Development of a Predictive Model for Iron Levels in Bovine Muscle Tissue Using Hair as a Predictor

A study conducted in 2023 developed a noninvasive predictive model for iron levels in Hereford cattle muscle tissue using hair as a predictor. The model was constructed using the least squares method and identified magnesium, potassium, iron, aluminum, and chromium levels in hair as the most effective predictors. The model was validated using cross-validation and found to be accurate. This method allows for the assessment of iron levels in cattle muscle tissue throughout the period of productive use, enabling the diagnosis of animal elementosis and assessment of the iron level burden. The study involved 31 Hereford cattle. Future research plans to enhance prediction accuracy by incorporating new data and addressing model constraints.