| Records |
Author  |
Özkan, Ş.; Ahmadi, B.V.; Bonesmo, H.; Østerås, O.; Stott, A.; Harstad, O.M. |
| Title |
Impact of animal health on greenhouse gas emissions |
Type |
Journal Article |
| Year |
2015 |
Publication |
Advances in Animal Biosciences |
Abbreviated Journal |
Advances in Animal Biosciences |
| Volume |
6 |
Issue |
01 |
Pages |
24-25 |
| Keywords |
dairy; GHG emissions; cull rate; health; HolosNor |
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English |
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| ISSN |
2040-4700 |
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Article |
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LiveM, ft_macsur |
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no |
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MA @ admin @ |
Serial |
4573 |
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| Author |
Özkan, S. |
| Title |
The greenhouse gas emissions intensity of herds with mastitis |
Type |
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| Year |
2015 |
Publication |
FACCE MACSUR Reports |
Abbreviated Journal |
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| Volume |
5 |
Issue |
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Pages |
Sp5-42 |
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| Abstract |
Mastitis is an inflammatory disease of milking cows, causing production and economic losses in dairy farms. The main pathogens causing majority of the intramammary infections are Staphylococcus aureus, Streptococcus dysgalactiae, Escherichia coli and coagulase-negative Staphylococci. Here, we analysed the effect of mastitis on herd parameters such as milk yield, feed intake, replacement rate, gross margin and greenhouse gas emissions. The data were collected from the Norwegian Dairy Herd Recording System between 2010 and 2012. The farm data were recorded from 20 farms in Norway, based on health, fertility and breeding characteristics. SimHerd, a computer simulation model was used to estimate the impact of the observed levels of mastitis on herd parameters which were then fed into a whole farm model, HolosNor, to calculate the greenhouse gas emissions on the farm. The standard values provided in the SimHerd except for mastitis occurrence were applied in the scenario simulations. A further study is planned to parameterize each herd with specific herd characteristics in SimHerd so that herd specific estimates of the effect of mastitis on greenhouse gas emissions can be performed. No Label |
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MACSUR Science Conference 2015 »Integrated Climate Risk Assessment in Agriculture & Food«, 8–9+10 April 2015, Reading, UK |
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Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
2157 |
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| Author |
Özkan, á¹¢.; Bonesmo, H.; Østerås, O.; Harstad, O.M. |
| Title |
Effect of Increased Somatic Cell Count and Replacement Rate on Greenhouse Gas Emissions in Norwegian Dairy Herds |
Type |
Report |
| Year |
2014 |
Publication |
FACCE MACSUR Reports |
Abbreviated Journal |
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| Volume |
3 |
Issue |
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Pages |
Sp3-1 |
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| Abstract |
Dairy sector contributes around 4% of global greenhouse gas (GHG) emissions, of which 2/3 and 1/3 are attributed to milk and meat production, respectively. The main GHGs released from dairy farms are methane, nitrous oxide and carbon dioxide. The increased trend in emissions has stimulated research evaluating alternative mitigation options. Much of the work to date has focused on animal breeding, dietary factors and rumen manipulation. There have been little studies assessing the impact of secondary factors such as animal health on emissions at farm level. Production losses associated with udder health are significant. Somatic cell count (SCC) is an indicator on udder health. In Norway, around 45, 60 and 70% of cows in a dairy herd at first, second and third lactation are expected to have SCC of 50,000 cells/ml and above. Another indirect factor is replacement rate. Increasing the replacement rate due to health disorders, infertility and reduced milk yield is likely to increase the total farm emissions if the milking heifer replacements are kept in the herd.In this study, the impact of elevated SCC (200,000 cells/ml and above) and replacement rate on farm GHG emissions was evaluated. HolosNor, a farm scale model adapting IPCC methodology was used to estimate net farm GHG emissions. Preliminary results indicate an increasing trend in emissions (per kg milk and meat) as the SCC increases. Results suggest that animal health should be considered as an indirect mitigation strategy; however, further studies are required to enable comparisons of different farming systems. No Label |
