Subclinical mastitis in Jersey dairy cows and its effects on productivity and inflammatory markers

• Published in: Semina. Ciências agrárias : revista cultural e científica da Universidade Estadual de Londrina Vol. 45; no. 3; pp. 819 - 834
• Main Authors: Reitz, Greyce Kelly Schmitt, Pelegrini, Mariana Monteiro Boeng, Molinari, Pietra Viertel, Londero, Uriel Secco, Feijó, Josiane de Oliveira, Corrêa, Marcio Nunes, Alvarado-Rincón, Joao Alveiro, Gueretz, Juliano Santos, Peripolli, Vanessa, Schwegler, Elizabeth
• Format: Journal Article
• Language: English
• Published: Universidade Estadual de Londrina 01.05.2024
• Subjects: Dairy cattle; Lactose; Paraoxonase 1; Somatic cell count
• DOI: 10.5433/1679-0359.2024v45n3p819
• ISSN: 1676-546X

This study assessed the effect of subclinical mastitis on the productivity and inflammatory markers in Jersey dairy cows. Blood, milk, and milk yield data were collected from 59 Jersey dairy cows reared under a semi-extensive system. Milk samples were collected from individual collectors and evaluated for their somatic cell count (SCC), lactose (Lact), protein, fat, total and defatted dry extracts (DDE), casein, freezing point, and milk urea nitrogen (MUN) levels. After milking, blood was collected by puncturing the coccygeal arteriovenous complex. In the serum samples, the inflammatory biomarkers paraoxonase-1, albumin, and total plasma protein levels were analyzed using colorimetric methods. Samples of the entire diet provided and pastures were submitted for bromatological analysis. Additionally, the body condition score, number of lactations, milk yield, days of lactation, calving interval, number of inseminations until conception, calving-conception interval, and days of pregnancy were analyzed. The cows were categorized based on their SCC into a subclinical mastitis group (SubG), with SCC levels greater than or equal to 200,000 cells/mL, and a control group (CG), with SCC levels below 200,000 cells/mL. Blood metabolic variables, milk quality, and milk production data were analyzed using multivariate regression, analysis of variance, and logistic regression using the SAS® program. The multivariate regression analysis revealed that several markers, such as Lact, total protein, and casein, influenced milk composition, predicting over 97% of the data. The SubG showed lower concentrations of Lact (4.37 vs. 4.47%; P = 0.0002), MUN (20.55 vs. 23.85 mg/dL; P = 0.02), and DDE (9.24 vs. 9.50%; P = 0.02) compared with the CG; moreover, animals in the SubG had a higher number of lactations compared with those in the CG (4.30 vs. 2.69; P = 0.0039). Cows with a Lact content lower than 4.265% (quartile 25%), compared with those with Lact content greater than 4.565% (quartile 100%), were 52 times more likely to have subclinical mastitis. Jersey dairy cows with subclinical mastitis have lower Lact, urea, and defatted dry extract levels in their milk as well as a higher number of lactations. Therefore, Lact levels in milk serve as a good diagnostic marker of subclinical mastitis in Jersey cows. Subclinical mastitis in Jersey dairy cows did not decrease milk yield nor effect reproductive performance.