Multiple Country Approach to Improve the Test-Day Prediction of Dairy Cows’ Dry Matter Intake

Multiple Country Approach to Improve the Test-Day Prediction of Dairy Cows’ Dry Matter Intake

We predicted dry matter intake of dairy cows using parity, week of lactation, milk yield, milk mid-infrared (MIR) spectrum, and MIR-based predictions of bodyweight, fat, protein, lactose, and fatty acids content in milk. The dataset comprised 10,711 samples of 534 dairy cows with a geographical dive...

Full description

Bibliographic Details
Main Authors: Anthony Tedde, Clément Grelet, Phuong N. Ho, Jennie E. Pryce, Dagnachew Hailemariam, Zhiquan Wang, Graham Plastow, Nicolas Gengler, Eric Froidmont, Frédéric Dehareng, Carlo Bertozzi, Mark A. Crowe, Hélène Soyeurt, on behalf of the GplusE Consortium
Format: Article
Language:English
Published: MDPI AG 2021-05-01
Series:Animals
Subjects:
dry matter intake
partial least square
artificial neural network
dimensionality reduction
machine learning
dairy cows
Online Access:https://www.mdpi.com/2076-2615/11/5/1316

Internet

https://www.mdpi.com/2076-2615/11/5/1316

Similar Items