2023
DOI: 10.1016/j.animal.2023.101000
|View full text |Cite
|
Sign up to set email alerts
|

Predicting fibre digestibility in Holstein dairy cows fed dry-hay-based rations through machine learning

D. Cavallini,
E. Raffrenato,
L.M.E. Mammi
et al.
Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

1
0
0

Year Published

2023
2023
2024
2024

Publication Types

Select...
4

Relationship

0
4

Authors

Journals

citations
Cited by 4 publications
(1 citation statement)
references
References 55 publications
1
0
0
Order By: Relevance
“…The lack of differences for in vitro digestibility is in agreement with the observation of others for similar diets (94,95). For both groups, the level of N excretion was within the range reported by Spanghero and Kowalski (57) for similar N intake, while the NB estimate was lower, probably due to the higher milk N recorded in our study or a combination of unaccounted for N, such as urinary N excretion in forms not detected by the Kjeldhal method (e.g., nitrate), volatile losses of gaseous N and ammonia, and dermal scurf (57,96).…”
Section: Milk Performances Dry Matter Intake In Vivo Digestibility An...supporting
confidence: 92%
“…The lack of differences for in vitro digestibility is in agreement with the observation of others for similar diets (94,95). For both groups, the level of N excretion was within the range reported by Spanghero and Kowalski (57) for similar N intake, while the NB estimate was lower, probably due to the higher milk N recorded in our study or a combination of unaccounted for N, such as urinary N excretion in forms not detected by the Kjeldhal method (e.g., nitrate), volatile losses of gaseous N and ammonia, and dermal scurf (57,96).…”
Section: Milk Performances Dry Matter Intake In Vivo Digestibility An...supporting
confidence: 92%