Climate Risks and Data Analytics for Grass Tetany Prevention

Climate change is having a significant impact on the agricultural industry, and one of the most pressing issues is the risk of grass tetany. Grass tetany is a metabolic disorder characterised by abnormally low levels of magnesium in the blood serum, and it can have devastating effects on cattle. High potassium levels in the soil, from either high-potassium soils or potassium fertilisers, reduce the amount of available magnesium in the plant and can lead to grass tetany. Unfortunately, the particular conditions causing mortality as a result of grass tetany are not tightly defined, leaving the occurrence and severity of the condition to be unpredictable.

The unpredictability of grass tetany makes it difficult for producers to prevent it, and the cost of prevention is similar to an annual insurance program in prediction of the high economic impact that will occur when conditions cause a major grass tetany event to occur. The signs of grass tetany include twitching ears or face, a ‘staggering’ type of gait, excitement, bellowing, aggressiveness, and muscular spasms. Without immediate treatment, these symptoms will usually worsen and lead to death.

In order to mitigate the risk of grass tetany, producers must be able to accurately predict the conditions that will lead to the occurrence of the disease. This is where data analytics comes in. By using data analytics, producers can analyse the data they have collected on soil type, topography, rainfall, geographical zone, age, breed, and associated magnesium nutrition to determine the conditions that are most likely to lead to grass tetany. This data can then be used to develop strategies to prevent the occurrence of the disease.

For example, producers can use data analytics to determine which areas of their land are most at risk of grass tetany and take steps to reduce the risk in those areas. This could include reducing the amount of potassium fertiliser used in those areas, or introducing a magnesium supplement such as Rumevite Magnesium Block. Data analytics can also be used to monitor the conditions in areas where grass tetany is likely to occur, so that producers can take action to prevent it before it becomes a problem.

By using data analytics to analyse the data they have collected on soil type, topography, rainfall, geographical zone, age, breed, and associated magnesium nutrition, producers can better understand the risks of grass tetany and take steps to prevent it. This will help to reduce the economic losses associated with the disease and ensure the health and safety of their cattle.