Advantages of Data Fusion: First Multivariate Curve Resolution Analysis of Fused Liquid Chromatographic Second-Order Data with Dual Diode Array-Fluorescent Detection

Abstract

For the first time, liquid chromatography-diode array detection (LC-DAD) and liquid-chromatography fluorescence detection (LC-FLD) second-order data, collected in a single chromatographic run, were fused and chemometrically processed for the quantitation of coeluting analytes. Two different experimental mixtures composed of fluorescent and nonfluorescent endocrine disruptors were analyzed. Adequate pretreatment of the matrices before their fusion was crucial to attain reliable results. Multivariate curve resolution-alternating least-squares (MCR-ALS) was applied to LC-DAD, LC-FLD, and fused LC-DAD-FLD data. Although different degrees of improvement are observed when comparing the fused matrix results in relation to those obtained using a single detector, clear benefits of data fusion are demonstrated through: (1) the obtained limits of detection in the ranges 2.1-24 ng mL-1 and 0.9-6.3 ng mL-1 for the two evaluated systems and (2) the low relative prediction errors, below 7% in all cases, indicating good recoveries and precision. The feasibility of fusing data and its advantages in the analysis of real samples was successfully assessed through the study of spiked tap, underground, and river water samples.