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Home▶ Journals▶ Indian Journal of Veterinary Sciences and Biotechnology▶Archive▶Vol. 18 No. 4 (2022)▶Prediction of Lifetime Milk Yield using Principal Component…
Indian Journal of Veterinary Sciences and Biotechnology
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Prediction of Lifetime Milk Yield using Principal Component Analysis in Gir Cattle

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Nikhil S. Dangar — Department of Animal Genetics and Breeding, College of Veterinary Science and Animal Husbandry, Navsari Agricultural University, Navsari, Gujarat, India
Pravin H. Vataliya — Directorate of Extension Education, Kamdhenu University, Gandhinagar, Gujrat, India.
Published 15 Sep 2022 Vol. 18 No. 4 (2022), pp. 92-96 ● Open access
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Abstract

The objective of the research was to investigate the relationship among production traits i.e., lactation milk yield, lactation length  and lactation peak milk yield of the first three lactations using principal component analysis and formulation of prediction equation  to predict lifetime milk production in Gir cattle. Data were from multiparous dairy cows of the University farm. Principal component  analysis with correlation matrix was used to find the relationship among lactation milk yield, lactation length and lactation peak milk  yield of first three lactation and other fixed effects, including the year of calving, season and parity with random effect of sire. The  principal components were fitted to identify the best-fitted model for predicting lifetime milk yield using all principal components as  a predictor in different combinations. The first six principal components (first lactation milk yield, lactation length and peak milk yield,  second lactation milk yield, lactation length and peak milk yield), explained 98% variation in the estimated values with adjusted R2=  59.85% variation in the estimated values. The curve estimation analysis revealed that the first six principal components as the predictor  was the most fitting model for predicting lifetime milk yield. The prediction equation found most fitted will be useful for the selection  of Gir cattle at an early stage of lactation. 

KeywordsGir cattleLifetime milk yieldMultiple linear regressionPredictionPrincipal component

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  1. Bhatacharya, T.K., & Gandhi, R.S. (2005). Principal components versus multiple regression analysis to predict lifetime production of Karan Fries cattle. Indian Journal of Animal Sciences, 75(11), 1317-1320.
  2. Chaudhary, P.N., Kapadiya, P.S., Gadariya, M.R., Gamit, P.M. & Savaliya, B.D. (2022). Test-day and other milk recording options for prediction of lactation milk yield on Gir cows. Indian Journal of Veterinary Science and Biotechnology, 18(2), 85-89.
  3. Chapman, K.W., Lawless, H.T., & Boor, K.J. (2001). Quantitative descriptive analysis and principal component analysis for sensory characterization of ultra-pasteurized milk. Journal of Dairy Science, 84, 12-20.
  4. Dangar, N., & Vataliya, P. (2017). Genetic, Phenotypic and Environmental Trend for Milk Yield and Production Efficiency Traits in Gir Cattle. International Journal of Livestock Research, 7(9), 36-42.
  5. Dangar, N., & Vataliya, P. (2015). Factors affecting lactation milk yield in Gir Cattle. Indian Veterinary Journal, 92(7), 71-73. Hotelling, H. (1933). Analysis of the complex of statistical variables into principal components. Journal of Educational Psychology, 24, 417-441, 498-502.
  6. Khan, T.A., Tomar, A.K. S., & Dutt, T. (2012). Prediction of lifetime milk production in synthetic crossbred cattle strain Vrindavani of North India. Indian Journal of Animal Sciences, 82, 1367-1371.
  7. Khan, T.A., Tomar, A.K.S., Dutt, T., & Bhushan, B. (2013). Principal component regression analysis in lifetime milk yield
  8. prediction of crossbred cattle strain Vrindavani of North India. Indian Journal of Animal Sciences, 83, 1288-1291.
  9. Parikh, S.S., Savaliya, B.D., Patbandha, T. K. & Makwana, R.B. (2022). Calf, dam and sire factors affect body weight of Gir calve. Indian Journal of Veterinary Science and Biotechnology, 18(2), 49-53.
  10. Rougoor, C.W., Sundaram, R., & Van Arendonk, J.A.M. (2000). The relation between breeding management and 305–day milk production determined via principal components regression and partial least squares. Livestock Production Science, 66, 71-83.

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