Comparison of machine learning methods to predict udder health status based on somatic cell counts in dairy cows
Abstract Bovine mastitis is one of the most important economic and health issues in dairy farms. Data collection during routine recording procedures and access to large datasets have shed the light on the possibility to use trained machine learning algorithms to predict the udder health status of co...
Saved in:
Main Authors: | Tania Bobbo, Stefano Biffani, Cristian Taccioli, Mauro Penasa, Martino Cassandro |
---|---|
Format: | article |
Language: | EN |
Published: |
Nature Portfolio
2021
|
Subjects: | |
Online Access: | https://doaj.org/article/f92da889623c4b0d91bf3a497f495f1f |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A new standard model for milk yield in dairy cows based on udder physiology at the milking-session level
by: Patrick Gasqui, et al.
Published: (2017) -
Effect of test year, parity number and days in milk on somatic cell count in dairy cows of Los Ríos region in Chile
by: Sebastino,Kiala B., et al.
Published: (2020) -
Milking Machines on Chilean Dairy Farms and their Effects on Somatic Cell Count and Milk Yield: A Fied Study
by: Garcés A,R, et al.
Published: (2006) -
Machine learning approaches for the prediction of lameness in dairy cows
by: S. Shahinfar, et al.
Published: (2021) -
Structural equation modeling for investigating multi-trait genetic architecture of udder health in dairy cattle
by: Sara Pegolo, et al.
Published: (2020)