Skip to content
naulon
Not checkedNot checked for notices yet.

Serum glucose, urea nitrogen, cholesterol, and total proteins in crossbred repeat breeder and normally cyclic cows

Rashed Khan Barson, Shasthi Padder, Abu Sadath Md. Sayam and 3 more

Journal of Advanced Veterinary and Animal Research · 2019

doi:10.5455/javar.2019.f316 (opens in a new tab)

We email you when a new notice or a question about this paper appears.

Abstract

Objective: This study was designed to determine and compare the serum glucose, urea nitrogen, cholesterol, and total protein (TP) level in crossbred repeat breeder (RB) and normally cyclic cows to find out the relationship of these metabolic factors with repeat breeding syndrome (RBS). Materials and Methods: A total of 592 breedable cows from 34 farms were examined from Mymensingh and Chittagong districts. Seventy cows were identified as RB cows and another 10 cows were randomly selected as normally cyclic control cows for this study. Blood sample from each cow was collected and the serum was separated. The serum samples were analyzed by auto blood analyzer. Results: Cows affected with RBS had significant variation in their glucose, urea, and cholesterol levels. Serum glucose (43.00 gm/dl) level was significantly lower than in normally cyclic cows. On the other hand, serum urea and cholesterol levels were significantly higher than in normally cyclic cows. However, the TP concentrations did not differ between RB and cyclic cows. RB cows had a lower trend (6.815 mg/dl) of serum TP than in normally cyclic cows. Conclusion: This research might help scientists and veterinarians to understand that the high serum urea and cholesterol level along with low glucose and TP level could have some effect in the development of RBS in crossbred cows. It will potentially help veterinary practitioners and farmers to take preventive measures against RBS of crossbred cows. [J Adv Vet Anim Res 2019; 6(1.000): 82-85]

Abstract licence: CC BY

Reads

Read by people on this page

None yet.

Checked or read by AI through naulon

None yet.

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.

Are you an author?

Is this your paper?

Claim it to add your note and be paid when agents cite it. Free.