%0 Journal Article
%9 Article
%W National Agricultural Library
%~ PubAg
%B Canadian journal of animal science
%T A comparison of neural network and multiple regression predictions for 305-day lactation yield using partial lactation records
%U http://pubs.nrc-cnrc.gc.ca/aic-journals/cjas.html
%A Grzesiak, W.
%A Lacroix, R.
%A Wójcik, J.
%A Blaszczyk, P.
%V 2003 v.83 no.2
%K calving
%K dairy cattle
%K herds
%K lactation
%K milk
%K milk yield
%K models
%K regression analysis
%M 387055
%X Milk yield predictions based on artificial neural etworks and multiple regression were studied. The 305-d lactation yield predictions were based on milk yield of the first 4 test days. Average 305-d milk production of the herd, number of days in milk and month of calving. The predictions made with either the neural network or the multiple regression model did not differ (P > 0.05) from the values estimated with the current Polish dairy cattle evaluation system. The neural network model may be alternative method of predicting these traits.
%D 2003
%= 2017-02-22
%G
%8 2003
%V v. 83
%N no. 2
%P pp. 307-310