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Use of a partial least squares regression model to predict Test Day of milk, fat and protein yields in dairy goats

Macciotta, Nicolò Pietro Paolo and Dimauro, Corrado and Bacciu, Nicola and Fresi, Pancrazio and Cappio Borlino, Aldo (2006) Use of a partial least squares regression model to predict Test Day of milk, fat and protein yields in dairy goats. Animal Science, Vol. 82 , p. 463-468. eISSN 1748-748X. Article.

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DOI: 10.1079/ASC200659


A model able to predict missing test day data for milk, fat and protein yields on the basis of few recorded tests was proposed, based on the partial least squares (PLS) regression technique, a multivariate method that is able to solve problems related to high collinearity among predictors. A data set of 1731 lactations of Sarda breed dairy Goats was split into two data sets, one for model estimation and the other for the evaluation of PLS prediction capability. Eight scenarios of simplified recording schemes for fat and protein yields were simulated. Correlations among predicted and observed test day yields were quite high (from 050 to 088 and from 053 to 096 for fat and protein yields, respectively, in the different scenarios). Results highlight great flexibility and accuracy of this multivariate technique.

Item Type:Article
ID Code:3619
Uncontrolled Keywords:Goats, milk fat, milk protein, prediction, regression analysis
Subjects:Area 07 - Scienze agrarie e veterinarie > AGR/17 Zootecnica generale e miglioramento genetico
Area 07 - Scienze agrarie e veterinarie > AGR/19 Zootecnica speciale
Divisions:001 Università di Sassari > 01 Dipartimenti > Scienze zootecniche
Publisher:Cambridge University Press
Copyright Holders:© British Society of Animal Science 2006
Publisher Policy:Depositato in conformità con la politica di copyright dell'Editore
Deposited On:23 Mar 2010 13:21

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