TY - JOUR
T1 - Second-order Data by Flow Injection Analysis with Spectrophotometric Diode-array Detection and Incorporated Gel-filtration Chromatographic Column
AU - Bechmann, Iben Ellegaard
PY - 1997
Y1 - 1997
N2 - A flow injection analysis (FIA) system furnished with a gel-filtration chromatographic column and with photodiode-array detection was used for the generation of second-order data. The system presented is a model system in which the analytes are blue dextran, potassium hexacyanoferrate(III) and heparin. It is shown that the rank of the involved sample data matrices corresponds to the number of chemical components present in the sample. The PARAFAC (parallel factor analysis) algorithm combined with multiple linear regression and the tri-PLS (tri-linear partial least-squares regression), which allows unknown substances to be present in the sample, are implemented for FIA systems and it is illustrated how these three-way algorithms can handle spectral interferents. The prediction ability of the two methods for pure two-component samples and also the predictions ability in the presence of unknown interferents are satisfactory. However, the predictions obtained by tri-PLS are slightly better than those obtained using PARAFAC regression algorithm. (C) 1997 Elsevier Science B.V.
AB - A flow injection analysis (FIA) system furnished with a gel-filtration chromatographic column and with photodiode-array detection was used for the generation of second-order data. The system presented is a model system in which the analytes are blue dextran, potassium hexacyanoferrate(III) and heparin. It is shown that the rank of the involved sample data matrices corresponds to the number of chemical components present in the sample. The PARAFAC (parallel factor analysis) algorithm combined with multiple linear regression and the tri-PLS (tri-linear partial least-squares regression), which allows unknown substances to be present in the sample, are implemented for FIA systems and it is illustrated how these three-way algorithms can handle spectral interferents. The prediction ability of the two methods for pure two-component samples and also the predictions ability in the presence of unknown interferents are satisfactory. However, the predictions obtained by tri-PLS are slightly better than those obtained using PARAFAC regression algorithm. (C) 1997 Elsevier Science B.V.
U2 - 10.1016/S0039-9140(96)02066-8
DO - 10.1016/S0039-9140(96)02066-8
M3 - Journal article
SN - 0039-9140
VL - 44
SP - 585
EP - 591
JO - Talanta
JF - Talanta
IS - 4
ER -