What does oestrus detection have to do with economics and carbon footprints?

Oestrus detection

Last week’s article identified the importance of accurately detecting oestrus so that time and money are not wasted unnecessarily. Wastage can occur on any scale. From the micro level – a straw will be wasted if a cow not in oestrus at AI, to the individual cow level where, for example, a cow is culled due to fertility issues related to failure to detect oestrus to the whole farm where the cost of replacement of cull cows is a part of the farm enterprise costs. 

Until a heifer calves she has been a net cost to the farm, and income from the cow entering the dairy herd will not break even until after, on average, two lactations (Boulton et al, 2017). If a cow on the average farm fails to complete two lactations, her rearing costs will never be covered and her “debt” is added to the balance sheet of the rest of the herd.

There have been considerable improvements in the UK herd monitored by NMR with the median calving to first service interval down from 105 days (2010) to 81 days (2019) in the 500 herds included in the data. But there is still room for improvement, for example, despite the median reducing from 32%, there is still a median of 21% of cows with a service interval of  >50 days (Wright, 2020). Some of these may be due to silent heats where increased activity associated with oestrus is absent and so may be missed by observation and movement detection methods.

Carbon footprints

The UK is committed to “net zero” carbon emissions by 2050 and ruminants – with their production of carbon dioxide and methane (a shorter lived but more potent contributor than CO2 where, for example, global livestock methane emissions in 2014 were 97.1 million tonnes which is equivalent to 2.72 gigatonnes of carbon dioxide (Dangal et al, 2014)) are considered an area where reductions are essential.

I was told recently that a goal can be reached by multiple small improvements, none of which of themselves are huge but together they reach the goal. This improvement is due to increased yields per cow, in turn due to improved nutrition, fertility and genetics. This is likely to be the situation with dairy farms – they will not simply disappear to achieve net zero – but by a whole series of improvements from feed to supermarket shelf – the UK current 1.2kg of carbon per litre of milk – will be reduced still further. The process has already started with the UK dairy herd reduced from 2.2 million cows in 2001 to 1.9 million in 2018 whilst achieving an increase in yield of 0.5 million litres per year despite the reduction in cow numbers (Porter, 2019). Further improvement will come about by tightening, for example, fertility management, so that each cow remains in the herd well beyond her economic break even and thereby reduces the number of replacement heifers required. Accurate heat detection has its part to play in fertility management and thus in providing an incremental improvement in the UK dairy herd carbon footprint.

Don’t forget the improvements that have already been made when challenged “that methane from livestock is an important contributor to climate change” (Smith and Balmford, 2020).

Check out this report by DairyCo for more information on the carbon footprint of milk in the UK.


So a step to take towards lowering the carbon footprint could be improved fertility management to reduce total number of cows and increase yield, but how do we do this? P4Rapid is a product manufactured by Ridgeway Science that allows pen side testing of milk to indicate fertility to the vet or farmer. This simple, 10 minute test can provide information on where a cow is in her cycle and can thus aid in the correct timing of AI. By implementing frequent fertility testing (on site, using cost effective means) we can improve heard fertility.

If you would like to find out more about P4Rapid visit the website here or if you would like to purchase tests please click here.


Boulton AC et al, 2017. An empirical analysis of the cost of rearing dairy heifers from birth to first calving and the time taken to repay these costs. Animal (2017), 11:8, pp 1372–1380.

Dangal SRS et al, 2014. Methane emission from the global livestock sector during 1890 to 2014: magnitude, trends and spatiotemporal patterns. Global Chang Biol 23 4147 – 61.

Porter R, 2019. Footprint Focus. Cow Management August/September 2019 page 18.

Smith P and Balmford A, 2020. Climate Change: “no get out of jail free card”. Veterinary Record 186 2 71.

Wright, K, 2020. Dig into fertility data. Cow Management January/ February 2020 page 32.