Partial least-squares regression for multicomponent kinetic determinations in linear and non-linear systems

M. Blanco, J. Coello, H. Iturriaga, S. Maspoch, M. Redón

Research output: Contribution to journalArticleResearchpeer-review

33 Citations (Scopus)


The potential of partial least-squares regression (PLS) for resolution of binary mixtures by kinetic procedures is evaluated, both in a linear system as in the presence of a synergistic effect. Kinetic first order curves for the variation of the fluorescence intensity at a single wavelength were simulated and the effect of instrumental noise, experimental reproducibility, the analyte concentration ratio and the rate constant ratio was studied. Instrumental noise was modelled from measurements with a commercial spectrofluorimeter. To simulate experimental reproducibility, rate constant values were randomly chosen from normal distributions with the rate constant nominal values as mean and different standard deviations. Synergistic effects were modelled by adding a multiplicative term in the reaction rate of the product formation. Results show that PLS is an excellent calibration method to resolve mixtures by first-order kinetic procedures, without the need of any previous knowledge about rate constant values. It is also shown that it is possible to resolve mixtures in the presence of synergistic effects if the chemical system fulfil some conditions, mainly the rate constant ratio be higher than three. To show the potentiality of PLS on an experimental case it has been applied to the kinetic-spectrofluorimetric resolution of mixtures of hydrazine and hydroxylamine using as reactive the 2-hydroxybenzaldehyde azine. This chemical system is known to be subject of an important synergistic effect. © 1995.
Original languageEnglish
Pages (from-to)309-320
JournalAnalytica Chimica Acta
Issue number2-3
Publication statusPublished - 10 Mar 1995


  • Differential reaction rate
  • Hydrazine
  • Hydroxylamine
  • Kinetic methods
  • Partial least-squares regression
  • Synergistic effects


Dive into the research topics of 'Partial least-squares regression for multicomponent kinetic determinations in linear and non-linear systems'. Together they form a unique fingerprint.

Cite this