Abstract
The needle algorithm, based on a uniqueness test in target factor analysis, has been applied to several HPLC-DAD simulated data sets in both chromatographic and spectral directions. Information regarding the number of analytes in the system, the presence of minor compounds, the location of peak maxima and eventually some characteristics of the spectral shapes have been obtained. The location of peak maxima has also been used as a starting point to build a new kind of initial estimates to be input in iterative curve resolution methods, such as ALS (alternating least squares). The resolution results have been compared with the ones computed using initial estimations based on evolving factor analysis.
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