Indicators and Bacterial Diversity of Subclinical Mastitis in Iran's Industrial Cattle Farms

BACKGROUND: Mastitis is an important and prevalent infectious disease in dairy herds that imposes high economic losses annually to the animal industry. Numerous infectious agents, including bacteria, fungi and viruses, can cause mastitis, with Staphylococcus spp. and Streptococcus spp. as prevalent causative agents. Mastitis is typically classified as clinical or subclinical, which impacts lactose and somatic cell count (SCC) volumes in milk. MATERIAL AND METHOD: In this cross-sectional study, 108 Holstein Friesian cows from three industrial farms in Iran were sampled; after exclusion of five samples for culture contamination, a total of 427 milk samples were analysed. Samples with SCC > 200,000 cells/mL were considered positive for subclinical mastitis. RESULTS: Overall, 238/427 samples (55.7%) exceeded this SCC cut-off. Staphylococcus aureus and Klebsiella spp. were the most frequent isolates among culture-positive samples. Antibiotic susceptibility testing was performed on 11 representative isolates (selected to cover the main species and herds). A significant negative association between milk lactose and log-SCC was observed (p < 0.05). CONCLUSION: These results indicate lactose reduction as a useful indirect indicator of subclinical mastitis and document the bacterial profile of industrial Iranian farms.

Authors

Institutions

Publication Details

Journal
Veterinary Medicine and Science
Published
2026-04-15
DOI
https://doi.org/10.1002/vms3.70951
Primary Topic
Milk Quality and Mastitis in Dairy Cows
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Indicators and Bacterial Diversity of Subclinical Mastitis in Iran's Industrial Cattle Farms

Nooriyeh Garaei, Sina Salajegheh Tazerji, Roozbeh Kalantari
Veterinary Medicine and Science
Milk Quality and Mastitis in Dairy Cows
article

Indicators and Bacterial Diversity of Subclinical Mastitis in Iran's Industrial Cattle Farms

Nooriyeh Garaei, Sina Salajegheh Tazerji, Roozbeh Kalantari
article en

Abstract

BACKGROUND: Mastitis is an important and prevalent infectious disease in dairy herds that imposes high economic losses annually to the animal industry. Numerous infectious agents, including bacteria, fungi and viruses, can cause mastitis, with Staphylococcus spp. and Streptococcus spp. as prevalent causative agents. Mastitis is typically classified as clinical or subclinical, which impacts lactose and somatic cell count (SCC) volumes in milk. MATERIAL AND METHOD: In this cross-sectional study, 108 Holstein Friesian cows from three industrial farms in Iran were sampled; after exclusion of five samples for culture contamination, a total of 427 milk samples were analysed. Samples with SCC > 200,000 cells/mL were considered positive for subclinical mastitis. RESULTS: Overall, 238/427 samples (55.7%) exceeded this SCC cut-off. Staphylococcus aureus and Klebsiella spp. were the most frequent isolates among culture-positive samples. Antibiotic susceptibility testing was performed on 11 representative isolates (selected to cover the main species and herds). A significant negative association between milk lactose and log-SCC was observed (p < 0.05). CONCLUSION: These results indicate lactose reduction as a useful indirect indicator of subclinical mastitis and document the bacterial profile of industrial Iranian farms.

Veterinary Medicine and ScienceVol. 12(3)
Islamic Azad University, Tehran (IR), University of Calgary (CA), South Health Campus (CA)
Openalex Percentile: Top 22%
Milk Quality and Mastitis in Dairy Cows
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.