By Gareth Salmon
Today is World Milk Day. Established two decades ago by the FAO in celebration of the global dairy sector and the value of milk, the day offers an opportunity to reflect on the value of data relating to milk.
Photo: Biodiversity Heritage Library (source)
Here in the UK milk data is vital for the successful functioning of our dairy farms. Routine milk recording lets farmers identify their best and worst producers, informing a whole host of management decisions. Milk quality is also closely scrutinised and influences the price farmers get for their milk; data is an essential here to retain contracts. British milk generally passes through a formal value chain, therefore we can be fairly confident in the data that says on 16th May 2020 UK dairy farmers produced 44.57 million litres1.
In Sub-Saharan Africa milk is more likely to pass through informal value chains, potentially up to 80-90% of all milk sold2,3; making it much more challenging to report total production quantities. On farms across the continent the value of milk recording is becoming increasingly apparent, particularly where efforts are being made to improve the breeding stock, health and nutrition of animals to tackle yield gaps. For instance the African Dairy Genetic Gains project, where the establishment of performance recording systems in Tanzania and Ethiopia is informing breeding programmes to improve productivity. Historically, efforts to improve dairy production on smallholder farms have been significantly hindered by a lack of performance records4. On the other side of the continent the Senegal Dairy Genetics project gathered two years’ worth of milk performance and management records from farmers, informing not only which breeds were the most productive, but which were most profitable (interestingly they were not the same). As food security challenges continue, the mantra "if you don’t measure it, you can’t manage it", will become increasingly relevant.
These efforts to increase milk production and productivity with farmers in Sub-Saharan Africa arise from the data that demonstrates the significant value of milk. Data tells us that milk provides essential vitamins and minerals for infants and those with limited access to nutritious foods. Rearing cattle and selling milk can be an important source of income and the whole value chain (formal or informal) provides employment5.
Ironically, milk is not whiter than white, it has its significant challenges. Milk can carry food-borne diseases, particularly where hygiene levels are compromised, for instance where cold chains are limited. Rearing livestock brings the risk of zoonotic diseases. An inappropriate use of antibiotics to maintain dairy animals contributes to the significant global challenge of antimicrobial resistance5. These challenges are recognised because data exists to reveal them.
Probably the most controversial issue relating to milk is the negative environmental impact of its production. In 2006 Livestock’s Long Shadow6 presented data to demonstrate the impact on climate change and air pollution, water use and pollution, and biodiversity. Since this divisive and decisive publication the conversation (like the climate) has continued to heat up; sometimes supported by data, sometimes not. According to data from the Global Livestock Environmental Assessment Model (from the Food and Agricultural Organization for the United Nations) milk production (including that from cattle, buffalo, sheep and goats) accounts for 30% of total livestock greenhouse gas emissions. The important point is that there is significant variation in the volume of greenhouse gases emitted for each litre of milk produced (the emission intensity); this relates directly to the efficiency of production. Such data highlights that although milk production is likely to contribute significantly to emissions, things can be done better (more efficiently); reducing our impact if we consume milk.
There is no doubt that milk (from livestock rather than oats, soy or nuts) will continue as an important commodity for humanity. But like most things data is key to how we understand and manage the context around milk; in general the more data the better!
Gareth Salmon is a Researcher with SEBI. SEBI facilitates the Livestock Data for Decisions (LD4D) Community of Practice and manages livestockdata.org.
 Opoola et al. 2019. Current situations of animal data recording, dairy improvement infrastructure, human capacity and strategic issues affecting dairy production in sub-Saharan Africa. Trop Anim Health Prod. 51, 1699–1705. https://doi.org/10.1007/s11250-019-01871-9.
 Ojango et al. 2019. Genetic evaluation of test-day milk yields from smallholder dairy production systems in Kenya using genomic relationships. Journal of Dairy Science. 102: 6. 5266-5278. https://doi.org/10.3168/jds.2018-15807.