Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2019 Apr 11;9(2):16-24.
doi: 10.1093/af/vfz003. eCollection 2019 Apr.

Analytics in sustainable precision animal nutrition

Douglas M Liebe  1 , Robin R White  1
Affiliations

Analytics in sustainable precision animal nutrition

Douglas M Liebe et al. Anim Front. .
No abstract available

Keywords: Internet of things; computer vision; data mining; machine learning.

PubMed Disclaimer

Figures

Figure 1.
Figure 1.
Depiction of the feedback loops between the farm manager, animal, and environment. The animal and environment influence each other, as do the animal and the manager’s decisions about the animal. Additionally, the manager can make decisions about the environment that will influence the animal.
Figure 2.
Figure 2.
Example of principal component analysis from three to two dimensions. Consider flashing a light on a set of points in three dimensions and observing the shadows of the points in two dimensions on the wall. The shining of the flashlight through the data represents the search for the plane which creates the greatest variance between groups in the data. The angle of the light in the bottom picture finds a better two-dimensional plane to project the points onto compared with the image above.
Figure 3.
Figure 3.
Comparison of fitting models after grouping results from principal component analysis (PCA). Grouping data based on a clustering algorithm allows the same model increased flexibility when making predictions. Notice that the model used does not change, only the data used to train the model is varied. DMI, dry matter intake.
Figure 4.
Figure 4.
An example plot of the proportion of variance explained by each additional component in principal component analysis. Variance explained by each additional component can vary considerably based on the data you are working with (Shah et al., 2018).
Figure 5.
Figure 5.
An example of a neural network framework. Circles represent individual equations which are fed data from all connected nodes. The lack of a 1-1 ratio of nodes in each layer of the network forces the model to condense information and leads to the most important information being determined iteratively through backpropagation of error (Ivezic et al., 2014).
See this image and copyright information in PMC

References

    1. Altman N. S. 1992. An Introduction to kernel and nearest-neighbor nonparametric regression. Am. Stat. 46:175–185. doi:10.1080/00031305.1992.10475879
    1. Berckmans D. 2014. Precision livestock farming technologies for welfare management in intensive livestock systems. Rev. Sci. Tech. 33:189–196. doi:10.20506/rst.33.1.2273 - PubMed
    1. Berry D. P., M. P., Coffey J. E., Pryce Y., de Haas P., Løvendahl N., Krattenmacher J. J., Crowley Z., Wang D., Spurlock K., Weigel, et al.2014. International genetic evaluations for feed intake in dairy cattle through the collation of data from multiple sources. J. Dairy Sci. 97:3894–3905. doi:10.3168/jds.2013-7548 - DOI - PubMed
    1. Berry D. P., and Crowley J. J.. . 2013. Cell biology symposium: genetics of feed efficiency in dairy and beef cattle. J. Anim. Sci. 91:1594–1613. doi:10.2527/jas.2012-5862 - DOI - PubMed
    1. Dale A. J., McGettrick S., Gordon A. W., and Ferris C. P.. . 2016. The effect of two contrasting concentrate allocation strategies on the performance of grazing dairy cows. Grass Forage Sci. 71:379–388. doi:10.1111/gfs.12185

LinkOut - more resources