Abstract A comparison of two multi-way methodologies is presented regarding the simultaneous quantitation of several analytes in complex samples. Both protocols are based on liquid chromatography with fluorescence detection, in the following modes: (1) collecting second-order/three-way data by fluorescence emission detection at a fixed excitation wavelength, and (2) measuring third-order/four-way data through excitation-emission fluorescence matrix detection. Ten quinolone antibiotics were simultaneously analyzed in edible animal tissues such as chicken liver and bovine liver and kidney. Multivariate curve resolution - alternating least-squares (MCR-ALS) provided excellent results with the second-order strategy, with average relative prediction errors in the range 4–12% for real samples, at analyte concentrations which are compatible with the corresponding maximum residue levels. For third-order data, however, the overall MCR-ALS analytical results were worse than for second-order data (relative errors were in the range 9–23%), and one analyte was not resolved. As an alternative, unfolded partial least-squares with residual bi- and trilinearization (U-PLS/RBL and U-PLS/RTL) were applied to both second- and third-order data, with relative errors of 7–18% and 5–27% respectively. The latter errors were significantly larger than those for MCR-ALS/second-order data, although the U-PLS/RTL model permitted the detection of all analytes when processing the third-order data. Relative advantages and disadvantages of the applied procedures are discussed on the basis of the analytical performances and the specific details of the instrumental setups.

中文翻译：

---

使用化学计量学工具研究使用两种不同荧光检测器获得的三路和四路液相色谱数据的质量，并将其应用于动物组织中喹诺酮类抗生素的测定

摘要 针对复杂样品中多种分析物的同时定量，介绍了两种多路方法的比较。两种方案均基于带荧光检测的液相色谱，采用以下模式：（1）通过固定激发波长下的荧光发射检测收集二阶/三路数据，以及（2）测量三阶/四路数据通过激发发射荧光矩阵检测。同时分析鸡肝、牛肝肾等食用动物组织中的10种喹诺酮类抗生素。多元曲线分辨率 - 交替最小二乘法 (MCR-ALS) 为二阶策略提供了出色的结果，真实样本的平均相对预测误差在 4-12% 范围内，在与相应的最大残留水平相容的分析物浓度下。然而，对于三阶数据，整体 MCR-ALS 分析结果比二阶数据差（相对误差在 9-23% 的范围内），并且一种分析物没有得到解决。作为替代方案，具有残差双线性和三线性化（U-PLS/RBL 和 U-PLS/RTL）的未折叠偏最小二乘法应用于二阶和三阶数据，相对误差为 7-18% 和 5分别为 –27%。后者的误差明显大于 MCR-ALS/二阶数据的误差，尽管 U-PLS/RTL 模型允许在处理三阶数据时检测所有分析物。