New Zealand’s economy is highly reliant on the dairy industry so anything that affects the quality of our milk products is extremely important. One condition that can adversely affect milk quality is mastitis – when the udder of the cow becomes infected by bacteria and the udder tissue becomes inflamed. Milk from cows with mastitis has to be thrown away, so it is important for farmers to be able to detect when cows have mastitis.
Testing for mastitis
One way farmers test for mastitis is to take milk from a cow and add a special detergent to it. The detergent breaks down cells, which then release DNA and a gel forms. This gel formation depends on the amount of DNA present – a cow with mastitis has a lot of white (infection-fighting) blood cells in its milk, meaning lots of DNA is released. The viscosity of the gel indicates how sick the cow is – a high viscosity means there is more infection.
The problem with this test is that it is only qualitative – it can’t be measured. The farmer can only see if a gel forms or not. Dr Michael Walmsley from the University of Waikato wanted to develop a quantitative test that would measure the degree of gel formation and allow the farmer to work out how sick the cow is by knowing how many white blood cells there are.
Michael’s research team introduced a small amount of the detergent into the milk and used a viscometer to measure how the viscosity of the gel changed over time. The gel was a non-Newtonian fluid that was initially rheopectic (the gel’s viscosity increased with stress over time). The sample was stirred and a gel formed, increasing in viscosity until it reached a peak. Then it slowly reverted to a low-viscosity liquid (possibly due to the DNA breaking down), which is known as thixotropic behaviour.
This created a curve showing the gel forming (the initial part of the curve), increasing in viscosity with DNA being released (peaking) and then reverting to a low-viscosity liquid (dropping off).
The research team discovered that different levels of infection created different curves, which gave them a quantitative measure. The next step was to design some equipment that could be used by farmers that would give a measure that was easy for farmers to verify. This was later done by a local company, using the measure of viscosity of the gel compared to known cell concentration curves.