The aim of this study is to model milk yield
using the MARS method using independent variables such as Holstein cows control
day, milking time, conductivity and mobility. MARS is a non-parametric method
for predicting linear sub-models to determine appropriate knot points of
non-linear models. This study included daily lactation records for 80 Holstein
cows between 2006 and 2011. For each lactation, the most suitable model was
determined by testing different maximum interaction models. The model
suitability is generally assessed by the criteria that generalized
cross-validation criterion (GCV) minimum and R2 maximum values. When
these criteria are taken into consideration, the non-interactive model for the
first four lactations and the 3 interacting model for the fifth lactation are
determined as the best models. The determination coefficients (R2) of the MARS models according to the lactation order
are found to be 0.983, 0.991, 0.991, 0.975 and 0.950, respectively. All the independent variable coefficients in models
were found to be important at 99% level. In all models, MARS has been
identified as the most meaningful variable of control day. According to these
results, we can say that the estimation of milk yield of models produced by
MARS is successful and safe.
Primary Language | Turkish |
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Journal Section | RESEARCH ARTICLE |
Authors | |
Publication Date | June 15, 2018 |
Submission Date | August 11, 2017 |
Acceptance Date | September 11, 2017 |
Published in Issue | Year 2018Volume: 21 Issue: 3 |
International Peer Reviewed Journal
Free submission and publication
Published 6 times a year
KSU Journal of Agriculture and Nature
e-ISSN: 2619-9149