• Title of article

    Estimation of Genetic Parameters for Milk Composition Traits in Indian Murrah Buffaloes

  • Author/Authors

    Valsalan, Jamuna Animal Genetics and Breeding Division - National Dairy Research Institute, Karnal, Haryana, India , Kumar Gupta, Ashok Animal Genetics and Breeding Division - National Dairy Research Institute, Karnal, Haryana, India , Kumar Chakravarty, Atish Animal Genetics and Breeding Division - National Dairy Research Institute, Karnal, Haryana, India , Ayoub Mir, Mohsin Animal Genetics and Breeding Division - National Dairy Research Institute, Karnal, Haryana, India

  • Pages
    5
  • From page
    229
  • To page
    233
  • Abstract
    The genetic parameters of monthly test day milk composition traits are used to find out the effectiveness of selection and to assess the producing ability of buffaloes in the herd. Data of 565 Murrah buffaloes sired by 72 bulls scattered over a period of 22 years (1993 to 2014) maintained at ICAR-National Dairy Research Institute, Karnal were used in the study. Minimum monthly test day fat percentage was estimated as 9.58±0.04 % on Test day 5 (165th day) while maximum monthly test fat percentage was estimated as 9.78±0.04% on Test day 2 (62th day). Minimum monthly test day SNF percentage was estimated as 9.60±0.01% on Test day 9 (291th day) and maximum monthly test fat percentage was estimated as 9.68±0.01% on Test day 3 (97th day.) Heritability estimates of monthly test day fat percentage ranged from 0.09 ± 0.03 on Test day 9 (296th day) to 0.19 ± 0.02 Test day 2 (62th day). Heritability estimates of monthly test day SNF percentage ranged from 0.06 ± 0.002 on Test day 8 (258th day) to 0.21 ± 0.06 Test day 3 (97th day). The estimates of genetic parameters suggests that emphasis should be given to milk composition traits along with milk yield for improving overall performances and effectiveness of selection criteria in Murrah buffaloes.
  • Keywords
    Fat percentage , SNF percentage , Heritability , Correlation , Murrah buffaloes
  • Journal title
    Advances in Animal and Veterinary Sciences
  • Serial Year
    2017
  • Record number

    2580948