Weiss W P, Hansen S L
Department of Animal Sciences, Ohio Agricultural Research and Development Center, The Ohio State University, Wooster, OH 44691.
Department of Animal Science, Iowa State University, Ames, IA 50011.
J Dairy Sci. 2024 Dec;107(12):10099-10114. doi: 10.3168/jds.2024-25150. Epub 2024 Aug 31.
The mineral requirements or recommendations generated by various NASEM committees are used by many ration formulation programs. The current NASEM dairy requirement system uses the factorial approach (requirements for maintenance, lactation, gestation, and growth) for most minerals, but when data or equations were not available to estimate factorial requirements the committee used available data to estimate adequate intake values. The current beef NASEM uses the factorial method for Ca and P and recommendations for the other minerals. The factorial method works well for Ca and P because adequate data are available to estimate absorption coefficients (AC) and maintenance requirements. In addition, feeding Ca and P above requirements has few if any positive effects. For many other minerals the factorial method is problematic. Estimating both the maintenance requirement and AC can be extremely difficult and inaccuracies in those values have a major impact on accuracy of total dietary requirements. Some minerals have positive effects on health, production, and reproduction when fed above factorially determined requirements. For those minerals, response models rather than or in addition to requirement models are more appropriate. The AC is in the denominator of the factorial equation and converts absorbed requirements into dietary requirements. The AC for trace minerals is small, often <0.1, and small changes in a low AC can have substantial effects on dietary requirements. Although accurate AC are essential for the factorial method to work, woefully few data are available on the true absorption of trace minerals. Because of antagonism to absorption (e.g., negative effect of S on absorption of Cu, Mn, Se, and Zn) equations will be needed to estimate AC under different dietary conditions, but current data are inaccurate to generate equations. The systems currently used will almost always prevent clinical mineral deficiencies, but because of uncertainties, most nutritionists formulate diets to exceed and often far exceed established recommendations. This leads to increased costs, potential antagonism, and increased manure excretion of environmentally important minerals. More accurate systems for estimating mineral requirements will optimize animal performance and health while keeping costs in check and reducing environmental damage.
美国国家科学院、工程院和医学院（NASEM）各委员会制定的矿物质需求或建议被许多日粮配方程序所采用。当前的NASEM奶牛需求系统对大多数矿物质采用析因法（维持、泌乳、妊娠和生长的需求），但当缺乏数据或方程来估计析因需求时，委员会会使用现有数据来估计适宜摄入量值。当前的NASEM肉牛需求系统对钙和磷采用析因法，对其他矿物质则采用建议值。析因法对钙和磷效果良好，因为有足够的数据来估计吸收系数（AC）和维持需求。此外，饲喂高于需求的钙和磷几乎没有积极影响。对于许多其他矿物质，析因法存在问题。估计维持需求和AC都可能极其困难，这些值的不准确会对总日粮需求的准确性产生重大影响。一些矿物质在饲喂量高于析因确定的需求时，对健康、生产和繁殖有积极影响。对于这些矿物质，响应模型而非需求模型或两者结合更为合适。AC在析因方程的分母中，将吸收需求转换为日粮需求。微量矿物质的AC很小，通常<0.1，低AC的微小变化会对日粮需求产生重大影响。尽管准确的AC对于析因法的有效应用至关重要，但关于微量矿物质真实吸收的数据却少之又少。由于存在吸收拮抗作用（例如，硫对铜、锰、硒和锌吸收的负面影响），需要方程来估计不同日粮条件下的AC，但目前的数据不准确，无法生成方程。目前使用的系统几乎总能预防临床矿物质缺乏，但由于存在不确定性，大多数营养学家配制的日粮会超过甚至常常远远超过既定建议。这导致成本增加、潜在的拮抗作用以及对环境重要矿物质的粪便排泄增加。更准确的矿物质需求估计系统将优化动物性能和健康，同时控制成本并减少环境破坏。
