Application of bilinear least squares/residual bilinearization in bulk liquid membrane system for simultaneous multicomponent quantification of two synthetic dyes

作者：Khani Rouhollah; Ghasemi Jahan B^*; Shemirani Farzaneh; Rahmanian Reza

来源：Chemometrics and Intelligent Laboratory Systems, 2015, 144: 48-55.

DOI：10.1016/j.chemolab.2015.03.012

• Bulk liquid membrane
• Bilinear least squares/residual bilinearization
• Anionic azo dyes
• Second-order calibration
• Food samples
• Spectral deconvolution

For the first time, this research reports a new application of bulk liquid membrane (BLM) with second-order calibration based on the bilinear least squares/residual bilinearization (BLLS/RBL) algorithm, as a novel method for simultaneous removal and quantification of allura red (AR) and sunset yellow (SY) as model compounds in soft drinks and food samples. Due to severe spectral overlapping between the AR and SY and strong colinearities present in the data set, common second-order multivariate calibration methods, such as parallel factor analysis (PARAFAC) and multivariate curve resolution-alternating least-squares (MCR-ALS), could not be successfully applied to the presently studied samples. At first, the basic experimental parameters affecting the transport of the target dyes were investigated and optimized. Then under the optimum conditions, we have explored an alternative use of BLLS/RBL methodology, which can work adequately with strongly overlapping spectra and colinearities problems. Satisfactory results were obtained for analysis of target analytes. The proposed method was validated by comparison with a reference method based on high-performance liquid chromatography-ultra violet detection (HPLC-UV) and no significant differences were found between the reference values and the ones obtained with the proposed method. Such a chemometrics-based protocol may be a very promising tool for more analytical applications in real samples monitoring, due to its advantages of easy sample pretreatment, accuracy, sufficient spectral resolution and concentration prediction even in the presence of unknown interferences.

• 出版日期2015-5-15