Sequential injection analysis linked to multivariate curve resolution with alternating least squares
作者： A. Pasamontes , M.P. Callao
DOI: 10.1016/J.TRAC.2005.04.017
关键词: Multivariate curve resolution 、 Artificial intelligence 、 Chemometrics 、 Multivariate analysis 、 Combined technique 、 Analyse qualitative 、 Qualitative analysis 、 Sequential injection analysis 、 Pattern recognition 、 Computer science 、 Alternating least squares
摘要: Abstract This article discusses the potential of using sequential injection analysis (SIA) for generating second-order data. To treat these data, we used multivariate curve resolution with alternating least squares (MCR–ALS) as chemometric tool. combination can be both qualitative and quantitative analyses, since it provides concentration spectra profiles various species. By combining techniques (SIA–MCR–ALS), several analytes determined simultaneously in presence interferents without need to pretreat sample. We describe state art by reviewing literature 2004 necessary conditions applying tools this type also discuss advantages disadvantages combined technique examine future prospects SIA MCR–ALS.
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