Literature DB >> 29406080

Impact of subclinical mastitis on greenhouse gas emissions intensity and profitability of dairy cows in Norway.

Şeyda Özkan Gülzari1, Bouda Vosough Ahmadi2, Alistair W Stott3.   

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 800,000cells/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 1.01kg (kilogram) and 0.95kg 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 50,000cells/mL in relation to SCC level 800,000cells/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.
Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Dairy cow; Dynamic programming; Greenhouse gas emissions intensity; Profitability; Subclinical mastitis; Whole farm modelling

Mesh:

Substances:

Year:  2017        PMID: 29406080     DOI: 10.1016/j.prevetmed.2017.11.021

Source DB:  PubMed          Journal:  Prev Vet Med        ISSN: 0167-5877            Impact factor:   2.670


  5 in total

1.  Financial and economic analyses of the impact of cattle mastitis on the profitability of Egyptian dairy farms.

Authors:  M F Azooz; Safaa A El-Wakeel; H M Yousef
Journal:  Vet World       Date:  2020-09-02

2.  Infectious Diseases, Livestock, and Climate: A Vicious Cycle?

Authors:  Vanessa O Ezenwa; David J Civitello; Brandon T Barton; Daniel J Becker; Maris Brenn-White; Aimée T Classen; Sharon L Deem; Zoë E Johnson; Susan Kutz; Matthew Malishev; Rachel M Penczykowski; Daniel L Preston; J Trevor Vannatta; Amanda M Koltz
Journal:  Trends Ecol Evol       Date:  2020-10-07       Impact factor: 17.712

3.  Can technology help achieve sustainable intensification? Evidence from milk recording on Irish dairy farms.

Authors:  Lorraine Balaine; Emma J Dillon; Doris Läpple; John Lynch
Journal:  Land use policy       Date:  2020-01-20

4.  The effects of improved performance in the U.S. dairy cattle industry on environmental impacts between 2007 and 2017.

Authors:  Judith L Capper; Roger A Cady
Journal:  J Anim Sci       Date:  2020-01-01       Impact factor: 3.159

5.  Association between Udder and Quarter Level Indicators and Milk Somatic Cell Count in Automatic Milking Systems.

Authors:  Maddalena Zucali; Luciana Bava; Alberto Tamburini; Giulia Gislon; Anna Sandrucci
Journal:  Animals (Basel)       Date:  2021-12-07       Impact factor: 2.752

  5 in total

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