Magnesium in dairy cattle nutrition: A meta-analysis on magnesium absorption in dairy cattle and assessment of simple solubility tests to predict magnesium availability from supplemental sources

Supplemental Mg sources differ in bioavailability, and solubility is one of the determining factors. We explored whether and which in vitro solubility tests could reliably differentiate the quality of supplemental Mg sources. In experiment 1, we compared 3 chemical methods using an acetic acid solution (50 mL/L, termed vinegar test), a 1 M ammonium nitrate solution, and an artificial rumen buffer fluid without rumen microbiota. The Mg solubility results suggested the vinegar test was the best method due to its robustness, simplicity, and reproducibility. In experiment 2, we validated the reliability of the vinegar test using 4 MgO sources from experiment 1 and 12 new MgO sources plus a laboratory-grade MgO as a standard. Accordingly, we repeated the vinegar test with short (0.5 h) and long (3.0 h) incubation times on these sources and then conducted ruminal incubations in 24-h batch culture experiments. The repeated vinegar test resulted in similar results as in experiment 1. Linear regression across both experiments showed the soluble Mg content (g/kg) = 44.46 (+/- 2.55) x pH - 142.9 (+/- 14.9), root mean square error (RMSE) = 10.2, P slope <0.001, and concordance correlation coefficient (CCC) = 0.953. The predictable pH range was from 4 to 6. The equation cannot be applied to low-alkaline sources such as Mg sulfate, Mg acetate, or a group of MgO with exceptionally high alkaline properties showing a cluster of pH above 8.5. Solubility of the MgO sources in the vinegar test ranged from 5 to 35%, whereas the 24-h ruminal incubations led to more solubility (15-70%). Nevertheless, the differences among most MgO sources were parallel to the data from the in vitro rumen solubility. Next, we performed a meta-analysis of published studies (21 studies, 94 treatments) to assess the true Mg absorption in vivo and potential factors affecting Mg absorption in dairy cows. It appeared that on average dairy cows absorbed about 20% of the Mg intake (range 10-40%), regardless of their lactation status. We revealed a new strategy to predict Mg absorption relative to dietary K as follows: true Mg absorption (g/d) = 0.3395 (+/- 0.025, P < 0.001) x Mg intake (g/d) - 1.9273 (+/- 1.16, P = 0.11) when dietary K <= 20 g/kg DM, and 0.154 (+/- 1.06, P = 0.05) + 0.209 (+/- 0.026, P < 0.001) x Mg intake (g/d) when dietary K >20 g/kg DM (RMSE = 2.19). This strategy improved the accuracy of prediction as compared with the existing prediction (CCC = 0.922 vs. 0.845). Still, over- or underestimations inherent to individual studies were evident and might be related to unaccountable factors, especially the quality of supplemental Mg sources. In conclusion, the vinegar test is a useful tool to rank inorganic Mg sources with alkaline properties. Including in vitro solubility data in Mg nutrition research could help to refine the prediction of bioavailable Mg contents and increase precision in feed formulation. Supplemental Mg sources differ in bioavailability, and solubility is one of the determining factors. We explored whether and which in vitro solubility tests could reliably differentiate the quality of supplemental Mg sources. In experiment 1, we compared 3 chemical methods using an acetic acid solution (50 mL/L, termed vinegar test), a 1 M ammonium nitrate solution, and an artificial rumen buffer fluid without rumen microbiota. The Mg solubility results suggested the vinegar test was the best method due to its robustness, simplicity, and reproducibility. In experiment 2, we validated the reliability of the vinegar test using 4 MgO sources from experiment 1 and 12 new MgO sources plus a laboratory-grade MgO as a standard. Accordingly, we repeated the vinegar test with short (0.5 h) and long (3.0 h) incubation times on these sources and then conducted ruminal incubations in 24-h batch culture experiments. The repeated vinegar test resulted in similar results as in experiment 1. Linear regression across both experiments showed the soluble Mg content (g/kg) = 44.46 (±2.55) × pH - 142.9 (±14.9), root mean square error (RMSE) = 10.2, P slope <0.001, and concordance correlation coefficient (CCC) = 0.953. The predictable pH range was from 4 to 6. The equation cannot be applied to low-alkaline sources such as Mg sulfate, Mg acetate, or a group of MgO with exceptionally high alkaline properties showing a cluster of pH above 8.5. Solubility of the MgO sources in the vinegar test ranged from 5 to 35%, whereas the 24-h ruminal incubations led to more solubility (15-70%). Nevertheless, the differences among most MgO sources were parallel to the data from the in vitro rumen solubility. Next, we performed a meta-analysis of published studies (21 studies, 94 treatments) to assess the true Mg absorption in vivo and potential factors affecting Mg absorption in dairy cows. It appeared that on average dairy cows absorbed about 20% of the Mg intake (range 10-40%), regardless of their lactation status. We revealed a new strategy to predict Mg absorption relative to dietary K as follows: true Mg absorption (g/d) = 0.3395 (±0.025, P < 0.001) × Mg intake (g/d) - 1.9273 (±1.16, P = 0.11) when dietary K ≤20 g/kg DM, and 0.154 (±1.06, P = 0.05) + 0.209 (±0.026, P < 0.001) × Mg intake (g/d) when dietary K >20 g/kg DM (RMSE = 2.19). This strategy improved the accuracy of prediction as compared with the existing prediction (CCC = 0.922 vs. 0.845). Still, over- or underestimations inherent to individual studies were evident and might be related to unaccountable factors, especially the quality of supplemental Mg sources. In conclusion, the vinegar test is a useful tool to rank inorganic Mg sources with alkaline properties. Including in vitro solubility data in Mg nutrition research could help to refine the prediction of bioavailable Mg contents and increase precision in feed formulation.© 2024, The Authors. Published by Elsevier Inc. and Fass Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Veterinärmedizinische Universität Wien
Nutrition Sciences NV
Nutr Sci
Università degli Studi di Milano
University of Milan