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Milk yield prediction between Bunaji Holstein Friesian cross bred and Holstein Frisian cows using linear, cubic and quadratic models
Author(s) -
Mohammed Liman,
Gwaza Sylvester,
Bala Dogara
Publication year - 2018
Publication title -
biotechnology in animal husbandry
Language(s) - English
Resource type - Journals
eISSN - 2217-7140
pISSN - 1450-9156
DOI - 10.2298/bah1801119l
Subject(s) - yield (engineering) , polynomial regression , quadratic model , mathematics , lactation , zoology , linear regression , quadratic equation , dairy cattle , variance components , statistics , biology , physics , geometry , pregnancy , response surface methodology , genetics , thermodynamics
The aim of this study was to compare three different models (Linear, cubic and quadratic) to find best model for predicting milk yield. Data originated from the monthly milk yields records of 251 Bunaji Holstein Friesian crossed and Holstein Friesian cows from 2010 to 2015. The daily milk yield data were regressed against time (day of lactation) for individual cow, using the procedure of SAS, (2002). The resulting polynomial regression coefficients (linear, quadratic and cubic) were then subjected to variance of analysis. All models provided an acceptable level of accuracy in predicting milk yield for Bunaji Holstein Friesian crossed and Holstein Friesian cows, but cubic model is observed to be the most suitable with (R) values of (0.659, 0.582, 0.810 and 0.621) followed by quadratic model (0.447, 0.516, 0.614 and 0.605) while linear model has the least R values (0.02, 0.496, 0.548 and 0.309) in all the study farms.

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