In-Line Registered Milk Fat-to-Protein Ratio for the Assessment of Metabolic Status in Dairy Cows

Abstract

This study endeavors to ascertain alterations in the in-line registered milk fat-to-protein ratio as a potential indicator for evaluating the metabolic status of dairy cows. Over the study period, farm visits occurred biweekly on consistent days, during which milk composition (specifically fat and protein) was measured using a BROLIS HerdLine in-line milk analyzer (Brolis Sensor Technology, Vilnius, Lithuania). Clinical examinations were performed at the same time as the farm visits. Blood was drawn into anticoagulant-free evacuated tubes to measure the activities of GGT and AST and albumin concentrations. NEFA levels were assessed using a wet chemistry analyzer. Using the MediSense and FreeStyle Optium H systems, blood samples from the ear were used to measure the levels of BHBA and glucose in plasma. Daily blood samples were collected for BHBA concentration assessment. All samples were procured during the clinical evaluations. The cows were categorized into distinct groups: subclinical ketosis (SCK; n = 62), exhibiting elevated milk F/P ratios without concurrent clinical signs of other post-calving diseases; subclinical acidosis (SCA; n = 14), characterized by low F/P ratios (<1.2), severe diarrhea, and nondigestive food remnants in feces, while being free of other post-calving ailments; and a healthy group (H; n = 20), comprising cows with no clinical indications of illness and an average milk F/P ratio of 1.2. The milk fat-to-protein ratios were notably higher in SCK cows, averaging 1.66 (±0.29; p < 0.01), compared to SCA cows (0.93 ± 0.1; p < 0.01) and healthy cows (1.22). A 36% increase in milk fat-to-protein ratio was observed in SCK cows, while SCA cows displayed a 23.77% decrease. Significant differences emerged in AST activity, with SCA cows presenting a 26.66% elevation (p < 0.05) compared to healthy cows. Moreover, SCK cows exhibited a 40.38% higher NEFA concentration (p < 0.001). A positive correlation was identified between blood BHBA and NEFA levels (r = 0.321, p < 0.01), as well as a negative association between BHBA and glucose concentrations (r = −0.330, p < 0.01). Notably, AST displayed a robust positive correlation with GGT (r = 0.623, p < 0.01). In light of these findings, this study posits that milk fat-to-protein ratio comparisons could serve as a non-invasive indicator of metabolic health in cows. The connections between milk characteristics and blood biochemical markers of lipolysis and ketogenesis suggest that these markers can be used to check the metabolic status of dairy cows on a regular basis.

The Relation between Milk Lactose Concentration and the Rumination, Feeding, and Locomotion Behavior of Early-Lactation Dairy Cows

“…In our previous study, we discovered that cows with higher milk lactose concentrations were significantly more active (increasing by 54.47%) and had a lower risk of developing subclinical acidosis (SARA), as demonstrated by a 2.52% increase in the reticulo-ruminal pH and a 9.86% extension in the rumination time [ 15 ]. Antanaitis et al [ 5 ] found that cows suffering from acidosis were less active compared to healthy ones. The definition of SARA based on rumen pH is subject to debate [ 31 ], but previous research [ 32 , 33 ] has shown that a rumen pH below 6 is indicative of SARA.…”

“…During each milking cycle, the analyzer continuously measures the composition of each cow’s milk. This ‘mini-spectroscope’ can be mounted on the milking stalls or on a milking robot in the milk line and requires no additional reagents or maintenance [ 5 ]. Milk serves as an ideal medium for assessing the health of dairy cows due to its non-invasive collection method and ease of access, making it a common tool for detecting ketosis and other issues related to production [ 6 ].…”

“…Therefore, further exploration into the use of early milk sampling and the potential integration of novel data sources is warranted to enhance the accuracy of early warning systems. Additionally, to ensure the robustness of predictive models against variations in farm management and feed compositions, it is crucial to gather and evaluate more data from diverse farms before implementing such models in practice [ 5 ]. Understanding the linkage between lactose concentrations and cow behaviors can help farms to pre-emptively address issues like mastitis, which is known to alter lactose levels, before they escalate into more severe health problems.…”

Impact of Heat Stress on the In-Line Registered Milk Fat-to-Protein Ratio and Metabolic Profile in Dairy Cows

“…To ensure the model's applicability and adaptability to different management practices and diets, it is essential to incorporate and evaluate additional data from various farms before its practical implementation [21]. Recently, technologies that record behavior have become commercially accessible, paving the way for advancements in precision cattle husbandry [22]. The daily milk fat-to-protein ratios of cows can be measured using a BROLIS HerdLine in-line milk analyzer (Brolis Sensor Technology, Vilnius, Lithuania).…”

Changes in Parameters Registered by Innovative Technologies in Cows with Subclinical Acidosis

“…Before the model is put into operation, further data from other farms must be incorporated and assessed in order to guarantee that it is applicable to a variety of management styles and dietary requirements [21]. A BROLIS HerdLine in-line milk analyzer (Brolis Sensor Technology, Vilnius, Lithuania) can be used to measure the daily milk fat-to-protein ratios of cows [22]. Understanding the relationships between these features in food, blood, and milk can assist in understanding the health and production status of animals.…”