Literature DB >> 22818470

Factors associated with ruminal pH at herd level.

T Geishauser1, N Linhart, A Neidl, A Reimann.   

Abstract

The objective of this study was to evaluate factors associated with ruminal pH at herd level. Four hundred and thirty-two cows of a Thuringian dairy herd were sampled before claw trimming using a rumen fluid scoop. Volume and pH of the rumen sample were measured, and lactation number, percentage of concentrates in the ration, days in milk (DIM), time of day, and daily milk yield were recorded. Rumen sampling was successful in 99.8% of the cows. The average sample volume was 25 mL. Rumen sample pH decreased with increasing percentage of concentrates in the ration. Ruminal pH decreased from calving to 77 DIM, and grew subsequently to 330 DIM. During the day, rumen pH followed a sinus curve, with maxima in the morning (0915 h) and afternoon (1533 h), and a minimum around noon (1227 h). Ruminal pH decreased with increasing daily milk yield. Lactation number interacted with daily milk yield on rumen pH. The percentage of concentrates in the ration, DIM, time of day, and daily milk yield were significant factors affecting ruminal pH at the herd level.
Copyright © 2012 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

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Year:  2012        PMID: 22818470     DOI: 10.3168/jds.2012-5380

Source DB:  PubMed          Journal:  J Dairy Sci        ISSN: 0022-0302            Impact factor:   4.034


  10 in total

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Journal:  Appl Environ Microbiol       Date:  2015-02       Impact factor: 4.792

2.  Effects of Concentrate Supplementation on Growth Performance, Rumen Fermentation, and Bacterial Community Composition in Grazing Yaks during the Warm Season.

Authors:  Dongwen Dai; Kaiyue Pang; Shujie Liu; Xun Wang; Yingkui Yang; Shatuo Chai; Shuxiang Wang
Journal:  Animals (Basel)       Date:  2022-05-29       Impact factor: 3.231

3.  Altered microbiomes in bovine digital dermatitis lesions, and the gut as a pathogen reservoir.

Authors:  Martin Zinicola; Fabio Lima; Svetlana Lima; Vinicius Machado; Marilia Gomez; Dörte Döpfer; Charles Guard; Rodrigo Bicalho
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4.  Bayesian modeling reveals host genetics associated with rumen microbiota jointly influence methane emission in dairy cows.

Authors:  Qianqian Zhang; Gareth Difford; Goutam Sahana; Peter Løvendahl; Jan Lassen; Mogens Sandø Lund; Bernt Guldbrandtsen; Luc Janss
Journal:  ISME J       Date:  2020-05-04       Impact factor: 10.302

5.  Host genetics and the rumen microbiome jointly associate with methane emissions in dairy cows.

Authors:  Gareth Frank Difford; Damian Rafal Plichta; Peter Løvendahl; Jan Lassen; Samantha Joan Noel; Ole Højberg; André-Denis G Wright; Zhigang Zhu; Lise Kristensen; Henrik Bjørn Nielsen; Bernt Guldbrandtsen; Goutam Sahana
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Review 6.  Opportunities to Harness High-Throughput and Novel Sensing Phenotypes to Improve Feed Efficiency in Dairy Cattle.

Authors:  Cori J Siberski-Cooper; James E Koltes
Journal:  Animals (Basel)       Date:  2021-12-22       Impact factor: 2.752

7.  Rumen and lower gut microbiomes relationship with feed efficiency and production traits throughout the lactation of Holstein dairy cows.

Authors:  Hugo F Monteiro; Ziyao Zhou; Marilia S Gomes; Phillip M G Peixoto; Erika C R Bonsaglia; Igor F Canisso; Bart C Weimer; Fabio S Lima
Journal:  Sci Rep       Date:  2022-03-22       Impact factor: 4.379

8.  Long-Term Effects of Dietary Supplementation with Olive Oil and Hydrogenated Vegetable Oil on the Rumen Microbiome of Dairy Cows.

Authors:  Nathaly Cancino-Padilla; Natalia Catalán; Karen Siu-Ting; Christopher J Creevey; Sharon A Huws; Jaime Romero; Einar Vargas-Bello-Pérez
Journal:  Microorganisms       Date:  2021-05-22

9.  Community structure of the metabolically active rumen bacterial and archaeal communities of dairy cows over the transition period.

Authors:  Zhigang Zhu; Samantha Joan Noel; Gareth Frank Difford; Waleed Abu Al-Soud; Asker Brejnrod; Søren Johannes Sørensen; Jan Lassen; Peter Løvendahl; Ole Højberg
Journal:  PLoS One       Date:  2017-11-08       Impact factor: 3.240

10.  Predicting the Digestive Tract Development and Growth Performance of Goat Kids Using Sigmoidal Models.

Authors:  Mahmoud Abdelsattar; Yimin Zhuang; Kai Cui; Yanliang Bi; Naifeng Zhang
Journal:  Animals (Basel)       Date:  2021-03-10       Impact factor: 2.752

  10 in total

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