Department of Animal Production and Health, University of Padua, 35020 Legnaro (PD), Italy.
Nutristar S.p.A., 42122 Reggio Emilia (RE), Italy.
J Dairy Sci. 2018 Nov;101(11):9967-9970. doi: 10.3168/jds.2018-14740. Epub 2018 Sep 13.
A large portion of the cow's ration is composed of forages that can vary greatly in mineral concentrations, which may affect animal performance and health. Current methods for mineral analysis require sample destruction either through wet or dry ashing and complex analytical techniques for individual minerals. Energy dispersive X-ray fluorescence (EDXRF) is a nondestructive, multi-mineral, spectroscopy technique, which makes mineral quantification simple, direct, and affordable. The study objective was to evaluate the prediction performance of EDXRF of Na, Mg, P, S, Cl, Ca, K, Mn, Fe, Cu, and Zn concentrations in forages. Twelve certified plant samples with a wide range in mineral concentrations were used to develop calibrations, and 35 forages (18 alfalfa hays, 10 grass hays, 7 corn silages) with measured mineral concentrations, which were collected over several years from 3 proficiency programs, were used as an independent validation set. All the samples were previously dried and finely ground and were prepared by compressing them into a round dense pellet, 40 mm in diameter, using a 40-ton pneumatic laboratory press. Samples were scanned using an EDXRF instrument enhanced for lighter minerals like Na and Mg. Samples were scanned at 20 keV and at 40 KeV associated with an Al filter, for a total analysis time of approximately 6 min. Calibrations were developed with Bruker SpectraEDX (Bruker, Hamburg, Germany) software and optimized to minimize the standard error of calibration. All of the minerals had acceptable calibration performance with coefficient of determination ranging from 0.93 (P) and 0.99 (Cl, Ca, and Mn) and coefficients of variation within 5 to 14%, which are similar to the coefficients of variation of the reference analysis. The coefficients of variation for Na was an exception, with a coefficients of variation of 29%. The validation set obtained similar statistical results as that observed in calibration. The root mean square error of prediction corrected for bias was similar to the standard error of calibration, indicating that it is possible to build a robust calibrations that performed well across different type of forages by using 12 reference samples with a sufficient range in mineral concentrations that were determined accurately. A bias correction was necessary to improve prediction accuracy only for K (-0.23% dry matter) and Ca (-0.16% dry matter). Energy dispersive X-ray fluorescence demonstrated the ability to be an accurate, direct, and simple technique for forage mineral analysis.
奶牛的大部分饲料由各种草料组成，其矿物质浓度可能有很大差异，这可能会影响动物的生产性能和健康。目前的矿物质分析方法需要通过湿法或干法灰化来破坏样品，并对个别矿物质进行复杂的分析技术。能量色散 X 射线荧光（EDXRF）是一种非破坏性的、多矿物质的光谱技术，它使矿物质定量分析变得简单、直接和经济实惠。本研究的目的是评估 EDXRF 对饲草中 Na、Mg、P、S、Cl、Ca、K、Mn、Fe、Cu 和 Zn 浓度的预测性能。使用 12 个具有广泛矿物质浓度范围的经过认证的植物样本来建立校准曲线，35 种饲草（18 种苜蓿干草、10 种禾本科干草、7 种玉米青贮）的矿物质浓度是通过几年间从 3 个熟练程度计划中收集的，用作独立验证集。所有样本均经过干燥和精细研磨，并使用 40 吨气动实验室压力机将其压缩成直径为 40 毫米的圆形致密颗粒来制备。使用增强了对 Na 和 Mg 等轻矿物质的 EDXRF 仪器对样品进行扫描。样品在 20keV 和 40keV 下进行扫描，并使用 Al 滤光片，总分析时间约为 6 分钟。校准曲线是使用 Bruker SpectraEDX（德国汉堡的 Bruker）软件开发的，并进行了优化，以最小化校准的标准误差。所有矿物质的校准性能都可以接受，决定系数范围从 0.93（P）到 0.99（Cl、Ca 和 Mn），变异系数在 5%到 14%之间，与参考分析的变异系数相似。Na 的变异系数是个例外，其变异系数为 29%。验证集获得了与校准观察到的类似的统计结果。经偏倚校正的预测均方根误差与校准标准误差相似，这表明可以通过使用 12 个具有足够矿物质浓度范围且准确测定的参考样本，建立稳健的校准曲线，从而对不同类型的饲草进行良好的分析。仅需要对 K（-0.23%干物质）和 Ca（-0.16%干物质）进行偏差校正，以提高预测精度。能量色散 X 射线荧光证明是一种准确、直接和简单的饲草矿物质分析技术。
