production of milk yield from udder circumference and distance between teats in West African Dwarf and red Sokoto goats

Authors

  • M.N. Benji University of agriculture, P.M.B 2240, Abeokuta, Nigeria
  • O.A Osinowu University of agriculture, P.M.B 2240, Abeokuta, Nigeria

DOI:

https://doi.org/10.51791/njap.v36i1.918

Keywords:

Goats, Uddercircumference, Distance between teats, Milk yield, prediction

Abstract

Udder circumference (UD) and distance between teats (DBT) measured before and after  milking were used to determine CUC (UC before milking minus UC after milking) and CDT (DBT before milking minus DBT after milking).  All four parameters were utilized as independent variables in two milk yeild from 202 weekly records of 17 lactating does, consisting of 8 West African Dwarf (WAD) and 9 Red sokoto (RS) goats. WAD and RS goats hadsimilar mean values for daily milk yield ( 270.34±12.47 ml vs 245.26±14.51 ml) and UC(28.49±0.33 vs 28.49± 0.13 cm). Both models had significant ( P<0.001) R2 values ranging from 0.244 to 0.757. UC was the best index of milk yeild (R2=0.688) followed by CUC (R2=0.467) in the linear regressionequation while DBT and CDT yeilded lower R2 Values (0.244 vs 0.258).  Inclusion of all four parameters in the multiple linear regression equation yeilded the highest R2 (0.757). The predictive equation was Y= 441.443 + 25.739X1 + 23.349-21.265X+61.080X4 in which Y is milk yeilded, Xi , X represent UC, CUC, DBT and CDT respectively. Positive and significant (P<0.001) phenotypic correlations were observed between UCand milk yeilded (0.759), CUC and milk yeilded (0.690). DBT and milk yield (0.498), CDT and milk yield(0.508). In the current practice of collecting collecting weekly records, early prediction of future milk production from udder circumference measured prior to milking will be accurate using linear regression predictive equation. Alternatively, if more traits related to udder size such as UC, CUC,DBT and CDT are incorporated as independent variables in multiple linear regression equation, milk production would be predicted with better accuracy.

Author Biographies

M.N. Benji, University of agriculture, P.M.B 2240, Abeokuta, Nigeria

Department of animal Breeding and genetics

O.A Osinowu, University of agriculture, P.M.B 2240, Abeokuta, Nigeria

Department of Animal physiology

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Published

2021-01-01

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Section

Articles