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dc.contributor.authorGulzari SOen
dc.contributor.authorVosough Ahmadi Ben
dc.contributor.authorStott AWen
dc.date.accessioned2017-11-29T12:01:26Z
dc.date.available2017-11-29T12:01:26Z
dc.date.issued2017
dc.identifier.citation150
dc.identifier.issn0167-5877
dc.identifier.urihttps://doi.org/10.1016/j.prevetmed.2017.11.021
dc.identifier.urihttp://hdl.handle.net/11262/11353
dc.description.abstractImpaired 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/milliliter (mL) 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 kilogram (kg) 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 quality 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 in Norway are warranted.en
dc.description.sponsorshipScottish Government RESAS Strategic Research Programme (RD2.4.2)en
dc.language.isoenen
dc.relation.isformatof14733en
dc.relation.ispartofPreventive Veterinary Medicineen
dc.rightsCopyright © 2017 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license.
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectDairy cowen
dc.subjectDynamic programmingen
dc.subjectGreenhouse gas emissions intensityen
dc.subjectProfitabilityen
dc.subjectSubclinical mastitisen
dc.subjectWhole farm modellingen
dc.titleImpact of subclinical mastitis on greenhouse gas emissions intensity and profitability of dairy cows in Norwayen
dc.typeArticleen
dc.description.versionVersion of record
dc.extent.pageNumbers19-29
rioxxterms.publicationdate2017-11-27
rioxxterms.typeJournal Article/Reviewen
dcterms.dateAccepted2017-11-26
refterms.accessExceptionNAen
refterms.dateDeposit2017-11-29
refterms.depositExceptionNAen
refterms.panelUnspecifieden
refterms.technicalExceptionNAen
refterms.versionAMen


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Copyright © 2017 The Authors. Published by Elsevier B.V.

This is an open access article under the CC BY-NC-ND license.
Except where otherwise noted, this item's license is described as Copyright © 2017 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license.