Evaluation of Novel Biomarkers as Predictive Measures of Mastitis – Establishing a Relationship With Health Status, Lamb Performance, And Determination of Prevalence of Mastitis in Ewes Under Intensive Management

Inflammation of the mammary gland, also known as mastitis, is a prevalent and financially impactful disease in sheep production. The objectives of this survey were to 1) evaluate current testing methods: somatic cell count (SCC), California Mastitis Test (CMT), and bacterial culture, as well as novel biomarkers: lamb performance, milk composition, and udder conformation, for their impact on ewes categorized as clinically healthy or unhealthy under intensive management systems at 15 days in milk (DIM) and 30 DIM, and 2) identify biological markers that are correlated with clinical and subclinical mastitis. Milk, blood, and fecal samples, a visual and physical exam, as well as measures for intestinal parasite load (FAMACHA scores) were collected from lactating ewes at 15 DIM and 30 DIM, and fecal samples, body weights, and FAMACHA scores were collected from their lambs. Milk samples were evaluated for SCC, CMT, milk composition, and bacterial species identification (MALDI). Blood samples, FAMACHA scores, and components of the physical exam were utilized to determine systemic ewe health. Lamb weaning weights and calculated average daily gain (ADG) were collected to be used as a physical measure of decreased milk production, frequently seen in cases of mastitis. We hypothesized that there would be increases in SCC and CMT, and alterations in milk composition for ewes that are categorized with different health statuses, with compounding effects from other mastitis risk factors. Additionally, we hypothesized that correlations will be identified between biomarkers and SCC, CMT, and lamb performance for healthy ewes that differ between litter size and DIM. It was observed that SCC and CMT differed by health status, SCC, CMT, udder conformation, lamb ADG, and lamb weaning weights differed by litter size, and CMT, milk fat (MF), and milk total solids (MTS) differed by DIM. Additionally, correlations were established between several testing methods and SCC, CMT, and lamb ADG. These results indicated that MF, MTS, lactose, protein, and lamb performance could serve as novel biomarkers to identify subclinical mastitis, but more investigation is needed to determine what biological processes causes these differences and correlations.

Publication Details

Journal
Digital Commons - USU (Utah State University)
Published
2025-08-18
DOI
https://doi.org/10.26076/97b7-21d2
Primary Topic
Geochemistry and Geologic Mapping
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Evaluation of Novel Biomarkers as Predictive Measures of Mastitis – Establishing a Relationship With Health Status, Lamb Performance, And Determination of Prevalence of Mastitis in Ewes Under Intensive Management

Digital Commons - USU (Utah State University)
Geochemistry and Geologic Mapping
article

Evaluation of Novel Biomarkers as Predictive Measures of Mastitis – Establishing a Relationship With Health Status, Lamb Performance, And Determination of Prevalence of Mastitis in Ewes Under Intensive Management

article en

Abstract

Inflammation of the mammary gland, also known as mastitis, is a prevalent and financially impactful disease in sheep production. The objectives of this survey were to 1) evaluate current testing methods: somatic cell count (SCC), California Mastitis Test (CMT), and bacterial culture, as well as novel biomarkers: lamb performance, milk composition, and udder conformation, for their impact on ewes categorized as clinically healthy or unhealthy under intensive management systems at 15 days in milk (DIM) and 30 DIM, and 2) identify biological markers that are correlated with clinical and subclinical mastitis. Milk, blood, and fecal samples, a visual and physical exam, as well as measures for intestinal parasite load (FAMACHA scores) were collected from lactating ewes at 15 DIM and 30 DIM, and fecal samples, body weights, and FAMACHA scores were collected from their lambs. Milk samples were evaluated for SCC, CMT, milk composition, and bacterial species identification (MALDI). Blood samples, FAMACHA scores, and components of the physical exam were utilized to determine systemic ewe health. Lamb weaning weights and calculated average daily gain (ADG) were collected to be used as a physical measure of decreased milk production, frequently seen in cases of mastitis. We hypothesized that there would be increases in SCC and CMT, and alterations in milk composition for ewes that are categorized with different health statuses, with compounding effects from other mastitis risk factors. Additionally, we hypothesized that correlations will be identified between biomarkers and SCC, CMT, and lamb performance for healthy ewes that differ between litter size and DIM. It was observed that SCC and CMT differed by health status, SCC, CMT, udder conformation, lamb ADG, and lamb weaning weights differed by litter size, and CMT, milk fat (MF), and milk total solids (MTS) differed by DIM. Additionally, correlations were established between several testing methods and SCC, CMT, and lamb ADG. These results indicated that MF, MTS, lactose, protein, and lamb performance could serve as novel biomarkers to identify subclinical mastitis, but more investigation is needed to determine what biological processes causes these differences and correlations.

Digital Commons - USU (Utah State University)
Openalex Percentile: Top 38%
Geochemistry and Geologic Mapping
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.