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/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.
Original language | English |
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Pages (from-to) | 19 - 29 |
Number of pages | 11 |
Journal | Preventive Veterinary Medicine |
Volume | 150 |
Early online date | 27 Nov 2017 |
DOIs | |
Publication status | First published - 27 Nov 2017 |
Bibliographical note
1031423Keywords
- Dairy cow
- Dynamic programming
- Greenhouse gas emissions intensity
- Profitability
- Subclinical mastitis
- Whole farm modelling