Assessing different cross-validation schemes for predicting novel traits using sensor data: an application to dry matter intake and residual feed intake using milk spectral data-Reference-Cited by-同舟云学术

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Assessing different cross-validation schemes for predicting novel traits using sensor data: an application to dry matter intake and residual feed intake using milk spectral data

Published:2024-06 Issue: Volume: Page:
ISSN:0022-0302
Container-title:Journal of Dairy Science
language:en
Short-container-title:Journal of Dairy Science

Author:

Adkinson A.Yilmaz,Abouhawwash M.,VandeHaar M.J.,Gaddis K.L. Parker,Burchard J.,Peñagaricano F.,White H.M.,Weigel K.A.,Baldwin R.,Santos J.E.P.,Koltes J.E.,Tempelman R.J.

Funder

Foundation for Food and Agriculture Research

Publisher

American Dairy Science Association

Reference28 articles.

1. Invited review: Mid-infrared spectroscopy as phenotyping tool for milk traits1;De Marchi;J. Dairy Sci.,2014

2. Mining data from milk infrared spectroscopy to improve feed intake predictions in lactating dairy cows;Dórea;J. Dairy Sci.,2018

3. Bayesian regression models outperform partial least squares methods for predicting milk components and technological properties using infrared spectral data;Ferragina;J. Dairy Sci.,2015

4. Model Evaluation by Comparison of Model-Based Predictions and Measured Values;Gauch;Agron. J.,2003

5. Standardization of milk mid-infrared spectra from a European dairy network;Grelet;J. Dairy Sci.,2015

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