weights from body measurements in East Anatolian Red calves. Journal of Ataturk University Agriculture Faculty 32, 61–65.Google Scholar
Wilson, L. L., Egan, C. L. & Terosky, T. L. (1997). Body measurements and body weights of special-fed Holstein veal calves. Journal of Dairy Science 80, 3077–3082.CrossRefGoogle ScholarPubMed
Yanar, M., Tuzemen, N., Ozhan, M., Aydin, R. & Ugur, F. (1995). Prediction of body weight from body measurements in Brown Swiss cattle. Turkish Journal of Veterinary and Animal Science 19, 357–360.Google Scholar