Chronic mastitis is a persistent inflammation of the udder in dairy cows, typically caused by an ongoing infection. While mastitis is commonly known for its clinical forms, where the signs are visible and treatable, chronic mastitis often remains subclinical, meaning it presents no obvious symptoms. Despite being less visible, chronic mastitis can significantly affect milk production and the overall health of the herd.

Although most losses in dairy production due to mastitis are linked to clinical cases, chronic mastitis can also be highly problematic. Subclinical chronic mastitis leads to ongoing milk production losses and increases the risk of pathogen transmission across the herd. Early detection of chronic mastitis is crucial, as it allows farmers to intervene before the infection spreads or worsens, minimizing long-term damage and associated costs.

Detecting chronic mastitis early is key to managing its impact. One of the primary indicators of mastitis is the Somatic Cell Count (SCC), which measures the number of somatic cells present in milk. A high SCC (typically above 200,000 SCC/ml) signals that the cow may be suffering from subclinical mastitis.

The sensor-based technologies like Labby can help monitor mastitis indicators such as SCC and the presence of blood in milk. Data collected from multiple milkings allows for better prediction of whether a cow’s subclinical mastitis is likely to become chronic. With the use of machine learning models and sensor data from farms across Europe and North America, studies have shown that it’s possible to predict chronic mastitis with high accuracy.

The treatment of chronic mastitis typically involves separating the affected cow from the herd, adjusting feed, and applying specific therapies like antibiotics or dry cow therapy. Early detection of chronic cases allows farmers to avoid more severe outcomes, such as culling.

Labby’s advanced milk testing technology can play a pivotal role in detecting chronic mastitis early. Our system offers real-time Somatic Cell Count (SCC) testing, providing farmers with instant data on milk quality. By continuously monitoring SCC levels, Labby helps farmers catch early warning signs of subclinical mastitis before it becomes chronic.

In addition to SCC, Labby’s inline milk analyzers track other key health indicators like milk yield and fat/protein content. The integration of AI-powered reports enables farmers to spot trends in milk quality, allowing them to act swiftly in preventing chronic mastitis. Our technology empowers farmers with the data they need to protect their herds and optimize milk production.

Labby’s solution supports early intervention, providing a reliable and accurate tool to manage mastitis, improve animal welfare, and enhance productivity on the farm.

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Work Citied:

Bonestroo, J., van der Voort, M., Hogeveen, H., Emanuelson, U., Klaas, I. C., & Fall, N. (2022). Forecasting chronic mastitis using automatic milking system sensor data and gradient-boosting classifiers. Computers and Electronics in Agriculture, 200, 107266. https://www.sciencedirect.com/science/article/pii/S0168169922003192