مقایسة برآوردهای حاصل از حداقل مربعات معمولی و تجزیة مؤلفه‌های اصلی در پیش‌بینی بازده لاشة بزهای نژاد لری

نوع مقاله : مقاله پژوهشی

نویسندگان

1 استادیار گروه علوم دامی، دانشکدة کشاورزی، دانشگاه لرستان

2 استادیار گروه علوم دامی، پردیس کشاورزی و منابع طبیعی دانشگاه رازی کرمانشاه

چکیده

هدف این پژوهش به دست آوردن ارتباط بین بازده لاشه و برخی اندازه‌های بدن در بزهای نژاد لری بود. ابتدا وزن زنده و شش صفت ظاهری بدن برای186 بز اندازه‌گیری شد. سپس برای محاسبة بازده لاشه، دام‌ها کشتار شدند. نتایج بیانگر وجود هم‌خطی در متغیرهای وزن لاشه، وزن بدن و دور سینه بود. برای حذف اثر نامطلوب هم‌خطی از روش تجزیة مؤلفه‌های اصلی استفاده شد. ضرایب نهایی پیش‌بینی بازده لاشه برای وزن لاشه، وزن بدن، دور سینه، دور شکم، قد، طول بدن، طول حیوان و نمرة وضعیت بدن به ترتیب 0049/0، 0006/0، 0016/0-، 0029/0-، 0008/0-، 0008/0، 0001/0 و 0175/0 بود. نتایج نشان داد که مشکل هم‌خطی چندگانه بین متغیرهای مستقل در پیش‌بینی بازده لاشه با روش تجزیة مؤلفه‌های اصلی قابل حل بوده و این روش به برآورد ضرایب پایدار و قابل اعتماد با خطای معیار کمتر در مقایسه با برآوردهای حاصل از حداقل مربعات معمولی منجر می‌شود. نتایج این تحقیق همچنین نشان داد، به دلیل امکان اندازه‌گیری صفات ظاهری بدن در دام زنده، این متغیرها می‌توانند به عنوان یک معیار انتخاب، برای بهبود صفاتی استفاده شوند که در دام زنده قابل اندازه‌گیری نیستند.
 

کلیدواژه‌ها

عنوان مقاله [English]

Comparison of the estimators obtained from ordinary least squares and principle component analysis methods to predict carcass yield in Lori goats breed

نویسندگان [English]

  • Majid Khaldari 1
  • Saheb Forotanifar 2
1 Department of Animal Science, Faculty of Agriculture, Lorestan University, Khorram-Abad, Iran
2 University College of Agriculture and Natural Resources, Razi University, Iran
چکیده [English]

The present study was carried out to establish the relationships between carcass yield and some body measurements in Lori goat breed. The first body weight (BW) and morphological traits of 186 heads goat were recorded. The animals were then slaughtered to calculate the carcass yield. Results showed the colinearity among the traits. In order to eliminate colinearity problems, principal component analysis was used. The final predicted coefficients of carcass yield for carcass weight, body weight, heart girth, paunch girth, height at wither, body lengthBL, animal length and body condition score was 0.0049, 0.0006, -0.0016, -0.0029, -0.0008, 0.0008, 0.0001 and 0.0175, respectively. Results showed that the problem of multicollinearity in the relationship between carcass yield and independent variables in goats can be solved using principal component analysis. This method leads to more stable and reliable coefficients with less standard error than those from ordinary least squares. Furthermore, Body measurements can be used as selection criterion to improve carcass yield that it cannot be recorded on a live animal.

