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Tim A. McAllister

Researcher at Agriculture and Agri-Food Canada

Publications -  907
Citations -  37778

Tim A. McAllister is an academic researcher from Agriculture and Agri-Food Canada. The author has contributed to research in topics: Rumen & Silage. The author has an hindex of 85, co-authored 862 publications receiving 32409 citations. Previous affiliations of Tim A. McAllister include University of Alberta & University of Guelph.

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A modified spectrophotometric assay to estimate deglycosylation of steroidal saponin to sapogenin by mixed ruminal microbes.

TL;DR: Mixed rumen bacteria deglycosylate steroidal saponin to sapogenin, at activity levels unaffected by prior exposure to sap onin, but they were unable to degrade the sapogen in core structure.
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Investigation of Macrolide Resistance Genotypes in Mycoplasma bovis Isolates from Canadian Feedlot Cattle

TL;DR: Antimicrobial susceptibility testing of five macrolides of M. bovis isolates found that >99% of isolates were resistant to tildipirosin and tilmicosin, regardless of the number and positions of the mutations, and the genotypes generated for 23S rRNA and the L4 and L22 ribosomal proteins were compared.
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In vitro ruminal fermentation of ground and dry-rolled barley grain differing in starch content

TL;DR: In vitro ruminal fermentation of ground and dry-rolled barley samples differing in starch content was evaluated using a batch culture technique as mentioned in this paper, and the results showed that both high starch and ground barley samples had greater gas production, short chain fatty acids (SCFA), dry matter (DM) and starch disappearance.
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A proposed approach to estimate and reduce the environmental impact from whole farms

TL;DR: In this article, the HOLOS model has been developed (using country specific emission factors) to explore potential mitigation practices with respect to GHG emission reduction or increased carbon storage, which can create nutrient surpluses and thus other environmental hazards (e.g. for human and/or ecosystem health).
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Modelling considerations in the analysis of associations between antimicrobial use and resistance in beef feedlot cattle.

TL;DR: Results varied markedly depending on the modelling approach, emphasizing the importance of exploring and reporting multiple modelling methods based on a balanced consideration of important factors such as study design, mathematical appropriateness, research question and target audience.