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no |
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MA @ admin @ |
Serial |
2218 |
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| Author |
Özkan Gülzari, Ş.; Vosough Ahmadi, B.; Stott, A.W. |
| Title |
Impact of subclinical mastitis on greenhouse gas emissions intensity and profitability of dairy cows in Norway |
Type |
Journal Article |
| Year |
2018 |
Publication |
Preventive Veterinary Medicine |
Abbreviated Journal |
Preventive Veterinary Medicine |
| Volume |
150 |
Issue |
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Pages |
19-29 |
| Keywords |
Dairy cow; Dynamic programming; Greenhouse gas emissions intensity; Profitability; Subclinical mastitis; Whole farm modelling |
| Abstract |
Impaired animal health causes both productivity and profitability losses on dairy farms, resulting in inefficient use of inputs and increase in greenhouse gas (GHG) emissions produced per unit of product (i.e. emissions intensity). Here, we used subclinical mastitis as an exemplar to benchmark alternative scenarios against an economic optimum and adjusted herd structure to estimate the GHG emissions intensity associated with varying levels of disease. Five levels of somatic cell count (SCC) classes were considered namely 50,000 (i.e. SCC50), 200,000, 400,000, 600,000 and 800,000 cells/mL (milliliter) of milk. The effects of varying levels of SCC on milk yield reduction and consequential milk price penalties were used in a dynamic programming (DP) model that maximizes the profit per cow, represented as expected net present value, by choosing optimal animal replacement rates. The GHG emissions intensities associated with different levels of SCC were then computed using a farm-scale model (HolosNor). The total culling rates of both primiparous (PP) and multiparous (MP) cows for the five levels of SCC scenarios estimated by the model varied from a minimum of 30.9% to a maximum of 43.7%. The expected profit was the highest for cows with SCC200 due to declining margin over feed, which influenced the DP model to cull and replace more animals and generate higher profit under this scenario compared to SCC50. The GHG emission intensities for the PP and MP cows with SCC50 were 1.01 kg (kilogram) and 0.95 kg carbon dioxide equivalents (CO2e) per kg fat and protein corrected milk (FPCM), respectively, with the lowest emissions being achieved in SCC50. Our results show that there is a potential to reduce the farm GHG emissions intensity by 3.7% if the milk production was improved through reducing the level of SCC to 50,000 cells/mL in relation to SCC level 800,000 cells/mL. It was concluded that preventing and/or controlling subclinical mastitis consequently reduces the GHG emissions per unit of product on farm that results in improved profits for the farmers through reductions in milk losses, optimum culling rate and reduced feed and other variable costs. We suggest that further studies exploring the impact of a combination of diseases on emissions intensity are warranted. |
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0167-5877 |
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| Notes |
LiveM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
5181 |
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| Author |
Özkan Gülzari, Ş.; Kipling, R. |
| Title |
Understanding the potential of existing models to characterize animal health conditions and estimate greenhouse gas emissions |
Type |
Report |
| Year |
2017 |
Publication |
FACCE MACSUR Reports |
Abbreviated Journal |
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| Volume |
10 |
Issue |
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Pages |
L2.2-D2 |
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| Abstract |
The primary objective of this study was to assess the status and priorities for future development in modelling of the impacts of animal health on greenhouse gas (GHG) emissions. It also aimed to facilitate communication between experimental researchers and modellers by defining a list of parameters that are needed to model livestock health and disease, and the impact of health conditions on GHG emissions. The summary presented here provides a brief overview of ongoing work, which the L2.1/L2.2 partners, with support from the Global Research Alliance Animal Health Network (GRA AHN), is currently developing into a paper for publication in a peer reviewed journal. |
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LiveM |
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no |
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MA @ admin @ |
Serial |
4979 |
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