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Using machine learning methods to predict dry matter intake from milk mid-infrared spectroscopy data on Swedish dairy cattle

In this research communication we compare three different approaches for developing dry matter intake (DMI) prediction models based on milk mid-infrared spectra (MIRS), using data collected from a research herd over five years. In dairy production, knowledge of individual DMI could be important and...

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Bibliographic Details
Main Authors: Mohamad Salleh, Suraya, Danielsson, Rebecca, Kronqvist, Cecilia
Format: Article
Published: Cambridge University Press (CUP) 2023
Online Access:http://psasir.upm.edu.my/id/eprint/108431/
https://www.cambridge.org/core/journals/journal-of-dairy-research/article/using-machine-learning-methods-to-predict-dry-matter-intake-from-milk-midinfrared-spectroscopy-data-on-swedish-dairy-cattle/A06673BFE835058C2CA1FDFC975AA58F
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http://psasir.upm.edu.my/id/eprint/108431/
https://www.cambridge.org/core/journals/journal-of-dairy-research/article/using-machine-learning-methods-to-predict-dry-matter-intake-from-milk-midinfrared-spectroscopy-data-on-swedish-dairy-cattle/A06673BFE835058C2CA1FDFC975AA58F

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