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Current IssueEditorial BoardOnline First ArticlesArchive

Research Article

volume 53 issue 10 (october 2019) : 1287-1291,   Doi: 10.18805/ijar.B-3661

Comparative efficiency of different multiple linear regression prediction equations of first lactation 305-day milk yield for sire evaluation in Murrah buffaloes

S
Saroj Kumar Sahoo
A
Avtar Singh
G
G.S. Ambhore
S
S.K. Dash
P
P.P. Dubey
1<div style="text-align: justify;">ICAR-National Dairy Research Institute, Karnal-132 001, Haryana, India.</div>
Cite article:- Sahoo Kumar Saroj, Singh Avtar, Ambhore G.S., Dash S.K., Dubey P.P. (2018). Comparative efficiency of different multiple linear regression prediction equations of first lactation 305-day milk yield for sire evaluation in Murrah buffaloes. Indian Journal of Animal Research. 53(10): 1287-1291. doi: 10.18805/ijar.B-3661.

ABSTRACT

In this study, first lactation 39059 weekly test-day milk yield records of 961 Murrah buffaloes were used to predict first lactation 305-day milk yield (FL305DMY) by stepwise backward regression method. The best single, two, three and four test day combinations were selected for prediction of FL305DMY based on adjusted R2 and RMSE values. The sires were evaluated for 305-day actual and predicted first lactation milk yield based on derived multiple regression equations using four methods viz. least squares (LSQ), simple regressed least squares (SRLS), best linear unbiased prediction sire model (BLUP-SM) and best linear unbiased prediction animal model (BLUP-AM) methods. The effectiveness of different sire evaluation methods were judged by error variance, coefficient of determination, coefficient of variation and spearman’s rank correlation. The accuracy of prediction of FL305DMY from weekly test day milk yields were observed to be best for TD-7 (48th day) and TD-22 (153rd day) combination with BLUP-AM as the most efficient method for sire evaluation. It was concluded that the FL305DMY can be predicted as early as 153rd day of lactation and further can be used for early genetic evaluation of Murrah sires.

REFERENCES

  1. Banik, S. and Gandhi, R. S. (2006). Animal model versus conventional methods of sire evaluation in Sahiwal cattle. Asian-Australasian    Journal of Animal Sciences 19(9): 1225-1228.
  2. Banu, R.N. (2010). Genetic evaluation of the lactation curve in Karan Fries cattle. Ph.D. Thesis, NDRI, (Deemed University), Karnal, India.
  3. Chakraborty , D., Dhaka, S. S., Pander, B. L., Yadav, A. S., Singh, S., Malik P. K. (2010). Prediction of lactation milk yield from test day records in Murrah buffaloes. Indian Journal of Animal Science 80: 244-245.
  4. Dash, S.K., Gupta, A.K., Singh, A., Chakravarty, A.K., Madhusoodanan, M., Valsalan, J., Shivahre, P.R., Hussain, A. (2014). Evaluation of efficiency of sire model and animal model in Holstein Friesian crossbred cattle considering first lactation production and fertility traits. Veterinary World 7: 933-937.
  5. Dongre, V.B., Gandhi, R.S., Singh, A, Ruhil A.P. (2012). Comparative efficiency of artificial neural networks and multiple linear regression analysis for prediction of first lactation 305-day milk yield in Sahiwal cattle. Livestock Science 147 (1-3):192-197.
  6. Kumar, V., Chakravarty, A. K., Patil, C. S., Shivahre, P. R., Gupta, A. (2015). Comparison among different conventional methods of sire evaluation in Murrah buffalo. Indian Journal of Animal Science 85(6): 670-673.
  7. Mukherjee, S. (2005). Genetic evaluation of Frieswal cattle. Ph.D Thesis, NDRI (Deemed University), Karnal, Haryana, India.
  8. Rana, J.S. (2008). Genetic evaluation of Murrah buffalo sires based on part lactation and test day milk yield records. Ph.D. Thesis submitted to Ch. Charan Singh University, Meerut (UP).
  9. Sahoo, S.K., Singh, A., Dash, S.K., Ambhore, G.S. (2017). Modeling lactation curve for genetic evaluation of Murrah buffaloes. Indian Journal of Animal Research DOI: 10.18805/ijar.B-3432
  10. SAS Enterprise Guide 4.3. (2003). SAS Institute Incorporation Raleigh, North Carolina, U.S.A.
  11. Singh, M., Singh, A., Gupta, A.K., Chakravarty, A.K., Prakash, V., Singh, A., Sahoo, S.K. (2014). Relative effectiveness of best linear unbiased prediction-animal model vis-à-vis other sire evaluation methods for genetic evaluation of Murrah sires. Indian Journal of Dairy Science 67(6):510-514.
  12. Singh, S. and Tailor, S.P. (2013). Prediction of 305 days first lactation milk yield from fortnightly test and part yields. Indian Journal of Animal Science 83(2): 166-169. 
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    Research Article

    volume 53 issue 10 (october 2019) : 1287-1291,   Doi: 10.18805/ijar.B-3661

    Comparative efficiency of different multiple linear regression prediction equations of first lactation 305-day milk yield for sire evaluation in Murrah buffaloes

