Bayesian regression models outperform partial least squares methods for predicting milk components and technological properties using infrared spectral data

The aim of this study was to assess the performance of Bayesian models commonly used for genomic selection to predict "difficult-to-predict" dairy traits, such as milk fatty acid (FA) expressed as percentage of total fatty acids, and technological properties, such as fresh cheese yield and...

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Podrobná bibliografie
Vydáno v:	Journal of dairy science Ročník 98; číslo 11; s. 8133
Hlavní autoři:	Ferragina, A, de los Campos, G, Vazquez, A I, Cecchinato, A, Bittante, G
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	United States 01.11.2015
Témata:	Animals Bayes Theorem Calibration Cattle Cheese - analysis Fatty Acids - analysis Female Least-Squares Analysis Milk - chemistry Milk Proteins - analysis Principal Component Analysis Regression Analysis Spectroscopy, Fourier Transform Infrared - veterinary fatty acid cheese yield milk trait Bayesian method infrared spectroscopy
ISSN:	1525-3198, 1525-3198
On-line přístup:	Zjistit podrobnosti o přístupu
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