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PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e6460 ◽  
Author(s):  
Kristin Tormoehlen ◽  
Yvette J. Johnson-Walker ◽  
Emily W. Lankau ◽  
Maung San Myint ◽  
John A. Herrmann

Background Wild birds using livestock facilities for food and shelter may contribute to dissemination of enteric pathogens or antimicrobial resistant bacteria. However, drivers of microbial exchange among wildlife and livestock are not well characterized. Predisposition for acquiring and retaining environmental bacteria may vary among species because of physiologic or behavioral differences, complicating selection of a bacterial model that can accurately characterize microbial connections among hosts of interest. This study compares the prevalence and antibiotic resistance phenotypes of two potential model bacterial organisms isolated from wild birds and their environments. Methods We compared prevalence and resistance profiles of Escherichia coli and Enterococcus species isolated from environmental swabs and bird feces on a residential control site, a confinement dairy, a pasture-based beef farm, and a confinement beef farm. Results Bird feces at all sites had low-to-moderate prevalence of Escherichia coli (range: 17–47%), despite potential for exposure on farms (range: 63–97%). Few Escherichia coli were isolated from the control environment. Enterococcus faecalis was dominant in birds at both beef farms (62% and 81% of Enterococcus isolates) and low-to-moderately prevalent at the dairy and control sites (29% and 23% of isolates, respectively). Antimicrobial resistance prevalence was higher in farm samples compared to those from the residential control, but distribution of resistant isolates varied between the bacterial genera. Birds on all farms carried resistant Enterococcus at similar rates to that of the environment, but resistance was less common in bird-associated Escherichia coli despite presence of resistant isolates in the farm environment. Discussion Bacterial species studied may affect how readily bacterial exchange among populations is detected. Selection of microbial models must carefully consider both the questions being posed and how findings might influence resulting management decisions.


2017 ◽  
Vol 5 (28) ◽  
Author(s):  
Lidia Sanabria ◽  
Lorena Lagrave ◽  
Christiane Nishibe ◽  
Augusto C. A. Ribas ◽  
Martín J. Zumárraga ◽  
...  

ABSTRACT This work reports the draft genome sequences of the Mycobacterium bovis strains M1009 and M1010, isolated from the lymph nodes of two infected cows on a beef farm in Paraguay. Comparative genomics between these strains and other regional strains may provide more insights regarding M. bovis epidemiology in South America.


2016 ◽  
Vol 62 (5-6) ◽  
pp. 545-552 ◽  
Author(s):  
Masayuki Hojito ◽  
Yoko Adachi ◽  
Yutaka Ono ◽  
Hideki Ogasawara

2016 ◽  
Vol 16 ◽  
pp. 87-93
Author(s):  
C.J. Mulvaney ◽  
D.J. Maccoll

Summary StockCARE has become recognised as a programme that can add value to sheep and beef farm businesses. The recognition is most likely built on some of the key features and benefits: • A systems based programme which has been proven to add value • Monitoring and benchmarking are the platform, but the intensity of the collection, interpretation and utilisation of information related to key drivers of every production system, is unique • StockCARE has a proven framework for a disciplined approach to the collection and analysis of production information. • The initial emphasis is on identifying, understanding and defining the factors that may limit performance, before solutions are considered • Farmers are encouraged to create a strong business team and develop strong relationships with people such as bankers, agronomists, fertiliser representatives and stock agents • StockCARE is about helping farmers optimise their business performance because not every farmer can be the "best" • StockCARE is long term, with on-going support for continuous improvement.


Author(s):  
A.D. Mackay ◽  
A.P. Rhodes ◽  
I. Power ◽  
M.E. Wedderburn

It is timely, with farming within biophysical limits as an emerging feature of the future operating environment for the sector, to explore whether the substantial productivity gains seen in the sheep and beef sector over the last 20 years translate into improved ecoefficiency and a reduction in the sector's environmental footprint. In this paper the changes in the relationship between inputs (e.g., livestock numbers, nutrients) and outputs (e.g., meat and fibre, greenhouse gas (GHG) emissions, nitrate) of the MAF Sheep and Beef Farm Monitoring models that cover hard hill country (Gisborne and Central North Island) and easy hill finishing (Manawatu) over the last 20 years were explored using the Overseer nutrient budget model. For the hard hill country extensive sheep and beef farm operation, the productivity gains made since 1989/90 translate into significant eco-efficiency gains, including a 47% increase in saleable product/ha (107 to 167 kg per ha), 21% reduction in nitrate leaching per kg of saleable product (0.065 to 0.054 kg N per kg animal product) and 40% reduction in the GHG emissions per kg of saleable product (27 to 19.2 kg CO2-e per kg animal product). The improvements have come through increased meat production. In contrast, the contribution from wool has been unchanged since 1989/90. These eco-efficiency gains, however, did not extend to include an overall reduction in N leaching or GHG emissions per hectare. In the easy hill finishing operation, where the MAF model farm size more than doubled over the last 20 years, there was little change in the eco-efficiency, but again also little change in total emissions. As we move to an operating environment where there are limits on emissions to the environment, understanding how to quantify eco-efficiency and monitor changes in this performance indicator becomes more than just an academic exercise. Keywords: Sheep and beef, eco-efficiency, meat and fibre production, N leaching, hill country


animal ◽  
2012 ◽  
Vol 6 (9) ◽  
pp. 1503-1511 ◽  
Author(s):  
I. Blanco-Penedo ◽  
M. López-Alonso ◽  
R.F. Shore ◽  
M. Miranda ◽  
C. Castillo ◽  
...  

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