    S
    Saroj Kumar Sahoo
    A
    Avtar Singh
    G
    G.S. Ambhore
    S
    S.K. Dash
    P
    P.P. Dubey
    1<div style="text-align: justify;">ICAR-National Dairy Research Institute, Karnal-132 001, Haryana, India.</div>
    Cite article:- Sahoo Kumar Saroj, Singh Avtar, Ambhore G.S., Dash S.K., Dubey P.P. (2018). Comparative efficiency of different multiple linear regression prediction equations of first lactation 305-day milk yield for sire evaluation in Murrah buffaloes. Indian Journal of Animal Research. 53(10): 1287-1291. doi: 10.18805/ijar.B-3661.

    ABSTRACT

    In this study, first lactation 39059 weekly test-day milk yield records of 961 Murrah buffaloes were used to predict first lactation 305-day milk yield (FL305DMY) by stepwise backward regression method. The best single, two, three and four test day combinations were selected for prediction of FL305DMY based on adjusted R2 and RMSE values. The sires were evaluated for 305-day actual and predicted first lactation milk yield based on derived multiple regression equations using four methods viz. least squares (LSQ), simple regressed least squares (SRLS), best linear unbiased prediction sire model (BLUP-SM) and best linear unbiased prediction animal model (BLUP-AM) methods. The effectiveness of different sire evaluation methods were judged by error variance, coefficient of determination, coefficient of variation and spearman’s rank correlation. The accuracy of prediction of FL305DMY from weekly test day milk yields were observed to be best for TD-7 (48th day) and TD-22 (153rd day) combination with BLUP-AM as the most efficient method for sire evaluation. It was concluded that the FL305DMY can be predicted as early as 153rd day of lactation and further can be used for early genetic evaluation of Murrah sires.

    REFERENCES

    1. Banik, S. and Gandhi, R. S. (2006). Animal model versus conventional methods of sire evaluation in Sahiwal cattle. Asian-Australasian    Journal of Animal Sciences 19(9): 1225-1228.
    2. Banu, R.N. (2010). Genetic evaluation of the lactation curve in Karan Fries cattle. Ph.D. Thesis, NDRI, (Deemed University), Karnal, India.
    3. Chakraborty , D., Dhaka, S. S., Pander, B. L., Yadav, A. S., Singh, S., Malik P. K. (2010). Prediction of lactation milk yield from test day records in Murrah buffaloes. Indian Journal of Animal Science 80: 244-245.
    4. Dash, S.K., Gupta, A.K., Singh, A., Chakravarty, A.K., Madhusoodanan, M., Valsalan, J., Shivahre, P.R., Hussain, A. (2014). Evaluation of efficiency of sire model and animal model in Holstein Friesian crossbred cattle considering first lactation production and fertility traits. Veterinary World 7: 933-937.
    5. Dongre, V.B., Gandhi, R.S., Singh, A, Ruhil A.P. (2012). Comparative efficiency of artificial neural networks and multiple linear regression analysis for prediction of first lactation 305-day milk yield in Sahiwal cattle. Livestock Science 147 (1-3):192-197.
    6. Kumar, V., Chakravarty, A. K., Patil, C. S., Shivahre, P. R., Gupta, A. (2015). Comparison among different conventional methods of sire evaluation in Murrah buffalo. Indian Journal of Animal Science 85(6): 670-673.
    7. Mukherjee, S. (2005). Genetic evaluation of Frieswal cattle. Ph.D Thesis, NDRI (Deemed University), Karnal, Haryana, India.
    8. Rana, J.S. (2008). Genetic evaluation of Murrah buffalo sires based on part lactation and test day milk yield records. Ph.D. Thesis submitted to Ch. Charan Singh University, Meerut (UP).
    9. Sahoo, S.K., Singh, A., Dash, S.K., Ambhore, G.S. (2017). Modeling lactation curve for genetic evaluation of Murrah buffaloes. Indian Journal of Animal Research DOI: 10.18805/ijar.B-3432
    10. SAS Enterprise Guide 4.3. (2003). SAS Institute Incorporation Raleigh, North Carolina, U.S.A.
    11. Singh, M., Singh, A., Gupta, A.K., Chakravarty, A.K., Prakash, V., Singh, A., Sahoo, S.K. (2014). Relative effectiveness of best linear unbiased prediction-animal model vis-à-vis other sire evaluation methods for genetic evaluation of Murrah sires. Indian Journal of Dairy Science 67(6):510-514.
    12. Singh, S. and Tailor, S.P. (2013). Prediction of 305 days first lactation milk yield from fortnightly test and part yields. Indian Journal of Animal Science 83(2): 166-169. 
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