کلیدواژه‌ها [English]

  • carcass yield, principle component analysis, body measurements
  • multicollinearity, selection criterion

مراجع

  1. Addrizzo, J.R. (2004). Use of goat milk and goat meat as therapeutic aids in cardiovascular diseases. Dairy Goat Journal, 82, 27-27.
  2. Badi, A., Fissehaye, N. & Rattan, P. (2002). Estimation of live body weight in Eritrean goat from heart girth and height at withers. Indian journal of animal sciences, 72, 893-895.
  3. Barros Gomes, H.F., Goncalves, H.C., Polizel Neto, A., Canizares, L., Ignacio, G., Roca, R.d.O., Marques, R.O., de Oliveira, G.M. & Queiroz, E.O. (2013). Common factors method to predict the carcass composition tissue in kid goats. Revista Brasileira de Zootecnia, 42, 193.
  4. Chatterjee, S. & Hadi, A.S. (2013). Regression analysis by example, John Wiley & Sons.
  5. De Villiers, J., Gcumisa, S., Gumede, S., Thusi, S., Dugmore, T., Cole, M., Du Toit, J., Vatta, A. & Stevens, C. (2009) Estimation of live body weight from the heart girth measurement in KwaZulu-Natal goats. Applied Animal Husbandry & Rural Development, 2, 1-8.
  6. Draper, N.R. & Smith, H. (1981). Applied regression analysis (2nd ed.). New york: Wiley.
  7. Fekedulegn, B.D., Colbert, J., Hicks Jr, R. & Schuckers, M.E. (2002). Coping with multicollinearity: An example on application of principal components regression in dendroecology. Published by USDA FOREST SERVICE, 11 CAMPUS BLVD SUITE 200, NEWTOWN SQUARE PA 19073-3294 (http://www.fs.fed.us/ne/morgantown/4557/dendrochron/rpne721.pdf)
  8. Fritts, H.C., Blasing, T.J., Hayden, B.P. & Kutzbach, J.E. (1970). Multivariate techniques for specifying tree-growth and climate relationships and for reconstructing anomalies in paleoclimate. Journal of Applied Meteorology, 10 (5), 845-64.
  9. Gunst, R.F. & Mason, R.L. (1980) Regression analysis and its application: a data-oriented approach. New York: CRC Press.
  10. Hair, J.F., Tatham, R.L., Anderson, R.E. & Black, W. (2006). Multivariate data analysis, Pearson Prentice Hall Upper Saddle River, NJ.
  11. Khaldari, M. (2014). Sheep and goat husbandry (5th Ed.). Jahade-daneshgahi publisher, pp 505 (in Farsi).
  12. Khan, H., Muhammad, F., Ahmad, R., Nawaz, G., Zubair, R. & Zubair, M. (2006). Relationship of body weight with linear body measurements in goats. Journal of Agricultural and Biological Science, 1, 51-54.
  13. Koyuncu, M. & Altıncekic, S. O. (2013). Importance of body condition score in dairy goats. Macedonian Journal of Animal Science, 3(2), 167-173.
  14. Leng, J., Zhu, R.-J., Zhao, G.-R., Yang, Q.-R., Mao & H.-M. (2010). Quantitative and qualitative body traits of Longling Yellow goats in China. Agricultural Sciences in China, 9, 408-415.
  15. Mahieu, M., Naves, M. & Arquet, R. (2011). Predicting the body mass of goats from body measurements. Livestock Research Rural Development, 23.
  16. Malau-Aduli, A., Aziz, M., Kojima, T., Niibayashi, T., Oshima, K. & Komatsu, M. (2004). Fixing collinearity instability using principal component and ridge regression analyses in the relationship between body measurements and body weight in Japanese Black cattle. Journal of Animal and Veterinary Advances, 3 (12), 856-863.
  17. Monteiro, A.C., Teixeira, A., Azevedo, J.T. & Silva, S.R. (2012). Determination of carcass composition of goats by video image analysis (http://www2.atb-potsdam.de/cigr- imageanalysis/images/images12/tabla_137_C0737.pdf)
  18. Muhammad, F., Khan, H., Zubair, M. & Nawaz, G. (2006). Relationship of body weight with linear body measurements in goats. Journal of Animal and Veterinary Advances,
