This study was conducted to evaluate the effects of high-temperature stress on dairy cow productivity and the correlation between rumen sensors. The data were collected on the temperature, humidity, milk productivity, milk components, blood components, and rumen sensor data from 125 dairy cows during the experimental period (1 May 2020 to 30 October 2020). High-temperature stress of dairy cows was evaluated based on the temperature-humidity index (THI). The correlations between the high-temperature stress, productivity, and sensor data were analyzed using SAS and R programs. The THI ranged from 46.9 to 81.0 during the experimental period, and a significant decrease was observed in the milk production of dairy cows during August ( < 0.05). Milk production was evaluated to decrease by 1.8% because of high-temperature stress during the experimental period. There was a significantly high negative correlation between the THI ratio of day and rumen temperature (r = 0.744; < 0.001). The other rumen sensor data did not show a significant correlation with the productivity of dairy cows. The results can be utilized as a guideline for managing temperature and humidity to maintain dairy cow productivity on farms in high-temperature stress conditions.
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http://dx.doi.org/10.3390/ani14192848 | DOI Listing |
Heliyon
January 2025
Haramaya University, School of Animal and Range Sciences, P. O. Box 138, Dire Dawa, Ethiopia.
The aim of the study was to determine the relationship between slaughter weight (SW) with body components and liner body measurements and investigate the coefficient of correlation between slaughter weight with body component and liner body measurements to select the best regression equation. Data on liner body measurements (height at wither and at hips, heart girth, body length, height and width of hump, height at fall and hind legs, body sheath height, height at hooks, barrel circumference, width of face, length of face and tail circumference) and slaughter weight of body components (Hot Carcass Weight (HCW), Empty Body Weight (ESW), Internal Offal (IO) and External Offal (EO)) were collected from 62 Hararghe cattle at Haramaya University abattoir. ESW was calculated as SW with less gut contents.
View Article and Find Full Text PDFHeliyon
March 2024
Department of Microbiology, University of Dhaka, Dhaka, 1000, Bangladesh.
Foot-and-mouth disease virus (FMDV), the causative agent of the foot-and-mouth disease of cattle population possesses a rapid evolutionary rate. In Bangladesh, the first circulation of the O/ME-SA/SA-2018 lineage as a novel sublineage, MYMBD21 was reported from our laboratory. The first whole genome sequence of an isolate, BAN/MY/My-466/2021 (shortly named My-466) of the SA-2018 lineage is characterized and represented in this study.
View Article and Find Full Text PDFAnim Microbiome
January 2025
Department of Large Animal Clinical Sciences, University of Florida, Gainesville, FL, 32610, USA.
Background: Cows that develop metritis experience dysbiosis of their uterine microbiome, where opportunistic pathogens overtake uterine commensals. An effective immune response is critical for maintaining uterine health. Nonetheless, periparturient cows experience immune dysregulation, which seems to be intensified by prepartum over-condition.
View Article and Find Full Text PDFBMC Vet Res
January 2025
Department of Large Animal Diseases and Clinic, Institute of Veterinary Medicine, Warsaw University of Life Sciences, Warsaw, 02-787, Poland.
Background: Elevated BHB levels are hypothesized to influence hepatic antioxidant enzyme expression and activity, contributing to oxidative response. However, the impact of BHB between 0.8 and 1.
View Article and Find Full Text PDFAnal Chim Acta
January 2025
Christian Doppler Laboratory for Innovative Gut Health Concepts of Livestock, Austria; BOKU University, Vienna, Dept. IFA-Tulln, Institute of Bioanalytics and Agro-Metabolomics, Tulln, Austria.
Background: Untargeted metabolomics requires robust and reliable strategies for data processing to extract relevant information form the underlying raw data. Multiple platforms for data processing are available, but the choice of software tool can have an impact on the analysis. This study provides a comprehensive evaluation of four workflows based on commonly used metabolomics software tools: XCMS, Compound Discoverer, MS-DIAL, and MZmine.
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