Estimating the nonlinear association of online somatic cell count, lactate dehydrogenase, and electrical conductivity with milk yield.


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:
Apr 2022
Historique:
received: 29 09 2021
accepted: 04 12 2021
pubmed: 1 2 2022
medline: 23 3 2022
entrez: 31 1 2022
Statut: ppublish

Résumé

Reduction of milk yield is one of the principal components in the cost of mastitis. However, past research into the association between milk yield and mastitis indicators is limited. Past research has not been based on online or in-line daily measurements and has not fully explored nonlinearity and the thresholds at which milk yield starts to decrease. In dairy herds with automated milking systems equipped with sensors, mastitis indicators of individual cows are measured on an intraday frequency, which provides unprecedented avenues to explore such effects in detail. The aim of this observational study was primarily to investigate the nonlinear associations of lactate dehydrogenase (LDH), electrical conductivity (EC), and somatic cell count (SCC) with milk yield at various stages of lactation, parity, and mastitis chronicity status (i.e., whether the cow had SCC ≥200,000 SCC/mL for the last 28 d). We also investigated thresholds at which mastitis indicators (LDH, EC, and SCC) started to be negatively associated with milk yield. We used data from 21 automated milking system herds measuring EC and online SCC. Of these herds, 7 of the 21 additionally measured online LDH. We operationalized milk yield as milk synthesis rate in kilograms per hour. Applying a generalized additive model, we estimated the milk synthesis rate as a function of the 3 mastitis indicators for 3 different subgroups based on parity, stage of lactation, and mastitis chronicity. Partial dependence plots of the mastitis indicators were used to evaluate the milk synthesis rate to study if the milk synthesis rate was associated with mastitis indicators at a specific level. Results showed that milk synthesis rate decreased with increasing SCC, LDH, and EC, but in a nonlinear fashion. The thresholds at which milk synthesis rate started to decrease were 2.5 LnSCC (12,000 SCC/mL) to 3.75 LnSCC (43,000 SCC/mL), 0 to 1 LnLDH (1-2.7 U/L), and 5.0 to 6.0 mS/cm for EC. Additionally, another substantial decrease of milk synthesis rate was observed at thresholds of 5.625 LnSCC (277,000 SCC/mL) and 3 LnLDH (20 LDH U/L) but not for EC. Having chronic mastitis decreased milk synthesis rate in all models. The identified nonlinearities between mastitis indicators and milk synthesis rate should be incorporated in statistical models for more accurate estimations of milk loss due to mastitis.

Identifiants

pubmed: 35094852
pii: S0022-0302(22)00051-0
doi: 10.3168/jds.2021-21351
pii:
doi:

Substances chimiques

L-Lactate Dehydrogenase EC 1.1.1.27

Types de publication

Journal Article Observational Study Observational Study, Veterinary

Langues

eng

Sous-ensembles de citation

IM

Pagination

3518-3529

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 license (http://creativecommons.org/licenses/by/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)

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

Nils Fall (N)

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

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.

Henk Hogeveen (H)

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

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Classifications MeSH