  19. Myers, R.H. (2000). Classical and modern regression with applications (Duxbury Classic). Duxbury Press, Pacific Grove.
  20. Ogah, D. (2011). In vivo prediction of live weight and carcass traits using body measurements in indigenous guinea fowl. Biotechnology in Animal Husbandry, 27, 1827-1836.
  21. Ogah, D., Musa, I. & Yusuf, N. (2013). Prediction of carcass weight from body measurements in West African Dwarf goat using canonical correlation analysis. Egyptian Journal of Sheep and Goat Sciences. Egyptian Association for Sheep and Goat, pp. 75-79.
  22. Ojedapo, L., Adedeji, T., Olayeni, T., Adedeji, O., Abdullah, A. & Ojebiyi, O. (2007). Influence of age and sex on body weight and some body linear measurements of extensively reared wad goats in derived savannah zone of Nigeria. Journal of Animal and Veterinary Advances.
  23. Okpeku, M., Yakubu, A., Peters, S., Ozoje, M., Ikeobi, C., Adebambo, O. & Imumorin, I. (2011). Application of multivariate principal component analysis to morphological characterization of indigenous goats in Southern Nigeria. Acta Agriculturae Slovenica, 98, 101-109.
  24. Ozkaya, S. & Bozkurt, Y. (2009). The accuracy of prediction of body weight from body measurements in beef cattle. Archiv Tierzucht, 52, 371-377.
  25. Rahman, F. (2007) Prediction of carcass weight from the body characteristics of Black Bengal goats. International Journal of Agriculture and Biology, 9, 431-434.
  26. Rook, A., Dhanoa, M. & 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.
  27. Sen, A., Santra, A. & Karim, S. (2004). Carcass yield, composition and meat quality attributes of sheep and goat under semiarid conditions. Meat science, 66, 757-763.
  28. Shahin, K.A. & Hassan, N. (2000). Sources of shared variability among body shape characters at marketing age in New Zealand White and Egyptian rabbit breeds.Annales de Zootechnie, 49, 435-445.
  29. Simm, G. & Dingwall, W. (1989). Selection indices for lean meat production in sheep. Livestock Production Science, 21, 223-233.
  30. Slippers, S., Letty, B. & De Villiers, J. (2000). Prediction of the body weight of Nguni goats. South African Journal of Animal Science, 30, 127-128.
  31. Stamper, N. (2010). Linear and ltrasound measurements in crossbred goats as a predictor of live and hot carcass weights, University of Tennessee at Martin.
  32. Vargas, S., Larbi, A. & Sanchez, M. (2007). Analysis of size and conformation of native Creole goat breeds and crossbreds used in smallholder agrosilvopastoral systems in Puebla, Mexico. Tropical animal health and production, 39, 279-286.
  33. Villaquiran, M., Gipson, T., Merkel, R., Goetsch, A. & Sahlu, T. (2004). Body Condition Scores in Goats. American Institute for Goat Research, Langston University.
  34. Yakubu, A. (2009). Fixing collinearity instability in the estimation of body weight from morpho-biometrical traits of West African Dwarf goats. Trakia Journal of Sciences, 7, 61-66.
  35. YAKUBU, A. (2011). Fixing multicollinearity instability in the prediction of body weight from morphometric traits of White Fulani cows. Journal of Central European Agriculture, 11.
  36. Yigrem, S., Banerjee, S. & Berihun, K. (2013). Comparison of linear with Some non linear regression Methods to estimate Hot Carcass Weight Using Live Weight in Arsi-Bale Sheep and Goats of both the Sexes. World Applied Sciences Journal, 21, 1603-1608.
  37. Talton, C. (2011). Meat yield, quality and cuts. Georgia organics conference, UGA Cooperative Extension March.

فایل ها

سابقه مقاله

  • تاریخ دریافت: 10 مهر 1393
  • تاریخ بازنگری: 26 بهمن 1393
  • تاریخ پذیرش: 14 فروردین 1394

هم رسانی

ارجاع به این مقاله

آمار