Usefulness of differential somatic cell count for udder health monitoring: Effect of intramammary infections, days in milk, quarter location, and parity on quarter-level differential somatic cell count and somatic cell score in apparently healthy dai

Microbial infections of the mammary gland often cause mastitis, and it can lead to substantial economic losses within the dairy industry due to its direct negative impact on milk production and composition and the associated treatment costs. Somatic cell count has emerged as a critical indicator in monitoring udder health, and recently, the large-scale availability of differential cell count analysis potentially offers new insights into underlying physiological processes. Therefore, the main objective of this study was to estimate the variation of differential SCC (DSCC) and SCC of individual quarter-level milk samples of cows according to (1) their intramammary infectious status; (2) parity of the cow; (3) quarter location; and (4) DIM at the time of sampling. A convenience sample of 5 dairy herds using an automated milking system was selected and visited every 2 wk for milk sample collection. The determination of SCC and DSCC was performed by Lactanet using a CombiFoss 7 DC instrument. The bacteriological culture was performed according to the National Mastitis Council standards. The different types of colonies (up to 10 colonies) were counted and identified using MALDI-TOF. Given the hierarchical structure of the data, a 4-level, linear mixed model with herd, cow, and quarter as random intercepts was built with either SCS or DSCC as the outcome. Differential SCC varied broadly in the SCS range 2 to 12 but tended to have a narrower variation at higher SCS levels. The effect of DIM on DSCC depended on the parity. Early in lactation, primiparous cows tended to have lower DSCC than older cows. Following 230 DIM, the DSCC in primiparous exhibited an upward trend, whereas, in older cows, it tended to decline. The quarter position did not affect either DSCC or SCS. Quarters infected with Staphylococcus chromogenes, Streptococcus dysgalactiae, Staphylococcus aureus, Staphylococcus epidermidis, "other major," and "other minor," had an increase in DSCC by ∼10.2%, 9.9%, 9.8%, 9.2%, 6.0%, and 4.9%, respectively, when compared with quarters with no growth. Our findings highlighted that IMI, parity, and DIM influenced DSCC. Therefore, these parameters should be considered when interpreting DSCC.

Authors

Institutions

Publication Details

Journal
Journal of Dairy Science
Published
2024-12-18
DOI
https://doi.org/10.3168/jds.2024-25401
Citations
6
Primary Topic
Milk Quality and Mastitis in Dairy Cows
Type
article
Field-Weighted Citation Impact
3.41
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Usefulness of differential somatic cell count for udder health monitoring: Effect of intramammary infections, days in milk, quarter location, and parity on quarter-level differential somatic cell count and somatic cell score in apparently healthy dai

Simon Dufour, D.E. Santschi, Mariana Fonseca, Daryna Kurban et al.
6 citations
Journal of Dairy Science
Milk Quality and Mastitis in Dairy Cows
3.41
article

Usefulness of differential somatic cell count for udder health monitoring: Effect of intramammary infections, days in milk, quarter location, and parity on quarter-level differential somatic cell count and somatic cell score in apparently healthy dai

Simon Dufour, D.E. Santschi, Mariana Fonseca, Daryna Kurban, Jean‐Philippe Roy, Elouise Molgat
article en
6 citations

Abstract

Microbial infections of the mammary gland often cause mastitis, and it can lead to substantial economic losses within the dairy industry due to its direct negative impact on milk production and composition and the associated treatment costs. Somatic cell count has emerged as a critical indicator in monitoring udder health, and recently, the large-scale availability of differential cell count analysis potentially offers new insights into underlying physiological processes. Therefore, the main objective of this study was to estimate the variation of differential SCC (DSCC) and SCC of individual quarter-level milk samples of cows according to (1) their intramammary infectious status; (2) parity of the cow; (3) quarter location; and (4) DIM at the time of sampling. A convenience sample of 5 dairy herds using an automated milking system was selected and visited every 2 wk for milk sample collection. The determination of SCC and DSCC was performed by Lactanet using a CombiFoss 7 DC instrument. The bacteriological culture was performed according to the National Mastitis Council standards. The different types of colonies (up to 10 colonies) were counted and identified using MALDI-TOF. Given the hierarchical structure of the data, a 4-level, linear mixed model with herd, cow, and quarter as random intercepts was built with either SCS or DSCC as the outcome. Differential SCC varied broadly in the SCS range 2 to 12 but tended to have a narrower variation at higher SCS levels. The effect of DIM on DSCC depended on the parity. Early in lactation, primiparous cows tended to have lower DSCC than older cows. Following 230 DIM, the DSCC in primiparous exhibited an upward trend, whereas, in older cows, it tended to decline. The quarter position did not affect either DSCC or SCS. Quarters infected with Staphylococcus chromogenes, Streptococcus dysgalactiae, Staphylococcus aureus, Staphylococcus epidermidis, "other major," and "other minor," had an increase in DSCC by ∼10.2%, 9.9%, 9.8%, 9.2%, 6.0%, and 4.9%, respectively, when compared with quarters with no growth. Our findings highlighted that IMI, parity, and DIM influenced DSCC. Therefore, these parameters should be considered when interpreting DSCC.

Journal of Dairy ScienceVol. 108(4)
Cegep de Saint Hyacinthe (CA), Artificial Insemination Center of Quebec (CA), Ste. Anne's Hospital (CA), CTT Group (Canada) (CA)
Zero hunger
Openalex Percentile: Top 8%
Milk Quality and Mastitis in Dairy Cows
3.41
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.