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Identification of Patterns of Trace Mineral Deficiencies in Dairy and Beef Cattle Herds in Spain
Candela Fernández-Villa1,2, Lucas Rigueira1,2, Marta López-Alonso3
1Department of Anatomy, Animal Production and Clinical Veterinary Sciences, Faculty of Veterinary, University of Santiago de Compostela, Campus Terra, 27002 Lugo, Spain.
Abstract:
Microminerals such as cobalt (Co), copper (Cu), iodine (I), iron (Fe), manganese (Mn), molybdenum (Mo), selenium (Se), and zinc (Zn) play key roles in cattle health. However, trace element imbalances are often underdiagnosed. This study retrospectively analyzed serum samples from 1273 cows across 117 herds in Spain, encompassing conventional dairy (n = 46), pasture-based dairy (n = 11), organic dairy (n = 25), and semi-extensive beef (n = 35) systems. Trace elements were determined by inductively coupled plasma mass spectrometry (ICP-MS). All herds were investigated for clinical or productive issues where mineral deficiencies were suspected. Significant differences were found in serum trace mineral concentrations between production systems. Adequacy rates were highest in conventional dairy herds receiving routine mineral supplementation, while deficiencies in Se, I, and Cu were frequently detected in pasture-based, organic, and beef herds. Zinc deficiencies were rare and typically involved complex, combined deficiencies. At the farm level, multielement deficiencies (≥3 elements) were detected in 39-45% of organic, pasture-based, and beef herds, but in only 5% of conventional dairy herds (p < 0.001). Principal component and cluster analyses produced consistent groupings of minerals according to dietary supplementation and soil-driven exposure. These findings highlight the increased vulnerability of low-input systems to complex micromineral imbalances and underline the importance of system-adapted mineral-monitoring and supplementation strategies in herd health management. However, as the study is based on diagnostic submissions rather than a randomized herd survey, the findings should be interpreted with caution due to potential selection bias.
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