Progression of different udder inflammation indicators and their episode length after onset of inflammation using automatic milking system sensor data.


Journal

Journal of dairy science
ISSN: 1525-3198
Titre abrégé: J Dairy Sci
Pays: United States
ID NLM: 2985126R

Informations de publication

Date de publication:
Mar 2021
Historique:
received: 13 12 2019
accepted: 24 09 2020
pubmed: 29 12 2020
medline: 15 4 2021
entrez: 28 12 2020
Statut: ppublish

Résumé

In automatic milking systems (AMS), sensors can measure cow behavior and milk composition at every milking. The aim of this observational study of previously collected data was to gain insight into the differences in dynamics of udder inflammation indicators between cows that recover and those that do not recover after detection of an initial inflammation. Milk diversion (milk separated from the bulk tank and thus indicating farmer intervention), conductivity, and somatic cell count (SCC) data from 4 wk before the initial inflammation to 12 wk after the initial inflammation were used to analyze 2,584 cases of udder inflammation. An udder inflammation case was defined as an initial observation of SCC ≥200,000 cells/mL as well as 1 additional SCC measurement >200,000 cells/mL within 10 d after the initial case, among other requirements. The data originated from 15 AMS herds in 6 countries. Four subsets of cows were created based on whether milk was diverted after the initial inflammation and whether the udder inflammation cases recovered, using a 10-d rolling average SCC threshold of 200,000 cells/mL and checking whether this rolling mean was below the threshold within 90 d after the initial inflammation as the indication of recovery. This formed the following subsets of cow lactations: milk diverted-recovered, milk diverted-not recovered, no milk diverted-not recovered, no milk diverted-recovered. Thresholds of 100,000 SCC/mL and 300,000 SCC/mL for the definition of case and recovery were also applied in a sensitivity analysis but with no substantial difference in results. Linear mixed models were used for each subset to study the variation in SCC (natural logarithm of SCC divided by 1,000) and σ-conductivity (natural logarithm of standard deviation of quarter conductivities). When observing the fraction of cows with SCC <200,000 cells/mL in the recovery subsets, most cows recovered within 20 d after the initial inflammation. In the recovery subsets, both σ-conductivity and SCC stabilized, mostly within 3 to 4 wk after the initial inflammation. σ-Conductivity stabilized above the pre-onset level in all subsets and did not show a clear increase in the no-milk-diverted subgroups, whereas SCC stabilized closer to the pre-onset level. Overall, this study indicated a cutoff point between nonchronic and chronic changes in indicators 3 to 4 wk after the initial inflammation for SCC and σ-conductivity.

Identifiants

pubmed: 33358823
pii: S0022-0302(20)31066-3
doi: 10.3168/jds.2019-18054
pii:
doi:

Types de publication

Journal Article Observational Study, Veterinary

Langues

eng

Sous-ensembles de citation

IM

Pagination

3458-3473

Informations de copyright

The Authors. Published by Elsevier Inc. and Fass Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Auteurs

John Bonestroo (J)

DeLaval International AB, Gustaf De Lavals väg 15, 147 21 Tumba, Sweden; Swedish University of Agricultural Sciences, Department of Clinical Sciences, PO Box 7054, SE-750 07 Uppsala, Sweden; Wageningen University and Research, Business Economics Group, Hollandseweg 1, 6706 KN Wageningen, the Netherlands. Electronic address: John.bonestroo@delaval.com.

Mariska van der Voort (M)

Wageningen University and Research, Business Economics Group, Hollandseweg 1, 6706 KN Wageningen, the Netherlands.

Nils Fall (N)

Swedish University of Agricultural Sciences, Department of Clinical Sciences, PO Box 7054, SE-750 07 Uppsala, Sweden.

Henk Hogeveen (H)

Wageningen University and Research, Business Economics Group, Hollandseweg 1, 6706 KN Wageningen, the Netherlands.

Ulf Emanuelson (U)

Swedish University of Agricultural Sciences, Department of Clinical Sciences, PO Box 7054, SE-750 07 Uppsala, Sweden.

Ilka Christine Klaas (IC)

DeLaval International AB, Gustaf De Lavals väg 15, 147 21 Tumba, Sweden.

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Classifications MeSH