AUTHOR=Arlauskaitė Samanta , Girdauskaitė Akvilė , Rutkauskas Arūnas , Džermeikaitė Karina , Krištolaitytė Justina , Televičius Mindaugas , Malašauskienė Dovilė , Anskienė Lina , Japertas Sigitas , Baumgartner Walter , Antanaitis Ramūnas 

TITLE=Precision monitoring of rumination and locomotion in relation to milk fat-to-protein ratio in early lactation dairy cattle

JOURNAL=Frontiers in Veterinary Science

VOLUME=Volume 12 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/veterinary-science/articles/10.3389/fvets.2025.1632224

DOI=10.3389/fvets.2025.1632224

ISSN=2297-1769

ABSTRACT=The milk fat-to-protein ratio (FPR) is a valuable indicator of metabolic health in dairy cows, especially during early lactation when cows are most susceptible to negative energy balance. This study aimed to evaluate the relationship between FPR, milk composition, blood biochemical parameters, and behavioral indicators in early-lactation Holstein cows. Twenty-seven cows between 9 and 59 days in milk were monitored and categorized into three groups: low-grade ruminal acidosis (LGRA; FPR < 1.2), healthy (H; FPR 1.2–1.5), and subclinical ketosis (SCK; FPR > 1.5). Milk composition was assessed in real time using the Brolis HerdLine in-line analyzer, while rumination time, reticulorumen temperature, water intake, and activity were recorded using SmaXtec boluses. Blood samples were collected weekly to analyze metabolic and biochemical parameters. Cows in the SCK group exhibited significantly lower milk lactose and protein concentrations, shorter rumination time, lower iron levels, and higher milk fat content, NEFA concentrations, and activity levels compared to the LGRA and healthy groups. The study demonstrated that elevated FPR is associated with metabolic and behavioral changes indicative of subclinical metabolic disorders, particularly subclinical ketosis. The integration of real-time milk composition data, behavioral monitoring, and blood biochemical analysis enables a comprehensive and non-invasive approach for early detection and management of metabolic imbalances in dairy herds. This study highlights the potential of precision monitoring technologies to improve animal welfare and productivity by supporting proactive herd health management.